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KAIST Mobile Clinic Module to Fill Negative Pressure Ward Shortage
Efficient versatile ready-for-rapid building system of MCM will serve as both a triage unit and bridge center in emergency medical situations A team from KAIST has developed a low-cost and ready-for-rapid-production negative pressure room called a Mobile Clinic Module (MCM). The MCM is expandable, moveable, and easy to store through a combination of negative pressure frames, air tents, and multi-function panels. The MCM expects to quickly meet the high demand for negative pressure beds in the nation and eventually many other countries where the third wave of COVID-19 is raging. The module is now ready to be rolled out after a three-week test period at the Korea Cancer Center Hospital. Professor Tek-Jin Nam’s team swung into action, rapidly working together with researchers, engineers with expertise in mechanical design, and a team of clinical doctors to complete the MCM as one of KAIST’s New Deal R&D initiatives launched last July. Professor Nam cites ‘expandability’ as the key feature of the MCM. Eventually, it will serve as both a triage unit and bridge center in emergency medical situations. “The module is a very efficient and versatile unit building system. It takes approximately two hours to build the basic MCM unit, which comprises four negative pressure bed rooms, nurse’s station, locker room, and treatment room. We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms,” said Professor Nam. “It will also be helpful for managing less-severe patients who need to be monitored daily in quarantined rooms or as bridge stations where on-site medical staff can provide treatment and daily monitoring before hospitalization. These wards can be efficiently deployed either inside or outside existing hospitals.” The research team specially designed the negative pressure frame to ensure safety level A for the negative pressure room, which is made of a multi-function panel wall and roofed with an air tent. The multi-function panels can hold medical appliances such as ventilators, oxygen and bio-signal monitors. Positive air pressure devices supply fresh air from outside the tent. An air pump and controller maintain air beam pressure, while filtering exhausted air. An internal air information monitoring system efficiently controls room air pressure and purifies the air. While a conventional negative pressure bed is reported to cost approximately 3.5 billion KRW (50 billion won for a ward), this module is estimated to cost 0.75 billion won each (10 billion won for a ward), cutting the costs by approximately 80%. The MCM is designed to be easily transported and relocated due to its volume, weight, and maintainability. This module requires only one-fourth of the volume of existing wards and takes up approximately 40% of their weight. The unit can be transported in a 40-foot container truck. “We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms. We look forward to the MCM upgrading epidemic management resources around the world.” Professor Nam’s team is also developing antiviral solutions and devices such as protective gear, sterilizers, and test kits under the KAIST New Deal R&D Initiative that was launched to promptly and proactively respond to the epidemic. More than 45 faculty members and researchers at KAIST are collaborating with industry and clinical hospitals to develop the antiviral technology that will improve preventive measures, diagnoses, and treatment.
2021.01.07
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DeepTFactor Predicts Transcription Factors
A deep learning-based tool predicts transcription factors using protein sequences as inputs A joint research team from KAIST and UCSD has developed a deep neural network named DeepTFactor that predicts transcription factors from protein sequences. DeepTFactor will serve as a useful tool for understanding the regulatory systems of organisms, accelerating the use of deep learning for solving biological problems. A transcription factor is a protein that specifically binds to DNA sequences to control the transcription initiation. Analyzing transcriptional regulation enables the understanding of how organisms control gene expression in response to genetic or environmental changes. In this regard, finding the transcription factor of an organism is the first step in the analysis of the transcriptional regulatory system of an organism. Previously, transcription factors have been predicted by analyzing sequence homology with already characterized transcription factors or by data-driven approaches such as machine learning. Conventional machine learning models require a rigorous feature selection process that relies on domain expertise such as calculating the physicochemical properties of molecules or analyzing the homology of biological sequences. Meanwhile, deep learning can inherently learn latent features for the specific task. A joint research team comprised of Ph.D. candidate Gi Bae Kim and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST, and Ye Gao and Professor Bernhard O. Palsson of the Department of Biochemical Engineering at UCSD reported a deep learning-based tool for the prediction of transcription factors. Their research paper “DeepTFactor: A deep learning-based tool for the prediction of transcription factors” was published online in PNAS. Their article reports the development of DeepTFactor, a deep learning-based tool that predicts whether a given protein sequence is a transcription factor using three parallel convolutional neural networks. The joint research team predicted 332 transcription factors of Escherichia coli K-12 MG1655 using DeepTFactor and the performance of DeepTFactor by experimentally confirming the genome-wide binding sites of three predicted transcription factors (YqhC, YiaU, and YahB). The joint research team further used a saliency method to understand the reasoning process of DeepTFactor. The researchers confirmed that even though information on the DNA binding domains of the transcription factor was not explicitly given the training process, DeepTFactor implicitly learned and used them for prediction. Unlike previous transcription factor prediction tools that were developed only for protein sequences of specific organisms, DeepTFactor is expected to be used in the analysis of the transcription systems of all organisms at a high level of performance. Distinguished Professor Sang Yup Lee said, “DeepTFactor can be used to discover unknown transcription factors from numerous protein sequences that have not yet been characterized. It is expected that DeepTFactor will serve as an important tool for analyzing the regulatory systems of organisms of interest.” 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. -Publication Gi Bae Kim, Ye Gao, Bernhard O. Palsson, and Sang Yup Lee. DeepTFactor: A deep learning-based tool for the prediction of transcription factors. (https://doi.org/10.1073/pnas202117118) -Profile Distinguished Professor Sang Yup Lee leesy@kaist.ac.kr Metabolic &Biomolecular Engineering National Research Laboratory http://mbel.kaist.ac.kr Department of Chemical and Biomolecular Engineering KAIST
2021.01.05
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Astrocytes Eat Connections to Maintain Plasticity in Adult Brains
Developing brains constantly sprout new neuronal connections called synapses as they learn and remember. Important connections — the ones that are repeatedly introduced, such as how to avoid danger — are nurtured and reinforced, while connections deemed unnecessary are pruned away. Adult brains undergo similar pruning, but it was unclear how or why synapses in the adult brain get eliminated. Now, a team of KAIST researchers has found the mechanism underlying plasticity and, potentially, neurological disorders in adult brains. They published their findings on December 23 in Nature. “Our findings have profound implications for our understanding of how neural circuits change during learning and memory, as well as in diseases,” said paper author Won-Suk Chung, an assistant professor in the Department of Biological Sciences at KAIST. “Changes in synapse number have strong association with the prevalence of various neurological disorders, such as autism spectrum disorder, schizophrenia, frontotemporal dementia, and several forms of seizures.” Gray matter in the brain contains microglia and astrocytes, two complementary cells that, among other things, support neurons and synapses. Microglial are a frontline immunity defense, responsible for eating pathogens and dead cells, and astrocytes are star-shaped cells that help structure the brain and maintain homeostasis by helping to control signaling between neurons. According to Professor Chung, it is generally thought that microglial eat synapses as part of its clean-up effort in a process known as phagocytosis. “Using novel tools, we show that, for the first time, it is astrocytes and not microglia that constantly eliminate excessive and unnecessary adult excitatory synaptic connections in response to neuronal activity,” Professor Chung said. “Our paper challenges the general consensus in this field that microglia are the primary synapse phagocytes that control synapse numbers in the brain.” Professor Chung and his team developed a molecular sensor to detect synapse elimination by glial cells and quantified how often and by which type of cell synapses were eliminated. They also deployed it in a mouse model without MEGF10, the gene that allows astrocytes to eliminate synapses. Adult animals with this defective astrocytic phagocytosis had unusually increased excitatory synapse numbers in the hippocampus. Through a collaboration with Dr. Hyungju Park at KBRI, they showed that these increased excitatory synapses are functionally impaired, which cause defective learning and memory formation in MEGF10 deleted animals. “Through this process, we show that, at least in the adult hippocampal CA1 region, astrocytes are the major player in eliminating synapses, and this astrocytic function is essential for controlling synapse number and plasticity,” Chung said. Professor Chung noted that researchers are only beginning to understand how synapse elimination affects maturation and homeostasis in the brain. In his group’s preliminary data in other brain regions, it appears that each region has different rates of synaptic elimination by astrocytes. They suspect a variety of internal and external factors are influencing how astrocytes modulate each regional circuit, and plan to elucidate these variables. “Our long-term goal is understanding how astrocyte-mediated synapse turnover affects the initiation and progression of various neurological disorders,” Professor Chung said. “It is intriguing to postulate that modulating astrocytic phagocytosis to restore synaptic connectivity may be a novel strategy in treating various brain disorders.” This work was supported by the Samsung Science & Technology Foundation, the National Research Foundation of Korea, and the Korea Brain Research Institute basic research program. Other contributors include Joon-Hyuk Lee and Se Young Lee, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST); Ji-young Kim, Hyoeun Lee and Hyungju Park; Research Group for Neurovascular Unit, Korea Brain Research Institute (KBRI); Seulgi Noh, and Ji Young Mun, Research Group for Neural Circuit, KBRI. Kim, Noh and Park are also affiliated with the Department of Brain and Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST). -Profile Professor Won-Suk Chung Department of Biological Sciences Gliabiology Lab (https://www.kaistglia.org/) KAIST -Publication "Astrocytes phagocytose adult hippocampal synapses for circuit homeostasis" https://doi.org/10.1038/s41586-020-03060-3
2020.12.24
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Electrosprayed Micro Droplets Help Kill Bacteria and Viruses
With COVID-19 raging around the globe, researchers are doubling down on methods for developing diverse antimicrobial technologies that could be effective in killing a virus, but harmless to humans and the environment. A recent study by a KAIST research team will be one of the responses to such efforts. Professor Seung Seob Lee and Dr. Ji-hun Jeong from the Department of Mechanical Engineering developed a harmless air sterilization prototype featuring electrosprayed water from a polymer micro-nozzle array. This study is one of the projects being supported by the KAIST New Deal R&D Initiative in response to COVID-19. Their study was reported in Polymer. The electrosprayed microdroplets encapsulate reactive oxygen species such as hydroxyl radicals, superoxides that are known to have an antimicrobial function. The encapsulation prolongs the life of reactive oxygen species, which enable the droplets to perform their antimicrobial function effectively. Prior research has already proven the antimicrobial and encapsulation effects of electrosprayed droplets. Despite its potential for antimicrobial applications, electrosprayed water generally operates under an electrical discharge condition, which can generate ozone. The inhalation of ozone is known to cause damage to the respiratory system of humans. Another technical barrier for electrospraying is the low flow rate problem. Since electrospraying exhibits the dependence of droplet size on the flow rate, there is a limit for the amount of water microdroplets a single nozzle can produce. With this in mind, the research team developed a dielectric polymer micro-nozzle array to perform the multiplexed electrospraying of water without electrical discharge. The polymer micro-nozzle array was fabricated using the MEMS (Micro Electro-Mechanical System) process. According to the research team, the nozzle can carry five to 19 micro-nozzles depending on the required application. The high aspect ratio of the micro-nozzle and an in-plane extractor were proposed to concentrate the electric field at the tip of the micro-nozzle, which prevents the electrical discharge caused by the high surface tension of water. A micro-pillar array with a hydrophobic coating around the micro-nozzle was also proposed to prevent the wetting of the micro-nozzle array. The polymer micro-nozzle array performed in steady cone jet mode without electrical discharge as confirmed by high-speed imaging and nanosecond pulsed imaging. The water microdroplets were measured to be in the range of six to 10 μm and displayed an antimicrobial effect on Escherichia coli and Staphylococcus aureus. Professor Lee said, “We believe that this research can be applied to air conditioning products in areas that require antimicrobial and humidifying functions.” Publication: Jeong, J. H., et al. (2020) Polymer micro-atomizer for water electrospray in the cone jet mode. Polymer. Vol. No. 194, 122405. Available online at https://doi.org/10.1016/j.polymer.2020.122405 Profile: Seung Seob Lee, Ph.D. sslee97@kaist.ac.kr http://mmst.kaist.ac.kr/ Professor Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Ji-hun Jeong, Ph.D. jiuni6022@kaist.ac.kr Postdoctoral researcher Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2020.12.21
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Mystery Solved with Math: Cytoplasmic Traffic Jam Disrupts Sleep-Wake Cycles
KAIST mathematicians and their collaborators at Florida State University have identified the principle of how aging and diseases like dementia and obesity cause sleep disorders. A combination of mathematical modelling and experiments demonstrated that the cytoplasmic congestion caused by aging, dementia, and/or obesity disrupts the circadian rhythms in the human body and leads to irregular sleep-wake cycles. This finding suggests new treatment strategies for addressing unstable sleep-wake cycles. Human bodies adjust sleep schedules in accordance with the ‘circadian rhythms’, which are regulated by our time keeping system, the ‘circadian clock’. This clock tells our body when to rest by generating the 24-hour rhythms of a protein called PERIOD (PER) (See Figure 1). The amount of the PER protein increases for half of the day and then decreases for the remaining half. The principle is that the PER protein accumulating in the cytoplasm for several hours enters the cell nucleus all at once, hindering the transcription of PER genes and thereby reducing the amount of PER. However, it has remained a mystery how thousands of PER molecules can simultaneously enter into the nucleus in a complex cell environment where a variety of materials co-exist and can interfere with the motion of PER. This would be like finding a way for thousands of employees from all over New York City to enter an office building at the same time every day. A group of researchers led by Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences solved the mystery by developing a spatiotemporal and probabilistic model that describes the motion of PER molecules in a cell environment. This study was conducted in collaboration with Professor Choogon Lee’s group from Florida State University, where the experiments were carried out, and the results were published in the Proceedings of the National Academy of Sciences (PNAS) last month. The joint research team’s spatial stochastic model (See Figure 2) described the motion of PER molecules in cells and demonstrated that the PER molecule should be sufficiently condensed around the cell nucleus to be phosphorylated simultaneously and enter the nucleus together (See Figure 3 Left). Thanks to this phosphorylation synchronization switch, thousands of PER molecules can enter the nucleus at the same time every day and maintain stable circadian rhythms. However, when aging and/or diseases including dementia and obesity cause the cytoplasm to become congested with increased cytoplasmic obstacles such as protein aggregates and fat vacuoles, it hinders the timely condensation of PER molecules around the cell nucleus (See Figure 3 Right). As a result, the phosphorylation synchronization switch does not work and PER proteins enter into the nucleus at irregular times, making the circadian rhythms and sleep-wake cycles unstable, the study revealed. Professor Kim said, “As a mathematician, I am excited to help enable the advancement of new treatment strategies that can improve the lives of so many patients who suffer from irregular sleep-wake cycles. Taking these findings as an opportunity, I hope to see more active interchanges of ideas and collaboration between mathematical and biological sciences.” This work was supported by the National Institutes of Health and the National Science Foundation in the US, and the International Human Frontiers Science Program Organization and the National Research Foundation of Korea. Publication: Beesley, S. and Kim, D. W, et al. (2020) Wake-sleep cycles are severely disrupted by diseases affecting cytoplasmic homeostasis. Proceedings of the National Academy of Sciences (PNAS), Vol. 117, No. 45, 28402-28411. Available online at https://doi.org/10.1073/pnas.2003524117 Profile: Jae Kyoung Kim, Ph.D. Associate Professor jaekkim@kaist.ac.kr http://mathsci.kaist.ac.kr/~jaekkim @umichkim on Twitter Department of Mathematical Sciences Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea Profile: Choogon Lee, Ph.D. Associate Professor clee@neuro.fsu.edu https://med.fsu.edu/biosci/lee-lab Department of Biomedical Sciences Florida State University Florida, USA (END)
2020.12.11
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Three Professors Named to Highly Cited Researchers 2020 List
Distinguished Professor Sukbok Chang from the Department of Chemistry, Distinguished Professor Sang-Yup Lee from the Department of Chemical & Biomolecular Engineering, and Professor Jiyong Eom from the College of Business were named to Clarivate’s Highly Cited Researchers 2020 list. Clarivate announced the researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. A total of 6,167 researchers from more than 60 countries were listed this year and 37 Korean scholars made the list. The methodology that determines the “Who’s Who” of influential researchers draws on data and analyses performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based. More than 6,000 researchers from 21 fields in the sciences, social sciences, and cross field categories were selected based on the number of highly cited papers they produced over an 11-year period from January 2009 to December 2019. Professor Chang made the list six years in a row, while Professor Lee made it for four consecutive years, and Professor Eom for the last two years. Professor Chang’s group (http://sbchang.kaist.ac.kr) investigates catalytic hydrocarbon functionalization. Professor Lee (http://mbel.kaist.ac.kr) is a pioneering scholar in the field of metabolic engineering, systems, and synthetic biology. Professor Eom’s (https://kaistceps.quv.kr) research extends to energy and environmental economics and management, energy big data, and green information systems.
2020.11.30
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Feel the Force with ElaStick
ElaStick, a handheld variable stiffness display, renders the dynamic haptic response of a flexible object Haptic controllers play an important role in providing rich and immersive virtual reality experiences. Professor Andrea Bianchi’s team in the Department of Industrial Design recreated the haptic response of flexible objects made of different materials and with different shapes by changing the stiffness of a custom-controller – ElaStick. ElaStick is a portable hand-held force-feedback controller that is capable of rendering the illusion of how flexible and deformable objects feel when held in the hand. This VR haptic controller can change its stiffness in two directions independently and continuously. Since providing haptic feedback enhances the VR experience, researchers have suggested numerous approaches for rendering the physical properties of virtual objects - such as weights, the movement of mass, impacts, and damped oscillations. The research team designed a new mechanism based on a quaternion joint and four variable-stiffness tendons. The quaternion joint is a two-DoF bending joint that enables ElaStick to bend and oscillate in any direction using a pair of tendons with varying stiffness. In fact, each tendon around the joint is made of a series of elastic rubber bands and inelastic fishing lines and can vary its stiffness by changing the proportion of the two materials. Thanks to these structures, each pair of tendons can behave independently, controlling the anisotropic characteristics of the entire device. “The main challenge was to implement the mechanism to control the stiffness while maintaining independence between deformations in two perpendicular directions,” said Professor Bianchi. The research team successfully measured the relative threshold of human perception on the stiffness of a handheld object. The results showed that the just-noticeable difference (JND) of human perception of stiffness is at most about 30% of the change from the initial value. It also found that appropriate haptic responses significantly enhance the quality of the VR experience. The research team surveyed the perceived realism, immersion, and enjoyment of participants after they played with various flexible objects in VR. “It is meaningful that the haptic feedback of a flexible object was mechanically reproduced and its effectiveness in VR was proven. ElaStick has succeeded in implementing a novel mechanism to recreate the dynamic response of flexible objects that mimic real ones, suggesting a new category of haptic feedback that can be provided in VR,” explained Professor Bianchi. The team plans to extend the ElaStick’s applications, from being used merely as a game controller to driving simulations, medical training, and many other digital contexts. This research, led by MS candidate Neung Ryu, won the Best Paper Award at the ACM UIST 2020 (the ACM Symposium on User Interface Software & Technology) last month. -ProfileProfessor Andrea BianchiMakinteract.kaist.ac.krDepartment of Industrial DesignKAIST
2020.11.23
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To Talk or Not to Talk: Smart Speaker Determines Optimal Timing to Talk
A KAIST research team has developed a new context-awareness technology that enables AI assistants to determine when to talk to their users based on user circumstances. This technology can contribute to developing advanced AI assistants that can offer pre-emptive services such as reminding users to take medication on time or modifying schedules based on the actual progress of planned tasks. Unlike conventional AI assistants that used to act passively upon users’ commands, today’s AI assistants are evolving to provide more proactive services through self-reasoning of user circumstances. This opens up new opportunities for AI assistants to better support users in their daily lives. However, if AI assistants do not talk at the right time, they could rather interrupt their users instead of helping them. The right time for talking is more difficult for AI assistants to determine than it appears. This is because the context can differ depending on the state of the user or the surrounding environment. A group of researchers led by Professor Uichin Lee from the KAIST School of Computing identified key contextual factors in user circumstances that determine when the AI assistant should start, stop, or resume engaging in voice services in smart home environments. Their findings were published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) in September. The group conducted this study in collaboration with Professor Jae-Gil Lee’s group in the KAIST School of Computing, Professor Sangsu Lee’s group in the KAIST Department of Industrial Design, and Professor Auk Kim’s group at Kangwon National University. After developing smart speakers equipped with AI assistant function for experimental use, the researchers installed them in the rooms of 40 students who live in double-occupancy campus dormitories and collected a total of 3,500 in-situ user response data records over a period of a week. The smart speakers repeatedly asked the students a question, “Is now a good time to talk?” at random intervals or whenever a student’s movement was detected. Students answered with either “yes” or “no” and then explained why, describing what they had been doing before being questioned by the smart speakers. Data analysis revealed that 47% of user responses were “no” indicating they did not want to be interrupted. The research team then created 19 home activity categories to cross-analyze the key contextual factors that determine opportune moments for AI assistants to talk, and classified these factors into ‘personal,’ ‘movement,’ and ‘social’ factors respectively. Personal factors, for instance, include: 1. the degree of concentration on or engagement in activities, 2. the degree urgency and busyness, 3. the state of user’s mental or physical condition, and 4. the state of being able to talk or listen while multitasking. While users were busy concentrating on studying, tired, or drying hair, they found it difficult to engage in conversational interactions with the smart speakers. Some representative movement factors include departure, entrance, and physical activity transitions. Interestingly, in movement scenarios, the team found that the communication range was an important factor. Departure is an outbound movement from the smart speaker, and entrance is an inbound movement. Users were much more available during inbound movement scenarios as opposed to outbound movement scenarios. In general, smart speakers are located in a shared place at home, such as a living room, where multiple family members gather at the same time. In Professor Lee’s group’s experiment, almost half of the in-situ user responses were collected when both roommates were present. The group found social presence also influenced interruptibility. Roommates often wanted to minimize possible interpersonal conflicts, such as disturbing their roommates' sleep or work. Narae Cha, the lead author of this study, explained, “By considering personal, movement, and social factors, we can envision a smart speaker that can intelligently manage the timing of conversations with users.” She believes that this work lays the foundation for the future of AI assistants, adding, “Multi-modal sensory data can be used for context sensing, and this context information will help smart speakers proactively determine when it is a good time to start, stop, or resume conversations with their users.” This work was supported by the National Research Foundation (NRF) of Korea. Publication: Cha, N, et al. (2020) “Hello There! Is Now a Good Time to Talk?”: Opportune Moments for Proactive Interactions with Smart Speakers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 4, No. 3, Article No. 74, pp. 1-28. Available online at https://doi.org/10.1145/3411810 Link to Introductory Video: https://youtu.be/AA8CTi2hEf0 Profile: Uichin Lee Associate Professor uclee@kaist.ac.kr http://ic.kaist.ac.kr Interactive Computing Lab. School of Computing https://www.kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
2020.11.05
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Chemical Scissors Snip 2D Transition Metal Dichalcogenides into Nanoribbon
New ‘nanoribbon’ catalyst should slash cost of hydrogen production for clean fuels Researchers have identified a potential catalyst alternative – and an innovative way to produce them using chemical ‘scissors’ – that could make hydrogen production more economical. The research team led by Professor Sang Ouk Kim at the Department of Materials Science and Engineering published their work in Nature Communications. Hydrogen is likely to play a key role in the clean transition away from fossil fuels and other processes that produce greenhouse gas emissions. There is a raft of transportation sectors such as long-haul shipping and aviation that are difficult to electrify and so will require cleanly produced hydrogen as a fuel or as a feedstock for other carbon-neutral synthetic fuels. Likewise, fertilizer production and the steel sector are unlikely to be “de-carbonized” without cheap and clean hydrogen. The problem is that the cheapest methods by far of producing hydrogen gas is currently from natural gas, a process that itself produces the greenhouse gas carbon dioxide–which defeats the purpose. Alternative techniques of hydrogen production, such as electrolysis using an electric current between two electrodes plunged into water to overcome the chemical bonds holding water together, thereby splitting it into its constituent elements, oxygen and hydrogen are very well established. But one of the factors contributing to the high cost, beyond being extremely energy-intensive, is the need for the very expensive precious and relatively rare metal platinum. The platinum is used as a catalyst–a substance that kicks off or speeds up a chemical reaction–in the hydrogen production process. As a result, researchers have long been on the hunt for a substitution for platinum -- another catalyst that is abundant in the earth and thus much cheaper. Transition metal dichalcogenides, or TMDs, in a nanomaterial form, have for some time been considered a good candidate as a catalyst replacement for platinum. These are substances composed of one atom of a transition metal (the elements in the middle part of the periodic table) and two atoms of a chalcogen element (the elements in the third-to-last column in the periodic table, specifically sulfur, selenium and tellurium). What makes TMDs a good bet as a platinum replacement is not just that they are much more abundant, but also their electrons are structured in a way that gives the electrodes a boost. In addition, a TMD that is a nanomaterial is essentially a two-dimensional super-thin sheet only a few atoms thick, just like graphene. The ultrathin nature of a 2-D TMD nanosheet allows for a great many more TMD molecules to be exposed during the catalysis process than would be the case in a block of the stuff, thus kicking off and speeding up the hydrogen-making chemical reaction that much more. However, even here the TMD molecules are only reactive at the four edges of a nanosheet. In the flat interior, not much is going on. In order to increase the chemical reaction rate in the production of hydrogen, the nanosheet would need to be cut into very thin – almost one-dimensional strips, thereby creating many edges. In response, the research team developed what are in essence a pair of chemical scissors that can snip TMD into tiny strips. “Up to now, the only substances that anyone has been able to turn into these ‘nano-ribbons’ are graphene and phosphorene,” said Sang Professor Kim, one of the researchers involved in devising the process. “But they’re both made up of just one element, so it’s pretty straightforward. Figuring out how to do it for TMD, which is made of two elements was going to be much harder.” The ‘scissors’ involve a two-step process involving first inserting lithium ions into the layered structure of the TMD sheets, and then using ultrasound to cause a spontaneous ‘unzipping’ in straight lines. “It works sort of like how when you split a plank of plywood: it breaks easily in one direction along the grain,” Professor Kim continued. “It’s actually really simple.” The researchers then tried it with various types of TMDs, including those made of molybdenum, selenium, sulfur, tellurium and tungsten. All worked just as well, with a catalytic efficiency as effective as platinum’s. Because of the simplicity of the procedure, this method should be able to be used not just in the large-scale production of TMD nanoribbons, but also to make similar nanoribbons from other multi-elemental 2D materials for purposes beyond just hydrogen production. -ProfileProfessor Sang Ouk KimSoft Nanomaterials Laboratory (http://snml.kaist.ac.kr)Department of Materials Science and EngineeringKAIST
2020.10.29
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'Mini-Lungs' Reveal Early Stages of SARS-CoV-2 Infection
Researchers in Korea and the UK have successfully grown miniature models of critical lung structures called alveoli, and used them to study how the coronavirus that causes COVID-19 infects the lungs. To date, there have been more than 40 million cases of COVID-19 and almost 1.13 million deaths worldwide. The main target tissues of SARS-CoV-2, the virus that causes COVID-19, especially in patients that develop pneumonia, appear to be alveoli – tiny air sacs in the lungs that take up the oxygen we breathe and exchange it with carbon dioxide to exhale. To better understand how SARS-CoV-2 infects the lungs and causes disease, a team of Professor Young Seok Ju from the Graduate School of Medical Science and Engineering at KAIST in collaboration with the Wellcome-MRC Cambridge Stem Cell Institute at the University of Cambridge turned to organoids – ‘mini-organs’ grown in three dimensions to mimic the behaviour of tissue and organs. The team used tissue donated to tissue banks at the Royal Papworth Hospital NHS Foundation Trust and Addenbrooke’s Hospital, Cambridge University NHS Foundations Trust, UK, and Seoul National University Hospital to extract a type of lung cell known as human lung alveolar type 2 cells. By reprogramming these cells back to their earlier ‘stem cell’ stage, they were able to grow self-organizing alveolar-like 3D structures that mimic the behaviour of key lung tissue. “The research community now has a powerful new platform to study precisely how the virus infects the lungs, as well as explore possible treatments,” said Professor Ju, co-senior author of the research. Dr. Joo-Hyeon Lee, another co-senior author at the Wellcome-MRC Cambridge Stem Cell Institute, said: “We still know surprisingly little about how SARS-CoV-2 infects the lungs and causes disease. Our approach has allowed us to grow 3D models of key lung tissue – in a sense, ‘mini-lungs’ – in the lab and study what happens when they become infected.” The team infected the organoids with a strain of SARS-CoV-2 taken from a patient in Korea who was diagnosed with COVID-19 on January 26 after traveling to Wuhan, China. Using a combination of fluorescence imaging and single cell genetic analysis, they were able to study how the cells responded to the virus. When the 3D models were exposed to SARS-CoV-2, the virus began to replicate rapidly, reaching full cellular infection just six hours after infection. Replication enables the virus to spread throughout the body, infecting other cells and tissue. Around the same time, the cells began to produce interferons – proteins that act as warning signals to neighbouring cells, telling them to activate their antiviral defences. After 48 hours, the interferons triggered the innate immune response – its first line of defence – and the cells started fighting back against infection. Sixty hours after infection, a subset of alveolar cells began to disintegrate, leading to cell death and damage to the lung tissue. Although the researchers observed changes to the lung cells within three days of infection, clinical symptoms of COVID-19 rarely occur so quickly and can sometimes take more than ten days after exposure to appear. The team say there are several possible reasons for this. It may take several days from the virus first infiltrating the upper respiratory tract to it reaching the alveoli. It may also require a substantial proportion of alveolar cells to be infected or for further interactions with immune cells resulting in inflammation before a patient displays symptoms. “Based on our model we can tackle many unanswered key questions, such as understanding genetic susceptibility to SARS-CoV-2, assessing relative infectivity of viral mutants, and revealing the damage processes of the virus in human alveolar cells,” said Professor Ju. “Most importantly, it provides the opportunity to develop and screen potential therapeutic agents against SARS-CoV-2 infection.” “We hope to use our technique to grow these 3D models from cells of patients who are particularly vulnerable to infection, such as the elderly or people with diseased lungs, and find out what happens to their tissue,” added Dr. Lee. The research was a collaboration involving scientists from KAIST, the University of Cambridge, Korea National Institute of Health, Institute for Basic Science (IBS), Seoul National University Hospital and Genome Insight in Korea. - ProfileProfessor Young Seok JuLaboratory of Cancer Genomics https://julab.kaist.ac.kr the Graduate School of Medical Science and EngineeringKAIST
2020.10.26
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KAIST Showcases Healthcare Technologies at K-Hospital Fair 2020
KAIST Pavilion showcased its innovative medical and healthcare technologies and their advanced applications at the K-Hospital Fair 2020. Five KAIST research groups who teamed up for the Post-COVID-19 New Deal R&D Initiative Project participated in the fair held in Seoul last week. The K-Hospital Fair is a yearly event organized by the Korean Hospital Association to present the latest research and practical innovations to help the medical industry better serve the patients. This year, 120 healthcare organizations participated in the fair and operated 320 booths. At the fair, a research group led by Professor Il-Doo Kim from the Department of Materials Science and Engineering demonstrated the manufacturing process of orthogonal nanofibers used to develop their ‘recyclable nano-fiber filtered face mask’ introduced in March of this year. This mask has garnered immense international attention for maintaining its sturdy frame and filtering function even after being washed more than 20 times. Professor Kim is now extending his facilities for the mass production of this mask at his start-up company. While awaiting final approval from the Ministry of Food and Drug Safety to bring his product into the market, Professor Kim is developing other mask variations such as eco-friendly biodegradable masks and transparent masks to aid the hearing-impaired who rely on lip reading to communicate. The team working under Professor Wonho Choe from the Department of Nuclear and Quantum Engineering presented two low-temperature plasma sterilizers for medical use, co-developed with Plasmapp, a start-up company founded by a KAIST alumnus. Their sterilizers are the first ones that can sterilize medical devices by diffusing hydrogen peroxide vapor into the pouch. They rapidly sterilize medical instruments and materials in just seven minutes without leaving toxic residue, while reducing sterilization time and costs by 90%. Professor Hyung-Soon Park and his researchers from the Department of Mechanical Engineering introduced a smart protective suit ventilation system that features high cooling capacity and a slimmed-down design. For comfortable use, the suit is equipped with a technique that monitors its inner temperature and humidity and automatically controls its inner circulation accordingly. The group also presented a new system that helps a person in a contaminated suit undress without coming into contact with the contaminated outer part of the suit. Professor Jong Chul Ye's group from the Department of Bio and Brain Engineering demonstrated AI software that can quickly diagnose an infectious disease based on chest X-ray imaging. The technique compares the differences in the severity of pneumonia in individual patients to distinguish whether their conditions fall under viral pneumonia including COVID-19, bacterial pneumonia, tuberculosis, other diseases, or normal conditions. The AI software visualizes the basis of its reasoning for each of the suspected diseases and provides them as information that can be utilized by medical personnel. Finally, researchers of Professor Ki-Hun Jeong’s team from the Department of Bio and Brain Engineering demonstrated their ultra-high-speed sub-miniature molecular diagnostic system for the on-site diagnosis of diseases. The existing Polymerase Chain Reaction (PCR) diagnostic usually takes from 30 minutes to an hour to provide results, but their new technique using an LED light source can present results within just three minutes and it is expected to be used actively for on-site diagnosis. Professor Choongsik Bae, the Director of the Post-COVID-19 New Deal R&D Initiative Project, said, “KAIST will build a healthy relationship amongst researchers, enterprises, and hospitals to contribute to the end of COVID-19 and build a new paradigm of Korean disease prevention and control.” KAIST launched the Post-COVID-19 New Deal R&D Initiative in July with the support of the Ministry of Science and ICT of Korea. This unit was created to overcome the pandemic crisis by using science and technology, and to contribute to economic development by creating a new antiviral drug industry. The unit is comprised of 464 KAIST members including professors, researchers, and students as well as 503 professionals from enterprises, hospitals, and research centers. (END)
2020.10.26
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Experts to Help Asia Navigate the Post-COVID-19 and 4IR Eras
Risk Quotient 2020, an international conference co-hosted by KAIST and the National University of Singapore (NUS), will bring together world-leading experts from academia and industry to help Asia navigate the post-COVID-19 and Fourth Industrial Revolution (4IR) eras. The online conference will be held on October 29 from 10 a.m. Korean time under the theme “COVID-19 Pandemic and A Brave New World”. It will be streamed live on YouTube at https://www.youtube.com/c/KAISTofficial and https://www.youtube.com/user/NUScast. The Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) at KAIST organized this conference in collaboration with the Lloyd's Register Foundation Institute for the Public Understanding of Risk (IPUR) at NUS. During the conference, global leaders will examine the socioeconomic impacts of the COVID-19 pandemic on areas including digital innovation, education, the workforce, and the economy. They will then highlight digital and 4IR technologies that could be utilized to effectively mitigate the risks and challenges associated with the pandemic, while harnessing the opportunities that these socioeconomic effects may present. Their discussions will mainly focus on the Asian region. In his opening remarks, KAIST President Sung-Chul Shin will express his appreciation for the Asian populations’ greater trust in and compliance with their governments, which have given the continent a leg up against the coronavirus. He will then emphasize that by working together through the exchange of ideas and global collaboration, we will be able to shape ‘a brave new world’ to better humanity. Welcoming remarks by Prof. Sang Yup Lee (Dean, KAIST Institutes) and Prof. Tze Yun Leong (Director, AI Technology at AI Singapore) will follow. For the keynote speech, Prof. Lan Xue (Dean, Schwarzman College, Tsinghua University) will share China’s response to COVID-19 and lessons for crisis management. Prof. Danny Quah (Dean, Lee Kuan Yew School of Public Policy, NUS) will present possible ways to overcome these difficult times. Dr. Kak-Soo Shin (Senior Advisor, Shin & Kim LLC, Former Ambassador to the State of Israel and Japan, and Former First and Second Vice Minister of the Ministry of Foreign Affairs of the Republic of Korea) will stress the importance of the international community’s solidarity to ensure peace, prosperity, and safety in this new era. Panel Session I will address the impact of COVID-19 on digital innovation. Dr. Carol Soon (Senior Research Fellow, Institute of Policy Studies, NUS) will present her interpretation of recent technological developments as both opportunities for our society as a whole and challenges for vulnerable groups such as low-income families. Dr. Christopher SungWook Chang (Managing Director, Kakao Mobility) will show how changes in mobility usage patterns can be captured by Kakao Mobility’s big data analysis. He will illustrate how the data can be used to interpret citizen’s behaviors and how risks can be transformed into opportunities by utilizing technology. Mr. Steve Ledzian’s (Vice President, Chief Technology Officer, FireEye) talk will discuss the dangers caused by threat actors and other cyber risk implications of COVID-19. Dr. June Sung Park (Chairman, Korea Software Technology Association (KOSTA)) will share how COVID-19 has accelerated digital transformations across all industries and why software education should be reformed to improve Korea’s competitiveness. Panel Session II will examine the impact on education and the workforce. Dr. Sang-Jin Ban (President, Korean Educational Development Institute (KEDI)) will explain Korea’s educational response to the pandemic and the concept of “blended learning” as a new paradigm, and present both positive and negative impacts of online education on students’ learning experiences. Prof. Reuben Ng (Professor, Lee Kuan Yew School of Public Policy, NUS) will present on graduate underemployment, which seems to have worsened during COVID-19. Dr. Michael Fung’s presentation (Deputy Chief Executive (Industry), SkillsFuture SG) will introduce the promotion of lifelong learning in Singapore through a new national initiative known as the ‘SkillsFuture Movement’. This movement serves as an example of a national response to disruptions in the job market and the pace of skills obsolescence triggered by AI and COVID-19. Panel Session III will touch on technology leadership and Asia’s digital economy and society. Prof. Naubahar Sharif (Professor, Division of Social Science and Division of Public Policy, Hong Kong University of Science and Technology (HKUST)) will share his views on the potential of China in taking over global technological leadership based on its massive domestic market, its government support, and the globalization process. Prof. Yee Kuang Heng (Professor, Graduate School of Public Policy, University of Tokyo) will illustrate how different legal and political needs in China and Japan have shaped the ways technologies have been deployed in responding to COVID-19. Dr. Hayun Kang (Head, International Cooperation Research Division, Korea Information Society Development Institute (KISDI)) will explain Korea’s relative success containing the pandemic compared to other countries, and how policy leaders and institutions that embrace digital technologies in the pursuit of public welfare objectives can produce positive outcomes while minimizing the side effects. Prof. Kyung Ryul Park (Graduate School of Science and Technology Policy, KAIST) will be hosting the entire conference, whereas Prof. Alice Hae Yun Oh (Director, MARS Artificial Intelligence Research Center, KAIST), Prof. Wonjoon Kim (Dean, Graduate School of Innovation and Technology Management, College of Business, KAIST), Prof. Youngsun Kwon (Dean, KAIST Academy), and Prof. Taejun Lee (Korea Development Institute (KDI) School of Public Policy and Management) are to chair discussions with the keynote speakers and panelists. Closing remarks will be delivered by Prof. Chan Ghee Koh (Director, NUS IPUR), Prof. So Young Kim (Director, KAIST KPC4IR), and Prof. Joungho Kim (Director, KAIST Global Strategy Institute (GSI)). “This conference is expected to serve as a springboard to help Asian countries recover from global crises such as the COVID-19 pandemic through active cooperation and joint engagement among scholars, experts, and policymakers,” according to Director So Young Kim. (END)
2020.10.22
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