Results 161 to 170 of about 413,149 (292)

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

open access: yesAdvanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki   +2 more
wiley   +1 more source

Machine‐Learning Decomposition Identifies a Big Two Structure in Human Personality with Distinct Neurocognitive Profiles

open access: yesAdvanced Science, EarlyView.
Using machine learning on a mega‐scale global dataset (n = 1,336,840) reveals a robust personality trait architecture beyond the Big Five. A Big Two model, broadly capturing social engagement and internal mentation, defines a geometric space that links personality to neurocognitive profiles.
Kaixiang Zhuang   +7 more
wiley   +1 more source

A Biomarker‐Driven Ovary–Endometrium Organ‐on‐a‐Chip Mimicking 3D Multicellular Complexity and Menstrual Cyclicity for Predicting Reproductive Toxicity

open access: yesAdvanced Science, EarlyView.
We present a dual‐organ, biomarker‐integrated ovaryendometrium organ‐on‐a‐chip that recapitulates 3D tissue complexity, menstrual cycle dynamics, and hormonal crosstalk. This platform enables real‐time, cell‐typespecific fluorescent readouts of reproductive toxicity using ANGPTL4 and SERPINB2 as early‐response reporters.
Soo‐Rim Kim   +6 more
wiley   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

open access: yesAdvanced Science, EarlyView.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich   +2 more
wiley   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

open access: yesAdvanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee   +4 more
wiley   +1 more source

Gut Mycobiota‐Associated Tryptophan Catabolites Protect Against Metabolic Dysfunction‐Associated Steatotic Liver Disease

open access: yesAdvanced Science, EarlyView.
ABSTRACT Accumulating evidence suggests that the intestinal microbiota participates in the progression of metabolic dysfunction‐associated steatotic liver disease (MASLD) through microbiota‐host interaction. However, the beneficial role of commensal mycobiota in MASLD progression remains poorly understood.
Shuping Qiao   +11 more
wiley   +1 more source

Analysis of BDS Fractional Cycle Biases and PPP Ambiguity Resolution. [PDF]

open access: yesSensors (Basel), 2019
Jiang W   +5 more
europepmc   +1 more source

Decoding Triphenotypic Neutrophils in Cervical Cancer Evolution and Targeting SPP1+/GBP1+/ELOVL5+ Tumor‐Associated Neutrophils to Sensitize Immunotherapy

open access: yesAdvanced Science, EarlyView.
The functional schematic diagram of tumor associated neutrophils. Abstract Enhancing cervical cancer (CC) immunotherapy requires deciphering the heterogeneous tumor immune microenvironment (TIME), particularly neutrophil phenotypic dynamics. Here, 1) we collected 543 CC cases to find that patients with elevated neutrophil levels have a higher incidence
Xingyu Chang   +7 more
wiley   +1 more source

Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation‐Informed Protein Language Model

open access: yesAdvanced Science, EarlyView.
A TP53‐specific predictor, CaVepP53, is developed by fine‐tuning ESMC on experimentally validated variants, quantifying pathogenicity via Euclidean distances. It outperforms general‐purpose models and extends to five cancer genes, enabling interpretable variant classification for precision medicine.
Huiying Chen   +15 more
wiley   +1 more source

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