Vitamin K, SXR, and GGCX

Vitamin K was discovered in 1929 as a substance essential for blood coagulation and had been clinically utilized before the precise mechanism of action became aware in 1970s. The function as a cofactor of γ-glutamyl carboxylase (GGCX) was the mechanism firstly discovered with the identification of several substrate proteins including blood coagulation factors and osteocalcin. Recently, we and others have shown that vitamin K has other modes of function, such as ligand of nuclear receptor SXR (steroid and xenobiotic receptor) and its murine ortholog PXR (pregnane X receptor) and modulator of protein kinase A (PKA) activity. Besides its importance in blood coagulation, involvement of vitamin K has been shown in two major aging-related diseases, osteoporosis and osteoarthritis. Based on clinical and epidemiological studies, vitamin K is shown to have protective roles for both of them. Interestingly, clinical studies concerning single nucleotide polymorphisms (SNPs) of GGCX and γ-carboxylated status of osteocalcin suggested relationship between GGCX activity and bone-protective effect, while recent findings from basic research indicated that vitamin K functions mediated by SXR/PXR as well as GGCX are important in the bone metabolism. We also suggested that cartilage-protective effect is mediated by SXR/PXR signaling by animal experiments using Pxr knockout mice

Ultrabright narrow-band telecom two-photon source for long-distance quantum communication

We demonstrate an ultrabright narrow-band two-photon source at the 1.5 -\mu m telecom wavelength for long-distance quantum communication. By utilizing a bow-tie cavity, we obtain a cavity enhancement factor of $4.06\times 10^4$. Our measurement of the second-order correlation function $G^{(2)} ({\tau})$ reveals that the linewidth of $2.4$ MHz has been hitherto unachieved in the 1.5 -\mu m telecom band. This two-photon source is useful for obtaining a high absorption probability close to unity by quantum memories set inside quantum repeater nodes. Furthermore, to the best of our knowledge, the observed spectral brightness of $3.94\times 10^5$ pairs/(s$\cdot$MHz$\cdot$mW) is also the highest reported over all wavelengths.Comment: 11 pages, 4 figures, 2 table

Generative Colorization of Structured Mobile Web Pages

Color is a critical design factor for web pages, affecting important factors such as viewer emotions and the overall trust and satisfaction of a website. Effective coloring requires design knowledge and expertise, but if this process could be automated through data-driven modeling, efficient exploration and alternative workflows would be possible. However, this direction remains underexplored due to the lack of a formalization of the web page colorization problem, datasets, and evaluation protocols. In this work, we propose a new dataset consisting of e-commerce mobile web pages in a tractable format, which are created by simplifying the pages and extracting canonical color styles with a common web browser. The web page colorization problem is then formalized as a task of estimating plausible color styles for a given web page content with a given hierarchical structure of the elements. We present several Transformer-based methods that are adapted to this task by prepending structural message passing to capture hierarchical relationships between elements. Experimental results, including a quantitative evaluation designed for this task, demonstrate the advantages of our methods over statistical and image colorization methods. The code is available at https://github.com/CyberAgentAILab/webcolor.Comment: Accepted to WACV 202

LayoutDM: Discrete Diffusion Model for Controllable Layout Generation

Controllable layout generation aims at synthesizing plausible arrangement of element bounding boxes with optional constraints, such as type or position of a specific element. In this work, we try to solve a broad range of layout generation tasks in a single model that is based on discrete state-space diffusion models. Our model, named LayoutDM, naturally handles the structured layout data in the discrete representation and learns to progressively infer a noiseless layout from the initial input, where we model the layout corruption process by modality-wise discrete diffusion. For conditional generation, we propose to inject layout constraints in the form of masking or logit adjustment during inference. We show in the experiments that our LayoutDM successfully generates high-quality layouts and outperforms both task-specific and task-agnostic baselines on several layout tasks.Comment: To be published in CVPR2023, project page: https://cyberagentailab.github.io/layout-dm

A Catalog of GAL4 Drivers for Labeling and Manipulating Circadian Clock Neurons in Drosophila melanogaster

Daily rhythms of physiology, metabolism, and behavior are orchestrated by a central circadian clock. In mice, this clock is coordinated by the suprachiasmatic nucleus, which consists of 20,000 neurons, making it challenging to characterize individual neurons. In Drosophila, the clock is controlled by only 150 clock neurons that distribute across the fly's brain. Here, we describe a comprehensive set of genetic drivers to facilitate individual characterization of Drosophila clock neurons. We screened GAL4 lines that were obtained from Drosophila stock centers and identified 63 lines that exhibit expression in subsets of central clock neurons. Furthermore, we generated split-GAL4 lines that exhibit specific expression in subsets of clock neurons such as the 2 DN2 neurons and the 6 LPN neurons. Together with existing driver lines, these newly identified ones are versatile tools that will facilitate a better understanding of the Drosophila central circadian clock

Towards Flexible Multi-modal Document Models

Creative workflows for generating graphical documents involve complex inter-related tasks, such as aligning elements, choosing appropriate fonts, or employing aesthetically harmonious colors. In this work, we attempt at building a holistic model that can jointly solve many different design tasks. Our model, which we denote by FlexDM, treats vector graphic documents as a set of multi-modal elements, and learns to predict masked fields such as element type, position, styling attributes, image, or text, using a unified architecture. Through the use of explicit multi-task learning and in-domain pre-training, our model can better capture the multi-modal relationships among the different document fields. Experimental results corroborate that our single FlexDM is able to successfully solve a multitude of different design tasks, while achieving performance that is competitive with task-specific and costly baselines.Comment: To be published in CVPR2023 (highlight), project page: https://cyberagentailab.github.io/flex-d

GPU-accelerated integral imaging and full-parallax 3D display using stereo-plenoptic camera system

In this paper, we propose a novel approach to produce integral images ready to be displayed onto an integral- imaging monitor. Our main contribution is the use of commercial plenoptic camera, which is arranged in a stereo configuration. Our proposed set-up is able to record the radiance, spatial and angular, information simultaneously in each different stereo position. We illustrate our contribution by composing the point cloud from a pair of captured plenoptic images, and generate an integral image from the properly registered 3D information. We have exploited the graphics processing unit (GPU) acceleration in order to enhance the integral-image computation speed and efficiency. We present our approach with imaging experiments that demonstrate the improved quality of integral image. After the projection of such integral image onto the proposed monitor, 3D scenes are displayed with full-parallax