A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Prediction of(n,2n)reaction cross-sections of long-lived fission products based on tensor model

Interest has recently emerged in potential applications of(n,2n)reactions of unstable nuclei.Challenges have arisen because of the scarcity of experimental cross-sectional data.This study aims to predict the(n,2n)reaction cross-section of long-lived fission products based on a tensor model.This tensor model is an extension of the collaborative filtering algorithm used for nuclear data.It is based on tensor decomposition and completion to predict(n,2n)reaction cross-sections;the corresponding EXFOR data are applied as training data.The reliability of the proposed tensor model was validated by comparing the calculations with data from EXFOR and different databases.Predictions were made for long-lived fission products such as^(60)Co,^(79)Se,^(93)Zr,^(107)P,^(126)Sn,and^(137)Cs,which provide a predicted energy range to effectively transmute long-lived fission products into shorter-lived or less radioactive isotopes.This method could be a powerful tool for completing(n,2n)reaction cross-sectional data and shows the possibility of selective transmutation of nuclear waste.

BIM Improved with RV and AR Technologies

The study addresses the integration of the Building Information Modelling (BIM) methodology with Virtual Reality (VR) and Augmented Reality (AR) technologies in the context of the development of a multidisciplinary project, involving architecture, structures, water network and electrical system components. In order to cover in detail the various design features, the case study was limited to a specific area of a house, the sanitary rooms, as it presents sufficient complexity in modeling and the application of VR and AR software. The VR/AR functionalities applied over the BIM model increase the potential of BIM in the construction sector, contributing to the achievement of a high level of collaboration and control of the project based on an immersive and interactive environment. The elaboration of the different phases of a BIM design requires the transfer of models between BIM and VR/AR systems, allowing us to analyze the main advantages that BIM/VR/AR integration can introduce in the construction industry. The study contributes positively to achieving new knowledge in BIM, being disseminated in an academic research work and illustrated in a practical context.

The Collaboratory for the Study of Earthquake Predictability in China:Experiment Design and Preliminary Results of CSEP2.0

Since the inaugural international collaboration under the framework of the Collaboratory for the Study of Earthquake Predictability(CSEP)in 2007,numerous forecast models have been developed and operated for earthquake forecasting experiments across CSEP testing centers(Schorlemmer et al.,2018).Over more than a decade,efforts to compare forecasts with observed earthquakes using numerous statistical test methods and insights into earthquake predictability,which have become a highlight of the CSEP platform.

A Biogas Production Model from the Combination of Pig Manure and Cow Dung in N’Zérékoré City, Republic of Guine

This present research work focuses on the valorization of pig droppings for production of biogas in mono digestion and co-digestion with proportions of cow dung from the urban commune of N’Zérékoré. It was carried out in December 2020 in the Physics laboratory of the University of N’Zérékoré. The anaerobic digestion process took 25 days in an almost constant ambient temperature of 25˚C. Five digesters were loaded on 12/06/2020, two of which with 1 kg of pig dung and 1 kg of cow dung both in mono-digestion. The 3 other digesters in co-digestion with different proportions of pig manure and cow dung. The substrate in each digester is diluted in 2 liters of water, with a proportion of (1/2). The main results obtained are: 1) the evolution of the temperature and pH during digestion process, 2) the average biogas productions 0.61 liters for (D1);1.20 liter for (D2);1.65 liter for (D3);1.51 liter for (D4) and 1.31 liter for (D5). The cumulative amounts of biogas are respectively: D1 (7.95 liters), D2 (15.60 liters), D3 (21.50 liters), D4 (19.65 liters) and D5 (17.05 liters). The total cumulative production is 81.75 liters at the end of the process. The originality of this research work is that the proposed model examines the relation between the daily biogas production and the variation of temperature, pH and pressure. The combustibility test showed the biogas produced during the first week was no combustible (contains less than 50% methane). Combustion started from the biogas produced from the 15th day and it is from the 20th day that a significant amount of stable yellow/blue flame was observed. The results of this study show the combination of pig manure and cow dung presents advantages for optimal biogas production.

Heterogeneity in song rates in the Collared Flycatcher(Ficedula albicollis)explained with the availability parameter in generalized N-mixture models:Its importance for abundance estimates in avian aural counts

Binomial N-mixture models are commonly applied to estimate abundance unaffected by imperfect detection,but are known to be sensitive to violations of assumptions.One of the model’s assumptions,the independence of detections has rarely been tested.It requires that during a survey,detection of one individual does not affect detection of another individual.This assumption can be frequently violated in passerine birds,which exhibit territorial behaviour by singing,since neighbouring individuals are likely to motivate each other to vocalize,leading to non-independence in singing activity and in the following detection rate.Here,we explored this phenomenon with the generalized,binomial version of the N-mixture model,where detection probability is decomposed into availability probability φ-which can be interpreted as per capita song rate or the probability of vocalising-and actual detection probability p,given vocalisations take place.Using repeated counts of the Collared Flycatcher(Ficedula albicollis)as a case study,and treating the maximum observed counts C_(maxi) at a site i as an explanatory covariate for φ,we showed that per capita song rates increased with observed counts at a site.Hence,if song rates vary due to local abundance,including C_(maxi)as an explanatory variable for song rate addressed with φ,helps to explain this variation(which otherwise goes undetected)and improves inferences under the model.This had strong effects on the resulting abundance estimates:if this relationship was ignored in the models,total estimated population sizes were consequently lower by as much as 22-27%,compared to when this effect was included.Since it is likely that song rates may commonly be density-dependent in birds manifesting territorial behaviours by singing,further tests addressing violations of independence assumptions in these models are needed.As suggested by Kery and Royle(2016),despite some form of circularity likely being involved,modelling heterogeneity in the detection process with the help of C_(maxi)in standard N-mixture models(which,given availability,conflate availability with detection in a single parameter)should be applicable as well.

高压管汇材料疲劳性能测试及P-S-N模型曲线的拟合

高压管汇作为压裂设备中的主要易损件之一,其失效危害较大。它的失效原因主要是疲劳、冲蚀、腐蚀或者材料缺陷引起的刺漏和爆裂,其中尤以疲劳失效最不可预估。目前,对于高压管汇材料的疲劳性能研究不够深入,为解决高压管汇材料疲劳寿命的准确描述问题,以某国产高压管汇材料为例,进行了一系列疲劳试验,并基于试验数据,采用多种分布模型和不同S-N模型进行拟合分析,得出综合评价拟合能力最强的P-S-N模型。结果表明,该材料在中长疲劳寿命区,Weibull三参数模型在7级应力水平下综合评价能力最好;在存活率分别为50%、90%、99%、99.9%时,指数S-N模型的拟合系数均大于0.98,拟合能力最好。得出的P-S-N模型曲线可以为高压管汇的疲劳寿命以及安全设计提供依据。

基于新型“1+X+N”人才培养模式的一流本科课程建设探索

为了适应时代的发展需求,响应国务院提出的在应用型本科高校启动“学历证书+若干职业技能等级证书”制度(即“1+X”证书制度)的试点工作,民办本科院校积极探索“1+X+N”人才培养新模式。在人才培养新模式下,省级一流本科课程光纤通信技术课程组从明确课程定位、推动教学改革、加大资源建设、优化教学内容与实施过程、推进课程思政、改善课程成绩评定等方面开展工作,努力提升学生在光纤通信方面的综合应用能力,培养出满足新时代通信发展需求的高质量人才。

N-Calculator与NUFER耦合模型和组合预测法在食物氮足迹研究中的应用

为改善传统N-Calculator模型的局限性,加强食物氮足迹核算结果与环境影响的联系,提高活性氮管理预见性,将N-Calculator模型与食物系统养分流动(Nutrient Flows in Food Chains,Environment and Resources Use,NUFER)模型进行耦合,以估算我国2001—2020年人均食物氮足迹,建立组合预测体系。结果显示:2001—2020年,我国人均食物氮足迹由16.04 kg N/a增至18.95 kg N/a;全国食物氮足迹由20.47 Mt N/a增至26.76 Mt N/a;居民饮食结构正由以植物源食物为主的低氮消费模式转向以动物源食物为主的高氮消费模式;食物生产过程产生的活性氮的最终归宿为大气(64.3%)、水体和深层土壤(35.7%);我国食物氮足迹与人均可支配收入、城市化率、动物源食物消费氮占比呈正相关性,与恩格尔系数呈负相关性;未来10 a我国人均食物氮足迹呈增长趋势,预测结果显示年均增幅为0.16 kg N/a。

陆地高分辨率水文—生物地球化学过程CNMM-DNDC三维模型的研发及应用进展

CNMM-DNDC模型是本文作者团队研发的陆地高分辨率水文—生物地球化学过程三维模型。本文系统介绍了建模背景和理念、核心过程和模型特点、模拟功能和观测验证、多尺度区域或流域初步应用以及未来发展展望。自2018年刊发首个版本以来,该模型经过了多方面科学过程改进和模拟功能扩展,在元素化学反应、物质相变和机械迁移等基本物理、化学、生物过程层面,完成了对陆地表层系统碳氮磷水循环全耦合的精细刻画。迄今开展的观测验证表明,CNMM-DNDC模型基本普适于不同生物气候带(从热带到寒区多年冻土地带)的流域或区域长时间序列“三高”(时间、空间和过程高分辨率)综合模拟,实现对陆地生态系统的碳、氮、磷、水三维运移、水土流失、水力驱动溶解态和颗粒态碳氮磷横向迁移、碳氮温室气体和污染气体排放、生态系统生产力、水分蒸散发和水分能量平衡等众多可持续发展目标表征变量的预测。该模型广泛推广应用于多尺度区域或流域的复杂过程虚拟科学试验研究和服务于面向生态环境建设与减污降碳的优化调控决策,可望为协同落实联合国多个可持续发展目标提供先进的数值模拟技术支撑。

基于自适应AR模型巡航飞行参数预测研究

为更准确实现飞行参数趋势预测,提出一种基于自适应自回归(AR)模型的稳定巡航飞行参数预测方法。根据稳定巡航参数筛选条件,获取建模所需飞行参数。利用卡尔曼滤波原理估计AR模型参数,并与飞行参数构建系统方程,利用无迹卡尔曼滤波实时更新、修正AR模型参数估计值,将自适应AR模型的预测值与曲线拟合模型和灰色模型的预测值进行对比。以波音B777-300ER飞机的快速存取记录器数据样本进行仿真验证,结果表明:自适应AR模型在数据预测和收敛速率方面均更优,可有效降低预报模型随步数增加导致的精度误差,提高参数预测准确性。研究在飞机维修保障、状态监控与预测等方面具有重要作用。

基于改进N-K模型的地铁盾构掘进安全风险耦合研究

为预防和控制地铁盾构掘进施工过程中的关键安全风险,并精准判断哪些风险耦合情境是导致事故发生的显著情境,提出改进N-K模型研究地铁盾构掘进安全风险耦合;综合运用文献研究、事故案例、专家访谈等方法,辨识地铁盾构掘进的关键安全风险因素;基于N-K模型提出新的地铁盾构掘进安全风险耦合评估模型,并选用安全事故案例验证该模型的适用性。结果表明:辨识得到地铁盾构掘进关键安全风险因素清单,包括4类一级风险因素,21个二级风险因素;地铁盾构掘进施工安全风险随着耦合因素种类的增加而变大,4因素风险耦合值最高,3因素风险耦合值次之,双因素风险耦合值最低,作业人员安全意识薄弱和机械故障参与作用的耦合情境更容易发生安全事故。

基于D3AR的半球共形阵低空风切变风速估计方法

针对半球共形阵体制下进行低空风切变检测时会受到强地杂波信号的干扰,导致风切变信号难以检测的问题,提出了一种基于空时自回归的直接数据域算法(Space-Time Autoregressive Direct Data Domain,D3AR)的低空风切变风速估计方法。该方法首先将待检测距离单元的数据从空域、时域以及空时域进行信号对消处理;然后将处理后的数据矩阵描述为空时自回归(Autoregression,AR)模型并估计模型参数;再通过构造与杂波子空间正交的空间来实现对杂波的抑制,最后通过提取待检测单元的最大多普勒频率来估计风场速度。根据仿真结果显示,该方法有效地实现了地杂波抑制,并且能够精确估计风速。

基于MS(2)-AR-TVTP模型的I_(BD)波动周期非对称性和持续性分析

国际干散货运输市场源于国际贸易的衍生需求,受世界经济的影响,是一个典型的周期性市场。选取1999年11月~2021年12月的波罗的海干散货运价指数(I_(BD))月度数据,在检验序列平稳性的基础上,确定最优滞后长度,构建两区制的时变转换概率马尔科夫转换自回归模型,分析I_(BD)波动周期的持续时间、转换拐点和非对称性等主要特征。研究结果表明:模型能有效拟合I_(BD)波动周期的主要特征,周期平均持续时间为33.7个月,自2008年9月之后呈缩短态势,上升期和下降期交互更频繁;I_(BD)波动周期具有非对称性,周期内上升期持续时间比下降期长,I_(BD)维持上升期更具有稳定性。周期性特征结果可为干散货航运业造船投资和市场经营提供决策依据。

基于AR-ECM平均差异模型的串联电池组SOC、容量多尺度联合估计方法

考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM)。基于此模型,提出串联电池组SOC、容量多尺度联合估计算法。该算法由2个部分组成,一是基于AR-ECM的MDM及差异化模型参数辨识策略:条件辨识策略和定频分组辨识策略;二是基于多时间尺度H无穷滤波(multi-timescale H infinity filter,Mts-HIF)的电池组SOC、容量联合估计算法。通过将所提出MDM中的自回归平均模型(autoregression mean model,AR-MM)与传统MDM中的n阶RC平均模型(nRC mean model,nRC-MM)比较,结果表明所提出的AR-MM在复杂运行工况下具有更优的动态跟随性能。依据最小化信息量准则(akaike information criterion,AIC),AR-MM具有更优的复杂度与精度的权衡。通过与基于多时间尺度扩展卡尔曼滤波(multi-timescale extended Kalman filter,Mts-EKF)联合状态估计算法比较,结果表明所提出的Mts-HIF状态估计算法具有更优的鲁棒性、精度和收敛速度。

基于DEMATEL/N-K的机坪管制系统运行风险因素耦合分析

为了分析机坪管制系统风险因素的耦合性,将决策实验室分析(DEMATEL)模型与N-K模型相结合形成新的风险因素耦合分析模型。首先,利用N-K模型对2017—2019年机坪管制运行不安全事件进行耦合分析,计算不同耦合方式的耦合值;然后,利用DEMATEL模型计算安全风险因素的影响度和被影响度,确定要素的中心度排序,通过DEMATEL模型得到的综合影响矩阵计算可达矩阵,用来分析风险因素的可达性,最后,利用风险因素耦合值对各风险节点的中心度进行修正,获得关键的风险因素。基于实际运行数据,通过DEMATEL/N-K模型分析机坪管制系统的关键风险因素。结果表明,人为因素和机械因素之间的耦合程度明显更高,即更容易导致事故的发生,其中地面保障人员操作出错或未有效观察航空器造成航空器或地面保障设备故障是重点防控的对象。此外,在夜晚或雨天等视线条件下工作,更容易发生不安全事件,应当采取措施控制此类风险。

融合N-K模型的复杂网络船舶自沉事故风险因素耦合分析

为定量分析船舶自沉风险因素间的影响关系,识别导致船舶自沉事故的关键因素,科学预防事故的发生,引入融合N-K模型的复杂网络研究船舶自沉事故风险耦合。首先结合中国海事局公布的136起船舶自沉事故案例,分析事故致因,将船舶自沉事故风险因素归纳为4个一级风险因素和15个二级风险因素,运用N-K模型计算出一级风险因素风险耦合的发生概率和风险值;然后,以二级风险因素为节点、致因关联为边,构建危险因子的关联网络,通过风险可达性分析和网络节点中心度分析,探究危险因子的作用机制,对危险因子进行初步识别,并以N-K模型计算的耦合值对节点中心度进行改进,获得最终的关键风险因素;最后,挖掘船舶自沉事故致因网络的凝聚子群并进行分析,得到密度矩阵,确定风险关联性最强的二级风险因素,以期从事故源头上采取有效措施,为船舶自沉事故的科学预防提供有益参考。结果表明:船舶自沉事故的发生与风险耦合值成正比,耦合因素越多则风险值越大;人的因素和船舶因素风险耦合易导致船舶自沉事故;导致船舶自沉事故的关键风险因素为安全意识淡薄、公司未履责、船舶管理不到位、公司管理不到位、船舶故障、船舶不适航,其中安全意识淡薄与其他风险关联性最大,须重点防范。

Perceptual video coding method based on JND and AR model

In order to achieve better perceptual coding quality while using fewer bits, a novel perceptual video coding method based on the just-noticeable-distortion （JND） model and the auto-regressive （AR） model is explored. First, a new texture segmentation method exploiting the JND profile is devised to detect and classify texture regions in video scenes. In this step, a spatial-temporal JND model is proposed and the JND energy of every micro-block unit is computed and compared with the threshold. Secondly, in order to effectively remove temporal redundancies while preserving high visual quality, an AR model is applied to synthesize the texture regions. All the parameters of the AR model are obtained by the least-squares method and each pixel in the texture region is generated as a linear combination of pixels taken from the closest forward and backward reference frames. Finally, the proposed method is compared with the H.264/AVC video coding system to demonstrate the performance. Various sequences with different types of texture regions are used in the experiment and the results show that the proposed method can reduce the bit-rate by 15% to 58% while maintaining good perceptual quality.

医学院校思政课“1+3+N”教学实践探析

“1+3+N”教学模式围绕医学院校特色、医学专业和医学生特点,基于移动互联技术,坚持以学生为中心,有机融合网络教学、课堂教学和实践教学3种集中教学形式,辅以N种分散教学形式,实现思政课与医学生医学梦的同频共振。学生通过网络课堂预习基本知识点,教师在课堂教学中着重讲解重难点并解答学生预习遇到的问题,学生通过实践教学把所学理论知识内化于心、外化于行。小班讨论等N种分散教学形式旨在培养学生听、读、看、写、讲、行能力。“1+3+N”教学模式弥补了传统灌输式授课方式的短板,调动了医学生学习思政课的积极性和主动性。影响该教学模式实践效果的因素包括学校网络教学基础设施和信息化教学设备情况、师生相关技术掌握情况、网络教学管理情况、网络教学和课堂教学衔接情况、实践教学组织实施情况等,针对这些影响因素,采取相应优化策略,以提升教学效果。