Nationalized International Criminal Law: Genocidal Intent, Command Responsibility, and an Overview of the South Korean Implementing Legislation of the ICC Statute

Article published in the Michigan State International Law Review

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

Dynamical mean-field theory of Hubbard-Holstein model at half-filling: Zero temperature metal-insulator and insulator-insulator transitions

We study the Hubbard-Holstein model, which includes both the electron-electron and electron-phonon interactions characterized by $U$ and $g$, respectively, employing the dynamical mean-field theory combined with Wilson's numerical renormalization group technique. A zero temperature phase diagram of metal-insulator and insulator-insulator transitions at half-filling is mapped out which exhibits the interplay between $U$ and $g$. As $U$ ($g$) is increased, a metal to Mott-Hubbard insulator (bipolaron insulator) transition occurs, and the two insulating states are distinct and can not be adiabatically connected. The nature of and transitions between the three states are discussed.Comment: 5 pages, 4 figures. Submitted to Physical Review Letter

Scene-Adaptive Video Frame Interpolation via Meta-Learning

Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, and occlusion. It is therefore difficult for a single network with fixed parameters to generalize across different videos. Ideally, one could have a different network for each scenario, but this is computationally infeasible for practical applications. In this work, we propose to adapt the model to each video by making use of additional information that is readily available at test time and yet has not been exploited in previous works. We first show the benefits of `test-time adaptation' through simple fine-tuning of a network, then we greatly improve its efficiency by incorporating meta-learning. We obtain significant performance gains with only a single gradient update without any additional parameters. Finally, we show that our meta-learning framework can be easily employed to any video frame interpolation network and can consistently improve its performance on multiple benchmark datasets.Comment: CVPR 202

Introduction on atomic layer deposition for high-k dielectric & high mobility oxide semiconductor thin film transistors

Amorphous oxide semiconductors have been widely studied for the potential use in flat panel displays such as active matrix liquid crystal display (LCD) and Organic light emitting diodes (OLEDs). Since reporting amorphous InGaZnO semiconductor thin film transistor (TFT) in 2003 & 2004, many multi-component oxide semiconductors have been intensively investigated and developed by reactive sputtering method. Very recently, the sputtered InGaZnO TFTs are already adopted in mass-production to fabricate AMOLED TVs. However, there remain several problems such as high mobility & stability issues. Also, virtual and argument reality (VR, AR) applications are rapidly emerging in display markets but the main issues are high resolution and low-voltage driving technologies. Please click Additional Files below to see the full abstract

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach

Constructing an organized dataset comprised of a large number of images and several captions for each image is a laborious task, which requires vast human effort. On the other hand, collecting a large number of images and sentences separately may be immensely easier. In this paper, we develop a novel data-efficient semi-supervised framework for training an image captioning model. We leverage massive unpaired image and caption data by learning to associate them. To this end, our proposed semi-supervised learning method assigns pseudo-labels to unpaired samples via Generative Adversarial Networks to learn the joint distribution of image and caption. To evaluate, we construct scarcely-paired COCO dataset, a modified version of MS COCO caption dataset. The empirical results show the effectiveness of our method compared to several strong baselines, especially when the amount of the paired samples are scarce.Comment: EMNLP 2019. Project page : https://sites.google.com/view/emnlp19scarcecaptio