Daegu Gyeongbuk Institute of Science and Technology
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Novel Series Elastic Actuator towards High Torque Capacity with High Sensitive Torque Measurement
No full textSeries Elastic Actuator (SEA) has widely been used in various robotic applications due to its ability to provide safe and accurate force. However, conventionally, securing the high torque sensitivity of the SEA of the spring is challenging due to the limitation of natural frequency and torque capacity, making it less applicable in certain situations. Therefore, this paper proposes a novel Series Spring-Embraced Elastic Actuator (SSE-EA), which uses a Transmitted Force-Sensing SEA (TFSEA) structure and a vertical torsional spring to high torque sensitivity. The design method of the spring is proposed to maximize the advantages of the structure. In addition, mechanisms and controller designs are presented to achieve sensitive torque control for heavy load tasks. Through several validations, we evaluate the performance and applicability of the SSE-EA. IEEEFALSEsciescopu
MDGAs perform activity- dependent synapse type- specific suppression via distinct extracellular mechanisms
No full textMDGA (MAM domain containing glycosylphosphatidylinositol anchor) family proteins were previously identified as synaptic suppressive factors. However, various genetic manipulations have yielded often irreconcilable results, precluding precise evaluation of MDGA functions. Here, we found that, in cultured hippocampal neurons, conditional deletion of MDGA1 and MDGA2 causes specific alterations in synapse numbers, basal synaptic transmission, and synaptic strength at GABAergic and glutamatergic synapses, respectively. Moreover, MDGA2 deletion enhanced both N - methyl - D - aspartate (NMDA) receptor - and alpha- amino - 3 - hydroxy - 5 - methylisoxazole - 4 - propionic acid (AMPA) receptor - mediated postsynaptic responses. Strikingly, ablation of both MDGA1 and MDGA2 abolished the effect of deleting individual MDGAs that is abrogated by chronic blockade of synaptic activity. Molecular replacement experiments further showed that MDGA1 requires the meprin/ A5 protein/PTPmu (MAM) domain, whereas MDGA2 acts via neuroligin - dependent and/or MAM domain - dependent pathways to regulate distinct postsynaptic properties. Together, our data demonstrate that MDGA paralogs act as unique negative regulators of activity - dependent postsynaptic organization at distinct synapse types, and cooperatively contribute to adjustment of excitation-inhibition balance.FALSEsciescopu
Digital-Twin Simulation for a Comprehensive Analysis of Silicon/Graphite Composite Electrodes
No full textSiOx/graphite composite electrodes, microstructure, mechanical degradation, Digital twin simulation, lithium-ion batteryThis study investigates the electrochemical and mechani al behavior of SiOx/graphite composite electrodes under different charge rates using a digital twin simulation. We utilized FIB-SEM to capture the 3D structure of the electrodes, enabling accurate multiphysic simulation. The experiments revealed that higher SOL led to significant mechanical degradation, such as particle cracking and interparticle disconnection, reducing the cycle life of the electrodes. The simulations have an accuracy of 0.54% compared to the experimental results, demonstrating that fast charging results in lower SOL, minimal volume expansion, and lower internal stress. Conversely, slow charging increases SOL, leading to greater volume expansion and higher internal stress. This stres is concentrated around SiOx agglomeration, causing mechanical failures. The study also observed changes in porosity and tortuosity during charging, with slower rates causing pore blockage and increased ionic pathway length. Our findings highlight the importance of controlling the dispersion of Si- based active materials and optimizing electrode density to mitigate stress concentration and mechanical degradation. This study provides valuable insights into the structural and mechanical stability of Si-based electrodes, offering a method to evaluate their performance and aiding the development of more durable Si-based lithium-ion batteries.|이 연구는 다양한 충전 율속에서 실리콘/흑연 복합 전극의 전기화학적 및 기계적 거동을 실험 기법과 디지털 트윈 시뮬레이션을 통하여 조사하였습니다. 전극의 삼차원 구조를 포착하기 위해 FIB-SEM을 활용하여 실제 전극 형상을 반영한 삼차원 구조체를 생성하였으며, 구조적 및 전기화학적 특성의 정확한 시뮬레이션을 가능하게 했습니다. 실험 결과, 높은 리튬화 상태는 입자 균열 및 입자 간 연결 단락과 같은 심각한 기계적 손상을 초래하여 전극의 수명을 단축시키는 것으로 나타났습니다. 그리고 낮은 리튬화 상태에서는 오히려 부피 팽창이 적어 기계적 열화의 영향이 적어 수명 특성이 더 좋았습니다. 시뮬레이션 결과는 실험 결과와 비교하였을 때 0.54% 오차로 일치하였으며, 빠른 충전이 낮은 리튬화 상태, 낮은 부피 팽창 및 낮은 내부 스트레스를 초래함을 보여주었습니다. 반면, 느린 충전은 리튬화 상태를 증가시켜 더 큰 부피 팽창과 높은 내부 응력을 유발했습니다. 이 응력은 실리콘 입자 주변에 집중되어 기계적 실패를 일으켰습니다. 또한, 느린 충전 속도가 기공 닫힘 및 이온 경로 길이 증가를 초래하면서 충전 중 공극도 및 굴곡도의 변화를 일으켰습니다. 위 연구 결과를 통해 실리콘 기반 활물질의 분산을 제어하고 전극 밀도를 최적화하여 응력 집중 및 기계적 손상을 완화하는 것의 중요성을 강조합니다. 또한 실리콘 기반의 음극에서 리튬화 상태에 따라 전극이 받는 기계적 열화의 정도가 발생할 수 있습니다. 이 연구는 실리콘 기반 전극의 구조적 및 기계적 안정성을 평가할 수 있는 방법론을 제시하며 보다 수명특성이 뛰어난 실리콘 기반 리튬 이온 배터리를 개발하는 데 도움이 될 수 있습니다.1. Introduction 1
2. Experiment Details 2
3. Simulation Model 4
4. Result & Discussion 7
5. Conclusion 18
References 21MasterdCollectio
Robust Cryptosystem Identification Under Various Operation Modes Using Deep Recurrent Neural Networks
No full textIn the Ciphertext Only Attack (COA), an attacker can access and use only ciphertexts, identifying the type of cryptosystem is critical for further attack. The attacker can analyze patterns in the ciphertexts that have different forms according to the cryptosystem and recognize the type of cryptosystem. We propose deep learning-based cryptosystem identification by investigating eight cryptosystems, DES, S-DES, AES, S-AES, Blowfish, RC2, SPECK, and RSA. The Recurrent Neural Network (RNN)-based deep learning model with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) is utilized to identify cryptosystems. The proposed method is used to classify ciphertext in each operation mode such as CBC, CFB, OFB, and CTR, into the corresponding cipher system. The performance of the proposed method was evaluated with recall, precision, classification accuracy, and F1 score. To verify effectiveness and superiority, we compared the proposed method with different machine learning-based and deep learning-based classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and BERT, a Large Language Model (LLM). Moreover, the previous methods in cryptosystem identification were also compared with the proposed method, and the results showed that eight cryptosystems were successfully recognized under various operation modes. The proposed method outperformed the other machine learning-based, and its deep learning-based classifiers were superior in cryptosystem identification. Furthermore, the proposed method showed a classification accuracy of 97.3 and 96.2 % in CBC and CFB, respectively, while the highest accuracy in the previous methods was 20% in CBC and 85.5% in CFB. © 2024 IEEE
A Discrete Multitone Wireline Transceiver With Clipping Ratio Optimization For ADC-Based High-Speed Serial Links
No full textIn this paper, we investigated the relationship between clipping ratio and bit-error rate (BER) for a discrete multitone (DMT) wireline transceiver. The peak-to-average-power ratio (PAPR) controls the trade-off between signal-to-noise ratio (SNR) and non-linear distortion, such as clipping. The bit-errorrate (BER) performance degrades for both cases: high distortion due to the low PAPR and low SNR caused by the high PAPR. The optimal spot is obtained by conducting a sweep simulation on MATLAB software. The simulation results demonstrate that the 1E-6 order BER is achieved with the 160 Gb/s data rate and 12.3dB PAPR when communicating over a channel, exhibiting 18dB channel insertion loss (IL) at Nyquist frequency. © 2024 IEEE
Advanced Full-Color Perovskite Nanocrystal Patterning for Next-Generation Ultrathin Skin-Attachable Displays
No full textWe present a novel ultrahigh-resolution perovskite nanocrystal (PeNC) patterning technique for ultrathin wearable displays. Our method employs double-layer transfer printing to layer PeNCs and organic charge transport layers, preventing internal cracking and achieving RGB pixelated patterns at 2550 PPI and monochromatic patterns at 33,000 line pairs per inch. The resulting perovskite light-emitting diodes (PeLEDs) display exceptional electroluminescence, with quantum efficiencies significantly higher than previously reported printed PeLEDs. This technology enables the creation of flexible, multicolor PeLEDs that adhere to curvilinear surfaces, including human skin, supporting various mechanical deformations. These advancements suggest significant potential for PeLEDs in future high-definition wearable displays
Double-edged effects of electrolyte additive on interfacial stability in fast-charging lithium-ion batteries
No full textEssential, but not too much-Roles of electrolyte additive (FEC) in Li+ solvation structures and interfacial reactions are revealed in a high-concentration electrolyte. While excessive FEC addition can intervene in original Li+ solvation, compromising interfacial kinetics, minimal FEC is essential in fast-charging applications to seamlessly facilitate Li+ desolvation while reinforcing interfacial stability.FALSEsciescopu
A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation
No full textEffiDynaMix, a novel, efficient, gray-box, nonparametric dynamics modeling method, integrates mathematical dynamics with Gaussian Mixture Model (GMM) for simplified training data creation and improved generalization. It outperforms traditional methods like conv-GMM, GP, and LSTM in training efficiency and accuracy with new data. By leveraging dynamic equations, EffiDynaMix enhances learning efficiency and adaptability, offering advancements in robotic system precision and computational efficiency, leading to faster and more responsive robots. © 2024 IEEE
대사상태 의존적 감정조절에 대한 해마 이끼 세포 내 GLP1 수용체의 역할
No full textmetabolic state, hippocampal mossy cell, GLP1 receptor, anxiety, depression, emotionAnxiety is a feeling of fear and unease that helps us avoid threat. Previous research indicates that metabolic state is related to emotional regulation such as fear, but the relationship between specific metabolic hormones and mood-related behavior is unexplored. Glucagon-like peptide 1 (GLP1), a hormone primarily secreted by the small intestine regulates metabolic state. The GLP1 receptor (GLP1r) is distributed across various regions including the ventral hippocampus. However, the role of GLP1r in hippocampal mossy cells remains unclear. Here, we demonstrated that mice exhibited reduced anxiety levels when in a starved state. Furthermore, genetic silencing of GLP1r specifically in the ventral hilus exhibits lower anxiety and depression-like behaviors. These findings highlight the critical role of hippocampal GLP1 receptors in metabolic state- dependent mood regulation. This research provides novel insights into the complex interplay between anxiety disorders and metabolic conditions, providing potentials for therapeutic interventions targeting GLP1r in the hippocampus.
Keywords: metabolic state, hippocampal mossy cell, GLP1 receptor, anxiety, depression, emotion|불안은 두려움과 불안감의 감정이며, 위협을 피하는 데 도움을 줍니다. 이전 연구에 따르면 대사 상태는 두려움과 같은 감정 조절과 관련이 있지만 특정 대사 호르몬과 기분 관련 행동 사이의 관계는 탐구되지 않았습니다. 소장에서 주로 분비되는 호르몬인 글루카곤 유사 펩타이드 1(GLP1)은 대사 상태를 조절합니다. GLP1 수용체(GLP1r)는 배측 해마를 포함한 다양한 영역에 분포되어 있습니다. 그러나 해마 이끼 세포에서 GLP1r 의 역할은 아직 불분명합니다. 여기에서 우리는 쥐가 굶주린 상태에 있을 때 불안 수준이 감소한다는 것을 입증했습니다. 더욱이, 특히 배측 hilus 에서 GLP1r 의 유전적 침묵은 낮은 불안 및 우울증세와 유사한 행동을 나타냅니다. 이러한 발견은 대사 상태 의존적 기분 조절에서 해마 GLPr 의 중요한 역할을 강조합니다. 이 연구는 불안 장애와 대사 상태 사이의 복잡한 상호 작용에 대한 새로운 시각을 제공하여 해마에서 GLP1r 을 표적으로 하는 치료 중재의 가능성을 제공합니다.
키워드: 대사상태, 해마 이끼세포, GLP1 수용체, 불안, 우울증, 감정Ⅰ. Introduction 1
II. Methods 3
III. Results 8
IV. Discussion 22
V. Reference 25
VI. 요약문 27MasterdCollectio
ACCELERATED CELL DEATH 6 is a crucial genetic factor shaping the natural diversity of age- and salicylic acid-induced leaf senescence in Arabidopsis
No full textLeaf senescence is a crucial process throughout evolution, vital for plant fitness as it facilitates the gradual shift of energy allocation between photosynthesis and catabolism overtime. This onset is influenced by a complex interplay of genetic and environmental factors, making senescence a key adaptation mechanism for plants in their natural habitats. Our study investigated the genetic mechanism underlying age-induced leaf senescence in Arabidopsis natural populations. Using a phenome high-throughput investigator, we comprehensively analyzed senescence responses across 234 Arabidopsis accessions and identified that environmental factors (e.g., ambient temperature) and physiological factors (e.g., defense responses) are substantially linked to senescence phenotypes. Through genome-wide association mapping, we identified the ACCELERATED CELL DEATH 6 (ACD6) locus as a potential regulator of senescence variation among natural accessions. Knocking out ACD6 in accessions with early and delayed senescence phenotypes resulted in varying degrees of delay in age-induced senescence, highlighting the accession-dependent regulatory role of ACD6 in leaf senescence. Furthermore, our findings suggest ACD6's involvement in senescence regulation via the salicylic acid signaling pathway. In summary, our study sheds light on the genetic regulation of leaf senescence in Arabidopsis natural populations, with the discovery of ACD6 as a potential candidate for genetic modification to enhance plant adaptation and survival. © 2024 Scandinavian Plant Physiology Society.FALSEsciescopu