Social Ties and User Generated Content: Evidence from an Online Social Network

We use variation in wind speeds at surfing locations in Switzerland as exogenous shifters of users' propensity to post content about their surfing activity onto an online social network. We exploit this variation to test whether users' social ties on the network have a causal effect on their content generation, and whether conent generation in turn has a similar causal effect on the users' abilty to form social ties. Economically significant causal effects of this kind can produce positive feedback that generate multiplier e¤ects to interventions that subsidize tie formation. We argue these interventions can therefore be the basis of a strategy by the rm to indirectly faciliate content generation on the site. The exogenous variation provided by wind speeds enable us to measure this feedback empirically and to assess the return on investment from such policies. We use a detailed dataset from an online social network that comprises the complete details of social tie formation and content generation on the site. The richness of he data enable us to control for several spurious confounds that have typically plagued empirical analysis of social interactions. Our results show evidence for significant positive feedback in user generated content. We discuss the implications of the estimates for the management of the content and the growth of the network

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Social Ties and User Generated Content: Evidence from an Online Social Network

We use variation in wind speeds at surfing locations in Switzerland as exogenous shifters of users' propensity to post content about their surfing activity onto an online social network. We exploit this variation to test whether users' social ties on the network have a causal effect on their content generation, and whether conent generation in turn has a similar causal effect on the users' abilty to form social ties. Economically significant causal effects of this kind can produce positive feedback that generate multiplier e¤ects to interventions that subsidize tie formation. We argue these interventions can therefore be the basis of a strategy by the rm to indirectly faciliate content generation on the site. The exogenous variation provided by wind speeds enable us to measure this feedback empirically and to assess the return on investment from such policies. We use a detailed dataset from an online social network that comprises the complete details of social tie formation and content generation on the site. The richness of he data enable us to control for several spurious confounds that have typically plagued empirical analysis of social interactions. Our results show evidence for significant positive feedback in user generated content. We discuss the implications of the estimates for the management of the content and the growth of the network

A critical comparison of integral projection and matrix projection models for demographic analysis

Structured demographic models are among the most common and useful tools in population biology. However, the introduction of integral projection models (IPMs) has caused a profound shift in the way many demographic models are conceptualized. Some researchers have argued that IPMs, by explicitly representing demographic processes as continuous functions of state variables such as size, are more statistically efficient, biologically realistic, and accurate than classic matrix projection models, calling into question the usefulness of the many studies based on matrix models. Here, we evaluate how IPMs and matrix models differ, as well as the extent to which these differences matter for estimation of key model outputs, including population growth rates, sensitivity patterns, and life spans. First, we detail the steps in constructing and using each type of model. Second, we present a review of published demographic models, concentrating on size-based studies, which shows significant overlap in the way IPMs and matrix models are constructed and analyzed. Third, to assess the impact of various modeling decisions on demographic predictions, we ran a series of simulations based on size-based demographic data sets for five biologically diverse species. We found little evidence that discrete vital rate estimation is less accurate than continuous functions across a wide range of sample sizes or size classes (equivalently bin numbers or mesh points). Most model outputs quickly converged with modest class numbers (≥10), regardless of most other modeling decisions. Another surprising result was that the most commonly used method to discretize growth rates for IPM analyses can introduce substantial error into model outputs. Finally, we show that empirical sample sizes generally matter more than modeling approach for the accuracy of demographic outputs. Based on these results, we provide specific recommendations to those constructing and evaluating structured population models. Both our literature review and simulations question the treatment of IPMs as a clearly distinct modeling approach or one that is inherently more accurate than classic matrix models. Importantly, this suggests that matrix models, representing the vast majority of past demographic analyses available for comparative and conservation work, continue to be useful and important sources of demographic information.Support for this work was provided by NSF awards 1146489, 1242558, 1242355, 1353781, 1340024, 1753980, and 1753954, 1144807, 0841423, and 1144083. Support also came from USDA NIFA Postdoctoral Fellowship (award no. 2019-67012-29726/project accession no. 1019364) for R. K. Shriver; the Swiss Polar Institute of Food and Agriculture for N. I. Chardon; the ICREA under the ICREA Academia Programme for C. Linares; and SERDP contract RC-2512 and USDA National Institute of Food and Agriculture, Hatch project 1016746 for A .M. Louthan. This is Contribution no. 21-177-J from the Kansas Agricultural Experiment Station

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Episodic Occurrence of Favourable Weather Constrains Recovery of a Cold Desert Shrubland After Fire

Key to the long-term resilience of dryland ecosystems is the recovery of foundation plant species following disturbance. In ecosystems with high interannual weather variability, understanding the influence of short-term environmental conditions on establishment of foundation species is essential for identifying vulnerable landscapes and developing restoration strategies. We asked how annual environmental conditions affect post-fire establishment of Artemisia tridentata, a shrub species that dominates landscapes across much of the western United States, and evaluated the influence of episodic establishment on population recovery. We collected A. tridentata stem samples from 33 plots in 12 prescribed fire sites that burned 8–11 years before sampling. We determined individual establishment years using annual growth rings. We measured seasonal soil environmental conditions at the study sites and asked if these conditions predicted annual establishment density. We then evaluated whether establishment patterns could be predicted by site-level climate or dominant subspecies. Finally, we tested the effect of the magnitude and frequency of post-fire establishment episodes on long-term population recovery. Annual post-fire recruitment of A. tridentata was driven by the episodic availability of spring soil moisture. Annual establishment was highest with wetter spring soils (relative influence [RI] = 19.4%) and later seasonal dry-down (RI = 11.8%) in the year of establishment. Establishment density declined greatly 4 to 5 years after fire (RI = 17.1%). Post-fire establishment patterns were poorly predicted by site-level mean climate (marginal R2 ≤ 0.18) and dominant subspecies (marginal R2 ≤ 0.43). Population recovery reflected the magnitude, but not the frequency, of early post-fire establishment pulses. Post-fire A. tridentata density and cover (measured 8–11 years after fire) were more strongly related to the magnitude of the largest establishment pulse than to establishment frequency, suggesting that population recovery may occur with a single favourable establishment year. Synthesis and applications. This study demonstrates the importance of episodic periods of favourable weather for long-term plant population recovery following disturbance. Management strategies that increase opportunities for seed availability to coincide with favourable weather conditions, such as retaining unburned patches or repeated seeding treatments, can improve restoration outcomes in high-priority areas

Sexual selection on male vocal fundamental frequency in humans and other anthropoids

D.A.P. was supported by a National Institutes of Mental Health T32 MH70343-05 fellowship. J.R.W. was supported by a National Science Foundation predoctoral fellowship.In many primates, including humans, the vocalizations of males and females differ dramatically, with male vocalizations and vocal anatomy often seeming to exaggerate apparent body size. These traits may be favoured by sexual selection because low-frequency male vocalizations intimidate rivals and/or attract females, but this hypothesis has not been systematically tested across primates, nor is it clear why competitors and potential mates should attend to vocalization frequencies. Here we show across anthropoids that sexual dimorphism in fundamental frequency (F0) increased during evolutionary transitions towards polygyny, and decreased during transitions towards monogamy. Surprisingly, humans exhibit greater F0 sexual dimorphism than any other ape. We also show that low-F0 vocalizations predict perceptions of men’s dominance and attractiveness, and predict hormone profiles (low cortisol and high testosterone) related to immune function. These results suggest that low male F0 signals condition to competitors and mates, and evolved in male anthropoids in response to the intensity of mating competition.PostprintPeer reviewe

Quantitative Description of Glycan-Receptor Binding of Influenza A Virus H7 Hemagglutinin

In the context of recently emerged novel influenza strains through reassortment, avian influenza subtypes such as H5N1, H7N7, H7N2, H7N3 and H9N2 pose a constant threat in terms of their adaptation to the human host. Among these subtypes, it was recently demonstrated that mutations in H5 and H9 hemagglutinin (HA) in the context of lab-generated reassorted viruses conferred aerosol transmissibility in ferrets (a property shared by human adapted viruses). We previously demonstrated that the quantitative binding affinity of HA to α2→6 sialylated glycans (human receptors) is one of the important factors governing human adaptation of HA. Although the H7 subtype has infected humans causing varied clinical outcomes from mild conjunctivitis to severe respiratory illnesses, it is not clear where the HA of these subtypes stand in regard to human adaptation since its binding affinity to glycan receptors has not yet been quantified. In this study, we have quantitatively characterized the glycan receptor-binding specificity of HAs from representative strains of Eurasian (H7N7) and North American (H7N2) lineages that have caused human infection. Furthermore, we have demonstrated for the first time that two specific mutations; Gln226→Leu and Gly228→Ser in glycan receptor-binding site of H7 HA substantially increase its binding affinity to human receptor. Our findings contribute to a framework for monitoring the evolution of H7 HA to be able to adapt to human host.National Institutes of Health (U.S.) (GM R37 GM057073-13)Singapore-MIT Alliance for Research and Technolog

In the blood: the myth and reality of genetic markers of identity

The differences between copies of the human genome are very small, but tend to cluster in different populations. So, despite the fact that low inter-population differentiation does not support a biological definition of races statistical methods are nonetheless claimed to be able to predict successfully the population of origin of a DNA sample. Such methods are employed in commercial genetic ancestry tests, and particular genetic signatures, often in the male-specific Y-chromosome or maternally-inherited mitochondrial DNA, have become widely identified with particular ancestral or existing groups, such as Vikings, Jews, or Zulus. Here, we provide a primer on genetics, and describe how genetic markers have become associated with particular groups. We describe the conflict between population genetics and individual-based genetics and the pitfalls of over-simplistic genetic interpretations, arguing that although the tests themselves are reliable, the interpretations are unreliable and strongly influenced by cultural and other social forces.</p

Ancestral Components of Admixed Genomes in a Mexican Cohort

For most of the world, human genome structure at a population level is shaped by interplay between ancient geographic isolation and more recent demographic shifts, factors that are captured by the concepts of biogeographic ancestry and admixture, respectively. The ancestry of non-admixed individuals can often be traced to a specific population in a precise region, but current approaches for studying admixed individuals generally yield coarse information in which genome ancestry proportions are identified according to continent of origin. Here we introduce a new analytic strategy for this problem that allows fine-grained characterization of admixed individuals with respect to both geographic and genomic coordinates. Ancestry segments from different continents, identified with a probabilistic model, are used to construct and study “virtual genomes” of admixed individuals. We apply this approach to a cohort of 492 parent–offspring trios from Mexico City. The relative contributions from the three continental-level ancestral populations—Africa, Europe, and America—vary substantially between individuals, and the distribution of haplotype block length suggests an admixing time of 10–15 generations. The European and Indigenous American virtual genomes of each Mexican individual can be traced to precise regions within each continent, and they reveal a gradient of Amerindian ancestry between indigenous people of southwestern Mexico and Mayans of the Yucatan Peninsula. This contrasts sharply with the African roots of African Americans, which have been characterized by a uniform mixing of multiple West African populations. We also use the virtual European and Indigenous American genomes to search for the signatures of selection in the ancestral populations, and we identify previously known targets of selection in other populations, as well as new candidate loci. The ability to infer precise ancestral components of admixed genomes will facilitate studies of disease-related phenotypes and will allow new insight into the adaptive and demographic history of indigenous people