The Pedophile Prophet? Breathing a Culturally Relative Point of View into a Controversial Cultural Debate

This work focuses on a controversial topic within women studies of the Islamic world, the very young marriage of Mohammad\u27s second wife Aisha. The work attempts to meet the issue on level ground and explain that while this may seem as a spark on conflict between non-Muslim cultures and the Islamic world this marriage was not altogether that uncommon for the time

Investigating the Magnitude and Range of the Urban Heat Island within Gettysburg, Pennsylvania

Cities experience UHIs due to the thermal properties (albedo, thermal emittance, radiative flux, and heat capacity) of human-made substances and urban geometry. This study investigated the existence of an urban heat island (UHI) in Gettysburg, Pennsylvania. The goal of this project was to assess whether a small-scale city like Gettysburg demonstrates an UHI effect and, if present, the extent and magnitude of the UHI. We hypothesized that (1) temperatures within the city are significantly higher than the surrounding area, (2) the magnitude of the UHI will diminish as distance from the city center increases, and (3) the UHI will not extend further than 0.5 miles outside the city center. Air temperatures were collected using digital thermometers over four weeks along two different transects that each extended one mile from the center square of Gettysburg. Our results show that Gettysburg, despite its small size, has an UHI. A linear regression model shows that there is a strong correlation between temperature and distance from the center square. The magnitude of the UHI lessens with increasing distance from the center of town. The first two hypotheses were supported while the hypothesis that the UHI will be localized was not. Statistically analyses show that the temperature change remains significant past 0.5 miles. The results of this study demonstrate that even a small-scale city like Gettysburg create a UHI

Can Specification Searches Be Useful for Hypothesis Generation?

Previous studies suggest that results from specification searches, as typically employed in structural equation modeling, should not be used to reach strong research conclusions due to their poor reliability. Analyses of computer generated data indicate that search results can be sufficiently reliable for exploratory purposes with properly designed and analyzed studies

The relative efficiency of time-to-progression and continuous measures of cognition in presymptomatic Alzheimer's disease.

IntroductionClinical trials on preclinical Alzheimer's disease are challenging because of the slow rate of disease progression. We use a simulation study to demonstrate that models of repeated cognitive assessments detect treatment effects more efficiently than models of time to progression.MethodsMultivariate continuous data are simulated from a Bayesian joint mixed-effects model fit to data from the Alzheimer's Disease Neuroimaging Initiative. Simulated progression events are algorithmically derived from the continuous assessments using a random forest model fit to the same data.ResultsWe find that power is approximately doubled with models of repeated continuous outcomes compared with the time-to-progression analysis. The simulations also demonstrate that a plausible informative missing data pattern can induce a bias that inflates treatment effects, yet 5% type I error is maintained.DiscussionGiven the relative inefficiency of time to progression, it should be avoided as a primary analysis approach in clinical trials of preclinical Alzheimer's disease

Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative.

IntroductionWe characterize long-term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative.MethodsWe apply a latent time joint mixed-effects model to 16 cognitive, functional, biomarker, and imaging outcomes in Alzheimer's Disease Neuroimaging Initiative. Markov chain Monte Carlo methods are used for estimation and inference.ResultsWe find good concordance between latent time and diagnosis. Change in amyloid positron emission tomography shows a moderate correlation with change in cerebrospinal fluid tau (ρ = 0.310) and phosphorylated tau (ρ = 0.294) and weaker correlation with amyloid-β 42 (ρ = 0.176). In comparison to amyloid positron emission tomography, change in volumetric magnetic resonance imaging summaries is more strongly correlated with cognitive measures (e.g., ρ = 0.731 for ventricles and Alzheimer's Disease Assessment Scale). The average disease trends are consistent with the amyloid cascade hypothesis.DiscussionThe latent time joint mixed-effects model can (1) uncover long-term disease trends; (2) estimate the sequence of pathological abnormalities; and (3) provide subject-specific prognostic estimates of the time until onset of symptoms

Predicting the course of Alzheimer's progression.

Alzheimer's disease is the most common neurodegenerative disease and is characterized by the accumulation of amyloid-beta peptides leading to the formation of plaques and tau protein tangles in brain. These neuropathological features precede cognitive impairment and Alzheimer's dementia by many years. To better understand and predict the course of disease from early-stage asymptomatic to late-stage dementia, it is critical to study the patterns of progression of multiple markers. In particular, we aim to predict the likely future course of progression for individuals given only a single observation of their markers. Improved individual-level prediction may lead to improved clinical care and clinical trials. We propose a two-stage approach to modeling and predicting measures of cognition, function, brain imaging, fluid biomarkers, and diagnosis of individuals using multiple domains simultaneously. In the first stage, joint (or multivariate) mixed-effects models are used to simultaneously model multiple markers over time. In the second stage, random forests are used to predict categorical diagnoses (cognitively normal, mild cognitive impairment, or dementia) from predictions of continuous markers based on the first-stage model. The combination of the two models allows one to leverage their key strengths in order to obtain improved accuracy. We characterize the predictive accuracy of this two-stage approach using data from the Alzheimer's Disease Neuroimaging Initiative. The two-stage approach using a single joint mixed-effects model for all continuous outcomes yields better diagnostic classification accuracy compared to using separate univariate mixed-effects models for each of the continuous outcomes. Overall prediction accuracy above 80% was achieved over a period of 2.5 years. The results further indicate that overall accuracy is improved when markers from multiple assessment domains, such as cognition, function, and brain imaging, are used in the prediction algorithm as compared to the use of markers from a single domain only

Canonical Generations and the British Left: The Narrative Construction of the Miners’ Strike 1984–85

‘Generations’ have been invoked to describe a variety of social and cultural relationships, and to understand the development of self-conscious group identity. Equally, the term can be an applied label and politically useful construct; generations can be retrospectively produced. Drawing on the concept of ‘canonical generations’ – those whose experiences come to epitomise an event of historic and symbolic importance – this article examines the narrative creation and functions of ‘generations’ as collective memory shapes and re-shapes the desire for social change. Building a case study of the canonical role of the miners’ strike of 1984–85 in the narrative history of the British left, it examines the selective appropriation and transmission of the past in the development of political consciousness. It foregrounds the autobiographical narratives of activists who, in examining and legitimising their own actions and prospects, (re)produce a ‘generation’ in order to create a relatable and useful historical understanding

Solving for closure errors due to polarization leakage in radio interferometry of unpolarized sources

Mechanical and electronic imperfections can result into polarization leakage in individual antennas of a radio interferometer. Such leakages manifest themselves as closure errors even in co-polar visibility measurements of unpolarized sources. This paper describes and tests a method for the study of polarization leakage for radio interferometric telescopes using {\it only} the nominally co-polar visibilities for unpolarized calibrators. Interpretation of the resulting closure phases on the Poincar\'e sphere is presented. Since unpolarized sources are used, the actual solutions for leakage parameters is subject to a degeneracy which is discussed. This however, does not affect the correction of closure errors in our scheme