Who Benefits from Obtaining a GED? Evidence from High School and Beyond

This paper examines the value of the GED credential and the conventional high school diploma in explaining the earnings of 27-year-old males in the early 1990s. The data base is the High School & Beyond sophomore cohort. We replicate the basic findings of prior studies that implicitly assume the labor market value of the GED credential does not depend on the skills with which dropouts left school. We show that these average effects mask a more complicated pattern. Obtaining a GED is associated with higher earnings at age 27 for those male dropouts who had very weak cognitive skills as tenth graders, but not for those who had stronger cognitive skills as tenth graders.

Do the Cognitive Skills of School Dropouts Matter in the Labor Market?

Does the U.S. labor market reward cognitive skill differences among high school dropouts, the members of the labor force with the least educational attainments? This paper reports the results of an exploration of this question, using a new data set that provides information on the universe of dropouts who last attempted the GED exams in Florida and New York between 1984 and 1990. The design of the sample reduces variation in unmeasured variables such as motivation that are correlated with cognitive skills. We examine the labor market returns to basic cognitive skills as measured by GED test scores. We explore whether the returns differ by gender and race. The results indicate quite large earnings returns to cognitive skills for both male and female dropouts, and for white and non-white dropouts. The earnings payoff to skills increases with age.

Bump at the End of the Bridge: Review and Analysis of Rider Discomfort

Localized irregularities in the road profile are a well-known and persistent cause of rider discomfort when entering and exiting many bridges. This work addresses this so called “bump at the end of the bridge” problem first, through a review of relevant literature focusing on causes of the bump problem, mitigation techniques, retrofitting techniques, and special bump problems related to integral abutment bridges. Then, recognizing that approach slabs play a crucial role in the development of the bump, this problem is addressed through an investigation and comparison of approach slab designs and details utilized by various states. And, finally, the “bump at the end of the bridge” problem is addressed through dynamic analyses to ascertain the impact that various parameters of the bump geometry, road conditions, and vehicle speed have on rider discomfort. The results of the dynamic analyses indicate that the slope of the approach slab (i.e., the bump) and vehicle speed have the biggest impact on rider discomfort. Recommendations for future research are also noted

Differential neuroproteomic and systems biology analysis of spinal cord injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets

The openVA Toolkit for Verbal Autopsies

Verbal autopsy (VA) is a survey-based tool widely used to infer cause of death (COD) in regions without complete-coverage civil registration and vital statistics systems. In such settings, many deaths happen outside of medical facilities and are not officially documented by a medical professional. VA surveys, consisting of signs and symptoms reported by a person close to the decedent, are used to infer the cause of death for an individual, and to estimate and monitor the cause of death distribution in the population. Several classification algorithms have been developed and widely used to assign cause of death using VA data. However, The incompatibility between different idiosyncratic model implementations and required data structure makes it difficult to systematically apply and compare different methods. The openVA package provides the first standardized framework for analyzing VA data that is compatible with all openly available methods and data structure. It provides an open-sourced, R implementation of several most widely used VA methods. It supports different data input and output formats, and customizable information about the associations between causes and symptoms. The paper discusses the relevant algorithms, their implementations in R packages under the openVA suite, and demonstrates the pipeline of model fitting, summary, comparison, and visualization in the R environment

Supplementary materials for "Bayesian factor models for probabilistic cause of death assessment with verbal autopsies"

Supplementary materials for "Bayesian factor models for probabilistic cause of death assessment with verbal autopsies": p. 1-