The Effects of Habitat Fragmentation and Factors Influencing Nest Box Use on the Southern Flying Squirrel (Glaucomys volans) in Southern Illinois

I studied the effects of habitat :fragmentation on the southern flying squirrel (Glaucomys volans) in 30 forest fragments in southern Illinois. The fragments ranged in size from 6 ha to 5264 ha, and had varying degrees of isolation. I placed 10 nest boxes in each habitat fragment and checked them monthly. I captured southern flying squirrels in 24 of the 30 fragments, and found evidence of squirrels (i.e., nests and feeding stations) in 4 additional fragments. Thus, only 2 fragments did not show any evidence of squirrel use suggesting that the southern flying squirrel may not be particularly sensitive to the negative impacts of habitat fragmentation, in a primarily forested landscape like southern Illinois. However, the 2 fragments apparently lacking squirrels were small and isolated

Constant net-time headway as key mechanism behind pedestrian flow dynamics

We show that keeping a constant lower limit on the net-time headway is the key mechanism behind the dynamics of pedestrian streams. There is a large variety in flow and speed as functions of density for empirical data of pedestrian streams, obtained from studies in different countries. The net-time headway however, stays approximately constant over all these different data sets. By using this fact, we demonstrate how the underlying dynamics of pedestrian crowds, naturally follows from local interactions. This means that there is no need to come up with an arbitrary fit function (with arbitrary fit parameters) as has traditionally been done. Further, by using not only the average density values, but the variance as well, we show how the recently reported stop-and-go waves [Helbing et al., Physical Review E, 75, 046109] emerge when local density variations take values exceeding a certain maximum global (average) density, which makes pedestrians stop.Comment: 7 pages, 7 figure

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Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary measures to quantify bias with respect to protected attributes such as gender and age. We then present algorithms for computing fairness-aware re-ranking of results. For a given search or recommendation task, our algorithms seek to achieve a desired distribution of top ranked results with respect to one or more protected attributes. We show that such a framework can be tailored to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution. We evaluate the proposed algorithms via extensive simulations over different parameter choices, and study the effect of fairness-aware ranking on both bias and utility measures. We finally present the online A/B testing results from applying our framework towards representative ranking in LinkedIn Talent Search, and discuss the lessons learned in practice. Our approach resulted in tremendous improvement in the fairness metrics (nearly three fold increase in the number of search queries with representative results) without affecting the business metrics, which paved the way for deployment to 100% of LinkedIn Recruiter users worldwide. Ours is the first large-scale deployed framework for ensuring fairness in the hiring domain, with the potential positive impact for more than 630M LinkedIn members.Comment: This paper has been accepted for publication at ACM KDD 201

Monstrous Silhouette: The Development of the Female Monster in British Literature

In this thesis, I analyze the effects of social, political, and economic change and the historical effects of said change on the literary representations of female monsters as portrayed by male authors in medieval and Victorian literature. To contextualize the literature selected, each chapter involves extensive research which I argue influenced the presentation of the characters selected. Each chapter also includes extensive textual analysis to show direct examples in the text relating to the historical context, followed by a section tying the ideology of the thesis with the context provided in the historical and textual analysis sections. The purpose of this analysis is to demonstrate the repercussions of social change on the social standings of women and the manifestation of those changes within literature as a form of expression for the conflicting representations of the nature of femininity and the anxieties of the male writers in these moments of upheaval. At the beginning of this analysis, there was some expectation for a direct correlation between masculine anxieties and increases in female independence resulting in wholly negative portrayals of women, resulting on monstrous images; however, each character, despite their clearly monstrous traits, was nuanced in a way that was frequently empathetic, particularly when placed within the historical context of social change

Analyzing monthly extreme sea levels with a time-dependent GEV model

A statistical model to analyze different time scales of the variability of extreme high sea levels is presented. This model uses a time-dependent generalized extreme value (GEV) distribution to fit monthly maxima series and is applied to a large historical tidal gauge record (San Francisco, California). The model allows the identification and estimation of the effects of several time scales —such as seasonality, interdecadal variability, and secular trends— in the location, scale, and shape parameters of the probability distribution of extreme sea levels. The inclusion of seasonal effects explains a large amount of data variability, thereby allowing a more efficient estimation of the processes involved. Significant correlation with the Southern Oscillation index and the nodal cycle, as well as an increase of about 20% for the secular variability of the scale parameter have been detected for the particular dataset analyzed. Results show that the model is adequate for a complete analysis of seasonal-to-interannual sea level extremes providing time-dependent quantiles and confidence intervals

Cooling of Quark Stars in the Color Superconductive Phase: Effect of Photons from Glueball decay

The cooling history of a quark star in the color superconductive phase is investigated. Here we specifically focus on the 2-flavour color (2SC) phase where novel process of photon generation via glueball (GLB) decay have been already investigated (Ouyed & Sannino 2001). The picture we present here can in principle be generalized to quark stars entering a superconductive phase where similar photon generation mechanisms are at play. As much as 10^{45}-10^{47} erg of energy is provided by the GLB decay in the 2SC phase. The generated photons slowly diffuse out of the quark star keeping it hot and radiating as a black-body (with possibly a Wien spectrum in gamma-rays) for millions of years. We discuss hot radio-quiet isolated neutron stars in our picture (such as RX J185635-3754 and RX J0720.4-3125) and argue that their nearly blackbody spectra (with a few broad features) and their remarkably tiny hydrogen atmosphere are indications that these might be quark stars in the color superconductive phase where some sort of photon generation mechanism (reminiscent of the GLB decay) has taken place. Fits to observed data of cooling compact stars favor models with superconductive gaps of Delta_2SC = 15-35 MeV and densities rho_2SC=(2.5-3.0)rho_N (rho_N being the nuclear matter saturation density) for quark matter in the 2SC phase. If correct, our model combined with more observations of isolated compact stars could provide vital information to studies of quark matter and its exotic phases.Comment: 7 journal pages, 4 figures, accepted for publication in MNRAS (more discussions on photon cooling versus neutrino cooling before and after pairing of quarks