Are All Successful Communities Alike? Characterizing and Predicting the Success of Online Communities

The proliferation of online communities has created exciting opportunities to study the mechanisms that explain group success. While a growing body of research investigates community success through a single measure -- typically, the number of members -- we argue that there are multiple ways of measuring success. Here, we present a systematic study to understand the relations between these success definitions and test how well they can be predicted based on community properties and behaviors from the earliest period of a community's lifetime. We identify four success measures that are desirable for most communities: (i) growth in the number of members; (ii) retention of members; (iii) long term survival of the community; and (iv) volume of activities within the community. Surprisingly, we find that our measures do not exhibit very high correlations, suggesting that they capture different types of success. Additionally, we find that different success measures are predicted by different attributes of online communities, suggesting that success can be achieved through different behaviors. Our work sheds light on the basic understanding of what success represents in online communities and what predicts it. Our results suggest that success is multi-faceted and cannot be measured nor predicted by a single measurement. This insight has practical implications for the creation of new online communities and the design of platforms that facilitate such communities.Comment: To appear at The Web Conference 201

Effect of breastfeeding on gastrointestinal infection in infants: A targeted maximum likelihood approach for clustered longitudinal data

The PROmotion of Breastfeeding Intervention Trial (PROBIT) cluster-randomized a program encouraging breastfeeding to new mothers in hospital centers. The original studies indicated that this intervention successfully increased duration of breastfeeding and lowered rates of gastrointestinal tract infections in newborns. Additional scientific and popular interest lies in determining the causal effect of longer breastfeeding on gastrointestinal infection. In this study, we estimate the expected infection count under various lengths of breastfeeding in order to estimate the effect of breastfeeding duration on infection. Due to the presence of baseline and time-dependent confounding, specialized "causal" estimation methods are required. We demonstrate the double-robust method of Targeted Maximum Likelihood Estimation (TMLE) in the context of this application and review some related methods and the adjustments required to account for clustering. We compare TMLE (implemented both parametrically and using a data-adaptive algorithm) to other causal methods for this example. In addition, we conduct a simulation study to determine (1) the effectiveness of controlling for clustering indicators when cluster-specific confounders are unmeasured and (2) the importance of using data-adaptive TMLE.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS727 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Evolution of the Insertion-Deletion Mutation Rate Across the Tree of Life

Citation: Sung, W., Ackerman, M. S., Dillon, M. M., Platt, T. G., Fuqua, C., Cooper, V. S., & Lynch, M. (2016). Evolution of the Insertion-Deletion Mutation Rate Across the Tree of Life. G3-Genes Genomes Genetics, 6(8), 2583-2591. doi:10.1534/g3.116.030890/-/DC1Mutations are the ultimate source of variation used for evolutionary adaptation, while also being predominantly deleterious and a source of genetic disorders. Understanding the rate of insertion-deletion mutations (indels) is essential to understanding evolutionary processes, especially in coding regions, where such mutations can disrupt production of essential proteins. Using direct estimates of indel rates from 14 phylogenetically diverse eukaryotic and bacterial species, along with measures of standing variation in such species, we obtain results that imply an inverse relationship of mutation rate and effective population size. These results, which corroborate earlier observations on the base-substitution mutation rate, appear most compatible with the hypothesis that natural selection reduces mutation rates per effective genome to the point at which the power of random genetic drift (approximated by the inverse of effective population size) becomes overwhelming. Given the substantial differences in DNA metabolism pathways that give rise to these two types of mutations, this consistency of results raises the possibility that refinement of other molecular and cellular traits may be inversely related to species-specific levels of random genetic drift

Anisotropy in the Cosmic Microwave Background at Degree Angular Scales: Python V Results

Observations of the microwave sky using the Python telescope in its fifth season of operation at the Amundsen-Scott South Pole Station in Antarctica are presented. The system consists of a 0.75 m off-axis telescope instrumented with a HEMT amplifier-based radiometer having continuum sensitivity from 37-45 GHz in two frequency bands. With a 0.91 deg x 1.02 deg beam the instrument fully sampled 598 deg^2 of sky, including fields measured during the previous four seasons of Python observations. Interpreting the observed fluctuations as anisotropy in the cosmic microwave background, we place constraints on the angular power spectrum of fluctuations in eight multipole bands up to l ~ 260. The observed spectrum is consistent with both the COBE experiment and previous Python results. There is no significant contamination from known foregrounds. The results show a discernible rise in the angular power spectrum from large (l ~ 40) to small (l ~ 200) angular scales. The shape of the observed power spectrum is not a simple linear rise but has a sharply increasing slope starting at l ~ 150.Comment: 5 page

Competition between Intramolecular and Intermolecular Interactions in an Amyloid-Forming Protein

Despite much progress in understanding the folding and the aggregation processes of proteins, the rules defining their interplay have yet to be fully defined. This problem is of particular importance since many diseases are initiated by protein unfolding and hence the propensity to aggregate competes with intramolecular collapse and other folding events. Here, we describe the roles of intramolecular and intermolecular interactions in defining the length of the lag time and the apparent rate of elongation of the 100-residue protein human β2-microglobulin at pH 2.5, commencing from an acid-denatured state that lacks persistent structure but contains significant non-random hydrophobic interactions. Using a combination of site-directed mutagenesis, quantitative kinetic analysis and computational methods, we show that only a single region of about 10 residues in length, determines the rate of fibril formation, despite the fact that other regions exhibit a significant intrinsic propensity for aggregation. We rationalise these results by analysing the effect of incorporating the conformational properties of acid-unfolded β2-microglobulin and its variants at pH 2.5 as measured by NMR spectroscopy into the Zyggregator aggregation prediction algorithm. These results demonstrate that residual structure in the precursor state modulates the intrinsic propensity of the polypeptide chain to aggregate and that the algorithm developed here allows the key regions for aggregation to be more clearly identified and the rates of their self-association to be predicted. Given the common propensity of unfolded chains to form non-random intramolecular interactions as monomers and to self-assemble subsequently into amyloid fibrils, the approach developed should find widespread utility for the prediction of regions important in amyloid formation and their rates of self-assembly. © 2009 Elsevier Ltd. All rights reserved

Method and apparatus for automatic control of a humanoid robot

A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes

Balancing employee needs, project requirements and organisational priorities in team deployment

The 'people and performance' model asserts that performance is a sum of employee ability, motivation and opportunity (AMO). Despite extensive evidence of this people-performance link within manufacturing and many service sectors, studies within the construction industry are limited. Thus, a recent research project set out to explore the team deployment strategies of a large construction company with the view of establishing how a balance could be achieved between organisational strategic priorities, operational project requirements and individual employee needs and preferences. The findings suggested that project priorities often took precedence over the delivery of the strategic intentions of the organisation in meeting employees' individual needs. This approach is not sustainable in the long term because of the negative implications that such a policy had in relation to employee stress and staff turnover. It is suggested that a resourcing structure that takes into account the multiple facets of AMO may provide a more effective approach for balancing organisational strategic priorities, operational project requirements and individual employee needs and preferences more appropriately in the future