「きれいな一本」を実現する文化が国際的なスポーツパフォーマンスに与える影響 -日本男子エリート柔道の事例-

早大学位記番号:新9153早稲田大

Inductive Graph Neural Networks for Spatiotemporal Kriging

Time series forecasting and spatiotemporal kriging are the two most important tasks in spatiotemporal data analysis. Recent research on graph neural networks has made substantial progress in time series forecasting, while little attention has been paid to the kriging problem -- recovering signals for unsampled locations/sensors. Most existing scalable kriging methods (e.g., matrix/tensor completion) are transductive, and thus full retraining is required when we have a new sensor to interpolate. In this paper, we develop an Inductive Graph Neural Network Kriging (IGNNK) model to recover data for unsampled sensors on a network/graph structure. To generalize the effect of distance and reachability, we generate random subgraphs as samples and reconstruct the corresponding adjacency matrix for each sample. By reconstructing all signals on each sample subgraph, IGNNK can effectively learn the spatial message passing mechanism. Empirical results on several real-world spatiotemporal datasets demonstrate the effectiveness of our model. In addition, we also find that the learned model can be successfully transferred to the same type of kriging tasks on an unseen dataset. Our results show that: 1) GNN is an efficient and effective tool for spatial kriging; 2) inductive GNNs can be trained using dynamic adjacency matrices; 3) a trained model can be transferred to new graph structures and 4) IGNNK can be used to generate virtual sensors.Comment: AAAI 202

Research and Analysis of the Booming Market of Korea’s IP Image LOOPY

International IP industry practice is an essential component of international communication and cross-cultural exchange. (Rong & Ji, 2020) Recently, the Korean IP LOOPY has exploded and there are many valuable experiences worth learning from. This article delves into the reasons for the success of the renowned IP LOOPY and proposes a method for inspiring the creation of successful IP. This study collected young people's opinions on the popularity of LOOPY in the form of a questionnaire, and collected a total of 108 valid feedback survey data. Through a detailed analysis of the data, it is found that the reasons for LOOPY’s success include unique character designs, emotional resonance that is highly attuned to audience needs, and excellent IP management strategies.Based on this, this paper proposes a method for creating new IP. Firstly, creativity should be at the core to create a unique story background and attractive characters and world view. Secondly, attention should be paid to the needs of the audience, creating emotional resonance points, and enhancing fan stickiness. Then, continuous content creation of the IP. Finally, diversified marketing methods should be used to expand the influence of the IP. The conclusions drawn from this research have certain reference significance for the development of China's IP industry and aim to provide useful guidance for practitioners

Сan citizen Internet banking in China become a champion in the digital transformation era?

This study aims to make theoretical and practical contributions by addressing stagnation in the context of digital transformation (DX) and proposing specific measures. Focusing on the banking industry’s skilled response to rapid changes to maintain and improve competitiveness, this study employs quantitative methods to investigate the expectations and assessments of Chinese financial service users regarding Internet banking. With a clear objective, this study seeks to contribute theoretically and practically by addressing stagnation in DX. Specifically, it focuses on the banking industry’s response to rapid changes, employing quantitative methods to assess and understand Chinese financial service users’ expectations of Internet banking. The results reveal that the prevalent use of payment services through mobile applications has significantly expanded the scope of financial services among citizens. Key factors driving innovation in the financial industry through fintech include close communication with consumers, service enhancement and sophistication and ensuring reliability. Privacy and the ethical use of personal information have been found to function as an indirect pathway that plays a vital role in socio-economic activities, acting as a critical element for the future development of the financial industry. These findings provide actionable insights for fostering innovation and development in the financial sector. The uniqueness of this study lies in its primary quantitative data analysis, which compares the prospects of financial services in China’s advanced DX market. It shows the path the banking industry should take, emphasising the simplicity of mobile applications and the high frequency with which vital components are used. Going beyond theoretical insights, this research is a practical guide for implementing specific actions in a real business environment. It provides valuable insights into the Chinese market and offers guidelines for the broader financial industry currently navigating the intense waves of DX, ultimately aiming for sustainable and effective DX

Individual popularity and activity in online social systems

We propose a stochastic model of web user behaviors in online social systems, and study the influence of attraction kernel on statistical property of user or item occurrence. Combining the different growth patterns of new entities and attraction patterns of old ones, different heavy-tailed distributions for popularity and activity which have been observed in real life, can be obtained. From a broader perspective, we explore the underlying principle governing the statistical feature of individual popularity and activity in online social systems and point out the potential simple mechanism underlying the complex dynamics of the systems.Comment: 7 pages, 7 figures, 1 table, accepted for publication in Physica

Analysis of the regimes of feedback effects in quantum dot laser

We investigated the optical feedback effects on the static and dynamic characteristics of 1.3 μm quantum-dot (QD) Fabry-Pérot (FP) laser under reflection from -40 dB up to -8 dB. The onset of coherence collapse is determined as -14 dB from the optical and electrical spectra. Although the degradation in small signal modulation is reported above this critical feedback level, transmission operation with available eye diagram under higher feedback is demonstrated. Under 10 Gb/s modulation, there is no obvious degradation in eye diagram regarding the eye shape and extinction ratio up to feedback ratio of -8 dB. The higher feedback tolerance of QD laser under large signal modulation is attributed to the impact of gain compression. This high-speed feedback-resistant operation also indicates that QD laser is a promising light source for isolator-free photonic integrated circuits

Proteoform-resolved profiling of plasminogen activation reveals novel abundant phosphorylation site and primary N-terminal cleavage site

Plasminogen (Plg), the zymogen of plasmin (Plm), is a glycoprotein involved in fibrinolysis and a wide variety of other physiological processes. Plg dysregulation has been implicated in a range of diseases. Classically, human Plg is categorized into two types, supposedly having different functional features, based on the presence (type I) or absence (type II) of a single N-linked glycan. Using high-resolution native mass spectrometry, we uncovered that the proteoform profiles of human Plg (and Plm) are substantially more extensive than this simple binary classification. In samples derived from human plasma, we identified up to 14 distinct proteoforms of Plg, including a novel highly stoichiometric phosphorylation site at Ser339. To elucidate the potential functional effects of these post-translational modifications, we performed proteoform-resolved kinetic analyses of the Plg-to-Plm conversion using several canonical activators. This conversion is thought to involve at least two independent cleavage events: one to remove the N-terminal peptide and another to release the active catalytic site. Our analyses reveal that these processes are not independent but are instead tightly regulated and occur in a step-wise manner. Notably, N-terminal cleavage at the canonical site (Lys77) does not occur directly from intact Plg. Instead, an activation intermediate corresponding to cleavage at Arg68 is initially produced, which only then is further processed to the canonical Lys77 product. Based on our results, we propose a refined categorization for human Plg proteoforms. In addition, we reveal that the proteoform profile of human Plg is more extensive than that of rat Plg, which lacks, for instance, the here-described phosphorylation at Ser339

Multi-wavelength 128 Gbit s−1 λ−1 PAM4 optical transmission enabled by a 100 GHz quantum dot mode-locked optical frequency comb

Semiconductor mode-locked lasers (MLLs) with extremely high repetition rates are promising optical frequency comb (OFC) sources for their usage as compact, high-efficiency, and low-cost light sources in high-speed dense wavelength-division multiplexing transmissions. The fully exploited conventional C- and L- bands require the research on O-band to fulfil the transmission capacity of the current photonic networks. In this work, we present a passive two-section InAs/InGaAs quantum-dot (QD) MLL-based OFC with a fundamental repetition rate of ∼100 GHz operating at O-band wavelength range. The specially designed device favours the generation of nearly Fourier-transform-limited pulses in the entire test range by only pumping the gain section while with the absorber unbiased. The typical integrated relative intensity noise of the whole spectrum and a single tone are −152 and −137 dB Hz−1 in the range of 100 MHz–10 GHz, respectively. Back-to-back data transmissions for seven selected tones have been realised by employing a 64 Gbaud four-level pulse amplitude modulation format. The demonstrated performance shows the feasibility of the InAs QD MLLs as a simple structure, easy operation, and low power consumption OFC sources for high-speed fibre-optic communications

A Deep Learning-Based Multi-Signal Radio Spectrum Monitoring Method for UAV Communication

Unmanned aerial vehicles (UAVs), relying on wireless communication, are inevitably influenced by the complex electromagnetic environment, attributed to the development of wireless communication technology. The modulation information of signals can assist in identifying device information and interference in the environment, which is significant for UAV communication environment monitoring. Therefore, in scenarios involving the communication of UAVs, it is necessary to find out how to perform the spectrum monitoring method to obtain the modulation information. Most existing methods are unsuitable for scenarios where multiple signals appear in the same spectrum sequence or do not use an end-to-end structure. Firstly, we established a spectrum dataset to simulate the UAV communication environment and developed a label method. Then, detection networks were employed to extract the presence and location information of signals in the spectrum. Finally, decision-level fusion was used to combine the output results of multiple nodes. Five modulation types, including ASK, FSK, 16QAM, DSB-SC, and SSB, were used to simulate different signal sources in the communication environment. Accuracy, recall, and F1 score were used as evaluation metrics. The networks were tested at different signal-to-noise ratios (SNRs). Among the different modulation types, FSK exhibits the most stable recognition performance across different models. The proposed method is of great significance for wireless radio spectrum monitoring in complex electromagnetic environments and is adaptable to scenarios where multiple receivers are used in vast terrains, providing a deep learning-based approach to radio monitoring solutions for UAV communication