Sunglass Partners With DIYROCKETS To Launch 3D-Printed Rocket Engine Design Competition

So excited to be a part of the DIYRockets team! Here is a link to the competition on our website:

http://darle64.wix.com/openspaceuniversity#!rocketchallenge/c22xk

Here is the TechCrunch coverage on the competition:

http://techcrunch.com/2013/03/08/sunglass-partners-with-diyrockets-to-launch-3d-printed-rocket-engine-design-competition/

I’m getting a chance to talk to the International Space Station crew!

I’m going to be 1 of 150 to talk to the International Space Station crew, I’m so excited!

http://www.nasa.gov/connect/social/social_ISSscience_feb2013.html

Solve for X: Collaborative Science

Today knowledge creation is dominated by universities and large corporations. These entities are largely responsible for creating new theories and products. But, Adrien Treuille thinks that is going to change and that by 2025, knowledge creation will be spread throughout society and be produced by ad hoc groups of people utilizing the internet. There is evidence that this is already happening.

One example of the knowledge creation model that Treuille posits is protein folding. It is typically done by large universities on super computers. Treuille and colleagues created FoldIt, a game that allows players all over the world to compete to solve protein folding problems. Treuille says that currently there are over 100,000 players worldwide. I’ve played FoldIt a few times. If you like 3D puzzles you’ll love it! Give it a try and see what you think.

Treuille and colleagues have created another example of a collaborative online game called EteRNA, which allows players to design molecules. The molecules are then synthesized and the experimental results are sent back to the players with a score. Over the course of six months, 30,000 EteRNA players reached a point where their worst nanoengineering solutions were still better than the best computer generated ones. Treuille and colleagues have published their results in Nature.

Treuille thinks that examples like FoldIt and EteRNA make a case to augment crowdsourcing to what he refers to as crowdsolving, where large groups of people work with big data and computation to solve problems. Building on this concept, Treuille thinks that using the scores from these collaborative online crowdsolving games, a monetary or other motivational reward could be offered, allowing individuals to be paid for their intellectual labor.

Could this model be utilized to solve global societal problems? Actually, Innocentive, Ashoka Changemakers, and Challenge.gov are a couple of examples that I’ve come across in the last few years that seem to utilize a similar model. Although Innocentive, Ashoka Changemakers, and Challenge.gov don’t use a gaming aspect, they incorporate crowdsourcing to solve real world problems and offer prizes to the winners. I’m sure there are more like these and I’m sure we’ll start to see more like FoldIt and EteRNA in the future. I’m not sure if FoldIt and EteRNA qualify as serious games, but the gaming element, definitely adds an important online engagement element to the model.

The entire Solve for X talk about collaborative science can be seen here.

Solve for X: Nano spray on antenna

Google’s Solve for X website states that it is “a place to hear and discuss radical technology ideas for solving global problems”. Right now, there are approximately 19 talks on the site http://www.wesolveforx.com/#.  There were two talks about ideas that I’ve already heard of, Fold It and Matternet. I plan to address both of these talks in future posts. The talk that contained one of the most fascinating and original ideas I’ve come across in a long time was titled, Low Power Wireless Everywhere. Essentially, Anthony Sutera and his company have developed a nano spray on antenna.

The idea developed when a colleague of Anthony Sutera’s who used to be in the Special Operations community said that when he was in theater, he couldn’t transport or conceal antennas to effectively transmit. He asked Sutera if he could solve this problem. What Sutera came up with, was a wireless nano spray antenna that consists of 1000s of nano capacitors.  In field tests, Sutera’s wireless nano spray antenna ended up working an order of magnitude better than the standard antennas the government client had been using.

Here are a few fascinating field test results:

The nano spray antenna material was painted onto a tree. Within 5 minutes, it was connected and transmitting on VHF to an aircraft 14 miles overhead. This was double the range of a standard antenna on the ground.

When the nano spray antenna material was applied to a one milliwatt RFID tag, it increased the readable range from 5’ to 700’.

The nano spray antenna material successfully communicated under water over 1 NM at 50 MHz, 3 Watts, submerged at periscope depth.

I agree with Sutera that this new nano spray antenna material represents a paradigm shift in antenna technology. He envisions several uses for the material which will enable wireless connectivity anywhere. Sutera is also doing experiments in which the material actually takes energy out of the atmosphere. With that in mind, instead of having the large cell phone tower infrastructure that we have today, think about having cell sites that are painted on walls and power themselves.

I can’t help but thinking about all the applications this technology could have…this is genius!

Here’s a direct link to Sutera’s talk: http://www.wesolveforx.com/#t=t&n=f35b89ba

Higher Education Solutions Network

Yesterday I was invited to attend the official announcement luncheon for the Higher Education Solutions Network (HESN) at the National Academy of Sciences. HESN is being touted as a DARPA-like approach to US Foreign Aid. Seven universities were chosen to house development labs, whose purpose will be to create innovative, low-cost solutions to improve health, reduce poverty, and reduce conflicts.

The universities that were chosen are:

-   Texas A&M, which will study the “intersection between poverty, conflict, and food insecurity.”

-   Makerere University in Uganda, which will create an “international partnership that will apply science and technology to improve the resilience of African communities against natural and political stresses.”

-   MIT, which will “foster local innovation by supporting the ingenuity, creativity and resiliance [sic] of people living in poverty” and evaluate technological solutions.

-   Michigan State University, which will analyze how ” population growth, rapid urbanization, climate change, pressures on land, and skills gaps” affect food security.

-   Duke University, which will “identify and scale promising new technologies in healthcare delivery and prevention.”

-   The University of California, Berkeley, which hopes “to create a new field of Development Engineering.

-   The College of William & Mary, which will create “high resolution geospatial data and powerful analytical and GIS tools that enable USAID and the global development community to more effectively target, monitor and evaluate aid projects and programs.”

http://news.sciencemag.org/scienceinsider/2012/11/a-darpa-approach-to-us-foreign-a.html

After Raj Shah made opening remarks, a representative from each university took the stage to briefly describe their respective program initiatives. Although all 7 universities presented compelling ideas for how they intended to contribute to the HESN, there were 2 that stood out in my mind.

A student from the College of William & Mary spoke about a project involving the analysis of aid data, which revealed that World Bank relief efforts were concentrated in the south of Kenya, rather than in poorest northern areas of the country. This analysis helped in making decisions to reallocate the distribution of aid. Also, there was another project the student referred to as “the Yelp for development finance”, which allowed end users of aid to rate specific aid organizations, thereby closing the customer feedback loop.

Duke also caught my attention. As it states above, Duke will be focusing on healthcare delivery and prevention. Although that is an area of interest to me, what really caught my ear, was that the HESN effort is going to be housed in the Social Entrepreneurship Accelerator at Duke SEAD. In doing so, I think that Duke maybe adding an additional cross sector collaboration element, by bringing in potential contributors from the social entrepreneurial academic, and government sectors.

I am interested to see what the HESN will produce.

NOVA: Making stuff smaller, cleaner, smarter, and stronger

I recently watched the NOVA series Making Stuff which originally aired in 2011. It gives a behind-the-scenes look at scientific innovations ushering in a new generation of materials that are stronger, smaller, cleaner, and smarter. I recommend watching the series in it’s entirety,
http://www.pbs.org/wgbh/nova/tech/making-stuff.html
but if you have a limited amount of time, I’ve provided times for the segments I found most interesting below. I hope you enjoy them as much as I did. Thank you Stephanie for recommending the series to me.

Making Stuff: Smaller
http://www.pbs.org/wgbh/nova/tech/making-stuff.html#making-stuff-smaller
26.12-34.30: nanobots to cure specific types of blindness
45.36-52.00 :nanobots to kill cancer

Making Stuff: Cleaner
http://www.pbs.org/wgbh/nova/tech/making-stuff.html#making-stuff-cleanerhttp://www.pbs.org/wgbh/nova/tech/making-stuff.html#making-stuff-cleaner
10.00-15.45 electric motorcycles that go from 0 to 60 in less than a second
15.45- 24.10 hydrogen powered cars
26.00- 27.48 biofuel
32.43-37.00 bioplastic
37.00-40.28 upcycling = plastic bags to nanotubes to batteries
40.28-44.00 trash to electricity
44.00-46.00  energy storage and waste
46.03-48.45 bloom box = clean energy without a grid
48.45- 52.06 artificial photosynthesis

Making Stuff: Smarter
http://www.pbs.org/wgbh/nova/tech/making-stuff.html#making-stuff-smarter
6.11-9.30 sharklet and fighting antibiotic resistant bacteria
14.45-17.26  climbing robot based on gecko adhesive
19.52-24.45 battle jacket, self-healing and self-sealing coating
29.00-33.32 MR fluid
36.00-38.24- mimic bird flight
43.30-45.17 targeted chemotherapy
49.00-51.20 invisibility

Making Stuff: Stronger
http://www.pbs.org/wgbh/nova/tech/making-stuff.html#making-stuff-stronger
steel, kevlar, carbon nanotubes, spider silk

Wired Health Conference: Eric Topol and Nicholas Christakis

I live streamed parts of the Wired Health Conference a few days ago and I found Eric Topol and Nicholas Christakis particularly engaging. If you are unfamiliar with the work of these two gentlemen, brief speaker bios can be found here:
http://www.wiredhealthconference.com/speakers.html#topol

Eric Topol

Eric Topol engaged in a discussion with Wired Executive Editor Thomas Goetz, titled Information Into Action. First, they discussed health-based genetics. Topol said that although the American Medical Association thinks that patients shouldn’t have access to their own DNA information, he thinks that DNA should be democratized, and that this will have to be driven by consumer demand.

Goetz brought up that the FDA currently has a list of approximately 120-130 drugs that have specific genetic interactions. Goetz stated that he knew he shouldn’t take Plavix, a well-known drug, that Topol was instrumental in developing, which helps to prevent blood clots, because Goetz did a 23 and me test. 23 and me provides customers with their own DNA information https://www.23andme.com/. Goetz’s 23 and me test revealed that Plavix simply wouldn’t be effective, based on his genetics. Topol relayed that the list of genetic-specific drugs that Goetz mentioned, are only being utilized in a few centers, which Topol thinks is unfortunate.

Next, Topol said that although genetic specific drugs may not be utilized much in the US, that in Taiwan, genetic testing laws aid the Taiwanese in obtaining genetic specific drugs. I agree with Topol up to this point. I think that people should have access to their own DNA information, if they want it. But, laws that require mandatory DNA testing, no matter what the end goal, are a definite red flag for me.

There are several bioethical issues that genetic testing rouses, the two that immediately came to my mind are eugenics and privacy. Here is a brief look into bioethical issues regarding genetic testing from the Presidential Commission for the Study of Bioethical Issues. http://blog.bioethics.gov/2012/02/02/ethical-questions-around-genetic-testing/.  The entire report can also be downloaded from the site. I am not going to go into more depth regarding bioethical issues, but I just want to seriously caution that although genetic testing may assist in targeting drugs to individuals, genetic testing as a whole is a complicated and divisive issue.

During the final part of the discussion, Topol discussed some examples of Scripps digital medicine. Here are some examples:

1. A 90 micron nanosensor that Caltech is assisting Scripps develop, that when coupled with genomic signatures, could signal a smart phone days before a heart attack would occur. Other future possibilities for nanosensors could include monitoring free circulating DNA in someone who’s had cancer or who is at high risk or monitoring antibodies in the immune system to warn someone of an imminent immune attack.

2.  cardiogram sensor + smart phone app

3.  glucose sensor + smart phone app

4. GE mini portable ultrasound, that topo has used to replace his stethescope since 2010

The entire video for Information Into Action can be seen here: http://fora.tv/2012/10/16/Eric_Topol_Information_into_Action_at_Wired_Health

Nicholas Christakis

Nicholas Christakis engaged in a discussion with Wired writer Clive Thompson, titled How People Networks Impact Health. First, Christakis described how he and his collaborators used the Framingham heart study data, coupled with other data sets, to study obesity, weight loss/gain, smoking, and drinking. Christakis said that although these topics were the initial focus of their research, it evolved into studies centered around cooperation and altruism. And the larger questions that came into focus were: why do we make networks and why do they have the structure that they do?

Christakis said that the network studies lead to a new way of forecasting epidemics. If you can identify central people in a network and monitor them with their permission, possibly using big data technology, the person at the center of the network, should theoretically be affected before the average person in the network. Christakis said that this network-based methodology could inform health professionals where an epidemic will be tomorrow and where it will be in 2-6 weeks. Christakis provided a hypothetical. A few thousand New Yorkers volunteer to report when they have the flu and release their network data, possibly via their phones. If this were to happen, it would be theoretically possible for the NY Health Department to know about a health epidemic, weeks before it strikes.

Lastly, Christakis said that in addition to forecasting epidemics, he and his colleagues have also have considered how to target key people in networks with information, in order to accelerate overall network adoption. Christakis thinks that this network-based methodology could be utilized to accelerate the adoption of beneficial innovations, better health practices, and other valuable information.

The entire video for How People Networks Impact Health can be seen here:
http://fora.tv/2012/10/16/Nicholas_Christakis_How_People_Networks_Impact_Health

Big Data + Health Care

My last post focused on the overarching general topic of how big data analytics could be utilized towards social good. In this post, I would like to focus in on big data analytics and their applications/possible applications in the health sector.

Diagnostic data is produced in real-time. Being able to process and analyze this vast amount of data almost simultaneously, is already helping save lives. In the neonatal critical care unit in Toronto, IBM Streams monitors every heartbeat, breath, anomaly, and more. The Streams platform functions as an early warning system, assisting doctors in finding novel ways to circumvent life-threatening infections up to 24 hours earlier than in the past. This example is taken from pp. 126-127 of the IBM e-book Understanding Big Data. I think that it is an excellent primer on big data. You can download the free e-book here: https://www.ibm.com/developerworks/wikis/display/db2oncampus/FREE+ebook+-+Understanding+Big+Data

Now, from one specific example to the bigger picture. I agree with the Computational Biology article, Digital Epidemiology, published in July 2012, that mobile, social, real-time data could provide local and timely information about global disease and health dynamics. A few possibilities include:

- Ability to observe the spatiotemporal movements of millions of people during a disease outbreak

- Rapid detection of an unusual illness in a remote village anywhere in the world

- Near real-time estimation of influenza activity levels

- Assessment of vaccination sentiments during pandemic preparedness efforts

- Social media could inform health professionals about emerging trends in a wide range of health behaviors

Big data analytics on mobile phones have already been used to:

- Create a realistic model of human mobility

- Predict the rate of spread of drug resistance

- Assess the prospects of malaria eradication

- Monitor population movements during the Haiti cholera outbreak in near real-time

The Digital Epidemiology article can be downloaded here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002616

One area that I am particularly interested in is biosurveillance, which involves using large scale natural language processing (NLP) for tracking outbreak related information. Which is why an article by Robert Munro, et. al., Tracking Epidemics with Natural Language Processing and Crowdsourcing, published by the Association for the Advancement of Artificial Intelligence, piqued my interest.

The researchers make three main arguments:

1.  Search-log-based detection methods like Google Flu Trends, are a trailing signal that follow other reports. That said, may still be unsurpassed in automated early prediction of season epidemics.

2.  Existing systems have made erroneous conclusions about the correct machine-learning techniques to employ, mostly due to lack of training data, and that crowdsourcing may be a way to overcome this.

3.  Crowdsourcing is suitable for scalable annotation in active learning systems that need to rapidly adapt to massive amounts of changing information, like when a new disease starts spreading through a new region.

The article also gives a great summary of related projects in the field: ARGUS, HealthMap, ProMed, WHO, and Google Flu Trends. If you are interested in the topic of biosurveillance, I highly recommend reading the entire article. http://www.robertmunro.com/research/munro12epidemics.pdf

As a whole, I think it is an exciting time to be at the intersection of mobile, health, and big data analytics. I think there could be a myriad of beneficial outcomes, which could assist frontline health workers, their patients, and the global health community at large.

Big Data + Social Good

The Gates Foundation recently hosted a webcast on digital strategy for nonprofits. The Director of Social Strategy for the American Red Cross, had a slide in her presentation titled, How Americans use Social Tools in Emergencies. The statistic that I couldn’t get out of my head, is that more than 76% of people who posted a distress message to a social media site,  expected to be rescued within 3 hours. The Director of Social Strategy for the American Red Cross thought that the public may need some tempering, as to whether or not that was plausible.

I immediately thought, maybe, it depends. Was The Director of Social Strategy for the American Red Cross basing her statement on personnel and resources available or on information available? If she was basing her statement on a personnel and resources available constraint, and that it just isn’t possible to rescue everyone who posts a distress message to a social media site within 3 hours, that made sense to me. However, if she was basing her statement on not being able to process the social media information fast enough to perform a rescue within 3 hours, with readily available personnel and resources, big data analytics may be able to analyze distress messages sent via social media fast enough to make a 3 hour rescue possible.

I will come back to the theoretical 3 hour rescue time frame, but now I want to give you a powerful example of how big data analytics is being utilized right now in business and industry. Recently, the Danish wind power plant manufacturer Vestas Wind Systems and IBM won the 2012 Big Data Award jury at the Computerwoche Big Data Congress in Germany. Lars Christensen, Vice President of Plant Siting & Forecasting, estimates that Vestas will soon have between 18 to 24 petabytes of data. To put that into perspective, that is like watching 70 years of HD video. Of course all of that data is worthless without applying analytics. Using a customized IBM big data analytics solution, answers to queries that used to take Vestas 3 weeks, now take 15 minutes.
http://www.ibmbigdatahub.com/blog/lords-data-storm-vestas-and-ibm-win-big-data-award

Now, let’s go back and think about the theoretical 3 hour rescue time frame, within the context of big data analytics. First, consider an analogy between the data Vestas is analyzing and the number of social media distress messages. If Vestas is able to answer queries in 15 minutes, that used to take 3 weeks, on petabytes of data, I posit that it is theoretically possible to analyze social media distress messages to make a 3 hour rescue time frame plausible. I am not taking into account personnel or resource constraints, but focusing on how social media distress messages could be analyzed in the context of big data.

Although it may appear that I am solely making a case that someone could be rescued within 3 hours of posting a distress message to a social media site, what I’d like to do, is use this specific theoretical scenario to do some inductive reasoning and ask, how can big data be applied for social good?

I have seen big data analytics being discussed in business, academia, and government. I haven’t seen much, if any, discussion and/or application of big data analytics in the humanitarian sector. If you are reading this post and are aware of such discussion and/or application, I welcome the information, as I think that big data analytics could have profound effects on the humanitarian sector.

Why should we be interested in global mobile phone usage?

As I watched the Social Good Summit (SGS) last Saturday, I was reminded of percentages of global mobile phone users and how mobile phones can be utilized, topics that I have been interested in for years now. During How Digital is Redefining Diplomacy, Charles Ray, Former U.S. Ambassador to the Republic of Zimbabwe, stated that over 60% of Zimbabwean youth with no electricity are accessing the internet through mobile phones. And, during Can Mobile Phones Eliminate Pediatric Aids, Josh Nesbit, CEO of Medic Mobile, stated that 90% of world’s population is covered by a mobile signal; 50% of people in sub-saharan Africa own cell phones.

The SGS talks mentioned above, focused on mobile governance and mobile health respectively, and reminded me of an Individual Research and Development proposal I wrote while working at Johns Hopkins Applied Physics Lab back in 2009.  It posited that mobile phones were powerful tools that were being utilized for: health, governance, politics, education, reporting and coordinating natural disasters, work, to recruit blood donors, to raise philanthropic funds, banking, and business. Now, three years later, I have no doubt that there are several other creative ways that mobile phones are being utilized.

In addition to making me recall my 2009 research proposal, the statistics mentioned at SGS made me decide to update my knowledge regarding percentages of global mobile phone usage. Here are two reports that you might find useful:
The World in 2011: Fact and Figures, International Telecommunication Union (ITU)
http://www.itu.int/ITU-D/ict/facts/2011/index.html
The Traffic and Market Data Report, Ericsson
http://hugin. info/1061/R/1561267/483187.pdf

Here is only one statistic from each of these reports. The World in 2011: Fact and Figures by The International Telecommunication Union (ITU) says that global mobile penetration is now at 87 percent and 79 percent in the developing world. And, The Traffic and Market Data Report by Ericsson says that mobile growth is particularly rapid in China and India, where 50 million new subscriptions were added in Q3 of 2011.  I am only mentioning a few statistics regarding global mobile phone usage, because I don’t want to get bogged down in statistics in this post. However, I encourage everyone reading this, to do their own research, if they are curious about the topic.

In conclusion, I think that the myriad of ways that mobile phones are being/could be utilized, in conjunction with the percentage of global mobile phone users, makes the mobile phone a powerful tool. In fact, that statement was the impetus for submitting my 2009 research proposal. Therefore, I hope that SGS sparks more discussion about how mobile phones can be leveraged around the globe in valuable ways.

If you have any ideas you’d like to share, please put them in the comments section. Or, if you’d rather not share with everyone, you can always send me a private email via my “about” page.

Unleashing the Power of Open Innovation in Government

Today is the third and final day of the Social Good Summit (SGS). Some of the organizations involved include Mashable, the United Nations Foundation, 92Y, Ericsson, UNDP, and the Bill & Melinda Gates Foundation. Yesterday, I live streamed three or four of the approximately eighteen topics that were presented. All of the topics are serious complex problems, that obviously warrant in-depth discussions. The SGS allotted approximately 10-30 minutes for each topic presentation, which isn’t much time. That said, I think that one of the goals of SGS is to simply heighten awareness and to spark world-wide discussion of these topics.

Out of the three or four that I was able to watch yesterday, I’d like to focus on one in particular. Todd Park, White House Chief Technology Officer, gave a talk entitled, Unleashing the Power of Open Innovation in Government.  I was skeptical from the start, seeing the words “Innovation” and “Government” used together. But, Park made some compelling points and gave concrete examples. The Open Data Initiative piqued my interest.

The Open Data Initiative is designed to share government data to fuel entrepreneurship. In 2010, the Department of Health and Human Services (HHS) let it be known that its data was available to entrepreneurs and innovators.  Since then, businesses and nonprofits have utilized this data to create new products, services, and jobs. http://www.whitehouse.gov/innovationfellows/opendata

Park used concrete examples to back up these claims. Here are just two of the businesses that have been created, resulting from access to the HHS data:

iTriage –  an app developed by two ER physicians that allows one to evaluate symptoms, find possible causes, and most importantly, locate appropriate medical facilities. Find out more about iTriage at http://about.itriagehealth.com/

PulsePoint – app users, who have indicated they are trained in cardiopulmonary resuscitation (CPR) and are willing to assist in case of an emergency, can be notified if someone nearby is having a cardiac emergency and may require CPR. The app also directs these citizen rescuers to the exact location of the closest publicly accessible Automated External Defibrillator (AED).  Find out more about PulsePoint at http://pulsepoint.org/app/

Park went on to explain that the HHS data was a pilot program, and that the results were favorable enough that the White House is now launching sister government data sharing programs for health, energy, education, and nonprofits. More information can be found at data.gov.

No, I am still not convinced that the government is a place that is innovative per se, but Park did convince me that as White House Chief Technology Officer, he is making changes. More importantly, changes that appear to be getting some results.

Why should we be interested in Big Data?

In the last few years, there has been a lot of talk about big data. First, a succinct definition from IBM:

“Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.”  http://www-01.ibm.com/software/data/bigdata/

Of course the real focus isn’t necessarily the big data set itself, but what useful real-time actionable information can be gleaned from the big data set using analytics.

Dataminr, a New York City start-up, through a partnership with Twitter, has access to Twitter’s 340 million tweets per day. Some examples of useful, real-time actionable information that the Dataminr analytics engine has claimed to produce are:

- Detecting Osama Bin Laden’s death 20 minutes before global news media broke the story
- An assassination attempt on an Arab head of state
- Government sanctions against a major international telecommunications company
- A natural disaster in Texas

These are a few examples, from one company, which illustrate how the social media big data set in particular, can potentially provide information to influence: financial markets, government, business, and humanitarian efforts.

In my opinion, applying analytics to big data sets to glean useful real-time actionable information, is in its infancy.  Recently, I have been delving into digital epidemiology and outbreak surveillance. I may post on that topic in the future.