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Mechanistic Insights into DNA Recognition by FOXO4 and Development of a Peptide Targeting Senescent Cells via FOXO4-p53 Inhibition
No full textThis thesis investigates the molecular mechanisms underlying the function of the human forkhead box O 4 (FOXO4) transcription factor, elucidates its DNA recognition mechanism, and develops a novel therapeutic approach for targeting senescent cells, highlighting its potential impact on aging biology.
First, we explore the mechanism by which FOXO4 differentially recognizes target and non-target DNA sequences despite exhibiting similar binding affinities. This selectivity is crucial for precise transcriptional regulation but has remained unclear. Through comprehensive NMR-based analyses, particularly paramagnetic relaxation enhancement (PRE) experiments, we demonstrate that the conserved region 3 (CR3) transactivation domain (TAD) plays a crucial regulatory role in DNA sequence discrimination. Our findings reveal that CR3 remains proximal to the forkhead domain (FHD) when non-target DNA is present, effectively occluding the non-target DNA-binding interface. In contrast, CR3 is released upon FHD binding to target DNA, as the FHD forms a stable complex with the DNA. Furthermore, 15N relaxation measurements indicate that FHD exhibits flexibility when bound to non-target DNA but adopts a more rigid conformation upon target DNA binding. These interactions are primarily mediated by electrostatic forces, as evidenced by their sensitivity to salt concentrations. This sensitivity provides insight into how FOXO4 can navigate the cellular environment to locate and bind its target sequences amidst the vast genomic landscape. The dynamic interplay between CR3 and FHD represents a novel mechanism for transcription factor target selection that extends conventional DNA-protein recognition models.
Next, we apply our understanding of FOXO4 interactions to address the challenge of cellular senescence in aging. Senescent cells, characterized by permanent cell cycle arrest and secretion of inflammatory factors, contribute significantly to age-related pathologies and cancer recurrence following chemotherapy. We aim to target the FOXO4-p53 interaction, essential for senescent cell survival and potentially druggable. Through systematic biophysical methods, including NMR spectroscopy and cellular experiments, we determined critical regions within the p53 TAD involved in FOXO4 binding. This detailed structural knowledge enabled us to design CPP-CAND, an optimized cell-penetrating peptide inhibitor targeting the FOXO4-p53 interaction. Our peptide demonstrated remarkable selectivity in disrupting FOXO4-p53 nuclear foci and inducing apoptosis in senescent cells while sparing non-senescent counterparts. Notably, CPP-CAND proved effective against senescent cancer cells induced by common chemotherapy treatments with doxorubicin and cisplatin, suggesting potential applications as an adjuvant therapy to prevent cancer recurrence. Mechanistic studies confirmed that CPP-CAND functions by activating caspase-mediated apoptosis pathways specifically in senescent cells, offering advantages in selectivity, efficacy, and cost-effectiveness over existing senolytic approaches.
Collectively, this research advances our understanding of transcription factor biology and demonstrates how mechanistic insights at the molecular level can be translated into targeted therapeutic strategies. We have elucidated a novel regulatory mechanism for FOXO4's DNA target selection and leveraged our understanding of protein-protein interactions to develop a promising senolytic agent. The designed peptide inhibitor offers significant potential for addressing challenges in aging biology and cancer therapy through specific disruption of the FOXO4-p53 interaction, thereby opening new avenues for intervention in age-related diseases and chemotherapy-induced senescence.DoctorAbstract i
List of contents iii
List of tables v
List of figures vi
Chapter 1. Introduction: Structural Features and Functional Roles of FOXO Transcription Factors 1
1. 1. Introduction 2
1. 2. Structural features and DNA recognition of FOXO proteins 2
1. 3. Functional diversity of FOXO family members 3
1. 4. FOXO4: a target for therapeutic intervention 4
1. 5. Conclusion 5
Chapter 2. NMR-Based Analysis of FOXO4's Differential DNA Sequence Recognition 7
2. 1. Introduction 8
2. 2. Materials and methods 11
2. 2-1. Sample preparation 11
2. 2-2. Nuclear magnetic resonance (NMR) experiments 11
2. 2-3. 15N Relaxation Measurements 12
2. 2-4. Isothermal titration calorimetry (ITC) 13
2. 3. Results 14
2. 3-1. CR3 is positioned near the FHD when bound to non-target DNA 14
2. 3-2. FHD-Non-Target DNA Interaction Shows Fast Exchange Under High Salt Concentration 15
2. 3-3. FHD Exhibits Increased Flexibility When Binding Non-Target DNA 16
2. 4. Discussion 17
2. 5. Summary 20
Chapter 3. Design of Senolytic Peptide for FOXO4-p53 Pathway Disruption to Trigger Apoptosis in Senescent Cells 36
3. 1. Introduction 37
3. 2. Materials and methods 40
3. 2-1. Sample preparation 40
3. 2-2. NMR experiments 40
3. 2-3. Fluorescence Polarization Anisotropy Assay (FPA) 41
3. 2-4. Cell Culture 41
3. 2-5. Cell Viability Measurements 42
3. 2-6. Immunofluorescence Assays 42
3. 2-7. In vitro cellular uptake by flow cytometry 43
3. 3. Results 44
3. 3-1. The p53 TAD2 region is essential for mediating its interaction with FOXO4 FHD 44
3. 3-2. Crucial hydrophobic amino acid residues within p53 TAD2 play a vital role in its binding to
FOXO4 FHD 45
3. 3-3. Engineering a Cell-Permeable Peptide by Reducing Acidity 46
3. 3-4. CPP-CAND Demonstrates Superior Senolytic Activity Through Enhanced Cellular Uptake 47
3. 3-5. CPP-CAND Disrupts FOXO4-p53 Complexes and Triggers Caspase-Mediated Apoptosis 48
3. 4. Discussion 50
3. 5. Summary 53
Appendix 78
References 90
Korean Abstract 100
Curriculum Vitae 102
Acknowledgements 10
Study on a Functional Role of GPR39 in Keratinocytes
No full textGPR39, an orphan G-protein-coupled receptor (GPCR), is widely expressed across various tissues and has been implicated in promoting keratinocyte proliferation in the skin. However, studies on its signaling pathways and specific functions in this tissue are limited. In this study, we investigated the role of GPR39 in keratinocyte proliferation using the HaCaT cell line and a peptide agonist, GJ39A, targeting GPR39. We first observed that GJ39A treatment increased intracellular calcium levels, and BrdU assays confirmed that GJ39A promoted keratinocyte proliferation. Further, using various inhibitors, we determined that this proliferation occurred via the PLC-Ca2+-CaMKII-Raf-MEK-ERK signaling pathway. In addition, GJ39A treatment increased the expression of Cyclin D1, a key regulator of cell cycle progression, as well as the expression levels of tight junction proteins occludin and ZO-1, which are essential for skin barrier function. Finally, we observed that GPR39 activation enhanced keratinocyte wound closure in an in vitro scratch model. Additionally, complementary Transwell assays confirmed that GJ39A treatment significantly increased HaCaT cell migration, reinforcing the findings from the scratch model. These findings suggest that GPR39 plays a critical role in keratinocyte proliferation and skin tissue repair, potentially promoting wound healing through Ca2+-dependent signaling pathways.MasterABSTRACT ⅰ
CONTENTS ⅱ
LIST OF FIGURES ⅳ
Ⅰ. INTRODUCTION 1
Ⅱ. MATERIALS AND METHODS 3
2.1 Peptide synthesis 3
2.2 Cell culture 3
2.3 Intracellular calcium measurement 3
2.4 Cell proliferation assay 4
2.5 Chemicals 4
2.6 Western blot analysis 4
2.7 Wound healing assay 5
2.8 Transwell assay 5
2.9 Statistical analysis 6
Ⅲ. RESULT 7
3.1 Effect of GJ39A on HaCaT Cell Intracellular Calcium Levels and Proliferation. 7
3.2 Optimization of ERK Phosphorylation by GJ39A: Time and Concentration Analysis 7
3.3 Investigation of Signaling Pathways Involved in ERK Phosphorylation Using
Inhibitors 7
3.4 Increased Expression of Cyclin D1, ZO-1, and Occludin Induced by GJ39A 8
3.5 Wound Healing Assay in HaCaT Cells Treated with GJ39A 8
3.6 Evaluation of Cell Migration Induced by GJ39A in HaCaT Cells Using Transwell
Assay 9
Ⅳ. DISCUSSION 10
Ⅴ. SUMMARY 12
Ⅵ. REFERENCES 20
Ⅶ. ACKNOWLEDGEMENT 2
Molecular Aggregation and Percolation Behavior in Aqueous Binary Liquid Mixtures
No full textUnderstanding how small organic molecules aggregate and influence solvent structure is fundamental to explaining phenomena ranging from phase separation to protein destabilization. In complex biological environments, such solutes can subtly or drastically alter the hydrogen bonding network of water, affect solvation layers, and promote conformational changes in biomolecules. Our study provides a systematic framework for probing this relationship, offering insights that can guide further exploration into solute mediated protein unfolding, solvent dependent phase transitions, and the design of solute in aqueous environments. We investigate the molecular aggregation and percolation behavior of ethanol (ETH), tetramethylurea (TMU), and tetrahydrofuran (THF) in aqueous binary mixtures employing molecular dynamics simulations using graph-theoretical analysis, and percolation analysis at temperature, 350 K. Our results show that percolation behavior is governed not simply by solute concentration but by how molecules interact and spatially organize. ETH remains well-solvated with weak self-association, showing delayed percolation transition with low spanning probability even at higher concentration. THF undergoes early and sharp percolation due to strong self-aggregation and phase separation tendencies, forming compact clusters giving high fractal dimension values greater then critical value of 2.53 with minimal impact on water structure. TMU exhibits a unique dual behavior, forming spatially dispersed with low h-value, but internally dense clusters with high spanning probability and large fractal dimension value, that percolate without macroscopic phase separation, while simultaneously causing significant disruption to the hydrogen-bond network of water. Our findings demonstrate that the balance between solute-solute aggregation and solute-water interactions plays a critical role in network connectivity and percolation thresholds. Further the results offer into how solutes modulate aqueous environments and highlight TMU’s distinct capacity to perturb water structure, providing a molecular basis for its known effects on protein conformation and stability.MasterChapter I. INTRODUCTION 1
Chapter II. METHODS 3
2.1. Computational Details 3
2.2. Radial Distribution Function 3
2.3. Graph Theoretical Analysis 4
2.4. Cluster Size Distribution 4
2.5. h-value for inhomogeneity 4
2.6. Percolation Analysis 5
2.6.1. Percolating Cluster 5
2.6.2. Fractal Dimension 6
Chapter III. RESULT AND DISCUSSION 7
Chapter IV. CONCLUSION 16
References 17
Acknowledgements 19
Curriculum Vitae 2
Circulating BMP-7 Level is Independent of Sarcopenia in Older Asian Adults
No full textBackground: In vitro and animal studies have demonstrated that bone morphogenetic protein-7 (BMP-7), renowned for its osteogenic properties, also exerts beneficial effects on muscle metabolism by enhancing myogenesis and reversing muscle atrophy. Despite being proposed as a common regulatory factor for both muscle and bone, the impact of BMP-7 on human muscle health has not been thoroughly investigated. Methods: This cross-sectional study involved 182 community-dwelling older adults who underwent a comprehensive geriatric assessment in South Korea. Sarcopenia was diagnosed using Asian-specific cutoffs, and serum BMP-7 levels were quantified via enzyme immunoassay. Results: The mean age of the participants was 72.2±7.3 years, with 62.6% being female. After adjustments for confounders, serum BMP-7 levels were not significantly different between individuals with and without sarcopenia, nor were there differences based on skeletal muscle mass, strength, or physical performance levels (p=0.423 to 0.681). Likewise, no correlations were detected between circulating BMP-7 levels and any sarcopenia assessment metrics such as skeletal muscle index, grip strength, gait speed, or chair stand completion times (p=0.127 to 0.577). No significant associations were observed between increases in serum BMP-7 concentrations and the risk of sarcopenia or poor muscle phenotypes (p=0.431 to 0.712). Stratifying participants into quartiles based on serum BMP-7 levels also indicated no differences in sarcopenia-related parameters (p=0.663 to 0.996). Conclusion: Despite experimental evidence supporting BMP-7’s role in muscle metabolism, this study found no significant association between serum BMP-7 levels and clinical indicators of muscle health in older adults. These findings challenge the utility of serum BMP-7 as a biomarker for sarcopenia in this demographic. © 2025 by The Korean Geriatrics Society.TRUEscopuskc
OnomaCap: Making Non-speech Sound Captions Accessible and Enjoyable through Onomatopoeic Sound Representation
No full textNon-speech sounds play an important role in setting the mood of a video and aiding comprehension. However, current non-speech sound captioning practices focus primarily on sound categories, which fails to provide a rich sound experience for d/Deaf and hard-of-hearing (DHH) viewers. Onomatopoeia, which succinctly captures expressive sound information, offers a potential solution but remains underutilized in non-speech sound captioning. This paper investigates how onomatopoeia benefits DHH audiences in non-speech sound captioning. We collected 7,962 sound-onomatopoeia pairs from listeners and developed a sound-onomatopoeia model that automatically transcribes sounds into onomatopoeic descriptions indistinguishable from human-generated ones. A user evaluation of 25 DHH participants using the model-generated onomatopoeia demonstrated that onomatopoeia significantly improved their video viewing experience. Participants most favored captions with onomatopoeia and category, and expressed a desire to see such captions across genres. We discuss the benefits and challenges of using onomatopoeia in non-speech sound captions, offering insights for future practices. © 2025 Copyright held by the owner/author(s)
Ultrafast optical imaging techniques for exploring rapid neuronal dynamics
No full textOptical neuroimaging has significantly advanced our understanding of brain function, particularly through techniques such as two-photon microscopy, which captures three-dimensional brain structures with sub-cellular resolution. However, traditional methods struggle to record fast, complex neuronal interactions in real time, which are crucial for understanding brain networks and developing treatments for neurological diseases such as Alzheimer's, Parkinson's, and chronic pain. Recent advancements in ultrafast imaging technologies, including kilohertz two-photon microscopy, light field microscopy, and event-based imaging, are pushing the boundaries of temporal resolution in neuroimaging. These techniques enable the capture of rapid neural events with unprecedented speed and detail. This review examines the principles, applications, and limitations of these technologies, highlighting their potential to revolutionize neuroimaging and improve the diagnose and treatment of neurological disorders. Despite challenges such as photodamage risks and spatial resolution trade-offs, integrating these approaches promises to enhance our understanding of brain function and drive future breakthroughs in neuroscience and medicine. Continued interdisciplinary collaboration is essential to fully leverage these innovations for advancements in both basic and clinical neuroscience. © 2025 Elsevier B.V., All rights reserved.TRUEsciescopu
Structurally ordered intermetallic electrocatalysts and anticorrosive carbon materials for durable green hydrogen energy systems: A theory-guided experimental validation
No full textThe 21st-century modern society widely recognizes the critical importance of developing advanced energy technologies. Nations worldwide are increasingly committed to achieving carbon neutrality by investing in environmentally sustainable energy storage and conversion technologies with renewable energy sources. Among renewable energy sources, hydrogen is attracted as a crucial resource in achieving net-zero and sustainable development goals. Accelerating the transition to a hydrogen society involves water electrolysis systems and fuel cells that produce and utilize green hydrogen. This thesis explores two key electrochemical applications: polymer electrolyte membrane fuel cells (PEMFCs) and anion exchange membrane water electrolyzers (AEMWEs). These were selected from a broad range of electrochemical devices due to their distinctive roles in a hydrogen-based energy ecosystem. Ensuring electrochemical stability is critical to achieving reliable cathode for PEMFC and AEMWE systems. To achieve long-term application systems, this work emphasizes two primary research strategies: (1) intermetallic nanostructuring and (2) the development of anticorrosive carbon materials. In this thesis, computational chemistry is systematically applied to address the aforementioned research challenges and develop efficient energy materials for electrochemical applications, utilizing methods such as density functional theory (DFT) and machine learning (ML) potentials. DFT has proven highly effective in predicting the properties and structures of electrochemical catalysts, becoming an essential tool for research and development in this field. However, due to the required computational resources, its application is generally limited to systems containing a few hundred atoms. To overcome these issues, ML-assisted multi-scale simulations are introduced in this thesis. Advances in computing hardware and the rise of artificial intelligence have enabled the development of ML techniques for multi-scale modeling and the generation of accurate force fields across a wide variety of systems. In Chapter 2, ordered intermetallic nanostructures are employed to enhance the intrinsic activity and durability of PEMFC and AEMWE systems. In PEMFC, machine- learning potentials are developed and applied for real-size simulations of intermetallic PtCo nanostructures to investigate their theoretical durability by comparing dissolution potentials. Through systematic experimental approaches, the predicted theoretical results were clearly validated, demonstrating the enhanced electrocatalytic performance of the intermetallic nanostructures. In AEMWE, the theory-guided design of intermetallic PtNi nanostructures provides critical insights into both fundamental dissolution potential and predictions of catalytic activity. Successful experimental validation, from half-cell tests to large-scale AEMWE stack systems, showed a degradation rate of less than 2 % over 3,000 h of operation. In Chapter 3, fluorine-doped graphene nanoribbons (F-GNR)-based anticorrosive carbon materials are proposed as an effective strategy for developing highly durable PEMFCs. Fluorine is particularly beneficial for corrosion resistance due to the strong carbon-fluorine (C-F) covalent bond. According to the DFT results in this thesis, F-GNR and F-GNR@CNT composites show improved resistance to carbon corrosion, exhibiting lower binding energies with corrosion sources such as H2O and oxygen atoms compared to pristine GNR. Experimentally, F-GNR-based carbon materials demonstrate their potential as cathode additives, enhancing structural stability and water management. In Chapter 4, fundamental guidance and validations based on DFT calculations were provided to effectively develop energy materials for various electrochemical conversion and storage systems. These systems include oxygen/hydrogen electrocatalysts, CO2 reduction reactions (CO2RR), Li/Zn batteries, and supercapacitors. The thesis provides in-depth theoretical insights into the design of computational models, detailing the methods used to optimize these materials. It also offers comprehensive computational analysis on key aspects such as catalytic activity, long-term durability, and electronic structure. This theoretical framework is crucial for understanding the mechanisms and for guiding the development of high-performance energy materials in these electrochemical systems.DoctorAbstract 1
Ⅰ. Introduction 26
1.1 Hydrogen society and energy applications 26
1.1.1 Research Background 26
1.1.2 References 28
1.2 Polymer electrolyte membrane fuel cell (PEMFC) 30
1.2.1 Introduction 30
1.2.2 Research Challenges and Strategies 31
1.2.3 References 33
1.3 Anion exchange membrane water electrolyzer (AEMWE) 38
1.3.1 Introduction 38
1.3.2 Research Challenges and Strategies 39
1.3.3 References 41
1.4 Computational Methodologies 44
1.4.1 Rising Needs of Computational Science for Developing Energy Materials . 44
1.4.2 Principle and Appliance of Density Functional Theory 45
1.4.3 The Development and Appliance of Machine-Learning Potential 47
1.4.4 References 48
Ⅱ. Ordering-engineered intermetallic nanostructure 50
2.1 Necessity for employing intermetallic nanostructure. 50
2.1.1 Research Background 50
2.1.2 References 53
2.2 Real-size artificial intelligence multiscale simulations in a highly ordered Pt@PtCo
core-shell for durable PEMFC 54
2.2.1 Introduction 54
2.2.2 Computational Details and Experimental Procedures 57
2.2.3 Results and Discussion 61
2.2.4 Conclusions 71
2.2.5 References 72
2.3 Locking the atomic Ni leaching on ordered PtNi nanostructure for long-term
practical hydrogen production 84
2.3.1 Introduction 84
2.3.2 Computational Details and Experimental Procedures 86
2.3.3 Results and Discussion 92
2.3.4 Conclusions 100
2.3.5 References 101
Ⅲ. Durable anticorrosive carbon materials 120
3.1 Necessity for developing durable anticorrosive carbon materials 120
3.1.1 Research Background 120
3.1.2 Reference 122
3.2 Fluorine-decorated graphene nanoribbons for an anticorrosive PEMFC 126
3.2.1 Introduction 126
3.2.2 Computational Details and Experimental Procedures 128
3.2.3 Results and Discussion 135
3.2.4 Conclusions 145
3.2.5 References 147
3.3 “Straw in the Clay Soil” Strategy: Anticarbon corrosive fluorine‐decorated graphene
nanoribbons@CNT composite for long‐term PEMFC 166
3.3.1 Introduction 166
3.3.2 Computational Details and Experimental Procedures 168
3.3.3 Results and Discussion 175
3.3.4 Conclusions 187
3.3.5 References 188
Ⅳ. Computational Approaches in Electrochemical Energy Conversion and Storage 211
4.1 Theoretical validations for oxygen electrocatalysts 211
4.1.1 Potential-driven coordinated oxygen migration promotes the catalytic
performance of Pd clusters towards H2O2 Production 211
4.1.1.1 Introduction 211
4.1.1.2 Computational Details 214
4.1.1.3 Results and Discussion 215
4.1.1.4 Conclusions 218
4.1.1.5 References 219
4.2 Theoretical validations for hydrogen electrocatalysts 239
4.2.1 Hierarchical Ni-Mo2C/N-doped carbon Mott-Schottky array for water
electrolysis 239
4.2.1.1 Introduction 239
4.2.1.2 Computational Details 242
4.2.1.3 Results and Discussion 244
4.2.1.4 Conclusions 246
4.2.1.5 References 247
4.2.2 Collapsing the bottleneck by the interfacial effect of Ni/CeO2 for long-term
hydrogen production using waste alkaline water in practical-scale AEMWE 259
4.2.2.1 Introduction 259
4.2.2.2 Computational Details 261
4.2.2.3 Results and Discussion 261
4.2.2.4 Conclusions 265
4.2.2.5 References 266
4.3 Theoretical validations for CO2 conversion electrocatalysts 277
4.3.1 Plasma-induced oxygen vacancies in amorphous MnOx boost catalytic
performance for electrochemical CO2 reduction 277
4.3.1.1 Introduction 277
4.3.1.2 Computational Details 279
4.3.1.3 Results and Discussion 280
4.3.1.4 Conclusions 281
4.3.1.5 References 282
4.3.2 Atomic iridium species anchored on porous carbon network support: An
outstanding electrocatalyst for CO2 conversion to CO 286
4.3.2.1 Introduction 286
4.3.2.2 Computational Details 288
4.3.2.3 Results and Discussion 290
4.3.2.4 Conclusions 294
4.3.2.5 References 295
4.4 Theoretical validations for battery and supercapacitor systems 308
4.4.1 Efficient Zn metal anode enabled by O, N-codoped carbon microflowers . 308
4.4.1.1 Introduction 308
4.4.1.2 Computational Details 310
4.4.1.3 Results and Discussion 311
4.4.1.4 Conclusions 313
4.4.1.5 References 314
4.4.2 Hierarchical porous structure construction for highly stable self-supporting
lithium metal anode 321
4.4.2.1 Introduction 321
4.4.2.2 Computational Details 323
4.4.2.3 Results and Discussion 324
4.4.2.4 Conclusions 326
4.4.2.5 References 326
4.4.3 Interaction mechanism between MOF-derived cobalt/rGO composite and
sulfur for long cycle life of lithium-sulfur batteries 334
4.4.3.1 Introduction 334
4.4.3.2 Computational Details 336
4.4.3.3 Results and Discussion 337
4.4.3.4 Conclusions 338
4.4.3.5 References 339
4.4.4 O, N‐Codoped, self‐activated, holey carbon sheets for low‐cost and high‐
loading zinc‐ion supercapacitors 345
4.4.4.1 Introduction 345
4.4.4.2 Computational Details 347
4.4.4.3 Results and Discussion 348
4.4.4.4 Conclusions 350
4.4.4.5 References 351
Ⅴ. Overall conclusion 35
Characterizing few-cycle UV resonant dispersive waves through direct field sampling
No full textWe demonstrate compression of few-cycle ultraviolet (UV) resonant dispersive waves (RDWs) generated in a cascaded hollow capillary fiber setup using a Yb laser system. Temporal characterization is performed using both tunneling ionization with a perturbation for the time-domain observation of an electric field (TIPTOE) and self-diffraction frequency-resolved optical gating (SD-FROG), which show good agreement. Through careful dispersion management, we compress the RDW pulse to 6.9 fs at a ∼390-nm central wavelength. This is the first, to our knowledge, measurement of an RDW using the TIPTOE method and demonstrates the viability of this technique to reliably characterize few-cycle UV pulses with μJ pulse energies. © 2025 Elsevier B.V., All rights reserved.FALSEsciescopu
Observer-based Control for Linear Continuous-Time Systems with Fully Homomorphic Encryption
No full textThis paper is concerned with designing an encrypted observer-based controller for linear continuous-time systems. To be specific, this paper deploys a fully homomorphic encryption (FHE) scheme to directly compute control inputs in an encrypted form without decryption, thus avoiding data eavesdropping. Note that the deployment of FHE in observer-based controllers inevitably faces challenges in handling quantization errors due to the quantization required by the encryption-decryption processes. That motivates us to propose a novel encrypted form for computations of the continuous-time controller, and present rigorous stability analysis based on its virtual dynamics. Consequently, stability criteria are formulated in terms of tractable conditions associated with quantization gains and sampling intervals. Numerical results on DC motor control corresponding to several quantization gains and sampling intervals demonstrate the validity of our method. IEEEFALSEsciescopu
Wafer-scale fabrication of memristive passive crossbar circuits for brain-scale neuromorphic computing
No full textMemristive passive crossbar circuits hold great promise for neuromorphic computing, offering high integration density combined with massively parallel operation. However, scaling up the integration complexity of such circuits remains challenging due to low device yield, stemming from the intrinsic properties of filamentary switching and limitations in current crossbar fabrication technologies. Here, we report a scalable passive crossbar device technology achieved through a co-design approach for memristors and crossbar structures. The proposed hardware platform is fabricated using CMOS-compatible processes without complex and high-temperature steps, enabling high device yield along with reliable and multibit operation. Importantly, the fabrication process is successfully scaled to a 4-inch wafer, maintaining an average device yield (>similar to 95%) and preserving key switching characteristics. The potential of this platform is showcased by implementing image classification of the fashion MNIST benchmark with an ex-situ trained spiking neural network. We believe that our work represents a significant step toward brain-scale neuromorphic computing systems.TRUEsciescopu