Dataset for the identification of a ultra-low frequency multidirectional energy harvester for wind turbines.

This paper presents a publicly available dataset designed to support the identification (characterization) and performance optimization of an ultra-low-frequency multidirectional vibration energy harvester. The dataset includes detailed measurements from experiments performed to fully characterize its dynamic behaviour. The experimental data encompasses both input (acceleration)-output (energy) relationships, as well as internal system dynamics, measured using a synchronized image processing and signal acquisition system.

The Chilean COVID-19 Genomics Network Biorepository: A Resource for Multi-Omics Studies of COVID-19 and Long COVID in a Latin American Population.

Although a lack of diversity in genetic studies is an acknowledged obstacle for personalized medicine and precision public health, Latin American populations remain particularly understudied despite their heterogeneity and mixed ancestry. This gap extends to COVID-19 despite its variability in susceptibility and clinical course, where ethnic background appears to influence disease severity, with non-Europeans facing higher hospitalization rates. In addition, access to high-quality samples and data is a critical issue for personalized and precision medicine, and it has become clear that the solution lies in biobanks.

Anesthetic management of idiopathic intracranial hypertension during pregnancy. A case report.

Idiopathic intracranial hypertension (IIH) is a condition characterized by elevated intracranial pressure (ICP) of unknown etiology, more prevalent in obese women of childbearing age. The management of IIH during pregnancy represents a multidisciplinary challenge, as medical treatment is contentious due to the foetal teratogenic risk, and the technically challenging placement of a ventriculoperitoneal shunt is hindered by the presence of the pregnant uterus. The goal of anaesthetic management during childbirth is to maintain hemodynamic stability, cerebral perfusion pressure, and cerebral tissue oxygenation, while avoiding abrupt fluctuations in intracranial pressure.

Artificial intelligence for geoscience: Progress, challenges, and perspectives.

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability.