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Now Playing: Wolfram Technology Conference 2012 Videos

Wolfram technology users from around the world gathered in our headquarter city last month for another successful Wolfram Technology Conference. Attendees got exclusive access to the latest information about our emerging technologies and gained insights from colleagues who shared innovative ways of using Wolfram products. A selection of videos from the conference is now available on YouTube. Check them out to see some of the creative applications our users have developed, including a high-level interface to MIDI sound, an innovative way to solve a Rubik's Cube from pictures, and a route finding system... just to name a few.
Wolfram Blog Team
Announcements & Events

Wolfram Innovator Awards 2012

Stephen Wolfram presented the second annual Wolfram Innovator Awards at the 2012 Wolfram Technology Conference to honor individuals who have made significant contributions to their industry or field of science. Nominated by Wolfram employees and selected by a panel of Wolfram technology experts, this year’s winners are: Craig W. Carter, Professor of Materials Science and Engineering at MIT Robert B. Nachbar, Mathematician, Chemist, and Biologist at Merck Research Laboratories Thomas Roux, Financial Risk Manager at BRED Banque Populaire Rubén Berrocal and Marisa Talavera, National Secretary for Science and Technology and Director of Innovation in Learning (respectively), Panama Government Richard Anderson, Computer Scientist Fred Szabo, Mathematics and Statistics Professor, Concordia University
Wolfram Blog Team
Best of Blog

Code Length Measured in 14 Languages

Update: See our latest post on How the Wolfram Language Measures Up. I stumbled upon a nice project called Rosetta Code. Their stated aim is "to present solutions to the same task in as many different languages as possible, to demonstrate how languages are similar and different, and to aid a person with a grounding in one approach to a problem in learning another." After amusing myself by contributing a few solutions (Flood filling, Mean angle, and Sum digits of an integer being some of mine), I realized that the data hidden in the site provided an opportunity to quantify a claim that I have often made over the years—that Mathematica code tends to be shorter than equivalent code in other languages. This is due to both its high-level nature and built-in computational knowledge. Here is what I found. Mathematica code is typically less than a third of the length of the same tasks written in other languages, and often much better.
Jon McLoone, Director, Technical Communication & Strategy
Education & Academic

Wolfram Research and American Education Week

This week is American Education Week (November 11–17), and in a very fundamental way, our goal as a company is to improve educational standards and accessibility around the world with our technology. For over 20 years, Wolfram Research has been at the forefront of combining technology with education. It started with Mathematica and grew with Wolfram|Alpha, mobile apps, the Wolfram Demonstrations Project, Wolfram SystemModeler, and much more. From simple elementary math to highly complex physics, Wolfram's tools are used not only around the nation, but around the whole world. Next year marks the 25th anniversary of Mathematica. Today, Mathematica is a staple at both research universities and smaller liberal arts colleges. In fact, Mathematica has been adopted by many school systems throughout the country, including SUNY, CUNY, and the Minnesota State Colleges and Universities System (MnSCU). We've partnered with MnSCU to make Mathematica available to Minnesota public high schools through an outreach program. And the government of Panama, having recognized the importance of investing in its future, has recently focused on teaching Mathematica to professors, researchers, and students in all computer-accessible high schools and universities countrywide.
Crystal Fantry, Education Content Manager
Education & Academic

Join The Computer-Based Math™ Education Forum

The computerbasedmath.org community has been growing steadily since the project first started in 2010. Several thousand of you have signed up to show your support, share your ideas, and help spread the word. The Computer-Based Math™ Education Summit has been a great tool for bringing the community together, but we wanted a central hub where the community can gather more than just once a year. So we've launched the The Computer-Based Math Education Forum. Whatever your background, join the conversation and share your experiences.
Michael Belcher, Marketing Project Coordinator, European Sales
Announcements & Events

Developing Light Microscopy Techniques with Mathematica

For Daniel Zicha, head of Light Microscopy at Cancer Research UK, Mathematica is the ultimate tool for biomedical research because it's "quick to develop and then quick to test and visualize the results conveniently and interactively." Zicha uses Mathematica in the development of light microscopy techniques as well as in collaborative research in applications of image processing and analysis methods. Within his collaborative research work in the area of metastasis, Zicha's use of Mathematica to visualize and qualitatively analyze cell morphology led to the discovery of a novel metastasis suppressor. In this video, he describes Mathematica's role in the project and the advantages of having one environment for rapid prototyping, qualitative analysis, and interactive visualization.
Wolfram Blog Team
Products

Dose Selection for Drug Trials Using Wolfram SystemModeler and Mathematica

Explore the contents of this article with a free Wolfram SystemModeler trial. During the last decades, the development and use of therapeutic monoclonal antibodies (mAbs) have grown rapidly. Today, more than 30 different mAbs are successfully used in the clinic—playing important roles in treating complex diseases such as cancers and auto-immune disorders—and more than 200 are in clinical trials. The history of mAbs has, however, not been without problems. In 2006, a first-in-human clinical trial of an mAb, aimed at treating leukemia and rheumatoid arthritis, went terribly wrong. Although the trial was run according to an approved protocol, all volunteers receiving the drug had severe inflammatory reactions and multiple organ failure. The tragic event shocked the medical community and highlighted a very important issue: how do you select a safe starting dose in first-in-human trials? Now, as you may guess, the complete answer to this question is not an easy one. It's also beyond the scope of this blog post. However, as a consequence of the dramatic happenings in 2006, the European Medicines Agency (EMEA) recently published new guidelines to address the issue of starting dose selection in first-in-human trials. Interestingly, the guidelines recommend that the use of modeling and simulation should play an integral part in the selection process, and in this post I thought we would study what such an approach might look like using Wolfram SystemModeler and Mathematica.
Robert Palmer, Applications Engineer
Education & Academic

Falling Faster than the Speed of Sound

Earlier this month, on a nice day, Felix Baumgartner jumped from 39,045 meters, or 24.26 miles, above the Earth from a capsule lifted by a 334-foot-tall helium filled balloon (twice the height of Nelson's column and 2.5 times the diameter of the Hindenberg). Wolfram|Alpha tells us the jump was equivalent to a fall from 4.4 Mount Everests stacked on top of each other, or falling 93% of the length of a marathon. At 24.26 miles above the Earth, the atmosphere is very thin and cold, only about -14 degrees Fahrenheit on average. The temperature, unlike air pressure, does not change linearly with altitude at such heights. As Wolfram|Alpha shows us, it rises and falls depending on factors such as the decreased density of air with rising altitude, but also the absorption of UV light by the ozone layer. At 39 kilometers, the horizon is roughly 439 miles away. At this layer of the atmosphere, called the stratosphere, the air pressure is only 3.3 millibars, equivalent to 0.33% of the air pressure at sea level. To put it another way, the mass of the air above 39 kilometers is only 0.32851% of the total air mass. Given this knowledge, we know that 99.67% of the world's atmosphere lay beneath him. This information was important to Felix's goal to break the sound barrier in free fall because the rate of drag is directly related to air pressure. With less air around him, there would be less drag, and thus he could reach a higher maximum speed. Of course, this would require him to wear an oxygenated suit to allow him to breathe, in addition to keeping him warm.
Jason Martinez, Research Programmer, Wolfram|Alpha Scientific Content
Education & Academic

Calculating the Energy between Two Cubes

In my last blog post, we discussed 3D charge configurations that have sharp edges. Reader Rich Heart commented on it and asked whether Mathematica can calculate the force between two charged cubes, as done by Bengt Fornberg and Nick Hale and in the appendix of Lloyd N. Trefethen's book chapter. The answer to the question from the post is: Yes, we can; I mean, yes, Mathematica can. Actually, it is quite straightforward to treat a more general problem than two just-touching cubes of equal size: We can deal with two cubes of different edge lengths L1 L2 We can calculate the force for any separation X, where X is the distance between the two cube centers (including the case of penetrating cubes; think plasma) We will use a method that can be generalized to higher-dimensional cubes without having to do more nested integrals Instead of calculating the force between the two cubes, we will calculate the total electrostatic energy of the system of the two cubes. The force is then simply the negative gradient of the total energy with respect to X. The electrostatic energy (in appropriate units) is given by: (In the following calculations, we will skip the constant [with respect to X] prefactors Q1 L1-3 Q2 L2-3 or Q1 Q2 if not needed.) Approaching this integral head-on doing one integral after another is possible, but a very tedious and time-consuming operation. Instead, to avoid having to carry out a nested six-dimensional integral, we remember the Laplace transform of 1 / √s.
Michael Trott, Chief Scientist, Wolfram|Alpha Scientific Content
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