A Visit to the Battlefield

This piece was transcribed and edited by Michael J. Birkner and Richard E. Winslow. With fighting concluded at Gettysburg on July 3, 1863, the enormous task of burying the dead, treating the wounded, and rehabilitating the town began in earnest. Although Gettysburg looked and smelled worse than it ever had or ever would again, thousands of people arrived on the battlefield in the days and weeks following General Robert E. Lee\u27s retreat. Some came to minister to the sick and reclaim the bodies of neighbors and loved ones; others scavenged souvenirs of the battle. Of the many visits to the battlefield in July 1863, few have been more affectingly described than the account of Joseph H. Foster of Portsmouth, New Hampshire. In the document reprinted below, of a speech Foster delivered at the Unitarian Sabbath School in Portsmouth on July 26, 1863, he describes a brief trip to Gettysburg from which he had just returned. His objective in going to Gettysburg was straightforward: he wanted to locate the body of his neighbor and friend Henry L. Richards and bring it back to New Hampshire for a proper interment. [excerpt

Democracy\u27s Shield: Voices of WWII

Based on a body of 700 oral history interviews archived at Gettysburg College, Democracy\u27s Shield relates the American military experience through the voices of those who served – from early awareness of the conflict in Europe and East Asia to the dropping of the atomic bomb, victory, occupation and homecoming. The text is illustrated with images of artifacts from the library\u27s Special Collections. Table of Contents ForewordIntroduction Portents of War Pearl Harbor Draft Status and Volunteering Exams, Induction, Training Heading to the Front Attitudes about the Enemy Race, Gender and the War Effort GI Joe Aboard Ship Up in the Air Medical Experience Leisure Activity Connections with Home European Theater D-Day Pacific Theater Experience of Battle POWs Death Camps Atomic Bomb Occupation Going Home Reflections The Interviewees Note on Sources Acknowledgments About the Editors The Dwight D. Eisenhower Society War in Focus Credits and Illustrations Donorshttps://cupola.gettysburg.edu/books/1180/thumbnail.jp

Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data

Analysis of viral strand sequence data and viral replication capacity could potentially lead to biological insights regarding the replication ability of HIV-1. Determining specific target codons on the viral strand will facilitate the manufacturing of target specific antiretrovirals. Various algorithmic and analysis techniques can be applied to this application. We propose using multiple testing to find codons which have significant univariate associations with replication capacity of the virus. We also propose using a data adaptive multiple regression algorithm to obtain multiple predictions of viral replication capacity based on an entire mutant/non-mutant sequence profile. The data set to which these techniques were applied consists of 317 patients, each with 282 sequenced protease and reverse transcriptase codons. Initially, the multiple testing procedure (Pollard and van der Laan, 2003) was applied to the individual specific viral sequence data. A single-step multiple testing procedure method was used to control the family wise error rate (FWER) at the five percent alpha level. Additional augmentation multiple testing procedures were applied to control the generalized family wise error (gFWER) or the tail probability of the proportion of false positives (TPPFP). Finally, the loss-based, cross-validated Deletion/Substitution/Addition regression algorithm (Sinisi and van der Laan, 2004) was applied to the dataset separately. This algorithm builds candidate estimators in the prediction of a univariate outcome by minimizing an empirical risk, and it uses cross-validation to select fine-tuning parameters such as: size of the regression model, maximum allowed order of interaction of terms in the regression model, and the dimension of the vector of covariates. This algorithm also is used to measure variable importance of the codons. Findings from these multiple analyses are consistent with biological findings and could possibly lead to further biological knowledge regarding HIV-1 viral data

Resampling Based Multiple Testing Procedure Controlling Tail Probability of the Proportion of False Positives

Simultaneously testing a collection of null hypotheses about a data generating distribution based on a sample of independent and identically distributed observations is a fundamental and important statistical problem involving many applications. In this article we propose a new resampling based multiple testing procedure asymptotically controlling the probability that the proportion of false positives among the set of rejections exceeds q at level alpha, where q and alpha are user supplied numbers. The procedure involves 1) specifying a conditional distribution for a guessed set of true null hypotheses, given the data, which asymptotically is degenerate at the true set of null hypotheses, and 2) specifying a generally valid null distribution for the vector of test-statistics proposed in Pollard and van der Laan (2003), and generalized in our subsequent articles Dudoit et al. (2004), van der Laan et al. (2004a) and van der Laan et al. (2004b). We establish the finite sample rational behind our proposal, and prove that this new multiple testing procedure asymptotically controls the wished tail probability for the proportion of false positives under general data generating distributions. In addition, we provide simulation studies establishing that this method is generally more powerful in finite samples than our previously proposed augmentation multiple testing procedure (van der Laan et al. (2004b)) and competing procedures from the literature. Finally, we illustrate our methodology with a data analysis

Application of a Multiple Testing Procedure Controlling the Proportion of False Positives to Protein and Bacterial Data

Simultaneously testing multiple hypotheses is important in high-dimensional biological studies. In these situations, one is often interested in controlling the Type-I error rate, such as the proportion of false positives to total rejections (TPPFP) at a specific level, alpha. This article will present an application of the E-Bayes/Bootstrap TPPFP procedure, presented in van der Laan et al. (2005), which controls the tail probability of the proportion of false positives (TPPFP), on two biological datasets. The two data applications include firstly, the application to a mass-spectrometry dataset of two leukemia subtypes, AML and ALL. The protein data measurements include intensity and mass-to-charge (m/z) ratios of bone marrow samples, with two replicates per sample. We apply techniques to preprocess the data; i.e. correct for baseline shift of the data as well as appropriately smooth the intensity profiles over the m/z values. After preprocessing the data we show an application of a TPPFP multiple testing techniques (van der Laan et al. (2005)) to test the difference between two groups of patients (AML/ALL) with respect to their intensity values over various m/z ratios, thus indicative of testing proteins of different sizes. Secondly, we will show an illustration of the E-Bayes/Bootstrap TPPFP procedure on a bacterial data set. In this application we are interested in finding bacteria whose mean difference over time points is differentially expressed between two U.S. cities. With both of these data applications, we also show comparisons to the van der Laan et al. (2004b) tppfp augmentation method, and discover the E-Bayes/Bootstrap TPPFP method is less conservative, therefore rejecting more tests at a specific alpha leve

Data Adaptive Pathway Testing

A majority of diseases are caused by a combination of factors, for example, composite genetic mutation profiles have been found in many cases to predict a deleterious outcome. There are several statistical techniques that have been used to analyze these types of biological data. This article implements a general strategy which uses data adaptive regression methods to build a specific pathway model, thus predicting a disease outcome by a combination of biological factors and assesses the significance of this model, or pathway, by using a permutation based null distribution. We also provide several simulation comparisons with other techniques. In addition, this method is applied in several different ways to an HIV-1 dataset in order to assess the potential biological pathways in the data

Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data

A new data filtering method for SELDI-TOF MS proteomic spectra data is described. We examined technical repeats (2 per subject) of intensity versus m/z (mass/charge) of bone marrow cell lysate for two groups of childhood leukemia patients: acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). As others have noted, the type of data processing as well as experimental variability can have a disproportionate impact on the list of interesting proteins (see Baggerly et al. (2004)). We propose a list of processing and multiple testing techniques to correct for 1) background drift; 2) filtering using smooth regression and cross-validated bandwidth selection; 3) peak finding; and 4) methods to correct for multiple testing (van der Laan et al. (2005)). The result is a list of proteins (indexed by m/z) where average expression is significantly different among disease (or treatment, etc.) groups. The procedures are intended to provide a sensible and statistically driven algorithm, which we argue provides a list of proteins that have a significant difference in expression. Given no sources of unmeasured bias (such as confounding of experimental conditions with disease status), proteins found to be statistically significant using this technique have a low probability of being false positives

Terahertz radiation driven chiral edge currents in graphene

We observe photocurrents induced in single layer graphene samples by illumination of the graphene edges with circularly polarized terahertz radiation at normal incidence. The photocurrent flows along the sample edges and forms a vortex. Its winding direction reverses by switching the light helicity from left- to right-handed. We demonstrate that the photocurrent stems from the sample edges, which reduce the spatial symmetry and result in an asymmetric scattering of carriers driven by the radiation electric field. The developed theory is in a good agreement with the experiment. We show that the edge photocurrents can be applied for determination of the conductivity type and the momentum scattering time of the charge carriers in the graphene edge vicinity.Comment: 4 pages, 4 figure, additional Supplemental Material (3 pages, 1 figure