Boltzmann Equation for Relativistic Neutral Scalar Field in Non-equilibrium Thermo Field Dynamics

A relativistic neutral scalar field is investigated on the basis of the Schwinger-Dyson equation in the non-equilibrium thermo field dynamics. A time evolution equation for a distribution function is obtained from a diagonalization condition for the Schwinger-Dyson equation. An explicit expression of the time evolution equation is calculated in the $\lambda\phi^4$ interaction model at the 2-loop level. The Boltzmann equation is derived for the relativistic scalar field. We set a simple initial condition and numerically solve the Boltzmann equation and show the time evolution of the distribution function and the relaxation time.Comment: 23 pages, 9 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

Brain-inspired neural network navigation system with hippocampus, prefrontal cortex, and amygdala functions

We propose a brain-inspired neural network model consisting of the hippocampus, prefrontal cortex, and amygdala models for a navigation system that acquires specific knowledge in home environments from few experiences. The proposed model was evaluated in a home environment using a robot simulator. In the experiment, the robot determines a path for navigation based on the knowledge acquired by the brain-inspired model.2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS 2021), November 16-19, 2021, Hualien, Taiwa

セキドウ タイキ レーダー ヲ モチイタ コウド 150 km エンジリョクセン フキソク コウゾウ ノ ドリフト ソクド ニ カンスル ケンキュウ

高度130-170 kmの電離圏において昼間に発生する「高度150 km沿磁力線不規則構造(FAI)エコー」は,赤道域に設置されたVHFレーダーによって1960年代以降,観測されてきた.本研究では,2007年8月から2009年10月までに,インドネシアの赤道大気レーダー(EAR)によって昼間に観測された150 km FAIエコーのドリフト速度の統計解析を行った。このデータと経験モデルから得られたF 領域プラズマ・ドリフト速度及び,ヒカマルカIS レーダーによる観測結果との比較を行った.その結果,150 km FAI エコーの磁力線直交上/ 南向きドリフト速度は,午後において減少することが明らかになった.この傾向は,F 領域プラズマ・ドリフト速度の場合と一致する.一方,150 km FAI エコーの西向きドリフト速度は,昼間において時間とともに減少する傾向があり,ヒカマルカの非干渉散乱レーダーで観測されたF 領域プラズマ・ドリフト速度が示すような正午付近の極大は顕著ではなかった.150 km FAI ドリフト速度の大きさは,F 領域プラズマ・ドリフト速度と比較し,平均で鉛直成分は約3 m/s 小さく,東西成分は25 m/s 小さいことが明らかになった.この違いを,電場生成領域であるE 領域の,磁気緯度による違いで説明するのは難しく,高度150 km 付近で生成される局所的な電場が影響している可能性が考えられる.Between 130 and 170 km altitude in the daytime ionosphere, the so-called 150-km field-aligned irregularities (FAIs) have been observed since the 1960s at equatorial regions with several very high frequency (VHF) radars. We report statistical results of 150-km FAI drift velocities on a plane perpendicular to the geomagnetic field, acquired by analyzing the Doppler velocities of 150-km FAIs observed with the Equatorial Atmosphere Radar (EAR) at Kototabang, Indonesia during the period from Aug. 2007 to Oct. 2009. We found that the southward/upward perpendicular drift velocity of the 150-km FAIs tends to decrease in the afternoon and that this feature is consistent with that of F-region plasma drift velocities over the magnetic equator. The zonal component of the 150-km FAI drift velocity is westward and decreases with time, whereas the F-region plasma drift velocity observed with the incoherent scatter radar at Jicamarca, Peru, which is westward, reaches a maximum at about noon. The southward/upward and zonal drift velocities of the 150-km FAIs are smaller than that of the F-region plasma drift velocity by approximately 3 m/s and 25 m/s, respectively, on average. The large difference between the 150-km FAI and F-region plasma drift velocities may not arise from a difference in the magnetic latitudes at which their electric fields are generated. Electric fields generated at the altitude at which the 150-km FAIs occur may not be negligible

Japanese Lung Cancer Society Guidelines for Stage IV NSCLC With EGFR Mutations

Patients with NSCLC in East Asia, including Japan, frequently contain EGFR mutations. In 2018, we published the latest full clinical practice guidelines on the basis of those provided by the Japanese Lung Cancer Society Guidelines Committee. The purpose of this study was to update those recommendations, especially for the treatment of metastatic or recurrent EGFR-mutated NSCLC. We conducted a literature search of systematic reviews of randomized controlled and nonrandomized trials published between 2018 and 2019 that multiple physicians had reviewed independently. On the basis of those studies and the advice from the Japanese Society of Lung Cancer Expert Panel, we developed updated guidelines according to the Grading of Recommendations, Assessment, Development, and Evaluation system. We also evaluated the benefits of overall and progression-free survival, end points, toxicities, and patients’ reported outcomes. For patients with NSCLC harboring EGFR-activating mutations, the use of EGFR tyrosine kinase inhibitors (EGFR TKIs), especially osimertinib, had the best recommendation as to first-line treatment. We also recommended the combination of EGFR TKI with other agents (platinum-based chemotherapy or antiangiogenic agents); however, it can lead to toxicity. In the presence of EGFR uncommon mutations, except for an exon 20 insertion, we also recommended the EGFR TKI treatment. However, we could not provide recommendations for the treatment of EGFR mutations with immune checkpoint inhibitors, including monotherapy, and its combination with cytotoxic chemotherapy, because of the limited evidence present in the literature. The 2020 Japanese Lung Cancer Society Guidelines can help community-based physicians to determine the most appropriate treatments and adequately provide medical care to their patients

The role of wingbeat frequency and amplitude in flight power

Body-mounted accelerometers provide a new prospect for estimating power use in flying birds, as the signal varies with the two major kinematic determinants of aerodynamic power: wingbeat frequency and amplitude. Yet wingbeat frequency is sometimes used as a proxy for power output in isolation. There is, therefore, a need to understand which kinematic parameter birds vary and whether this is predicted by flight mode (e.g. accelerating, ascending/descending flight), speed or morphology. We investigate this using high-frequency acceleration data from (i) 14 species flying in the wild, (ii) two species flying in controlled conditions in a wind tunnel and (iii) a review of experimental and field studies. While wingbeat frequency and amplitude were positively correlated, R2 values were generally low, supporting the idea that parameters can vary independently. Indeed, birds were more likely to modulate wingbeat amplitude for more energy-demanding flight modes, including climbing and take-off. Nonetheless, the striking variability, even within species and flight types, highlights the complexity of describing the kinematic relationships, which appear sensitive to both the biological and physical context. Notwithstanding this, acceleration metrics that incorporate both kinematic parameters should be more robust proxies for power than wingbeat frequency alone