An ANN model offers the most accurate and reliable prediction of bubble-point pressure for Rmelan crude oils. For practical ...

A peer-reviewed paper about Chinese startup DeepSeek's models explains their training approach but not how they work through ...

Using cutting-edge algorithms and exascale supercomputers, researchers have created the most realistic simulations yet of matter flowing into black holes. Building on decades of research, a group of c ...

That’s because a new framework is improving the probabilistic reasoning of LLMS like ChatGPT and Gemini. School of ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Volvo’s decision to strip lidar hardware from its 2026 lineup marks a sharp turn for a brand that had positioned laser sensors as central to its safety and autonomy story. The move reshapes not only ...

This study presents a valuable tool named TSvelo, a computational framework for RNA velocity inference that models transcriptional regulation and gene-specific splicing. The evidence supporting the ...

Abstract: Temporal-variant linear equations (TVLEs) are widely acknowledged for their pivotal role in various engineering fields, offering a potent means to model dynamic processes and evolving ...

Abstract: The structure of a submersible permanent magnet tubular linear motor (SPPMTLM) can significantly affect its load spectrum. However, the existing models do not account for this effect. This ...

OpenAI Unveils ‘Strawberry’ Model, Optimized for Complex Coding and Math Your email has been sent OpenAI o1, one of a family of models known as Strawberry, is designed for building rather than ...

This study predicts the characteristics of a compressible polytropic air spring model. A second-order nonlinear autonomous air spring model is presented. The proposed model is based on the assumption ...