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Distinguished Professor Sukbok Chang Donates His Prize Money
The honoree of the 2019 Korea Best Scientist and Technologist Award, Distinguished Professor Sukbok Chang donated his prize money of one hundred million KRW to the Chemistry Department Scholarship Fund and the Lyu Keun-Chul Sports Complex Management Fund during a donation ceremony last week.
Professor Chang won the award last month in recognition of his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. Professor Chang, a world renowned chemist, has been recognized for his 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.
“All my achievements are the results of my students’ hard work and dedication. I feel very fortunate to have such talented team members. I want to express my sincere gratitude for such a great research environment that we have worked together in so far,” said Professor Chang at the ceremony.
KAIST President Sung-Chul Shin said, “Not only will Professor Chang’s donation make a significant contribution to the Department of Chemistry, but also to the improvement of the Lyu Keun-Chul Sports Complex’s management, which directly links to the health and welfare of the KAIST community.”
Professor Chang currently holds the position of distinguished professor at KAIST and director of the Center for Catalytic Hydrocarbon Functionalizations in the Institute for Basic Science (IBS). He previously received the Kyung-Ahm Academic Award in 2013 and the Korea Toray Science Award in 2018. All these prize money also went to the school.
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2019.08.26 View 8319 -
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 28810 -
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 33432 -
'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.”
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2019.07.26 View 12451 -
Newly Identified Meningeal Lymphatic Vessels Answers the Key Questions on Brain Clearance
(Figure: Schematic images of location and features of meningeal lymphatic vessels and their changes associated with ageing.)
Just see what happens when your neighborhood’s waste disposal system is out of service. Not only do the piles of trash stink but they can indeed hinder the area’s normal functioning. That is also the case when the brain’s waste management is on the blink.
The buildup of toxic proteins in the brain causes a massive damage to the nerves, leading to cognitive dysfunction and increased probability of developing neurodegenerative disorders such as Alzheimer's disease. Though the brain drains its waste via the cerebrospinal fluid (CSF), little has been understood about an accurate route for the brain’s cleansing mechanism.
Medical scientists led by Professor Gou Young Koh at the Graduate School of Medical Science and Engineering have reported the basal side of the skull as the major route, so called “hotspot” for CSF drainage.
They found that basal meningeal lymphatic vessels (mLVs) function as the main plumbing pipes for CSF. They confirmed macromolecules in the CSF mainly runs through the basal mLVs. Notably, the team also revealed that the brain’s major drainage system, specifically basal mLVs are impaired with aging. Their findings have been reported in the journal Nature on July 24.
Throughout our body, excess fluids and waste products are removed from tissues via lymphatic vessels. It was only recently discovered that the brain also has a lymphatic drainage system. mLVs are supposed to carry waste from the brain tissue fluid and the CSF down the deep cervical lymph nodes for disposal. Still scientist are left with one perplexing question — where is the main exit for the CSF? Though mLVs in the upper part of the skull (dorsal meningeal lymphatic vessels) were reported as the brain’s clearance pathways in 2014, no substantial drainage mechanism was observed in that section.
“As a hidden exit for CSF, we looked into the mLVs trapped within complex structures at the base of the skull,” says Dr. Ji Hoon Ahn, the first author of this study. The researchers used several techniques to characterize the basal mLVs in detail. They used a genetically engineered lymphatic-reporter mouse model to visualize mLVs under a fluorescence microscope. By performing a careful examination of the mice skull, they found distinctive features of basal mLVs that make them suitable for CSF uptake and drainage. Just like typical functional lymphatic vessels, basal mLVs are found to have abundant lymphatic vessel branches with finger-like protrusions. Additionally, valves inside the basal mLVs allow the flow to go in one direction. In particular, they found that the basal mLVs are closely located to the CSF. Dr. Hyunsoo Cho, the first author of this study explains, “All up, it seemed a solid case that basal mLVs are the brain’s main clearance pathways.
The researchers verified such specialized morphologic characteristics of basal mLVs indeed facilitate the CSF uptake and drainage. Using CSF contrast-enhanced magnetic resonance imaging in a rat model, they found that CSF is drained preferentially through the basal mLVs. They also utilized a lymphatic-reporter mouse model and discovered that fluorescence-tagged tracer injected into the brain itself or the CSF is cleared mainly through the basal mLVs. Jun-Hee Kim, the first author of this study notes, “We literally saw that the brain clearance mechanism utilizing basal outflow route to exit the skull.
It has long been suggested that CSF turnover and drainage declines with ageing. However, alteration of mLVs associated with ageing is poorly understood. In this study, the researchers observed changes of mLVs in young (3-month-old) and aged (24~27-months-old) mice. They found that the structure of the basal mLVs and their lymphatic valves in aged mice become severely flawed, thus hampering CSF clearance. The corresponding author of this study, Dr. Koh says, “By characterizing the precise route for fluids leaving the brain, this study improves our understanding on how waste is cleared from the brain. Our findings also provide further insights into the role of impaired CSF clearance in the development of age-related neurodegenerative diseases.”
Many current therapies for Alzheimer’s disease target abnormally accumulated proteins, such as beta-amyloid. By mapping out a precise route for the brain’s waste clearance system, this study may be able to help find ways to improve the brain’s cleansing function. Such breakthrough might become quite a sensational strategy for eliminating the buildup of aging-related toxic proteins. “It definitely warrants more extensive investigation of mLVs in patients with age-related neurodegenerative disease such as Alzheimer’s disease prior to clinical investigation,” adds Professor Koh.
2019.07.25 View 32503 -
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 35961 -
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 37341 -
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.
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2019.07.09 View 12164 -
Wearable Robot 'WalkON Suit' Off to Cybathlon 2020
Standing upright and walking alone are very simple but noble motions that separate humans from many other creatures. Wearable and prosthetic technologies have emerged to augment human function in locomotion and manipulation. However, advances in wearable robot technology have been especially momentous to Byoung-Wook Kim, a triplegic for 22 years following a devastating car accident.
Kim rejoiced after standing upright and walking again by putting on the ‘WalkON Suit,’ the wearable robot developed by Professor Kyoungchul Kong’s team. Even more, Kim won third prize in the powered exoskeleton race at Cybathlon 2016, an international cyborg Olympics hosted by ETH Zurich.
Now Kim and Professor Kong’s team are all geared up for the Cybathlon Championship 2020. Professor Kong and his startup, Angel Robotics, held a kickoff ceremony for Cybathlon 2020 at KAIST on June 24. The 2020 championship will take place in Switzerland.
Only pilots with complete paralysis of the legs resulting from spinal cord injuries are eligible to participate in the Cybathlon, which takes place every four years. Pilots compete against each other while completing everyday tasks using technical assistance systems in six different disciplines: a brain-computer interface race, a functional electrical stimulation bike race, a powered arm prosthesis race, a powered leg prosthesis race, a powered exoskeleton race, and a powered wheelchair race. The 2016 championship drew 66 pilots from 56 teams representing 25 countries.
In the powered exoskeleton race, pilots complete everyday activities such as getting up from a sofa and overcoming obstacles such as stairs, ramps, or slopes and up to four pilots compete simultaneously on tracks to solve six tasks; and the pilot that solves the most tasks in the least amount of time wins the race.
(Kim, a triplegic for 22 years demonstrates walking and climbing the stairs (below photo) wearing the WalkOn Suit during the media day on June 21 at KAIST.)
Kim, who demonstrated walking and climbing the stairs wearing the WalkON Suit during the media day for the Cybathlon 2020 kickoff ceremony on June 21 at KAIST, said, “I have been confined to a wheelchair for more than 20 years. I am used to it so I feel like the wheelchair is one of my body parts. Actually, I don’t feel any big difficulties in doing everyday tasks in wheelchair. But whenever I face the fact that I will never be able to stand up with my own two legs again, I am so devastated.” He continued, “I still remember the day when I stood up with my own two legs by myself after 22 years. It was beyond description.”
The market for wearable robots, especially for exoskeleton robots, is continuing to grow as the aging population has been a major challenge in almost every advanced country. The global market for these robots expects to see annual growth of 41.2% to 8.3 billion US dollars by 2025. Healthcare wearable robots for the elderly and rehabilitation take up the half of the market share followed by wearable robots for industrial and defense purposes.
Professor Kong from the Department of Mechanical Engineering and his colleagues have developed two wearable robot systems in 2014: The "WalkON Suit" for complete paraplegics and “Angel Suit” for those with partial impairment in walking ability such as the elderly and rehabilitation patients.
Professor Kong said after 15 years of basic research, the team is now able to develop its own distinct technologies. He said their robots are powered by non-resistant precision drives with algorithms recognizing the user’s moving intention. Incorporated with prosthetic devices technology from the Severance Rehabilitation Hospital, their control technology has led to the production of a customizable robot suit optimized for each user’s physical condition.
The WalkON Suit, which boasts a maximum force of 250 Nm and maximum rotation speed of 45 RPM, gives the user high-energy efficiency modeled after the physiology of the human leg. It allows users to walk on flat ground and down stairs, climb up and down inclines, and sit and lie down. Currently the battery lasts five to six hours for locomotion and the approximate 25 kg of robot weight still remains a technical challenge to upgrade.
Professor Kong’s team has grafted AR glass technology into the WalkOn Suit that one of his pilots put on for the torch relay of the PyongChang Paralympics in 2018. His team is now upgrading the WalkON Suit 4.0 for next year’s competition. Severance Rehabilitation Hospital will help the seven pilots with their training.
Professor Kong said his goal is to make robots that can make people with disabilities much more independent. He stressed, “Wearable robots should be designed for each single user. We provide a very good graphical user interface so that we can design, check, and also verify our optimized design for users’ best performance.”
(Seven pilots and Professor Kong (fifth from left in second row) pose with guests who joined the Cybathlon 2020 kickoff ceremony. President Shin (fifth from right) made a congratulatory remarks during the ceremony.)
2019.06.25 View 40693 -
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 43955 -
Hydrogen-Natural Gas Hydrates Harvested by Natural Gas
A hydrogen-natural gas blend (HNGB) can be a game changer only if it can be stored safely and used as a sustainable clean energy resource. A recent study has suggested a new strategy for stably storing hydrogen, using natural gas as a stabilizer. The research proposed a practical gas phase modulator based synthesis of HNGB without generating chemical waste after dissociation for the immediate service.
The research team of Professor Jae Woo Lee from the Department of Chemical and Biomolecular Engineering in collaboration with the Gwangju Institute of Science and Technology (GIST) demonstrated that the natural gas modulator based synthesis leads to significantly reduced synthesis pressure simultaneously with the formation of hydrogen clusters in the confined nanoporous cages of clathrate hydrates. This approach minimizes the environmental impact and reduces operation costs since clathrate hydrates do not generate any chemical waste in both the synthesis and decomposition processes.
For the efficient storage and transportation of hydrogen, numerous materials have been investigated. Among others, clathrate hydrates offer distinct benefits. Clathrate hydrates are nanoporous inclusion compounds composed of a 3D network of polyhedral cages made of hydrogen-bonded ‘host’ water molecules and captured ‘guest’ gas or liquid molecules.
In this study, the research team used two gases, methane and ethane, which have lower equilibrium conditions compared to hydrogen as thermodynamic stabilizers. As a result, they succeeded in stably storing the hydrogen-natural gas compound in hydrates. According to the composition ratio of methane and ethane, structure I or II hydrates can be formed, both of which can stably store hydrogen-natural gas in low-pressure conditions.
The research team found that two hydrogen molecules are stored in small cages in tuned structure I hydrates, while up to three hydrogen molecules can be stored in both small and large cages in tuned structure II hydrates. Hydrates can store gas up to about 170-times its volume and the natural gas used as thermodynamic stabilizers in this study can also be used as an energy source.
The research team developed technology to produce hydrates from ice, produced hydrogen-natural gas hydrates by substitution, and successfully observed that the tuning phenomenon only occurs when hydrogen is involved in hydrate formation from the start for both structures of hydrates.
They expect that the findings can be applied to not only an energy-efficient gas storage material, but also a smart platform to utilize hydrogen natural gas blends, which can serve as a new alternative energy source with targeted hydrogen contents by designing synthetic pathways of mixed gas hydrates.
The research was published online in Energy Storage Materials on June 6, with the title ‘One-step formation of hydrogen clusters in clathrate hydrates stabilized via natural gas blending’.
Professor Lee said, “HNGB will utilize the existing natural gas infrastructure for transportation, so it is very likely that we can commercialize this hydrate system. We are investigating the kinetic performance through a follow-up strategy to increase the volume of gas storage.
This study was funded by the National Research Foundation of Korea and BK21 plus program.
(Figure1. Schematics showing the storage method for hydrogen in a natural gas hydrate using a substitution method and storage method directly from ice to a hydrogen-natural gas hydrate.)
(Figure 2. Artificially synthesized and dissociated hydrogen-natural gas hydrates. The Raman spectra of tuned sI and sII hydrate showing the hydrogen clusters in each cage.)
2019.06.21 View 41375 -
Efficiently Producing Fatty Acids and Biofuels from Glucose
Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.
The newly developed strain, created by Distinguished Professor Sang Yup Lee and his team, showed the highest efficiency in producing fatty acids and biodiesels ever reported. It will be expected to serve as a new platform to sustainably produce a wide array of fatty acid-based products from glucose and other carbon substrates.
Fossil fuels, which have long been energy resources for our daily lives, are now facing serious challenges: depletion of their reserves and their role in global warming. The production of sustainable bio-based renewable energy has emerged as an essential alternative and many studies to replace fossil fuels are underway. One of the representative examples is biodiesel. Currently, it is mainly being produced through the transesterification of vegetable oils or animal fats.
The research team engineered oleaginous microorganisms, Rhodococcus opacus, to produce fatty acids and their derivatives that can be used as biodiesel from glucose, one of the most abundant and cheap sugars derived from non-edible biomass.
Professor Lee’s team has already engineered Escherichia coli to produce short-chain hydrocarbons, which can be used as gasoline (published in Nature as the cover paper in 2013). However, the production efficiency of the short-chain hydrocarbons using E. coli (0.58 g/L) fell short of the levels required for commercialization.
To overcome these issues, the team employed oil-accumulating Rhodococcus opacus as a host strain in this study. First, the team optimized the cultivation conditions of Rhodococcus opacus to maximize the accumulation of oil (triacylglycerol), which serves as a precursor for the biosynthesis of fatty acids and their derivatives. Then, they systematically analyzed the metabolism of the strain and redesigned it to enable higher levels of fatty acids and two kinds of fatty acid-derived biodiesels (fatty acid ethyl esters and long-chain hydrocarbons) to be produced.
They found that the resulting strains produced 50.2, 21.3, and 5.2 g/L of fatty acids, fatty acid ethyl esters, and long-chain hydrocarbons, respectively. These are all the highest concentrations ever reported by microbial fermentations. It is expected that these strains can contribute to the future industrialization of microbial-based biodiesel production.
“This technology creates fatty acids and biodiesel with high efficiency by utilizing lignocellulose, one of the most abundant resources on the Earth, without depending on fossil fuels and vegetable or animal oils. This will provide new opportunities for oil and petroleum industries, which have long relied on fossil fuels, to turn to sustainable and eco-friendly biotechnologies,” said Professor Lee.
This paper titled “Engineering of an oleaginous bacterium for the production of fatty acids and fuels” was published in Nature Chemical Biology on June 17.
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 (NRF) of Korea (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557).
(Figure: Metabolic engineering for the production of free fatty acids (FFAs), fatty acid ethyl esters (FAEEs), and long-chain hydrocarbons (LCHCs) in Rhodococcus opacus PD630. Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.)
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Source:
Hye Mi Kim, Tong Un Chae, So Young Choi, Won Jun Kim and Sang Yup Lee. Engineering of an oleaginous bacterium for the production of fatty acids and fuels. Nature Chemical Biology ( https://www.nature.com/nchembio/ ) DOI: 10.1038/s41589-019-0295-5
Profile
Dr. Sang Yup Lee
leesy@kaist.ac.kr
Distinguished Professor at the Department of Chemical and Biomolecular Engineering
KAIST
2019.06.19 View 49164