Cluster categories from Fukaya categories

We show that the derived wrapped Fukaya category $D^\pi\mathcal{W}(X_{Q}^{d+1})$, the derived compact Fukaya category $D^\pi\mathcal{F}(X_{Q}^{d+1})$ and the cocore disks $L_{Q}$ of the plumbing space $X_{Q}^{d+1}$ form a Calabi--Yau triple. As a consequence, the quotient category $D^\pi\mathcal{W}(X_{Q}^{d+1})/D^\pi\mathcal{F}(X_{Q}^{d+1})$ becomes the cluster category associated to $Q$. One of its properties is a Calabi--Yau structure. Also it is known that this quotient category is quasi-equivalent to the Rabinowitz Fukaya category due to the work of Ganatra--Gao--Venkatesh. We compute the morphism space of $L_{Q}$ in $D^\pi\mathcal{W}(X_{Q}^{d+1})/D^\pi\mathcal{F}(X_{Q}^{d+1})$ using the Calabi--Yau structure, which is isomorphic to the Rabinowitz Floer cohomology of $L_{Q}$.Comment: 19 pages, Comments are welcom

Business cycle and herding behavior in stock returns: theory and evidence

This study explains the role of economic uncertainty as a bridge between business cycles and investors’ herding behavior. Starting with a conventional stochastic differential equation representing the evolution of stock returns, we provide a simple theoretical model and empirically demonstrate it. Specifically, the growth rate of gross domestic product and the power law exponent are used as proxies for business cycles and herding behavior, respectively. We find stronger herding behavior during recessions than during booms. We attribute this to economic uncertainty, which leads to strong behavioral bias in the stock market. These findings are consistent with the predictions of the quantum model.</p

HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models

Large Language Models (LLMs) trained on massive corpora demonstrate impressive capabilities in a wide range of tasks. While there are ongoing efforts to adapt these models to languages beyond English, the attention given to their evaluation methodologies remains limited. Current multilingual benchmarks often rely on back translations or re-implementations of English tests, limiting their capacity to capture unique cultural and linguistic nuances. To bridge this gap for the Korean language, we introduce HAE-RAE Bench, a dataset curated to challenge models lacking Korean cultural and contextual depth. The dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension. Contrary to traditional evaluation suites focused on token or sequence classification and specific mathematical or logical reasoning, HAE-RAE Bench emphasizes a model's aptitude for recalling Korean-specific knowledge and cultural contexts. Comparative analysis with prior Korean benchmarks indicates that the HAE-RAE Bench presents a greater challenge to non-native models, by disturbing abilities and knowledge learned from English being transferred.Comment: Revised Erro

Mice lacking the PSD-95-interacting E3 ligase, Dorfin/Rnf19a, display reduced adult neurogenesis, enhanced long-term potentiation, and impaired contextual fear conditioning

Protein ubiquitination has a significant influence on diverse aspects of neuronal development and function. Dorfin, also known as Rnf19a, is a RING finger E3 ubiquitin ligase implicated in amyotrophic lateral sclerosis and Parkinson&apos;s disease, but its in vivo functions have not been explored. We report here that Dorfin is a novel binding partner of the excitatory postsynaptic scaffolding protein PSD-95. Dorfin-mutant (Dorfin-/-) mice show reduced adult neurogenesis and enhanced long-term potentiation in the hippocampal dentate gyrus, but normal long-term potentiation in the CA1 region. Behaviorally, Dorfin-/- mice show impaired contextual fear conditioning, but normal levels of cued fear conditioning, fear extinction, spatial learning and memory, object recognition memory, spatial working memory, and pattern separation. Using a proteomic approach, we also identify a number of proteins whose ubiquitination levels are decreased in the Dorfin-/- brain. These results suggest that Dorfin may regulate adult neurogenesis, synaptic plasticity, and contextual fear memory19101sciescopu

Human Motion Prediction by Combining Spatial and Temporal Information With Independent Global Orientation

In this study, we address the challenge of 3D human motion prediction from motion capture data, which has become critical in various applications such as autonomous vehicles and human-robot interaction. Previous deep learning-based methods have improved prediction accuracy, but require significant network parameters and do not effectively consider independent joint movements. To overcome the limitations, we propose two lightweight network structures for human motion prediction: LG-Net and LGT-Net, which focus on the individual movements of distinct human limbs and their inter-dependencies. The LG-Net comprises local and global networks, while the LGT-Net combines the proposed LG-Net structure with Long and Short Term Memory (LSTM) cells to exploit temporal information. Our networks, designed to be extremely lightweight with only 0.08M and 0.5M parameters, achieve higher prediction performance compared to state-of-the-art methods. In addition, this study is the first to consider the root joint to improve motion prediction performance. The proposed approach demonstrates the potential for efficient and accurate human motion prediction in various applications

COVID-19 and REITs crash: predictability and market conditions

This study examines the applicability of the log-periodic power law (LPPL) model for the real estate investment trust (REIT) market in the early stages of the coronavirus disease 2019 (COVID-19) pandemic. Our results indicate that unlike in the 2008 global financial crisis, the market conditions were unsuitable for applying LPPL for predicting the COVID-19-induced critical time in the REIT market. Before the pandemic, investors’ herding behavior was extremely weak, and market efficiency was improving, indicating a low probability of the formation of endogenous bubbles. Thus, policymakers should use this bubble-based model while carefully considering market conditions, including investors’ herding behavior and market efficiency. For this purpose, the power law exponent and Hurst exponent can be used to gauge market conditions along with comprehensive market information regarding the appropriateness of applying the LPPL model.</p

Let&apos;s Talk@Clubhouse: Exploring Voice-Centered Social Media Platform and its Opportunities, Challenges, and Design Guidelines

© 2022 ACM.Due to the pandemic, social media has become an essential route to satisfy socializing needs. Expanding from dominant services like Facebook and Instagram, a new wave caused a stir-Clubhouse as a voice-centered social media platform. Despite its worldwide popularity after its launch in 2020, general properties of Clubhouse have not been actively discussed. Accordingly, this study explores Clubhouse&apos;s opportunities and challenges as a voice-centered social media through its user experiences. We conducted interviews with regular Clubhouse users (N=26) to gain insight into their motivation, social networking, and conversations. Findings highlight that voice is effective for establishing social relationships via interactivity and intimacy, mutual respect, and convenience from ephemerality. Conversely, users reported patterns of the privacy paradox and the oligopoly of communication. Design guidelines for future voice-centric social media are proposed. Our initial study of Clubhouse will encourage more dialogues on voice-centered social media and its potential as a major platform.N

Are referees unfair to away teams? Evidence from the Premier League

This study examines the contribution of the crowd effect to home advantage in the English Premier League. Using the coronavirus 2019 pandemic as a natural experiment, we test crowd effects based on the changes in the number of audiences. We find that the difference in the number of audiences has an impact on the players’ performance, leading to the home advantage. Different from previous studies, which report a referee bias induced by crowd effect, our findings suggest that the crowd effect has no direct influence on referees. Specifically, more yellow cards against away teams results from more aggressive plays by these teams, a response to performance suppression by the home crowd. Findings suggest that social pressures caused by the crowd effect influence only players, not referees.</p