2,363 research outputs found
The moduli space of branched superminimal surfaces of a fixed degree, genus and conformal structure in the four-sphere
Bisphosphonate inhibits the expression of cyclin A2 at the transcriptional level in normal human oral keratinocytes.
Nitrogen-containing bisphosphonates (N-BPs) are the most widely used anti-resorptive agents in the treatment of bone-related diseases. N-BPs inhibit bone resorption by specifically targeting osteoclasts, bone-resorbing cells. However, soft tissue toxicity, such as oral or gastrointestinal (GI) ulcerations has frequently been reported in N-BP users, suggesting that N-BPs may also directly target cells other than osteoclasts. Previously, we reported that BPs inhibit proliferation without inducing the apoptosis of normal human oral keratinocytes (NHOKs). However, the molecular mechanisms through which N-BPs inhibit the proliferation of NHOKs are not yet fully understood. In this study, we performed gene expression profiling in N-BP-treated NHOKs and identified cyclin A2 as one of the most commonly downregulated genes. When the NHOKs were treated with N-BPs, we found that the level of cyclin A2 was suppressed in a dose- and time-dependent manner. In addition, the protein level of cyclin A2 was also significantly lower in oral epithelial cells in N-BP-treated oral mucosal tissue constructs. Cyclin A2 promoter reporter assay revealed that N-BPs inhibited the luciferase activity, indicating that the inhibition of cyclin A2 expression occurs at the transcriptional level. Furthermore, N-BPs did not alter the expression of cyclin A2 in normal human oral fibroblasts (NHOFs), suggesting that the effect of N-BPs on cyclin A2 expression may be cell-type specific. Thus, the findings of our study demonstrate that the inhibition of NHOK proliferation by N-BPs is mediated, at least in part, by the suppression of cyclin A2 expression at the transcriptional level, which may explain the underlying mechanisms of soft tissue toxicity by N-BPs
Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling
To capture the relationship between samples and labels, conditional
generative models often inherit spurious correlations from the training
dataset. This can result in label-conditional distributions that are imbalanced
with respect to another latent attribute. To mitigate this issue, which we call
spurious causality of conditional generation, we propose a general two-step
strategy. (a) Fairness Intervention (FI): emphasize the minority samples that
are hard to generate due to the spurious correlation in the training dataset.
(b) Corrective Sampling (CS): explicitly filter the generated samples and
ensure that they follow the desired latent attribute distribution. We have
designed the fairness intervention to work for various degrees of supervision
on the spurious attribute, including unsupervised, weakly-supervised, and
semi-supervised scenarios. Our experimental results demonstrate that FICS can
effectively resolve spurious causality of conditional generation across various
datasets.Comment: TMLR 202
S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions
Vision-language models, such as contrastive language-image pre-training
(CLIP), have demonstrated impressive results in natural image domains. However,
these models often struggle when applied to specialized domains like remote
sensing, and adapting to such domains is challenging due to the limited number
of image-text pairs available for training. To address this, we propose S-CLIP,
a semi-supervised learning method for training CLIP that utilizes additional
unpaired images. S-CLIP employs two pseudo-labeling strategies specifically
designed for contrastive learning and the language modality. The caption-level
pseudo-label is given by a combination of captions of paired images, obtained
by solving an optimal transport problem between unpaired and paired images. The
keyword-level pseudo-label is given by a keyword in the caption of the nearest
paired image, trained through partial label learning that assumes a candidate
set of labels for supervision instead of the exact one. By combining these
objectives, S-CLIP significantly enhances the training of CLIP using only a few
image-text pairs, as demonstrated in various specialist domains, including
remote sensing, fashion, scientific figures, and comics. For instance, S-CLIP
improves CLIP by 10% for zero-shot classification and 4% for image-text
retrieval on the remote sensing benchmark, matching the performance of
supervised CLIP while using three times fewer image-text pairs.Comment: NeurIPS 202
MASKER: Masked Keyword Regularization for Reliable Text Classification
Pre-trained language models have achieved state-of-the-art accuracies on
various text classification tasks, e.g., sentiment analysis, natural language
inference, and semantic textual similarity. However, the reliability of the
fine-tuned text classifiers is an often underlooked performance criterion. For
instance, one may desire a model that can detect out-of-distribution (OOD)
samples (drawn far from training distribution) or be robust against domain
shifts. We claim that one central obstacle to the reliability is the
over-reliance of the model on a limited number of keywords, instead of looking
at the whole context. In particular, we find that (a) OOD samples often contain
in-distribution keywords, while (b) cross-domain samples may not always contain
keywords; over-relying on the keywords can be problematic for both cases. In
light of this observation, we propose a simple yet effective fine-tuning
method, coined masked keyword regularization (MASKER), that facilitates
context-based prediction. MASKER regularizes the model to reconstruct the
keywords from the rest of the words and make low-confidence predictions without
enough context. When applied to various pre-trained language models (e.g.,
BERT, RoBERTa, and ALBERT), we demonstrate that MASKER improves OOD detection
and cross-domain generalization without degrading classification accuracy. Code
is available at https://github.com/alinlab/MASKER.Comment: AAAI 2021. First two authors contributed equall
Measuring surface dislocation nucleation in defect-scarce nanostructures
Linear defects in crystalline materials, known as dislocations, are central to the understanding of plastic deformation and mechanical strength, as well as control of performance in a variety of electronic and photonic materials. Despite a thorough understanding of dislocation structure and their interactions, measurements of the energetics and kinetics of dislocation nucleation have not been possible, as synthesizing and testing pristine crystals absent of defects has been prohibitively challenging. In this talk, experiments that directly measure the surface dislocation nucleation strengths in high qualityPd nanowhiskers subjected to uniaxial tension will be presented. We find that, whereas nucleation strengths are weakly size- and strain-rate-dependent, a strong temperature dependence is uncovered, corroborating predictions that nucleation is assisted by thermal fluctuations. We measure atomic-scale activation volumes, which explain both the ultrahigh athermal strength as well as the temperature-dependent scatter, evident in our experiments and well captured by a thermal activation model. Modeling of the probabilistic nature of surface dislocation nucleation suggests activation energies consistent with surface self-diffusion as the rate-limiting step needed to promote displacive activity. In this context, approaches allowing for modification of the surface chemistry and structure of metallic nanostructures to either inhibit or enhance surface diffusion will be discussed
The Prevalence of Hepatitis C Virus Infection in Korea: Pooled Analysis
This study evaluated the prevalence of hepatitis C virus (HCV) infections in Korea. Pooled estimates of the anti-HCV positivity were calculated using the data published in 15 reports on the general population and health check-up examinees. The overall pooled estimate of the prevalence of HCV among middle-aged adults (40 yr old and above) was 1.68% (95% confidence interval: 1.51-1.86%) during the year of 1990-2000 among the general population. Most of the published data indicated that the prevalence of anti-HCV increased with age. The anti-HCV positivity was significantly higher in females than in males. Because the risk of HCV exposure in blood recipients has decreased remarkably, the spread of HCV through means other than a transfusion must be prevented
Controlled manipulation of oxygen vacancies using nanoscale flexoelectricity
Oxygen vacancies, especially their distribution, are directly coupled to the
electromagnetic properties of oxides and related emergent functionalities that
have implication in device applications. Here using a homoepitaxial strontium
titanate thin film, we demonstrate a controlled manipulation of the oxygen
vacancy distribution using the mechanical force from a scanning probe
microscope tip. By combining Kelvin probe force microscopy imaging and
phase-field simulations, we show that oxygen vacancies can move under a
stress-gradient-induced depolarisation field. When tailored, this nanoscale
flexoelectric effect enables a controlled spatial modulation. In motion, the
scanning probe tip thereby deterministically reconfigures the spatial
distribution of vacancies. The ability to locally manipulate oxygen vacancies
on-demand provides a tool for the exploration of mesoscale quantum phenomena,
and engineering multifunctional oxide devices.Comment: 35 pages, Main text and the supplementary information combine
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