Related papers: SCN as a Local Probe of Protein Structural Dynamic…
Concentrated aqueous solutions of the protein lysozyme undergo a liquid solid transition upon a temperature quench into the unstable spinodal region below a characteristic arrest temperature of Tf=15C. We use video microscopy and…
Selenium is experiencing renewed interest as a elemental semiconductor for a range of optoelectronic and energy applications due to its irresistibly simple composition and favorable wide bandgap. However, its high volatility and low…
As it stands today, the search for extraterrestrial intelligence (SETI) is highly dependent on our ability to detect interesting candidate signals, or technosignatures, in radio telescope observations and distinguish these from human radio…
Stochastic neighbor embedding (SNE) methods $t$-SNE, UMAP are two most popular dimensionality reduction methods for data visualization. Contrastive learning, especially self-supervised contrastive learning (SSCL), has showed great success…
Convolutional Neural Networks (CNNs) are the predominant model used for a variety of medical image analysis tasks. At inference time, these models are computationally intensive, especially with volumetric data. In principle, it is possible…
Isotopic effects in projectile fragmentation at relativistic energies have been studied with the ALADIN forward spectrometer at SIS. Stable and radioactive Sn and La beams with an incident energy of 600 MeV per nucleon have been used in…
The dynamics of peptide-protein binding and unbinding of a variant of the RNase S system has been investigated. To initiate the process, a photoswitchable azobenzene moiety has been covalently linked to the S-peptide, thereby switching its…
Convolutional neural networks (CNNs) have received increasing attention over the last few years. They were initially conceived for image categorization, i.e., the problem of assigning a semantic label to an entire input image. In this paper…
Type-I Superluminous Supernovae (SLSNe) are an exotic class of core-collapse SN (CCSN) that can be up to 100 times brighter and more slowly-evolving than normal CCSNe. SLSNe represent the end-stages of the most massive stripped stars, and…
Stochastic resonance (SR) is a well known phenomenon in dynamical systems. It consists of the amplification and optimization of the response of a system assisted by stochastic noise. Here we carry out the first experimental study of SR in…
Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging…
Pressure provides a powerful parameter to control the protein conformation state, which at sufficiently high values can lead to unfolding. Here, we investigate the effects of increasing pressure up to $0.4$ GPa on hydrated lysozyme…
Long-range dependency modeling has been widely considered in modern deep learning based semantic segmentation methods, especially those designed for large-size remote sensing images, to compensate the intrinsic locality of standard…
We report about investigations of time-dependent structural modifications in single crystal graphene due to laser irradiation even at moderate power levels of 1mW in a diffraction limited spot. The structural modifications have been…
The linear noise approximation models the random fluctuations from the mean-field model of a chemical reaction that unfolds near the thermodynamic limit. Specifically, the fluctuations obey a linear Langevin equation up to order…
The convolutional neural network (CNN) is one of the most commonly used architectures for computer vision tasks. The key building block of a CNN is the convolutional kernel that aggregates information from the pixel neighborhood and shares…
We demonstrate the linear and nonlinear characterization of plasma-enhanced chemical vapor deposited silicon-rich silicon nitride (SRSN) racetrack ring resonator for on-chip application within the telecommunication wavelength range. The SRN…
Herein, we present a detailed analysis of an eigenvalue based sensing technique in the presence of correlated noise in the context of a Cognitive Radio (CR). We use a Standard Condition Number (SCN) based decision statistic based on…
Superluminous supernovae (SLSNe) are a class of intense celestial events that can be standardized for measuring cosmological parameters, bridging the gap between type Ia supernovae and the cosmic microwave background. In this work, we…
This study proposes a novel learning paradigm for spiking neural networks (SNNs) that replaces the perceptron-inspired abstraction with biologically grounded neuron models, jointly optimizing synaptic weights and intrinsic neuronal…