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Perceptual generalization across visual and tactile spaces
No full textCross-modal generalization enables animals to adapt to changing environments. In a recent paper, Guyoton, Matteucci, et al. demonstrated that a dorsal cortical region enables visuo-tactile generalization by constructing peri-personal space representations. These findings expand current understanding of the neural circuits supporting perceptual generalization across sensory modalities.
APOBEC3A drives deaminase mutagenesis in human gastric epithelium
No full textCancer genomes frequently carry apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC)-associated DNA mutations, suggesting APOBEC enzymes as innate mutagens during cancer initiation and evolution. However, the pure mutagenic impacts of the specific enzymes among this family remain unclear in human normal cell lineages. Here, we investigate the comparative mutagenic activities of APOBEC3A and APOBEC3B, through whole-genome sequencing of human normal gastric organoid lines carrying doxycycline-inducible APOBEC expression cassettes. Our findings demonstrate that transcriptional upregulation of APOBEC3A leads to the acquisition of a massive number of genomic mutations in just a few cell cycles. In contrast, despite clear deaminase activity and DNA damage, APOBEC3B upregulation does not generate a significant increase in mutations in the gastric epithelium. APOBEC3B-associated mutagenesis remains minimal even in the context of TP53 inactivation. Further analysis of the mutational landscape following APOBEC3A upregulation reveals a detailed spectrum of APOBEC3A-associated mutations, including indels, primarily 1 bp deletions, clustered mutations, and evidence of selective pressures acting on cells carrying the mutations. Our observations provide a clear foundation for understanding the mutational impact of APOBEC enzymes in human cells.
Enhanced Test Data Management in Spacecraft Ground Testing: A Practical Approach for Centralized Storage and Automated Processing
No full textIn recent years, spacecraft have been developed to support higher data-rate communication systems and accommodate a wider range of payloads. These advancements have led to the generation of large volumes of data and increased system complexity. In particular, during the ground-testing phase, the need for an effective test data management strategy has become increasingly important to improve test efficiency and reduce costs, as sorting, distributing, and analyzing extensive test data is both time consuming and resource intensive. To address these challenges, this study introduces a practical and implementation-oriented autonomous system for centralized test data handling, which has been successfully applied and verified during actual spacecraft development and ground testing operations. The system enables the rapid transfer of test data to centralized storage without waiting for test completion or requiring human intervention by utilizing an event-triggered architecture. In addition, it automatically provides the transferred test data in multiple formats tailored to each engineering team, facilitating effective data comparison and analysis. It also performs automated test data validation without manual input. The performance of the enhanced test data management was evaluated through big-data analysis of logs generated during automated test data transfer and post-processing in actual spacecraft ground tests.
Photonics-based wireless transmission of 16-QAM signals using feedforward compensation of the frequency and phase noise of free-running lasers
No full textOptical heterodyne-based signal generation offers a promising pathway for sub-THz wireless systems. However, the frequency and phase instability of free-running lasers degrade the quality of wireless signals considerably. We experimentally demonstrate a wireless transmission of 16 quadrature amplitude modulation (16-QAM) signals using feedforward frequency and phase compensation applied to the heterodyned output of two free-running lasers. The frequency and phase fluctuations of optically heterodyned signals are detected by using a 90 degrees hybrid coupler and used to drive an optical IQ modulator for compensation. We successfully transmit 80-Gb/s 16-QAM signals at 132 GHz over a wireless channel, achieving distances of up to 30 m without carrier phase estimation at the receiver. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
Enhanced catalytic activity of metal-doped Cu/ZnO/Al2O3 catalyst incorporated polyethylene glycol for CO2 hydrogenation to methanol
No full textThe increasing concerns over greenhouse gas emissions have driven significant research into sustainable carbon utilization strategies. Among these, the catalytic hydrogenation of CO2 to methanol has emerged as a promising approach, offering both carbon capture and value-added chemical production. In this study, a Cu/ZnO/Al2O3 (CZA) catalyst was synthesized via an enhanced co-precipitation method with adding polyethylene glycol (PEG) surfactant to improve porosity and surface functionality. Additionally, Ga and Ti were introduced as promoters to enhance catalytic performance. Catalytic performance tests demonstrated that the Ti-doped CZA catalyst (TiCZA-3PG) exhibited the highest CO2 conversion (35.6 %) and space-time yield (STY) of methanol (312.6 mmol/ (gcat center dot h)) at 280 degrees C under 50 bar, even outperforming a commercial catalyst. The improved performance is attributed to enhanced Cu-ZnO interaction, increased active sites due to oxygen vacancies, and suppression of the reverse water-gas shift reaction, ensuring higher methanol selectivity. This study highlights the synergistic effects of PEG-assisted synthesis and hetero-metal doping, presenting an effective strategy for optimizing Cu-based catalysts for CO2 hydrogenation to methanol.
Charge-dependent localization of Toll-like receptor 5 at the plasma membrane
No full textProper subcellular localization of Toll-like receptors (TLRs) is essential for initiating appropriate innate immune responses against pathogens while avoiding self-reactivity. Unc-93 homolog B1 (UNC93B1) is known to mediate the intracellular trafficking of nucleotide-sensing TLRs such as TLR9 which undergoes rapid internalization into endolysosomes upon reaching the cell surface. We previously demonstrated that UNC93B1 also facilitates the plasma membrane localization of TLR5, a sensor for bacterial flagellin. Unlike TLR9, TLR5 remained stably at the cell surface under steady-state conditions, suggesting the involvement of distinct sorting mechanisms. Using mutagenesis-based approaches, we found that the cytoplasmic domain of TLR5 is required for its surface retention, whereas the cytoplasmic domain of TLR9 is dispensable for internalization. Notably, TLR5 contains polybasic residues in its C-terminal region, absent in other TLRs. Deletion or alanine substitution of these residues led to constitutive endocytosis of TLR5. Conversely, appending the TLR5 C-terminal region to the C-terminus of TLR9 promoted its surface accumulation. Moreover, when the TLR5 C-terminal sequence was fused to a cytosolic protein along with a myristoylation motif, it mediated membrane association of the cytosolic protein in a charge-dependent manner. We further found that this region can directly interact with phosphatidic acid, an anionic phospholipid enriched in the plasma membrane. These findings reveal an electrostatic mechanism by which TLR5 is selectively retained at the plasma membrane, providing new insight into receptor-specific localization of TLRs. (c) 2025 The Author(s). Published by Elsevier Inc. on behalf of Korean Society for Molecular and Cellular Biology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Stabilized negative capacitance for near-theoretical efficiency and high reliability in charge trap flash memory
No full textNegative capacitance (NC) in ferroelectric heterostructures offers a promising pathway to internal voltage application for energy-efficient electronics. However, its adoption in non-volatile memory has been hindered by instability and limited endurance. Here, we demonstrate a stabilized NC-enhanced charge trap flash (NC-CTF) memory that simultaneously achieves high programming efficiency, long retention, and robust cycling endurance through dual interfacial engineering. An ultrathin Al2O3 interlayer in Hf0.5Zr0.5O2 (HZO) modulates domain configurations and promotes energy redistribution into depolarization energy, reinforcing the NC effect. Simultaneously, a TiO2 layer between the charge trap layer (CTL) and blocking oxide (BO) increases the conduction band offset, suppressing parasitic charge injection and degradation. As a result, the NC-CTF device achieves a near-ideal incremental step pulse programming (ISPP) slope of similar to 0.95, a 13.4 V memory window enabling quad-level cell (QLC) operation, and endurance exceeding 10(4) program/erase cycles. The integration of NC physics with flash memory architecture offers a scalable and CMOS-compatible platform for ultra-low-power memory and neuromorphic computing, contributing to the advancement of energy-efficient and intelligent nano-electronic systems.
Feasibility of 2-D analyses in determining the design member forces in asymmetric 3-D RC frame structures
No full textOn the basis of an examination of the general characteristics in the structural behavior of 3-D RC frame structures, this paper introduces the possibility of adopting a 2-D frame structural analysis in the preliminary design stage at which the initial design sections are determined, even in the case of asymmetric 3-D RC frame structures. Upon consideration of the creep deformation of concrete and the construction sequence, which dominantly affect the structural responses of concrete structures, material nonlinear analyses of RC frame structures are performed with the use of a numerical approach based on the moment-curvature relation of an RC section, because it can deliver computational efficiency in 3-D RC frame structures composed of many beams and columns. Furthermore, a simplified numerical solution procedure that can reflect the change in the moment-curvature relations with the magnitude of the axial force and the biaxial bending moments is introduced and its exactness is verified through correlation studies between experimental data and numerical results. Typical asymmetric 3-D RC frame structures are considered with variation in the arrangement of asymmetric upper floors, and the structural responses are analyzed from the perspective of member forces to examine whether the member forces determined through a 2-D analysis can be used in the preliminary design of asymmetric 3-D RC frame structures. Finally, through a comparison of member forces in RC frame structures, it can be concluded that 2-D RC frame analyses only considering the construction sequence can be utilized in the preliminary design of 3-D RC frame structures with or without symmetry.
SPATS: a practical system for comparative analysis of spatio-temporal graph neural networks
No full textThanks to technological advances in sensors and artificial intelligence, large amounts of data that combine spatial and temporal information are being produced in multiple domains. Spatio-temporal graph neural networks (STGNNs) have been recognized as highly effective models for analyzing spatio-temporal data, and so numerous novel STGNN models have recently been developed. However, no systematic and in-depth study has been carried out on the existing STGNN models with various datasets. Thus, it remains to be undecided whether more recent methods achieve better performance than traditional approaches. In this study, we propose a practical system, called SPAtio-Temporal graph System (SPATS), that performs effectively and efficiently the fair comparison of various STGNN models and datasets. SPATS introduces a unified data format to reduce dependency on data models and exploits GPU clusters to handle a large number of model comparisons automatically. Extensive experiments demonstrate that SPATS can efficiently compare STGNN models with reduced memory footprints and fully exploit GPU clusters. Furthermore, SPATS allows us to easily find the effective combination between the STGNN models and the datasets in various domains that have not been examined before.