Posts archived in Hardware
Thorlabs and Newport have offered 3D models of their products for a long time. However, they’re typically in formats for expensive programs like SolidWorks and AutoCAD. In the past year or two, Newport has been slowly adding to their library of Google SketchUp models.
I still prefer SolidWorks, but I’m optimistic that I’ll eventually switch to SketchUp. Regardless, it’s nice to see a company supporting free tools.
Like many of you, I went to monster truck show last weekend.
The competition reminded me MATLAB’s new thing: Cody.
It’s a bunch of problems posed as MATLAB coding tasks. For example:
Find the mean of each consecutive pair of numbers in the input row vector. For example,
x=[1 2 3] —-> y = [1.5 2.5]
x=[100 0 0 0 100] —-> y = [50 0 0 50]
To solve the problem, you write a MATLAB program that performs that input-output transformation. Of the correct answers, the shortest program wins. Answers are automatically checked for correctness and there is a graphic display of length and correctness of submitted answers:
At the very least, I think this is a clever tool for learning MATLAB. Working through exercises is pretty dry. This is effectively the same thing, but the competetion aspect is energizing. Most problems are locked until you solve easier ones. You can submit your own problems too. So this could be a sneaky way to crowd source your own work.
Long live competion.
On the topic of MATLAB learning materials (covered previously here and lots more MATLAB stuff here), MIT has some online courses freely available. Here’s an “aggressively gentle” intro to MATLAB, and some more MATLAB resources. (Hat tip to MH)
Also here’s a link from an older post on xcorr (Patrick Mineault’s excellent blog). This course webpage has a bunch of examples in MATLAB code. They’re great for simultaneously learning MATLAB and visual neuroscience.
Visual.ly recently posted a list of the top visualizations of 2011. This is a map of the world in which Twitter tweets are plotted using their GeoIP info and color-coded based on language. Looks cool, but there is no message. I could have guessed how this map would look. Germans tweet in German, Brazilians tweet in Portuguese, and so on. Big urban centers have a lot of tweets. Developing economic areas and sparsely populated regions don’t. I don’t see anything interesting. And so many of the colors are difficult to distinguish, if there is any new information, it’s difficult to figure out. They should have added more text labels on the map to identify languages near where they are found. Really? This is #1 on the list?
The field of data visualization is not well defined. The comeliness of a visualization is important, but if there is nothing revealed by the visualization– no story told– then it fails. There seems to be quite a number of people who enjoy studying data visualization who are almost purely interested in the aesthetics. This makes it difficult to really get good advice. A recent book review in Science by Robert Kosara seems to be wrestling with this issue. Two books are covered, Yau’s Visualize This, and Lima’s Visual Complexity. The former is a practical guide to creating effective visualizations, the latter is a collection of breath takingly beautiful works of art with no apparent message. Kosara notes that Lima “never attempts to explain what viewers can learn from any of the examples.”
Tufte has already said much of what needs to be said about data visualization. For example: “Have a message.” “No chart junk.” “Maximize the data-ink ratio.” Tufte himself said of Lima’s book, “One useful question to ask of each image is: What did I learn from this, in addition to seeing an elegant architecture?”
Yau does an excellent job following Tufte’s principles. He has a website that is worth checking out, flowingdata.com. And don’t forget Tufte’s own website. Junk Charts is good too. It just posted this holiday Venn diagram:
Next time you’re explaining TIRF to someone, start off by showing them this piece of artwork. (Arndt von Scheidt, source)
Apple’s Safari web browser v5.1 has an annoying behavior where tabs reload/refresh like crazy. This can cause lost work and data.
Disable the problematic behavior this way:
1. Close Safari
2. Open a terminal and enter this command
defaults write com.apple.safari IncludeInternalDebugMenu 1
3. Restart Safari. You should see a new menu to the right of “Help” called “Debug”.
4. Select “Use Multi-process Windows” so that it no longer has a checkmark beside it.
That should fix it. (via)
For the next two weeks, you can get a personal 1 year subscription to any of the Nature publications for a price equal to that journal’s impact factor. (link) (via xcorr)
Think you could do a better job allocating the NIH budget? This is your chance to not just armchair quarterback the budget management, but offer some constructive input.
Sally Rockey is actively soliciting your comments and it’s not too late to chime in.
First, try the nifty web app they built where you can adjust the number of small and large grants funded and see how that changes the landscape accordingly (screenshot above).
Let me add some clarification to the hybrid PMT post.
The actual signal that comes off of a PMT in response to a photon is a pulse of current. The amplitude of this pulse can vary wildly, and the variation is referred to as multiplicative noise. For that reason, photon counting schemes typically use a simple threshold-crossing to trigger counts, which often mostly solves multiplicative noise. You’re smart, so I know you’re already wondering what happens when two pulses occur very close to each other in time. This is called “pile up” and it’s a problem. There are different ways to deal with it, but since single pulses can be so variable, it’s difficult to deal with it effectively. I also want to note that even for dim images, events WILL come close enough together SOMETIMES. And for bright images, it happens quite often, and this precludes quantitative imaging.
Hybrid PMTs address this by having a huge gain at the first stage which essentially decreases the noise (by a factor of sqrt(n)) so that the photon-evoked pulses are less variable. They can also be designed to make the pulses briefer. Brief pulses = less pileup, and more regular pulses means that more sophisticated schemes can be used to accurately count photons. All in all, this results in more quantitative imaging. Of course, this is most relevant for bright images.
Alright, back to watching Plaxico Burress not catching passes.
George McNamara is planning on updating the massive PubSpectra (previously mentioned here).
He’s currently soliciting submissions. Do you have any to contribute?
(link)