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In the field of autonomous vehicles (AVs), accurately discerning commander intent and executing linguistic commands within a visual context presents a significant challenge. This paper introduces a sophisticated encoder-decoder framework, developed to address visual grounding in AVs. Our Context-Aware Visual Grounding (CAVG) model is an advanced system that integrates five core encoders—Text, Emotion, Image, Context, and Cross-Modal—with a multimodal decoder. This integration enables the CAVG model to adeptly capture contextual semantics and to learn human emotional features, augmented by state-of-the-art Large Language Models (LLMs) including GPT-4. The architecture of CAVG is reinforced by the implementation of multi-head cross-modal attention mechanisms and a Region-Specific Dynamic (RSD) layer for attention modulation. This architectural design enables the model to efficiently process and interpret a range of cross-modal inputs, yielding a comprehensive understanding of the correlation between verbal commands and corresponding visual scenes. Empirical evaluations on the Talk2Car dataset, a real-world benchmark, demonstrate that CAVG establishes new standards in prediction accuracy and operational efficiency. Notably, the model exhibits exceptional performance even with limited training data, ranging from 50% to 75% of the full dataset. This feature highlights its effectiveness and potential for deployment in practical AV applications. Moreover, CAVG has shown remarkable robustness and adaptability in challenging scenarios, including long-text command interpretation, low-light conditions, ambiguous command contexts, inclement weather conditions, and densely populated urban environments.

Summary: Preadipocyte determination expanding the pool of preadipocytes is a vital process in adipocyte hyperplasia, but the molecular mechanisms underlying this process are yet to be elucidated. Herein, SRY-related HMG box transcription factor 4 (SOX4) was identified as a critical target in response to BMP4- and TGFβ-regulated preadipocyte determination. SOX4 deficiency is sufficient to promote preadipocyte determination in mesenchymal stem cells (MSCs) and acquisition of preadipocyte properties in nonadipogenic lineages, while its overexpression impairs the adipogenic capacity of preadipocytes and converts them into nonadipogenic lineages. Mechanism studies indicated that SOX4 activates and cooperates with LEF1 to retain the nuclear localization of β-catenin, thus mediating the crosstalk between TGFβ/BMP4 signaling pathway and Wnt signaling pathway to regulate the preadipocyte determination. In vivo studies demonstrated that SOX4 promotes the adipogenic-nonadipogenic conversion and suppresses the adipocyte hyperplasia. Together, our findings highlight the importance of SOX4 in regulating the adipocyte hyperplasia in obesity.