Blue-Emitting BODIPY Dyes

BODIPY which consists of a dipyrromethene complex with disubstituted boron has emerged as a superior fluorophore in various research fields. BODIPY typically shows high quantum yield with environment-insensitive fluorescence emission, sharp excitation and emission peaks, high water solubility and biocompatibility, and photostability. So far, various kinds of BODIPY derivatives have been developed and applied in not only academia such as chemistry, biochemistry, biomedical engineering, and medicine but also industries. BODIPY shows dramatic photophysical property changes upon substitution of functional groups or pi bond elongation on the main core structure. Among them, the blue-emitting BODIPY dyes with their synthesis and photophysical analysis were recently reported. In this chapter, the key information of the blue-emitting BODIPY dyes and their recent cutting-edge applications are summarized

Progression of Impending Central Retinal Vein Occlusion to the Ischemic Variant Following Intravitreal Bevacizumab

A 60-year-old woman who had experienced two episodes of amaurosis fugax in her right eye presented with vision loss. Two weeks earlier, at a private clinic, she was diagnosed with impending central retinal vein occlusion (CRVO) of the right eye and received an intravitreal injection of bevacizumab. Two weeks after this injection she was diagnosed with ischemic CRVO. At 11-weeks post-presentation, extremely ischemic features were observed with fluorescein angiographic findings of severe vascular attenuation and extensive retinal capillary obliteration. At 22-weeks post-presentation she was diagnosed with neovascular glaucoma; she experienced no visual improvement over the following several months

Robust Co-catalytic Performance of Nanodiamonds Loaded on WO3 for the Decomposition of Volatile Organic Compounds under Visible Light

Proper co-catalysts (usually noble metals), combined with semiconductor materials, are commonly needed to maximize the efficiency of photocatalysis. Search for cost-effective and practical alternatives for noble-metal co-catalysts is under intense investigation. In this work, nanodiamond (ND), which is a carbon nanomaterial with a unique sp(3)(core)/sp(2)(shell) structure, was combined with WO3 (as an alternative co-catalyst for Pt) and applied for the degradation of volatile organic compounds under visible light. NDs-loaded WO3 showed a highly enhanced photocatalytic activity for the degradation of acetaldehyde (similar to 17 times higher than bare WO3), which is more efficient than other well-known co-catalysts (Ag, Pd, Au, and CuO) loaded onto WO3 and comparable to Pt-loaded WO3. Various surface modifications of ND and photoelectochemical measurements revealed that the graphitic carbon shell (sp(2)) on the diamond core (spa) plays a crucial role in charge separation and the subsequent interfacial charge transfer. As a result, ND/WO3 showed much higher production of OH radicals than bare WO3 under visible light. Since ND has a highly transparent characteristic, the light shielding that is often problematic with other carbon-based co-catalysts was considerably lower with NDs-loaded WO3. As a result, the photocatalytic activity of NDs/WO3 was higher than that of WO3 loaded with other carbon-based co-catalysts (graphene oxide or reduced graphene oxide). A range of spectroscopic and photo(electro)chemical techniques were systematically employed to investigate the properties of NDs-loaded WO3. ND is proposed as a cost-effective and practical nanomaterial to replace expensive noble-metal co-catalysts.1124Ysciescopu

Feature Structure Distillation for BERT Transferring

Knowledge distillation is an approach to transfer information on representations from a teacher to a student by reducing their difference. A challenge of this approach is to reduce the flexibility of the student's representations inducing inaccurate learning of the teacher's knowledge. To resolve it in BERT transferring, we investigate distillation of structures of representations specified to three types: intra-feature, local inter-feature, global inter-feature structures. To transfer them, we introduce \textit{feature structure distillation} methods based on the Centered Kernel Alignment, which assigns a consistent value to similar features structures and reveals more informative relations. In particular, a memory-augmented transfer method with clustering is implemented for the global structures. In the experiments on the nine tasks for language understanding of the GLUE dataset, the proposed methods effectively transfer the three types of structures and improve performance compared to state-of-the-art distillation methods. Indeed, the code for the methods is available in https://github.com/maroo-sky/FSDComment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Labor Productivity In Emerging Markets: Evidence From Brazil, China, India, And Russia (BRIC)

Despite the great amount of attention to emerging markets, much still remains unknown about firm performance in emerging economies. To fill this gap, this study aims to investigate factors that influence labor productivity of firms in Brazil, China, India, and Russia (BRIC countries). This study focuses on features of business environments of emerging markets such as informality, corruption, foreign ownership, and external audit. Using a cross-national sample of 8,885 firms from the World Bank Enterprise Surveys dataset, we find that informality is negatively associated with labor productivity, while corruption and external audit are positively related to labor productivity. Implications will be discussed

Domain Adaptive Transfer Attack (DATA)-based Segmentation Networks for Building Extraction from Aerial Images

Semantic segmentation models based on convolutional neural networks (CNNs) have gained much attention in relation to remote sensing and have achieved remarkable performance for the extraction of buildings from high-resolution aerial images. However, the issue of limited generalization for unseen images remains. When there is a domain gap between the training and test datasets, CNN-based segmentation models trained by a training dataset fail to segment buildings for the test dataset. In this paper, we propose segmentation networks based on a domain adaptive transfer attack (DATA) scheme for building extraction from aerial images. The proposed system combines the domain transfer and adversarial attack concepts. Based on the DATA scheme, the distribution of the input images can be shifted to that of the target images while turning images into adversarial examples against a target network. Defending adversarial examples adapted to the target domain can overcome the performance degradation due to the domain gap and increase the robustness of the segmentation model. Cross-dataset experiments and the ablation study are conducted for the three different datasets: the Inria aerial image labeling dataset, the Massachusetts building dataset, and the WHU East Asia dataset. Compared to the performance of the segmentation network without the DATA scheme, the proposed method shows improvements in the overall IoU. Moreover, it is verified that the proposed method outperforms even when compared to feature adaptation (FA) and output space adaptation (OSA).Comment: 11pages, 12 figure

The Effects of Heat and Massage Application on Autonomic Nervous System

∙ The authors have no financial conflicts of interest. © Copyright: Yonsei University College of Medicine 2011 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Licens

Atomic Resolution Imaging of Rotated Bilayer Graphene Sheets Using a Low kV Aberration-corrected Transmission Electron Microscope

Modern aberration-corrected transmission electron microscope (TEM) with appropriate electron beam energy is able to achieve atomic resolution imaging of single and bilayer graphene sheets. Especially, atomic configuration of bilayer graphene with a rotation angle can be identified from the direct imaging and phase reconstructed imaging since atomic resolution Moir pattern can be obtained successfully at atomic scale using an aberration-corrected TEM. This study boosts a reliable stacking order analysis, which is required for synthesized or artificially prepared multilayer graphene, and lets graphene researchers utilize the information of atomic configuration of stacked graphene layers readily.ope