Npas4: Linking Neuronal Activity to Memory

Immediate-early genes (IEGs) are rapidly activated after sensory and behavioral experience and are believed to be crucial for converting experience into long-term memory. Neuronal PAS domain protein 4 (Npas4), a recently discovered IEG, has several characteristics that make it likely to be a particularly important molecular link between neuronal activity and memory: it is among the most rapidly induced IEGs, is expressed only in neurons, and is selectively induced by neuronal activity. By orchestrating distinct activity-dependent gene programs in different neuronal populations, Npas4 affects synaptic connections in excitatory and inhibitory neurons, neural circuit plasticity, and memory formation. It may also be involved in circuit homeostasis through negative feedback and psychiatric disorders. We summarize these findings and discuss their implications.National Institutes of Health (U.S.) (Grant MH091220-01

The Effect of Negative Learning-related Emotions on Higher Education Faculty\u27s Online Professional Development

This research examined how faculty\u27s negative learning-related emotions were associated with their technology acceptance and learning engagement in online professional development

Clearing residual planetesimals by sweeping secular resonances in transitional disks: a lone-planet scenario for the wide gaps in debris disks around Vega and Fomalhaut

Extended gaps in the debris disks of both Vega and Fomalhaut have been observed. These structures have been attributed to tidal perturbations by multiple super-Jupiter gas giant planets. Within the current observational limits, however, no such massive planets have been detected. Here we propose a less stringent `lone-planet' scenario to account for the observed structure with a single eccentric gas giant and suggest that clearing of these wide gaps is induced by its sweeping secular resonance. During the depletion of the disk gas, the planet's secular resonance propagates inward and clears a wide gap over an extended region of the disk. Although some residual intermediate-size planetesimals may remain in the gap, their surface density is too low to either produce super-Earths or lead to sufficiently frequent disruptive collisions to generate any observable dusty signatures. The main advantage of this lone-planet sweeping-secular-resonance model over the previous multiple gas giant tidal truncation scenario is the relaxed requirement on the number of gas giants. The observationally inferred upper mass limit can also be satisfied provided the hypothetical planet has a significant eccentricity. A significant fraction of solar or more massive stars bear gas giant planets with significant eccentricities. If these planets acquired their present-day kinematic properties prior to the depletion of their natal disks, their sweeping secular resonance would effectively impede the retention of neighboring planets and planetesimals over a wide range of orbital semi-major axes.Comment: 20 pages, 12 figures. Accepted for publication in Ap

Influence of air supply velocity on temperature field in the self heating process of coal

The air supply velocity is an important factor affecting the spontaneous combustion of coal. The appropriate air velocity can not only provide the oxygen required for the oxidation reaction, but maintains the good heat storage environment. Therefore, it is necessary to study the influence of the actual air velocity in the pore space on the self-heating process of coal particles. This paper focuses on studying the real space piled up by spherical particles. CFD simulation software is used to establish the numerical model from pore scale. Good fitness of the simulation results with the existing results verifies the feasibility of the calculation method. Later, the calculation conditions are changed to calculate and analyze the velocity field and the temperature field for self-heating of some particles (the surface of the particles is at a certain temperature) and expound the effect of different air supply velocities on gathering and dissipating the heat

RBA-GCN: Relational Bilevel Aggregation Graph Convolutional Network for Emotion Recognition

Emotion recognition in conversation (ERC) has received increasing attention from researchers due to its wide range of applications. As conversation has a natural graph structure, numerous approaches used to model ERC based on graph convolutional networks (GCNs) have yielded significant results. However, the aggregation approach of traditional GCNs suffers from the node information redundancy problem, leading to node discriminant information loss. Additionally, single-layer GCNs lack the capacity to capture long-range contextual information from the graph. Furthermore, the majority of approaches are based on textual modality or stitching together different modalities, resulting in a weak ability to capture interactions between modalities. To address these problems, we present the relational bilevel aggregation graph convolutional network (RBA-GCN), which consists of three modules: the graph generation module (GGM), similarity-based cluster building module (SCBM) and bilevel aggregation module (BiAM). First, GGM constructs a novel graph to reduce the redundancy of target node information. Then, SCBM calculates the node similarity in the target node and its structural neighborhood, where noisy information with low similarity is filtered out to preserve the discriminant information of the node. Meanwhile, BiAM is a novel aggregation method that can preserve the information of nodes during the aggregation process. This module can construct the interaction between different modalities and capture long-range contextual information based on similarity clusters. On both the IEMOCAP and MELD datasets, the weighted average F1 score of RBA-GCN has a 2.17$\sim$5.21\% improvement over that of the most advanced method