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Metabolically Engineered Bacterium Produces Lutein
A research group at KAIST has engineered a bacterial strain capable of producing lutein. The research team applied systems metabolic engineering strategies, including substrate channeling and electron channeling, to enhance the production of lutein in an engineered Escherichia coli strain. The strategies will be also useful for the efficient production of other industrially important natural products used in the food, pharmaceutical, and cosmetic industries.
Figure: Systems metabolic engineering was employed to construct and optimize the metabolic pathways for lutein production, and substrate channeling and electron channeling strategies were additionally employed to increase the production of the lutein with high productivity.
Lutein is classified as a xanthophyll chemical that is abundant in egg yolk, fruits, and vegetables. It protects the eye from oxidative damage from radiation and reduces the risk of eye diseases including macular degeneration and cataracts. Commercialized products featuring lutein are derived from the extracts of the marigold flower, which is known to harbor abundant amounts of lutein. However, the drawback of lutein production from nature is that it takes a long time to grow and harvest marigold flowers. Furthermore, it requires additional physical and chemical-based extractions with a low yield, which makes it economically unfeasible in terms of productivity. The high cost and low yield of these bioprocesses has made it difficult to readily meet the demand for lutein.
These challenges inspired the metabolic engineers at KAIST, including researchers Dr. Seon Young Park, Ph.D. Candidate Hyunmin Eun, and Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering. The team’s study entitled “Metabolic engineering of Escherichia coli with electron channeling for the production of natural products” was published in Nature Catalysis on August 5, 2022.
This research details the ability to produce lutein from E. coli with a high yield using a cheap carbon source, glycerol, via systems metabolic engineering. The research group focused on solving the bottlenecks of the biosynthetic pathway for lutein production constructed within an individual cell. First, using systems metabolic engineering, which is an integrated technology to engineer the metabolism of a microorganism, lutein was produced when the lutein biosynthesis pathway was introduced, albeit in very small amounts.
To improve the productivity of lutein production, the bottleneck enzymes within the metabolic pathway were first identified. It turned out that metabolic reactions that involve a promiscuous enzyme, an enzyme that is involved in two or more metabolic reactions, and electron-requiring cytochrome P450 enzymes are the main bottleneck steps of the pathway inhibiting lutein biosynthesis.
To overcome these challenges, substrate channeling, a strategy to artificially recruit enzymes in physical proximity within the cell in order to increase the local concentrations of substrates that can be converted into products, was employed to channel more metabolic flux towards the target chemical while reducing the formation of unwanted byproducts.
Furthermore, electron channeling, a strategy similar to substrate channeling but differing in terms of increasing the local concentrations of electrons required for oxidoreduction reactions mediated by P450 and its reductase partners, was applied to further streamline the metabolic flux towards lutein biosynthesis, which led to the highest titer of lutein production achieved in a bacterial host ever reported. The same electron channeling strategy was successfully applied for the production of other natural products including nootkatone and apigenin in E. coli, showcasing the general applicability of the strategy in the research field.
“It is expected that this microbial cell factory-based production of lutein will be able to replace the current plant extraction-based process,” said Dr. Seon Young Park, the first author of the paper. She explained that another important point of the research is that integrated metabolic engineering strategies developed from this study can be generally applicable for the efficient production of other natural products useful as pharmaceuticals or nutraceuticals.
“As maintaining good health in an aging society is becoming increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other valuable natural products of medical or nutritional importance,” explained Distinguished Professor Sang Yup Lee.
This work was supported by the Cooperative Research Program for Agriculture Science & Technology Development funded by the Rural Development Administration of Korea, with further support from the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and by the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project of the National Research Foundation funded by the Ministry of Science and ICT of Korea.
2022.08.05 View 9875 -
A System for Stable Simultaneous Communication among Thousands of IoT Devices
A mmWave Backscatter System, developed by a team led by Professor Song Min Kim is exciting news for the IoT market as it will be able to provide fast and stable connectivity even for a massive network, which could finally allow IoT devices to reach their full potential.
A research team led by Professor Song Min Kim of the KAIST School of Electrical Engineering developed a system that can support concurrent communications for tens of millions of IoT devices using backscattering millimeter-level waves (mmWave).
With their mmWave backscatter method, the research team built a design enabling simultaneous signal demodulation in a complex environment for communication where tens of thousands of IoT devices are arranged indoors. The wide frequency range of mmWave exceeds 10GHz, which provides great scalability. In addition, backscattering reflects radiated signals instead of wirelessly creating its own, which allows operation at ultralow power. Therefore, the mmWave backscatter system offers internet connectivity on a mass scale to IoT devices at a low installation cost.
This research by Kangmin Bae et al. was presented at ACM MobiSys 2022. At this world-renowned conference for mobile systems, the research won the Best Paper Award under the title “OmniScatter: Sensitivity mmWave Backscattering Using Commodity FMCW Radar”. It is meaningful that members of the KAIST School of Electrical Engineering have won the Best Paper Award at ACM MobiSys for two consecutive years, as last year was the first time the award was presented to an institute from Asia.
IoT, as a core component of 5G/6G network, is showing exponential growth, and is expected to be part of a trillion devices by 2035. To support the connection of IoT devices on a mass scale, 5G and 6G each aim to support ten times and 100 times the network density of 4G, respectively. As a result, the importance of practical systems for large-scale communication has been raised.
The mmWave is a next-generation communication technology that can be incorporated in 5G/6G standards, as it utilizes carrier waves at frequencies between 30 to 300GHz. However, due to signal reduction at high frequencies and reflection loss, the current mmWave backscatter system enables communication in limited environments. In other words, it cannot operate in complex environments where various obstacles and reflectors are present. As a result, it is limited to the large-scale connection of IoT devices that require a relatively free arrangement.
The research team found the solution in the high coding gain of an FMCW radar. The team developed a signal processing method that can fundamentally separate backscatter signals from ambient noise while maintaining the coding gain of the radar. They achieved a receiver sensitivity of over 100 thousand times that of previously reported FMCW radars, which can support communication in practical environments. Additionally, given the radar’s property where the frequency of the demodulated signal changes depending on the physical location of the tag, the team designed a system that passively assigns them channels. This lets the ultralow-power backscatter communication system to take full advantage of the frequency range at 10 GHz or higher.
The developed system can use the radar of existing commercial products as gateway, making it easily compatible. In addition, since the backscatter system works at ultralow power levels of 10uW or below, it can operate for over 40 years with a single button cell and drastically reduce installation and maintenance costs.
The research team confirmed that mmWave backscatter devices arranged randomly in an office with various obstacles and reflectors could communicate effectively. The team then took things one step further and conducted a successful trace-driven evaluation where they simultaneously received information sent by 1,100 devices.
Their research presents connectivity that greatly exceeds network density required by next-generation communication like 5G and 6G. The system is expected to become a stepping stone for the hyper-connected future to come.
Professor Kim said, “mmWave backscatter is the technology we’ve dreamt of. The mass scalability and ultralow power at which it can operate IoT devices is unmatched by any existing technology”. He added, “We look forward to this system being actively utilized to enable the wide availability of IoT in the hyper-connected generation to come”.
To demonstrate the massive connectivity of the system, a trace-driven evaluation of 1,100 concurrent tag transmissions are made. Figure shows the demodulation result of each and every 1,100 tags as red triangles, where they successfully communicate without collision.
This work was supported by Samsung Research Funding & Incubation Center of Samsung Electronics and by the ITRC (Information Technology Research Center) support program supervised by the IITP (Institute of Information & Communications Technology Planning & Evaluation).
Profile: Song Min Kim, Ph.D.Professorsongmin@kaist.ac.krhttps://smile.kaist.ac.kr
SMILE Lab.School of Electrical Engineering
2022.07.28 View 9835 -
Atomically-Smooth Gold Crystals Help to Compress Light for Nanophotonic Applications
Highly compressed mid-infrared optical waves in a thin dielectric crystal on monocrystalline gold substrate investigated for the first time using a high-resolution scattering-type scanning near-field optical microscope.
KAIST researchers and their collaborators at home and abroad have successfully demonstrated a new platform for guiding the compressed light waves in very thin van der Waals crystals. Their method to guide the mid-infrared light with minimal loss will provide a breakthrough for the practical applications of ultra-thin dielectric crystals in next-generation optoelectronic devices based on strong light-matter interactions at the nanoscale.
Phonon-polaritons are collective oscillations of ions in polar dielectrics coupled to electromagnetic waves of light, whose electromagnetic field is much more compressed compared to the light wavelength. Recently, it was demonstrated that the phonon-polaritons in thin van der Waals crystals can be compressed even further when the material is placed on top of a highly conductive metal. In such a configuration, charges in the polaritonic crystal are “reflected” in the metal, and their coupling with light results in a new type of polariton waves called the image phonon-polaritons. Highly compressed image modes provide strong light-matter interactions, but are very sensitive to the substrate roughness, which hinders their practical application.
Challenged by these limitations, four research groups combined their efforts to develop a unique experimental platform using advanced fabrication and measurement methods. Their findings were published in Science Advances on July 13.
A KAIST research team led by Professor Min Seok Jang from the School of Electrical Engineering used a highly sensitive scanning near-field optical microscope (SNOM) to directly measure the optical fields of the hyperbolic image phonon-polaritons (HIP) propagating in a 63 nm-thick slab of hexagonal boron nitride (h-BN) on a monocrystalline gold substrate, showing the mid-infrared light waves in dielectric crystal compressed by a hundred times.
Professor Jang and a research professor in his group, Sergey Menabde, successfully obtained direct images of HIP waves propagating for many wavelengths, and detected a signal from the ultra-compressed high-order HIP in a regular h-BN crystals for the first time. They showed that the phonon-polaritons in van der Waals crystals can be significantly more compressed without sacrificing their lifetime.
This became possible due to the atomically-smooth surfaces of the home-grown gold crystals used as a substrate for the h-BN. Practically zero surface scattering and extremely small ohmic loss in gold at mid-infrared frequencies provide a low-loss environment for the HIP propagation. The HIP mode probed by the researchers was 2.4 times more compressed and yet exhibited a similar lifetime compared to the phonon-polaritons with a low-loss dielectric substrate, resulting in a twice higher figure of merit in terms of the normalized propagation length.
The ultra-smooth monocrystalline gold flakes used in the experiment were chemically grown by the team of Professor N. Asger Mortensen from the Center for Nano Optics at the University of Southern Denmark.
Mid-infrared spectrum is particularly important for sensing applications since many important organic molecules have absorption lines in the mid-infrared. However, a large number of molecules is required by the conventional detection methods for successful operation, whereas the ultra-compressed phonon-polariton fields can provide strong light-matter interactions at the microscopic level, thus significantly improving the detection limit down to a single molecule. The long lifetime of the HIP on monocrystalline gold will further improve the detection performance.
Furthermore, the study conducted by Professor Jang and the team demonstrated the striking similarity between the HIP and the image graphene plasmons. Both image modes possess significantly more confined electromagnetic field, yet their lifetime remains unaffected by the shorter polariton wavelength. This observation provides a broader perspective on image polaritons in general, and highlights their superiority in terms of the nanolight waveguiding compared to the conventional low-dimensional polaritons in van der Waals crystals on a dielectric substrate.
Professor Jang said, “Our research demonstrated the advantages of image polaritons, and especially the image phonon-polaritons. These optical modes can be used in the future optoelectronic devices where both the low-loss propagation and the strong light-matter interaction are necessary. I hope that our results will pave the way for the realization of more efficient nanophotonic devices such as metasurfaces, optical switches, sensors, and other applications operating at infrared frequencies.”
This research was funded by the Samsung Research Funding & Incubation Center of Samsung Electronics and the National Research Foundation of Korea (NRF). The Korea Institute of Science and Technology, Ministry of Education, Culture, Sports, Science and Technology of Japan, and The Villum Foundation, Denmark, also supported the work.
Figure. Nano-tip is used for the ultra-high-resolution imaging of the image phonon-polaritons in hBN launched by the gold crystal edge.
Publication:
Menabde, S. G., et al. (2022) Near-field probing of image phonon-polaritons in hexagonal boron nitride on gold crystals. Science Advances 8, Article ID: eabn0627. Available online at https://science.org/doi/10.1126/sciadv.abn0627.
Profile:
Min Seok Jang, MS, PhD
Associate Professor
jang.minseok@kaist.ac.kr
http://janglab.org/
Min Seok Jang Research Group
School of Electrical Engineering
http://kaist.ac.kr/en/
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
2022.07.13 View 13017 -
Professor Juho Kim’s Team Wins Best Paper Award at ACM CHI 2022
The research team led by Professor Juho Kim from the KAIST School of Computing won a Best Paper Award and an Honorable Mention Award at the Association for Computing Machinery Conference on Human Factors in Computing Systems (ACM CHI) held between April 30 and May 6.
ACM CHI is the world’s most recognized conference in the field of human computer interactions (HCI), and is ranked number one out of all HCI-related journals and conferences based on Google Scholar’s h-5 index. Best paper awards are given to works that rank in the top one percent, and honorable mention awards are given to the top five percent of the papers accepted by the conference.
Professor Juho Kim presented a total of seven papers at ACM CHI 2022, and tied for the largest number of papers. A total of 19 papers were affiliated with KAIST, putting it fifth out of all participating institutes and thereby proving KAIST’s competence in research.
One of Professor Kim’s research teams composed of Jeongyeon Kim (first author, MS graduate) from the School of Computing, MS candidate Yubin Choi from the School of Electrical Engineering, and Dr. Meng Xia (post-doctoral associate in the School of Computing, currently a post-doctoral associate at Carnegie Mellon University) received a best paper award for their paper, “Mobile-Friendly Content Design for MOOCs: Challenges, Requirements, and Design Opportunities”.
The study analyzed the difficulties experienced by learners watching video-based educational content in a mobile environment and suggests guidelines for solutions. The research team analyzed 134 survey responses and 21 interviews, and revealed that texts that are too small or overcrowded are what mainly brings down the legibility of video contents. Additionally, lighting, noise, and surrounding environments that change frequently are also important factors that may disturb a learning experience.
Based on these findings, the team analyzed the aptness of 41,722 frames from 101 video lectures for mobile environments, and confirmed that they generally show low levels of adequacy. For instance, in the case of text sizes, only 24.5% of the frames were shown to be adequate for learning in mobile environments. To overcome this issue, the research team suggested a guideline that may improve the legibility of video contents and help overcome the difficulties arising from mobile learning environments.
The importance of and dependency on video-based learning continue to rise, especially in the wake of the pandemic, and it is meaningful that this research suggested a means to analyze and tackle the difficulties of users that learn from the small screens of mobile devices. Furthermore, the paper also suggested technology that can solve problems related to video-based learning through human-AI collaborations, enhancing existing video lectures and improving learning experiences. This technology can be applied to various video-based platforms and content creation.
Meanwhile, a research team composed of Ph.D. candidate Tae Soo Kim (first author), MS candidate DaEun Choi, and Ph.D. candidate Yoonseo Choi from the School of Computing received an honorable mention award for their paper, “Stylette: styling the Web with Natural Language”.
The research team developed a novel interface technology that allows nonexperts who are unfamiliar with technical jargon to edit website features through speech. People often find it difficult to use or find the information they need from various websites due to accessibility issues, device-related constraints, inconvenient design, style preferences, etc. However, it is not easy for laymen to edit website features without expertise in programming or design, and most end up just putting up with the inconveniences. But what if the system could read the intentions of its users from their everyday language like “emphasize this part a little more”, or “I want a more modern design”, and edit the features automatically?
Based on this question, Professor Kim’s research team developed ‘Stylette’, a system in which AI analyses its users’ speech expressed in their natural language and automatically recommends a new style that best fits their intentions. The research team created a new system by putting together language AI, visual AI, and user interface technologies. On the linguistic side, a large-scale language model AI converts the intentions of the users expressed through their everyday language into adequate style elements. On the visual side, computer vision AI compares 1.7 million existing web design features and recommends a style adequate for the current website. In an experiment where 40 nonexperts were asked to edit a website design, the subjects that used this system showed double the success rate in a time span that was 35% shorter compared to the control group.
It is meaningful that this research proposed a practical case in which AI technology constructs intuitive interactions with users. The developed technology can be applied to existing design applications and web browsers in a plug-in format, and can be utilized to improve websites or for advertisements by collecting the natural intention data of users on a large scale.
2022.06.13 View 8529 -
Now You Can See Floral Scents!
Optical interferometry visualizes how often lilies emit volatile organic compounds
Have you ever thought about when flowers emit their scents?
KAIST mechanical engineers and biological scientists directly visualized how often a lily releases a floral scent using a laser interferometry method. These measurement results can provide new insights for understanding and further exploring the biosynthesis and emission mechanisms of floral volatiles.
Why is it important to know this? It is well known that the fragrance of flowers affects their interactions with pollinators, microorganisms, and florivores. For instance, many flowering plants can tune their scent emission rates when pollinators are active for pollination. Petunias and the wild tobacco Nicotiana attenuata emit floral scents at night to attract night-active pollinators. Thus, visualizing scent emissions can help us understand the ecological evolution of plant-pollinator interactions.
Many groups have been trying to develop methods for scent analysis. Mass spectrometry has been one widely used method for investigating the fragrance of flowers. Although mass spectrometry reveals the quality and quantity of floral scents, it is impossible to directly measure the releasing frequency. A laser-based gas detection system and a smartphone-based detection system using chemo-responsive dyes have also been used to measure volatile organic compounds (VOCs) in real-time, but it is still hard to measure the time-dependent emission rate of floral scents.
However, the KAIST research team co-led by Professor Hyoungsoo Kim from the Department of Mechanical Engineering and Professor Sang-Gyu Kim from the Department of Biological Sciences measured a refractive index difference between the vapor of the VOCs of lilies and the air to measure the emission frequency. The floral scent vapor was detected and the refractive index of air was 1.0 while that of the major floral scent of a linalool lily was 1.46.
Professor Hyoungsoo Kim said, “We expect this technology to be further applicable to various industrial sectors such as developing it to detect hazardous substances in a space.” The research team also plans to identify the DNA mechanism that controls floral scent secretion.
The current work entitled “Real-time visualization of scent accumulation reveals the frequency of floral scent emissions” was published in ‘Frontiers in Plant Science’ on April 18, 2022. (https://doi.org/10.3389/fpls.2022.835305).
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF-2021R1A2C2007835), the Rural Development Administration (PJ016403), and the KAIST-funded Global Singularity Research PREP-Program.
-Publication:H. Kim, G. Lee, J. Song, and S.-G. Kim, "Real-time visualization of scent accumulation reveals the frequency of floral scent emissions," Frontiers in Plant Science 18, 835305 (2022) (https://doi.org/10.3389/fpls.2022.835305)
-Profile:Professor Hyoungsoo Kimhttp://fil.kaist.ac.kr
@MadeInH on TwitterDepartment of Mechanical EngineeringKAIST
Professor Sang-Gyu Kimhttps://sites.google.com/view/kimlab/home Department of Biological SciencesKAIST
2022.05.25 View 9430 -
Neuromorphic Memory Device Simulates Neurons and Synapses
Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence
Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.
Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.
Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.
The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory.
Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.”
This result entitled “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse” was published in the May 19, 2022 issue of Nature Communications.
-Publication:Sang Hyun Sung, Tae Jin Kim, Hyera Shin, Tae Hong Im, and Keon Jae Lee (2022) “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse,” Nature Communications May 19, 2022 (DOI: 10.1038/s41467-022-30432-2)
-Profile:Professor Keon Jae Leehttp://fand.kaist.ac.kr
Department of Materials Science and EngineeringKAIST
2022.05.20 View 13478 -
Anonymous Donor Makes a Gift of Property Valued at 30 Billion KRW
The KAIST Development Foundation announced on May 9 that an anonymous donor in his 50s made a gift of real estate valued at 30 billion KRW. This is the first donation from an anonymous benefactor on such a grand scale. The benefactor expressed his wishes to fund scholarships for students in need and R&D for medical and bio sciences.
According to the Development Foundation official, the benefactor is reported to have said that he felt burdened that he earned much more than he needed and was looking for the right way to share his assets. The benefactor refused to hold an official donation ceremony and meeting with high-level university administrators.
The donor believes that KAIST is filled with young and dynamic energy, saying, “I would like to help KAIST move forward and create breakthroughs that will benefit the nation as well as all humanity.”
Before making up his mind to give his asset to KAIST, he had planned to establish his own social foundation but he changed his mind. “I decided that an investment in education would be the best investment,” he said. He explained that he was inspired by his KAIST graduate friend who is running a company. He was deeply motivated to help KAIST after witnessing the KAIST graduate’s passion for conducting his business.
After receiving the gift, KAIST President Kwang Hyung Lee was thankful for the full support and trust of the benefactor. “We will spare no effort to foster next-generation talents and advance science and technology in the field of biomedicine.”
2022.05.11 View 5561 -
LightPC Presents a Resilient System Using Only Non-Volatile Memory
Lightweight Persistence Centric System (LightPC) ensures both data and execution persistence for energy-efficient full system persistence
A KAIST research team has developed hardware and software technology that ensures both data and execution persistence. The Lightweight Persistence Centric System (LightPC) makes the systems resilient against power failures by utilizing only non-volatile memory as the main memory.
“We mounted non-volatile memory on a system board prototype and created an operating system to verify the effectiveness of LightPC,” said Professor Myoungsoo Jung. The team confirmed that LightPC validated its execution while powering up and down in the middle of execution, showing up to eight times more memory, 4.3 times faster application execution, and 73% lower power consumption compared to traditional systems.
Professor Jung said that LightPC can be utilized in a variety of fields such as data centers and high-performance computing to provide large-capacity memory, high performance, low power consumption, and service reliability.
In general, power failures on legacy systems can lead to the loss of data stored in the DRAM-based main memory. Unlike volatile memory such as DRAM, non-volatile memory can retain its data without power. Although non-volatile memory has the characteristics of lower power consumption and larger capacity than DRAM, non-volatile memory is typically used for the task of secondary storage due to its lower write performance. For this reason, nonvolatile memory is often used with DRAM. However, modern systems employing non-volatile memory-based main memory experience unexpected performance degradation due to the complicated memory microarchitecture.
To enable both data and execution persistent in legacy systems, it is necessary to transfer the data from the volatile memory to the non-volatile memory. Checkpointing is one possible solution. It periodically transfers the data in preparation for a sudden power failure. While this technology is essential for ensuring high mobility and reliability for users, checkpointing also has fatal drawbacks. It takes additional time and power to move data and requires a data recovery process as well as restarting the system.
In order to address these issues, the research team developed a processor and memory controller to raise the performance of non-volatile memory-only memory. LightPC matches the performance of DRAM by minimizing the internal volatile memory components from non-volatile memory, exposing the non-volatile memory (PRAM) media to the host, and increasing parallelism to service on-the-fly requests as soon as possible.
The team also presented operating system technology that quickly makes execution states of running processes persistent without the need for a checkpointing process. The operating system prevents all modifications to execution states and data by keeping all program executions idle before transferring data in order to support consistency within a period much shorter than the standard power hold-up time of about 16 minutes. For consistency, when the power is recovered, the computer almost immediately revives itself and re-executes all the offline processes immediately without the need for a boot process.
The researchers will present their work (LightPC: Hardware and Software Co-Design for Energy-Efficient Full System Persistence) at the International Symposium on Computer Architecture (ISCA) 2022 in New York in June. More information is available at the CAMELab website (http://camelab.org).
-Profile: Professor Myoungsoo Jung Computer Architecture and Memory Systems Laboratory (CAMEL)http://camelab.org School of Electrical EngineeringKAIST
2022.04.25 View 22958 -
Professor Hyunjoo Jenny Lee to Co-Chair IEEE MEMS 2025
Professor Hyunjoo Jenny Lee from the School of Electrical Engineering has been appointed General Chair of the 38th IEEE MEMS 2025 (International Conference on Micro Electro Mechanical Systems). Professor Lee, who is 40, is the conference’s youngest General Chair to date and will work jointly with Professor Sheng-Shian Li of Taiwan’s National Tsing Hua University as co-chairs in 2025.
IEEE MEMS is a top-tier international conference on microelectromechanical systems and it serves as a core academic showcase for MEMS research and technology in areas such as microsensors and actuators.
With over 800 MEMS paper submissions each year, the conference only accepts and publishes about 250 of them after a rigorous review process recognized for its world-class prestige. Of all the submissions, fewer than 10% are chosen for oral presentations.
2022.04.18 View 7045 -
Professor Lik-Hang Lee Offers Metaverse Course for Hong Kong Productivity Council
Professor Lik-Hang Lee from the Department of Industrial System Engineering will offer a metaverse course in partnership with the Hong Kong Productivity Council (HKPC) from the Spring 2022 semester to Hong Kong-based professionals.
“The Metaverse Course for Professionals” aims to nurture world-class talents of the metaverse in response to surging demand for virtual worlds and virtual-physical blended environments. The HKPC’s R&D scientists, consultants, software engineers, and related professionals will attend the course. They will receive a professional certificate on managing and developing metaverse skills upon the completion of this intensive course.
The course will provide essential skills and knowledge about the parallel virtual universe and how to leverage digitalization and industrialization in the metaverse era. The course includes comprehensive modules, such as designing and implementing virtual-physical blended environments, metaverse technology and ecosystems, immersive smart cities, token economies, and intelligent industrialization in the metaverse era.
Professor Lee believes in the decades to come that we will see rising numbers of virtual worlds in cyberspace known as the ‘Immersive Internet’ that will be characterized by high levels of immersiveness, user interactivity, and user-machine collaborations.
“Consumers in virtual worlds will create novel content as well as personalized products and services, becoming as catalyst for ‘hyperpersonalization’ in the next industrial revolution,” he said.
Professor Lee said he will continue offering world-class education related to the metaverse to students in KAIST and professionals from various industrial sectors, as his Augmented Reality and Media Lab will focus on a variety of metaverse topics such as metaverse campuses and industrial metaverses.
The HKPC has worked to address innovative solutions for Hong Kong industries and enterprises since 1967, helping them achieve optimized resource utilization, effectiveness, and cost reduction as well as enhanced productivity and competitiveness in both local and international markets. The HKPC has advocated for facilitating Hong Kong’s reindustrialization powered by Industry 4.0 and e-commerce 4.0 with a strong emphasis on R&D, IoT, AI, digital manufacturing.
The Augmented Reality and Media Lab led by Professor Lee will continue its close partnerships with HKPC and its other partners to help build the epicentre of the metaverse in the region. Furthermore, the lab will fully leverage its well-established research niches in user-centric, virtual-physical cyberspace (https://www.lhlee.com/projects-8 ) to serve upcoming projects related to industrial metaverses, which aligns with the departmental focus on smart factories and artificial intelligence.
2022.04.06 View 8379 -
Distinguished Professor Sukbok Chang Named the 2022 Ho-Am Laureate
Distinguished Professor Sukbok Chang from the Department of Chemistry was named the awardee of the Ho-Am Prize in the fields of chemistry and life sciences. The award has recognized the most distinguished scholars, individuals, and organizations in physics and mathematics, chemistry and life sciences, engineering, medicine, arts, and community service in honor of the late founder of Samsung Group Byong-Chul Lee, whose penname is Ho-Am. The awards ceremony will be held on May 31 and awardees will receive 300 million KRW in prize money.
Professor Chang became the fourth KAIST Ho-Am laureate following Distinguished Professor Sang Yup Lee in engineering in 2014, Distinguished Professor Jun Ho Oh in engineering in 2016, and Distinguished Professor Gou Young Koh in medicine in 2018.
Professor Chang is a renowned chemist who has made pioneering research in the area of transition metal catalysis for organic transformations. Professor Chang is also one of the Highly Cited Researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. He has made the list seven years in a row from 2016.
Professor Chang has developed a range of new and impactful C-H bond functionalization reactions. By using his approaches, value-added molecules can be readily produced from chemical feedstocks, representatively hydrocarbons and (hetero)arenes. His research team elucidated fundamental key mechanistic aspects in the course of the essential C-H bond activation process of unreactive starting materials. He was able to utilize the obtained mechanistic understanding for the subsequent catalyst design to develop more efficient and highly (stereo)selective catalytic reactions.
Among the numerous contributions he made, the design of new mechanistic approaches toward metal nitrenoid transfers are of especially high impact to the chemical community. Indeed, a series of important transition metal catalyst systems were developed by Professor Chang to enable the direct and selective C-H amidation of unreactive organic compounds, thereby producing aminated compounds that have important applicability in synthetic, medicinal, and materials science. He has also pioneered in the area of asymmetric C-H amination chemistry by creatively devising various types of chiral transition metal catalyst systems, and his team proved for the first time that chiral lactam compounds can be obtained at an excellent level of stereoselectivity.
Another significant contribution of Professor. Chang was the introduction of dioxazolones as a robust but highly reactive source of acyl nitrenoids for the catalytic C-H amidation reactions, and this reagent is now broadly utilized in synthetic chemistry worldwide.
Professor Chang also leads a research group in the Center for Catalytic Hydrocarbon Functionalizations at the Institute for Basic Science.
2022.04.06 View 7885 -
Mathematicians Identify a Key Source of Cell-to-Cell Variability in Cell Signaling
Systematic inferences identify a major source of heterogeneity in cell signaling dynamics
Why do genetically identical cells respond differently to the same external stimuli, such as antibiotics? This long-standing mystery has been solved by KAIST and IBS mathematicians who have developed a new framework for analyzing cell responses to some stimuli. The team found that the cell-to-cell variability in antibiotic stress response increases as the effective length of the cell signaling pathway (i.e., the number of rate-limiting steps) increases. This finding could identify more effective chemotherapies to overcome the fractional killing of cancer cells caused by cell-to-cell variability.
Cells in the human body contain signal transduction systems that respond to various external stimuli such as antibiotics and changes in osmotic pressure. When an external stimulus is detected, various biochemical reactions occur sequentially. This leads to the expression of relevant genes, allowing the cells to respond to the perturbed external environment. Furthermore, signal transduction leads to a drug response (e.g., antibiotic resistance genes are expressed when antibiotic drugs are given).
However, even when the same external stimuli are detected, the responses of individual cells are greatly heterogeneous. This leads to the emergence of persister cells that are highly resistant to drugs. To identify potential sources of this cell-to cell variability, many studies have been conducted. However, most of the intermediate signal transduction reactions are unobservable with current experimental techniques.
A group of researchers including Dae Wook Kim and Hyukpyo Hong and led by Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences and IBS Biomedical Mathematics Group solved the mystery by exploiting queueing theory and Bayesian inference methodology. They proposed a queueing process that describes the signal transduction system in cells. Based on this, they developed Bayesian inference computational software using MBI (the Moment-based Bayesian Inference method). This enables the analysis of the signal transduction system without a direct observation of the intermediate steps. This study was published in Science Advances.
By analyzing experimental data from Escherichia coli using MBI, the research team found that cell-to-cell variability increases as the number of rate-limiting steps in the signaling pathway increases.
The rate-limiting steps denote the slowest steps (i.e., bottlenecks) in sequential biochemical reaction steps composing cell signaling pathways and thus dominates most of the signaling time. As the number of the rate-limiting steps increases, the intensity of the transduced signal becomes greatly heterogeneous even in a population of genetically identical cells. This finding is expected to provide a new paradigm for studying the heterogeneous antibiotic resistance of cells, which is a big challenge in cancer medicine.
Professor Kim said, “As a mathematician, I am excited to help advance the understanding of cell-to-cell variability in response to external stimuli. I hope this finding facilitates the development of more effective chemotherapies.”
This work was supported by the Samsung Science and Technology Foundation, the National Research Foundation of Korea, and the Institute for Basic Science.
-Publication:Dae Wook Kim, Hyukpyo Hong, and Jae Kyoung Kim (2022) “Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: the rate-limiting step number,”Science Advances March 18, 2022 (DOI: 10.1126/sciadv.abl4598)
-Profile:Professor Jae Kyoung Kimhttp://mathsci.kaist.ac.kr/~jaekkim
jaekkim@kaist.ac.kr@umichkim on TwitterDepartment of Mathematical SciencesKAIST
2022.03.29 View 10046