About 16% of the world's population has major depressive disorder. Traditional antidepressants have slow effect rates and low response rates. Many studies shown that doses ketamine can produce rapid effective antidepressant effects. However, its mechanism action needs further exploration. Lipopolysaccharide (LPS) was used to establish a depression model in rats PC12 nerve cells were for vitro experiments. (2,4)-Dimethoxybenzylidene anabaseine dihydrochloride (GTS-21), specific agonist α7...

Non-autoregressive (NAR) generative models are valuable because they can handle diverse conditional generation tasks in a more principled way than their autoregressive (AR) counterparts, which constrained by sequential dependency requirements. Recent advancements NAR models, such as diffusion language have demonstrated superior performance unconditional compared to AR (e.g., GPTs) of similar sizes. However, improvements do not always lead improved performance. We show that key reason for...

Introduction Emotion recognition is crucial in facilitating human-computer emotional interaction. To enhance the credibility and realism of emotion recognition, researchers have turned to physiological signals, particularly EEG as they directly reflect cerebral cortex activity. However, due inter-subject variability non-smoothness generalization performance models across subjects remains a challenge. Methods In this study, we proposed novel approach that combines time-frequency analysis...

Board games are extensively studied in the AI community because of their ability to reflect/represent real-world problems with a high-level abstraction, and irreplaceable role as testbeds state-of-the-art algorithms. Modern board commonly featured partially observable state spaces imperfect information. Despite some recent successes tackling perfect information like chess Go, most still challenging have yet be solved. This paper empirically explores capabilities Reinforcement Learning (RL)...

Individual head-related transfer functions (HRTFs) are necessary for rendering authentic spatial perceptions in audio applications. To obtain individual HRTFs while avoiding tedious and complicated measurement calculation, an improved customization method based on anthropometry matching is proposed. In the method, a set of HRTFs, which best match to pinna shape listener using four pinna-related anatomical parameters, selected as listener's from pre-acquired HRTF baseline database. A series...

Aspect-based sentiment analysis (ABSA) is a fine-grained task of that presents great benefits to real-word applications. Recently, the methods utilizing graph neural networks over dependency trees are popular, but most them merely considered if there exist dependencies between words, ignoring types these dependencies, which carry important information, as with different have effects. In addition, they neglected correlations and part-of-speech (POS) labels, helpful for imformation. To address...

Understanding and profiling player motivation complements extends research on gameflow, profiling, game artificial intelligence, which helps us design entertaining games. However, automated identification of a player's motive profile remains an open challenge. An emerging technology that shows promise as novel technique for identifying cognitive phenomena is electroencephalography (EEG). This paper begins with survey literature applying EEG to measure characteristics relevant types. Then we...

Individual differences in motivation can explain why people act differently the same situation, and which aspects of a game with different motive profiles may find most engaging. However, identifying player's profile from data available during gameplay remains an open research question. Besides range subjective objective techniques for player motivation, electroencephalography (EEG) technology could offer automatic, technique that best describes given player. This article proposes framework...

As an alternative to IP-based network, Named Data Networking (NDN) is designed for data retrieval and have native support mobility via name based message transmission. Although some recent studies proofed the feasibility benefits of adopting named into content retrieval, it still lacks smart package forwarding strategy in VANET. In view fact that most vehicles' movement desired information certain social features are not completely random, this paper presents a improved which forwards...

Understanding the motive profile of users in virtual worlds, computer games or interactive simulation environments promises to complement research on game flow, player experience modelling and data mining. Traditionally work these areas examines statistics from interacting with existing games. This paper takes an alternative approach explores design artificial agents that can aid detection a user player's profile. We demonstrate decision-making scenario requires opponent trade off social...

Since head-related transfer functions (HRTFs) represent the interactions between sounds and physiological structures of listeners, anthropometric parameters a straightforward way to customize (or predict) individualized HRTFs. This paper proposes hybrid algorithm for predicting median-plane HRTFs using parameters. The proposed consists three parts: decomposition HRTFs; selection key parameters; establishing prediction formula. Firstly, an independent component analysis (ICA) is applied from...

Head-related transfer functions (HRTFs), which reflect the interaction between sound waves and human anatomical structures, are core of virtual auditory environments (VAEs). To achieve authentic VAEs, individual HRTFs need to be incorporated in signal synthesis. Accurately measuring HRTF-relevant anthropometric parameters is important anthropometry-based HRTF customization method regarded as a promising approach obtain HRTFs. Traditional measurement methods using rulers photography suffer...

Document classification is a research topic aiming to predict the overall text sentiment polarity with advent of deep neural networks. Various learning algorithms have been employed in current studies improve performance. To this end, paper proposes hierarchical hybrid network multi-head attention (HHNN-MHA) model on task document classification. The proposed contains two layers deal word-sentence level and sentence-document respectively. In first layer, CNN integrated into Bi-GRU mechanism...

We present OmniJARVIS, a novel Vision-Language-Action (VLA) model for open-world instruction-following agents in Minecraft. Compared to prior works that either emit textual goals separate controllers or produce the control command directly, OmniJARVIS seeks different path ensure both strong reasoning and efficient decision-making capabilities via unified tokenization of multimodal interaction data. First, we introduce self-supervised approach learn behavior encoder produces discretized...

Little is known about the relationship between team proactivity and performance. Drawing on cognitive theory, we argue that task conflict may be mediator performance authoritarian leadership moderate mediation relationship. In end, discuss contribution limitations of model suggest some directions for further research.

Probabilistic Circuits (PCs) are a general and unified computational framework for tractable probabilistic models that support efficient computation of various inference tasks (e.g., computing marginal probabilities). Towards enabling such reasoning capabilities in complex real-world tasks, Liu et al. (2022) propose to distill knowledge (through latent variable assignments) from less but more expressive deep generative models. However, it is still unclear what factors make this distillation...