5G技术在医院智能服务中的应用

纵观当今的发展格局,是科学技术高速发展的时代。随着5G时代的来临,网络技术在各个领域中扮演着越来越重要的角色。特别是在医疗方面,为医院的日常工作奠定了坚实的基础。今天就5G网络技术在医院只能服务中的应用展开谈论。     

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.     

Alterations in the Genomic Distribution of 5hmC in In Vivo Aged Human Skin Fibroblasts

5-Hydroxymethylcytosine (5hmC) is a functionally active epigenetic modification. We analyzed whether changes in DNA 5-hydroxymethylation are an element of age-related epigenetic drift. We tested primary fibroblast cultures originating from individuals aged 22–35 years and 74–94 years. Global quantities of methylation-related DNA modifications were estimated by the dot blot and colorimetric methods. Regions of the genome differentially hydroxymethylated with age (DHMRs) were identified by hMeDIP-seq and the MEDIPS and DiffBind algorithms. Global levels of DNA modifications were not associated with age. We identified numerous DHMRs that were enriched within introns and intergenic regions and most commonly associated with the H3K4me1 histone mark, promoter-flanking regions, and CCCTC-binding factor (CTCF) binding sites. However, only seven DHMRs were identified by both algorithms and all of their settings. Among them, hypo-hydroxymethylated DHMR in the intron of Rab Escort Protein 1 (CHM) coexisted with increased expression in old cells, while increased 5-hydroxymethylation in the bodies of Arginine and Serine Rich Protein 1 (RSRP1) and Mitochondrial Poly(A) Polymerase (MTPAP) did not change their expression. These age-related differences were not associated with changes in the expression of any of the ten-eleven translocation (TET) enzymes or their activity. In conclusion, the distribution of 5hmC in DNA of in vivo aged human fibroblasts underwent age-associated modifications. The identified DHMRs are, likely, marker changes.     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

Biocomposites of Epoxidized Natural Rubber/Poly(lactic acid) Modified with Natural Fillers (Part I)

The study aimed to prepare sustainable and degradable elastic blends of epoxidized natural rubber (ENR) with poly(lactic acid) (PLA) that were reinforced with flax fiber (FF) and montmorillonite (MMT), simultaneously filling the gap in the literature regarding the PLA-containing polymer blends filled with natural additives. The performed study reveals that FF incorporation into ENR/PLA blend may cause a significant improvement in tensile strength from (10 ± 1) MPa for the reference material to (19 ± 2) MPa for the fibers-filled blend. Additionally, it was found that MMT employment in the role of the filler might contribute to ENR/PLA plasticization and considerably promote the blend elongation up to 600%. This proves the successful creation of the unique and eco-friendly PLA-containing polymer blend exhibiting high elasticity. Moreover, thanks to the performed accelerated thermo-oxidative and ultraviolet (UV) aging, it was established that MMT incorporation may delay the degradation of ENR/PLA blends under the abovementioned conditions. Additionally, mold tests revealed that plant-derived fiber addition might highly enhance the ENR/PLA blend’s biodeterioration potential enabling faster and more efficient growth of microorganisms. Therefore, materials presented in this research may become competitive and eco-friendly alternatives to commonly utilized petro-based polymeric products.     

Corrosion behaviour of Mg-Gd-Y-Zn-Ag alloy components with different sizes after cooling

The corrosion behaviour of Mg-6Gd-3Y-1Zn-0.3Ag (wt.%) alloy components with different sizes after cooling was investigated. The alloys in the small components (SC) cooled fast, which were composed of α-Mg matrix and coarse long-period stacking ordered (LPSO) phases. The alloys in the large components (LC) cooled slowly, and there were thin lamellar LPSO phases precipitating inside the grains, except for α-Mg matrix and coarse LPSO phases. The hydrogen evolution test revealed that the corrosion rate of LC sample was higher than that of SC sample. Electrochemical impedance spectroscopy (EIS) test showed that the surface film on LC alloys provided worse protection. The corrosion morphologies indicated that the precipitation of the thin lamellar LPSO phases in LC sample caused severe micro-galvanic corrosion, which accelerated the rupture of the surface film.     

基于PMU的电力系统监控体系结构优化设计

文中提出了一种利用有限数量的相量测量单元(PMU)和相量数据集中器(PDC)设计最优监控结构的方法。通过在大量的设定值场景下,使电力系统可观测性曲线的期望值最大化,同时使通信基础设施成本最小化,最终确定PMU和PDC的最佳位置。提出了一种非线性动态扩展卡尔曼滤波(EFK)状态观测器。这种状态观测器可以将暂态行为转换为由代数微分方程描述的广域电力系统,而无需非线性反演技术。最后以IEEE-5电力系统为例,说明了该方法的有效性。     

建筑工业化发展的多群体演化博弈与仿真研究

新型建筑工业化具有高质量、低消耗、可循环发展等特征，其推广已上升到国家战略层面。利用演化博弈方法，建立“政府-开发商-银行” 的三方动态演化博弈模型，进行各博弈主体策略的演化稳定性分析，并针对初始状态、奖惩力度、借贷风险和开发成本等对演化结果的影响进行动态仿真。在此基础上， 考虑开发商群体的网络拓扑特征对演化真实性的影响，引入复杂网络理论， 以无标度网络为载体描述开发商个体的连接偏好和决策机制，构建政府监管下的建筑工业化扩散模型，并通过仿真深入研究相关因素对扩散深度的影响作用，最后结合仿真结果给出相应对策建议。     

Iron-based sulfur and nitrogen dual doped porous carbon as durable electrocatalysts for oxygen reduction reaction

The widespread use of fuel cell technology is hampered by the use of expensive and scarce platinum metal in electrodes which is required to facilitate the sluggish oxygen reduction reaction (ORR). In this work, a viable synthetic approach was developed to prepare iron-based sulfur and nitrogen dual doped porous carbon (Fe@SNDC) for use in ORR. Benzimidazole, a commercially available monomer, was used as a precursor for N doped carbon and calcined with potassium thiocyanate at different temperatures to tune the pore size, nitrogen content and different types of nitrogen functionality such as pyridinic, pyrrolic and graphitic. The Fe@SNDC–950 with high surface area, optimum N content of about 5 at% and high amount of pyridinic and graphitic N displayed an onset potential and half-wave potential of 0.98 and 0.83 V vs RHE, respectively, in 0.1 M KOH solution. The catalyst also exhibits similar oxygen reduction reaction performance compared to Pt/C (20 wt%) in acidic media. Furthermore, when compared to commercially available Pt/C (20 wt%), Fe@SNDC–950 showed enhanced durability over 6 h and poison tolerance in case of methanol crossover with the concentration up to 3.0 M in oxygen saturated alkaline electrolyte. Our study demonstrates that the presence of N and S along with Fe-N moieties synergistically served as ORR active sites while the high surface area with accessible pores allowed for efficient mass transfer and interaction of oxygen molecules to the active sites contributing to the ORR activity of the catalyst.     

基于NR-Transformer的集群作业运行时间预测

高性能集群的作业调度通常使用作业调度系统来实现，准确填写作业运行时间能在很大程度上提升作业调度效率。现有的研究通常使用机器学习的预测方式，在预测精度和实用性上还存在一定的提升空间。为了进一步提高集群作业运行时间预测的准确率，考虑先对集群作业日志进行聚类，将作业类别信息添加到作业特征中，再使用基于注意力机制的NR-Transformer网络对作业日志数据建模和预测。在数据处理上，根据与预测目标的相关性、特征的完整性和数据的有效性，从历史日志数据集中筛选出7维特征，并按作业运行时间的长度将其划分为多个作业集，再对各作业集分别进行训练和预测。实验结果表明，相比于传统机器学习和BP神经网络，时序神经网络结构有更好的预测性能，其中NR-Transformer在各作业集上都有较好的性能。