Ministerial Weights and Government Formation: Estimation Using a Bargaining Model

This paper proposes a method to estimate relative ministerial weights in parliamentary democracies. Specifically, our method combines a bargaining model of government formation with maximum likelihood estimation. The data required for estimation are who formateurs are, what each party’s voting weight is, and what ministerial seats each party obtains. We use variation of the data and the structure of the bargaining model to recover ministerial weights and other parameters. Additionally, the method can measure the effects of voting weights and formateur advantage. We apply our proposed method to the case of Japan. Our results statistically show that political players value pork-related posts (such as the Minister of Construction) more than prestigious ones (such as the Minister of Foreign Affairs). We also find that there is a significant formateur advantage, while voting weights do not have a significant scale effectGovernment Formation, Bargaining

Scalable Machine Learning Methods for Massive Biomedical Data Analysis.

Modern data acquisition techniques have enabled biomedical researchers to collect and analyze datasets of substantial size and complexity. The massive size of these datasets allows us to comprehensively study the biological system of interest at an unprecedented level of detail, which may lead to the discovery of clinically relevant biomarkers. Nonetheless, the dimensionality of these datasets presents critical computational and statistical challenges, as traditional statistical methods break down when the number of predictors dominates the number of observations, a setting frequently encountered in biomedical data analysis. This difficulty is compounded by the fact that biological data tend to be noisy and often possess complex correlation patterns among the predictors. The central goal of this dissertation is to develop a computationally tractable machine learning framework that allows us to extract scientifically meaningful information from these massive and highly complex biomedical datasets. We motivate the scope of our study by considering two important problems with clinical relevance: (1) uncertainty analysis for biomedical image registration, and (2) psychiatric disease prediction based on functional connectomes, which are high dimensional correlation maps generated from resting state functional MRI.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111354/1/takanori_1.pd

Engineering of halohydrin hydrogen-halide-lyase (H-lyase) for efficient L-carnitine production

L-carnitine is a beta-hydroxy carboxylic acid known as a dietary supplement with the effect of fat-burning or anti-fatigue. Although several production processes of L-carnitine are proposed including fermentation, chiral resolution or asymmetric synthesis, there are disadvantages with each from the point of view of yield, side-reactions or productivity. We have engaged in technology development of efficient enzymatic production of various chemicals for years, represented with the world’s first industrialized bioprocess for acrylamide. Leveraging our specialty including proprietary nitrile-related enzymes and associated technologies, we attempted to develop a further efficient production process of L-carnitine (Figure 1). Please click Additional Files below to see the full abstract

Vascular Senescence in Chronic kidney Disease; Association of Aryl Hydrocarbon Receptor Activated by Indoxyl Sulfate

The impact of chronic kidney disease (CKD) on the occurrence of cardiovascular disease (CVD) is a major concern and this reciprocal relation is currently so called "cardio-renal syndrome". More detailed understanding in its mechanism may have a possibility to reduce the global burden of CVD. Of note, uremic toxins have been known to accumulate in the progression of CKD and play an important role for worsening renal function, on the other hand, recent studies suggest that they also negatively affect cardiovascular system. In this review, we delve into the role of aryl hydrocarbon receptor (AhR) in uremic toxicities, as highlighted in our latest work and give a new insight for the mechanism of cardio-renal syndrome

Accurate and molecular-size-tolerant NMR quantitation of diverse components in solution.

木質バイオマス中の各成分の物質量を正確に決定する手法の開発に成功 --木質バイオマスからの効率的なバイオエネルギー・製品原料の獲得にはずみ--. 京都大学プレスリリース. 2016-02-18.Determining the amount of each component of interest in a mixture is a fundamental first step in characterizing the nature of the solution and to develop possible means of utilization of its components. Similarly, determining the composition of units in complex polymers, or polymer mixtures, is crucial. Although NMR is recognized as one of the most powerful methods to achieve this and is widely used in many fields, variation in the molecular sizes or the relative mobilities of components skews quantitation due to the size-dependent decay of magnetization. Here, a method to accurately determine the amount of each component by NMR was developed. This method was validated using a solution that contains biomass-related components in which the molecular sizes greatly differ. The method is also tolerant of other factors that skew quantitation such as variation in the one-bond C-H coupling constant. The developed method is the first and only way to reliably overcome the skewed quantitation caused by several different factors to provide basic information on the correct amount of each component in a solution