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		<title>papers on Codeless Code</title>
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				<title>Evaluating LTL Formulas for On-Board Unmanned Vehicle Health Monitoring</title>
				<link>https://code.lol/papers/ltl-icas-2019/</link>
				<pubDate>Sun, 02 Jun 2019 00:00:00 +0000</pubDate>
				<guid>https://code.lol/papers/ltl-icas-2019/</guid>
				<description>&lt;section class=&#34;paper-abstract&#34;&gt;&#xA;&lt;h2&gt;Abstract&lt;/h2&gt;&#xA;&lt;p&gt;The proliferation of unmanned vehicle technologies has drastically increased their use in multiple domains. In the maritime domain, unmanned surface vehicles often pose special requirements for on-board health monitoring and fault mitigation due to long endurance, which increases the likelihood of failures when operating without human oversight. Whereas such vehicles can be equipped with numerous on-board sensors, detecting actual or impending failures is often more complicated than simply thresholding values of a sensor reading. In this paper, we will consider the use of Linear Temporal Logic (LTL) as a means to specify and then evaluate in real-time, the health status of an unmanned surface vehicle. This is accomplished by capturing nominal conditions in LTL formulas and then evaluating these formulas in real-time. The advantage of LTL is that it allows capturing value-based as well as time-based expectations for sensor readings when evaluating system status. We define a formal language which is an extension of LTL, and a corresponding software evaluation method with bounded performance. An example demonstration of the feasibility of the process is presented.&lt;/p&gt;</description>
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				<title>Quantification of Twist from the Central Lines of β-Strands</title>
				<link>https://code.lol/papers/twist-jcb-2018/</link>
				<pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate>
				<guid>https://code.lol/papers/twist-jcb-2018/</guid>
				<description>&lt;section class=&#34;paper-abstract&#34;&gt;&#xA;&lt;h2&gt;Abstract&lt;/h2&gt;&#xA;&lt;p&gt;&lt;strong&gt;Since the discovery of right-handed twist of a β-strand, many studies have been conducted to understand the twist. Given the atomic structure of a protein, twist angles have been defined using atomic positions of the backbone. However, limited study is available to characterize twist when the atomic positions are not available, but the central lines of β-strands are. Recent studies in cryoelectron microscopy show that it is possible to predict the central lines of β-strands from a medium-resolution density map. Accurate measurement of twist angles is important in identification of β-strands from such density maps. We propose an effective method to quantify twist angles from a set of splines. In a data set of 55 pairs of β-strands from 11 β-sheets of 11 proteins, the spline measurement shows comparable results as measured using the discrete method that uses atomic positions directly, particularly in capturing twist angle change along a pair, different levels of twist among different pairs, and the average of twist angles. The proposed method provides an alternative method to characterize twist using the central lines of a β-sheet.&lt;/strong&gt;&lt;/p&gt;</description>
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				<title>Analysis of β-strand Twist from the 3-dimensional Image of a Protein</title>
				<link>https://code.lol/papers/twist-acmbcb-2017/</link>
				<pubDate>Sun, 20 Aug 2017 00:00:00 +0000</pubDate>
				<guid>https://code.lol/papers/twist-acmbcb-2017/</guid>
				<description>&lt;section class=&#34;paper-abstract&#34;&gt;&#xA;&lt;h2&gt;Abstract&lt;/h2&gt;&#xA;&lt;p id=&#34;P1&#34;&gt;Electron cryo-microscopy (Cryo-EM) technique produces density maps that are 3-dimensional (3D) images of molecules. It is challenging to derive atomic structures of proteins from 3D images of medium resolutions. Twist of a β-strand has been studied extensively while little of the known information has been directly obtained from the 3D image of a β-sheet. We describe a method to characterize the twist of β-strands from the 3D image of a protein. An analysis of 11 β-sheet images shows that the Averaged Minimum Twist (AMT) angle is larger for a close set than for a far set of β-traces.&lt;/p&gt;</description>
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				<title>An Iterative Bézier Method for Fitting Beta-sheet Component of a Cryo-EM Density Map</title>
				<link>https://code.lol/papers/bezier-mbmb-2017/</link>
				<pubDate>Sat, 01 Apr 2017 00:00:00 +0000</pubDate>
				<guid>https://code.lol/papers/bezier-mbmb-2017/</guid>
				<description>&lt;section class=&#34;paper-abstract&#34;&gt;&#xA;&lt;h2&gt;Abstract&lt;/h2&gt;&#xA;&lt;p id=&#34;P1&#34;&gt;Cryo-electron microscopy (Cryo-EM) is a powerful technique to produce 3-dimensional density maps for large molecular complexes. Although many atomic structures have been solved from cryo-EM density maps, it is challenging to derive atomic structures when the resolution of density maps is not sufficiently high. Geometrical shape representation of secondary structural components in a medium-resolution density map enhances modeling of atomic structures. We compare two methods in producing surface representation of the β-sheet component of a density map. Given a 3-dimensional volume of β-sheet that is segmented from a density map, the performance of a polynomial fitting was compared with that of an iterative Bézier fitting. The results suggest that the iterative Bézier fitting is more suitable for β-sheets, since it provides more accurate representation of the corners that are naturally twisted in a β-sheet.&lt;/p&gt;</description>
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