Like many users of Endnote X, I was disappointed to see that the Word 2008 CWYW Update required Endnote X1. I begrudgingly downloaded the X1 demo, installed the CWYW update, and launched Word to test things out. After the Endnote toolbar appeared I hit the button to launch Endnote, and it turns out that I had accidentally left Endnote X running, which the toolbar actually switched to instead of launching Endnote X1! I was able to insert a few citations from Endnote X and everything seems to be working fine. As long as I manually launch Endnote X before using the CWYW toolbar everything works as expected.
Could it be that the CWYW update works perfectly with Endnote X, but they listed X1 as a requirement to convince people to upgrade? Over the past week I've prepared a manuscript with Word 2008 and Endnote X using the CWYW update and I haven't run into any problems. All of you Endnote X users out there might want to give this a try before upgrading to X1 if you're happy with Endnote X.
I am the proud owner of a new MacBook Pro and I'm in the process of transferring everything I need from my old G4 Laptop, I'm also looking at using iWork as an alternative to MS Office.
Like many scientists, we're interested in using graphics cards to increase the performance of some of our numerical code. With the addition of CUDA to the supported list of technologies on Mac OS X, I've started looking more closely at architecture and tools for implemented numerical code on the GPU. This won't be a CUDA tutorial, per se. Those will come later. However, I wanted to take some time to do a few comparisons between some CPU based technologies and the GPU equivalents.
I'm a huge fan of the FFT. We rely heavily on them in structural biology. Intellectually, they simply fascinate me. I don't know why, but they do. So I've chosen to look at FFT performance for this article.
One of the advantages of scripting languages like Python is the multitude of modules you can install and leverage in your research. One of the disadvantages of scripting languages like Python is the multitude of modules you can install and leverage in your research. Anyone who has worked with packages like Numpy and Scipy will know the dilemma: On the one hand, there is a lot of useful code in these packages; on the other, they can make getting started a pain in the neck, because installation is not always trivial, and often will depend upon other modules being pre-installed. This is the type of situation that projects like Fink and MacPorts have arisen to address in the space of UNIX tools.
So is there anything like Fink for scientific Python? It turns out there is: SAGE. The SAGE project slogan is ‘Creating a viable free open source alternative to Magma, Maple, Mathematica, and Matlab’, which will hopefully give you some idea of its lofty goals. In a nutshell, SAGE brings together a swath of different modules in one easy to install package.
I think Time Machine is fantastic, particularly when used with a Time Capsule. For this week, I just thought I would do a quick roundup of a few tricks and news I have collected on Time Machine.
Tip 1. There was this week an interesting software released, that allows access to Time Machine via the command-line. That's right. Instead of flying through space, you can just type some text and get some lines of text back, the good old way. The CLI version
tms was developed by Robert Pointon who runs the FernLightning website. It was designed to accept VCS-like command (which means similar to what you would do with version control software such as Subversion). Learn all about it on the tms website.
Software bundles like MacHeist have become a regular feature of the Mac landscape of late. There are plenty of good deals to be had, and plenty of discussion about the ethics of such bundles. But leaving all that aside, what would be your ideal bundle for science?
Nick Greeves is a senior lecturer at Liverpool University, he is also Mac using chemist. He has created a web site dedicated to displaying interactive 3D animations of some of the most important organic chemistry reactions. This site is an invaluable undergraduate teaching resource.
One interesting question in scientific publishing right now is how to "cross the lines" between academic publication and informal web discussions like blogging.
For example, I came across a blog post from Jon Udell, discussing how difficult it can be to find web discussions about scientific articles.
I've written before on this issue of memory bandwidth bottlenecks for certain
type of scientific codes (i.e. memory "bound" codes) on current multi-core Macs.
The main point is that with processors getting faster and faster (higher clock rates
and inclusion of additional cores) at a much more rapid rate compared with
If you had five minutes with the leadership of Apple's Science division, what would you ask? What are the biggest open questions for Science on the Mac? And what should Apple do to get more/better scientific apps to the Mac?