New Device May Revolutionize Computer Memory

Traditionally, there are two types of computer memory devices. Slow memory devices are used in persistent data storage technologies such as flash drives. They allow us to save information for extended periods of time, and are therefore called nonvolatile devices. Fast memory devices allow our computers to operate quickly, but aren't able to save data when the computers are turned off. The necessity for a constant source of power makes them volatile devices.

But now a research team from NC State has developed a single"unified" device that can perform both volatile and nonvolatile memory operation and may be used in the main memory.

"We've invented a new device that may revolutionize computer memory," says Dr. Paul Franzon, a professor of electrical and computer engineering at NC State and co-author of a paper describing the research."Our device is called a double floating-gate field effect transistor (FET). Existing nonvolatile memory used in data storage devices utilizes a single floating gate, which stores charge in the floating gate to signify a 1 or 0 in the device -- or one 'bit' of information. By using two floating gates, the device can store a bit in a nonvolatile mode, and/or it can store a bit in a fast, volatile mode -- like the normal main memory on your computer."

The double floating-gate FET could have a significant impact on a number of computer problems. For example, it would allow computers to start immediately, because the computer wouldn't have to retrieve start-up data from its hard drive -- the data could be stored in its main memory.

The new device would also allow"power proportional computing." For example, Web server farms, such as those used by Google, consume an enormous amount of power -- even when there are low levels of user activity -- in part because the server farms can't turn off the power without affecting their main memory.

"The double floating-gate FET would help solve this problem," Franzon says,"because data could be stored quickly in nonvolatile memory -- and retrieved just as quickly. This would allow portions of the server memory to be turned off during periods of low use without affecting performance."

Franzon also notes that the research team has investigated questions about this technology's reliability, and that they think the device"can have a very long lifetime, when it comes to storing data in the volatile mode."

The paper,"Computing with Novel Floating-Gate Devices," will be published Feb. 10 in IEEE'sComputer. The paper was authored by Franzon; former NC State Ph.D. student Daniel Schinke; former NC State master's student Mihir Shiveshwarkar; and Dr. Neil Di Spigna, a research assistant professor at NC State. The research was funded by the National Science Foundation.

NC State's Department of Electrical and Computer Engineering is part of the university's College of Engineering.

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Data Matrix Codes Used to Catalogue Archaeological Heritage

The marking of archaeological material, or coding, is the process in which archaeologists identify each of the artifacts discovered at a site through an identifier code which is currently applied manually to each item and which contains the name of the site, the archaeological level at which it was found and an inventory number. This information is essential because it remits to a complex network of data which contextualises each artifact individually.

Manual coding is a routine process which requires much time and effort, and in which many errors exists -- in some cases up to 40%. Moreover, with the pass of time the coding becomes unclear and this often may hinder subsequent studies. For this reason an important part of the work done in museums, especially with important artifacts or collection items, consists in recoding the objects.

The CEPAP team has achieved to reduce coding errors to 1% by applying a new digital cataloguing system used in several dig sites to register all types of collections.

To identify each object DM codes are applied directly to the objects. The codes adapt in proportion to the size of the identified artifact, up to a minimum of 3x3 millimetres. There are many advantages when these codes are compared to bar codes, a registry system which in past years was tested in different archaeological projects. Due to their size, in many cases bar codes cannot be applied directly to the objects and must be adhered to the bag containing the artifact. This however easily can give way to errors during the manipulation of the objects.

DM codes are printed with a program CEPAP designed for the firm IWS (Internet Web Serveis), one of the project collaborators, which makes it possible to introduce alphanumeric sequences, forming series with up to 20 digits to identify each of the objects.

Printed on polypropylene labels, the codes are adhered to the artifacts by first placing them between two layers of Paraloid B72, an acrylic resin widely used in restoration of archaeological material because of its durability and long-term protection of the label. If the label is damaged -- up to 30% of the code -- the information can be reprinted fully.

Each archaeological object contains an identifier code (site, archaeological unit and sequential name). The information of each code can be read using standard readers, video and photo cameras, mobile phone readers, etc. The data includes georeferenced information of the artifacts found at the sites and which are taken with a laser theodolite, as well as several quantitative or qualitative variables which are stored in electronic notebooks or PDAs. Therefore, every day when data is stored in the computer, archaeologists have access to an exhaustive and updated field inventory which includes all of the most recent findings. The program can design and modify quantitative and qualitative variables according to the precise needs of each research project.

In addition to representing a new technology application, the system offers other important advantages. The pilot project carried out in Spanish sites (Roca dels Bous and Cova Gran de Santa Linya in Lleida) and African sites (Olduvai Gorge in Tanzania and Mieso in Ethiopia) was directed by Dr Rafael Mora, director of the Centre and lecturer of Prehistory at UAB; Dr Paloma González and Dr Jorge Martínez Moreno. The new system demonstrates substantial advantages when compared to manual coding in terms of speed and reliability, as well as its easy incorporation into everyday archaeological research tasks.

That is why CEPAP researchers find it important for scientists and heritage managers in Spain to consider the possibility of adapting a unique automated registry and cataloguing system for archaeological material, relatively easy to use and fairly economical, which would allow to unify systems which are currently differentiated. At the same time it would give way to the development of digital applications such as data consultation via internet through databases combining DM code information and visual representations (drawings, photos or 3D scans), and cyberspace access to museum pieces, which would make it easier for both researchers and society in general to have access to cultural heritages.

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Improving Plants: New Software Quantifies Leaf Venation Networks, Enables Plant Biology Advances

To help address the challenge of how to quickly examine a large quantity of leaves, researchers at the Georgia Institute of Technology have developed a user-assisted software tool that extracts macroscopic vein structures directly from leaf images.

"The software can be used to help identify genes responsible for key leaf venation network traits and to test ecological and evolutionary hypotheses regarding the structure and function of leaf venation networks," said Joshua Weitz, an assistant professor in the Georgia Tech School of Biology.

The program, called Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI), enables scientists and breeders to measure the properties of thousands of veins much more quickly than manual image analysis tools.

Details of the LEAF GUI software program were published in the"Breakthrough Technologies" section of the January issue of the journalPlant Physiology. Development of the software, which is available for download atwww.leafgui.org, was supported by the Defense Advanced Research Projects Agency (DARPA) and the Burroughs Welcome Fund.

LEAF GUI is a user-assisted software tool that takes an image of a leaf and, following a series of interactive steps to clean up the image, returns information on the structure of that leaf's vein networks. Structural measurements include the dimensions, position and connectivity of all network veins, and the dimensions, shape and position of all non-vein areas, called areoles.

"The network extraction algorithms in LEAF GUI enable users with no technical expertise in image analysis to quantify the geometry of entire leaf networks -- overcoming what was previously a difficult task due to the size and complexity of leaf venation patterns," said the paper's lead author Charles Price, who worked on the project as a postdoctoral fellow at Georgia Tech. Price is now an assistant professor of plant biology at the University of Western Australia.

While the Georgia Tech research team is currently using the software to extract network and areole information from leaves imaged under a wide range of conditions, LEAF GUI could also be used for other purposes, such as leaf classification and description.

"Because the software and the underlying code are freely available, other investigators have the option of modifying methods as necessary to answer specific questions or improve upon current approaches," said Price.

LEAF GUI is not the only software program Weitz's group has developed to investigate the network characteristics of plants. In March 2010, Weitz's group co-authored another"Breakthrough Technologies" paper inPlant Physiologydetailing a way to analyze the complex root network structure of crop plants, with a focus on rice.

This work was performed in collaboration with Anjali Iyer-Pascuzzi, John Harer and Philip Benfey at Duke University and was supported by DARPA, the National Science Foundation and the Burroughs Welcome Fund.

"Both of these software programs are enabling tools in the growing field of 'plant phenomics,' which aims to correlate gene function, plant performance and response to the environment," noted Weitz."By identifying leaf vein characteristics and root structures that differ between plants, we are enabling advances in basic plant science and, in the case of crop plants, assisting researchers in identifying and potentially altering genes to improve plant health, yield and survival."

In addition to those already mentioned, Olga Symonova, Yuriy Mileyko and Troy Hilley also contributed to this work at Georgia Tech.

These projects were supported by the Defense Advanced Research Projects Agency (DARPA) (Award No. HR0011-05-1-0057), National Science Foundation (NSF Plant Genome Research Program Award Nos. 0606873 and 0820624) and Burroughs Wellcome Fund (BWF). The content is solely the responsibility of the principal investigator and does not necessarily represent the official views of DARPA, NSF or BWF.

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Fruit Fly Nervous System Provides New Solution to Fundamental Computer Network Problem

With a minimum of communication and without advance knowledge of how they are connected with each other, the cells in the fly's developing nervous system manage to organize themselves so that a small number of cells serve as leaders that provide direct connections with every other nerve cell, said author Ziv Bar-Joseph, associate professor of machine learning at Carnegie Mellon University.

The result, the researchers report in the Jan. 14 edition of the journalScience, is the same sort of scheme used to manage the distributed computer networks that perform such everyday tasks as searching the Web or controlling an airplane in flight. But the method used by the fly's nervous system to organize itself is much simpler and more robust than anything humans have concocted.

"It is such a simple and intuitive solution, I can't believe we did not think of this 25 years ago," said co-author Noga Alon, a mathematician and computer scientist at Tel Aviv University and the Institute for Advanced Study in Princeton, N.J.

Bar-Joseph, Alon and their co-authors -- Yehuda Afek of Tel Aviv University and Naama Barkai, Eran Hornstein and Omer Barad of the Weizmann Institute of Science in Rehovot, Israel -- used the insights gained from fruit flies to design a new distributed computing algorithm. They found it has qualities that make it particularly well suited for networks in which the number and position of the nodes is not completely certain. These include wireless sensor networks, such as environmental monitoring, where sensors are dispersed in a lake or waterway, or systems for controlling swarms of robots.

"Computational and mathematical models have long been used by scientists to analyze biological systems," said Bar-Joseph, a member of the Lane Center for Computational Biology in Carnegie Mellon's School of Computer Science."Here we've reversed the strategy, studying a biological system to solve a long-standing computer science problem."

Today's large-scale computer systems and the nervous system of a fly both take a distributive approach to performing tasks. Though the thousands or even millions of processors in a computing system and the millions of cells in a fly's nervous system must work together to complete a task, none of the elements need to have complete knowledge of what's going on, and the systems must function despite failures by individual elements.

In the computing world, one step toward creating this distributive system is to find a small set of processors that can be used to rapidly communicate with the rest of the processors in the network -- what graph theorists call a maximal independent set (MIS). Every processor in such a network is either a leader (a member of the MIS) or is connected to a leader, but the leaders are not interconnected.

A similar arrangement occurs in the fruit fly, which uses tiny bristles to sense the outside world. Each bristle develops from a nerve cell, called a sensory organ precursor (SOP), which connects to adjoining nerve cells, but does not connect with other SOPs.

For three decades, computer scientists have puzzled over how processors in a network can best elect an MIS. The common solutions use a probabilistic method -- similar to rolling dice -- in which some processors identify themselves as leaders, based in part on how many connections they have with other processors. Processors connected to these self-selected leaders take themselves out of the running and, in subsequent rounds, additional processors self-select themselves and the processors connected to them take themselves out of the running. At each round, the chances of any processor joining the MIS (becoming a leader) increases as a function of the number of its connections.

This selection process is rapid, Bar-Joseph said, but it entails lots of complicated messages being sent back and forth across the network, and it requires that all of the processors know in advance how they are connected in the network. That can be a problem for applications such as wireless sensor networks, where sensors might be distributed randomly and all might not be within communication range of each other.

During the larval and pupal stages of a fly's development, the nervous system also uses a probabilistic method to select the cells that will become SOPs. In the fly, however, the cells have no information about how they are connected to each other. As various cells self-select themselves as SOPs, they send out chemical signals to neighboring cells that inhibit those cells from also becoming SOPs. This process continues for three hours, until all of the cells are either SOPs or are neighbors to an SOP, and the fly emerges from the pupal stage.

In the fly, Bar-Joseph noted, the probability that any cell will self-select increases not as a function of connections, as in the typical MIS algorithm for computer networks, but as a function of time. The method does not require advance knowledge of how the cells are arranged. The communication between cells is as simple as can be.

The researchers created a computer algorithm based on the fly's approach and proved that it provides a fast solution to the MIS problem."The run time was slightly greater than current approaches, but the biological approach is efficient and more robust because it doesn't require so many assumptions," Bar-Joseph said."This makes the solution applicable to many more applications."

This research was supported in part by grants from the National Institutes of Health and the National Science Foundation.

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Quantum Quirk Contained

"We have demonstrated, for the first time, that a crystal can store information encoded into entangled quantum states of photons," says paper co-author Dr. Wolfgang Tittel of the University of Calgary's Institute for Quantum Information Science."This discovery constitutes an important milestone on the path toward quantum networks, and will hopefully enable building quantum networks in a few years."

In current communication networks, information is sent through pulses of light moving through optical fibre. The information can be stored on computer hard disks for future use.

Quantum networks operate differently than the networks we use daily.

"What we have is similar but it does not use pulses of light," says Tittel, who is a professor in the Department of Physics and Astronomy at the University of Calgary."In quantum communication, we also have to store and retrieve information. But in our case, the information is encoded into entangled states of photons."

In this state, photons are"entangled," and remain so even when they fly apart. In a way, they communicate with each other even when they are very far apart. The difficulty is getting them to stay put without breaking this fragile quantum link.

To achieve this task, the researchers used a crystal doped with rare-earth ions and cooled it to -270 Celsius. At these temperatures, material properties change and allowed the researchers to store and retrieve these photons without measurable degradation.

An important feature is that this memory device uses almost entirely standard fabrication technologies."The resulting robustness, and the possibility to integrate the memory with current technology such as fibre-optic cables is important when moving the currently fundamental research towards applications."

Quantum networks will allow the sending of information without one being afraid of somebody listening in.

"The results show that entanglement, a quantum physical property that has puzzled philosophers and physicists since almost hundred years, is not as fragile as is generally believed," says Tittel.

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Played by Humans, Scored by Nature, Online Game Helps Unravel Secrets of RNA

The game, called EteRNA harnesses game play to uncover principles for designing molecules of RNA, which biologists believe may be the key regulator of everything that happens in living cells. But the game doesn't end with the highest computer score. Rather, players are scored and ranked based on how well their virtual designs can be rendered as real, physical molecules. Each week's top designs are synthesized in a biochemistry laboratory so researchers can see if the resulting molecules fold themselves into the three-dimensional shapes predicted by computer models.

"Putting a ball through a hoop or drawing a better poker hand is the way we're used to winning games, but in EteRNA you score when the molecule you've designed can assemble itself," said Adrien Treuille, an assistant professor of computer science at Carnegie Mellon, who leads the EteRNA project with Rhiju Das, an assistant professor of biochemistry at Stanford."Nature provides the final score -- and nature is one tough umpire."

Because EteRNA is crowdsourcing the scientific method -- enlisting non-experts to uncover still-mysterious RNA design principles -- it is essential that scoring be rigorous.

"Nature confounds even our best computer models," said Jeehyung Lee, a computer science Ph.D. student at Carnegie Mellon who led the game's development."We knew that if we were to truly tap the wisdom of crowds, our game would have to expose players to every aspect of the scientific process: design, yes, but also experimentation, analysis of results and incorporation of those results into future designs."

The complex, three-dimensional shape of an RNA molecule is critical to its function. The goal of the EteRNA project is to design RNA knots, polyhedra and other shapes never seen before.

"We want to understand how RNA folds in a test tube and eventually in viruses and living cells," Das said."We also want to create a toolkit of basic building blocks that could be used to construct sensors, therapeutic agents and tiny machines."

By synthesizing a design generated by game play, researchers will learn quickly whether the resulting molecule folds into the predicted shape, or something close to it, or if it even folds at all. Even designs that are not synthesized will be scored by nature, in that their scores will be based on the performance of similar designs previously synthesized.

"These experiments are the first-line strategy for validating a design and a crucial part of the scientific method," said Das, whose lab at Stanford synthesizes the molecules."This makes EteRNA similar to what goes on in my lab on a daily basis: You make a prediction, do an experiment, make adjustments and start again." Initially, Das' lab is synthesizing eight designs each week, but is ramping up to synthesize about 100 a week.

RNA, or ribonucleic acid, long has been recognized as a messenger for genetic information, yet its role usually was overshadowed by DNA, which encodes genes, and by proteins, which do the work of the cell. But biologists now suspect RNA plays a much broader role as the regulator of cells, acting much like the operating system of a computer. Understanding RNA design could prove useful for treating or controlling such diseases as HIV, for creating RNA-based sensors and even for building computers out of RNA.

The game employs state-of-the-art simulation software that players use to generate designs. It includes training exercises and challenge puzzles for honing skills, as well as challenges for designing molecules that will be synthesized.

In its use of game play to generate results of scientific interest, EteRNA is similar to other online games such as Foldit, an online protein-folding game that Treuille helped create while at the University of Washington. In fact, Treuille and Das met when they sat at adjacent desks in the Washington biochemistry lab of David Baker, where Treuille was working on Foldit and Das was studying RNA and protein folding and occasionally offering advice.

Both men recognized that the lack of real-world feedback was a limitation of these games. They realized an RNA design game could solve this problem because RNA, unlike many biological molecules, can be readily synthesized in a matter of hours.

RNA consists of long, double strands of four bases -- adenine, guanine, cytosine and uracil -- with the shape determined by the sequence of the bases. The rules controlling shape are relatively simple, but the sheer size of the molecules greatly complicates the design process.

"We've already found it's better not to use regularly repeating sequences of bases because they prove unstable," Treuille said, based on play by beta testers."We're trying to build things that work in nature, and nature favors solutions that are robust."

The game is integrated with Facebook, so players can post accomplishments to their Facebook wall automatically and can create groups that talk about play and compete with each other.

The first challenges are relatively simple, arbitrary shapes, Das said, but will soon begin to incorporate designs of scientific relevance, such as RNA switches that could be used to sense and respond to other molecules in living cells.

Ultimately, players may end up creating designs and making discoveries of their own."They're already beginning to act like a scientific community," Treuille said."One player solved a puzzle that a widely used algorithm could not. Another player has written a strategy guide that proposes an algorithm for solving design problems that is different and simpler than anything in the scientific literature."

The EteRNA project is funded by a grant from the National Science Foundation.

For more information on EterRNA watch these video clips:

• What is the EteRNA game? (1:19)http://wms.andrew.cmu.edu:81/nmvideo/eterna_1.mov
• What have we learned from EteRNA? (1:57)http://wms.andrew.cmu.edu:81/nmvideo/eterna_2.mov 

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