323 research outputs found

    Decoding Single Molecule Time Traces with Dynamic Disorder

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    Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm - Variational Bayes-double chain Markov model (VB-DCMM) - to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na+^+ solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA

    MatGD: Materials Graph Digitizer

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    We have developed MatGD (Material Graph Digitizer), which is a tool for digitizing a data line from scientific graphs. The algorithm behind the tool consists of four steps: (1) identifying graphs within subfigures, (2) separating axes and data sections, (3) discerning the data lines by eliminating irrelevant graph objects and matching with the legend, and (4) data extraction and saving. From the 62,534 papers in the areas of batteries, catalysis, and MOFs, 501,045 figures were mined. Remarkably, our tool showcased performance with over 99% accuracy in legend marker and text detection. Moreover, its capability for data line separation stood at 66%, which is much higher compared to other existing figure mining tools. We believe that this tool will be integral to collecting both past and future data from publications, and these data can be used to train various machine learning models that can enhance material predictions and new materials discovery.Comment: 23 pages, 4 figure

    Advances in AFM Imaging Applications for Characterizing the Biophysical Properties of Amyloid Fibrils

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    Although the formation mechanism of amyloid fibrils in bodies is still debated, it has recently been reported how amyloid fibrils can be formed in vitro. Accordingly, we have gained a better understanding of the self-assembly mechanism and intrinsic properties of amyloid fibrils. Because the structure of amyloid fibrils consists of nanoscaled insoluble strands (a few nanometers in diameter and micrometers long), a special tool is needed to study amyloid fibrils at length. Atomic force microscopy (AFM) is supposed to be a versatile toolkit to probe such a tiny biomolecule. The physical/chemical properties of amyloid fibrils have been explored by AFM. In particular, AFM enables the visualization of amyloid fibrillation with different incubation times as well as the concentrations of the formed amyloid fibrils as affected by fibril diameters and lengths. Very recently, the minute structural changes and/or electrical properties of amyloid fibrils have been made by using advanced AFM techniques including dynamic liquid AFM, PeakForce QNM (quantitative nanomechanical mapping), and Kelvin probe force microscopy (KPFM). Herein, we summarize the biophysical properties of amyloid fibrils that are newly discovered with the help of those advanced AFM techniques and suggest our perspectives and future directions for the study of amyloid fibrils

    Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

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    In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beam-former by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.11Ysciescopu

    Building PRFs from TPRPs: Beyond the Block and the Tweak Length Bounds

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    A secure n-bit tweakable block cipher (TBC) using t-bit tweaks can be modeled as a tweakable uniform random permutation, where each tweak defines an independent random n-bit permutation. When an input to this tweakable permutation is fixed, it can be viewed as a perfectly secure t-bit random function. On the other hand, when a tweak is fixed, it can be viewed as a perfectly secure n-bit random permutation, and it is well known that the sum of two random permutations is pseudorandom up to 2n queries. A natural question is whether one can construct a pseudorandom function (PRF) beyond the block and the tweak length bounds using a small number of calls to the underlying tweakable permutations. A straightforward way of constructing a PRF from tweakable permutations is to xor the outputs from two tweakable permutations with c bits of the input to each permutation fixed. Using the multi-user security of the sum of two permutations, one can prove that the (t + n − c)-to-n bit PRF is secure up to 2n+c queries. In this paper, we propose a family of PRF constructions based on tweakable permutations, dubbed XoTPc, achieving stronger security than the straightforward construction. XoTPc is parameterized by c, giving a (t + n − c)-to-n bit PRF. When t < 3n and c = t/3 , XoTPt/3 becomes an (n + 2t/3 )-to-n bit pseudorandom function, which is secure up to 2n+2t/3 queries. It provides security beyond the block and the tweak length bounds, making two calls to the underlying tweakable permutations. In order to prove the security of XoTPc, we extend Mirror theory to q ≫ 2n, where q is the number of equations. From a practical point of view, our construction can be used to construct TBC-based MAC finalization functions and CTR-type encryption modes with stronger provable security compared to existing schemes
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