Transcriptomic and proteomic studies of condylar ossification of the temporomandibular joint in porcine embryos

Background:The ossification mechanism of the temporomandibular joint(TMJ)condyle remains unclear in human embryo.The size and structure of TMJ,shape of articular disc and the characteristics of omnivorous chewing in the pig are similar to those of humans.The pig is an ideal animal for studying the mechanism of ossification of the TMJ condyle during the embryonic period.Method:In a previous study by our group,it was found that there was no condylar ossification on embryonic day(E)45,but the ossification of condyle occurred between E75 and E90.In this study,a total of 12 miniature pig embryos on E45 and E85 were used.Six embryos were used for tissue sections(3 in each group).The remaining six embryos were used for transcriptomic and proteomic studies to find differential genes and proteins.The differentially expressed genes in transcriptome and proteomic analysis were verified by QPCR.Results:In total,1592 differential genes comprising 1086 up-regulated genes and 506 down-regulated genes were screened for fold changes of≥2 to≤0.5 between E45 and E85.In the total of 4613 proteins detected by proteomic analysis,there were 419 differential proteins including 313 up-regulated proteins and 106 down-regulated proteins screened for fold changes of≥2 to≤0.5 between E45 and E85.A total of 36 differential genes differing in both transcriptome and proteome analysis were found.QPCR analysis showed that 14 of 15 selected genes were consistent with transcriptome analysis.Conclusion:Condylar transcriptome and proteomic analysis during the development of TMJ in miniature pigs revealed the regulatory genes/proteins of condylar ossification.

Study on Ability of Ground Cover Plant of Taiyuan to Adsorb PM(2.5)

Four ground cover plant species of Taiyuan（ Iris,Hemerocallis,Sedum,Hosta） were selected to study their capacities in adsorbing PM（2.5）. Meanwhile,the concentration of PM（2.5） in Taiyuan between April 2017 and August 2017 was recorded,and the characteristics of PM（2.5） pollution in summer and autumn in Taiyuan were studied. The results showed that for the 4 plants,the ability to adsorb PM（2.5） was in the order from great to small of Hosta,Iris,Hemerocallis,Sedum,in which H. plantaginea had the best effect to adsorb PM（2.5）. The fresh weight and dry weight per gram of H. plantaginea were 4. 4 times and 2 times higher than those of S. spectabile,while the mass quality of dust adsorption was 2.8 times higher. The sorting result was the same as the ability to adsorb PM（2.5） of unit leaf area. The result of the coefficient of purification showed that the purification coefficients of 3 vegetation structure were positive,and the combination of trees and shrubs in university campus had strong PM（2.5） adsorption capacity. By comparing the seasonal variation of PM（2.5） concentration in Taiyuan city,it found that the PM（2.5） concentration was particularly high in late spring and early summer of Taiyuan,when most of the ground cover plants were not fully grown. Therefore,ground cover plants played an important role in the construction of landscape and the regulation of ecological environment in Taiyuan.

基于改进代价敏感直推式支持向量机的发电企业滥用市场力识别

随着现货市场的加速推进,准确地实时识别滥用市场力行为是电力市场违规行为管理的一项关键性任务。将改进的支持向量机与变分不等式求解算法结合,实现了在只有少量发电企业有标签数据情形下仍可以准确实时地识别发电企业滥用市场力行为。首先,结合电力市场实际情况,构造了滥用市场力识别指标体系,并基于电力市场高维数据的特点对数据进行降维。其次,针对发电企业有标签数据占总体数据小部分及数据不平衡的特点,提出了基于改进代价敏感直推式支持向量机的发电企业滥用市场力识别方法。然后,考虑到半监督算法求解时间较长,将求解问题转化为高效的变分不等式求解问题,并使用定制近邻法进行求解。最后,利用UCI数据集、电力市场仿真数据及实际电力市场数据进行试验。结果表明,该识别方法可以将滥用市场力的发电企业快速有效地识别出来。

An Examination of the Predictability of Tropical Cyclone Genesis in High-Resolution Coupled Models with Dynamically Downscaled Coupled Data Assimilation Initialization

Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions.

高强度螺旋钻孔压灌桩在输变电工程中的应用研究与展望

输变电工程中常采用钻孔灌注桩基础,但普通泥浆护壁钻孔灌注桩存在施工工艺繁杂、桩体混凝土质量及承载力稳定性差、泥浆护壁产生环境污染等缺点。通过对螺旋钻孔压灌桩这一新技术的施工工艺、质量评价方法、设计计算等方面进行总结,提出地聚合物高强度混凝土材料和螺旋钻孔压灌桩工艺结合的技术,并对该技术在输变电工程中的应用进行展望。

Numerical study on DPM dispersion and distribution in an underground development face based on dynamic mesh

In 2012,the International Agency for Research on Cancer(IARC)classified diesel particulate matter(DPM)as a carcinogen to human.With the increased usage of diesel equipment in underground mines,miners have a high risk of over-exposure to DPM,which has drawn many concerns from the public.This study used computational fluid dynamics(CFD)to analyse the DPM dispersion and concentration distribution characteristics in an underground development face based on an onsite experiment.The DPM emitted from a moving loader under a forcing auxiliary ventilation system was simulated.The motion of the load-haul-dump(LHD)in the tunnel was represented by a dynamic mesh method.The species transport approach was applied to study the DPM behaviours.High DPM concentration zones were then identified based on the simulation results.The results could provide guidelines for work practices and be helpful to an optimum auxiliary ventilation design to reduce underground miner exposure.

基于5G边缘计算的可调节负荷互动技术研究

将云计算与边缘计算系统集成应用于可调节负荷互动技术,可以在分布式体系结构中实现安全、可靠、高效的可调节负荷互动服务。针对第五代通信技术(5G)时代将有更多的需求响应(DR)终端接入可调节负荷的现状,通过分析边缘计算系统使用5G资源的方式,提出可根据不同的可调节负荷互动业务采用不同的5G切片传输方式。将可调节负荷互动的网络架构分为用户层、网络层、服务层,基于该架构提出了可调节负荷互动策略库动态加载模型,最后对未来可调节负荷互动信息物理融合发展提出了建议。

基于随机森林的变压器局部放电模式识别

针对目前在局部放电模式识别领域中常用的分类器算法的缺陷,本文研究随机森林(random forest,RF)算法在局部电放模式识别领域的应用。首先对局部放电试验数据提取统计特征量,构建放电的学习样本。利用十折法对算法分类性能进行评判,并比较常见分类算法BP神经网络、支持向量机(support vector machine,SVM)、KNN、分类回归树算法(classification and regression tree,CART)以及RF算法的识别准确率。结果表明:利用RF算法构建放电模式分类器的识别准确率最高。此外,利用组成RF的基分类算法CART可分析不同放电模式间的主要区别。

基于大规模的风电并网稳定性仿真研究

针对大规模的风电并网稳定性WPGS问题进行研究。利用电力系统分析综合程序PSASP软件,对并入电网后的风电场系统稳定性指标,如节点电压水平和UQ灵敏度进行了仿真研究。采用EPRI-36节点的分布式电网系统,在考虑风电场装机容量、电网电压等级和接入位置等因素条件下,应用PSASP软件对其稳定性进行了仿真,分别从电压水平、灵敏度和PV曲线3个方面进行了研究。仿真结果表明,当这3种因素情况不同时,会产生不同的稳定性问题,所得结论基本与实际相符,从而验证了其仿真的正确性。

影响光伏功率输出因素的研究与分析

本文分析了光伏电站输出功率的影响因素,重点讨论了光伏系统自身电气参数以及气象要素中的辐照度、天气状况、温度和季节对光伏发电量的影响。通过对某30MW光伏电站的历史发电功率数据进行分析整理,得出了相应的结论。该结论也为预测发电功率的输入样本的选取提供了理论基础。

换流阀低压加压试验方法与研究

依据±800kV特高压直流输电工程系统结构和接线方式,结合换流站实际运行方式,对换流阀低压加压试验方法和试验数据进行探讨和研究。提出使用输出为0~400V感应调压变压器进行低压调节和15kV/0.4kV试验升压变压器组成换流变升压电源,通过从换流变交流侧输入电压,直流侧对换流阀进行加压,模拟控制保护系统在低电压、低电流的整组试验,提高了换流阀低压加压的试验效率和准确性,为后续新建换流站低压加压试验提供了一定的试验依据。

串联隔震结构的抗连续倒塌性能

以某工程串联隔震结构为工程背景,对串联隔震结构进行抗连续倒塌性能研究.采用非线性有限元软件MSC.Marc建立该串联隔震结构精细化有限元模型,运用非线性动力拆除构件法研究该结构,并根据DOD2013所提出结构连续倒塌的失效准则进行评价.研究结果表明:串联隔震结构角柱区域为整个结构抗连续倒塌性能最薄弱环节,隔震层角柱和角柱隔震垫需进行加强和保护;随着楼层的增高,串联隔震结构抗连续倒塌性能逐渐变差.

A high-resolution Asia-Pacific regional coupled prediction system with dynamically downscaling coupled data assimilation

A regional coupled prediction system for the Asia-Pacific(AP-RCP)(38°E-180°,20°S-60°N) area has been established.The AP-RCP system consists of WRF-ROMS(Weather Research and Forecast,and Regional Ocean Model System) coupled models combined with local observational information through dynamically downscaling coupled data assimilation(CDA).The system generates 18-day forecasts for the atmosphere and ocean environment on a daily quasi-operational schedule at Pilot National Laboratory for Marine Science and Technology(Qingdao)(QNLM),consisting of 2 different-resolution coupled models:27 km WRF coupled with 9 km ROMS,9 km WRF coupled with 3 km ROMS,while a version of 3 km WRF coupled with 3 km ROMS is in a test mode.This study is a first step to evaluate the impact of high-resolution coupled model with dynamically downscaling CDA on the extended-range predictions,focusing on forecasts of typhoon onset,improved precipitation and typhoon intensity forecasts as well as simulation of the Kuroshio current variability associated with mesoscale oceanic activities.The results show that for realizing the extended-range predictability of atmospheric and oceanic environment characterized by statistics of mesoscale activities,a fine resolution coupled model resolving local mesoscale phenomena with balanced and coherent coupled initialization is a necessary first step.The next challenges include improving the planetary boundary physics and the representation of air-sea and air-land interactions to enable the model to resolve kilometer or sub-kilometer processes.

新组合模型在光电功率预测中的应用

为提高光伏预测要求的精准性,文章提出一种新算法将神经网络和ARMA算法改进组合,构成NEW ARMA-BP模型算法.以某30兆瓦的光伏电站采集的输出功率为输入样本,基于ARMA和BP神经网络算法在Matlab环境下依次搭建了相应的预测模型,预估光伏短期输出量.采用"误差正态检验图"判断基于两种不同算法的误差水平,依据两种单模型预测误差,运用所提出的新方法计算权值并获得新的预测值.基于Matlab的仿真结论验证了组合预测在光伏输出预测领域的适用性.