Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2

Spatiotemporal bias in genome sampling can severely confound discrete trait phylogeographic inference. This has impeded our ability to accurately track the spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, despite the availability of unprecedented numbers of SARS-CoV-2 genomes. Here, we present an approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2. We demonstrate that including travel history data yields i) more realistic hypotheses of virus spread and ii) higher posterior predictive accuracy compared to including only sampling location. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts.status: publishe

Observation of B→ϕKB\to \phi K and B→ϕK∗B\to \phi K^{*}

We have studied two-body charmless hadronic decays of $B$ mesons into the final states phi K and phi K^*. Using 9.7 million $B\bar{B}$ pairs collected with the CLEO II detector, we observe the decays B- -> phi K- and B0 -> phi K*0 with the following branching fractions: BR(B- -> phi K-)=(5.5 +2.1-1.8 +- 0.6) x 10^{-6} and BR(B0 -> phi K*0)=(11.5 +4.5-3.7 +1.8-1.7) x 10^{-6}. We also see evidence for the decays B0 -> phi K0 and B- -> phi K*-. However, since the statistical significance is not overwhelming for these modes we determine upper limits of <12.3 x 10^{-6} and <22.5 x 10^{-6} (90% C.L.) respectively.Comment: 9 pages postscript, also available through http://w4.lns.cornell.edu/public/CLN

Actin binding domains direct actin-binding proteins to different cytoskeletal locations

<p>Abstract</p> <p>Background</p> <p>Filamin (FLN) and non-muscle α-actinin are members of a family of F-actin cross-linking proteins that utilize Calponin Homology domains (CH-domain) for actin binding. Although these two proteins have been extensively characterized, little is known about what regulates their binding to F-actin filaments in the cell.</p> <p>Results</p> <p>We have constructed fusion proteins consisting of green fluorescent protein (GFP) with either the entire cross-linking protein or its actin-binding domain (ABD) and examined the localization of these fluorescent proteins in living cells under a variety of conditions. The full-length fusion proteins, but not the ABD's complemented the defects of cells lacking both endogenous proteins indicating that they are functional. The localization patterns of filamin (GFP-FLN) and α-actinin (GFP-αA) were overlapping but distinct. GFP-FLN localized to the peripheral cell cortex as well as to new pseudopods of unpolarized cells, but was observed to localize to the rear of polarized cells during cAMP and folate chemotaxis. GFP-αA was enriched in new pseudopods and at the front of polarized cells, but in all cases was absent from the peripheral cortex. Although both proteins appear to be involved in macropinocytosis, the association time of the GFP-probes with the internalized macropinosome differed. Surprisingly, the localization of the GFP-actin-binding domain fusion proteins precisely reflected that of their respective full length constructs, indicating that the localization of the protein was determined by the actin-binding domain alone. When expressed in a cell line lacking both filamin and α-actinin, the probes maintain their distinct localization patterns suggesting that they are not functionally redundant.</p> <p>Conclusion</p> <p>These observations strongly suggest that the regulation of the binding of these proteins to actin filaments is built into the actin-binding domains. We suggest that different actin binding domains have different affinities for F-actin filaments in functionally distinct regions of the cytoskeleton.</p

A Bayesian network to predict coastal vulnerability to sea level rise

This paper is not subject to U.S. copyright. The definitive version was published in Journal of Geophysical Research 116 (2011): F02009, doi:10.1029/2010JF001891.Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (−1 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions.Funding for this work was provided by the USGS Coastal and Marine Geology and Global Change Research programs

Overconfidence in Labor Markets

This chapter reviews how worker overconfidence affects labor markets. Evidence from psychology and economics shows that in many situations, most people tend to overestimate their absolute skills, overplace themselves relative to others, and overestimate the precision of their knowledge. The chapter starts by reviewing evidence for overconfidence and for how overconfidence affects economic choices. Next, it reviews economic explanations for overconfidence. After that, it discusses research on the impact of worker overconfidence on labor markets where wages are determined by bargaining between workers and firms. Here, three key questions are addressed. First, how does worker overconfidence affect effort provision for a fixed compensation scheme? Second, how should firms design compensation schemes when workers are overconfident? In particular, will a compensation scheme offered to an overconfident worker have higher-or lower-powered incentives than that offered to a worker with accurate self-perception? Third, can worker overconfidence lead to a Pareto improvement? The chapter continues by reviewing research on the impact of worker overconfidence on labor markets where workers can move between firms and where neither firms nor workers have discretion over wage setting. The chapter concludes with a summary of its main findings and a discussion of avenues for future research

Does Coupling Affect the Security of Masked Implementations?

Masking schemes achieve provable security against side-channel analysis by using secret sharing to decorrelate key-dependent intermediate values of the cryptographic algorithm and side-channel information. Masking schemes make assumptions on how the underlying leakage mechanisms of hardware or software behave to account for various physical effects. In this paper, we investigate the effect of the physical placement on the security using leakage assessment on power measurements collected from an FPGA. In order to differentiate other masking failures, we use threshold implementations as masking scheme in conjunction with a high-entropy pseudorandom number generator. We show that we can observe differences in---possibly---exploitable leakage by placing functions corresponding to different shares of a cryptographic implementation in close proximity

Truth tracking performance of social networks: how connectivity and clustering can make groups less competent

Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a true opinion following group deliberation. The model incorporates a fine-grained and realistic representation of belief (opinion) and trust, and it allows agents to consult outside information sources. We study a wide range of network structures and provide a detailed statistical analysis concerning the exact contribution of various network metrics to collective competence. Our results highlight and explain the collective risks involved in an overly networked or partitioned society. Specifically, we find that 96% of the variation in collective competence across networks can be attributed to differences in amount of connectivity (average degree) and clustering, which are negatively correlated with collective competence. A study of bandwagon or “group think” effects indicates that both connectivity and clustering increase the probability that the network, wholly or partly, locks into a false opinion. Our work is interestingly related to Gerhard Schurz’s work on meta-induction and can be seen as broadly addressing a practical limitation of his approach

What is information? Toward a theory of information as objective and veridical

Information systems are a strong and ever-growing discipline of enormous relevance to today’s informated world, and yet, as recent reviews have shown, there is still not an agreed and explicit conceptualization or definition of information. After an evaluative review of a range of theories of information, this paper develops and defends a particular theory, one that sees information as both objective and veridical. By objective, we mean that the information carried by signs and messages exists independently of its receivers or observers. The information carried by a sign exists even if the sign is not actually observed. By veridical, we mean that information must be true or correct in order to be information – information is truth-constituted. False information is not information, but misinformation or disinformation. The paper develops this theory and then discusses four contentious issues – information as objective rather than subjective; information as true or correct; information and knowledge; and information and the ambiguity of meaning. It concludes with a discussion of the practical implications of the theory