Single molecule pull down of double strand RNA binding proteins

RNA molecules are transcribed as single stranded naturally, but with most of them forming in to structures composed of duplex regions, loop, bulge or mismatches. RNAs with double stranded regions, or known as double-strand RNAs (dsRNAs). The class of proteins responsible for processing dsRNAs is termed double-stranded RNA binding proteins (dsRBP). In recent decades, an increasing number of reports have shown the role of dsRBP-dsRNA interaction as core strategy in various cellular regulation pathways, including RNA interference, anti-viral immunity, mRNA transport and alternative splicing. However, little is known about the molecular mechanisms underlying the interaction between dsRBPs and dsRNA. Here we examined four human dsRBPs, ADAD2, TRBP, Staufen 1 and ADAR1 `which have various numbers of RNA binding domains expressed in mammalian cells. We applied single molecule pull-down (SiMPull) assay to investigate the intensity of various dsRNA-dsRBP interactions. Our results demonstrate that despite the highly conserved dsRNA binding domains, the dsRBPs exhibit diverse substrate specificy. While TRBP and ADAR1 have a preference for binding simple duplex RNA, ADAD2 and Staufen1 display higher affinity to imperfectly base-paired structured RNA substrates. We also demonstrate ATP-independent sliding activity of TRBP and Staufen probed by single molecule protein induced fluorescence enhancement (smPIFE), which demonstrates how single molecule approaches could be utilized to provide new insight into molecular mechanisms involved in protein-RNA interaction. Collectively, our study highlights the diverse nature of substrate specificity exhibited by dsRBPs that may be critical for their cellular function

Investigating Distributions of Epochs in Wildland Fire Lifetimes

The objective of my research project is to explore the relationship between variables related to wildland fire and to model distributions of epochs in wildland fire lifetimes. Several distributional families are considered for modeling these epochs, including the exponential distribution, gamma distribution, Weibull distribution and continuous phase-type distribution. I explain each of these distributions in short terms and illustrate how they are fit. Visual results of my exploratory data analysis are illustrated in two parts, data visualization and data modeling, along with my interpretation of each. Since this work is preliminary, I conclude the report with a discussion on what I have learned from the overall research experience

Virtual to Real Reinforcement Learning for Autonomous Driving

Reinforcement learning is considered as a promising direction for driving policy learning. However, training autonomous driving vehicle with reinforcement learning in real environment involves non-affordable trial-and-error. It is more desirable to first train in a virtual environment and then transfer to the real environment. In this paper, we propose a novel realistic translation network to make model trained in virtual environment be workable in real world. The proposed network can convert non-realistic virtual image input into a realistic one with similar scene structure. Given realistic frames as input, driving policy trained by reinforcement learning can nicely adapt to real world driving. Experiments show that our proposed virtual to real (VR) reinforcement learning (RL) works pretty well. To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data

Sparse Hanson-Wright Inequality for a Bilinear Form of Sub-Gaussian Variables

In this paper, we derive a new version of Hanson-Wright inequality for a sparse bilinear form of sub-Gaussian variables. Our results are generalization of previous deviation inequalities that consider either sparse quadratic forms or dense bilinear forms. We apply the new concentration inequality to testing the cross-covariance matrix when data are subject to missing. Using our results, we can find a threshold value of correlations that controls the family-wise error rate. Furthermore, we discuss the multiplicative measurement error case for the bilinear form with a boundedness condition

Empirical Likelihood Inference for Area under the ROC Curve using Ranked Set Samples

The area under a receiver operating characteristic curve (AUC) is a useful tool to assess the performance of continuous-scale diagnostic tests on binary classification. In this article, we propose an empirical likelihood (EL) method to construct confidence intervals for the AUC from data collected by ranked set sampling (RSS). The proposed EL-based method enables inferences without assumptions required in existing nonparametric methods and takes advantage of the sampling efficiency of RSS. We show that for both balanced and unbalanced RSS, the EL-based point estimate is the Mann-Whitney statistic, and confidence intervals can be obtained from a scaled chi-square distribution. Simulation studies and two case studies on diabetes and chronic kidney disease data suggest that using the proposed method and RSS enables more efficient inference on the AUC

AlGaN LED用p型窒化物半導体/n型酸化亜鉛ヘテロ接合の作製と評価

紫外（UV）領域(200nm∼350nm)の光源として、AlGaN LEDが注目を浴びている。AlGaN LEDはAl組成を増加することで発光の短波長化が可能であるが、高いAl組成のAlGaNは正孔ドーピングや、オーミック接触の形成などに課題であり、高い発光効率のAlGaN LEDは実現されていない。効率向上に向けた手段の一つとして、トンネル接合を用いる方法が検討されている。具体的には、ホール濃度の低いp型層に対して、高電子濃度のn型層をトンネル接合し、n型層からホールを注入する方である。その他、高濃度n型層をコンタクト層に用いることが可能になることで、オーミック接触の形成も容易となる利点がある。これまでトンネル接合層の材料として、バンドギャップの狭いInGaNや内部分極の大きいAlNなどの組成の異なる窒化物半導体が検討されている。我々は、従来の窒化物半導体トンネル接合とは異なり、酸化亜鉛(ZnO)をトンネル層とする新たなトンネル接合型AlGaN LEDに注目している。ZnOはGaNと同程度に広いバンドキャップがあり、高濃度のn型ドーピングが可能な材料である。低抵抗率で電極にも使える他、トンネル層として用いた場合、ZnOの電子濃度が高く、分極効果が強いため、バンドを大きく曲げられ、良好なトンネル接合を実現する可能性がある。これまで、ZnOトンネル層を用いたトンネル接合型LEDの紫外発光が観測されたが、ZnOの成膜条件はまだ検討の余地がある。本研究では、成膜温度を中心に、異なる成膜温度（室温と300℃）で有機金属気相成長法による成膜したp型窒化物半導体（p-GaNとp-AlGaN）の上にそれぞれn型ZnOを接合し、これら4種のヘテロ接合を電流-電圧測定（I-V測定）で評価した。結果として、300℃で成膜したn-ZnOとp-GaNのヘテロ接合だけ整流性が観察された。この結果はpn接合が形成されていることを示している。また、バンドギャップより高いエネルギーを持つ紫外線で照射しながらI-V特性を評価し、300℃成膜したn-ZnO/p-GaNのヘテロ接合だけpn接合の空亡層で光生成した電子空孔による生成電流の増加が逆バイアス下で観察できた。このことは前述のI-V特性と整合性のある結果である。また、300℃で成膜したn-ZnOとp-GaNのヘテロ接合では、-10Vから電流が急激に増加したことにより、トンネル効果が生じていることを示唆している。残りのサンプルではpn接合は形成していないために、トンネル接合も形成していないと考えられる。今後の課題について、p型窒化物半導体/n-ZnOヘテロ接合がトンネル効果を示すメカニズムを精査する。また、このトンネル接合をAlGaN LEDに組み込み、発光効率の向上を目指す。電気通信大学202