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In this study, we present a new method for estimating input coefficient matrix with deep learning. We use the data of prefectures of Japan as the training data. However, the data is small and is likely to cause overfitting. Therefore, we attempt to avoid the over-fitting by creating new data of virtual areas aggregating multiple prefectures. The approach is based on the concept of data augmentation. As a result of predicting the input coefficient matrix of Yamaguchi prefecture and Gujo city, we showed that the method using deep learning can estimate the matrix with more stable accuracy than RAS method for these areas.

Germany's energy transition （Energiewende） is a paradigm shift into a low-carbon and nuclear-free economy. As part of the European Union's climate neutralization drive, aiming to reduce greenhouse gases to net-zero by the middle of the century. Generous financial support for wind and solar power has boosted renewable energy to produce more electricity than fossil fuels for the first time in 2020. Germany's energy transition is not a policy shift after the Fukushima nuclear disaster, but a long-term process of policy making in response to public opinion and technological trends. Germany's energy transition is still underway and needs to be extended beyond the power supply. However, it may already be pushing more thoroughly through pricing and volume regulations, such as the European Emissions Trading Scheme （EU-ETS） and changes to the carbon tax, which provides incentives for changes to low-carbon technologies. This paper analyses Germany's energy transition and climate policy. The purpose of this paper is to clarify the actual conditions and issues of the reduction effects of greenhouse gas emissions, which are the main policy issues of the energy conversion policy that has been developed mainly on renewable energy for these 20 years.

We performed this study to investigate whether serum cell-free DNA testing(liquid biopsy)of either methylated SEPT9 or methylated SST, which are possible biomarkers of HCC, in combination with AFP may improve clinical performance for the detection of HCC. Study subjects included 25 healthy controls, 15 patients with chronic liver disease without HCC, and 38 patients with HCC. Methylation level of serum cell-free SEPT9 and SST was measured by methylation-sensitive restriction enzymes followed by multiplex droplet digital polymerase chain reaction. According to receiver operating characteristic curve analysis to discriminate between non-HCC group(including control group and chronic liver disease without HCC group)and HCC group, area under the curve(AUC)was 0.73 by AFP and 0.73 by mSEPT9, whereas it was only 0.59 by mSST. Regarding combination tests, although negative predictive values were almost same between the AFP + mSEPT9 test and the AFP + mSST test(75.0% vs 72.2%),a positive predictive value of AFP + mSEPT9 test was higher than that of the AFP + mSST test(79.4% vs. 66.7%).In conclusions, methylated SEPT9 was a better companion marker of AFP for HCC screening than methylated SST.

This research aims to examine the relationship between political connections and bank performance during the COVID-19 pandemic in Indonesia, with data sample comprising banks listed on the Indonesia Stock Exchange （IDX）. The study employed a panel data linear regression and found an insignificant positive influence of political connections on banks' profitability. However, the result also indicates marginally lower profitability in politically connected banks compared to non-connected peers, and the event-study methodology reveals the tendency for affiliated banks to obtain substantial negative abnormal returns during the pandemic. Therefore, there is a negative effect of COVID-19 on stock performance of politically connected banks.

マーケット・タイミング理論が提唱されて以降，それを巡った実証研究が数多く行われている。しかしながら，実証研究のほとんどは欧米企業を対象として行われ，日本ではその理論がまだ注目されていない。本稿はマーケット・タイミング理論に基づき，株式発行におけるマーケット・タイミング行動に注目し，それに関する実証研究をサーベイする。主な結果は以下の2点である。まず日本企業ではマーケット・タイミング行動の実証的証拠が多いが，マーケット・タイミング行動と資本構成の関係についての実証研究はまだ少ない点である。また，マーケット・タイミング行動の資本構成への影響について，先行研究の結果が分かれており，そして異なる特性を持つ企業では影響効果も異なっている点である。このサーベイを通して，この研究分野の現状と動向を示し，さらなる発展に寄与することを目指す。

Retail investors, who are the majority traders in the Chinese stock market, cannot participate in off-line roadshows of IPO firms. Online roadshows are an important channel for them to learn about the situation of IPO firms. This study takes the IPO firms which are new-listed in Shenzhen Stock Exchange from 2010 to 2018 as the research subject, investigates the relationship between question-answers relevance in online roadshows and the first-day performance of IPO firms. According to the results, a high-level of question-answers relevance leads to a high first-day return and high liquidity. Furthermore, the additional analysis shows that the IPO firms with a high-level of question-answers relevance show stable long-term stock returns, on the contrary, the IPO firms with a low-level of question-answers relevance show the trends to decrease. Online roadshows could mitigate the information asymmetry between the investors and IPO firms, and play an important role in assessing firm values.