Complex saddles of the Veneziano amplitude

Saddle point approximation is a useful method to explore high energy asymptotic behaviors of string scattering amplitudes. We show that, even at tree-level, there are infinitely many complex saddles contributing to string scattering amplitudes, and that the complex saddles reproduce their appropriate poles and zeros. Each complex saddle is interpreted as a semi-classical path of a string in Lorentzian signature. The poles and zeros of the Veneziano amplitude are understood as constructive or destructive interference of such semi-classical paths.Comment: 20 pages, 6 figure

弦の散乱における過渡的カオスの解析

京都大学新制・課程博士博士(理学)甲第24412号理博第4911号新制||理||1702(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 橋本 幸士, 准教授 福間 將文, 教授 杉本 茂樹学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA

String is a double slit

We perform imaging of a fundamental string from string scattering amplitudes, and show that its image is a double slit

Efficient enzyme discovery from complex environmental microbiota using microbial single-cell sequencing

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Harnessing environmental microbiota for the discovery of novel biocatalytic enzymes using microbial single-cell genome sequencing

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Quantum phase transition and Resurgence: Lessons from 3d N=4\mathcal{N}=4 SQED

We study a resurgence structure of a quantum field theory with a phase transition to uncover relations between resurgence and phase transitions. In particular, we focus on three-dimensional $\mathcal{N}=4$ supersymmetric quantum electrodynamics (SQED) with multiple hypermultiplets, where a second-order quantum phase transition has been recently proposed in the large-flavor limit. We provide interpretations of the phase transition from the viewpoints of Lefschetz thimbles and resurgence. For this purpose, we study the Lefschetz thimble structure and properties of the large-flavor expansion for the partition function obtained by the supersymmetric localization. We show that the second-order phase transition is understood as a phenomenon where a Stokes and anti-Stokes phenomenon occurs simultaneously. The order of the phase transition is determined by how saddles collide at the critical point. In addition, the phase transition accompanies an infinite number of Stokes phenomena due to the supersymmetry. These features are appropriately mapped to the Borel plane structures as the resurgence theory expects. Given the lessons from the SQED, we provide a more general discussion on the relationship between the resurgence and phase transitions. In particular, we show how the information on the phase transition is decoded from the Borel resummation technique.Comment: 23+16 pages, 14 figure

Exploring deep learning techniques for wild animal behaviour classification using animal-borne accelerometers

Otsuka R., Yoshimura N., Tanigaki K., et al. Exploring deep learning techniques for wild animal behaviour classification using animal-borne accelerometers. Methods in Ecology and Evolution 15, 716 (2024); https://doi.org/10.1111/2041-210X.14294.Machine learning-based behaviour classification using acceleration data is a powerful tool in bio-logging research. Deep learning architectures such as convolutional neural networks (CNN), long short-term memory (LSTM) and self-attention mechanism as well as related training techniques have been extensively studied in human activity recognition. However, they have rarely been used in wild animal studies. The main challenges of acceleration-based wild animal behaviour classification include data shortages, class imbalance problems, various types of noise in data due to differences in individual behaviour and where the loggers were attached and complexity in data due to complex animal-specific behaviours, which may have limited the application of deep learning techniques in this area. To overcome these challenges, we explored the effectiveness of techniques for efficient model training: data augmentation, manifold mixup and pre-training of deep learning models with unlabelled data, using datasets from two species of wild seabirds and state-of-the-art deep learning model architectures. Data augmentation improved the overall model performance when one of the various techniques (none, scaling, jittering, permutation, time-warping and rotation) was randomly applied to each data during mini-batch training. Manifold mixup also improved model performance, but not as much as random data augmentation. Pre-training with unlabelled data did not improve model performance. The state-of-the-art deep learning models, including a model consisting of four CNN layers, an LSTM layer and a multi-head attention layer, as well as its modified version with shortcut connection, showed better performance among other comparative models. Using only raw acceleration data as inputs, these models outperformed classic machine learning approaches that used 119 handcrafted features. Our experiments showed that deep learning techniques are promising for acceleration-based behaviour classification of wild animals and highlighted some challenges (e.g. effective use of unlabelled data). There is scope for greater exploration of deep learning techniques in wild animal studies (e.g. advanced data augmentation, multimodal sensor data use, transfer learning and self-supervised learning). We hope that this study will stimulate the development of deep learning techniques for wild animal behaviour classification using time-series sensor data

Seronegative Oligoarthritis Preceding Psoriasis by 9.5 Years

We report a case of psoriatic arthritis where oligoarthritis preceded the skin lesions. A 57-year-old man complained of left third-finger pain. Laboratory examinations were negative for anti-cyclic citrullinated peptide antibodies and rheumatoid factor; he was treated for suspected rheumatoid arthritis. Six years later, X-ray revealed enthesitis of his fingers and wrist joint. At 9.5 years after the initial visit, skin lesions appeared in the left auricular region and buttock and dermatopathology findings indicated psoriasis vulgaris. The final diagnosis was psoriatic arthritis. In cases of seronegative oligoarthritis, psoriatic arthritis must be considered because some patients demonstrate osteoarticular lesions preceding skin lesions

Coexistence of muscle atrophy and high subcutaneous adipose tissue radiodensity predicts poor prognosis in hepatocellular carcinoma

IntroductionWe aimed to assess the prognostic implications of muscle atrophy and high subcutaneous adipose tissue (SAT) radiodensity in patients with hepatocellular carcinoma (HCC).MethodsIn this retrospective study, muscle atrophy was assessed using the psoas muscle index (PMI) obtained from computed tomography. SAT radiodensity was evaluated based on radiodensity measurements. Survival and multivariate analyses were performed to identify factors associated with prognosis. The impact of muscle atrophy and high SAT radiodensity on prognosis was determined through survival analysis.ResultsA total of 201 patients (median age: 71 years; 76.6% male) with HCC were included. Liver cirrhosis was observed in 72.6% of patients, and the predominant Child–Pugh grade was A (77.1%). A total of 33.3% of patients exhibited muscle atrophy based on PMI values, whereas 12.9% had high SAT radiodensity. Kaplan–Meier survival analysis demonstrated that patients with muscle atrophy had significantly poorer prognosis than those without muscle atrophy. Patients with high SAT radiodensity had a significantly worse prognosis than those without it. Muscle atrophy, high SAT radiodensity, the Barcelona Clinic Liver Cancer class B, C, or D, and Child–Pugh score ≥ 6 were significantly associated with overall survival. Further classification of patients into four groups based on the presence or absence of muscle atrophy and high SAT radiodensity revealed that patients with both muscle atrophy and high SAT radiodensity had the poorest prognosis.ConclusionMuscle atrophy and high SAT radiodensity are significantly associated with poor prognosis in patients with HCC. Identifying this high-risk subgroup may facilitate the implementation of targeted interventions, including nutritional therapy and exercise, to potentially improve clinical outcomes