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Kinetics of separation between the low and high density phases in a single component Lennard-Jones model has been studied via molecular dynamics simulations, at a very low temperature, in the space dimension $d=2$. For densities close to…
One of the critical steps in improving accurate single neuron reconstruction from three-dimensional (3D) optical microscope images is the neuronal structure segmentation. However, they are always hard to segment due to the lack in quality.…
Single-walled carbon nanotubes are hollow cylinders, that can grow centimeters long by carbon incorporation at the interface with a catalyst. They display semi-conducting or metallic characteristics, depending on their helicity, that is…
Vapor-liquid-solid (VLS) route and its variants are routinely used for scalable synthesis of semiconducting nanowires yet the fundamental growth processes remain unknown. Here, we employ atomic-scale computations based on model potentials…
Preterm neonates are highly likely to suffer from ventriculomegaly, a dilation of the Cerebral Ventricular System (CVS). This condition can develop into life-threatening hydrocephalus and is correlated with future neuro-developmental…
Measurement of peculiar velocities by combining redshifts and distance indicators is a powerful way to measure the growth rate of cosmic structure and test theories of gravity at low redshift. Here we constrain the growth rate of structure…
Spiking neural network (SNN) is interesting both theoretically and practically because of its strong bio-inspiration nature and potentially outstanding energy efficiency. Unfortunately, its development has fallen far behind the conventional…
Though type-Ia supernovae (SNe Ia) are found in all types of galaxies, recent local Hubble constant measurements have disfavored using SNe Ia in early-type or quiescent galaxies, aiming instead for better consistency with SNe Ia in…
Three dimensional convolutional neural networks (3DCNNs) have been applied in many tasks, e.g., video and 3D point cloud recognition. However, due to the higher dimension of convolutional kernels, the space complexity of 3DCNNs is generally…
One of the most exciting advancements in AI over the last decade is the wide adoption of ANNs, such as DNN and CNN, in many real-world applications. However, the underlying massive amounts of computation and storage requirement greatly…
Building discriminative representations for 3D data has been an important task in computer graphics and computer vision research. Convolutional Neural Networks (CNNs) have shown to operate on 2D images with great success for a variety of…
Convolutional Neural Networks (CNNs) have recently been shown to excel at performing visual place recognition under changing appearance and viewpoint. Previously, place recognition has been improved by intelligently selecting relevant…
Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application potential. However, it still remains underexplored whether…
We explore the effects of sample dimensionality on vortex pinning in a type-II, low-$T_C$, s-wave superconductor, NbN, in the presence of a perpendicular magnetic field, $H$. We find significant differences in the phase diagrams in the…
Convolutional Neural Networks (CNN) are more suitable, indeed. However, fixed kernel sizes make traditional CNN too specific, neither flexible nor conducive to feature learning, thus impacting on the classification accuracy. The convolution…
We have studied the low speed fracture regime for different glassy materials with variable but controlled length scales of heterogeneity in a carefully mastered surrounding atmosphere. By using optical and atomic force microscopy (AFM)…
With the rapid development of deep learning, Deep Spiking Neural Networks (DSNNs) have emerged as promising due to their unique spike event processing and asynchronous computation. When deployed on neuromorphic chips, DSNNs offer…
Accurate capacitance extraction is becoming more important for designing integrated circuits under advanced process technology. The pattern matching based full-chip extraction methodology delivers fast computational speed, but suffers from…
Scattering-type scanning near-field microscopy (s-SNOM) at terahertz (THz) frequencies could become a highly valuable tool for studying a variety of phenomena of both fundamental and applied interest, including mobile carrier excitations or…
We analyze the 3D kinematics of a sample of $\sim 4400$ red clump stars ranging between 5 and 10 kpc from the Galactic center and up to 3 kpc from the Galactic plane. This sample is representative for the metal-rich ([Fe/H] = -0.6 to 0.5)…