Computers Math

On Earth right now, there are about 10 trillion gigabytes of digital data, and every day, humans produce emails, photos, tweets, and other digital files that add up to another 2.5 million gigabytes of data. Much of this data is stored in enormous facilities known as exabyte data centers (an exabyte is 1 billion gigabytes), which can be the size of several football fields and cost around $1 billion to build and maintain.
Many scientists believe that an alternative solution lies in the molecule that contains our genetic information: DNA, which evolved to store massive quantities of information at very high density. A coffee mug full of DNA could theoretically store all of the world’s data, says Mark Bathe, an MIT professor of biological engineering.
“We need new solutions for storing these massive amounts of data that the world is accumulating, especially the archival data,” says Bathe, who is also an associate member of the Broad Institute of MIT and Harvard. “DNA is a thousandfold denser than even flash memory, and another property that’s interesting is that once you make the DNA polymer, it doesn’t consume any energy. You can write the DNA and then store it forever.”
Scientists have already demonstrated that they can encode images and pages of text as DNA. However, an easy way to pick out the desired file from a mixture of many pieces of DNA will also be needed. Bathe and his colleagues have now demonstrated one way to do that, by encapsulating each data file into a 6-micrometer particle of silica, which is labeled with short DNA sequences that reveal the contents.
Using this approach, the researchers demonstrated that they could accurately pull out individual images stored as DNA sequences from a set of 20 images. Given the number of possible labels that could be used, this approach could scale up to 1020 files.
Bathe is the senior author of the study, which appears today in Nature Materials. The lead authors of the paper are MIT senior postdoc James Banal, former MIT research associate Tyson Shepherd, and MIT graduate student Joseph Berleant. More

The 30,000 or so genes making up the human genome contain the instructions vital to life. Yet each of our cells expresses only a subset of these genes in their daily functioning. The difference between a heart cell and a liver cell, for example, is determined by which genes are expressed — and the correct expression of genes can mean the difference between health and disease.
Until recently, researchers investigating the genes underlying disease have been limited because traditional imaging techniques only allow for the study of a handful of genes at a time.
A new technique developed by Jun Hee Lee, Ph.D., and his team at the University of Michigan Medical School, part of Michigan Medicine, uses high-throughput sequencing, instead of a microscope, to obtain ultra-high-resolution images of gene expression from a tissue slide. The technology, which they call Seq-Scope, enables a researcher to see every gene expressed, as well single cells and structures within those cells, at incredibly high resolution: 0.6 micrometers or 66 times smaller than a human hair — beating current methods by multiple orders of magnitude.
“Whenever a pathologist gets a tissue sample, they stain it and look at it under the microscope — it’s how they diagnose disease,” explained Lee, an associate professor in the Department of Molecular & Integrative Physiology. “Instead of doing that, with our new method, we have made a microdevice that you can overlay with a tissue sample and sequence everything within it with a barcode with spatial coordinates.”
Each so-called barcode is made up of a nucleotide sequence — the pattern of A, T, G, an C — found in DNA. Using these barcodes, a computer is able to locate every gene within a tissue sample, creating a Google-like database of all of the mRNAs transcribed from the genome.
“People have been trying to do this with other methods, such as microprinting, microbeads or microfluidic devices, but because of technological limitations, their resolution has been a distance of 20-100 micrometers. At that resolution you can’t really see the level of detail needed to diagnose diseases,” Lee said.
Lee adds that the technology has the potential to create an unbiased systematic way to analyze genes.
“Whenever we do science, we had to make a hypothesis about the role of two or three genes, but now we have genome-wide data at the microscopic scale and much more knowledge about what’s going on inside that patient or model animal’s tissue.”
This knowledge could be used to provide insight into why certain patients respond to certain drugs while others do not, said Lee.
The team demonstrated the effectiveness of the technique using normal and diseased liver cells, successfully identifying dying liver cells, their surrounding inflamed immune cells and liver cells with altered gene expression.
“This technology actually showed many known pathological features that people have previously discovered but also many genes that are regulated in a novel way that was unrecognized previously,” said Lee. “Seq-Scope technology, combined with other single cell RNA sequencing techniques, could accelerate scientific discoveries and might lead to a new paradigm in molecular diagnosis.”
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Materials provided by Michigan Medicine – University of Michigan. Original written by Kelly Malcom. Note: Content may be edited for style and length. More

Organic semiconductors have earned a reputation as energy efficient materials in organic light emitting diodes (OLEDs) that are employed in large area displays. In these and in other applications, such as solar cells, a key parameter is the energy gap between electronic states. It determines the wavelength of the light that is emitted or absorbed. The continuous adjustability of this energy gap is desirable. Indeed, for inorganic materials an appropriate method already exists — the so-called blending. It is based on engineering the band gap by substituting atoms in the material. This allows for a continuous tunability as, for example in aluminum gallium arsenide semiconductors. Unfortunately, this is not transferable to organic semiconductors because of their different physical characteristics and their molecule-based construction paradigm, thus making continuous band gap tuning much more difficult.
However, with their latest publication scientists at the Center for Advancing Electronics Dresden (cfaed, TU Dresden) and at the Cluster of Excellence “e-conversion” at TU Munich together with partners from University of Würzburg, HU Berlin, and Ulm University for the first time realized energy-gap engineering for organic semiconductors by blending.
For inorganic semiconductors, the energy levels can be shifted towards one another by atomic substitutions, thus reducing the band gap (“band-gap engineering”). In contrast, band structure modifications by blending organic materials can only shift the energy levels concertedly either up or down. This is due to the strong Coulomb effects that can be exploited in organic materials, but this has no effect on the gap. “It would be very interesting to also change the gap of organic materials by blending, to avoid the lengthy synthesis of new molecules,” says Prof. Karl Leo from TU Dresden.
The researchers now found an unconventional way by blending the material with mixtures of similar molecules that are different in size. “The key finding is that all molecules arrange in specific patterns that are allowed by their molecular shape and size,” explains Frank Ortmann, a professor at TU Munich and group leader at the Center for Advancing Electronics Dresden (cfaed, TU Dresden). “This induces the desired change in the material´s dielectric constant and gap energy.”
The group of Frank Ortmann was able to clarify the mechanism by simulating the structures of the blended films and their electronic and dielectric properties. A corresponding change in the molecular packing depending on the shape of the blended molecules was confirmed by X-ray scattering measurements, performed by the Organic Devices Group of Prof. Stefan Mannsfeld at cfaed. The core experimental and device work was done by Katrin Ortstein and her colleagues at the group of Prof. Karl Leo, TU Dresden.
The results of this study have just been published in the journal Nature Materials. While this proves the feasibility of this type of energy-level engineering strategy, its employment will be explored for optoelectronic devices in the future.
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Materials provided by Technische Universität Dresden. Note: Content may be edited for style and length. More

Humans expect that AI is Benevolent and trustworthy. A new study reveals that at the same time humans are unwilling to cooperate and compromise with machines. They even exploit them.
Picture yourself driving on a narrow road in the near future when suddenly another car emerges from a bend ahead. It is a self-driving car with no passengers inside. Will you push forth and assert your right of way, or give way to let it pass? At present, most of us behave kindly in such situations involving other humans. Will we show that same kindness towards autonomous vehicles?
Using methods from behavioural game theory, an international team of researchers at LMU and the University of London have conducted large-scale online studies to see whether people would behave as cooperatively with artificial intelligence (AI) systems as they do with fellow humans.
Cooperation holds a society together. It often requires us to compromise with others and to accept the risk that they let us down. Traffic is a good example. We lose a bit of time when we let other people pass in front of us and are outraged when others fail to reciprocate our kindness. Will we do the same with machines?
Exploiting the machine without guilt
The study which is published in the journal iScience found that, upon first encounter, people have the same level of trust toward AI as for human: most expect to meet someone who is ready to cooperate. More

High-speed internet access has gone from an amenity to a necessity for working and learning from home, and the COVID-19 pandemic has more clearly revealed the disadvantages for American households that lack a broadband connection.
To tackle this problem, Michigan State University researchers have developed a new tool to smooth the collection of federal broadband access data that helps pinpoint coverage gaps across the U.S. The research was published May 26 In the journal PLOS ONE.
“Nearly 21% of students in urban areas are without at-home broadband, while 25% and 37% lack at-home broadband in suburban and rural areas,” said Elizabeth A. Mack, associate professor in the Department of Geography, Environment, and Spatial Sciences in the College of Social Science.
“As more of our day-to-day activities continue to move online, including education, commerce and health care, it’s essential that we understand where gaps in digital infrastructure exist. This is especially important if we want to address disparities in access related to demographics, socioeconomic status, and educational attainment,” she said.
When the U.S. Congress first passed the Telecommunications Act of 1996, the goal was to encourage competition in the telecommunications industry while improving the quality of service and lowering customer prices. To determine the act’s effectiveness, the Federal Communications Commission created a standardized form (Form 477) where twice a year, internet service providers are required to report where they provide service to residential and business customers.
“To date, Form 477 data remains the best publicly available data source regarding broadband deployment,” said Scott Loveridge, a professor in the Department of Agricultural, Food, and Resource Economics (AFRE). “Unfortunately, there are a lot of nuances to these data which to this point have prevented us from conducting useful analyses over time.”
One of these nuances is that the data collected from 2008 to 2018 spans the two census reporting periods of 2000 and 2010. This has made it difficult to look at the data overall and align it with the shifting census geographies, which do change each census year.
Loveridge, Mack and John Mann, an assistant professor with the Center for Economic Analysis, and several other researchers at the University of Texas and Arizona State University, worked together to produce a new dataset that resolves some of these issues by linking the breaks in the Form 477 data into a continuous timeline and aligning the data to the 2010 census.
“We developed a procedure for using the data to produce an integrated broadband time series,” Mann said. “The team has labeled the dataset BITS, which stands for a Broadband Integrated Time Series.”
“We hope these (BITS) data will be a tool to diagnosing gaps in broadband availability to help close the digital divide and enhance the participation of all people in online activities,” Mack said. “With shrinking public budgets and a need to pinpoint locations suffering from a chronic shortage of broadband, it is critical for policymakers to efficiently allocate the human, infrastructural and policy resources required to improve local conditions.”
This work was funded in part by a grant from the U.S. Department of Agriculture to examine broadband availability and its impact on business in rural and tribal areas.
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Materials provided by Michigan State University. Original written by Emilie Lorditch. Note: Content may be edited for style and length. More

People often think about human behavior in terms of what is happening in the present — reading a newspaper, driving a car, or catching a football. But other dimensions of behavior extend over weeks, months, and years.
Examples include a child learning how to read; an athlete recovering from a concussion; or a person turning 50 and wondering where all the time has gone. These are not changes that people perceive on a day-to-day basis. They just suddenly realize they’re older, healed, or have a new development skill.
“The field of neuroscience looks at the brain in multiple ways,” says Franco Pestilli, a neuroscientist at The University of Texas at Austin (UT Austin). “For example, we’re interested in how neurons compute and allow us to quickly react — it’s a fast response requiring visual attention and motor control. Understanding the brain needs big data to capture all dimensions of human behavior.”
As an expert in vision science, neuroinformatics, brain imaging, computational neuroscience, and data science, Pestilli’s research has advanced the understanding of human cognition and brain networks over the last 15 years.
Pestilli likes to compare the brain to the Internet, a powerful set of computers connected by cables simultaneously keeping many windows open and programs running. If the computer is healthy but the cables are not, long range communication between computers in different parts of the brain begins to fail. This in turn creates problems for our long-term behavior.
Pestilli and team are also interested in how biological computations change over longer time periods — such as how does our brain change as we lose our vision? More

Researchers from North Carolina State University have turned a longstanding challenge in DNA data storage into a tool, using it to offer users previews of stored data files — such as thumbnail versions of image files.
DNA data storage is an attractive technology because it has the potential to store a tremendous amount of data in a small package, it can store that data for a long time, and it does so in an energy-efficient way. However, until now, it wasn’t possible to preview the data in a file stored as DNA — if you wanted to know what a file was, you had to “open” the entire file.
“The advantage to our technique is that it is more efficient in terms of time and money,” says Kyle Tomek, lead author of a paper on the work and a Ph.D. student at NC State. “If you are not sure which file has the data you want, you don’t have to sequence all of the DNA in all of the potential files. Instead, you can sequence much smaller portions of the DNA files to serve as previews.”
Here’s a quick overview of how this works.
Users “name” their data files by attaching sequences of DNA called primer-binding sequences to the ends of DNA strands that are storing information. To identify and extract a given file, most systems use polymerase chain reaction (PCR). Specifically, they use a small DNA primer that matches the corresponding primer-binding sequence to identify the DNA strands containing the file you want. The system then uses PCR to make lots of copies of the relevant DNA strands, then sequences the entire sample. Because the process makes numerous copies of the targeted DNA strands, the signal of the targeted strands is stronger than the rest of the sample, making it possible to identify the targeted DNA sequence and read the file.
However, one challenge that DNA data storage researchers have grappled with is that if two or more files have similar file names, the PCR will inadvertently copy pieces of multiple data files. As a result, users have to give files very distinct names to avoid getting messy data. More

In a major scientific leap, University of Queensland researchers have created a quantum microscope that can reveal biological structures that would otherwise be impossible to see.
This paves the way for applications in biotechnology, and could extend far beyond this into areas ranging from navigation to medical imaging.
The microscope is powered by the science of quantum entanglement, an effect Einstein described as “spooky interactions at a distance.”
Professor Warwick Bowen, from UQ’s Quantum Optics Lab and the ARC Centre of Excellence for Engineered Quantum Systems (EQUS), said it was the first entanglement-based sensor with performance beyond the best possible existing technology.
“This breakthrough will spark all sorts of new technologies — from better navigation systems to better MRI machines, you name it,” Professor Bowen said.
“Entanglement is thought to lie at the heart of a quantum revolution. More