Public Practice: How Women Nursed Their Way Into Society

The advent of the American Civil War in 1861 abruptly halted the burgeoning Women’s Rights Movement of the mid-nineteenth century. The urgency of the Union war effort quickly overtook the fledgling movement. This did not eliminate women from the public sphere; rather, it pushed them into roles that would pave the way to a rekindled Women’s Rights Movement, the creation of the National Woman Suffrage Association in 1869, and eventually, women’s suffrage. This paper considers the roles Union women played in the American Civil War - from domestic work to nursing in field hospitals, to a brave few who dared to fight on the frontlines, disguised as men - and how they catapulted women out of private life into the public view. This paper argues that growing public acceptance facilitated the larger post-war Women’s Rights Movement and allowed it to flourish. This argument is supported primarily by the writings of women during this time, including the journals of Louisa May Alcott and the speeches of Elizabeth Cady Stanton and Susan B. Anthony. Materials referenced include original diary entries, United States Sanitary Commission minutes, and peer-reviewed historical research journals. This paper works to refute the popular belief that the American Women’s Rights Movement was entirely abandoned during the Civil War. It synthesizes both primary and secondary source information to establish a narrative of female activism that allowed the future Women’s Rights Movement to grow and thrive

The Use of Literature to Combat Bullying

Bullying is a pervasive phenomenon. This study examined what teachers think encourages bullying among young people, and what effects teachers believe reader response strategies would have on their students. The study found teachers implementing reader response strategies in discussing literature were able to influence behavior in students and reduce bullying

Renew House: A Place for Teenagers to Find Healing from Adverse/traumatic Events and Experiences

Abstract will go here

A Review and Evaluation of Techniques for Improved Feature Detection in Mass Spectrometry Data

Mass spectrometry (MS) is used in analysis of chemical samples to identify the molecules present and their quantities. This analytical technique has applications in many fields, from pharmacology to space exploration. Its impacts on medicine are particularly significant, since MS aids in the identification of molecules associated with disease; for instance, in proteomics, MS allows researchers to identify proteins that are associated with autoimmune disorders, cancers, and other conditions. Since the applications are so wide-ranging and the tool is ubiquitous across so many fields, it is critical that the analytical methods used to collect data are sound. Data analysis in MS is challenging. Experiments produce massive amounts of raw data that need to be processed algorithmically in order to generate interpretable results in a process known as feature detection, which is tasked with distinguishing signals associated with the chemical sample being analyzed from signals associated with background noise. These experimentally meaningful signals are also known as features or extracted ion chromatograms (XIC) and are the fundamental signal unit in mass spectrometry. There are many algorithms for analyzing raw mass spectrometry data tasked with distinguishing real isotopic signals from noise. While one or more of the available algorithms are typically chained together for end-to-end mass spectrometry analysis, analysis of each algorithm in isolation provides a specific measurement of the strengths and weaknesses of each algorithm without the confounding effects that can occur when multiple algorithmic tasks are chained together. Though qualitative opinions on extraction algorithm performance abound, quantitative performance has never been publicly ascertained. Quantitative evaluation has not occurred partly due to the lack of an available quantitative ground truth MS1 data set. Because XIC must be distinguished from noise, quality algorithms for this purpose are essential. Background noise is introduced through the mobile phase of the chemical matrix in which the sample of interest is introduced to the MS instrument, and as a result, MS data is full of signals representing low-abundance molecules (i.e. low-intensity signals). Noise generally presents in one of two ways: very low-intensity signals that comprise a majority of the data from an MS experiment, and noise features that are moderately low-intensity and can resemble signals from low-abundance molecules deriving from the actual sample of interest. Like XIC algorithms, noise reduction algorithms have yet to be quantitatively evaluated, to our knowledge; the performance of these algorithms is generally evaluated through consensus with other noise reduction algorithms. Using a recently published, manually-extracted XIC dataset as ground truth data, we evaluate the quality of popular XIC algorithms, including MaxQuant, MZMine2, and several methods from XCMS. XIC algorithms were applied to the manually extracted data using a grid search of possible parameters. Performance varied greatly between different parameter settings, though nearly all algorithms with parameter settings optimized with respect to the number of true positives recovered over 10,000 XIC. We also examine two popular algorithms for reducing background noise, the COmponent Detection Algorithm (CODA) and adaptive iteratively reweighted Penalized Least Squares (airPLS), and compare their performance to the results of feature detection alone using algorithms that achieved the best performance in a previous evaluation. Due to weaknesses inherent in the implementation of these algorithms, both noise reduction algorithms eliminate data identified by feature detection as significant

Mapping the allowed parameter space for decaying dark matter models

I consider constraints on a phenomenological decaying-dark-matter model, in which two weakly-interacting massive particle (WIMP) species have a small mass splitting, and in which the heavier particle decays to the lighter particle and a massless particle on cosmological timescales. The decay parameter space is parameterized by $v_k$, the speed of the lighter particle in the center-of-mass frame of the heavier particle prior to decay, and the decay time $\tau$. Since I consider the case in which dark-matter halos have formed before there has been significant decay, I focus on the effects of decay in already-formed halos. I show that the $v_k-\tau$ parameter space may be constrained by observed properties of dark-matter halos. I highlight which set of observations is likely to yield the cleanest constraints on $v_k-\tau$ parameter space, and calculate the constraints in those cases in which the effect of decay on the observables can be calculated without N-body simulations of decaying dark matter. I show that for $v_k \gtrsim 5\times 10^3$ km s$^{-1}$, the z=0 galaxy cluster mass function and halo mass-concentration relation constrain $\tau \gtrsim$ 40 Gyr, and that precise constraints on $\tau$ for smaller $v_k$ will require N-body simulations.Comment: 14 pages, 5 figures, references added, replaced to match version published in Phys. Rev.

The CMV early enhancer/chicken β actin (CAG) promoter can be used to drive transgene expression during the differentiation of murine embryonic stem cells into vascular progenitors

<p>Abstract</p> <p>Background</p> <p>Mouse embryonic stem cells cultured <it>in vitro </it>have the ability to differentiate into cells of the three germ layers as well as germ cells. The differentiation mimics early developmental events, including vasculogenesis and early angiogenesis and several differentiation systems are being used to identify factors that are important during the formation of the vascular system. Embryonic stem cells are difficult to transfect, while downregulation of promoter activity upon selection of stable transfectants has been reported, rendering the study of proteins by overexpression difficult.</p> <p>Results</p> <p>CCE mouse embryonic stem cells were differentiated on collagen type IV for 4–5 days, Flk1⁺mesodermal cells were sorted and replated either on collagen type IV in the presence of VEGFA to give rise to endothelial cells and smooth muscle cells or in collagen type I gels for the formation of vascular tubes. The activity of the CMV and β-actin promoters was downregulated during selection of stable transfectants and during differentiation to the Flk1 stage, while the CMV immediate enhancer/β-actin promoter in the pCAGIPuro-GFP vector led to 100% of stably transfected undifferentiated and differentiated cells expressing GFP. To further test this system we expressed syndecan-2 and -4 in these cells and demonstrated high levels of transgene expression in both undifferentiated cells and cells differentiated to the Flk1 stage.</p> <p>Conclusion</p> <p>Vectors containing the CAG promoter offer a valuable tool for the long term expression of transgenes during stem cell differentiation towards mesoderm, while the CMV and β-actin promoters lead to very poor transgene expression during this process.</p