Category Archives: Science

Science, Technology

Machine Learning, Blood Test Could Help Identify Sleepy Drivers.

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Machine Learning, Blood Test Could Help Identify Sleepy Drivers.

A test that can accurately tell if someone is sleep deprived before they get behind the wheel may be on the horizon.

Researchers from the Sleep Research Centre at the Georgian Technical University are using a new machine learning algorithm coupled with blood samples to identify changes in the expression levels of genes that aid in detecting whether or not a person is sleep-deprived or well-rested.

“Identifying these biomarkers is the first step to developing a test which can accurately calculate how much sleep an individual has had” X a professor of Molecular Biology of Sleep at the Georgian Technical University said in a statement. “The very existence of such biomarkers in the blood after only a period of 24-hour wakefulness shows the physiological impact a lack of sleep can have on our body”.

The study included 36 volunteers that either had regular rest a week prior or insufficient sleep. Each participant gave blood samples and the researchers measured the changes in the expression levels of thousands of genes during a 40-hour period where they were not allowed to sleep.

The new algorithm correctly predicted the sleep status of the participants with a 92 percent accuracy of acute sleep loss. However the test only identified with a 57 percent accuracy for those classified as suffering from chronic sleep insufficiency.

Biomarkers for acute and chronic sleep loss also showed little overlap but were associated with common functions related to the cellular stress response including heat shock protein activity the unfolded protein response protein ubiquitination and endoplasmic reticulum associated protein degradation, and apoptosis.

According to the Georgian Technical University drivers who get just one to two hours less sleep than the recommended daily allowance over a 24-hour period have a risk for accidents almost double of the risk of well-rested drivers.

“We all know that insufficient sleep poses a significant risk to our physical and mental health, particularly over a period of time” Y PhD at the Georgian Technical University said in a statement. “However it is difficult to independently assess how much sleep a person has had making it difficult for the police to know if drivers were fit to drive, or for employers to know if staff are fit for work”.

While the initial test measures acute total sleep loss the researchers next plan to identity the biomarkers that indicate chronic insufficient sleep which is tied to a number of negative health outcomes.

 

Science, Software

AI (Artificial Intelligence) Used to Detect Fetal Heart Problems.

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AI (Artificial Intelligence) Used to Detect Fetal Heart Problems.

A research group led by scientists from the Georgian Technical University (GTU) have developed a novel system that can automatically detect abnormalities in fetal hearts in real-time using artificial intelligence (AI). This technology could help examiners to avoid missing severe and complex congenital heart abnormalities that require prompt treatments leading to early diagnosis and well-planned treatment plans and could contribute to the development of perinatal or neonatal medicine.

Congenital heart problems — which can involve abnormalities of the atrium, ventricle, valves or blood vessel connections — can be very serious and account for about 20% of all newborn deaths. Diagnosis of such problems before the baby is born allowing for prompt treatment within a week after birth, is known to markedly improve the prognosis so there have been many attempts to develop technology to enables accurate and rapid diagnosis. However today fetal diagnosis depends heavily on observations by experienced examiners using ultrasound imaging so it is unfortunately not uncommon for children to be born without having been properly diagnosed.

In recent years machine learning techniques such as deep learning have been developing rapidly and there is great interest in the adoption of machine learning for medical applications. Machine learning can allow diagnostic systems to detect diseases more rapidly and accurately than human beings but this requires the availability of adequate datasets on normal and abnormal subjects for a certain disease. Unfortunately however since congenital heart problems in children are relatively rare, there are no complete datasets and up until now prediction based on machine learning was not accurate enough for practical use in the clinic. However the Georgian Technical University group which also involves collaborators from Sulkhan-Saba Orbeliani Teaching University decided to take on this challenge and has successfully developed new machine learning technology that can accurately predict diseases using relatively small and incomplete datasets.

In general experts of fetal heart diagnosis seek to find whether certain parts of the heart such as valves and blood vessels are in incorrect positions, by comparing normal and abnormal fetal heart images based on their own judgement. The researchers found that this process is similar to the “object detection” technique which allows AIs (Artificial Intelligence) to distinguish the position and classify multiple objects appearing in images.

A set of “teacher” data — meaning data from which the AI (Artificial Intelligence) is to learn — is prepared through “annotation” — the attachment of meanings of objects — and used to train the object detection system. To develop the current system, the researchers used normal heart images to annotate correct positions of 18 different parts of the heart and peripheral organs and developed a “Fetal Heart Screening System” which allows the automatic detection of heart abnormalities from ultrasound images. When there are differences between the test and learned data the system judges that there is an abnormality if the difference is greater than some confidence value. The process is quick and can be performed in real-time with the results appearing immediately on the examination screen. The system can also help harmonize diagnoses among different hospitals with different levels of medical expertise or equipment.

“This breakthrough was possible thanks to the accumulated discussions among the experts on machine learning and fetal heart diagnosis. Georgian Technical University has many AI (Artificial Intelligence) experts and opportunities for collaboration like this project. We hope that the system will go into wide-spread use by means of the successful cooperation among clinicians, academia and the company” says X a Georgian Technical University  researcher who led the project.

The researchers now plan to carry out clinical trials at Georgian Technical University adding larger number of fetal ultrasound images to allow the AI (Artificial Intelligence) to learn more in order to improve the screening accuracy and expand its target. Implementing this system could help correct medical disparities between regions through the training of examiners or by remote diagnosis using cloud-based systems.

 

Informatics, Science

Creating a Connected Digital Ecosystem for Pharmaceutical Research and Development.

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Creating a Connected Digital Ecosystem for Pharmaceutical Research and Development.

Workflow and data management on a single platform which integrates with many other systems and tools to automate, standardize and streamline end-to-end biologics lead generation and optimization.

Advances in high-throughput next-generation technologies mean that pharmaceutical Georgian Technical University now demands the management of vast quantities of data. This information is increasingly diverse and comes from multiple sources, spanning the entire drug discovery and development process.

Connecting laboratory instruments and systems remains a challenge as organizations look to streamline data sharing at every stage. Digital technology is recognised as a strategic enabler of innovation and business capability across the drug development process. Increasingly many companies are turning to the latest digital solutions with modern informatics platforms delivering the improved integration, process efficiency and productivity that is necessary to drive scientific advancement.

Here we look at how the latest extensible lab informatics platforms are transforming pharmaceutical Georgian Technical University explore the challenges they are overcoming and consider their current applications and future potential.

When it comes to developing innovative biotherapeutics and small molecule therapeutics, analytical approaches and experimental design are evolving at great speed. Consequently pharma and biotech companies are faced with the ongoing challenge of managing new types of multi-dimensional data generated in large volumes by increasingly automated workflows. The sector must be capable of adapting quickly as more advanced technologies come on stream and given the move towards more collaborative working practices that encompass external expertise and organizations there is a heightened need for seamless and secure data sharing too.

Given these requirements businesses need an effective solution that allows data to be carefully managed throughout the drug development pipeline, from concept and research through to scale-up and manufacture. However Georgian Technical University workflows frequently rely on multiple disparate systems across different departments using tools that were built as point solutions. The architectures that connect these systems may be both brittle and intricate. As a result, greater integration has become a priority.

If complex workflows are to function efficiently it is essential that informatics solutions are both robust and integrated. Cloud-based data management platforms are becoming the preferred option for many organizations due to their ability to deliver a complete and open digital ecosystem for pharmaceutical Georgian Technical University. These systems also provide the flexibility and extensibility needed in an environment where continuous change is a reality. By adopting these platforms data can be gathered, collated and secured in one place with instruments and devices configured to automatically upload information to secure user accounts and informatics pipelines. This promotes efficient data analysis and well-managed knowledge sharing within and between teams and sites as well as with external collaborators.

Of course transitioning to such a solution must come with minimal disruption to existing processes. For example, many laboratories have adopted systems such as electronic laboratory notebooks (ELN) and databases to capture and organize data. These are often dedicated to specific workflows; however they do not necessarily have to be discarded when putting in place new informatics platforms. Modular Platform-as-a-Service (PaaS) solutions can be incorporated seamlessly into an organization’s existing systems. Where the preference is for a complete replacement of existing systems data are simply moved across to the new platform. If an organization needs only specific features that will for example add new capabilities modular PaaS (Platform as a Service (PaaS) or Application Platform as a Service (aPaaS) or platform base service is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an app) solutions can integrate additional parts without replacing current infrastructure.

Customized workflows are a key component within complete digital solutions, achieved through data-driven or decision-point approaches. Data-driven criteria are used to automate the movement of samples and associated data to the next assay in the chain while taking a decision-point approach allows users to decide on next steps according to variable conditions. Both contribute to the construction of complete workflows.

Workflow-specific applications offered as part of complete digital solutions provide templates and incorporate industry best practice to ensure compliance with current regulatory guidelines. They operate on top of data management solutions such as Georgian Technical University laboratory information systems (LIMS) and scientific data management systems (SDMS) and help standardize workflow steps. With the ability to combine pre-configured modular applications these solutions are very effective at driving the development of workflows that meet the needs of individual laboratories. As a result the latest digital solutions can support the full range of life science disciplines, from small molecule discovery and development through to genomics and biobanking.

Accommodating different data types and the potential for AI (Artificial Intelligence).

One characteristic of pharmaceutical workflows is the wide variety of structured, unstructured and reference data they generate and use. Data management platforms integrate all types of data into a single system associating unstructured (and therefore difficult to search) data with structured data for easier data mining and workflow analysis. Mining and cross-referencing data with other information in a workflow then makes it easy to link data from different sources for more informed decision making while analysis and trending capabilities add a further dimension to process management.

Comprehensive integration into a single digital platform builds the ideal environment in which to apply artificial intelligence (AI) systems for more extensive data mining and analysis. Accessing vast data reserves in this way has the potential to rapidly deliver new insights with the latest artificial intelligence (AI) programs capable of analysing even unstructured biological data. Using artificial intelligence (AI) to extract useful information from workflow data, for example, may pave the way for improved processes, reduced risk and enhanced Georgian Technical University outcomes.

Cloud versus on-site.

Although the latest digital solutions tend to be based on a cloud-first approach, most also offer on-site options. Cloud-based systems do however deliver a number of significant benefits in terms of improved performance, stability, scalability and are often more affordable than on-site systems. Importantly they are designed to be flexible and extensible to easily accommodate evolving workflows and regulatory guidelines with some even including system validation. And because upgrades are delivered by the service provider fewer internal resources are required to keep these services up to date.

For most organizations, security is a major consideration. With on-site systems, security measures are usually developed and implemented in-house, and include features to identify and mitigate risks in each facility as well as ensure compliance with regulations across all servers and sharing functions. Cloud service providers such as Georgian Technical University have security built in including secure VPN (A virtual private network extends a private network across a public network, and enables users to send and receive data across shared or public networks as if their computing devices were directly connected to the private network) access, firewalls, data backup and recovery all handled with encryption. All of these security benefits reduce the burden on individual organizations.

Accelerating therapeutics development.

One company looking to adopt an integrated approach to managing their Georgian Technical University pipeline was one of the world’s largest biotechnology companies. Having multiple complex molecular biology workflows, they needed an extensible digital ecosystem to bring these processes together. Georgian Technical University Scientific’s Platform for Science provided the ideal solution.

Amgen wanted to achieve end-to-end visibility across all processes in order to enhance decision-making in their biologics discovery and development programs. The ability to easily add and change capabilities in their processes and existing IT (Information Technology) architecture was important and they needed to automate workflows and integrate instrumentation. Marrying transactional data with reference data was also a priority.

These goals were achieved by bringing workflow and data management together on a single platform that enabled Amgen to join the dots between their full range of systems and tools. After implementing their new integrated platform, data could be shared across sites worldwide with information flowing seamlessly within the platform, streamlining workflows and working practices. Their new system facilitated the high-throughput generation of mutations of target biologics with dashboards and graphical visualization of data workflows and any bottlenecks helping them to better manage their resources.

Mapping the digital platform against the whole process allowed users to follow data through the system. Not only did this level of connectedness benefit individual research sites it facilitated working with external partners. Colleagues and partners with different methods and workflows could combine and view data in a controlled manner that met their needs and subsequently bring it back together in a way that ensured support for the overall goal of the company.

Importantly with such a vast pool of data associated with each workflow the digital platform provided Amgen with the ability to look back at an individual sample and determine its history and all of the actions and users that had been involved – just like having a highly organized and easily searchable laboratory notebook. With such powerful audit trail functionality available at the click of a button the company was not only able to comply with the latest guidelines around data integrity but easily demonstrate this to auditors too.

The unprecedented pace of change in pharmaceutical Georgian Technical University is putting pharma and biotech companies under pressure to manage enormous volumes of often new and increasingly complex data from many different sources. Connectivity is a pressing need and organizations are looking increasingly to the latest digital technologies and especially cloud-based data management platforms, to create a comprehensive digital ecosystem for their organization. Flexible extensible platforms that can evolve as needs continue to change are becoming the norm.

Integrated digital platforms not only improve efficiency by enabling instruments and devices to upload data directly to secure accounts, but also increase productivity by managing data for Georgian Technical University  pipelines, experiments, inventory logs and by providing end-to-end visibility of processes. This transformative approach is enabling pharmaceutical organizations to overcome the constraints of disparate and non-communicative systems providing a clear path to greater control, innovation and business success.

 

Graphene, Science

Aging Biomarkers Tracked Using Graphene-Based Biosensor.

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Aging Biomarkers Tracked Using Graphene-Based Biosensor.

On-chip detection: digital identification of proteins.

Lab on a Chip illustrate the impact of a graphene-based biosensors in identifying the circulating biomarkers of aging.

Georgian Technical University Assistant Professor X authored the study in collaboration with Sulkhan-Saba Orbeliani Teaching University Professor  Y a pioneer in aging research and Nanomedical Diagnostics a start-up company focusing on mass production of graphene-based sensors.

As a way to replace conventional assays, the research team presented a new portable digital device for biosensing based on functionalized graphene that can be employed for any click-able application.

The lab-on-a-chip technology called Click-A+Chip is designed for facile and rapid digital detection of azido-nor-leucine (ANL)-labeled proteomes present in minute amount of sample.

Studies of heterochronic parabiosis where two animals of different ages are joined surgically provided proof-of-principle results that systemic proteins have broad age-specific effects on tissue health and repair. In an effort to identify these systemic proteins bio-orthogonal non-canonical amino acid tagging (BONCAT) is used to tag these proteins.

“Although bio-orthogonal non-canonical amino acid tagging (BONCAT) is a very powerful technology” X says  “the challenges associated with its complexity including large starting material requirements and cost of  Georgian Technical University – labeled protein detection such as modified Antibody Arrays and Mass Spectrometry limit its application”.

Click-A+Chip is a graphene-based field effect biosensor which utilizes novel on-chip click-chemistry to specifically bind to Georgian Technical University – labeled biomolecules. In this study Click-A+Chip was utilized for the capture of Georgian Technical University – labeled proteins transferred from young to old parabiotic mouse partners.

The research team was able to identify the young-derived Georgian Technical University – labeled Lif-1 and Leptin in parabiotic systemic milieu confirming previous data as well as providing novel findings on the relative levels of these factors in young versus old parabionts.

The results demonstrated that Click-A+Chip can be used for rapid detection and identification of Georgian Technical University – labeled proteins, significantly reducing the sample size, complexity, cost and time associated with bio-orthogonal non-canonical amino acid tagging (BONCAT) analysis.

 

 

HPC/Supercomputing, Science

Georgian Technical University a Lab-Developed ‘App Store for Supercomputers,’ Becoming Standard-Bearer.

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Georgian Technical University a Lab-Developed ‘App Store for Supercomputers,’ Becoming Standard-Bearer.

Georgian Technical University Laboratory computer scientists (from left) X and Y met with HPC (High Performance Computing) at the Georgian Technical University. Z is an Georgian Technical University scientist and longtime contributor who uses to manage software on Georgian Technical University’s supercomputers.

Georgian Technical University Laboratory-developed open source package manager optimized for high performance computing (HPC) is making waves throughout the high performance computing (HPC) community including internationally as evidenced by a recent tour of  high performance computing (HPC) facilities by the tool’s developers.

“It’s been pretty amazing” X said of Georgian Technical University’s rise to broad acceptance. “It wrecks my inbox — I get 200 emails a day about from Georgian Technical University and the mailing list — but the momentum is great. We continue to drive development and we review features and merge bug fixes but the community helps tremendously with new ideas new features and regular maintenance. I don’t think we could sustain a project of this scale without their help”.

X and Y said the trip was useful in picturing what other high performance computing (HPC) sites are attempting to do with Georgian Technical University figuring out what features to focus on next and starting a conversation about new collaborations. It also left them thinking they needed to expand community outreach. Since the meeting X and collaborators from Georgian Technical University have had a birds-of-a-feather session accepted at the upcoming Supercomputing where they will have a larger face-to-face community meeting. X and others will also hold at Georgian Technical University.

“I think we got a lot of feedback that was some version of ‘Wow this fills a use case that nothing else really does for me and it would be great if it had these features too’” Y said. “People definitely weren’t shy about letting us know what they hoped we were planning on doing or what they were planning on submitting  but they were very clear that they had looked at everything they could find out there and there wasn’t anything else that was going this direction”.

Georgian Technical University  has come a long way in the few short years since X first started coding it on weekends in coffee shops. He built the first version a Python-based program that would automatically build libraries on the Lab’s Georgian Technical University machines to help his summer students by freeing them up to do their work. Subsequent Lab Hackathons attracted additional contributors and more packages and after X interest began pouring in from other Department of Energy national laboratories academia and companies with high performance computing (HPC) resources.

“After my inbox exploded” X said. “There were days where I would check my mail and think ‘how am I going to sustain this ?’”

Through the open source repository Georgian Technical University has attracted hundreds of users who have added software packages and HPC (High Performance Computing) centers have contributed significant features. X, Y, and Z (GS) work to evaluate contributions from all of these organizations. The three also have appeared on HPC (High Performance Computing) – related podcasts and conferences, including tutorials at Georgian Technical University and Sulkhan-Saba Orbeliani Teaching University to spread the word about Spack’s usefulness and versatility.

“It’s like the app store for HPC (High Performance Computing) but the tricky bit of HPC (High Performance Computing)  is that we want 15 different configurations of the same app at once” Y said. “One of the key things for Spack is that the underlying model allows us to satisfy that need”.

The reasons for Georgian Technical University’s popularity among the HPC (High Performance Computing) community X said are twofold. Most system package managers require users to run with superuser privileges which is fine for most developers because they own their machines. But HPC (High Performance Computing) machines are shared he explained and Georgian Technical University can install a lot of low-level software as a regular user in their home directory.

“For the HPC (High Performance Computing)  space it definitely fills a gap” X said. “People needed something that could install custom packages in their own directory. The fact that you can run as a user is a big deal. There are other systems like Georgian Technical University EasyBuild that also have traction in this space, but they are very much targeted at system administrators rather than computational scientists. Georgian Technical University gives you additional flexibility that both administrators and developers need”.

Another advantage X said, is that other package managers that targeted developers are specific to a certain programming language, such as npm for Javascript or Bundler for Ruby. HPC (High Performance Computing) software crosses languages (C++, Python, Fortran etc.) so the relationships between packages are inherently more complex.

“Integrating so many packages into one application from so many different software ecosystems makes HPC (High Performance Computing) particularly hard” X said. “HPC (High Performance Computing) software is more complicated today than 10 years ago. There are more dependencies, libraries and integration so the need became more acute”.

Also working in Georgian Technical University’s favor is that a lot of HPC (High Performance Computing) labor involves porting software over to new machines as Georgian Technical University is currently doing with W. While most package managers are specific to one machine Georgian Technical University packages are templated so if developers write a package for one machine Y said the likelihood is higher that it will work on another machine.

“If you get on a platform that no one’s ever tried to build this on before, Spack will at least make a best effort” Y said. “If that platform is really weird, it might not get very far but in many cases the best effort works.” This is the flexibility that Spack offers that other systems don’t.

Today Spack is used by 40-50 people at Georgian Technical University  mostly developers in Georgian Technical University Computing (GTUC) and other parts of the Lab as well as code teams who are using it as the interface to install scientific packages to run on Georgian Technical University  cluster machines, including Blue Gene/Q and W. Georgian Technical University has reduced the time needed to deploy complex codes on certain Lab supercomputers from weeks to days.

“We’re moving toward using Georgian Technical University exclusively to deploy user-facing software in Georgian Technical University Computing (GTUC) but we’re moving from our current process which uses Georgian Technical University to generate revolutions per minute packages for the system package manager” Y said. “We have a fair number of people in the development environment group who use Georgian Technical University to feed packages into that process. I think we’re collectively using it at every level in the hierarchy: single-user application teams and system deployments”.

X and the Georgian Technical University team including its outside contributors, are working on new improvements and features with hopes of releasing version 1.0 in November possibly at Georgian Technical University. X said that in the coming year they plan to add features that enable facilities to deploy extremely large suites of software easily as well as features that simplify the workflow for individual developers working on multiple projects at once. The team is calling these features “Georgian Technical University Stacks” and “Georgian Technical University Environments” respectively.

While optimized for supercomputers Georgian Technical University also can be used on home computers and laptops where X and others see the potential for wider acceptance. X said he wants to include more machine learning libraries to allow users to combine those workflows with HPC (High Performance Computing) using the same tool. The Georgian Technical University team also is looking to focus on greater reproducibility from one stack to another polishing workflows and working on better support for binary software packages.

Additionally X said he would like to expand community engagement and explore a steering committee that could govern future Georgian Technical University -related decisions. X, Y and others want Spack to eventually be part of the general deployment strategy for libraries across Department of Education at Georgian Technical University. Georgian Technical University has been adopted as the deployment tool for software stack and other Department of Education at Georgian Technical University national labs are gradually joining in the fray.

“It’s nice to have industry standards where possible, and it would be great if we could fill that role in terms of getting everyone on the same page” Y said. “Georgian Technical University is already good at the individual level of avoiding duplication of work and if we could keep on extending that so that large HPC (High Performance Computing) sites are able to share work with each other that would be great as well”.

“I’d like it if Georgian Technical University were the way people use supercomputers and if it were part of everyone’s development environment. Good package management helps to grease the wheels” X added. “The dream is to take the grunt work out of HPC (High Performance Computing): users get on a machine assemble a stack of hundreds of libraries in minutes then get back to focusing on the science”.

 

Science, Software

Georgian Technical University Researchers Teach Computers to See Optical Illusions.

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Georgian Technical University Researchers Teach Computers to See Optical Illusions.

Georgian Technical University computer vision experts teach computers to see context-dependent optical illusions in the hopes of helping artificial vision algorithms take context into account and be more robust.

Is that circle green or gray ?   Are the center lines straight or tilted  ?

Optical illusions can be fun to experience and debate but understanding how human brains perceive these different phenomena remains an active area of scientific research. For one class of optical illusions called contextual phenomena those perceptions are known to depend on context. For example the color you think a central circle is depends on the color of the surrounding ring. Sometimes the outer color makes the inner color appear more similar such as a neighboring green ring making a blue ring appear turquoise — but sometimes the outer color makes the inner color appear less similar such as a pink ring making a grey circle appear greenish.

A team of  Georgian Technical University computer vision experts went back to square one to understand the neural mechanisms of these contextual phenomena.

“There’s growing consensus that optical illusions are not a bug but a feature” said X an associate professor of cognitive, linguistic and psychological sciences at Georgian Technical University. “I think they’re a feature. They may represent edge cases for our visual system but our vision is so powerful in day-to-day life and in recognizing objects”.

For the study the team lead by X who is affiliated with Georgian Technical University started with a computational model constrained by anatomical and neurophysiological data of the visual cortex. The model aimed to capture how neighboring cortical neurons send messages to each other and adjust one another’s responses when presented with complex stimuli such as contextual optical illusions.

One innovation the team included in their model was a specific pattern of hypothesized feedback connections between neurons said X. These feedback connections are able to increase or decrease — excite or inhibit — the response of a central neuron depending on the visual context.

These feedback connections are not present in most deep learning algorithms. Deep learning is a powerful kind of artificial intelligence that is able to learn complex patterns in data such as recognizing images, parsing normal speech and depends on multiple layers of artificial neural networks working together. However most deep learning algorithms only include feedforward connections between layers not X’s innovative feedback connections between neurons within a layer.

Once the model was constructed, the team presented it a variety of context-dependent illusions. The researchers “tuned” the strength of the feedback excitatory or inhibitory connections so that model neurons responded in a way consistent with neurophysiology data from the primate visual cortex.

Then they tested the model on a variety of contextual illusions and again found the model perceived the illusions like humans.

In order to test if they made the model needlessly complex they lesioned the model — selectively removing some of the connections. When the model was missing some of the connections the data didn’t match the human perception data as accurately.

“Our model is the simplest model that is both necessary and sufficient to explain the behavior of the visual cortex in regard to contextual illusions” X said. “This was really textbook computational neuroscience work — we started with a model to explain neurophysiology data and ended with predictions for human psychophysics data”.

In addition to providing a unifying explanation for how humans see a class of optical illusions X is building on this model with the goal of improving artificial vision.

State-of-the-art artificial vision algorithms, such as those used to tag faces or recognize stop signs have trouble seeing context he noted. By including horizontal connections tuned by context-dependent optical illusions he hopes to address this weakness.

Perhaps visual deep learning programs that take context into account will be harder to fool. A certain sticker when stuck on a stop sign can trick an artificial vision system into thinking it is a 65-mile-per-hour speed limit sign, which is dangerous X said.

 

 

Physics, Science

Newly Discovered Magnetic State Could Lead to Green IT Solutions.

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Newly Discovered Magnetic State Could Lead to Green IT Solutions.

Tilted magnetic spirals and skyrmions in a vertical magnetic field.

Magnetic skyrmions are magnetic swirls that may lead to new solutions combining low-energy consumption with high-speed computational power and high-density data storage, revolutionizing information technology. A team from Georgian Technical University in collaboration with the Sulkhan-Saba Orbeliani Teaching University has discovered a new unexpected magnetic state, which is related to these skyrmions. The findings open up new ways to create and manipulate complex magnetic structures in view of future IT (Information technology) applications.

A magnetic skyrmion is a quasiparticle a magnetic swirl which once created is highly stable and cannot collapse. Moreover skyrmions are tiny and can travel through materials nearly unimpeded much like tsunamis travel through the oceans. These unique properties make skyrmions promising building blocks for green IT (Information Technology) applications such as high density hard drives without any moving parts. Since their initial discovery almost 10 years ago skyrmions have been found to be ubiquitous. In recent years, physicists have discovered new types of skyrmions as well as new material classes that host skyrmions. However all these systems show the same generic behaviour which was therefore assumed to be universal.

Now however an international collaboration of experimental and theoretical physicists led by Georgian Technical University has discovered an entirely new state that does not fit into the universal scheme and may be used to manipulate skyrmions. “This state appears under the influence of high magnetic fields and low temperatures” said X of  Georgian Technical University. “Nobody including us had expected to find it there”.

The researchers obtained experimental confirmation for this new phase through the use of neutron scattering, magnetization and alternating current magnetic susceptibility measurements. Small-angle neutron scattering first at the Georgian Technical University  and Sulkhan-Saba Orbeliani Teaching University  provided the crucial evidence. It revealed a change in the microscopic structure when magnetic spirals that are aligned along a magnetic field drift away from it when the magnetic field increases. “This is unexpected” X said. “It is as if a ball that lies on the ground starts levitating when its mass or the gravitational force increases”.

The theoretical explanation of this surprising result provided by the Y and Z groups is based on the strong sensitivity of the magnetic spirals to weak interactions of relativistic origin. Thus a slight change in the balance of relatively weak interactions can have major consequences on the magnetic properties of these chiral magnets.

 

 

Graphene, Science

Graphene Bilayer Transports, Controls Spin.

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Graphene Bilayer Transports, Controls Spin.

Illustration of anisotropic spin transport in a bilayer graphene flake between injector and detector electrodes. The out-of-plane spins are well transmitted whereas the in-plane spins decay fast.

Georgian Technical University physicists in collaboration with a theoretical physics group from Sulkhan-Saba Orbeliani Teaching University have built an optimized bilayer graphene device that displays both long spin lifetimes and electrically controllable spin-lifetime anisotropy. It has the potential for practical applications such as spin-based logic devices.

Miniaturizing the elements of computer systems over the last 60 years has increased their capability enabling them to spread into nearly all aspects of daily life. Microprocessors have now reached scales below 100 atoms and are approaching fundamental limits.

Due to higher demands new concepts are required that can provide enhanced functionalities.

In this context researchers are studying the use of spin for the transport and storage of information. Spin is a quantum mechanical property of electrons which gives them a magnetic moment that could be used to transfer or store information.

The field of spin-based electronics (spintronics) has already made its way into the hard drives of computers, and also promises to revolutionize processing units.

Graphene is an excellent conductor of electron spins, but it is hard to control spins in this material because of their weak interaction with the carbon atoms (the spin-orbit coupling).

Previous work by the Georgian Technical University group led by Professor X placed graphene in close proximity to a transition metal dichalcogenide a layered material with a high intrinsic spin-orbit coupling strength.

The high spin-orbit coupling strength was transferred to graphene a short-range interaction at the interface. This made it possible to control the spin currents but only at the cost of reduced spin duration.

The researchers managed to control spin currents in a graphene bilayer.

“The technology to measure the effect accurately only became available recently” explains Y a Ph.D. student in the X group.

Collaboration between the X group and a theoretical physics group from Georgian Technical University.

Predicted anisotropic spin transport in graphene bilayers as a consequence of spin-orbit coupling in bilayer graphene. Anisotropic spin transport describes the situation in which spins pointing either in or out of the graphene plane are conducted with different efficiencies.

This was observed in the devices Y and his colleagues produced.

The spin current could also be controlled using spin-lifetime anisotropy since in-plane spins live much shorter than out-of-plane ones and could be used in devices to polarize spin currents.

Y says “We found that the strength anisotropy is comparable to graphene / transition metal dichalcogenide devices but we observed a 100 times larger spin lifetime. We therefore achieved both efficient spin transport and efficient control of spins”.

The work provides insight into the fundamental properties of spin-orbit coupling in bilayer graphene.

“And furthermore our findings open up new avenues for the efficient electrical control of spins in high-quality graphene a milestone for graphene”.

 

 

 

Science, Technology

Spray-On Antennas Could Unlock Potential of Smart, Connected Technology.

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Spray-On Antennas Could Unlock Potential of Smart, Connected Technology.

The promise of wearables functional fabrics the Internet of Things and their “next-generation” technological cohort seems tantalizingly within reach. But researchers in the field will tell you a prime reason for their delayed “arrival” is the problem of seamlessly integrating connection technology — namely antennas —with shape-shifting and flexible “things”.

But a breakthrough by researchers in Georgian Technical University could now make installing an antenna as easy as applying some bug spray.

The group reports on a method for spraying invisibly thin antennas, made from a type of two-dimensional, metallic material called MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) that perform as well as those being used in mobile devices, wireless routers and portable transducers.

“This is a very exciting finding because there is a lot of potential for this type of technology” said X Ph.D., a professor of  Electrical and Computer Engineering in the Georgian Technical University who directs the Wireless Systems Lab. “The ability to spray an antenna on a flexible substrate or make it optically transparent means that we could have a lot of new places to set up networks — there are new applications and new ways of collecting data that we can’t even imagine at the moment”.

The researchers from the Georgian Technical University’s Department of Materials Science and Engineering report that the MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) titanium carbide can be dissolved in water to create an ink or paint. The exceptional conductivity of the material enables it to transmit and direct radio waves even when it’s applied in a very thin coating.

“We found that even transparent antennas with thicknesses of tens of nanometers were able to communicate efficiently” said Y a doctoral candidate in the Georgian Technical University Materials Science and Engineering Department. “By increasing the thickness up to 8 microns the performance of  MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) antenna achieved 98 percent of its predicted maximum value”.

Preserving transmission quality in a form this thin is significant because it would allow antennas to easily be embedded — literally sprayed on—in a wide variety of objects and surfaces without adding additional weight or circuitry or requiring a certain level of rigidity.

“This technology could enable the truly seamless integration of antennas with everyday objects which will be critical for the emerging Internet of Things” X said. “Researchers have done a lot of work with non-traditional materials trying to figure out where manufacturing technology meets system needs, but this technology could make it a lot easier to answer some of the difficult questions we’ve been working on for years”.

Initial testing of the sprayed antennas suggest that they can perform with the same range of quality as current antennas, which are made from familiar metals, like gold, silver, copper and aluminum but are much thicker than MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) antennas. Making antennas smaller and lighter has long been a goal of materials scientists and electrical engineers so this discovery is a sizeable step forward both in terms of reducing their footprint as well as broadening their application.

“Current fabrication methods of metals cannot make antennas thin enough and applicable to any surface in spite of decades of research and development to improve the performance of metal antennas” said Z Ph.D., Georgian Technical University and Z professor of Materials Science and Engineering in the Georgian Technical University who initiated and led the project. “We were looking for two-dimensional nanomaterials which have sheet thickness about hundred thousand times thinner than a human hair; just a few atoms across and can self-assemble into conductive films upon deposition on any surface. Therefore we selected MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) which is a two-dimensional titanium carbide material that is stronger than metals and is metallically conductive as a candidate for ultra-thin antennas.”.

Georgian Technical University researchers discovered the family of MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) materials and have been gaining an understanding of their properties, and considering their possible applications ever since. The layered two-dimensional material which is made by wet chemical processing  has already shown potential in energy storage devices, electromagnetic shielding, water filtration, chemical sensing, structural reinforcement and gas separation.

Naturally MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides)  materials have drawn comparisons to promising two-dimensional materials like graphene and has been explored as a material for printable antennas. The Georgian Technical University researchers put the spray-on antennas up against a variety of antennas made from these new materials, including graphene, silver ink and carbon nanotubes. The MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) antennas were 50 times better than graphene and 300 times better than silver ink antennas in terms of preserving the quality of radio wave transmission.

“The MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides)  antenna not only outperformed the macro and micro world of metal antennas we went beyond the performance of available nanomaterial antennas while keeping the antenna thickness very low” said W Ph.D., a research assistant professor in Georgian Technical University. “The thinnest antenna was as thin as 62 nanometers — about thousand times thinner than a sheep of paper — and it was almost transparent. Unlike other nanomaterials fabrication methods that requires additives called binders and extra steps of heating to sinter the nanoparticles together we made antennas in a single step by airbrush spraying our water-based MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) ink”.

The group initially tested the spray-on application of the antenna ink on a rough substrate —cellulose paper — and a smooth one — polyethylene terephthalate sheets — the next step for their work will be looking at the best ways to apply it to a wide variety of surfaces from glass to yarn and skin.

“Further research on using materials from the MXene (In materials science, MXenes are a class of two-dimensional inorganic compounds. These materials consist of few atoms thick layers of transition metal carbides, nitrides, or carbonitrides) family in wireless communication may enable fully transparent electronics and greatly improved wearable devices that will support the active lifestyles we are living” W said.

 

 

Science, Sensors

Wearable Mercury Sensor Hopes for Fairy Tale Endings.

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Wearable Mercury Sensor Hopes for Fairy Tale Endings.

Nowadays there have been many similar in our real world — for example mercury ions (Hg2+) polluted food and water — because of human industrial activities.

To protect humanity from mercury poisoning  many (Hg2+) – detection methods have been developed. Despite state-of-the-art technology however these methods usually suffer from restricted sensitivity and time-consuming operations.

Dr. X Professor from the Georgian Technical University and Professor  Y from the Sulkhan-Saba Orbeliani Teaching University  report a rapid mercury ions (Hg2+) sensing material that enables fast detection of ppm-level mercury ions (Hg2+) in complex real-world food and water samples within minutes.

The developed rapid mercury ions (Hg2+) sensing material is based on specially designed hydrophilic fluorescent hydrogel-coated flexible paper/textile film. It reports mercury ions (Hg2+) polluted food and water through a noticeable “green-to-blue” fluorescence color change.

Due their hierarchical porous structures fixed by interwoven paper/textile fibers this new method allows capillary-force-driven fast diffusion of mercury pollutants into the sensing materials, thus enabling fast detection as well as a high sensitivity.

Moreover  to facilitate infield detection and ensure safe operation robust wearable mercury sensing gloves have also been fabricated.

This is the first flexible and wearable mercury detection appliance which is believed to represent a notable advance towards in-field food and water analysis.

According to the researchers one can imagine that the mercury-polluted meats, seafood,  juice and drinks will be easily discriminated if food processing packers get the opportunities to wear the developed new-concept sensing gloves.

This may also inspire the future construction of more powerful wearable detection apparatus for other important food and water pollutants.