1,032 research outputs found

    Complete and equivalent query rewriting using views.

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    Education Equity and Intergenerational Mobility: Quasi-experimental Evidence From Court-ordered School Finance Reforms

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    Starting from early seventies, court-ordered school finance reforms (SFRs) have fundamentally changed the landscape of primary and elementary education finance in the US. This paper employs SFRs as quasi-experiments to quantify the effects of education equity on intergenerational mobility within commuting zones. First, I use reduced form difference-in-difference analysis to show that 10 years of exposure to SFRs increases the average college attendance rate by about 5.2% for children with the lowest parent income. The effect of exposure to SFRs decreases with parent income and increases with the duration of exposure. Second, to directly model the causal pathways, I construct a measure for education inequity based on the association between school district education expenditure and median family income. Using exposure to SFRs as the instrumental variable, 2SLS analysis suggests that one standard deviation reduction in education inequality will cause the average college attendance rate to increase by 2.2% for children at the lower end of the parent income spectrum. Placing the magnitudes of these effects in context, I conclude that policies aimed at increasing education equity, such as SFRs, can substantially benefit poor children but they alone are not enough to overcome the high degree of existing inequalities

    Exploring the Connection Between Acid Exposure and Virulence in Listeria monocytogenes

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    Listeria monocytogenes is a gram-positive food-borne pathogen that is widely dispersed in the environment and can cause listeriosis with high fatality rates when consumed in contaminated food products. They are capable of growing over a wide range condition. Listeria is also able to tolerate adverse conditions which allows the bacterium to survive in unfavorable environments. The ubiquitous nature of L. monocytogenes makes it difficult to eliminate from food systems. One major problem in the food industry is the survival of L. monocytogenes under sublethal low pH-environment since organic acids are widely used as food decontaminants. Prior research has suggested that the use of organic acids in the food industry may unintentionally enhance pathogenicity of L. monocytogenes. This study examined the stress response of two strains of L. monocytogenes, N1-227 and R2-499, after lactic acid or acetic acid habituation. The first phase of the study investigated the impact of habituation to lactic acid and acetic acid on expression of transcription factors and genes related to acid resistance, bile resistance and virulence in L. monocytogenes strains N1-227 and R2-499 by qRT-PCR. Listeria cells were treated with a sublethal organic acid concentration and RNA samples were collected for transcriptome analysis after 20 minutes. Statistical analysis was performed to identify genes that increased or decreased in expression during organic acid habituation compared to cells without organic acid habituation. Results showed that organic acid habituation significantly induced expression of the acid and bile stress response genes in both strains, while expression of virulence genes was strain dependent. The second phase of this study investigated the in vivo virulence of habituated L. monocytogenes using the Galleria mellonella infection model. Virulence was determined by injecting the cells into G. mellonella larvae. After injection, the survival of G. mellonella and the L. monocytogenes growth kinetics in insects were evaluated and the median lethal time (LT50) was determined. Results showed that habituation in organic acid increased virulence of both strains as evidenced by decreased LT50 of G. mellonellalarvae. The growth of L. monocytogenes growth kinetics in insects between treatments for either strain showed no significant difference, indicating that the enhanced virulence observed in organic acid habituated cells is not due to enhanced survival or growth in the larvae. The third phase of this study investigated comprehensive transcriptional profile of L. monocytogenes strains N1-227 and R2-499 by RNA-seq in the presence or absence of organic acid. Results revealed detailed information about the mechanisms of L. monocytogenes responses to organic acid. As compared to L. monocytogenes grown in standard media, more differentially expressed genes (DEGs) were identified when cells were habituated with organic acid compared to cells habituated with inorganic acid. Induced expression of acid and bile stress response genes and virulence genes profiled using RT-qPCR technique in phase one was also validated by RNA-seq results. RNA-seq data were strongly correlated with the gene expression values obtained for those genes shared in the parallel qRT-PCR analysis (R2 = 0.74 for strain N1-227 and R2 = 0.79 for strain R2-499). Other DEGs included genes involved in cell motility, membrane transport and carbohydrate, amino acid metabolism and quorum sensing. Results from this project have increased the understanding of organic acid stress response in L. monocytogenes and may provide new leads for research and help to develop better strategies to prevent L. monocytogenes contamination in food

    Functional estimation in high-dimensional and infinite-dimensional models

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    Let P{\mathcal P} be a family of probability measures on a measurable space (S,A).(S,{\mathcal A}). Given a Banach space E,E, a functional f:E↦Rf:E\mapsto {\mathbb R} and a mapping θ:P↦E,\theta: {\mathcal P}\mapsto E, our goal is to estimate f(θ(P))f(\theta(P)) based on i.i.d. observations X1,…,Xn∼P,P∈P.X_1,\dots, X_n\sim P, P\in {\mathcal P}. In particular, if P={Pθ:θ∈Θ}{\mathcal P}=\{P_{\theta}: \theta\in \Theta\} is an identifiable statistical model with parameter set Θ⊂E,\Theta\subset E, one can consider the mapping θ(P)=θ\theta(P)=\theta for P∈P,P=Pθ,P\in {\mathcal P}, P=P_{\theta}, resulting in a problem of estimation of f(θ)f(\theta) based on i.i.d. observations X1,…,Xn∼Pθ,θ∈Θ.X_1,\dots, X_n\sim P_{\theta}, \theta\in \Theta. Given a smooth functional ff and estimators θ^n(X1,…,Xn),n≥1\hat \theta_n(X_1,\dots, X_n), n\geq 1 of θ(P),\theta(P), we use these estimators, the sample split and the Taylor expansion of f(θ(P))f(\theta(P)) of a proper order to construct estimators Tf(X1,…,Xn)T_f(X_1,\dots, X_n) of f(θ(P)).f(\theta(P)). For these estimators and for a functional ff of smoothness s≥1,s\geq 1, we prove upper bounds on the LpL_p-errors of estimator Tf(X1,…,Xn)T_f(X_1,\dots, X_n) under certain moment assumptions on the base estimators θ^n.\hat \theta_n. We study the performance of estimators Tf(X1,…,Xn)T_f(X_1,\dots, X_n) in several concrete problems, showing their minimax optimality and asymptotic efficiency. In particular, this includes functional estimation in high-dimensional models with many low dimensional components, functional estimation in high-dimensional exponential families and estimation of functionals of covariance operators in infinite-dimensional subgaussian models
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