Language Transfer of Audio Word2Vec: Learning Audio Segment Representations without Target Language Data

Audio Word2Vec offers vector representations of fixed dimensionality for variable-length audio segments using Sequence-to-sequence Autoencoder (SA). These vector representations are shown to describe the sequential phonetic structures of the audio segments to a good degree, with real world applications such as query-by-example Spoken Term Detection (STD). This paper examines the capability of language transfer of Audio Word2Vec. We train SA from one language (source language) and use it to extract the vector representation of the audio segments of another language (target language). We found that SA can still catch phonetic structure from the audio segments of the target language if the source and target languages are similar. In query-by-example STD, we obtain the vector representations from the SA learned from a large amount of source language data, and found them surpass the representations from naive encoder and SA directly learned from a small amount of target language data. The result shows that it is possible to learn Audio Word2Vec model from high-resource languages and use it on low-resource languages. This further expands the usability of Audio Word2Vec.Comment: arXiv admin note: text overlap with arXiv:1603.0098

A Humanities-Based Explanation for the Effects of Emotional Eating and Perceived Stress on Food Choice Motives during the COVID-19 Pandemic

Perceived stress affects emotional eating and food choices. However, the extent to which stress associates with food choice motives is not completely understood. This study assessed whether emotional eating mediates the associations between perceived stress levels and food choice motives (i.e., health, mood, convenience, natural content, price, sensory appeal, familiarities, weight control, and ethical concerns) during the Coronavirus Disease 2019 pandemic. A total of 800 respondents were surveyed in the United States in June 2020. Their perceived stress, emotional eating, and food choice motives were assessed by the Perceived Stress Scale, Dutch Eating Behavior Questionnaire, and Food Choice Questionnaire, respectively. Moderate to high levels of perceived stress were experienced by the majority (73.6%) of respondents. Perceived stress was significantly correlated with emotional eating ( = 0.26) as well as five out of nine food choice motives: mood ( = 0.32), convenience ( = 0.28), natural content ( = -0.14), price ( = 0.27), and familiarity ( = 0.15). Emotional eating was significantly correlated with four out of nine food choice motives: mood ( = 0.27), convenience ( = 0.23), price ( = 0.16), and familiarity ( = 0.16). The mediation analyses showed that emotional eating mediates the associations between perceived stress and five food choices motives: mood, convenience, sensory appeal, price, and familiarity. Findings were interpreted using theories and concepts from the humanities, specifically, folklore studies, ritual studies, and symbolic anthropology

DriveEnv-NeRF: Exploration of A NeRF-Based Autonomous Driving Environment for Real-World Performance Validation

In this study, we introduce the DriveEnv-NeRF framework, which leverages Neural Radiance Fields (NeRF) to enable the validation and faithful forecasting of the efficacy of autonomous driving agents in a targeted real-world scene. Standard simulator-based rendering often fails to accurately reflect real-world performance due to the sim-to-real gap, which represents the disparity between virtual simulations and real-world conditions. To mitigate this gap, we propose a workflow for building a high-fidelity simulation environment of the targeted real-world scene using NeRF. This approach is capable of rendering realistic images from novel viewpoints and constructing 3D meshes for emulating collisions. The validation of these capabilities through the comparison of success rates in both simulated and real environments demonstrates the benefits of using DriveEnv-NeRF as a real-world performance indicator. Furthermore, the DriveEnv-NeRF framework can serve as a training environment for autonomous driving agents under various lighting conditions. This approach enhances the robustness of the agents and reduces performance degradation when deployed to the target real scene, compared to agents fully trained using the standard simulator rendering pipeline.Comment: Project page: https://github.com/muyishen2040/DriveEnvNeR

Brain Gene Regulatory Networks Coordinate Nest Construction in Birds.

Nest building is a vital behavior exhibited during breeding in birds, and is possibly induced by environmental and social cues. Although such behavioral plasticity has been hypothesized to be controlled by adult neuronal plasticity, empirical evidence, especially at the neurogenomic level, remains limited. Here, we aim to uncover the gene regulatory networks that govern avian nest construction and examine whether they are associated with circuit rewiring. We designed an experiment to dissect this complex behavior into components in response to pair bonding and nest material acquisition by manipulating the presence of mates and nest materials in 30 pairs of zebra finches. Whole-transcriptome analysis of 300 samples from five brain regions linked to avian nesting behaviors revealed nesting-associated gene expression enriched with neural rewiring functions, including neurogenesis and neuron projection. The enriched expression was observed in the motor/sensorimotor and social behavior networks of female finches, and in the dopaminergic reward system of males. Female birds exhibited predominant neurotranscriptomic changes to initiate the nesting stage, while males showed major changes after entering this stage, underscoring sex-specific roles in nesting behavior. Notably, major neurotranscriptomic changes occurred during pair bonding, with minor changes during nest material acquisition, emphasizing social interactions in nest construction. We also revealed gene expression associated with reproductive behaviors and tactile sensing for nesting behavior. This study presents novel neurogenomic evidence supporting the hypothesis of adult neural plasticity underlying avian nest-construction behavior. By uncovering the genetic toolkits involved, we offer novel insights into the evolution of animals innate ability to construct nests

Void Structures in Regularly Patterned ZnO Nanorods Grown with the Hydrothermal Method

The void structures and related optical properties after thermal annealing with ambient oxygen in regularly patterned ZnO nanrorod (NR) arrays grown with the hydrothermal method are studied. In increasing the thermal annealing temperature, void distribution starts from the bottom and extends to the top of an NR in the vertical (c-axis) growth region. When the annealing temperature is higher than 400°C, void distribution spreads into the lateral (m-axis) growth region. Photoluminescence measurement shows that the ZnO band-edge emission, in contrast to defect emission in the yellow-red range, is the strongest under the n-ZnO NR process conditions of 0.003 M in Ga-doping concentration and 300°C in thermal annealing temperature with ambient oxygen. Energy dispersive X-ray spectroscopy data indicate that the concentration of hydroxyl groups in the vertical growth region is significantly higher than that in the lateral growth region. During thermal annealing, hydroxyl groups are desorbed from the NR leaving anion vacancies for reacting with cation vacancies to form voids