Probing molecular environments with a fictitious isotopic dipole

A HD-like (HD: mono-deuterated hydrogen molecule) isotopic dipole moment is proposed as a sensible probe for molecular environments, in particular for electrostatic fields and polarizable (reactive) sites of molecules. Fictitious nuclear masses are chosen in order to yield a rigid dipole with a small appropriate magnitude. Upon subtracting the Born-Oppenheimer energy, the interaction is reduced to field-dipole-like and dipole-polarizability-like terms, the last one being particularly informative since connected to potentially reactive sites. Possible asymmetries of this term appear as signatures of charged sites in the molecule. The field strength and orientation are easily obtained by identifying the minimum field-dipole energy configuration and flipping the dipole from it. Tests with hydrogen, water, benzene, and chlorobenzene molecules confirm the good performance of the method. In an application to test the present models for hydrogen activation by a frustrated Lewis pair, the full potential of the method is assessed.     

Inorganic Molecular Electride Mg4O3: Structure,Bonding, and Nonlinear Optical Properties

Growing demands of material science and, in particular, in the field of nonlinear optics (NLO) encourage us to look for stable highly polarizable molecules with excess diffuse electrons. An unusual class of compounds called electrides comply with these requirements. Many attempts have been made, yet only few electrides have been synthesized as solids and none of them as molecular species. In this paper, a new theoretically designed molecular species with electride characteristics is reported. The idea of this molecular electride comes from the formation of electride-like features in the MgO crystal with defect F-centers. The geometry of the investigated molecule can be described as a Mg₄O₄ cube with one oxygen atom removed. In Mg₄O₃, two 3s electrons are pushed out from the inner area of the molecule forming a diffuse electride multicentered bond. Our calculations show that this electride-like cluster possesses a noticeably large first hyperpolarizability β=5733 au. At the same time, a complete cube Mg₄O₄ and Mg₄O₃²⁺ without electride electron pair have much smaller β: 0 au and 741 au, respectively. This fact indicates the decisive role of the electride electron pair in NLO properties. Additionally, vertical detachment energies of isomers (VDE), excitation energies ΔE, polarizabilities α, and IR spectra were calculated. These properties, including β, are supposed to be observable experimentally and can serve as indirect evidence of the stable molecular electride formation.     

The Plasticity of the Carbohydrate Recognition Domain Dictates the Exquisite Mechanism of Binding of Human Macrophage Galactose-Type Lectin

The human macrophage galactose-type lectin (MGL), expressed on macrophages and dendritic cells (DCs), modulates distinct immune cell responses by recognizing N-acetylgalactosamine (GalNAc) containing structures present on pathogens, self-glycoproteins, and tumor cells. Herein, NMR spectroscopy and molecular dynamics (MD) simulations were used to investigate the structural preferences of MGL against different GalNAc-containing structures derived from the blood group A antigen, the Forssman antigen, and the GM2 glycolipid. NMR spectroscopic analysis of the MGL carbohydrate recognition domain (MGL-CRD, C181-H316) in the absence and presence of methyl α-GalNAc (α-MeGalNAc), a simple monosaccharide, shows that the MGL-CRD is highly dynamic and its structure is strongly altered upon ligand binding. This plasticity of the MGL-CRD structure explains the ability of MGL to accommodate different GalNAc-containing molecules. However, key differences are observed in the recognition process depending on whether the GalNAc is part of the blood group A antigen, the Forssman antigen, or GM2-derived structures. These results are in accordance with molecular dynamics simulations that suggest the existence of a distinct MGL binding mechanism depending on the context of GalNAc moiety presentation. These results afford new perspectives for the rational design of GalNAc modifications that fine tune MGL immune responses in distinct biological contexts, especially in malignancy.     

Enhancing the Viscosity-Sensitive Range of a BODIPY Molecular Rotor by Two Orders of Magnitude

Molecular rotors are a class of fluorophores that enable convenient imaging of viscosity inside microscopic samples such as lipid vesicles or live cells. Currently, rotor compounds containing a boron-dipyrromethene (BODIPY) group are among the most promising viscosity probes. In this work, it is reported that by adding heavy-electron-withdrawing −NO₂ groups, the viscosity-sensitive range of a BODIPY probe is drastically expanded from 5–1500 cP to 0.5–50 000 cP. The improved range makes it, to our knowledge, the first hydrophobic molecular rotor applicable not only at moderate viscosities but also for viscosity measurements in highly viscous samples. Furthermore, the photophysical mechanism of the BODIPY molecular rotors under study has been determined by performing quantum chemical calculations and transient absorption experiments. This mechanism demonstrates how BODIPY molecular rotors work in general, why the −NO₂ group causes such an improvement, and why BODIPY molecular rotors suffer from undesirable sensitivity to temperature. Overall, besides reporting a viscosity probe with remarkable properties, the results obtained expand the general understanding of molecular rotors and show a way to use the knowledge of their molecular action mechanism for augmenting their viscosity-sensing properties.     

Continuum versus discrete networks,graph Laplacians,and reproducing kernel Hilbert spaces

Motivated by applications to machine learning, we construct a reversible and irreducible Markov chain whose state space is a certain collection of measurable sets of a chosen l.c.h. space $\mathfrak{X}$. We study the resulting network (connected undirected graph), including transience, Royden and Riesz decompositions, and kernel factorization. We describe a construction for Hilbert spaces of signed measures which comes equipped with a new notion of reproducing kernels and there is a unique solution to a regularized optimization problem involving the approximation of $L^2$ functions by functions of finite energy. The latter has applications to machine learning (for Markov random fields, for example).     

Theoretical Design of Biodegradable Phthalic Acid Ester Derivatives in Marine and Freshwater Environments

The biodegradability of phtalic acid esters in marine and freshwater environments was characterized by their binding free energy with corresponding degrading enzymes. According to comprehensive biodegradation effects weights, the binding free energy values were converted into dimensionless efficacy coefficient using ratio normalization method. Then, considering comprehensive dual biodegradation effects value and the structural parameters of PAEs in both marine and freshwater environments, a 3D-QSAR pharmacophore model was constructed, five PAE derivatives (DBP−COOH, DBP−CHO, DBP−OH, DINP−NH₂, and DINP−NO₂) were screened out based on their environmental friendliness, functionality and stability. The prediction of biodegradation effects on five PAE derivatives by biodegradation models in marine and freshwater environment increased by 15.90 %, 15.84 %, 27.21 %, 12.33 %, and 8.32 %, and 21.57 %, 15.21 %, 20.99 %, 15.10 %, and 9.74 %, respectively. By simulating the photodegradation path of the PAE derivative molecular, it was found that DBP−OH can generate ^.OH and provides free radicals for the photodegradation of microplastics in the environment.     

在线社交网络控制实验的现状与展望

在线社交网络已发展成为一个独特的电子生态系统，其应用深刻影响着人们生活的方方面面。由于在线社交网络特性复杂，分析在线社交网络形成和变化中的规律成为当前计算机科学、社会学和物理学的一项挑战。传统上，在线社交网络实证研究主要采用计算机辅助的被动数据获取和分析方式。近年来，在真实大规模在线社交网络上直接进行控制实验从而主动获取数据并开展分析研究的方式广受关注。评述了这一领域的研究进展，包括：社交网络控制实验的主要研究模式；控制实验方法在社交网络结构、信息传播、行为和心理学等领域取得的主要成果以及主要实验工具的适用条件和局限性。最后，展望了人工智能技术在社交网络控制实验中的应用潜力，分析了智能算法对降低实验成本和提高实验效率的作用。     

多层网络级联失效的预防和恢复策略概述

现实生活中,与国计民生密切相关的基础设施网络大多不是独立存在的,而是彼此之间相互联系或依赖的,于是用于研究这些系统的多层网络模型随之产生.多层网络中的节点在失效或者遭受攻击后会因"层内"和"层间"的相互作用而产生级联效应,从而使得失效能够在网络层内和层间反复传播并使得失效规模逐步放大.因此,多层网络比单个网络更加脆弱.多层网络级联失效产生的影响和损失往往是非常巨大的,所以对多层网络级联失效的预防和恢复的研究具有重大意义.就多层网络级联失效的预防而言,主要包含故障检测,保护重要节点,改变网络耦合机制和节点备份等策略.就多层网络发生级联失效后的恢复策略而言,主要包含共同边界节点恢复、空闲连边恢复、加边恢复、重要节点优先恢复、更改拓扑结构、局域攻击修复、自适应边修复等策略.     

On the Motion of Substance in a Channel of a Network: Extended Model and New Classes of Probability Distributions

We discuss the motion of substance in a channel containing nodes of a network. Each node of the channel can exchange substance with: (i) neighboring nodes of the channel, (ii) network nodes which do not belong to the channel, and (iii) environment of the network. The new point in this study is that we assume possibility for exchange of substance among flows of substance between nodes of the channel and: (i) nodes that belong to the network but do not belong to the channel and (ii) environment of the network. This leads to an extension of the model of motion of substance and the extended model contains previous models as particular cases. We use a discrete-time model of motion of substance and consider a stationary regime of motion of substance in a channel containing a finite number of nodes. As results of the study, we obtain a class of probability distributions connected to the amount of substance in nodes of the channel. We prove that the obtained class of distributions contains all truncated discrete probability distributions of discrete random variable ω which can take values 0,1,⋯,N. Theory for the case of a channel containing infinite number of nodes is presented in Appendix A. The continuous version of the discussed discrete probability distributions is described in Appendix B. The discussed extended model and obtained results can be used for the study of phenomena that can be modeled by flows in networks: motion of resources, traffic flows, motion of migrants, etc.