The Jackprot Simulation Couples Mutation Rate with Natural Selection to Illustrate How Protein Evolution Is Not Random

Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke “design creationism” to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane’s hydrophobic/philic nature; a selective “pore” for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the “jackprot,” which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the “jackprot,” or highest-fitness complete-peptide sequence, required cumulative smaller “wins” (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons (“jackdons” that led to “jackacids” that led to the “jackprot”). The “jackprot” is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide “edition” and gene duplications to generate the 6TMs. Ion channels are essential to the physiology of neurons, ganglia, and brains, and were crucial to the evolutionary advent of consciousness. The Jackprot Simulation illustrates in a computer model that evolution is not and cannot be a random process as conceived by design creationists

On the spectrum of operators concerned with the reduced singular Cauchy integral

We investigate spectrums of the reduced singular Cauchy operator and its real and imaginary components

Contrast‐Enhanced Diagnostic Ultrasound Causes Renal Tissue Damage in a Porcine Model

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135402/1/jum201029101391.pd

Learning Structural Representations for Recipe Generation and Food Retrieval

Food is significant to human daily life. In this paper, we are interested in learning structural representations for lengthy recipes, that can benefit the recipe generation and food cross-modal retrieval tasks. Different from the common vision-language data, here the food images contain mixed ingredients and target recipes are lengthy paragraphs, where we do not have annotations on structure information. To address the above limitations, we propose a novel method to unsupervisedly learn the sentence-level tree structures for the cooking recipes. Our approach brings together several novel ideas in a systematic framework: (1) exploiting an unsupervised learning approach to obtain the sentence-level tree structure labels before training; (2) generating trees of target recipes from images with the supervision of tree structure labels learned from (1); and (3) integrating the learned tree structures into the recipe generation and food cross-modal retrieval procedure. Our proposed model can produce good-quality sentence-level tree structures and coherent recipes. We achieve the state-of-the-art recipe generation and food cross-modal retrieval performance on the benchmark Recipe1M dataset.Comment: Accepted at IEEE Transactions on Pattern Analysis and Machine Intelligence. arXiv admin note: substantial text overlap with arXiv:2009.0094

Asymptotic behaviour in temporal logic

International audienceno abstrac

Structure-Aware Generation Network for Recipe Generation from Images

Sharing food has become very popular with the development of social media. For many real-world applications, people are keen to know the underlying recipes of a food item. In this paper, we are interested in automatically generating cooking instructions for food. We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task. However, compared with image captioning datasets, the target recipes are long-length paragraphs and do not have annotations on structure information. To address the above limitations, we propose a novel framework of Structure-aware Generation Network (SGN) to tackle the food recipe generation task. Our approach brings together several novel ideas in a systematic framework: (1) exploiting an unsupervised learning approach to obtain the sentence-level tree structure labels before training; (2) generating trees of target recipes from images with the supervision of tree structure labels learned from (1); and (3) integrating the inferred tree structures with the recipe generation procedure. Our proposed model can produce high-quality and coherent recipes, and achieve the state-of-the-art performance on the benchmark Recipe1M dataset.Comment: Published at ECCV 202

The concept of mean free path in the kinetic Monte Carlo description of bulk fluid behaviour, vapour-liquid equilibria and surface adsorption of argon

Recently, kinetic Monte Carlo (kMC) simulation has been successfully applied to describe bulk fluid behaviour, vapour-liquid equilibrium and adsorption on a graphite surface [Ustinov and Do, J. Colloid Interf. Sci. 366(1) (2012), pp. 216-223]. Its advantage over Metropolis-MC lies in the excellent sampling of the energy space for the direct determination of the chemical potential. In this paper, we address the mechanics of the displacement of a particle, which is the only step in kMC. By invoking the mean free path (MFP) concept and the average travel distance, we establish the connection between the particle sampling of the volume space and the distance of travel of the particle related to the MFP through the Beer-Lambert law. We apply this procedure to vapour-liquid equilibrium in bulk fluid argon and to adsorption of argon on a graphite surface, and demonstrate that the results are entirely consistent with previous simulations

Inference of Tidal Elevation in Shallow Water Using a Vessel-Towed Acoustic Doppler Current Profiler

Vessel-towed acoustic Doppler current profilers (ADCPs) have been widely used to measure velocity profiles. Since the instrument is usually mounted on a catamaran floating on the surface, previous studies have used the water surface as the reference level from which the vertical coordinate for the velocity profile is defined. However, because of the tidal oscillation, the vertical coordinate thus defined is time-dependent in an Earth-coordinate system, which introduces an error to the estimated harmonic constants for the velocity. As a result, the total transport will also be in error. This is particularly a problem in shallow waters where the tidal elevation is relatively large. Therefore tidal elevation needs to be resolved to make a correct harmonic analysis for the velocity. The present study is aimed at resolving the tidal elevation change in shallow water using a vessel-towed ADCP. Semidiurnal and diurnal tidal elevations across the lower Chesapeake Bay have been determined using a vessel-towed ADCP. Data from four cruises ranging from 25 to 92 hours in 1996 and 1997 are used. Water depth averaged every 30 s by the ADCP is studied by harmonic and statistical analysis. By selecting only the data within a narrow band (similar to 320 m) over the planned transect, we are able to improve the reliability of the data. We then grid the depth data along the 16 km transect into 200 equal segments and use harmonic analysis to resolve the semidiurnal and diurnal tidal variations within each segment. We find that (1) the depth data from the ADCP contain both semidiurnal and diurnal signals that can be resolved, from which the surface elevation can be inferred, (2) the major error appears to come from spatial variation of the depth, (3) the semidiurnal and diurnal tidal variations of elevation inferred over Aat bottom topography account for almost 100% of the total variability, while those measurements over large bottom slopes account for a much lower percentage of the total variability, (4) at least 70% of the variability of depth can be explained by semidiurnal and diurnal tides if the bottom slope is smaller than 0.006, and (5) the spatial variation of both amplitude and phase of the elevation along the transect appears to be small with a slightly lower tidal amplitude at the south of the Chesapeake Bay entrance, consistent with the Coriolis effect. The inferred elevations from the ADCP readings are consistent with sea level measurements at a tide station 10 km inside the estuary