Blockchain Framework for Digital Learning and Information and Communications Technology

At present, the economic ties between countries worldwide are getting closer and closer. In a world where the internet industry is developing rapidly, Digital learning and ICT applications in blockchain have gradually matured. This paper takes digital learning and ICT blockchain application in e-commerce as the main research object, The rapid development of e-commerce has been promoted through the extensive application of digital learning and information and communication technology blockchain in e-commerce. Digital learning and information and communication technology solve the problems of e-commerce payment with encryption characteristics and security and openness in blockchain; At the same time, the information can be traced and cannot be tampered with to solve the quality problem of e-commerce goods. In a real sense to promote the sustainable development of the field of e-commerce, this study provides new ideas and guidance for the blockchain framework of e-learning and ICT in e-commerce

Immunological characterization of stroke-heart syndrome and identification of inflammatory therapeutic targets

Acute cardiac dysfunction caused by stroke-heart syndrome (SHS) is the second leading cause of stroke-related death. The inflammatory response plays a significant role in the pathophysiological process of cardiac damage. However, the mechanisms underlying the brain–heart interaction are poorly understood. Therefore, we aimed to analysis the immunological characterization and identify inflammation therapeutic targets of SHS. We analyzed gene expression data of heart tissue 24 hours after induction of ischemia stoke by MCAO or sham surgery in a publicly available dataset (GSE102558) from Gene Expression Omnibus (GEO). Bioinformatics analysis revealed 138 differentially expressed genes (DEGs) in myocardium of MCAO-treated compared with sham-treated mice, among which, immune and inflammatory pathways were enriched. Analysis of the immune cells infiltration showed that the natural killer cell populations were significantly different between the two groups. We identified five DIREGs, Aplnr, Ccrl2, Cdkn1a, Irak2, and Serpine1 and found that their expression correlated with specific populations of infiltrating immune cells in the cardiac tissue. RT–qPCR and Western blot methods confirmed significant changes in the expression levels of Aplnr, Cdkn1a, Irak2, and Serpine1 after MCAO, which may serve as therapeutic targets to prevent cardiovascular complications after stroke

BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization

Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone to insufficient exploration or model collapse without carefully tuning hyperparameters (aka meta-parameters). In the paper, we propose a general meta ERL framework via bilevel optimization (BiERL) to jointly update hyperparameters in parallel to training the ERL model within a single agent, which relieves the need for prior domain knowledge or costly optimization procedure before model deployment. We design an elegant meta-level architecture that embeds the inner-level's evolving experience into an informative population representation and introduce a simple and feasible evaluation of the meta-level fitness function to facilitate learning efficiency. We perform extensive experiments in MuJoCo and Box2D tasks to verify that as a general framework, BiERL outperforms various baselines and consistently improves the learning performance for a diversity of ERL algorithms.Comment: Published as a conference paper at European Conference on Artificial Intelligence (ECAI) 202

In Situ TEM Study of the Degradation of PbSe Nanocrystals in Air

PbSe nanocrystals have attracted widespread attention due to a variety of potential applications. However, the practical utility of these nanocrystals has been hindered by their poor air stability, which induces undesired changes in the optical and electronic properties. An understanding of the degradation of PbSe nanocrystals when they are exposed to air is critical for improving the stability and enhancing their applications. Here, we use in situ transmission electron microscopy (TEM) with an environmental cell connected to air to study PbSe nanocrystal degradation triggered by air exposure. We have also conducted a series of complementary studies, including in situ environmental TEM study of PbSe nanocrystals exposed to pure oxygen and PbSe nanocrystals in H2O using a liquid cell, and ex situ experiments, such as O2 plasma treatment and thermal heating of PbSe nanocrystals under different air exposure. Our in situ observations reveal that when PbSe nanocrystals are exposed to air (or oxygen) under electron beam irradiation, they experience a series of changes, including shape evolution of individual nanocrystals with the cuboid intermediates, coalescence between nanocrystals, and formation of PbSe thin films through drastic solid-state fusion. Further studies show that the PbSe thin films transform into an amorphous Pb rich phase or eventually pure Pb, which suggest that Se reacts with oxygen and can be evaporated under electron beam illumination. These various in situ and ex situ experimental results indicate that PbSe nanocrystal degradation in air is initiated by the dissociation and removal of ligands from the PbSe nanocrystal surface

Nonlinear Gossip Algorithms for Wireless Sensor Networks

We study some nonlinear gossip algorithms for wireless sensor networks. Firstly, two types of nonlinear single gossip algorithms are proposed. By using Lyapunov theory, Lagrange mean value theorem, and stochastic Lasalle’s invariance principle, we prove that the nonlinear single gossip algorithms can converge to the average of initial states with probability one. Secondly, two types of nonlinear multigossip algorithms are also presented and the convergence is proved by the same methods. Finally, computer simulation is also given to show the validity of the theoretical results

A Mode-Sum Prescription for Vacuum Polarization in Even Dimensions

We present a mode-sum regularization prescription for computing the vacuum polarization of a scalar field in static spherically-symmetric black hole spacetimes in even dimensions. This is the first general and systematic approach to regularized vacuum polarization in higher even dimensions, building upon a previous scheme we developed for odd dimensions. Things are more complicated here since the even-dimensional propagator possesses logarithmic singularities which must be regularized. However, in spite of this complication, the regularization parameters can be computed in closed form in arbitrary even dimensions and for arbitrary metric function $f(r)$. As an explicit example of our method, we show plots for vacuum polarization of a massless scalar field in the Schwarzschild-Tangherlini spacetime for even $d=4,...,10$. However, the method presented applies straightforwardly to massive fields or to nonvacuum spacetimes.Comment: arXiv admin note: text overlap with arXiv:1609.0816

Quantum Stress: Density Functional Theory Formulation and Physical Manifestation

The concept of "quantum stress (QS)" is introduced and formulated within density functional theory (DFT), to elucidate extrinsic electronic effects on the stress state of solids and thin films in the absence of lattice strain. A formal expression of QS (\sigma^Q) is derived in relation to deformation potential of electronic states ({\Xi}) and variation of electron density ({\Delta}n), \sigma^Q = {\Xi}{\Delta}n, as a quantum analog of classical Hook's law. Two distinct QS manifestations are demonstrated quantitatively by DFT calculations: (1) in the form of bulk stress induced by charge carriers; and (2) in the form of surface stress induced by quantum confinement. Implications of QS in some physical phenomena are discussed to underlie its importance.Comment: 5 pages, 4 figure

FGF: A web tool for Fishing Gene Family in a whole genome database

Gene duplication is an important process in evolution. The availability of genome sequences of a number of organisms has made it possible to conduct comprehensive searches for duplicated genes enabling informative studies of their evolution. We have established the FGF (Fishing Gene Family) program to efficiently search for and identify gene families. The FGF output displays the results as visual phylogenetic trees including information on gene structure, chromosome position, duplication fate and selective pressure. It is particularly useful to identify pseudogenes and detect changes in gene structure. FGF is freely available on a web server at http://fgf.genomics.org.cn