FeSe1-xSxのネマティック量子臨界点近傍における非フェルミ液体輸送特性

京都大学新制・課程博士博士(理学)甲第23452号理博第4746号新制||理||1680(附属図書館)京都大学大学院理学研究科物理学・宇宙物理学専攻(主査)教授 松田 祐司, 教授 石田 憲二, 教授 柳瀬 陽一学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA

RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation Network

Cross-domain few-shot segmentation (CD-FSS) aims to achieve semantic segmentation in previously unseen domains with a limited number of annotated samples. Although existing CD-FSS models focus on cross-domain feature transformation, relying exclusively on inter-domain knowledge transfer may lead to the loss of critical intra-domain information. To this end, we propose a novel residual transformation network (RestNet) that facilitates knowledge transfer while retaining the intra-domain support-query feature information. Specifically, we propose a Semantic Enhanced Anchor Transform (SEAT) module that maps features to a stable domain-agnostic space using advanced semantics. Additionally, an Intra-domain Residual Enhancement (IRE) module is designed to maintain the intra-domain representation of the original discriminant space in the new space. We also propose a mask prediction strategy based on prototype fusion to help the model gradually learn how to segment. Our RestNet can transfer cross-domain knowledge from both inter-domain and intra-domain without requiring additional fine-tuning. Extensive experiments on ISIC, Chest X-ray, and FSS-1000 show that our RestNet achieves state-of-the-art performance. Our code will be available soon.Comment: BMVC 202

Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning

In semi-supervised domain adaptation (SSDA), a few labeled target samples of each class help the model to transfer knowledge representation from the fully labeled source domain to the target domain. Many existing methods ignore the benefits of making full use of the labeled target samples from multi-level. To make better use of this additional data, we propose a novel Prototype-based Multi-level Learning (ProML) framework to better tap the potential of labeled target samples. To achieve intra-domain adaptation, we first introduce a pseudo-label aggregation based on the intra-domain optimal transport to help the model align the feature distribution of unlabeled target samples and the prototype. At the inter-domain level, we propose a cross-domain alignment loss to help the model use the target prototype for cross-domain knowledge transfer. We further propose a dual consistency based on prototype similarity and linear classifier to promote discriminative learning of compact target feature representation at the batch level. Extensive experiments on three datasets, including DomainNet, VisDA2017, and Office-Home demonstrate that our proposed method achieves state-of-the-art performance in SSDA.Comment: IJCAI 202

Two Stream Scene Understanding on Graph Embedding

The paper presents a novel two-stream network architecture for enhancing scene understanding in computer vision. This architecture utilizes a graph feature stream and an image feature stream, aiming to merge the strengths of both modalities for improved performance in image classification and scene graph generation tasks. The graph feature stream network comprises a segmentation structure, scene graph generation, and a graph representation module. The segmentation structure employs the UPSNet architecture with a backbone that can be a residual network, Vit, or Swin Transformer. The scene graph generation component focuses on extracting object labels and neighborhood relationships from the semantic map to create a scene graph. Graph Convolutional Networks (GCN), GraphSAGE, and Graph Attention Networks (GAT) are employed for graph representation, with an emphasis on capturing node features and their interconnections. The image feature stream network, on the other hand, focuses on image classification through the use of Vision Transformer and Swin Transformer models. The two streams are fused using various data fusion methods. This fusion is designed to leverage the complementary strengths of graph-based and image-based features.Experiments conducted on the ADE20K dataset demonstrate the effectiveness of the proposed two-stream network in improving image classification accuracy compared to conventional methods. This research provides a significant contribution to the field of computer vision, particularly in the areas of scene understanding and image classification, by effectively combining graph-based and image-based approaches

Identification and characterization of a circadian clock-associated pseudo-response regulator 7 gene from trifoliate orange

Circadian clock is usually involved in many physiological processes of plants, including responses to abiotic stress, whilst pseudo-response regulator 7 (PRR7) gene is the main component of the circadian clock. In this study, the cDNA of the PRR7 gene was obtained from trifoliate orange (Poncirus trifoliata). Based on the sequence analysis, the PtPRR7 gene had an open reading frame of 2343 bp, encoded 780 amino acids, and contained proteins of the REC and CCT domains. Subcellular localization indicated that PtPRR7 was mainly localized in the nucleus and a small amount of cytoplasm. qRT-PCR analysis revealed the highest expression level of PtPRR7 in roots than in both shoots and leaves. The PtPRR7 gene during 24 hours of soil water deficit exhibited a circadian rhythmic expression pattern: the expression peak at 9:00 am in leaves and at 21:00 pm in roots. Drought treatment affected PtPRR7 gene expression. Such data provide important references for understanding the characteristics of PtPRR7 gene in citrus plants

Eight-input optical programmable logic array enabled by parallel spectrum modulation

Despite over 40 years' development of optical logic computing, the studies have been still struggling to support more than four operands, since the high parallelism of light has not been fully leveraged blocked by the optical nonlinearity and redundant input modulation in existing methods. Here, we propose a scalable multi-input optical programmable logic array (PLA) with minimal logical input, enabled by parallel spectrum modulation. By making full use of the wavelength resource, an eight-input PLA is experimentally demonstrated, and there are 2^256 possible combinations of generated logic gates. Various complex logic fuctions, such as 8-256 decoder, 4-bit comparator, adder and multiplier are experimentally demonstrated via leveraging the PLA. The scale of PLA can be further extended by fully using the dimensions of wavelength and space. As an example, a nine-input PLA is implemented to realize the two-dimensional optical cellular automaton for the first time and perform Conway's Game of Life to simulate the evolutionary process of cells. Our work significantly alleviates the challenge of extensibility of optical logic devices, opening up new avenues for future large-scale, high-speed and energy-efficient optical digital computing

The role of miRNAs in Behçet’s disease

The symptoms of Behçet’s disease (BD), a multisystemic condition with autoimmune and inflammation as hallmarks, include arthritis, recurring oral and vaginal ulcers, skin rashes and lesions, and involvement of the nervous, gastrointestinal, and vascular systems. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), may be important regulators of inflammation and autoimmune disease. These ncRNAs are essential to the physiological and pathophysiological disease course, and miRNA in particular has received significant attention for its role and function in BD and its potential use as a diagnostic biomarker in recent years. Although promising as therapeutic targets, miRNAs must be studied further to fully comprehend how miRNAs in BD act biologically

Current and Future Distribution of Camellia sinensis in China Estimated by MaxEnt

Tea (Camellia sinensis L.) is an important cash crop. In the context of climate change, analyzing the current distribution of tea trees and climate change environmental variables to predict the potential distribution area of tea trees in the future can help decision-makers make appropriate planting decisions and promote sustainable management. In this study, an optimized MaxEnt model was used to predict the limiting factors of tea tree growth and distribution under current and future climate change scenarios. The climate soil mixing model [area under the curve (AUC) = 0.934] performed excellently. The results showed that precipitation, temperature, slope, and soil factors all affected the distribution of suitable habitats for tea trees. Compared with the current distribution area of tea trees, under three shared socioeconomic pathways (SSP126, SSP245, and SSP585), the area of highly suitable habitats for tea trees will expand, especially in 2061–2080 and 2081–2100 years, and the suitable area will extend overall to the north of China, indicating that future climate change may create more new suitable habitats for tea production, especially in Shandong, Shaanxi, Guizhou, and Yunnan provinces. This study will provide important scientific insights for tea production decision-making, tea garden location selection, and future adaptation methods, and will help in the cultivation and transplantation of tea trees in the future

Betaine Inhibits Interleukin-1β Production and Release: Potential Mechanisms

Betaine is a critical nutrient for mammal health, and has been found to alleviate inflammation by lowering interleukin (IL)-1β secretion; however, the underlying mechanisms by which betaine inhibits IL-1β secretion remain to be uncovered. In this review, we summarize the current understanding about the mechanisms of betaine in IL-1β production and release. For IL-1β production, betaine affects canonical and non-canonical inflammasome-mediated processing of IL-1β through signaling pathways, such as NF-κB, NLRP3 and caspase-8/11. For IL-1β release, betaine inhibits IL-1β release through blocking the exocytosis of IL-1β-containing secretory lysosomes, reducing the shedding of IL-1β-containing plasma membrane microvesicles, suppressing the exocytosis of IL-1β-containing exosomes, and attenuating the passive efflux of IL-1β across hyperpermeable plasma membrane during pyroptotic cell death, which are associated with ERK1/2/PLA2 and caspase-8/A-SMase signaling pathways. Collectively, this review highlights the anti-inflammatory property of betaine by inhibiting the production and release of IL-1β, and indicates the potential application of betaine supplementation as an adjuvant therapy in various inflammatory diseases associating with IL-1β secretion

Phosphorous fertilization alleviates drought effects on Alnus cremastogyne by regulating its antioxidant and osmotic potential

Alnus cremastogyne, a broad-leaved tree endemic to south-western China, has both commercial and restoration importance. However, little is known of its morphological, physiological and biochemical responses to drought and phosphorous (P) application. A randomized experimental design was used to investigate how drought affected A. cremastogyne seedlings, and the role that P applications play in these responses. Drought had significant negative effects on A. cremastogyne growth and metabolism, as revealed by reduced biomass (leaf, shoot and root), leaf area, stem diameter, plant height, photosynthetic rate, leaf relative water content, and photosynthetic pigments, and a weakened antioxidative defence mechanism and high lipid peroxidation level. However, the reduced leaf area and enhanced osmolyte (proline and soluble sugars) accumulation suggests drought avoidance and tolerance strategies in this tree. Applying P significantly improved the leaf relative water content and photosynthetic rate of drought-stressed seedlings, which may reflect increased anti-oxidative enzyme (superoxide dismutase, catalase and peroxidase) activities, osmolyte accumulation, soluble proteins, and decreased lipid peroxidation levels. However, P had only a slight or negligible effect on the well-watered plants. A. cremastogyne is sensitive to drought stress, but P facilitates and improves its metabolism primarily via biochemical and physiological rather than morphological adjustments, regardless of water availability.Instituto de Fisiología Vegeta