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This study presents valuable findings by reanalyzing previously published MEG and ECoG datasets to challenge the predictive nature of pre-onset neural encoding effects. The evidence supporting the ...

Abstract: The architectural design of an 8-bit signed multiplier optimized for delay performance is implemented using Radix-4 Booth encoding and Dadda tree reduction techniques. The integration of ...

This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

BACKGROUND: Genetic variants in components or regulators of the RAS-MAPK signaling pathway are causative for severe and early-onset hypertrophic cardiomyopathy (HCM) in patients with Noonan syndrome ...

Abstract: Fault diagnosis in microservice systems requires high availability, driving research towards multimodal learning that leverages heterogeneous monitoring data, including logs, metrics, and ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Kaelink is a high-performance, autonomous agent framework built on a .NET 8 microkernel architecture. It acts as your personal, always-online AI assistant that lives directly in your favorite ...