Extremely broad radio recombination maser lines toward the high-velocity ionized jet in Cepheus A HW2

We present the first detection of the H40a, H34a and H31a radio recombination lines (RRLs) at millimeter wavelengths toward the high-velocity, ionized jet in the Cepheus A HW2 star forming region. From our single-dish and interferometric observations, we find that the measured RRLs show extremely broad asymmetric line profiles with zero-intensity linewidths of ~1100 kms-1. From the linewidths, we estimate a terminal velocity for the ionized gas in the jet of >500 kms-1, consistent with that obtained from the proper motions of the HW2 radio jet. The total integrated line-to-continuum flux ratios of the H40a, H34a and H31a lines are 43, 229 and 280 kms-1, clearly deviating from LTE predictions. These ratios are very similar to those observed for the RRL maser toward MWC349A, suggesting that the intensities of the RRLs toward HW2 are affected by maser emission. Our radiative transfer modeling of the RRLs shows that their asymmetric profiles could be explained by maser emission arising from a bi-conical radio jet with a semi-aperture angle of 18 deg, electron density distribution varying as r^(-2.11) and turbulent and expanding wind velocities of 60 and 500 kms-1.Comment: 6 pages, 2 figures, 3 tables, accepted for publication in ApJ

Expanded Very Large Array observations of the H66{\alpha} and He66{\alpha} recombination lines toward MWC 349A

We have used the greatly enhanced spectral capabilities of the Expanded Very Large Array to observe both the 22.3 GHz continuum emission and the H66{\alpha} recombination line toward the well-studied Galactic emission-line star MWC 349A. The continuum flux density is found to be 411 $\pm$ 41 mJy in good agreement with previous determinations. The H66{\alpha} line peak intensity is about 25 mJy, and the average line-to-continuum flux ratio is about 5%, as expected for local thermodynamic equilibrium conditions. This shows that the H66{\alpha} recombination line is not strongly masing as had previously been suggested, although a moderate maser contribution could be present. The He66{\alpha} recombination line is also detected in our observations; the relative strengths of the two recombination lines yield an ionized helium to ionized hydrogen abundance ratio y+ = 0.12 $\pm$ 0.02. The ionized helium appears to share the kinematics of the thermally excited ionized hydrogen gas, so the two species are likely to be well mixed. The electron temperature of the ionized gas in MWC 349A deduced from our observations is 6,300 $\pm$ 600 K.Comment: Accepted for publication in ApJ

Fairness in Flowers: Campaign Toolkit

This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.ILRF_Flowers_ToolKit_2008.pdf: 511 downloads, before Oct. 1, 2020

Influence networks

Some behaviors, ideas or technologies spread and become persistent in society, whereas others vanish. This paper analyzes the role of social influence in determining such distinct collective outcomes. Agents are assumed to acquire information from others through a certain sampling process that generates an influence network, and they use simple rules to decide whether to adopt or not depending on the observed sample. We characterize, as a function of the primitives of the model, the diffusion threshold (i.e., the spreading rate above which the adoption of the new behavior becomes persistent in the population) and the endemic state (i.e., the fraction of adopters in the stationary state of the dynamics). We find that the new behavior will easily spread in the population if there is a high correlation between how influential (visible) and how easily influenced an agent is, which is determined by the sampling process and the adoption rule. We also analyze how the density and variance of the out-degree distribution affect the diffusion threshold and the endemic state.social influence, networks, diffusion threshold, endemic state

On the concept of depth for functional data

The statistical analysis of functional data is a growing need in many research areas. We propose a new depth notion for functional observations based on the graphic representation of the curves. Given a collection of functions, it allows to establish the centrality of a function and provides a natural center-outward ordering of the sample curves. Robust statistics such as the median function or a trimmed mean function can be defined from this depth definition. Its finite-dimensional version provides a new depth for multivariate data that is computationally very fast and turns out to be convenient to study high-dimensional observations. The natural properties are established for the new depth and the uniform consistency of the sample depth is proved. Simulation results show that the trimmed mean presents a better behavior than the mean for contaminated models. Several real data sets are considered to illustrate this new concept of depth. Finally, we use this new depth to generalize to functions the Wilcoxon rank sum test. It allows to decide whether two groups of curves come from the same population. This functional rank test is applied to girls and boys growth curves concluding that they present different growth patterns

Moving Stronger: Needs of the Criminal Justice Reform Movement

Moving Stronger: Needs of the Criminal Justice Reform Movement presents the struggles, victories, strengths and challenges of grassroots groups organizing for criminal justice reform across the country. Drawn from a national survey and in-depth interviews with members and clients of these groups, the report offers the insights and analyses of long-time organizers and emerging leaders, in their own words.The project aimed to assess the state of grassroots organizing around a broad spectrum of criminal justice reform issues, with the goal of bringing critical information to funders and grassroots groups about the diverse needs, organizing approaches and campaigns of groups around the country. The report will be distributed and used among grassroots groups to support networking, information and resource sharing, collaborative work and coalition building

Influence Networks

Some behaviors, ideas or technologies spread and become persistent in society, whereas others vanish. This paper analyzes the role of social influence in determining such distinct collective outcomes. Agents are assumed to acquire information from others through a certain sampling process that generates an influence network and use simple rules to decide whether to adopt or not depending on the observed sample. The diffusion threshold (i.e., the spreading rate above which the behavior becomes persistent in the population) and the endemic state (i.e., the fraction of adopters in the stationary state of the dynamics) are characterized as a function of the primitives of the model. The results highlight the importance of the correlation between visibility and connectivity (or degree) for diffusion purposes.social influence, networks, diffusion threshold, endemic state.

Depth-based inference for functional data

We propose robust inference tools for functional data based on the notion of depth for curves. We extend the ideas of trimmed regions, contours and central regions to functions and study their structural properties and asymptotic behavior. Next, we introduce a scale curve to describe dispersion in a sample of functions. The computational burden of these techniques is not heavy and so they are also adequate to analyze high-dimensional data. All these inferential methods are applied to different real data sets

Depth-based classification for functional data

Classification is an important task when data are curves. Recently, the notion of statistical depth has been extended to deal with functional observations. In this paper, we propose robust procedures based on the concept of depth to classify curves. These techniques are applied to a real data example. An extensive simulation study with contaminated models illustrates the good robustness properties of these depth-based classification methods

The Spread of Free-Riding Behavior in a Social Network

We study a model where agents, located in a social network, decide whether to exert effort or not in experimenting with a new technology (or acquiring a new skill, innovating, etc.). We assume that agents have strong incentives to free ride on their neighbors' effort decisions. In the static version of the model efforts are chosen simultaneously. In equilibrium, agents exerting effort are never connected with each other and all other agents are connected with at least one agent exerting effort. We propose a mean-field dynamics in which agents choose in each period the best response to the last period's decisions of their neighbors. We characterize the equilibrium of such a dynamics and show how the pattern of free riders in the network depends on properties of the connectivity distribution.free ride, independent set, local public good, mean field, social network.