Membrane fluidity and temperature sensing are coupled via circuitry comprised of Ole1, Rsp5, and Hsf1 in Candida albicans

Peer reviewedPublisher PD

Surviving the heat of the moment : a fungal pathogens perspective

Peer reviewedPublisher PD

Estimating the Explosion Time of Core-Collapse Supernovae from Their Optical Light Curves

Core-collapse supernovae are among the prime candidate sources of high energy neutrinos. Accordingly, the IceCube collaboration has started a program to search for such a signal. IceCube operates an online search for neutrino bursts, forwarding the directions of candidate events to a network of optical telescopes for immediate follow-up observations. If a supernova is identified from the optical observations, in addition to a directional coincidence a temporal photon-neutrino coincidence also needs to be established. To achieve this, we present a method for estimating the supernova explosion time from its light curve using a simple model. We test the model with supernova light curve data from SN1987A, SN2006aj and SN2008D and show that the explosion times can be determined with an accuracy of better than a few hours.Comment: Version accepted for publication by Astroparticle Physics; 13 pages, 5 figure

Remote determination of the velocity index and mean streamwise velocity profiles

Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Water Resources Research 53 (2017): 7521–7535, doi:10.1002/2017WR020504.When determining volumetric discharge from surface measurements of currents in a river or open channel, the velocity index is typically used to convert surface velocities to depth-averaged velocities. The velocity index is given by, inline image, where Ub is the depth-averaged velocity and Usurf is the local surface velocity. The USGS (United States Geological Survey) standard value for this coefficient, k = 0.85, was determined from a series of laboratory experiments and has been widely used in the field and in laboratory measurements of volumetric discharge despite evidence that the velocity index is site-specific. Numerous studies have documented that the velocity index varies with Reynolds number, flow depth, and relative bed roughness and with the presence of secondary flows. A remote method of determining depth-averaged velocity and hence the velocity index is developed here. The technique leverages the findings of Johnson and Cowen (2017) and permits remote determination of the velocity power-law exponent thereby, enabling remote prediction of the vertical structure of the mean streamwise velocity, the depth-averaged velocity, and the velocity index.National Institutes for Water Resources Grant Number: 2012NY189G2018-03-0

What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures

What is the nature of the feelings evoked by music? We investigated how people represent the subjective experiences associated with Western and Chinese music and the form in which these representational processes are preserved across different cultural groups. US (n = 1,591) and Chinese (n = 1,258) participants listened to 2,168 music samples and reported on the specific feelings (e.g., “angry,” “dreamy”) or broad affective features (e.g., valence, arousal) that they made individuals feel. Using large-scale statistical tools, we uncovered 13 distinct types of subjective experience associated with music in both cultures. Specific feelings such as “triumphant” were better preserved across the 2 cultures than levels of valence and arousal, contrasting with theoretical claims that valence and arousal are building blocks of subjective experience. This held true even for music selected on the basis of its valence and arousal levels and for traditional Chinese music. Furthermore, the feelings associated with music were found to occupy continuous gradients, contradicting discrete emotion theories. Our findings, visualized within an interactive map (https://www.ocf.berkeley.edu/∼acowen/music.html) reveal a complex, high-dimensional space of subjective experience associated with music in multiple cultures. These findings can inform inquiries ranging from the etiology of affective disorders to the neurological basis of emotion