Numerical climate model simulations suggest that global warming is enhanced or hampered by the spatial pattern of the warming itself. This phenomenon is known as the “pattern effect” and has in recent years become the most promising explanation for the change over time of climate sensitivity in climate models. Under historical global warming, different patterns of surface-temperature change have ...

Data-driven machine-learning models offer considerable promise for acoustic source localization. However, many existing models rely on training data that correlates time-of-flight (TOF) measurements with source locations, yet they struggle to handle the complexities arising from nonlinear wave propagation in materials with varying properties. Furthermore, these models overlook the noise and ...

Rapid three-dimensional imaging over extended fields of views (FOVs) is crucial to the study of organism-wide systems and biological processes in vivo. Selective-plane illumination microscopy (SPIM) is a powerful method for high spatio-temporal resolution in toto imaging of such biological specimens. However, typical SPIM implementations preclude conventional sample mounting and have anisotropic ...

This article explores the potential of Zeonor, a transparent cyclic olefin polymer, for applications in transparent acoustic/photo-acoustic transducers. Despite its widespread use in optics, microfluidics, medical devices, and electronics, Zeonor’s acoustic properties remain understudied. To extend this, the current work employs scanning acoustic microscopy (SAM) to obtain its mechanical properties. ...

Dynamic positron emission tomography and kinetic modeling play a critical role in tracer development research using small animals. Kinetic modeling from dynamic PET imaging requires accurate knowledge of an input function, ideally determined through arterial blood sampling. Arterial cannulation in mice, however, requires complex, time-consuming and terminal surgery, meaning that longitudinal ...

Millions of ionograms are acquired annually to monitor the ionosphere. The accumulated data contain untapped information from a range of locations, multiple solar cycles, and various geomagnetic conditions. In this study, we propose the application of deep convolutional neural networks to automatically classify and scale high-latitude ionograms. A supervised approach is implemented and the networks ...

Programmable nanoscale carriers, such as liposomes and DNA, are readily being explored for personalized medicine or disease prediction and diagnostics. The characterization of these nanocarriers is limited and challenging due to their complex chemical composition. Here, we demonstrate the utilization of surface-enhanced Raman spectroscopy (SERS), which provides a unique molecular fingerprint of ...

Meteoric ablation in the Earth’s atmosphere produces particles of nanometer size and larger. These particles can become charged and influence the charge balance in the D region (60–90 km) and the incoherent scatter observed with radar from there. Radar studies have shown that, if enough dust particles are charged, they can influence the received radar spectrum below 100 km, provided the electron ...

We investigate the collection of dust particles in the mesosphere with the MESS (MEteoric Smoke Sampler) instrument that is designed to fly on a sounding rocket. We assume that the ice particles that form in the polar mesosphere between 80 and 85 km altitude in summer contain meteoric smoke particles; and these should be collected with MESS. The instrument consists of a collection device with an ...

This study aimed to evaluate assistant nurses' knowledge of and attitudes towards pressure injuries in a clinical setting. It employed a cross-sectional design, using two validated surveys: PUKAT 2.0 and APUP, alongside open-ended questions. A convenience sample of 88 assistant nurses from five wards across two departments at a 600-bed university hospital in Sweden participated. Participants answered ...