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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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Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis. Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %. Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room. Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image. To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else. In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places. The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances. The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment. In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer. The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image. A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms. Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff." This study was conducted in collaboration with SM Instruments Inc. Profile: Yong-Hwa Park, Ph.D. Associate Professor yhpark@kaist.ac.kr http://human.kaist.ac.kr/ Human-Machine Interaction Laboratory (HuMaN Lab.) Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr/en/ Daejeon 34141, Korea Profile: Gyeong Tae Lee PhD Candidate hansaram@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Seong Hu Kim PhD Candidate tjdgnkim@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Hyeonuk Nam PhD Candidate frednam@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Young-Key Kim CEO sales@smins.co.kr http://en.smins.co.kr/ SM Instruments Inc. Daejeon 34109, Korea (END)
2020.08.13
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Hydrogel-Based Flexible Brain-Machine Interface
The interface is easy to insert into the body when dry, but behaves ‘stealthily’ inside the brain when wet Professor Seongjun Park’s research team and collaborators revealed a newly developed hydrogel-based flexible brain-machine interface. To study the structure of the brain or to identify and treat neurological diseases, it is crucial to develop an interface that can stimulate the brain and detect its signals in real time. However, existing neural interfaces are mechanically and chemically different from real brain tissue. This causes foreign body response and forms an insulating layer (glial scar) around the interface, which shortens its lifespan. To solve this problem, the research team developed a ‘brain-mimicking interface’ by inserting a custom-made multifunctional fiber bundle into the hydrogel body. The device is composed not only of an optical fiber that controls specific nerve cells with light in order to perform optogenetic procedures, but it also has an electrode bundle to read brain signals and a microfluidic channel to deliver drugs to the brain. The interface is easy to insert into the body when dry, as hydrogels become solid. But once in the body, the hydrogel will quickly absorb body fluids and resemble the properties of its surrounding tissues, thereby minimizing foreign body response. The research team applied the device on animal models, and showed that it was possible to detect neural signals for up to six months, which is far beyond what had been previously recorded. It was also possible to conduct long-term optogenetic and behavioral experiments on freely moving mice with a significant reduction in foreign body responses such as glial and immunological activation compared to existing devices. “This research is significant in that it was the first to utilize a hydrogel as part of a multifunctional neural interface probe, which increased its lifespan dramatically,” said Professor Park. “With our discovery, we look forward to advancements in research on neurological disorders like Alzheimer’s or Parkinson’s disease that require long-term observation.” The research was published in Nature Communications on June 8, 2021. (Title: Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity) The study was conducted jointly with an MIT research team composed of Professor Polina Anikeeva, Professor Xuanhe Zhao, and Dr. Hyunwoo Yook. This research was supported by the National Research Foundation (NRF) grant for emerging research, Korea Medical Device Development Fund, KK-JRC Smart Project, KAIST Global Initiative Program, and Post-AI Project. -Publication Park, S., Yuk, H., Zhao, R. et al. Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity. Nat Commun 12, 3435 (2021). https://doi.org/10.1038/s41467-021-23802-9 -Profile Professor Seongjun Park Bio and Neural Interfaces Laboratory Department of Bio and Brain Engineering KAIST
2020.07.13
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New Nanoparticle Drug Combination For Atherosclerosis
Physicochemical cargo-switching nanoparticles (CSNP) designed by KAIST can help significantly reduce cholesterol and macrophage foam cells in arteries, which are the two main triggers for atherosclerotic plaque and inflammation. The CSNP-based combination drug delivery therapy was proved to exert cholesterol-lowering, anti-inflammatory, and anti-proliferative functions of two common medications for treating and preventing atherosclerosis that are cyclodextrin and statin. Professor Ji-Ho Park and Dr. Heegon Kim from KAIST’s Department of Bio and Brain Engineering said their study has shown great potential for future applications with reduced side effects. Atherosclerosis is a chronic inflammatory vascular disease that is characterized by the accumulation of cholesterol and cholesterol-loaded macrophage foam cells in the intima. When this atherosclerotic plaque clogs and narrows the artery walls, they restrict blood flow and cause various cardiovascular conditions such as heart attacks and strokes. Heart attacks and strokes are the world’s first and fifth causes of death respectively. Oral statin administration has been used in clinics as a standard care for atherosclerosis, which is prescribed to lower blood cholesterol and inhibit its accumulation within the plaque. Although statins can effectively prevent the progression of plaque growth, they have only shown modest efficacy in eliminating the already-established plaque. Therefore, patients are required to take statin drugs for the rest of their lives and will always carry the risk of plaque ruptures that can trigger a blood clot. To address these issues, Professor Park and Dr. Kim exploited another antiatherogenic agent called cyclodextrin. In their paper published in the Journal of Controlled Release on March 10, Professor Park and Dr. Kim reported that the polymeric formulation of cyclodextrin with a diameter of approximately 10 nanometers(nm) can accumulate within the atherosclerotic plaque 14 times more and effectively reduce the plaque even at lower doses, compared to cyclodextrin in a non-polymer structure. Moreover, although cyclodextrin is known to have a cytotoxic effect on hair cells in the cochlea, which can lead to hearing loss, cyclodextrin polymers developed by Professor Park’s research group exhibited a varying biodistribution profile and did not have this side effect. In the follow-up study reported in ACS Nano on April 28, the researchers exploited both cyclodextrin and statin and form the cyclodextrin-statin self-assembly drug complex, based on previous findings that each drug can exert local anti-atherosclerosis effect within the plaque. The complex formation processes were optimized to obtain homogeneous and stable nanoparticles with a diameter of about 100 nm for systematic injection. The therapeutic synergy of cyclodextrin and statin could reportedly enhance plaque-targeted drug delivery and anti-inflammation. Cyclodextrin led to the regression of cholesterol in the established plaque, and the statins were shown to inhibit the proliferation of macrophage foam cells. The study suggested that combination therapy is required to resolve the complex inflammatory cholesterol-rich microenvironment within the plaque. Professor Park said, “While nanomedicine has been mainly developed for the treatment of cancers, our studies show that nanomedicine can also play a significant role in treating and preventing atherosclerosis, which causes various cardiovascular diseases that are the leading causes of death worldwide.” This work was supported by KAIST and the National Research Foundation (NRF) of Korea. Publications: 1. Heegon Kim, Junhee Han, and Ji-Ho Park. (2020) ‘Cyclodextrin polymer improves atherosclerosis therapy and reduces ototoxicity’ Journal of Controlled Release. Volume 319. Page 77-86. Available online at https://doi.org/10.1016/j.jconrel.2019.12.021 2. Kim, H., et al. (2020) ‘Affinity-Driven Design of Cargo-Switching Nanoparticles to Leverage a Cholesterol-Rich Microenvironment for Atherosclerosis Therapy’ ACS Nano. Available online at https://doi.org/10.1021/acsnano.9b08216 Profile: Ji-Ho Park, Ph.D. Associate Professor jihopark@kaist.ac.kr http://openwetware.org/wiki/Park_Lab Biomaterials Engineering Laboratory (BEL) Department of Bio and Brain Engineering (BIOENG) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Heegon Kim, Ph.D. Postdoctoral Researcher heegon@kaist.ac.kr BEL, BIOENG, KAIST (END)
2020.06.16
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Professor Sukyung Park Named Presidential Science and Technology Adviser
Professor Sukyung Park from the Department of Mechanical Engineering was appointed as the science and technology adviser to the President Jae-in Moon on May 4. Professor Park, at the age of 47, became the youngest member of the president’s senior aide team at Chong Wa Dae. A Chong Wa Dae spokesman said on May 4 while announcing the appointment, “Professor Park, a talent with a great deal of policymaking participation in science and technology, will contribute to accelerating the government’s push for science and technology innovation, especially in the information and communications technology (ICT) sector.” Professor Park joined KAIST in 2004 as the first female professor of mechanical engineering. She is a biomechanics expert who has conducted extensive research on biometric mechanical behaviors. Professor Park is also a member of the KAIST Board of Trustees. Before that, she served as a senior researcher at the Korea Institute of Machinery and Materials (KIMM) as well as a member of the Presidential Advisory Council on Science and Technology. After graduating from Seoul Science High School as the first ever two-year graduate, Professor Park earned a bachelor and master’s degrees in mechanical engineering at KAIST. She then finished her Ph.D. from the University of Michigan. (END)
2020.05.06
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Wearable Strain Sensor Using Light Transmittance Helps Measure Physical Signals Better
KAIST researchers have developed a novel wearable strain sensor based on the modulation of optical transmittance of a carbon nanotube (CNT)-embedded elastomer. The sensor is capable of sensitive, stable, and continuous measurement of physical signals. This technology, featured in the March 4th issue of ACS Applied Materials & Interfaces as a front cover article, shows great potential for the detection of subtle human motions and the real-time monitoring of body postures for healthcare applications. A wearable strain sensor must have high sensitivity, flexibility, and stretchability, as well as low cost. Those used especially for health monitoring should also be tied to long-term solid performance, and be environmentally stable. Various stretchable strain sensors based on piezo-resistive and capacitive principles have been developed to meet all these requirements. Conventional piezo-resistive strain sensors using functional nanomaterials, including CNTs as the most common example, have shown high sensitivity and great sensing performance. However, they suffer from poor long-term stability and linearity, as well as considerable signal hysteresis. As an alternative, piezo-capacitive strain sensors with better stability, lower hysteresis, and higher stretchability have been suggested. But due to the fact that piezo-capacitive strain sensors exhibit limited sensitivity and strong electromagnetic interference caused by the conductive objects in the surrounding environment, these conventional stretchable strain sensors are still facing limitations that are yet to be resolved. A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering suggested that an optical-type stretchable strain sensor can be a good alternative to resolve the limitations of conventional piezo-resistive and piezo-capacitive strain sensors, because they have high stability and are less affected by environmental disturbances. The team then introduced an optical wearable strain sensor based on the light transmittance changes of a CNT-embedded elastomer, which further addresses the low sensitivity problem of conventional optical stretchable strain sensors. In order to achieve a large dynamic range for the sensor, Professor Park and his researchers chose Ecoflex as an elastomeric substrate with good mechanical durability, flexibility, and attachability on human skin, and the new optical wearable strain sensor developed by the research group actually shows a wide dynamic range of 0 to 400%. In addition, the researchers propagated the microcracks under tensile strain within the film of multi-walled CNTs embedded in the Ecoflex substrate, changing the optical transmittance of the film. By doing so, it was possible for them to develop a wearable strain sensor having a sensitivity 10 times higher than conventional optical stretchable strain sensors. The proposed sensor has also passed the durability test with excellent results. The sensor’s response after 13,000 sets of cyclic loading was stable without any noticeable drift. This suggests that the sensor response can be used without degradation, even if the sensor is repeatedly used for a long time and in various environmental conditions. Using the developed sensor, the research team could measure the finger bending motion and used it for robot control. They also developed a three-axes sensor array for body posture monitoring. The sensor was able to monitor human motions with small strains such as a pulse near the carotid artery and muscle movement around the mouth during pronunciation. Professor Park said, “In this study, our group developed a new wearable strain sensor platform that overcomes many limitations of previously developed resistive, capacitive, and optical-type stretchable strain sensors. Our sensor could be widely used in a variety of fields including soft robotics, wearable electronics, electronic skin, healthcare, and even entertainment.” This work was supported by the National Research Foundation (NRF) of Korea. Publication: Jimin Gu, Donguk Kwon, Junseong Ahn, and Inkyu Park. (2020) “Wearable Strain sensors Using Light Transmittance Change of Carbon Nanotube-Embedded Elastomers with Microcracks” ACS Applied Materials & Interfaces. Volume 12. Issue 9. Available online at https://doi.org/10.1021/acsami.9b18069 Profile: Inkyu Park Professor inkyu@kaist.ac.kr http://mintlab1.kaist.ac.kr Micro/Nano Transducers Laboratory (MINT Lab) Department of Mechanical Engineering (ME)Korea Advanced Institute of Science and Technology (KAIST) Profile: Jimin Gu Ph.D. Candidate mint9411@kaist.ac.kr http://mintlab1.kaist.ac.kr MINT Lab KAIST ME (END)
2020.03.20
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‘OSK Rising Stars 30’ Recognizes Four KAISTians
Four KAISTians were selected as star researchers to brighten the future of optics in commemoration of the 30th anniversary of the Optical Society of Korea (OSK). As ‘OSK Rising Stars 30’, the OSK named 27 domestic researchers under the age of 40 who have made significant contributions and will continue contributing to the development of Korea’s optics academia and industry. Professor YongKeun Park from the Department of Physics was selected in recognition of his contributions to the field of biomedical optics. Professor Park focuses on developing novel optical methods for understanding, diagnosing, and treating human diseases, based on light scattering, light manipulation, and interferometry. As a member of numerous international optics societies including the OSA and the SPIE and a co-founder of two start-up companies, Professor Park continues to broaden his boundaries as a leading opticist and entrepreneur. Professor Jonghwa Shin from the Department of Materials Science and Engineering was recognized for blazing a trail in the field of broadband metamaterials. Professor Shin’s research on the broadband enhancement of the electric permittivity and refractive index of metamaterials has great potential in both academia and industry. Professor Hongki Yoo from the Department of Mechanical Engineering is expected to create a significant ripple effect in the diagnosis of cardiovascular disorders through the development of new optical imaging techniques and applications. Finally, Dr. Sejeong Kim, a KAIST graduate and a Chancellor’s postdoctoral research fellow at the University of Technology Sydney (UTS), was acknowledged for her optical device research utilizing two-dimensional materials. Dr. Kim’s research at UTS now focuses on the introduction of micro/nano cavities for new materials. (END)
2020.03.16
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Blood-Based Multiplexed Diagnostic Sensor Helps to Accurately Detect Alzheimer’s Disease
A research team at KAIST reported clinically accurate multiplexed electrical biosensor for detecting Alzheimer’s disease by measuring its core biomarkers using densely aligned carbon nanotubes. Alzheimer’s disease is the most prevalent neurodegenerative disorder, affecting one in ten aged over 65 years. Early diagnosis can reduce the risk of suffering the disease by one-third, according to recent reports. However, its early diagnosis remains challenging due to the low accuracy but high cost of diagnosis. Research team led by Professors Chan Beum Park and Steve Park described an ultrasensitive detection of multiple Alzheimer's disease core biomarker in human plasma. The team have designed the sensor array by employing a densely aligned single-walled carbon nanotube thin films as a transducer. The representative biomarkers of Alzheimer's disease are beta-amyloid42, beta-amyloid40, total tau protein, phosphorylated tau protein and the concentrations of these biomarkers in human plasma are directly correlated with the pathology of Alzheimer’s disease. The research team developed a highly sensitive resistive biosensor based on densely aligned carbon nanotubes fabricated by Langmuir-Blodgett method with a low manufacturing cost. Aligned carbon nanotubes with high density minimizes the tube-to-tube junction resistance compared with randomly distributed carbon nanotubes, which leads to the improvement of sensor sensitivity. To be more specific, this resistive sensor with densely aligned carbon nanotubes exhibits a sensitivity over 100 times higher than that of conventional carbon nanotube-based biosensors. By measuring the concentrations of four Alzheimer’s disease biomarkers simultaneously Alzheimer patients can be discriminated from health controls with an average sensitivity of 90.0%, a selectivity of 90.0% and an average accuracy of 88.6%. This work, titled “Clinically accurate diagnosis of Alzheimer’s disease via multiplexed sensing of core biomarkers in human plasma”, were published in Nature Communications on January 8th 2020. The authors include PhD candidate Kayoung Kim and MS candidate Min-Ji Kim. Professor Steve Park said, “This study was conducted on patients who are already confirmed with Alzheimer’s Disease. For further use in practical setting, it is necessary to test the patients with mild cognitive impairment.” He also emphasized that, “It is essential to establish a nationwide infrastructure, such as mild cognitive impairment cohort study and a dementia cohort study. This would enable the establishment of world-wide research network, and will help various private and public institutions.” This research was supported by the Ministry of Science and ICT, Human Resource Bank of Chungnam National University Hospital and Chungbuk National University Hospital. < A schematic diagram of a high-density aligned carbon nanotube-based resistive sensor that distinguishes patients with Alzheimer’s Disease by measuring the concentration of four biomarkers in the blood. > Profile: Professor Steve Park stevepark@kaist.ac.kr Department of Materials Science and Engineering http://steveparklab.kaist.ac.kr/ KAIST Profile: Professor Chan Beum Park parkcb at kaist.ac.kr Department of Materials Science and Engineering http://biomaterials.kaist.ac.kr/ KAIST
2020.02.07
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Rachmaninoff the most innovative of 18th and 19th century composers according to network science
Rachmaninoff, followed by Bach, Brahms and Mendelssohn, was the most innovative of the composers who worked during the Baroque, Classical and Romantic eras of music (1700 to 1900) according to a study published in the open access journal EPJ Data Science. A team of researchers from KAIST (Korea Advanced Institute of Science and Technology), calculated novelty scores for 900 classical piano compositions written by 19 composers between approximately 1700 and 1900. The scores were based on how musical compositions differed from all prior pieces of piano music and how they differed from previous piano works by the same composer. The authors found that composers from the Romantic era (1820 to 1910) tended to have high novelty scores. The authors from the Graduate School of Culture Technology at KAIST created a computer model which divided each composition into segments called ‘codewords’. Each ‘codeword’ consisted of all of the notes played together at a given time. Sequences of ‘codewords’ were then compared between compositions. The similarities between the sequences were used to create novelty scores for each composer and to determine the extent to which composers influenced each other. Juyong Park, the corresponding author, said: “Our model allows us to calculate the degree of shared melodies and harmonies between past and future works and to observe the evolution of western musical styles by demonstrating how prominent composers may have influenced each other. The period of music we studied is widely credited for having produced many musical styles that are still influential today.” The model distinguished each new musical period from the one before it by the rise of newly dominant and highly influential composers that indicated dramatic shifts in musical styles. The authors found that compositions from the Classical period (1750 to 1820) tended to have the lowest novelty scores. During this period Haydn and Mozart were highly influential but were later overtaken by Beethoven during the Classical-to-Romantic transitional period. The most innovative composer, indicated by the highest combined novelty score, was Rachmaninoff. His work during the Romantic era was novel when compared to the compositions of the other 18 composers included in the study, and his later works were novel compared to his earlier works. Lower novelty did not necessarily correlate with low influence. Beethoven was ranked in the lower half of novelty scores yet was the most influential composer during the Romantic period (1820 to 1910) and is widely considered one of the greatest composers of all time. Dr. Park said: “While novelty is necessary in a creative work it cannot account for all the creative and artistic qualities that go into creating melodies and harmonies that spread to later generations of composers. That may be why being more novel did not necessarily result in composers being more influential.” The authors suggest that their method could be applied to narrative or visual artworks by creating codewords from groups of words or colours and shapes. However, they caution that as only piano compositions were included in their analysis, it is unknown whether including all works by the 19 composers would have resulted in another composer being identified as the most original. Profile: Prof. Juyong Park, PhD juyongp@kaist.ac.kr Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2020.01.31
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KAIST Vaccine for Tick-Borne Disease ‘SFTS’ Protects Against Lethal Infection
A KAIST research team reported the development of a DNA vaccine for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) which completely protects against lethal infection in ferrets. The team confirmed that ferrets immunized with DNA vaccines encoding all SFTSV proteins showed 100% survival rate without detectable viremia and did not develop any clinical symptoms. This study was published in Nature Communications on August 23. Severe Fever with Thrombocytopenia Syndrome (SFTS) is a newly emerging tick-borne infectious disease. The disease causes fever, severe thrombocytopenia, leukocytopenia as well as vomiting and diarrhea. Severe cases end up with organ system failure often accompanied by hemorrhages, and its mortality rate stands at 10–20%. The viral disease has been endemic to East Asia but the spread of the tick vector to North America increases the likelihood of potential outbreak beyond the Far East Asia. The World Health Organization (WHO) has also put SFTSV into the priority pathogen requiring urgent attention category. Currently, no vaccine has been available to prevent SFTS. The research team led by Professor Su-Hyung Park noted that DNA vaccines induce broader immunity to multiple antigens than traditional ones. Moreover, DNA vaccines stimulate both T cell and antibody immunity, which make them suitable for vaccine development. They constructed DNA vaccines that encode full-length Gn, Gc, N, NS, and RNA polymerase genes based on common sequences of 31 SFTSV strains isolated from patients. Their vaccine candidates induced both neutralizing antibody response and multifunctional SFTSV-specific T cell response in mice and ferrets. To investigate the vaccine’s efficacy in vivo, the research team applied a recently developed ferret model that recapitulates fatal clinical symptoms in SFTSV infection in humans. Vaccinated ferrets were completely protected from lethal SFTSV challenge without SFTSV detection in their blood, whereas all control ferrets died within 10 days’ post-infection. The KAIST team found that anti-envelope antibodies play an important role in protective immunity, suggesting that envelope glycoproteins of SFTSV may be the most effective antigens for inducing protective immunity. Moreover, the study revealed that T cell responses specific to non-envelope proteins of SFTSV also can contribute to protection against SFTSV infection. Professor Park said, “This is the first study demonstrating complete protection against lethal SFTSV challenge using an immunocompetent, middle-sized animal model with clinical manifestations of SFTSV infection. We believe this study provides valuable insights into designing preventive vaccines for SFTSV.”
2020.01.31
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A System Controlling Road Active Noise to Hit the Road
The research team led by Professor Youngjin Park of the Department of Mechanical Engineering has developed a road noise active noise control (RANC) system to be commercialized in partnership with Hyundai Motor Group. On December 11, Hyundai Motor Group announced the successful development of the RANC system, which significantly reduces the road noise flowing into cars. The carmaker has completed the domestic and American patent applications for the location of sensors and the signal selection method, the core technology of RANC. RANC is a technology for reducing road noise during driving. This system consists of an acceleration sensor, digital signal processor (the control computer to analyze sound signals), microphone, amplifier, and audio system. To make the system as simple as possible, the audio system utilizes the original audio system embedded in the car instead of a separate system. The acceleration sensor first calculates the vibration from the road into the car. The location of the sensor is important for accurately identifying the vibration path. The research team was able to find the optimal sensor location through a number of tests. The System Dynamics and Applied Control Laboratory of Professor Park researched ways to significantly reduce road noise with Hyundai Motor Group for four years from 1993 as a G7 national project and published the results in international journals. In 2002, the researchers published an article titled “Noise Quietens Driving” in Nature, where they announced the first success in reducing road noise in actual cars. The achievement did not lead to commercialization, however, due to the lack of auxiliary technologies at the time, digital amplifiers and DSP for cars for example, and pricing issues. Since 2013, Professor Park’s research team has participated in one technology transfer and eight university-industry projects. Based on these efforts, the team was able to successfully develop the RANC system with domestic technology in partnership with Hyundai’s NVH Research Lab (Research Fellow, Dr. Gangdeok Lee; Ph.D. in aviation engineering, 1996), Optomech (Founder, Professor Gyeongsu Kim; Ph.D. in mechanical engineering, 1999), ARE (CEO Hyeonseok Kim; Ph.D. in mechanical engineering, 1998), WeAcom, and BurnYoung. Professor Park’s team led the project by performing theory-based research during the commercialization stage in collaboration with Hyundai Motor Group. For the commercialization of the RANC system, Hyundai Motor Group is planning to collaborate with the global car audio company Harman to increase the degree of completion and apply the RANC system to the GV 80, the first SUV model of the Genesis brand. “I am very delighted as an engineer to see the research I worked on from my early days at KAIST be commercialized after 20 years,” noted Professor Park. “I am thrilled to make a contribution to such commercialization with my students in my lab.”
2019.12.27
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New Liquid Metal Wearable Pressure Sensor Created for Health Monitoring Applications
Soft pressure sensors have received significant research attention in a variety of fields, including soft robotics, electronic skin, and wearable electronics. Wearable soft pressure sensors have great potential for the real-time health monitoring and for the early diagnosis of diseases. A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering developed a highly sensitive wearable pressure sensor for health monitoring applications. This work was reported in Advanced Healthcare Materials on November 21 as a front cover article. This technology is capable of sensitive, precise, and continuous measurement of physiological and physical signals and shows great potential for health monitoring applications and the early diagnosis of diseases. A soft pressure sensor is required to have high compliance, high sensitivity, low cost, long-term performance stability, and environmental stability in order to be employed for continuous health monitoring. Conventional solid-state soft pressure sensors using functional materials including carbon nanotubes and graphene have showed great sensing performance. However, these sensors suffer from limited stretchability, signal drifting, and long-term instability due to the distance between the stretchable substrate and the functional materials. To overcome these issues, liquid-state electronics using liquid metal have been introduced for various wearable applications. Of these materials, Galinstan, a eutectic metal alloy of gallium, indium, and tin, has great mechanical and electrical properties that can be employed in wearable applications. But today’s liquid metal-based pressure sensors have low-pressure sensitivity, limiting their applicability for health monitoring devices. The research team developed a 3D-printed rigid microbump array-integrated, liquid metal-based soft pressure sensor. With the help of 3D printing, the integration of a rigid microbump array and the master mold for a liquid metal microchannel could be achieved simultaneously, reducing the complexity of the manufacturing process. Through the integration of the rigid microbump and the microchannel, the new pressure sensor has an extremely low detection limit and enhanced pressure sensitivity compared to previously reported liquid metal-based pressure sensors. The proposed sensor also has a negligible signal drift over 10,000 cycles of pressure, bending, and stretching and exhibited excellent stability when subjected to various environmental conditions. These performance outcomes make it an excellent sensor for various health monitoring devices. First, the research team demonstrated a wearable wristband device that can continuously monitor one’s pulse during exercise and be employed in a noninvasive cuffless BP monitoring system based on PTT calculations. Then, they introduced a wireless wearable heel pressure monitoring system that integrates three 3D-BLiPS with a wireless communication module. Professor Park said, “It was possible to measure health indicators including pulse and blood pressure continuously as well as pressure of body parts using our proposed soft pressure sensor. We expect it to be used in health care applications, such as the prevention and the monitoring of the pressure-driven diseases such as pressure ulcers in the near future. There will be more opportunities for future research including a whole-body pressure monitoring system related to other physical parameters.” This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT. < Figure 1. The front cover image of Advanced Healthcare Materials, Volume 8, Issue 22. > < Figure 2. Highly sensitive liquid metal-based soft pressure sensor integrated with 3D-printed microbump array. > < Figure 3. High pressure sensitivity and reliable sensing performances of the proposed sensor and wireless heel pressure monitoring application. > -ProfileProfessor Inkyu ParkMicro/Nano Transducers Laboratoryhttp://mintlab1.kaist.ac.kr/ Department of Mechanical EngineeringKAIST
2019.12.20
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