Preparing publication quality images from your calculations is essential. To pre-visualize images to get the best orientations of your molecule, DTK2.0 includes two options: a new GUI called DensToolKitViewer and DTKQDMol.
Gotta say, watching Scarlett Johansson making eyes at Aquilops is not getting old. Screengrab from this clip, the good stuff starts about 6:19. This short clip from the Tonight Show is also pretty great. Aaaand Halloween costume: sorted. I already have everything I need! (…except the lifelike Aquilops puppet. Dammit.) I may get back to posting actual science when I’m not drowning in summer anatomy teaching. Three days to go.
This are just a few insights I have got from some of the talks I attended. As usual, this does not represent a report on the WATOC congress itself, but simply some aspects that caught my personal eye.
How do we make sense of the implications of current geopolitical, financial and technological volatility? What impact will all of this have on the relationship between libraries and publishers, and libraries and their users? This blog post is an attempt to address these questions.
Die EU-Migrationspolitik bewegt sich seit jeher zwischen Logiken selektiver Offenheit und Abschottung. Seit dem Sommer der Migration befindet sie sich in einer Konjunktur, in der sich Strategien einer stärkeren Europäisierung mit einer forcierten Renationalisierung konfrontiert sehen. In diesem Kontext entfalten sich aus den politischen Kämpfen und Rechtskämpfen widersprüchliche Dynamiken.
We are excited to welcome Emi Tanaka and Nima Hejazi to our team of Associate Editors for rOpenSci Stats Software Peer Review.They join Laura DeCicco, Julia Gustavsen, Jouni Helske, Toby Hocking, Rebecca Killick, Anna Krystalli, Mauro Lepore, Noam Ross, Maëlle Salmon, Emily Riederer, Adam Sparks, Beatriz Milz, Margaret Siple and Jeff Hollister.Since 2015, rOpenSci has operated a thorough and collaborative software peer review system.Our
How can we document software and computational analyses in such a way that others can convince themselves of their validity, and build on them for their own work? The question has been around for many years, and a number of attempts have been made to provide partial answers. This post provides a brief review and describes my own tentative answer, inviting you to play with it. Explainable AI is a hot topic today.
This is the fifth part of a blog post series on spatial machine learning with R. You can find the list of other blog posts in this series in part one.
Most regular readers will know about DinoCon, a two-day semi-technical/semi-popular conference being run by SV-POW!’s own Darren Naish. (Darren is very much a silent partner here, and is much better known for his own blog Tetrapod Zoology, and of course for his technical work.) The first ever DinoCon will be this summer — Saturday 16th & Sunday 17th August at the University of Exeter.
What began in the fall of 2024 as a weekly experiment - just me, a blank page, and a question about how technology and humanity are reshaping each other - quickly grew into something more.
Being a researcher implies a long stretch of studies at the university to specialize in a certain field. To me personally, it felt like I just kept studying and studying, year after year, and… here I am. One day, when I was 18 I went to the university and I am still there. I have come to realize that I never really mentally switched from being a student to being a professional or having a job.