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A 0.0308mm2 4.15pJ/conv VCO-Based Current Sensing Front-End with 2nd-Order ??2-???? Modulation
No full textProstate cancer derived EV detection and quantification with droplet compartmentalization and dark field microscopy using plasmonic resonance
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Zero-Shot Learning for??Reflection Removal of??Single 360-Degree Image
No full textThe existing methods for reflection removal mainly focus on removing blurry and weak reflection artifacts and thus often fail to work with severe and strong reflection artifacts. However, in many cases, real reflection artifacts are sharp and intensive enough such that even humans cannot completely distinguish between the transmitted and reflected scenes. In this paper, we attempt to remove such challenging reflection artifacts using 360-Degree images. We adopt the zero-shot learning scheme to avoid the burden of collecting paired data for supervised learning and the domain gap between different datasets. We first search for the reference image of the reflected scene in a 360-degree image based on the reflection geometry, which is then used to guide the network to restore the faithful colors of the reflection image. We collect 30 test 360-Degree images exhibiting challenging reflection artifacts and demonstrate that the proposed method outperforms the existing state-of-the-art methods on 360-Degree images
Dose evaluation of residents around landfill facilities using recycled concrete solidifying agent
No full textUnsupervised machine-learning algorithm for Orbit classification of electron trajectory under magnetic island
No full textThe tearing mode in fusion reactor is one of the instabilities which tears and reconnects magnetic field lines forming a topological object, so-called ???Magnetic Island??? on the current sheet where the magnetic field lines of opposing directions are close to each other[1]. In the magnetic island structure, particles, such as electrons, are expected to exhibit different trajectories with those in the absence of the magnetic island structure. In this work, the differences between particles??? trajectories in the presence / absence of magnetic island were simulated in Tokamak geometry by a passive particle code, named Particle Around Magnetic Island(PAMI), which has been developed on C++ and parallelized with Message Passing Interface(MPI). The simulation results calculated by PAMI were classified using unsupervised machine-learning(ML) algorithms, such as Self-Organizing Map(SOM)[2], Hierarchical Cluster Analysis(HCA)[3], and K-mean clustering.
In order to scan various particle trajectories near magnetic island structures, the code PAMI has been executed with inputs sampled based on initial speed, pitch-angle, and initial position of particles. The simulation results, which are stored in 3D positions on cylindrical coordinates of each time step, were transformed into parameters by Fourier Transforms, Chebyshev Polynomial, and Least Square Polynomials, in order to be dealt with by the ML algorithms for clustering
Intra-Lysosomal Assembly of Peptides for Highly Selective Cancer Cell Death and Overcoming of Drug Resistance
No full textLysosomes remain powerful organelles and important targets for cancer therapy, because cancer cell proliferation is greatly dependent on effective lysosomal function. Recent studies have shown that lysosomal membrane permeabilization induces cell death and is an effective way to treat cancers by bypassing the classical caspase-dependent apoptotic pathway. However, very few therapeutic strategies target the lysosomes of cancer cells. Most lysosome-targeted anticancer drugs have very low selectivity for cancer cells. Here, we show intra-lysosomal self-assembly of a peptide amphiphile as a powerful technique to overcome this problem. We designed a peptide amphiphile that localizes in the cancer lysosome and undergoes cathepsin B enzyme-instructed supramolecular assembly. This localized assembly induces lysosomal swelling, membrane permeabilization, and damage to the lysosome, and eventually causes caspase-independent apoptotic death of cancer cells. It has specific anticancer effects and is effective against drug-resistant cancers. Moreover, this peptide amphiphile exhibits high tumor targeting when attached to a tumor-targeting ligand and causes significant inhibition of tumor growth
