Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Tensor Decomposition-Based Channel Estimation and Sensing for Millimeter Wave MIMO-OFDM V2I Systems

An integrated sensing and communication(ISAC)scheme for a millimeter wave(mmWave)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)Vehicle-to-Infrastructure(V2I)system is presented,in which both the access point(AP)and the vehicle are equipped with large antenna arrays and employ hybrid analog and digital beamforming structures to compensate the path loss,meanwhile compromise between hardware complexity and system performance.Based on the sparse scattering nature of the mmWave channel,the received signal at the AP is organized to a four-order tensor by the introduced novel frame structure.A CANDECOMP/PARAFAC(CP)decomposition-based method is proposed for time-varying channel parameter extraction,including angles of departure/arrival(AoDs/AoAs),Doppler shift,time delay and path gain.Then leveraging the estimates of channel parameters,a nonlinear weighted least-square problem is proposed to recover the location accurately,heading and velocity of vehicles.Simulation results show that the proposed methods are effective and efficient in time-varying channel estimation and vehicle sensing in mmWave MIMOOFDM V2I systems.

A Survey on Deep Learning-Based 2D Human Pose Estimation Models

In this article,a comprehensive survey of deep learning-based(DLbased)human pose estimation(HPE)that can help researchers in the domain of computer vision is presented.HPE is among the fastest-growing research domains of computer vision and is used in solving several problems for human endeavours.After the detailed introduction,three different human body modes followed by the main stages of HPE and two pipelines of twodimensional(2D)HPE are presented.The details of the four components of HPE are also presented.The keypoints output format of two popular 2D HPE datasets and the most cited DL-based HPE articles from the year of breakthrough are both shown in tabular form.This study intends to highlight the limitations of published reviews and surveys respecting presenting a systematic review of the current DL-based solution to the 2D HPE model.Furthermore,a detailed and meaningful survey that will guide new and existing researchers on DL-based 2D HPE models is achieved.Finally,some future research directions in the field of HPE,such as limited data on disabled persons and multi-training DL-based models,are revealed to encourage researchers and promote the growth of HPE research.

Exploration on 2D DOA Estimation of Linear Array Motion:Uniform Linear Motion

Generally,due to the limitation of the dimension of the array aperture,linear arrays cannot achieve two-dimensional(2D)direction of arrival(DOA)estimation.But the emergence of array motion provides a chance for that.In this paper,a generalized motion scheme and a novel method of 2D DOA estimation are proposed by exploring the linear array motion.To be specific,the linear arrays are controlled to move along an arbitrary direction at a constant velocity and snap per fixed time delay.All the received signals are processed to synthesize the comprehensive observation vector for an extended 2D virtual aperture.Subsequently,since most of 2D DOA estimation methods are not universal to our proposed motion scheme and the reduced-dimensional(RD)method fails to handle the case of the coupled parameters,a decoupled reduced-complexity multiple signals classification(DRC MUSIC)algorithm is designed specifically.Simulation results demonstrate that:a)our proposed scheme can achieve underdetermined 2D DOA estimation just by the linear arrays;b)our designed DRC MUSIC algorithm has the good properties of high accuracy and low complexity;c)our proposed motion scheme with the DRC method has better universality in the motion direction.

2-D distributed pose estimation of multi-agent systems using bearing measurements

This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.

“双碳”目标下火电厂CO_(2)计量技术研究现状与展望

中国电力行业CO_(2)排放量是CO_(2)排放的主要来源,其中火电厂CO_(2)排放量在电力行业中占比最大。在“双碳”目标下,CO_(2)计量技术可以实现对火电厂中CO_(2)排放量的直观判断,为火电厂CO_(2)减排提供重要支撑,促进火电厂参与碳交易,带动区域经济发展。结合国内外政策,讨论了目前通用CO_(2)计量方法的实施进展,总结归纳了以碳核算为主、碳监测为辅的火电厂CO_(2)计量方法存在的问题,并对火电厂CO_(2)计量技术应用的重难点进行了分析。最后,对火电厂CO_(2)计量技术的发展及应用进行了展望。

Constrained least squares algorithm for channel vector estimation in 2-D RAKE receiver

Based on the fact that the variation of tile direction of arrival (DOA) isslower than that of the channel fading, the steering vector of the desired signal is estimatedfirstly using a subspace decomposition method and then a constrained condition is configured.Traffic signals are further employed to estimate the channel vector based on the constrained leastsquares criterion. We use the iterative least squares with projection (ILSP) algorithm initializedby the pilot to get the estimation. The accuracy of channel estimation and symbol detection can beprogressively increased through the iteration procedure of the ILSP algorithm. Simulation resultsdemonstrate that the proposed algorithm improves the system performance effectively compared withthe conventional 2-D RAKE receiver.

2型糖尿病患者肾功能损伤及氧合水平的BOLD MRI分析

目的 探讨采用血氧水平依赖磁共振成像(BOLD MRI)技术分析2型糖尿病(diabetes mellitus type2,T2DM)患者的估算肾小球滤过率(estimated glomerular filtration rate,eGFR)不同水平的肾缺氧改变。方法 选取T2DM患者以及同期健康正常者共78例,其中64例T2DM患者作为T2DM组,14例同期健康正常者作为对照组,均进行BOLD MRI检查。根据eGFR将64例T2DM患者又分为eGFR正常组(A组)、轻度功能损害组(B组)、中重度肾功能损害组(C组),测定肾脏髓质、皮质R2*(MR2*、CR2*)。采用单因素方差分析数据MR2*、CR2*的组间差异及其与eGFR的相关性,并采用受试者工作特征曲线(receiver operating characteristic cure, ROC)分析MR2*、CR2*值的诊断效能。结果 与对照组相比,A、B、C组MR2*、CR2*值均显著升高,差异有统计学意义(P均<0.05),均与eGFR呈正相关(P均<0.05),均可鉴别T2DM组与对照组,但MR2*值的鉴别敏感度稍高。结论 BOLD MRI可无创评估T2DM患者早期肾脏功能性缺氧改变,监测eGFR不同阶段的肾脏氧合水平,对临床治疗具有指导意义。

MRI IDEAL-IQ在2型糖尿病患者腹部脂肪量化中的应用价值

目的采用磁共振(MRI)非对称回波的最小二程估算法迭代水脂分离(IDEAL-IQ)技术评价2型糖尿病对腹部脂肪分布及内脏脂肪沉积的影响。方法前瞻性纳入温州医科大学附属第二医院29例健康志愿者(对照组)和39例2型糖尿病患者(2型糖尿病组),两组均进行3.0T磁共振IDEAL-IQ序列扫描,得到脂肪分数图像。在脂肪分数图像上测量两组右肝、椎体、两肾实质和肾窦以及胰腺的质子密度脂肪分数(PDFF)、腹腔内脂肪组织(VAT)面积和皮下脂肪组织(SAT)面积。比较两组PDFF、VAT面积和SAT面积。结果2型糖尿病组的右肝、胰腺、左肾窦、右肾窦和椎体的PDFF值均高于对照组,差异有统计学意义(均P<0.05)。2型糖尿病组的VAT面积显著大于对照组[(105.47±7.12)cm^(2)vs(81.36±6.94)cm^(2),P=0.043],而两组SAT面积差异无统计学意义(P>0.05)。在所有参与者中,VAT面积分别与右肝、胰腺、椎体、左肾窦和右肾窦PDFF呈显著正相关。结论MRI IDEAL-IQ技术可以量化成人腹部脏器及结构的脂肪情况,2型糖尿病影响患者腹部脂肪分布并导致腹腔内脏脂肪沉积。

Tribological Performance of Different Concentrations of Al_(2)O_(3)Nanofluids on Minimum Quantity Lubrication Milling

Nanofluid minimum quantity lubrication(NMQL)is a green processing technology.Cottonseed oil is suitable as base oil because of excellent lubrication performance,low freezing temperature,and high yield.Al_(2)O_(3)nanoparticles improve not only the heat transfer capacity but also the lubrication performance.The physical and chemical proper-ties of nanofluid change when Al_(2)O_(3)nanoparticles are added.However,the effects of the concentration of nanofluid on lubrication performance remain unknown.Furthermore,the mechanisms of interaction between Al_(2)O_(3)nanoparti-cles and cottonseed oil are unclear.In this research,nanofluid is prepared by adding different mass concentrations of Al_(2)O_(3)nanoparticles(0,0.2%,0.5%,1%,1.5%,and 2%wt)to cottonseed oil during minimum quantity lubrication(MQL)milling 45 steel.The tribological properties of nanofluid with different concentrations at the tool/workpiece interface are studied through macro-evaluation parameters(milling force,specific energy)and micro-evaluation parameters(surface roughness,micro morphology,contact angle).The result show that the specific energy is at the minimum(114 J/mm^(3)),and the roughness value is the lowest(1.63μm)when the concentration is 0.5 wt%.The surfaces of the chip and workpiece are the smoothest,and the contact angle is the lowest,indicating that the tribological proper-ties are the best under 0.5 wt%.This research investigates the intercoupling mechanisms of Al_(2)O_(3)nanoparticles and cottonseed base oil,and acquires the optimal Al_(2)O_(3)nanofluid concentration to receive satisfactory tribological properties.

Recursive weighted least squares estimation algorithm based on minimum model error principle

Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.

An Estimation of the Daily Intake of Di(2-ethlhexyl) Phthalate(DEHP) among Workers in Flavoring Factories

Objective To estimate the daily intake of DEHP among workers in flavoring factories. Methods 71 workers in two flavoring manufacturers, 27 administrators in those factories and 31 laboratory technicians in a research institute were recruited and assigned to exposure group, control group 1 and control group 2 respectively. Their urinary DEHP metabolites, mono（2-ethylhexyl） phthalate （MEHP）, mono-（2-ethyl-5-hydroxyhexyl） phthalate （MEHHP）, mono-（2-ethyl-5-oxohexyl） phthalate （MEOHP）, were detected by isotope dilution-ultra performance liquid chromatography-tandem mass spectrometry（UPLC-MS/MS）. The urinary metabolites concentrations were converted into DEHP intake levels using two pharmacokinetic models： the urine creatinine-excretion （UCE） one and the urine volume （UV） one. Results No significant differences were found among the three groups. Based on the urinary concentrations of Z3MEHP, we got a median daily DEHP intake of 3.22 or 1.85 μg/kg body-weight/day applying the UV or UCE models respectively. Depending on the UV model, three subjects （2.34%） exceeded the RfD value given by US EPA and the P50 of estimate daily DEHP intakes accounted for 16.10% of the RfD value. No subjects exceeded the limitation depending on the UCE model. Conclusion The workers in flavoring factories were not supposed to be the high DEHP exposure ones and their exposure level remained at a low risk.

Low Complexity Minimum Mean Square Error Channel Estimation for Adaptive Coding and Modulation Systems

Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.

Interference-Free Pilot Design and Channel Estimation Using ZCZ Sequences for MIMO-OFDM-Based C-V2X Communications

Cellular vehicle-to-everything(C-V2X) communications is regarded as a promising and feasible solution for 5G-enabled vehicular communications and networking. In this paper, we investigate the pilot design and channel estimation problem in MIMO-OFDM-based C-V2X systems with severe co-channel interference due to spectrum reusing among different V2X communication links. By using zero-correlation zone(ZCZ) sequences, we provide an interference-free pilot design scheme and a corresponding time-domain(TD) correlation-based channel estimation(TD-CCE) method. We employ the ZCZ sequences from the same family set to be designed as the TD pilot symbols and guarantee the pilot sequeneces for neighboring V2X communication links are code-division multiplexing(CDM). The co-channel pilot interference of the deisgned pilot symbols can be effectively eliminated by exploiting the provided TD-CCE method. Simulation results indicate that the accuracy of channel estimation can be effectively improved by the proposed scheme, whose performance is close to that of the non-interference situation.

一种基于ICESat-2激光光子与SRTM数据的冰川高程变化误差稳健估计方法

针对利用ICESat-2星载光子点云数据进行冰川高程变化监测时,不同地形条件下的ICESat-2激光光子数据质量差异较大导致冰川高程变化量估算误差较大的问题,本文以青藏高原上中国最大的海洋性冰川——恰青冰川为例,联合使用ICESat-2激光测高数据及30 m分辨率SRTM的DEM产品,提出了融合稳健估计准则的多函数拟合冰川高程变化量估算误差改正模型,降低了因地形坡度引起的冰川高程变化量估算误差;进而,估算了2000—2021年间恰青冰川的高程变化速度及质量变化量。结果表明,与对应的传统最小二乘估计结果相比,本文提出的融合稳健估计的函数模型改正效果更优。随后,将改正结果与多种数据进行交叉验证,能够证明该误差改正模型的有效性和可行性。因此,该模型可以有效改善冰川高程和质量变化信息提取的精度,研究结果表明,研究区21年间冰川高程变化速率约为(-0.52±0.56)m·a^(-1),冰川质量变化约为-12773.81×10^(5)t。此外,经过对21年间气象数据的年变化和月变化分析可知,气温和降水量等因素是引起冰川高程变化的主要动因。

肾小管脂滴包被蛋白2在预测糖尿病肾脏病进展中的作用及机制

目的:探讨肾小管上皮细胞中脂滴包被蛋白2(PLIN2)的表达变化能否预测糖尿病肾脏病(DKD)肾功能的减退,以及PLIN2促进DKD肾小管上皮细胞损伤的机制。方法:采用回顾性队列研究,选择12例非糖尿病患者(作为对照)和51例DKD患者为研究对象,收集人口学及实验室检查等资料。采用简化线性混合效应模型获得估算的肾小球滤过率(eGFR)斜率,Spearsman相关分析和广义线性模型预测PLIN2与DKD患者肾功能减退的关系。体内实验采用BKS-db/db小鼠和链脲佐菌素构建的糖尿病小鼠模型。体外实验采用葡萄糖处理原代肾小管上皮细胞,转染PLIN2 siRNA或过表达质粒。蛋白免疫印迹和免疫荧光染色检测PLIN2表达,油红染色检测脂滴蓄积,细胞实时能量代谢分析仪检测线粒体氧消耗率(OCR)。结果:DKD患者肾小管中的PLIN2表达水平较对照显著升高。随访24 (12,39)个月,DKD患者的eGFR斜率为-7.42(-19.77,-2.09) mL/(min·1.73 m^(2)·year)。基线时肾小管PLIN2阳性面积百分比的增大与随访期内eGFR斜率的变化显著相关[风险比(HR)=1.90,95%置信区间(CI):1.00~3.58],提示肾小管PLIN2预测DKD肾功能减退的价值。糖尿病小鼠模型肾小管中的脂滴和PLIN2表达均较对照组显著增多,葡萄糖处理造成肾小管上皮细胞中脂滴蓄积和PLIN2表达增多。干扰PLIN2显著缓解葡萄糖引起的脂滴蓄积;反之,过表达PLIN2加重葡萄糖引起的脂滴蓄积。葡萄糖处理造成肾小管上皮细胞线粒体OCR的下降在干扰PLIN2后得到缓解;然而,过表达PLIN2直接造成线粒体OCR降低。结论:肾小管PLIN2能预测DKD患者肾功能的减退。PLIN2抑制线粒体有氧呼吸,参与肾小管上皮细胞的脂滴蓄积和DKD的进展。

Winter wheat yield estimation based on assimilated Sentinel-2 images with the CERES-Wheat model

Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale. To verify this method, we applied the ensemble Kalman filter(EnKF) to assimilate the leaf area index(LAI) derived from Sentinel-2 data and simulated by the CERES-Wheat model. From this, we obtained the assimilated daily LAI during the growth stage of winter wheat across three counties located in the southeast of the Loess Plateau in China: Xiangfen, Xinjiang, and Wenxi. We assigned LAI weights at different growth stages by comparing the improved analytic hierarchy method, the entropy method, and the normalized combination weighting method, and constructed a yield estimation model with the measurements to accurately estimate the yield of winter wheat. We found that the changes of assimilated LAI during the growth stage of winter wheat strongly agreed with the simulated LAI. With the correction of the derived LAI from the Sentinel-2 images, the LAI from the green-up stage to the heading–filling stage was enhanced, while the LAI decrease from the milking stage was slowed down, which was more in line with the actual changes of LAI for winter wheat. We also compared the simulated and derived LAI and found the assimilated LAI had reduced the root mean square error(RMSE) by 0.43 and 0.29 m^(2) m^(–2), respectively, based on the measured LAI. The assimilation improved the estimation accuracy of the LAI time series. The highest determination coefficient(R2) was 0.8627 and the lowest RMSE was 472.92 kg ha^(–1) in the regression of the yields estimated by the normalized weighted assimilated LAI method and measurements. The relative error of the estimated yield of winter wheat in the study counties was less than 1%, suggesting that Sentinel-2 data with high spatial-temporal resolution can be assimilated with the CERES-Wheat model to obtain more accurate regional yield estimates.

司美格鲁肽和度拉糖肽治疗2型糖尿病的疗效与安全性比较:基于倾向性评分匹配的回顾性队列研究

目的探究司美格鲁肽对比度拉糖肽治疗2型糖尿病的疗效和安全性。方法采用多中心、回顾性队列研究设计,选择2021年4月—2023年7月在3家医院就诊的2型糖尿病患者为研究对象。根据用药情况分为司美格鲁肽组(以下简∶称“SEMA组”)、度拉糖肽组(以下简称“DULA组”),并根据基线性别、年龄、身体质量指数、血糖水平、糖尿病病程及并发症等,采用倾向性评分匹配法对2组患者进行1观察治疗后3、6、9、12个月的空腹血糖、餐后2 h血糖、糖化血红蛋白(HbA1c)、血肌酐、尿素氮、估算肾小球滤过率(eGFR)、尿白蛋白/肌酐比值(UACR)及不良反应的发生情况。结果倾向性评分匹配后,SEMA组和DULA组各纳入98例患者,2组患者的基线特征差异无统计学意义(P>0.05)。2组各随访时点的空腹血糖、餐后2 h血糖、HbA1c均较基线明显降低(P≤0.05)。2组各随访时点空腹血糖、餐后2 h血糖、HbA1c变化(各随访时点与基线差值)差异无统计学意义(P>0.05);第6个月时,SEMA组HbA1c<7%的比例高于DULA组(P<0.05)。相较于基线,SEMA组第6个月时血肌酐和尿素氮下降,第3、6个月时eGFR升高、UACR降低,差异均有统计学意义(P<0.05);DULA组第3、6个月时血肌酐升高、eGFR下降,第9个月时尿素氮下降,差异均有统计学意义(P<0.05)。第3、6个月时,SEMA组血肌酐较基线的降幅大于DULA组,SEMA组eGFR较基线的升幅大于DULA组,差异均有统计学意义(P<0.05);第6个月时,SEMA组UACR较基线的降幅大于DULA组,SEMA组肾功能不全比例低于DULA组,差异均有统计学意义(P<0.05)。2组不良反应发生率差异无统计学意义(P>0.05)。结论司美格鲁肽和度拉糖肽均可显著改善血糖控制效果,总体降糖效果相似,安全性相当,而司美格鲁肽有潜在的肾功能保护作用。

延长油田低渗油藏注CO_(2)后原油相态特征研究

为了解决延长低孔低渗油藏注水开发中后期面临水淹水窜等一系列开发矛盾问题,通过室内CO_(2)与原油PVT相态实验和细管实验测试,研究了地层原油中注CO_(2)后相态变化特征及CO_(2)与原油的最小混相压力。实验结果表明,原油中注CO_(2)后,饱和压力逐渐上升,原油膨胀能力很强,目前地层压力下地层原油的体积膨胀系数为1.2023,原油粘度的最大降幅可以达到70%以上,细管实验表明CO_(2)与地层原油的最小混相压力为22.51 MPa,原始地层压力下不能实现混相驱。该研究为延长油田注CO_(2)驱油可行性提供了理论依据,对延长低渗透油藏长期持续发展具有重要意义。

Explosion limits estimation and process optimization of direct propylene epoxidation with H2 and O2

Direct propylene epoxidation with H2 and O2,an attractive process to produce propylene oxide(PO),has a potential explosion danger due to the coexistence of flammable gases(i.e.,C3 H6 and H2)and oxidizer(i.e.,O2).The unknown explosion limits of the multi-component feed gas mixture make it difficult to optimize the reaction process under safe operation conditions.In this work,a distribution method is proposed and verified to be effective by comparing estimated and experimental explosion limits of more than 200 kinds of flammable gas mixture.Then,it is employed to estimate the explosion limits of the feed gas mixture,some results of which are also validated by the classic Le Chatelier’s Rule and flammable resistance method.Based on the estimated explosion limits,process optimization is carried out using commercially high and inherently safe reactant concentrations to enhance reaction performance.The promising results are directly obtained through the interface called gOPT in gPROMS only by using a simple,easy-constructed and mature packed-bed reactor,such as the PO yield of 13.3%,PO selectivity of 85.1%and outlet PO fraction of 1.8%.These results can be rationalized by indepth analyses and discussion about the effects of the decision variables on the operation safety and reaction performance.The insights revealed here could shed new light on the process development of the PO production based on the estimation of the explosion limits of the multi-component feed gas mixture containing flammable gase s,inert gas and O2,followed by process optimization.