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Accurate Detection of Low-Level Somatic Mutation in Intractable Epilepsy KAIST medical scientists have developed an advanced method for perfectly detecting low-level somatic mutation in patients with intractable epilepsy. Their study showed that deep sequencing replicates of major focal epilepsy genes accurately and efficiently identified low-level somatic mutations in intractable epilepsy. According to the study, their diagnostic method could increase the accuracy up to 100%, unlike the conventional sequencing analysis, which stands at about 30% accuracy. This work was published in Acta Neuropathologica. Epilepsy is a neurological disorder common in children. Approximately one third of child patients are diagnosed with intractable epilepsy despite adequate anti-epileptic medication treatment. Somatic mutations in mTOR pathway genes, SLC35A2, and BRAF are the major genetic causes of intractable epilepsies. A clinical trial to target Focal Cortical Dysplasia type II (FCDII), the mTOR inhibitor is underway at Severance Hospital, their collaborator in Seoul, Korea. However, it is difficult to detect such somatic mutations causing intractable epilepsy because their mutational burden is less than 5%, which is similar to the level of sequencing artifacts. In the clinical field, this has remained a standing challenge for the genetic diagnosis of somatic mutations in intractable epilepsy. Professor Jeong Ho Lee’s team at the Graduate School of Medical Science and Engineering analyzed paired brain and peripheral tissues from 232 intractable epilepsy patients with various brain pathologies at Severance Hospital using deep sequencing and extracted the major focal epilepsy genes. They narrowed down target genes to eight major focal epilepsy genes, eliminating almost all of the false positive calls using deep targeted sequencing. As a result, the advanced method robustly increased the accuracy and enabled them to detect low-level somatic mutations in unmatched Formalin Fixed Paraffin Embedded (FFPE) brain samples, the most clinically relevant samples. Professor Lee conducted this study in collaboration with Professor Dong Suk Kim and Hoon-Chul Kang at Severance Hospital of Yonsei University. He said, “This advanced method of genetic analysis will improve overall patient care by providing more comprehensive genetic counseling and informing decisions on alternative treatments.” Professor Lee has investigated low-level somatic mutations arising in the brain for a decade. He is developing innovative diagnostics and therapeutics for untreatable brain disorders including intractable epilepsy and glioblastoma at a tech-startup called SoVarGen. “All of the technologies we used during the research were transferred to the company. This research gave us very good momentum to reach the next phase of our startup,” he remarked. The work was supported by grants from the Suh Kyungbae Foundation, a National Research Foundation of Korea grant funded by the Ministry of Science and ICT, the Korean Health Technology R&D Project from the Ministry of Health & Welfare, and the Netherlands Organization for Health Research and Development. (Figure: Landscape of somatic and germline mutations identified in intractable epilepsy patients. a Signaling pathways for all of the mutated genes identified in this study. Bold: somatic mutation, Regular: germline mutation. b The distribution of variant allelic frequencies (VAFs) of identified somatic mutations. c The detecting rate and types of identified mutations according to histopathology. Yellow: somatic mutations, green: two-hit mutations, grey: germline mutations.)
2019.08.14 View 26812
Professor Sang Gyu Kim Receives Yeochon Award for Ecology Professor Sang-Gyu Kim from the Department of Biological Sciences was selected as the winner of the 12th Yeochon Award for Ecology presented by the Yeochon Association for Ecological Research. The award was conferred on August 13 in Jeju at the annual conference co-hosted by the Ecological Society of Korea and the Yeochon Association for Ecological Research. Professor Kim received 10 million KRW in prize money. Professor Kim was recognized for his achievements and contributions in studying herbivorous insects ‘rice weevils’ and their host plant ‘wild tobacco’, especially for having explored the known facts in traditional ecology at the molecular level. His findings are presented in his paper titled ‘Trichobaris weevils distinguish amongst toxic host plants by sensing volatiles that do not affect larval performance’ published in Molecular Ecology in July 2016. Furthermore, Professor Kim’s research team is continuing their work to identify the ecological functions of plant metabolites as well as interactions between flowers and insect vectors at the molecular level. In doing so, the team edits genes in various plant species using the latest gene editing technology. The Yeochon Award for Ecology was first established in 2005 with funds donated by a senior ecologist, the late Honorary Professor Joon-Ho Kim of Seoul National University. The award is named after the professor’s pen name “Yeochon” and is intended to encourage promising next-generation ecologists to produce outstanding research achievements in the field of basic ecology. Professor Kim said, “I will take this award as encouragement to continue taking challenging risks to observe ecological phenomenon from a new perspective. I will continue my research with my students with joy and enthusiasm.”
2019.08.14 View 5196
Manipulating Brain Cells by Smartphone Researchers have developed a soft neural implant that can be wirelessly controlled using a smartphone. It is the first wireless neural device capable of indefinitely delivering multiple drugs and multiple colour lights, which neuroscientists believe can speed up efforts to uncover brain diseases such as Parkinson’s, Alzheimer’s, addiction, depression, and pain. A team under Professor Jae-Woong Jeong from the School of Electrical Engineering at KAIST and his collaborators have invented a device that can control neural circuits using a tiny brain implant controlled by a smartphone. The device, using Lego-like replaceable drug cartridges and powerful, low-energy Bluetooth, can target specific neurons of interest using drugs and light for prolonged periods. This study was published in Nature Biomedical Engineering. “This novel device is the fruit of advanced electronics design and powerful micro and nanoscale engineering,” explained Professor Jeong. “We are interested in further developing this technology to make a brain implant for clinical applications.” This technology significantly overshadows the conventional methods used by neuroscientists, which usually involve rigid metal tubes and optical fibers to deliver drugs and light. Apart from limiting the subject’s movement due to bulky equipment, their relatively rigid structure causes lesions in soft brain tissue over time, therefore making them not suitable for long-term implantation. Although some efforts have been made to partly mitigate adverse tissue response by incorporating soft probes and wireless platforms, the previous solutions were limited by their inability to deliver drugs for long periods of time as well as their bulky and complex control setups. To achieve chronic wireless drug delivery, scientists had to solve the critical challenge of the exhaustion and evaporation of drugs. To combat this, the researchers invented a neural device with a replaceable drug cartridge, which could allow neuroscientists to study the same brain circuits for several months without worrying about running out of drugs. These ‘plug-n-play’ drug cartridges were assembled into a brain implant for mice with a soft and ultrathin probe (with the thickness of a human hair), which consisted of microfluidic channels and tiny LEDs (smaller than a grain of salt), for unlimited drug doses and light delivery. Controlled with an elegant and simple user interface on a smartphone, neuroscientists can easily trigger any specific combination or precise sequencing of light and drug delivery in any implanted target animal without the need to be physically inside the laboratory. Using these wireless neural devices, researchers can also easily setup fully automated animal studies where the behaviour of one animal could affect other animals by triggering light and/or drug delivery. “The wireless neural device enables chronic chemical and optical neuromodulation that has never been achieved before,” said lead author Raza Qazi, a researcher with KAIST and the University of Colorado Boulder. This work was supported by grants from the National Research Foundation of Korea, US National Institute of Health, National Institute on Drug Abuse, and Mallinckrodt Professorship. (A neural implant with replaceable drug cartridges and Bluetooth low-energy can target specific neurons .) (Micro LED controlling using smartphone application)
2019.08.07 View 30131
Synthesizing Single-Crystalline Hexagonal Graphene Quantum Dots (Figure: Uniformly ordered single-crystalline graphene quantum dots of various sizes synthesized through solution chemistry.) A KAIST team has designed a novel strategy for synthesizing single-crystalline graphene quantum dots, which emit stable blue light. The research team confirmed that a display made of their synthesized graphene quantum dots successfully emitted blue light with stable electric pressure, reportedly resolving the long-standing challenges of blue light emission in manufactured displays. The study, led by Professor O Ok Park in the Department of Chemical and Biological Engineering, was featured online in Nano Letters on July 5. Graphene has gained increased attention as a next-generation material for its heat and electrical conductivity as well as its transparency. However, single and multi-layered graphene have characteristics of a conductor so that it is difficult to apply into semiconductor. Only when downsized to the nanoscale, semiconductor’s distinct feature of bandgap will be exhibited to emit the light in the graphene. This illuminating featuring of dot is referred to as a graphene quantum dot. Conventionally, single-crystalline graphene has been fabricated by chemical vapor deposition (CVD) on copper or nickel thin films, or by peeling graphite physically and chemically. However, graphene made via chemical vapor deposition is mainly used for large-surface transparent electrodes. Meanwhile, graphene made by chemical and physical peeling carries uneven size defects. The research team explained that their graphene quantum dots exhibited a very stable single-phase reaction when they mixed amine and acetic acid with an aqueous solution of glucose. Then, they synthesized single-crystalline graphene quantum dots from the self-assembly of the reaction intermediate. In the course of fabrication, the team developed a new separation method at a low-temperature precipitation, which led to successfully creating a homogeneous nucleation of graphene quantum dots via a single-phase reaction. Professor Park and his colleagues have developed solution phase synthesis technology that allows for the creation of the desired crystal size for single nanocrystals down to 100 nano meters. It is reportedly the first synthesis of the homogeneous nucleation of graphene through a single-phase reaction. Professor Park said, "This solution method will significantly contribute to the grafting of graphene in various fields. The application of this new graphene will expand the scope of its applications such as for flexible displays and varistors.” This research was a joint project with a team from Korea University under Professor Sang Hyuk Im from the Department of Chemical and Biological Engineering, and was supported by the National Research Foundation of Korea, the Nano-Material Technology Development Program from the Electronics and Telecommunications Research Institute (ETRI), KAIST EEWS, and the BK21+ project from the Korean government.
2019.08.02 View 30890
'Flying Drones for Rescue' (Video Credit: ⓒNASA JPL) < Team USRG and Professor Shim (second from the right) > Having recently won the AI R&D Grand Challenge Competition in Korea, Team USRG (Unmanned System Research Group) led by Professor Hyunchul Shim from the School of Electrical Engineering is all geared up to take on their next challenges: the ‘Defense Advanced Research Projects Agency Subterranean Challenge (DARPA SubT Challenge)’ and ‘Lockheed Martin’s AlphaPilot Challenge’ next month. Team USRG won the obstacle course race in the ‘2019 AI R&D Grand Challenge Competition’ on July 12. They managed to successfully dominate the challenging category of ‘control intelligence.’ Having to complete the obstacle course race solely using AI systems without any connection to the internet made it difficult for most of the eight participating teams to pass the third section of the race, and only Team USRG passed the long pipeline course during their attempt in the main event. They also demonstrated, after the main event, that their drone can navigate all of the checkpoints including landing on the “H” mark using deep learning. Their drone flew through polls and pipes, and escaped from windows and mazes against strong winds, amid cheers and groans from the crowd gathered at the Korea Exhibition Center (KINTEX) in Goyang, Korea. The team was awarded three million KRW in prize money, and received a research grant worth six hundred million KRW from the Ministry of Science and ICT (MSIT). “Being ranked first in the race for which we were never given a chance for a test flight means a lot to our team. Considering that we had no information on the exact size of the course in advance, this is a startling result,” said Professor Shim. “We will carry out further research with this funding, and compete once again with the improved AI and drone technology in the 2020 competition,” he added. The AI R&D Grand Challenge Competition, which was first started in 2017, has been designed to promote AI research and development and expand its application to addressing high-risk technical challenges with significant socio-economic impact. This year’s competition presented participants with a task where they had to develop AI software technology for drones to navigate themselves autonomously during complex disaster relief operations such as aid delivery. Each team participated in one of the four tracks of the competition, and their drones were evaluated based on the criteria for each track. The divisions were broken up into intelligent context-awareness, intelligent character recognition, auditory intelligence, and control intelligence. Team USRG’s technological prowess has been already well acclaimed among international peer groups. Teamed up with NASA JPL, Caltech, and MIT, they will compete in the subterranean mission during the ‘DARPA SubT Challenge’. Team CoSTAR, as its name stands for, is working together to build ‘Collaborative SubTerranean Autonomous Resilient Robots.’ Professor Shim emphasized the role KAIST plays in Team CoSTAR as a leader in drone technology. “I think when our drone technology will be added to our peers’ AI and robotics, Team CoSTAR will bring out unsurpassable synergy in completing the subterrestrial and planetary applications. I would like to follow the footprint of Hubo, the winning champion of the 2015 DARPA Robotics Challenge and even extend it to subterranean exploration,” he said. These next generation autonomous subsurface explorers are now all optimizing the physical AI robot systems developed by Team CoSTAR. They will test their systems in more realistic field environments August 15 through 22 in Pittsburgh, USA. They have already received funding from DARPA for participating. Team CoSTAR will compete in three consecutive yearly events starting this year, and the last event, planned for 2021, will put the team to the final test with courses that incorporate diverse challenges from all three events. Two million USD will be awarded to the winner after the final event, with additional prizes of up to 200,000 USD for self-funded teams. Team USRG also ranked third in the recent Hyundai Motor Company’s ‘Autonomous Vehicle Competition’ and another challenge is on the horizon: Lockheed Martin’s ‘AlphaPilot Challenge’. In this event, the teams will be flying their drones through a series of racing gates, trying to beat the best human pilot. The challenge is hosted by Lockheed Martin, the world’s largest military contractor and the maker of the famed F-22 and F-35 stealth fighters, with the goal of stimulating the development of autonomous drones. Team USRG was selected from out of more than 400 teams from around the world and is preparing for a series of races this fall, beginning from the end of August. Professor Shim said, “It is not easy to perform in a series of competitions in just a few months, but my students are smart, hardworking, and highly motivated. These events indeed demand a lot, but they really challenge the researchers to come up with technologies that work in the real world. This is the way robotics really should be.” (END)
2019.07.26 View 9862
Flexible User Interface Distribution for Ubiquitous Multi-Device Interaction < Research Group of Professor Insik Shin (center) > KAIST researchers have developed mobile software platform technology that allows a mobile application (app) to be executed simultaneously and more dynamically on multiple smart devices. Its high flexibility and broad applicability can help accelerate a shift from the current single-device paradigm to a multiple one, which enables users to utilize mobile apps in ways previously unthinkable. Recent trends in mobile and IoT technologies in this era of 5G high-speed wireless communication have been hallmarked by the emergence of new display hardware and smart devices such as dual screens, foldable screens, smart watches, smart TVs, and smart cars. However, the current mobile app ecosystem is still confined to the conventional single-device paradigm in which users can employ only one screen on one device at a time. Due to this limitation, the real potential of multi-device environments has not been fully explored. A KAIST research team led by Professor Insik Shin from the School of Computing, in collaboration with Professor Steve Ko’s group from the State University of New York at Buffalo, has developed mobile software platform technology named FLUID that can flexibly distribute the user interfaces (UIs) of an app to a number of other devices in real time without needing any modifications. The proposed technology provides single-device virtualization, and ensures that the interactions between the distributed UI elements across multiple devices remain intact. This flexible multimodal interaction can be realized in diverse ubiquitous user experiences (UX), such as using live video steaming and chatting apps including YouTube, LiveMe, and AfreecaTV. FLUID can ensure that the video is not obscured by the chat window by distributing and displaying them separately on different devices respectively, which lets users enjoy the chat function while watching the video at the same time. In addition, the UI for the destination input on a navigation app can be migrated into the passenger’s device with the help of FLUID, so that the destination can be easily and safely entered by the passenger while the driver is at the wheel. FLUID can also support 5G multi-view apps – the latest service that allows sports or games to be viewed from various angles on a single device. With FLUID, the user can watch the event simultaneously from different viewpoints on multiple devices without switching between viewpoints on a single screen. PhD candidate Sangeun Oh, who is the first author, and his team implemented the prototype of FLUID on the leading open-source mobile operating system, Android, and confirmed that it can successfully deliver the new UX to 20 existing legacy apps. “This new technology can be applied to next-generation products from South Korean companies such as LG’s dual screen phone and Samsung’s foldable phone and is expected to embolden their competitiveness by giving them a head-start in the global market.” said Professor Shin. This study will be presented at the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019) October 21 through 25 in Los Cabos, Mexico. The research was supported by the National Science Foundation (NSF) (CNS-1350883 (CAREER) and CNS-1618531). Figure 1. Live video streaming and chatting app scenario Figure 2. Navigation app scenario Figure 3. 5G multi-view app scenario Publication: Sangeun Oh, Ahyeon Kim, Sunjae Lee, Kilho Lee, Dae R. Jeong, Steven Y. Ko, and Insik Shin. 2019. FLUID: Flexible User Interface Distribution for Ubiquitous Multi-device Interaction. To be published in Proceedings of the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019). ACM, New York, NY, USA. Article Number and DOI Name TBD. Video Material: https://youtu.be/lGO4GwH4enA Profile: Prof. Insik Shin, MS, PhD ishin@kaist.ac.kr https://cps.kaist.ac.kr/~ishin Professor Cyber-Physical Systems (CPS) Lab School of Computing Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Sangeun Oh, PhD Candidate ohsang1213@kaist.ac.kr https://cps.kaist.ac.kr/ PhD Candidate Cyber-Physical Systems (CPS) Lab School of Computing Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Prof. Steve Ko, PhD stevko@buffalo.edu https://nsr.cse.buffalo.edu/?page_id=272 Associate Professor Networked Systems Research Group Department of Computer Science and Engineering State University of New York at Buffalo http://www.buffalo.edu/ Buffalo 14260, USA (END)
2019.07.20 View 37420
Deciphering Brain Somatic Mutations Associated with Alzheimer's Disease Researchers have found a potential link between non-inherited somatic mutations in the brain and the progression of Alzheimer’s disease Researchers have identified somatic mutations in the brain that could contribute to the development of Alzheimer’s disease (AD). Their findings were published in the journal Nature Communications last week. Decades worth of research has identified inherited mutations that lead to early-onset familial AD. Inherited mutations, however, are behind at most half the cases of late onset sporadic AD, in which there is no family history of the disease. But the genetic factors causing the other half of these sporadic cases have been unclear. Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering and colleagues analysed the DNA present in post-mortem hippocampal formations and in blood samples from people aged 70 to 96 with AD and age-matched controls. They specifically looked for non-inherited somatic mutations in their brains using high-depth whole exome sequencing. The team developed a bioinformatics pipeline that enabled them to detect low-level brain somatic single nucleotide variations (SNVs) – mutations that involve the substitution of a single nucleotide with another nucleotide. Brain somatic SNVs have been reported on and accumulate throughout our lives and can sometimes be associated with a range of neurological diseases. The number of somatic SNVs did not differ between individuals with AD and non-demented controls. Interestingly, somatic SNVs in AD brains arise about 4.8 times more slowly than in blood. When the team performed gene-set enrichment tests, 26.9 percent of the AD brain samples had pathogenic brain somatic SNVs known to be linked to hyperphosphorylation of tau proteins, which is one of major hallmarks of AD. Then, they pinpointed a pathogenic SNV in the PIN1 gene, a cis/trans isomerase that balances phosphorylation in tau proteins, found in one AD patient’s brain. They found the mutation was 4.9 time more abundant in AT8-positive – a marker for hyper-phosphorylated tau proteins– neurons in the entorhinal cortex than the bulk hippocampal tissue. Furthermore, in a series of functional assays, they observed the mutation causing a loss of function in PIN1 and such haploinsufficiency increased the phosphorylation and aggregation of tau proteins. “Our study provides new insights into the molecular genetic factors behind Alzheimer’s disease and other neurodegenerative diseases potentially linked to somatic mutations in the brain,” said Professor Lee. The team is planning to expand their study to a larger cohort in order to establish stronger links between these brain somatic mutations and the pathogenesis of Alzheimer’s disease. (Figure 1. Bioinformatic pipeline for detecting low-level brain somatic mutations in AD and non-AD.) (Figure 2. Pathogenic brain somatic mutations associated with tau phosphorylation are significantly enriched in AD brains.) (Figure 3. A pathogenic brain somatic mutation in PIN1 (c. 477 C>T) is a loss-of-function and related functional assays show its haploinsufficiency increases phosphorylation and aggregation of tau.)
2019.07.19 View 34011
High-Performance Sodium Ion Batteries Using Copper Sulfide (Prof.Yuk and his two PhD candidates Parks) Researchers presented a new strategy for extending sodium ion batteries’ cyclability using copper sulfide as the electrode material. This strategy has led to high-performance conversion reactions and is expected to advance the commercialization of sodium ion batteries as they emerge as an alternative to lithium ion batteries. Professor Jong Min Yuk’s team confirmed the stable sodium storage mechanism using copper sulfide, a superior electrode material that is pulverization-tolerant and induces capacity recovery. Their findings suggest that when employing copper sulfide, sodium ion batteries will have a lifetime of more than five years with one charge per a day. Even better, copper sulfide, composed of abundant natural materials such as copper and sulfur, has better cost competitiveness than lithium ion batteries, which use lithium and cobalt. Intercalation-type materials such as graphite, which serve as commercialized anode materials in lithium ion batteries, have not been viable for high-capacity sodium storage due to their insufficient interlayer spacing. Thus, conversion and alloying reactions type materials have been explored to meet higher capacity in the anode part. However, those materials generally bring up large volume expansions and abrupt crystallographic changes, which lead to severe capacity degradation. The team confirmed that semi-coherent phase interfaces and grain boundaries in conversion reactions played key roles in enabling pulverization-tolerant conversion reactions and capacity recovery, respectively. Most of conversion and alloying reactions type battery materials usually experience severe capacity degradations due to having completely different crystal structures and large volume expansion before and after the reactions. However, copper sulfides underwent a gradual crystallographic change to make the semi-coherent interfaces, which eventually prevented the pulverization of particles. Based on this unique mechanism, the team confirmed that copper sulfide exhibits a high capacity and high cycling stability regardless of its size and morphology. Professor Yuk said, “Sodium ion batteries employing copper sulfide can advance sodium ion batteries, which could contribute to the development of low-cost energy storage systems and address the micro-dust issue” This study was posted in Advanced Science on April 26 online and selected as the inside back cover for June issue. (Figure: Schematic model demonstrating grain boundaries and phase interfaces formations.)
2019.07.15 View 26534
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions (Figure: Overall scheme of DeepEC) A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions. A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner. DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism. EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction. DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers. In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component. Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method. This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.” “DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim. Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT. Profile: -Professor Hyun Uk Kim (ehukim@kaist.ac.kr) https://sites.google.com/view/ehukim Department of Chemical and Biomolecular Engineering -Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr) Department of Chemical and Biomolecular Engineering http://mbel.kaist.ac.kr
2019.07.09 View 34277
Two Alumni Win the Korea Best Scientist and Technologist Awards Vice Chairman Ki-Nam Kim (Left) and Distinguished Professor Sukbok Chang (Right) <ⓒ Photo by MSIT and KOFST> Distinguished KAIST Professor Sukbok Chang from the Department of Chemistry and Vice Chairman Ki-Nam Kim of Samsung Electronics were selected as the winners of the “2019 Korea Best Scientist and Technologist Awards” by the Ministry of Science and ICT (MSIT) and the Korean Federation of Science and Technology Societies (KOFST). The awards, which were first handed out in 2003, are the highest honor bestowed to the two most outstanding scientists in Korea every year, and this year’s awardees are of greater significance as they are both KAIST alumni. Professor Chang was recognized for his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. His research group has also been actively involved in the development of highly selective catalytic systems allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions, and opening a new avenue for the utilization of biomass-derived platform chemicals. The results of his study have been introduced worldwide through many prestigious journals including Science, Nature Chemistry, and Nature Catalysis, making him one of the world's top 1% researchers by the number of references made to his papers by his peers over four consecutive years from 2015 to 2018. Vice Chairman Kim, who received his M.E. degree from KAIST’s School of Electrical Engineering in 1983, has been credited with playing a leading role in the development of system semiconductors. The awards were conferred on July 4 at the opening ceremony of the 2019 Korea Science and Technology Annual Meeting. (END)
2019.07.09 View 9551
Micropatch Made of DNA Researchers reported the fabrication of microstructure arrays of DNA materials using topographic control. This method provides a platform for forming multiscale hierarchical orientations of soft and biomaterials using a process of simple shearing and controlled evaporation on a patterned substrate. This approach enables the potential of patterning applications using DNA or other anisotropic biomaterials. DNA is one of the most abundant biomaterials found in all living organisms in nature. It has unique characteristics of fine feature size and liquid crystalline phase, enabling to create various kinds of microstructure DNA arrays. Based on these characteristics, DNA has been used as a building block for “origami” and textile art at the nanometer scale. A KAIST research team led by Professors Dong Ki Yoon and Hyungsoo Kim fabricated a DNA-based micropatch using the “coffee ring effect” and its multi-angle control technology, which was published online in Nature Communications on June 7. The research team used cheap DNA material extracted from salmon to realize the micropatch structure with well-aligned knit or ice cream cone shapes. When the DNA material in an aqueous solution is rubbed between two solid substrates while water is evaporating, DNA chains are unidirectionally aligned to make a thin film such as in LCD display devices. The DNA chains can make more complex microstructures such as knit or a texture with ice cream cone shapes when the same procedure is carried out in topographical patterns like microposts (Figure 1). This can be applied to make metamaterials by mixing with functionalized gold nanorods to show plasmonic color. Plasmon resonance is a phenomenon in which electrons vibrate uniformly on the surface of a substrate made of metal, reacting only to light that matches a specific energy to enhance the clarity and expression of colors. For this, the most important factor is the orientation in which the gold nanorods align. That is, when the rods are aligned side by side in one direction, the optical and electrical characteristics are maximized. The research team focused on this point and made the DNA micropatch as a frame to orient the gold nanorods in a unique shape and fabricated a plasmonic color film (Figure 2). Professor Yoon said this study is meaningful in that it deals with the evaporation phenomenon, which has not been studied much in the field of polymers and biopolymers in terms of basic science. He explained, “This will also help maximize the efficiency of polymeric materials that can be orientated in coating, 2D, and 3D printing applications. Furthermore, DNA that exists infinitely in nature can be expected to have industrial application value as a new material since it can easily form complexes with other materials as described in this study.” (Figure 1. The DNA micropatch using topographic control. (a) The experimental scheme. (b) Enlarged image of (e). (c-e) Different micropatches made of DNA using different shearing directions.) (Figure 2. The knit-like structures made of DNA-gold nanorod complex. (a,b) Optical and polarized optical microscopy images. (c-f) Plasmonic colors reflected from aligned DNA-gold nanorod complex depending on the sample rotation.)
2019.07.01 View 32508
Anti-drone Technology for Anti-Terrorism Applications (from top right clockwise: Professor Yongdae Kim, PhD Candidates Yujin Kwon, Juhwan Noh, Hocheol Shin, and Dohyun Kim) KAIST researchers have developed anti-drone technology that can hijack other drones by spoofing its location using fake GPS signals. This technology can safely guide a drone to a desired location without any sudden change in direction in emergency situations, and thus respond effectively to dangerous drones such as those intending to carry out acts of terrorism. Advancements in the drone industry have led to the wider use of drones in our daily lives in areas of reconnaissance, searching and rescuing, disaster prevention and response, and delivery services. At the same time, there has also been a growing concern about privacy, safety, and security issues regarding drones, especially those arising from intrusion into private property and secure facilities. Therefore, the anti-drone industry is rapidly expanding to detect and respond to this possible drone invasion. The current anti-drone systems used in airports and other key locations utilize electronic jamming signals, high-power lasers, or nets to neutralize drones. For example, drones trespassing on airports are often countered with simple jamming signals that can prevent the drones from moving and changing position, but this may result in a prolonged delay in flight departures and arrivals at the airports. Drones used for terrorist attacks – armed with explosives or weapons – must also be neutralized a safe distance from the public and vital infrastructure to minimize any damage. Due to this need for a new anti-drone technology to counter these threats, a KAIST research team led by Professor Yongdae Kim from the School of Electrical Engineering has developed technology that securely thwarts drones by tricking them with fake GPS signals. Fake GPS signals have been used in previous studies to cause confusion inside the drone regarding its location, making the drone drift from its position or path. However, such attack tactics cannot be applied in GPS safety mode. GPS safety mode is an emergency mode that ensures drone safety when the signal is cut or location accuracy is low due to a fake GPS signals. This mode differs between models and manufacturers. Professor Kim’s team analyzed the GPS safety mode of different drone models made from major drone manufacturers such as DJI and Parrot, made classification systems, and designed a drone abduction technique that covers almost all the types of drone GPS safety modes, and is universally applicable to any drone that uses GPS regardless of model or manufacturer. The research team applied their new technique to four different drones and have proven that the drones can be safely hijacked and guided to the direction of intentional abduction within a small margin of error. Professor Kim said, “Conventional consumer drones equipped with GPS safety mode seem to be safe from fake GPS signals, however, most of these drones are able to be detoured since they detect GPS errors in a rudimentary manner.” He continued, “This technology can contribute particularly to reducing damage to airports and the airline industry caused by illegal drone flights.” The research team is planning to commercialize the developed technology by applying it to existing anti-drone solutions through technology transfer.” This research, featured in the ACM Transactions on Privacy and Security (TOPS) on April 9, was supported by the Defense Acquisition Program Administration (DAPA) and the Agency for Defense Development (ADD). Image 1. Experimental environment in which a fake GPS signal was produced from a PC and injected into the drone signal using directional antennae Publication: Juhwan Noh, Yujin Kwon, Yunmok Son, Hocheol Shin, Dohyun Kim, Jaeyeong Choi, and Yongdae Kim. 2019. Tractor Beam: Safe-hijacking of Consumer Drones with Adaptive GPS Spoofing. ACM Transactions on Privacy and Security. New York, NY, USA, Vol. 22, No. 2, Article 12, 26 pages. https://doi.org/10.1145/3309735 Profile: Prof. Yongdae Kim, MS, PhD yongdaek@kaist.ac.kr https://www.syssec.kr/ Professor School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Juhwan Noh, PhD Candidate juhwan@kaist.ac.kr PhD Candidate System Security (SysSec) Lab School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea (END)
2019.06.25 View 42150

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