好アルカリ性Bacillus A-007株のK^+ : 促進ATPaseについて

1.好アルカリ性Bacillus A-007株の生育にとってK^+は必須であった.2.K^+-濃度を制限した培地(1.5mMK^+)で生育させた細胞の膜画分に, K^+により促進されるATPase活性が認められた.3.K^+促進ATPaseは, 動力学的特性及びウワバイン, NaN_3, PCMBに対する感受件において, 同菌株のH^+-ATPaseと明らかに異なっていた.1. K^+ was essential for the growth of an alkalophilic Bacillus A-007. 2. Membrane fraction, which was prepared from the cells grown in K^+ -limited medium (1.5mM K^+), showed K^+ -stimulated ATPase activity. 3. The K^+ -stimulated ATPase was clearly different from H^+ -ATPase on kinetical profile and ouabain-, NaN_3- and PCMB-sensvtivity

Essays on Labour Economics and Economic History

Chapter 1 investigates the relationship between family size and intergenerational inequality. I construct a fuzzy regression discontinuity design by the exogenous variation in fertility caused by the one-child policy. My findings present the one-child policy only reduces urban fertility. The empirical findings also suggest a negative correlation between family size and intergenerational inequality, but no causal effect exists. The role of siblings in sharing risks, son preference, more accessible student loans and relaxed budget constraints are plausible explanations for no causal effect.Chapter 2 introduces firm-specific returns to experience and tenure into a standard two-way fixed effects model and provide new evidence on heterogeneity of returns to experience and tenure across firms using administrative matched employer-employee data from Brazil from 1999 to 2014. We find that 1) assuming that employer-employee match quality is determined by firm-specific wage premia and firm-specific returns to experience and seniority, returns to tenure are not strongly related to firm wage premia (i.e. firm FEs), 2) returns to experience are strongly negatively correlated with firm wage premia, 3) the relationship between firm wage premium and return to experience is stronger for “blue collar” firms.Chapter 3 employs the demographic shocks in the late Qing dynasty as the instrumental variable to analyze the causal link between early industrialization and marriage patterns using a unique historical dataset. Our findings present a significantly negative relationship between early industrialization and fertility but no significant causal link between early industrialization and marriage age. While this indicates industrialization could reduce fertility, it may also suggest parents are more likely to use intra-marital birth control methods to limit fertility rather than delaying marriage age in traditional Chinese society. Finally, the opportunity cost of childcare for women and the quality-quantity trade-off are two main channels linking early industrialization to fewer children.</div

Table1_Effect of age and ICU types on mortality in invasive mechanically ventilated patients with sepsis receiving dexmedetomidine: a retrospective cohort study with propensity score matching.DOCX

Background: Dexmedetomidine is recommended for sedation in patients on mechanical ventilation. Whether age or ICU types could alter mortality in invasive mechanically ventilated patients with sepsis receiving dexmedetomidine is unknown.Methods: We included patients with sepsis receiving invasive mechanical ventilation from the Medical Information Mart for Intensive Care IV database. The exposure was intravenous dexmedetomidine administration during ICU stay. The primary outcome was 28-day mortality. The secondary outcomes were the length of ICU stay and liberation from invasive mechanical ventilation. Propensity score matching (PSM) and Cox proportional hazards regression were used to adjust for confounders and investigate any association. Restricted cubic spline models were used to evaluate potential nonlinear associations.Results: The pre-matched and propensity score-matched cohorts included 5,871 and 2016 patients, respectively. In the PSM cohorts, dexmedetomidine exposure was related to lower 28-day mortality (186 [17.7%] vs. 319 [30.3%]; p 65 years; HR, 0.65; 95% CI, 0.52–0.83; p Conclusion: Dexmedetomidine was associated with lower 28-day mortality in critically ill patients with sepsis receiving invasive mechanical ventilation, regardless of whether patients were younger or elderly, the first admission to the SICU or non-SICU.</p

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph

<div><p>In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks’ price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in <b>Finance and Insurance</b> industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.</p></div

The <i>free</i> and highest conditional probabilities of <i>Turnover</i> = 1 given (<i>HighNear</i>, <i>LowNear</i>).

<p>The <i>free</i> and highest conditional probabilities of <i>Turnover</i> = 1 given (<i>HighNear</i>, <i>LowNear</i>).</p

The <i>free</i> and highest conditional probabilities of <i>Illiquidity</i> = 1 given <i>Industry</i>.

<p>The <i>free</i> and highest conditional probabilities of <i>Illiquidity</i> = 1 given <i>Industry</i>.</p

Dynamical Bayesian factor graph with <i>r</i>_<i>th</i> = 6%: <i>G</i>^<i>r</i>6.

<p>The arrows indicate the time order of the member graphs. As a whole, the dynamical structure captures the mutual influential relationships as well as the dynamics of these relationships among all the factors.</p

The probabilities of <i>IsReversal</i> = 1 for year 2011.

<p>The probabilities of <i>IsReversal</i> = 1 for year 2011.</p

The <i>credibility</i> values of <i>G</i>^<i>r</i>6 and its member graphs.

<p>The <i>credibility</i> values of <i>G</i>^<i>r</i>6 and its member graphs.</p

The potential driving factors of return reversal.

<p>The potential driving factors of return reversal.</p