The Influence of Environment on the Chemical Evolution in Low-mass Galaxies

The mean alpha-to-iron abundance ratio ([$\alpha$/Fe]) of galaxies is sensitive to the chemical evolution processes at early time, and it is an indicator of star formation timescale ($\tau_{{\rm SF}}$). Although the physical reason remains ambiguous, there is a tight relation between [$\alpha$/Fe] and stellar velocity dispersion ($\sigma$) among massive early-type galaxies (ETGs). However, no work has shown convincing results as to how this relation behaves at low masses. We assemble 15 data sets from the literature and build a large sample that includes 192 nearby low-mass ($18<\sigma<80$~\kms) ETGs. We find that the [$\alpha$/Fe]-$\sigma$ relation generally holds for low-mass ETGs, except in extreme environments. Specifically, in normal galaxy cluster environments, the [$\alpha$/Fe]-$\sigma$ relation and its intrinsic scatter are, within uncertainties, similar for low-mass and high-mass ETGs. However, in the most massive relaxed galaxy cluster in our sample, the zero point of the relation is higher and the intrinsic scatter is significantly larger. By contrast, in galaxy groups the zero point of the relation offsets in the opposite direction, again with substantial intrinsic scatter. The elevated [$\alpha$/Fe] of low-mass ETGs in the densest environments suggests that their star formation was quenched earlier than in high-mass ETGs. For the low-mass ETGs in the lowest density environments, we suggest that their more extended star formation histories suppressed their average [$\alpha$/Fe]. The large scatter in [$\alpha$/Fe] may reflect stochasticity in the chemical evolution of low-mass galaxies.Comment: 7 pages, 3 figures, accepted by ApJ

A Tiger Compiler for the Cell Broadband Engine Architecture

The modern computing industry tends to build integrated circuits with multiple energy-efficient cores instead of ramping up the clock speed for each single processing unit. While each core may not run as fast as the single core model, such architecture allows more jobs to be handled in parallel and also provides better overall performance. Asymmetric Multiprocessing, also known as Heterogeneous Multiprocessing, involves multiple processors that differ architecturally from one another, especially where each processor has its own memory space. Under power limitations, this design could provide better performance than that attained through symmetric multiprocessing. However, the heterogeneous nature adds difficulty to programming. Each specific architecture requires its own program code. Programmers also need to explicitly transfer code and data between processors. This study describes the implementation of a compiler of the pedagogic Tiger language for the Cell Broadband Engine, an asymmetric multiprocessing platform jointly developed by Sony, Toshiba and IBM. The problem above is solved by introducing multiple backends for the Tiger language, along with a remote call stub (RCS) generator. Functions are compiled into different architectures, and calls across architectures are linked automatically through the stubs. RCS takes care of the execution context switch and hides details of the argument data/return value transfer. TigC simplifies the programming and building procedures. It also provides a high-level view of the whole program execution for future optimization because all of the source files are processed by a single compiler. As an example of this procedure, the possible optimization of data transfer during remote calls is investigated here

Panel Data Visualization in R (panelView) and Stata (panelview)

We develop an R package panelView and a Stata package panelview for panel data visualization. They are designed to assist causal analysis with panel data and have three main functionalities: (1) They plot the treatment status and missing values in a panel dataset; (2) they visualize the temporal dynamics of the main variables of interest; and (3) they depict the bivariate relationships between a treatment variable and an outcome variable either by unit or in aggregate. These tools can help researchers better understand their panel datasets before conducting statistical analysis

Selenium status and cardiovascular diseases: meta-analysis of prospective observational studies and randomized controlled trials

Background/Objectives: Selenium was thought to have a role in cardiovascular disease (CVD) owing to its antioxidant properties; however, evidence from observational studies and randomized controlled trials (RCTs) has been inconsistent and controversial. We thus conducted a meta-analysis to assess the discrepancies between observational and randomized trial evidence. Subjects/Methods: We searched MEDLINE and EMBASE for eligible prospective studies regarding the relationship between selenium and CVD up to 15 December 2013 and finally included 16 prospective observational studies and 16 RCTs. Random effects model was used to estimate the pooled relative risk (RR). Generalized least-squares trend test and restricted cubic spline model were performed to assess a linear and a nonlinear dose–response relationship. Results: Our meta-analysis of prospective studies showed a nonlinear relationship of CVD risk with blood selenium concentrations across a range of 30–165 μg/l and a significant benefit of CVD within a narrow selenium range of 55–145 μg/l. Our meta-analyses of RCTs showed that oral selenium supplements (median dose: 200 μg/day) for 2 weeks to 144 months significantly raised the blood selenium concentrations by 56.4 μg/l (95% confidence interval (CI): 40.9, 72.0 μg/l), whereas oral selenium supplements (median: 100 μg/day) for 6 to 114 months caused no effect on CVD (RR=0.91; 95% CI: 0.74, 1.10). Conclusions: Our meta-analysis in prospective studies demonstrated a significant inverse association between selenium status and CVD risk within a narrow selenium range and a null effect of selenium supplementation on CVD was observed in RCTs. These findings indicate the importance of considering selenium status, dose and safety in health assessment and future study design

What To Do (and Not to Do) with Causal Panel Analysis under Parallel Trends: Lessons from A Large Reanalysis Study

Two-way fixed effects (TWFE) models are ubiquitous in causal panel analysis in political science. However, recent methodological discussions challenge their validity in the presence of heterogeneous treatment effects (HTE) and violations of the parallel trends assumption (PTA). This burgeoning literature has introduced multiple estimators and diagnostics, leading to confusion among empirical researchers on two fronts: the reliability of existing results based on TWFE models and the current best practices. To address these concerns, we examined, replicated, and reanalyzed 37 articles from three leading political science journals that employed observational panel data with binary treatments. Using six newly introduced HTE-robust estimators, we find that although precision may be affected, the core conclusions derived from TWFE estimates largely remain unchanged. PTA violations and insufficient statistical power, however, continue to be significant obstacles to credible inferences. Based on these findings, we offer recommendations for improving practice in empirical research