An end-to-end computational framework and interactive web suite for designing, simulating, and optimizing Four-Stage Passive Microfluidic Blood Cell Filters using Deterministic Lateral Displacement (DLD) and Deep Learning Surrogate Models. By replacing hours of computationally expensive Navier-Stokes Computational Fluid Dynamics (CFD) simulations with sub-millisecond neural surrogate inference, this system performs multi-objective design space exploration to yield purified plasma and enriched cellular hematocrit fractions for downstream disease screening pipelines.
Executive Summary For decades, the human-machine interface has remained flat, characterized by sterile alphanumeric outputs and static diagnostic charts. As deep learning models grow in both parameter count and structural complexity, they increasingly resemble "black boxes"—compu…
🌟 Summary Huawei Ascend support arrives in Ultralytics, enabling YOLO models to export and run as hardware-optimized .om models on Ascend NPUs. 🚀 📊 Key Changes Huawei Ascend export and inference 🧠 Adds format=ascend to compile YOLO models through Huawei's CANN ATC compiler. P…
This is Version 29 revised preprint, with three core master equations modified and corrected compared to the earlier draft. We present a complete geometric unification framework built upon six-dimensional Riemann-Cartan geometry, reduced to a closed self-consistent system of 21 t…
This dataset contains manually annotated bounding boxes around the logos of 40 Bangladeshi news outlets as they appear on social media news photocards — square image-based news summaries distributed primarily on Facebook. It was created to support the development and evaluation o…
This preprint presents an empirical software engineering study on resolving main-thread performance bottlenecks in browser-based spatial computing. Abstract Real-time Retrieval-Augmented Generation (RAG) pipelines increasingly stream high-dimensional vector embeddings into browse…