AC2: An Efficient Protein Sequence Compression Tool Using Artificial Neural Networks and Cache-Hash Models

Recently, the scientific community has witnessed a substantial increase in the generation of protein sequence data, triggering emergent challenges of increasing importance, namely efficient storage and improved data analysis. For both applications, data compression is a straightforward solution. However, in the literature, the number of specific protein sequence compressors is relatively low. Moreover, these specialized compressors marginally improve the compression ratio over the best general-purpose compressors. In this paper, we present AC2, a new lossless data compressor for protein (or amino acid) sequences. AC2 uses a neural network to mix experts with a stacked generalization approach and individual cache-hash memory models to the highest-context orders. Compared to the previous compressor (AC), we show gains of 2–9% and 6–7% in reference-free and reference-based modes, respectively. These gains come at the cost of three times slower computations. AC2 also improves memory usage against AC, with requirements about seven times lower, without being affected by the sequences’ input size. As an analysis application, we use AC2 to measure the similarity between each SARS-CoV-2 protein sequence with each viral protein sequence from the whole UniProt database. The results consistently show higher similarity to the pangolin coronavirus, followed by the bat and human coronaviruses, contributing with critical results to a current controversial subject. AC2 is available for free download under GPLv3 license.     

Convective boson-fermion pairing mode in one-dimensional oscillating optical superlattice

A convective pairing mode of a boson-fermion mixture of ultracold atoms confined in an optical superlattice can be induced by the transformation between two optical superlattice configurations. This convective pairing mode only exists in discrete momentum vector zones for pairing energy gaps. The energy spectrum of gapped states is characterized by topological winding numbers. Two neighboring gapped states are bridged by an unstable chiral linear mode, which drives the boson-fermion pair into directional motion for a short period but remains static in the supersymmetric phase with time-reversal symmetry. The phase transition from a gapped mode to a gapless mode occurs at a critical temperature, whose distribution curve for chemical potential demonstrates a similar dome-like trend as that of high $T_c$ superconductor. The boson-fermion pairing may shed light on a possible mechanism of high-$T_c$ superconductivity.     

A CONSTITUTIVE MODEL FOR TRANSFORMATION, REORIENTATION AND PLASTIC DEFORMATION OF SHAPE MEMORY ALLOYS

A constitutive model is developed for the transformation, reorientation and plastic deformation of shape memory alloys (SMAs). It is based on the concept that an SMA is a mixture composed of austenite and martensite, the volume fraction of each phase is transformable with the change of applied thermal-mechanical loading, and the constitutive behavior of the SMA is the combination of the individual behavior of its two phases. The deformation of the martensite is separated into elastic, thermal, reorientation and plastic parts, and that of the austenite is separated into elastic, thermal and plastic parts. Making use of the Tanaka’s transformation rule modified by taking into account the effect of plastic deformation, the constitutive model of the SMA is obtained. The ferroelasticity, pseudoelasticity and shape memory effect of SMA Au-47.5 at.%Cd, and the pseudoelasticity and shape memory effect as well as plastic deformation and its effect of an NiTi SMA, are analyzed and compared with experimental results.     

A Unified Formulation of k-Means,Fuzzy c-Means and Gaussian Mixture Model by the Kolmogorov–Nagumo Average

Clustering is a major unsupervised learning algorithm and is widely applied in data mining and statistical data analyses. Typical examples include k-means, fuzzy c-means, and Gaussian mixture models, which are categorized into hard, soft, and model-based clusterings, respectively. We propose a new clustering, called Pareto clustering, based on the Kolmogorov–Nagumo average, which is defined by a survival function of the Pareto distribution. The proposed algorithm incorporates all the aforementioned clusterings plus maximum-entropy clustering. We introduce a probabilistic framework for the proposed method, in which the underlying distribution to give consistency is discussed. We build the minorize-maximization algorithm to estimate the parameters in Pareto clustering. We compare the performance with existing methods in simulation studies and in benchmark dataset analyses to demonstrate its highly practical utilities.     

On modeling left-truncated loss data using mixtures of distributions

A new statistical methodology is developed for fitting left-truncated loss data by using the G-component finite mixture model with any combination of Gamma, Lognormal, and Weibull distributions. The EM algorithm, along with the emEM initialization strategy, is employed for model fitting. We propose a new grid map which considers the model selection criterion (AIC or BIC) and risk measures at the same time, by using the entire space of models under consideration. A simulation study validates our proposed approach. The application of the proposed methodology and use of new grid maps are illustrated through analyzing a real data set that includes left-truncated insurance losses.     

Complex mixture analysis of organic compounds in green coffee bean extract by two‐dimensional NMR spectroscopy

A complex mixture analysis by one‐ and two‐dimensional nuclear magnetic resonance (NMR) spectroscopy was carried out for the first time for the identification and quantification of organic compounds in green coffee bean extract (GCBE). A combination of ¹H? ¹H DQF‐COSY, ¹H? ¹³C HSQC, and ¹H? ¹³C CT‐HMBC two‐dimensional sequences was used, and 16 compounds were identified. In particular, three isomers of caffeoylquinic acid were identified in the complex mixture without any separation. In addition, GCBE components were quantified by the integration of carbon signals by use of a relaxation reagent and an inverse‐gated decoupling method without a nuclear Overhauser effect. This NMR methodology provides detailed information about the kinds and amounts of GCBE components, and in our study, the chemical makeup of GCBE was clarified by the NMR results. Copyright © 2010 John Wiley & Sons, Ltd.     

A thermodynamically consistent explicit competitive adsorption isotherm model based on second-order single component behaviour

A competitive adsorption isotherm model is derived for binary mixtures of components characterized by single component isotherms which are second-order truncations of higher order equilibrium models suggested by multi-layer theory and statistical thermodynamics. The competitive isotherms are determined using the ideal adsorbed solution (IAS) theory which, in case of complex single component isotherms, does not generate explicit expressions to calculated equilibrium loadings and causes time consuming iterations in simulations of adsorption processes. The explicit model derived in this work is based on an analysis of the roots of a cubic polynomial resulting from the set of IAS equations. The suggested thermodynamically consistent and widely applicable competitive isotherm model can be recommended as a flexible tool for efficient simulations of fixed-bed adsorber dynamics.     

谐振管中混合工质的热声分离效应

本文在可压缩SIMPLE算法的基础上,基于先求解二维热声谐振腔内的速度场和温度场,然后利用求出的速度和温度值求解组分浓度场的思路,对混合工质的热声分离现象进行了数值研究。研究结果表明:在热声效应和热扩散效应共同作用下,声波能够将混合物中的两种气体分别泵向谐振腔的压力腹点和节点,使得混合气体在声波传播方向上逐渐分离。另外,通过考察5种不同管径下谐振管内径向浓度的变化规律,详细研究了浓度边界层在径向上的影响范围以及不同管径下的分离效率,并提出最佳管径应为16倍浓度渗透深度左右。     

Multiple M‐Effect Signal in Noble Gases and Hydrogen Mixture Discharge

The M‐effect (monochromatization‐effect) is a powerful process which can give high intensity monochromatic spectra with a certain wavelength depending on the type of used gas mixtures to generate the plasma state. The effect consists in the emission of a single spectral line emerging from plasma under specific experimental conditions involving one electropositive gas and one electronegative gas mixture. For example, in the case of Ne‐H₂ mixture, a clear monochrome radiation was obtained, corresponding to the λ_Ne =585.3 nm wavelength at 2p₁‐1s₂ transition in the Paschen notation, the pressures ranging between 10‐100 torr. In this paper we prove the general character of this effect, i.e. if the optical emission spectra (OES) reduced to selective lines can be noticed also in other multiple gas mixture discharges. The Ne‐Ar‐Xe mixture discharges with different percentages of H2 as electronegative gas added in has been investigated. The triple M‐effect, means three specific monochromatic lines, could be revealed in the OES at 50% of H2 addition in Ne‐Ar‐Xe mixture (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

纳秒脉冲电压下同轴场畸变开关多通道放电特性

使气体开关形成多通道放电是减小开关电感、通道电阻、电极熔蚀,提高开关寿命和稳定性的有效措施。设计了一种同轴场畸变气体火花开关,研究了开关在纳秒脉冲电压下的多通道放电现象。研究了脉冲电压上升速率与多通道放电特性的关系,比较了两种体积比的SF6/Ar混合气体多通道放电特性。实验结果表明:一定气压下,平均通道数随着脉冲电压上升率增加而增多,电流分布趋向均匀;相同脉冲峰值与气压比值,不同气压下,高气压下的通道数较多;SF6/Ar混合气体中,氩气含量较高情况下多通道放电特性较好。最后,结合J.C.Martin的多通道放电理论对实验结果作出了初步解释。