Interpreting Neural Operators: How Nonlinear Waves Propagate in Nonreciprocal Solids.

We present a data-driven pipeline for model building that combines interpretable machine learning, hydrodynamic theories, and microscopic models. The goal is to uncover the underlying processes governing nonlinear dynamics experiments. We exemplify our method with data from microfluidic experiments where crystals of streaming droplets support the propagation of nonlinear waves absent in passive crystals.

Case report & review: Bilateral NIFTP harboring concomitant HRAS and KRAS mutation: Report of an unusual case and literature review.

Diagnosis and treatment of thyroid disease are affected by the wide range of thyroid cancer subtypes and their varying degrees of aggressiveness. To better describe the indolent nature of thyroid neoplasms previously classified as noninvasive follicular variant of papillary thyroid carcinoma (NI-FVPTC), the Endocrine Pathology Society working group has recently coined the term "noninvasive follicular thyroid neoplasm with papillary-like nuclear features" (NIFTP). The purpose of this nomenclature change is to avoid patients the distress of cancer diagnosis and to decrease the overtreatment of thyroid nodules with a RAS-LIKE molecular profile similar to follicular adenoma.

Predicting Male Infertility Using Artificial Neural Networks: A Review of the Literature.

Male infertility is a relevant public health problem, but there is no systematic review of the different machine learning (ML) models and their accuracy so far. The present review aims to comprehensively investigate the use of ML algorithms in predicting male infertility, thus reporting the accuracy of the used models in the prediction of male infertility as a primary outcome. Particular attention will be paid to the use of artificial neural networks (ANNs).

Model-free characterization of topological edge and corner states in mechanical networks.

Topological materials can host edge and corner states that are protected from disorder and material imperfections. In particular, the topological edge states of mechanical structures present unmatched opportunities for achieving robust responses in wave guiding, sensing, computation, and filtering. However, determining whether a mechanical structure is topologically nontrivial and features topologically protected modes has hitherto relied on theoretical models.