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Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR)…
Biological measurements are often contaminated with large amounts of non-stationary noise which require effective noise reduction techniques. We present a new real-time deep learning algorithm which produces adaptively a signal opposing the…
Numerical simulation of numerous mm/cm-sized particles embedded in a gaseous disk has become an important tool in the study of planet formation and in understanding the dust distribution in observed protoplanetary disks. However, the mutual…
The atomisation of suspension containing liquid and dispersed particles is prevalent in many applications. Previous studies of droplet breakup mainly focused on homogeneous fluids, and the heterogeneous effect of particles on the breakup…
The electron density is a key parameter to characterize any plasma. Most of the plasma applications and research in the area of low-temperature plasmas (LTPs) are based on the accurate estimations of plasma density and plasma temperature.…
We present a machine-learning approach toward predicting spectroscopic constants based on atomic properties. After collecting spectroscopic information on diatomics and generating an extensive database, we employ Gaussian process regression…
Drowsiness state of a driver is a topic of extensive discussion due to its significant role in causing traffic accidents. This research presents a novel approach that combines Fuzzy Common Spatial Patterns (CSP) optimised Phase Cohesive…
This paper investigates the performance of the micro-electro-mechanical systems resonant sensor used for particle detection and concentration measurement. These fine and ultra-fine particles such as particulate matter (PM), ferrous…
In this work, a new methodology for comparing high power performance of different piezoelectric materials is presented. When comparing high power performance of piezoelectric materials of varying compositions and vibration modes, there…
Context. The compositional properties of hydrogenated amorphous carbons are known to evolve in response to the local conditions. Aims. To present a model for low-temperature, amorphous hydrocarbon solids, based on the microphysical…
Light-matter interaction dynamics is governed by the strength of local coupling constants, tailored by surrounding electromagnetic structures. Characteristic decay times in dipole-allowed fluorescent transitions are much faster than…
High energy density physics (HEDP) experiments commonly involve a dynamic wave-front propagating inside a low-density foam. This effect affects its density and hence, its transparency. A common problem in foam production is the creation of…
Microscopic dynamics reveal the origin of the bulk rheological response in complex fluids. In model systems particle motion can be tracked, but for industrially relevant samples this is often impossible. Here we adapt differential dynamic…
A two-dimensional strongly-coupled dusty plasma is modeled using Langevin and frictionless molecular dynamical simulations. The static viscosity $\eta$ and the wave-number-dependent viscosity $\eta(k)$ are calculated from the microscopic…
Modern structural biology relies on NMR, X-ray crystallography and cryo-electron microscopy for gaining information on biomolecules at nanometer, sub-nanometer or atomic resolution. All these methods, however, require averaging over a vast…
The results of the investigation of changes of parameters of dynamic bipolar charge-voltage and bipolar and unipolar dynamic current-voltage characteristics and transient currents connected with the pulse change of humidity for the samples…
Micromechanical constitutive parameters are important for many engineering materials, typically in microelectronic applications and material design. Their accurate identification poses a three-fold experimental challenge: (i) deformation of…
Current experiment techniques for vorticity measurement suffer from limited spatial and temporal resolution to resolve the small-scale eddy dynamics in turbulence. In this study, we develop a new method for direct vorticity measurement in…
We present a novel method of robust probabilistic cosmic web particle classification in three dimensions using a supervised machine learning algorithm. Training data was generated using a simplified $\Lambda$CDM toy model with…
We report an experimental study on the manipulation of colloidal particles in a drop sitting on a hydrogel. The manipulation is achieved by diffusiophoresis, which describes a directed motion of particles induced by solute gradients. By…