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"Colvin, Shawn"
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Diamond in the rough
After learning to play guitar at the age of ten, Shawn Colvin was determined to make a life in music--a decision that would send a small-town girl out on the open road for good. In 1997, two decades after she started, she got her big break. Like the troubled would-be arsonist and survivor of her smash hit \"Sunny Came Home,\" Colvin knows a thing or two about heartache--and setting fires. Diamond in the Rough recounts this passionate musician's coming-of-age, from the prairies of South Dakota to the dark smoky bars in Austin, Texas, to the world stage at the Grammys.--From publisher description.
Book
OFF DUTY --- Adventure & Travel -- Traveler's Tale: On the Road Again, and Again, So Help Me
[Singer-Songwriter Shawn Colvin on the seductive and disruptive powers of life as a journeyman] We were called the Dixie Diesels. The road is freedom; it is escape and redemption; it is flight from sins and sadness, a new place to start over.
Newspaper Article
On the Road Again, and Again, So Help Me
Playing western swing music in dance halls and dives across America was our trade. The road is freedom; it is escape and redemption; it is flight from sins and sadness, a new place to start over.
Newspaper Article
Moving to Austin Changed This Singer Songwriter’s Life—and How She Thought About Death
Swing by JuiceLand to pick up a Soul Boulder (coconut water, banana, blueberry, cherry, almond, cacao powder, brown rice protein, coconut oil, vanilla, and cinnamon—hold the brown rice protein, sub in peanut butter). — [...]I had fallen in love with an Illinois fiddle player named Willie, so I joined his country band, and the rest is history. In 1987 I sang backup vocals on one of the biggest hits of the decade—yes, that’s me harmonizing behind Suzanne Vega on “Luka”—and a year later I got signed to Columbia Records.
Magazine Article
POP
I STILL find myself going back to this song; they haven't done anything as good since. Their albums get better and better, but there's no individual song on them that's as haunting as this one. It's one of those \"beautiful tragedy\" songs, sad and wistful. It lures you in from the start, with just a lone guitar playing. You don't know where it's going to go, but suddenly you sink into this lush thing, with its lilting rhythm.
Newspaper Article
The One Page Magazine
The Big Profile HANNIBAL BURESS By Dave Itzkoff Hannibal Buress will be at the Stand-up Comics' Retirement Home before he drops \"Pickle Juice,\" a routine about his refusal to throw away jars of leftover brine, from his act. The show has already found an audience in part because, Bee says, many Canadians regard Fox News \"as a colossal practical joke.\" ASK JUDGE JOHN HODGMAN By John Hodgman RICHARD WRITES; My wife and I have a dispute about my staying up late to play video games.
Magazine Article
EXHIBIT SUGGESTIONS
According to the rules in the 2005 Exhibitors Guidebook, you can make suggestions to the Adult Home Arts Exhibitors Meeting.
Newspaper Article
Validating clustering of molecular dynamics simulations using polymer models
Background
Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models.
Results
We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters.
Conclusions
We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.
Journal Article