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。     

Inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products formation in a bovine serum albumin–fructose model

This study investigated the inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products (fAGEs) formation in a bovine serum albumin (BSA)–fructose model. Model systems of BSA and fructose were prepared, and curcumin or piperine was added. fAGEs and BSA oxidation product (dityrosine, kynurenine and N'-formylkynurenine) contents were determined. The results showed that fAGEs content decreased with increasing concentration of curcumin and piperine (P < 0.05). Addition of curcumin and piperine at 160 µg mL⁻¹ could inhibit fluorescent AGEs by 100% and 93% respectively. Dityrosine and N'-formylkynurenine contents decreased as curcumin and piperine concentration increased (P < 0.05). Furthermore, the result of principal component analysis indicated that curcumin and piperine markedly impeded BSA oxidation, resulting in a lower level of fAGEs in model systems. Therefore, adding curcumin and piperine may facilitate reduced fAGEs levels in BSA–fructose model.     

High-temperature oxidation behavior of monolithic Zr3[Al(Si)]4C6 and its composite incorporating 30vol% ZrB2-SiC: Providing a basis for broadening the service temperature

To provide a basis for the high-temperature oxidation of ultra-high temperature ceramics (UHTCs), the oxidation behavior of Zr₃[Al(Si)]₄C₆ and a novel Zr₃[Al(Si)]₄C₆-ZrB₂-SiC composite at 1500 °C were investigated for the first time. From the calculation results, the oxidation kinetics of the two specimens follow the oxidation dynamic parabolic law. Zr₃[Al(Si)]₄C₆ exhibited a thinner oxide scale and lower oxidation rate than those of the composite under the same conditions. The oxide scale of Zr₃[Al(Si)]₄C₆ exhibited a two-layer structure, while that of the composite exhibited a three-layer structure. Owing to the volatilization of B₂O₃ and the active oxidation of SiC, a porous oxide layer formed in the oxide scale of the composite, resulting in the degradation of its oxidation performance. Furthermore, the cracks and defects in the oxide scale of the composite indicate that the reliability of the oxide scale was poor. The results support the service temperature of the obtained ceramics.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

The effect of alkali metal oxide on the properties of borosilicate fireproof glass: Structure,thermal properties,viscosity, chemical stability

The purpose of the current work was to research the effect of alkali metal oxide on the structure, thermal properties, viscosity and chemical stability in the glass system (R₂O–CaO–B₂O₃–SiO₂) systematically. Because the glass would emulsify when Li₂O was added to the glass batch, this article did not discuss Li₂O. The results showed that when the amount of Na₂O was less than 4 mol.%, there was a higher interconnectivity of borate and silicate sub-networks in glass, as more mixed Si–O–B bonds were present in glass. The glass samples exhibited excellent thermal properties and chemical stabilities. As the amount of Na₂O exceeded 4 mol.%, the interconnectivity of borate and silicate sub-networks was weakened. The thermal properties and chemical stabilities of the glass samples were reduced. The connectivity of the silicate sub-network was weakened slightly as the Na/K ratio varied, and the coefficient of thermal expansion (CTE) of the glass samples gradually increased, and the resistance to thermal shock (RTS) value gradually decreased. Moreover, the viscosity of the glass samples decreased with the ratio of Na/Si and Na/K increased.     

The Multifaceted Mas-Related G Protein-Coupled Receptor Member X2 in Allergic Diseases and Beyond

Recent research on mast cell biology has turned its focus on MRGPRX2, a new member of the Mas-related G protein-coupled subfamily of receptors (Mrgprs), originally described in nociceptive neurons of the dorsal root ganglia. MRGPRX2, a member of this group, is present not only in neurons but also in mast cells (MCs), specifically, and potentially in other cells of the immune system, such as basophils and eosinophils. As emerging new functions for this receptor are studied, a variety of both natural and pharmacologic ligands are being uncovered, linked to the ability to induce receptor-mediated MC activation and degranulation. The diversity of these ligands, characterized in their human, mice, or rat homologues, seems to match that of the receptor’s interactions. Natural ligands include host defense peptides, basic molecules, and key neuropeptides such as substance P and vasointestinal peptide (known for their role in the transmission of pain and itch) as well as eosinophil granule-derived proteins. Exogenous ligands include MC secretagogues such as compound 48/80 and mastoparan, a component of bee wasp venom, and several peptidergic drugs, among which are members of the quinolone family, neuromuscular blocking agents, morphine, and vancomycin. These discoveries shed light on its capacity as a multifaceted participant in naturally occurring responses within immunity and neural stimulus perception, as in responses at the center of immune pathology. In host defense, the mice Mrgprb2 has been proven to aid mast cells in the detection of peptidic molecules from bacteria and in the release of peptides with antimicrobial activities and other immune mediators. There are several potential actions described for it in tissue homeostasis and repair. In the realm of pathologic response, there is evidence to suggest that this receptor is also involved in chronic inflammation. Furthermore, MRGPRX2 has been linked to the pathophysiology of non-IgE-mediated immediate hypersensitivity drug reactions. Different studies have shown its possible role in other allergic diseases as well, such as asthma, atopic dermatitis, contact dermatitis, and chronic spontaneous urticaria. In this review, we sought to cover its function in physiologic processes and responses, as well as in allergic and nonallergic immune disease.     

Statistical Piezotronic Effect in Nanocrystal Bulk by Anisotropic Geometry Control

Utilizing inner-crystal piezoelectric polarization charges to control carrier transport across a metal-semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano-electromechanical system (MEMS/NEMS), human-machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress-induced piezo-potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m⁻¹ MPa⁻¹ and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.     

Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.