5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

Tuning of shear thickening behavior and elastic strength of polyvinylidene fluoride via doping of ZnO-graphene

ZnO rice like nonarchitects are grafted on the graphene carbon core via a rapid microwave synthesis route. The prepared grafted systems are characterized via XRD, SEM, RAMAN, and XPS to examined the structural and morphological parameters. Zinc oxide grafted graphene sheets (ZnO-G) are further doped in β-phase of polyvinylidene fluoride (PVDF) to prepare the polymer nanocomposites (PNCs) via mixed solvent approach (THF/DMF). β-phase confirmation of PVDF PNCs is done by FTIR studies. It is observed that ZnO-G filler enhances the β-phase content in the PNCs. Non-doped PVDF and PNCs are further studied for rheological behavior under the shear rate of 1–100 s⁻¹. Doping of ZnO-G dopant to the PVDF matrix changes its discontinuous shear thickening (DST) behavior to continues shear thickening behavior (CST). Hydrocluster formation and their interaction with the dopant could be the reason for this striking DST to CST behavioral change. Strain amplitude sweep (10⁻³% -10%) oscillatory test reveals that the PNCs shows extended linear viscoelastic region with high elastic modulus and lower viscous modulus. Effective shear thickening behavior and strong elastic strength of these PNCs present their candidature for various fields including mechanical and soft body armor applications.     

The influence of FeNi nanoparticles on the microstructures and soft magnetic properties of FeSi soft magnetic composites

In this work, a new type of FeSi/FeNi soft magnetic powder core (SMPC) was successfully fabricated by coating FeNi nanoparticles on the surface of FeSi micrometer powder. The effects of different contents of FeNi nanoparticles on the micromorphology, internal structures, and soft magnetic properties of SMPCs were studied. The results show that FeNi nanoparticles adhere to the surface of FeSi powder, which can effectively fill the air gap between FeSi powder and is beneficial to the compaction of the powder cores during the pressing process. Thus, the density of the SMPCs is increased. Compared to FeSi SMPCs, the comprehensive soft magnetic properties of FeSi/FeNi SMPCs have been greatly improved. When adding 15 wt% FeNi nanoparticles, the SMPCs exhibit excellent magnetic properties with high effective permeability (increased by 43.8 %) and low core loss (decreased by 22.1 %). The high performance FeSi/FeNi SMPCs prepared in this work are expected to be widely used in power choke coils, uninterruptible power supplies, and boosts and inverter inductors.     

Some Molecular and Cellular Stress Mechanisms Associated with Neurodegenerative Diseases and Atherosclerosis

Chronic stress is a combination of nonspecific adaptive reactions of the body to the influence of various adverse stress factors which disrupt its homeostasis, and it is also a corresponding state of the organism’s nervous system (or the body in general). We hypothesized that chronic stress may be one of the causes occurence of several molecular and cellular types of stress. We analyzed literary sources and considered most of these types of stress in our review article. We examined genes and mutations of nuclear and mitochondrial genomes and also molecular variants which lead to various types of stress. The end result of chronic stress can be metabolic disturbance in humans and animals, leading to accumulation of reactive oxygen species (ROS), oxidative stress, energy deficiency in cells (due to a decrease in ATP synthesis) and mitochondrial dysfunction. These changes can last for the lifetime and lead to severe pathologies, including neurodegenerative diseases and atherosclerosis. The analysis of literature allowed us to conclude that under the influence of chronic stress, metabolism in the human body can be disrupted, mutations of the mitochondrial and nuclear genome and dysfunction of cells and their compartments can occur. As a result of these processes, oxidative, genotoxic, and cellular stress can occur. Therefore, chronic stress can be one of the causes forthe occurrence and development of neurodegenerative diseases and atherosclerosis. In particular, chronic stress can play a large role in the occurrence and development of oxidative, genotoxic, and cellular types of stress.     

Picosecond laser trimming of ceramic cores with porous multi-scale particle microstructure

The ceramic core, produced by hot injection molding, is one of the critical components for manufacturing high-performance aircraft engine turbine blades. However, the injection molding process will cause defects such as burrs and flashes in the fine structure of the formed ceramic core. Manual trimming is necessary, but the trimming quality is poor, and the yield is low. In this paper, the online trimming method of ceramic cores is studied. Based on the orthogonal experiment method, the optimal laser parameters for processing the ceramic core's porous multi-scale particle structure material were obtained. Further, the problems of the match head and tail phenomenon and dimensional accuracy improvement in trimming ceramic cores have been studied. A path optimisation method is proposed to improve the quality and accuracy of the trimming profile effectively. Finally, the overall process flow of ceramic core trimming is elaborated, and experimental verification is given. The results show that the ceramic core online trimming method proposed in this paper has advantages of high precision and high yield compared with the manual method, which will have substantial potential application value in the aviation field.     

Novel Bi-Doped Amorphous SnOx Nanoshells for Efficient Electrochemical CO2 Reduction into Formate at Low Overpotentials

Engineering novel Sn-based bimetallic materials could provide intriguing catalytic properties to boost the electrochemical CO₂ reduction. Herein, the first synthesis of homogeneous Sn_1−xBi_x alloy nanoparticles (x up to 0.20) with native Bi-doped amorphous SnO_x shells for efficient CO₂ reduction is reported. The Bi-SnO_x nanoshells boost the production of formate with high Faradaic efficiencies (>90%) over a wide potential window (−0.67 to −0.92 V vs RHE) with low overpotentials, outperforming current tin oxide catalysts. The state-of-the-art Bi-SnO_x nanoshells derived from Sn_0.80Bi_0.20 alloy nanoparticles exhibit a great partial current density of 74.6 mA cm⁻² and high Faradaic efficiency of 95.8%. The detailed electrocatalytic analyses and corresponding density functional theory calculations simultaneously reveal that the incorporation of Bi atoms into Sn species facilitates formate production by suppressing the formation of H₂ and CO.     

Simple Sequence Repeat Markers in Genetic Divergence and Marker-Assisted Selection of Rice Cultivars: A Review

Sequencing of rice genome has facilitated the understanding of rice evolution and has been utilized extensively for mining of DNA markers to facilitate marker-assisted breeding. Simple sequence repeat (SSR) markers that are tandemly repeated nucleotide sequence motifs flanked by unique sequences are presently the maker of choice in rice improvement due to their abundance, co-dominant inheritance, high levels of allelic diversity, and simple reproducible assay. The current level of genome coverage by SSR markers in rice is sufficient to employ them for genotype identification and marker-assisted selection in breeding for mapping of genes and quantitative trait loci analysis. This review provides comprehensive information on the mapping and applications of SSR markers in investigation of rice cultivars to study their genetic divergence and marker-assisted selection of important agronomic traits.     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

Combination of nuclear magnetic resonance spectroscopy and nonlinear methods to analyze the copolymerization of phosphonic acid derivatives

We demonstrate in this study that the combination of modern inline monitoring methods [here: inline nuclear magnetic resonance (NMR)] with simulations gains more exact and profound kinetic results than previously used methods like linearization without that combination. The ¹H-NMR spectroscopic data (more than 100 data points) are used to construct the copolymerization diagram. The reactivity ratios are obtained applying the van Herks nonlinear least square method. The examination of the radical copolymerization of 2-hydroxyethyl methacrylate (HEMA) with (2-{[2-(ethoxycarbonyl)prop-2-en-1-yl]oxy}ethyl) phosphonic acid (ECPPA) as important adhesive monomer used in dentistry yields reactivity ratios of r_HEMA = 1.83; r_ECPPA = 0.42. The copolymerization diagram reflects nonideal, non-azeotropic copolymerization. The sequence distribution of the obtained by Monte Carlo simulation indicates the generation of statistical copolymers. As an important finding, it is demonstrated that the repeating units responsible for etching and adhesion are arranged over the whole polymer chain, which is necessary to achieve proper functionality. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48256.     

苏6井区下石盒子组高分辨率层序地层学特征

以高分辨率层序地层学理论和技术方法为指导，在苏里格气田苏6井区地表露头、钻井岩心、测井、地震资料综合研究的基础上，通过基准面旋回结构、叠加样式的沉积动力学分析，将该井区下石盒子组划分为2个长期、5个中期和14个短期旋回层序；并较为详细地讨论了各期旋回层序特征；建立了以长期旋回层序界面和最大洪泛面为等时年代地层框架，以中期旋回层序为等时地层单元的高分辨率层序地层格架；通过分析，认为下石盒子组盒₈下段天然气储、盖条件最为有利；有利于储层发育的河道砂体主要出现在长、中期上升半旋回的中、下部，层序界面上相当短期旋回级别的单河道砂体是下石盒子组天然气勘探开发的主要目标。