October 2003
http://www.coe.berkeley.edu/labnotes/1003
Commuter-friendly version

Bernhard Boser holds an ImmunoSensor chip. The chips are donated by National Semiconductor and then modified in UC Berkeley's Microfabrication Laboratory. (David Pescovitz photo)

Beginning next summer, a tiny bio-chip developed at UC Berkeley will help researchers in Nicaragua understand and screen for a tropical disease that incapacitates as many as 100 million people each year. Melding microbiology with microcircuitry, the 2 millimeter square ImmunoSensor provides a quick, inexpensive test for the dengue virus, commonly known as "break-bone fever," even when the nearest clinical laboratory may be hundreds of miles away.

"In the third world, there aren't very many specialized labs that can test these blood samples," says co-inventor Bernhard E. Boser, a professor in the Department of Electrical Engineering and Computer Sciences and a researcher with the Center for Information Technology Research in the Interest of Society (CITRIS). "Many regions don't even have the quality of water you need to do traditional tests."

Each ImmunoSensor chip is fabricated using bulk processes similar to the way integrated circuits are manufactured. (courtesy the researchers)

The solution was to put the laboratory right on the chip, at a cost of less than $1 each. In fact, right now Boser and his collaborators--Molecular and Cell Biology professor P. Robert Beatty, professor Eva Harris in the School of Public Health, and their graduate students--are readying 1,000 of the ImmunoSensors to ship to Nicaragua in time for dengue season. Spread by mosquito, the dengue virus causes brutal headaches, intense fever, rashes, and, in infants, the risk of death. The field study is being coordinated by the Sustainable Sciences Institute (SSI), a non-profit organization focused on addressing local problems related to infectious diseases in developing nations.

Currently, diseases like the dengue virus are detected with a test called the Enzyme-Linked Immunosorbent Assay (ELISA), which detects antigens and antibodies in a blood sample. Antibodies are formed by the body in response to antigens -- molecules, often foreign, that the immune system recognizes as threats. For every antigen, there is an antibody that binds to it. It's this biochemical reaction that signals the immune system to start fighting off a disease. With ELISA, an enzyme is added to the sample that activates a visible colored dye in the presence of a particular antigen or antibody.

In lieu of messy enzymes and dyes, the ImmunoSensor employs magnetism and microelectronics. (See illustration.) First, a drop of blood is placed in a micron-scale well on the chip. There, it mixes with tiny micron-scale magnetic beads that are pre-coated with an antibody that bonds to the antigen indicative of a particular disease.

This illustration depicts the how antigens bind to both the magnetic beads and the magnetic sensors, called Hall sensors, on the surface of the chip. (courtesy the researchers)

"If the antigens are in the blood sample, the beads grab onto them," Boser explains.
Then, gravity causes the beads to fall onto a tiny array of 256 magnetic sensors at the bottom of the well. The sensor array is also coated with the particular antibody that binds to the disease antigen. After the beads settle, a magnetic field is applied. Beads that aren't now immobilized by the antigen on the surface of the chip are pulled away from the sensor array.

"We call it magnetic washing," Boser says.

Finally, the sensor array is activated. The electrical resistance of the array corresponds to the number of beads that are stuck on the sensors thanks to the antibody-antigen bond. The detection of immobilized beads mean the particular antigen is present and that the subject whose blood was tested most likely is infected with the dengue virus. The entire process takes little more than a minute. Currently, the chip plugs into a conventional laptop computer running the ImmunoSensor software that provides the data to the person administering the test. The next step, Boser says, is to make the chips wireless and port the software over to a palm computing platform, even further increasing their portability. Meanwhile, Beatty is working to develop an HIV test that would also run on the ImmunoSensor platform.

"You could imagine buckets of these chips, all coated with different antibodies so we can not only detect on-the-spot when someone is ill, but also find out exactly what illness they have," Boser says.

Professor Yoram Rubin is also the president of the International Commission on Ground Water, part of the International Association of Hydrological Sciences.

Between the rows of ripening grapes at the Robert Mondavi Vineyard in Napa Valley, a UC Berkeley researcher pushes a wheelbarrow outfitted with a ground-penetrating radar device. The field trip is part of a project that combines time-tested agricultural methods with high-technology geophysics to improve the quality of Northern California's finest wines.

Yoram Rubin, UC Berkeley professor of Civil and Environmental Engineering, is leading research to map the soil's water content at California vineyards using data generated from high-frequency radar systems. The aim is to give grape growers a tool for managing "stressed irrigation," a technique that keeps the plants a little bit thirsty, resulting in smaller grapes with better flavor rather than larger fruit and leafy vines.

"Our approach is noninvasive. There's no drilling, and we can provide quick and accurate estimates of soil moisture content over large areas," says Rubin, whose principal collaborator on the project is his former student Susan Hubbard, now a staff scientist in Lawrence Berkeley National Laboratory's Earth Science Division. The project is part of the Institute for Environmental Science and Engineering (IESE) and the Center for Information Technology Research in the Interest of Society (CITRIS).

Currently under way at Mondavi and Dehlinger Vineyards, Rubin's field research originated from an earlier study to monitor and understand the transport of bacteria through subsurface soil. Rubin realized that applying a similar noninvasive technique to measure distribution of water in soil could help conserve water resources in agriculture. The trick, however, was finding a receptive audience. Grape growers, he quickly realized, had a lot to gain from knowing what lies beneath the surface of their vineyards.

"If there's one community that's very interested in soil moisture, it's wine grape growers," he says. "Managing stressed irrigation yields higher quality fruit and enables growers to get higher prices."

Susan Hubbard drags a ground-penetrating radar instrument through the Robert Mondavi vineyard in Napa, California. (Mike Kowalsky photo)

To map the subsurface of a vineyard, Hubbard, Rubin, and his graduate students push a vacuum cleaner-sized radar instrument between the vines. The device sends high-frequency electromagnetic waves into the ground to depths of several meters depending on the type of soil being tested. The velocity of the waves' reflection is dependent on the ground's dielectric constant, the ability of a material to store electrical energy under the influence of an electric field. Soil has a low dielectric constant that is dramatically elevated in the presence of water. The signal's travel time is then interpreted as a measurement of soil moisture, much like data from a medical computed tomography (CT) scan provides physicians with information about a patient's tissue properties.

Every vineyard's soil will have different characteristics. At the Dehlinger vineyards, the waves bounce off a natural reflector in the ground-soil layer with significant variation in its electrical properties-and return to the radar's receiver. At Mondavi, there is no natural reflector. Instead, the instrument emits ground waves that travel laterally in a shallow zone of the soil. Depending on their frequency, the waves can penetrate up to one-half meter. The researchers take measurements using multiple frequencies and, combined with other projected data generated by a mathematical model, generate an accurate profile of the moisture around the roots of the vines.

"Once we identify the topology of the field, we can provide just six or so pivot points in a block (approx. 300 meters squared) that the farmers can check biweekly," Rubin says. "Collecting information from those points provides enough data to determine an irrigation schedule."

Firm control over stressed irrigation, Rubin says, also enables grape farmers to create uniform ripening patterns. Rather than return to the same plot multiple times during a harvest, farmers could increase efficiency by collecting all the fruit at one time, he explains. These techniques may provide insight into the biology of the vines as well.

"We'd like to understand which parts of the plant get water from particular soil depths." Rubin says. "For example, do the vines need uniform moisture to thrive?"

To answer these questions, Rubin is currently working on a proposal to collaborate with Todd Dawson, a UC Berkeley professor of Integrative Biology, on the next phase of the vineyard project. The hope is that, by combining the soil moisture profiles with Dawson's isotope analysis, a method used to determine distribution of certain elements in a material, the researchers will be able to produce a high-resolution picture of how the vines drink from the soil.

UC Berkeley civil engineering professor Raja Sengupta

In the near future, fleets of small airplanes may traverse our skies monitoring traffic conditions, collecting data from environmental sensors, and scoping out forest fires. The unusual thing about these aircraft is that their cockpits will be empty. UC Berkeley civil engineering professor Raja Sengupta is leading a College of Engineering project to build intelligent guidance systems for the next generation of unmanned air vehicles (UAVs). In August, Berkeley technology enabled a UAV equipped with machine vision to autonomously navigate a road for the very first time, even in cloudy and rainy weather the researchers ran into at a desert test site.

Sponsored by the Office of Naval Research's (ONR) Autonomous Intelligent Network and Systems (AINS) program, the August demonstration took place on a desert road outside of Tucson, Arizona. Amazingly, Berkeley's effort to outfit UAVs from Advanced Ceramics Research Corp. with machine vision began just four months before the successful demonstration.

Professor Raja Sengupta describes Berkeley's UAV system to Congressman Kurt Weldon at the test site in Arizona. (courtesy the researchers)

Today's UAV are just a few meters in length and can remain aloft for several hours at a time on a small tank of diesel fuel. The aircraft cost approximately $20 thousand each and are outfitted with Global Positioning System (GPS) receivers that provide location information. The user enters GPS waypoints that the UAV uses to get from point to point. According to Sengupta, the problem with GPS is that it's just not smart enough for most real-world applications. Take traffic monitoring, for example.

Earlier this year, Sengupta had been intrigued by demonstrations where UAVs collect freeway traffic data much like manned news helicopters do today. UAVs make sense because they keep people safely on the ground and are less expensive to operate.

"I wondered why these are not commercial systems," says Sengupta, the co-principal investigator of Berkeley's new ONR Center for Collaborative Control of Unmanned Vehicles. "Then I realized that it's very difficult for a UAV to follow a road. GPS errors can cause a UAV to veer off its path quite easily."

The Berkeley team's approach is to augment GPS with machine vision software and a $120 off-the-shelf video camera. The challenge, Sengupta explains, is for the computer to discern the road from the rest of the terrain from altitudes up to several hundred feet.

Unprocessed view of the test road from the UAV camera. Inset shows the result after image processing to find the road and lane boundaries. (courtesy the researchers)

The solution is a two-step process devised by Zu Kim, a researcher with the UC Berkeley-based PATH (Partners for Advanced Transit and Highways) program. First, the software distinguishes the road from the surrounding area based on differences in contrast. In the desert, for instance, the asphalt is much darker than the sand. Next, the lane boundaries are identified based on the lightness of lane markings as compared to the asphalt. Once the boundaries are located, the plane follows the lane from above.

"GPS will get the plane in the vicinity and once our system locks onto the road, the plane can adjust itself regardless of what the GPS says," Sengupta explains.

Following the success outside Tucson, the Berkeley team is attacking two more UAV navigation challenges. The first is obstacle avoidance, historically a tough problem in computer vision. Indeed, another Berkeley research project is focused on a vision system for trains that detects any obstacle on the tracks, a car or pedestrian for example, and alerts the engineer in time to avoid a collision. Sengupta hopes to adapt the same technology, based on computing a depth map of what the camera sees, to air vehicles so that they may steer around them and then quickly return to their original flight path.

The final prong in the Berkeley UAV research is focused on what Sengupta calls the "canyon problem." While monitoring traffic in an urban setting, a UAV may be forced to fly between buildings lining the road it's tracking. One intriguing solution was inspired by the navigation of bees. The insects are able to fly down a corridor without bouncing between the walls by determining if they seem to be moving past both walls at the same rate. If there's a discrepancy between walls, the bee adjusts its trajectory. Sengupta hopes that borrowing this biological principle behind bee flight will lead to a computationally quick way to deal with "urban canyons."

Solving all three problems could open up an entire realm of UAV applications far beyond traffic monitoring. Sengupta envisions environmental scientists periodically deploying UAVs to wirelessly gather data from remote environmental sensors--in forest canopies or marine areas for example--that can only transmit short distances due to limited battery power. UAVs could also safely and untiringly patrol forest canopies, enabling early-stage fires to be quickly detected and quenched before they blaze out of control.

"Our first test was a success because of the amazing students from civil and mechanical engineering who worked in the desert for three weeks in 120 degree heat getting the thing to fly," Sengupta says. "Now we've reached a critical mass and the ideas and applications are really bubbling up."

UC Berkeley professor Theodore E. Cohn's research may lead to better signals at railroad crossings.

Each year, approximately 400 people die trying to beat an oncoming train at railroad crossings. More than 1,000 others are injured. Why is it that so many people misjudge the speed of an oncoming train? That's the question Theodore E. Cohn, a Berkeley professor of vision science and bioengineering, hopes to answer. Understanding why people think they can win the race at railways, Cohn says, may lead to better signals that prevent drivers from thinking they're faster than a locomotive.

"In 1985, the theory was presented that we underestimate the speed of large objects," says Cohn, a researcher with PATH (Partners for Advanced Transit and Highways). "We're finally testing that idea for the first time."

To conduct their preliminary experiments, Cohn and his students created a computer-based laboratory test that didn't require any moving objects. In the study, each subject sees a square, grey box on a computer screen. The subject is instructed to hit a button the moment he or she notices the box begins to expand.

"The expansion of an object in your field of view is a cue your brain uses to determine how rapidly the object is moving toward you," Cohn says.

The geometry that links an object's expansion to our estimation of its speed was first described by astronomer and writer Sir Fred Hoyle in his 1957 science fiction novel The Black Cloud. As it turns out, Cohn's experiments revealed that the bigger an object is when you first see it, the longer it takes you to notice it change.

"That makes us think that an object may be approaching much more slowly than it really is," Cohn says.

Of course, the rate of expansion is not the only factor humans use to determine the speed of an oncoming object. Stereopsis, our binocular perception of depth, also helps us determine how close something is to us. The problem, Cohn says, is that stereopsis isn't very effective at distances of more than 10 meters.

"That's a problem when you're following a vehicle in traffic," Cohn says. "Interestingly, buses are rear-ended more often than cars and they're bigger. So we'd like to see if that's the case with trucks as well."

After the laboratory experiments are complete, the researchers will begin real-world tests to determine whether it is indeed a vehicle's large size that causes drivers to misjudge its speed. For example, Cohn and his students will compare their subjects' ability to estimate the speed of an approaching train compared to other smaller vehicles that travel along the railways.

Eventually, Cohn hopes his research could inform the design of new signal lights for trains. Currently, trains feature a triangle of headlights on their front ends. The approach is designed to give the onlooker a sense of the speed of the train based on how fast the triangle of light seems to be expanding. The irony, Cohn explains, is that the lights are too bright to look at them for the length of time necessary for the brain to process the information.

One system the researchers are considering entails nested rings of lights that are visible but not blinding. The system is similar to Cohn's Bus Bar, an advanced warning signal optimized to take advantage of the fastest pathways in a human's visual nervous system. Beginning at the center, each ring in the train signal light would flash on sequentially at a speed based on the velocity of the train.

" The lights would appear to be getting bigger faster than they should, given what you estimate the speed of the train to be," Cohn says. "That way, maybe we can compensate for our misestimation of the speed of large objects."

Along with devising new signaling systems, the researchers are conducting experiments to determine where our attention is focused when looking at an approaching object.

"This may give us a clue where we might place signals or markings on vehicles to prevent collisions," Cohn says.

Professor Michael Stonebraker, UC Berkeley Electrical Engineering and Computer Science

At the dawn of the digital age in the 1960s, large corporations began to migrate from paper records to digital files. The problem was that there was no easy way to find what you were looking for in the massive amounts of data stored. In the mid-1970s, UC Berkeley engineers pioneered a system to organize and access data that, in turn, spawned a $7 billion dollar industry now driven by companies like Oracle, Microsoft and IBM.

In 1970, IBM researcher E. F. Codd published a seminal paper outlining a novel way to organize and access data. Codd's "relational model of data for large shared data banks" called for information to be stored in tables that could be searched using a high-level language. Instead of searching through one record at a time, the user could specify a single query that would be performed across all of the data. For example, the new approach would enable car companies to instantly calculate how many cars of a specific model were sold in a particular geographic region during a given month.

IBM set out to develop a prototype system that would demonstrate Codd's idea. Simultaneously, Michael Stonebraker, a young professor of Electrical Engineering and Computer Sciences at UC Berkeley, was searching for a research project that would earn him tenure. He found it with relational databases.

Collaborating with professor Eugene Wong, Stonebraker began developing a relational data system called INGRES (Interactive Graphics and Retrieval System). Inspired by Codd's publications, Wong, Stonebraker and graduate student Jerry Held turned INGRES into a working system that could satisfy the needs of an urban systems project, led by Professor Pravin Varaiya.

Unlike IBM's similar System R project, the constantly-evolving INGRES code was freely available to users outside the University who wanted to experiment with the system themselves and offer suggestions. INGRES was an early example of the University's commitment to what's now called Open Source software distribution.

While still teaching at Berkeley, Stonebraker founded Ingres Corp. to commercialize the relational database technology. (The company was acquired in 1990 by ASK Computer Systems.) Shortly after launching Ingres Corp., Stonebraker and his students pushed databases ahead yet again with POSTGRES, a relational database that could understand "objects," groups of simpler pieces of data. POSTGRES, now known as PostgreSQL, is considered the most advanced open-source database available today. While at Berkeley, Stonebraker also developed Mariposa, the federated data system.

In August 1992, Stonebraker founded Illustra Information Technologies to commercialize POSTGRES and four years later joined database giant Informix Corporation as its CTO after the company acquired Illustra. He retired from UC Berkeley in 2000 and is currently an adjunct professor of computer science at MIT.

Held spent 18 years as an executive at Tandem Computers before managing the world's largest enterprise software business as a Senior Vice President at Oracle. He's now CEO of the Held Group, a venture capital firm.

Wong, a UC Berkeley professor emeritus of electrical engineering and computer sciences, served as head of the National Science Foundation's engineering directorate and Chairman of the Government of Hong Kong's Council of Advisers on Innovation and Technology. Last fall, he became CEO of Versata Inc., an Oakland-based business software and services company.

Evident in systems from Microsoft's SQL Server to FileMaker, the work of these Berkeley researchers provided us with the tools to harness the power of digital data in all its myriad forms.

Enrollment in UC Berkeley’s Pioneering Management of Technology Program Continues To Grow Original article: CITRIS Exports Education Through Distance Learning (CITRIS Newsletter, April 2003) http://www.citris.berkeley.edu/applications/education/distance_education.html Enrollment in UC Berkeley's Management of Technology (MOT) program continues to soar at a rate of about 20 percent year over the past three years. The MOT Program, a joint effort of the College of Engineering, the Haas School of Business, and the School of Information Management and Systems is designed to immerse students in the business of technology to prime them for success in industry. "With over 1,400 enrollments and 50 MOT courses, Berkeley's MOT program is by far the largest program of its type in the US," says Andrew Isaacs, executive director of MOT. In September, MOT co-sponsored the Haas School of Business's sixth annual Leading Edge Technology Conference, bringing together students, business leaders, entrepreneurs, technologists, and academics in an open forum to present and debate the technologies that are reshaping the marketplace of today and tomorrow. This year's keynote address was delivered by W.J. (Jerry) Sanders III, founder and Chairman of the Board of Advanced Micro Devices, Inc., a leading US-based seminconductor manufacturer. Meanwhile, each year the MOT lecture series brings a stellar line-up of speakers to the UC Berkeley campus to share their insights and experiences in the technology industry. This fall's line up includes: October 22: Jean Paul Jacob, technology evangelist at IBM October 29: Aart de Geus, founder and chairman of Synopsys November 5: Don Proctor, vice president of marketing at Cisco Systems November 12: Bud Tribble, chief technology officer for Apple Computer November 19: Kim Polese, founder of Marimba