Alberto López | Searcharxiv

arXiv2026

Current Unsolved Problems in Planetary Nebulae Research

While there has been significant progress in our understanding of the origin and evolu-tion of planetary nebulae in the last 50 years, there remain several unsolved problems. These include the true 3D morphological structure of the nebulae, origin of multipolar nebulae, the dust and molecular distribution relative to the optical nebulosity, large-scale structures outside of the main nebulae, the relevance of binarity to planetary nebulae evolution, and a precise definition of the planetary nebula phenomenon. The long-standing problem of elemental abundance discrepancy still remains unsolved. In this paper, we summarize current observations related to these problems and present possible future directions to tackle them.

astro-ph.SR↗

arXiv2025

Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data

Prediction of patient survival using high-dimensional multi-omics data requires systematic feature selection methods that ensure predictive performance, sparsity, and reliability for prognostic biomarker discovery. We developed a hybrid ensemble feature selection (hEFS) approach that combines data subsampling with multiple prognostic models, integrating both embedded and wrapper-based strategies for survival prediction. Omics features are ranked using a voting-theory-inspired aggregation mechanism across models and subsamples, while the optimal number of features is selected via a Pareto front, balancing predictive accuracy and model sparsity without any user-defined thresholds. When applied to multi-omics datasets from three pancreatic cancer cohorts, hEFS identifies significantly fewer and more stable biomarkers compared to the conventional, late-fusion CoxLasso models, while maintaining comparable discrimination performance. Implemented within the open-source mlr3fselect R package, hEFS offers a robust, interpretable, and clinically valuable tool for prognostic modelling and biomarker discovery in high-dimensional survival settings.

q-bio.GN↗