Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without nonalcoholic fatty liver

BACKGROUND The prevalence of non-alcoholic fatty liver(NAFLD)has increased recently.Subjects with NAFLD are known to have higher chance for renal function impairment.Many past studies used traditional multiple linear regression(MLR)to identify risk factors for decreased estimated glomerular filtration rate(eGFR).However,medical research is increasingly relying on emerging machine learning(Mach-L)methods.The present study enrolled healthy women to identify factors affecting eGFR in subjects with and without NAFLD(NAFLD+,NAFLD-)and to rank their importance.AIM To uses three different Mach-L methods to identify key impact factors for eGFR in healthy women with and without NAFLD.METHODS A total of 65535 healthy female study participants were enrolled from the Taiwan MJ cohort,accounting for 32 independent variables including demographic,biochemistry and lifestyle parameters(independent variables),while eGFR was used as the dependent variable.Aside from MLR,three Mach-L methods were applied,including stochastic gradient boosting,eXtreme gradient boosting and elastic net.Errors of estimation were used to define method accuracy,where smaller degree of error indicated better model performance.RESULTS Income,albumin,eGFR,High density lipoprotein-Cholesterol,phosphorus,forced expiratory volume in one second(FEV1),and sleep time were all lower in the NAFLD+group,while other factors were all significantly higher except for smoking area.Mach-L had lower estimation errors,thus outperforming MLR.In Model 1,age,uric acid(UA),FEV1,plasma calcium level(Ca),plasma albumin level(Alb)and T-bilirubin were the most important factors in the NAFLD+group,as opposed to age,UA,FEV1,Alb,lactic dehydrogenase(LDH)and Ca for the NAFLD-group.Given the importance percentage was much higher than the 2nd important factor,we built Model 2 by removing age.CONCLUSION The eGFR were lower in the NAFLD+group compared to the NAFLD-group,with age being was the most important impact factor in both groups of healthy Chinese women,followed by LDH,UA,FEV1 and Alb.However,for the NAFLD-group,TSH and SBP were the 5th and 6th most important factors,as opposed to Ca and BF in the NAFLD+group.

Pure State Feedback Switching Control Based on the Online Estimated State for Stochastic Open Quantum Systems

For the n-qubit stochastic open quantum systems,based on the Lyapunov stability theorem and LaSalle’s invariant set principle,a pure state switching control based on on-line estimated state feedback(short for OQST-SFC)is proposed to realize the state transition the pure state of the target state including eigenstate and superposition state.The proposed switching control consists of a constant control and a control law designed based on the Lyapunov method,in which the Lyapunov function is the state distance of the system.The constant control is used to drive the system state from an initial state to the convergence domain only containing the target state,and a Lyapunov-based control is used to make the state enter the convergence domain and then continue to converge to the target state.At the same time,the continuous weak measurement of quantum system and the quantum state tomography method based on the on-line alternating direction multiplier(QST-OADM)are used to obtain the system information and estimate the quantum state which is used as the input of the quantum system controller.Then,the pure state feedback switching control method based on the on-line estimated state feedback is realized in an n-qubit stochastic open quantum system.The complete derivation process of n-qubit QST-OADM algorithm is given;Through strict theoretical proof and analysis,the convergence conditions to ensure any initial state of the quantum system to converge the target pure state are given.The proposed control method is applied to a 2-qubit stochastic open quantum system for numerical simulation experiments.Four possible different position cases between the initial estimated state and that of the controlled system are studied and discussed,and the performances of the state transition under the corresponding cases are analyzed.

Detection of decline in estimated glomerular filtration rate in patients with type 2 diabetes by cystatin C-based equations

BACKGROUND Aging population is a significant issue in Viet Nam and across the globe.Elderly individuals are at higher risk of chronic kidney disease(CKD),especially those with diabetes.Several studies found that the estimated glomerular filtration rate(eGFR)determined using creatinine-based equations was not as accurate as that determined using cystatin C-based equations.Cystatin C-based equations may be beneficial in elderly patients with an age-associated decline in kidney function.Early determination of eGFR decline and associated factors would aid in appropriate interventions to improve kidney function in elderly patients with diabetes.AIM To determine the utility of cystatin C-based equations in early detection of eGFR decline and to explore factors associated with eGFR decline in elderly patients with diabetes.METHODS This cross-sectional study included 93 participants aged≥60 years evaluated in Can Tho University of Medicine and Pharmacy Hospital between October 2022 and July 2023,including 47 and 46 participants with and without diabetes respectively,according to the American Diabetes Association criteria for diabetes.The kappa coefficient,Student’s t,Mann-Whitney,χ2,Pearson’s correlation,multivariate logistic regression,and multiple linear regression analyses were employed.RESULTS The eGFRs were lower with the cystatin C-based equations than with the creatinine-based equations.Good agreement was found between the Modification of Diet in Renal Disease(MDRD)and CKD Epidemiology Collaboration(CKD-EPI)2021 creatinine-cystatin C equations(kappa=0.66).In the diabetes group,30%of the participants had low eGFR.Both plasma glucose and glycated hemoglobin were associated with an increased risk of eGFR decline(P<0.05)and negatively correlated with eGFR(P=0.001).By multivariate logistic regression,total cholesterol,and exercise were independently associated with low eGFR.By multiple linear regression,higher plasma glucose levels were correlated with lower eGFR(P=0.026,r=-0.366).CONCLUSION Cystatin C-based equations were superior in the early detection of a decline in eGFR,and the MDRD equation may be considered as an alternative to the CKD-EPI 2021 creatinine-cystatin C equation.Exercise,plasma glucose,and total cholesterol were independently associated with eGFR in patients with diabetes.

基于弹丸膛内运动参数和压力测试的火炮膛内燃气温度估算方法

为了解决火炮膛内测试环境恶劣而导致发射药燃气温度测试难度大的问题,基于微波干涉仪、压力测试系统,结合发射药配方性能计算理论、装药内弹道性能计算模型等理论,建立了一种基于实测参数的火炮膛内燃气温度估算方法,并开展了试验研究。结果表明:火炮膛内燃气温度的最高值约为2631.8 K,随着弹丸运动迅速降低,弹丸出炮口时膛内燃气温度降低到约1858.4 K;建立的火炮膛内发射药燃气温度估算方法可以有效地获得火炮整个内弹道过程中火药燃气温度随时间的变化规律,为低烧蚀发射药及装药的研制提供了一种新的研究手段。

基于点云处理的仿人机器人楼梯障碍物识别与剔除方法

环境感知对于仿人机器人自主导航和运动规划具有重要研究意义,是实现仿人机器人在复杂环境中进行自主移动进而完成特定任务的基础.在特殊的楼梯场景中仿人机器人环境感知过程面临诸多挑战,楼梯障碍物会破坏阶梯平面特征,导致仿人机器人获取不准确的楼梯参数而出现踏空、摔跤等问题.本文结合区域生长和平面构造方法识别和剔除楼梯障碍物点云,基于剔除障碍物后的楼梯进行三维参数估计.首先利用相邻点的投影之和最小原理准确完成对楼梯水平面的提取;其次根据区域生长算法判定楼梯障碍物聚类情况,构造平面并分析平面内点数以完成对障碍物点云的快速识别与剔除工作;最后对有障碍物楼梯与剔除障碍物楼梯进行楼梯三维感知实验.实验结果表明,本文剔除楼梯障碍物的平均精度为92.43%,且剔除后的楼梯参数感知误差仅为有障碍物时的0.5倍.总体表明所提算法能提高机器人在复杂楼梯环境中的楼梯参数估计精度,能够有效提高仿人机器人在复杂楼梯环境下的感知能力.

利用区域地震资料监测朝鲜地下核试验的研究进展

根据朝鲜6次地下核试验在中国东北及邻近地区产生的宽频带区域地震资料,中国科学院地质与地球物理研究所地震学学科组发展了一套用于监测地下核试验的地震学方法,主要包括震级测量和当量估计、高精度震中定位以及爆炸与天然地震事件识别等.在全球范围内,存在多个用于震级-当量转换的经验公式,确定何种公式适合于朝鲜半岛地区至关重要.通过搜集一组用于地震测深的化学爆炸的当量和埋深,并以这些已知爆炸源作为量规事件,能够标定朝鲜地下核试验场的震级-当量关系,从而实现对朝鲜地下核爆进行当量估计.在精确定位方面,发展了利用多事件之间波形互相关方法精确测定它们之间的走时差从而完成高精度相对震中定位.通过进一步利用Pn和Pg等多震相数据还实现了对核爆深度的相对定位.在爆炸震源识别方面,利用统计处理方法分析研究了不同类型事件所产生地震波的特征,包括6次地下核试验、4次天然地震和3次化学爆炸,以及一些矿区塌陷等.结果发现P和S类型波的振幅比,例如Pn/Lg、Pg/Lg和Pn/Sn等,在2 Hz以上能够较好区分各类震源.其中爆炸震源产生的振幅比显著高于天然地震的值.特别是,通过计算谱振幅比的台网平均值能够显著提高识别的可靠性.利用中国东北和附近地区地震台网所提供的数据可以准确地将朝鲜地下核试验从周边天然地震事件中识别出来.该方法同时得到化学爆炸的P/S谱振幅比值介于核爆炸和天然地震的群组之间.

调和分数Ornstein-Uhlenbeck金融模型的参数估计

为了描述金融资产价格过程的长相依性和自相似性,首先构建由调和分数布朗运动驱动的分数Ornstein-Uhlenbeck(O-U)模型.由于调和分数布朗运动是分数布朗运动的推广,故所构建的模型具有更广泛的应用.然后基于离散观测样本,利用最小二乘方法,得到模型漂移参数的估计量,并证明了估计量的相合性和渐近分布.最后,通过模拟展示了所得估计量的有限样本性质,模拟结果显示估计量的值拟合参数真值的效果较好.

A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical robots.This study proposes a novel end-to-end disparity estimation model to address these challenges.Our approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting interferences.This study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and efficiency.The model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video data.Experimental results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing parameters.Moreover,the model exhibited faster convergence during training,contributing to overall performance enhancement.This study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

Brain age estimation:premise,promise,and problems

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North America.Since old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

基于预测误差法的无人机安全控制器设计

具备安全性的无人机控制器是保障无人机作战完整性的重要因素之一,该控制器能够在安全的界限范围内控制无人机的飞行性能。针对无人机的安全控制器的设计问题,首先,对无人机的闭环控制系统进行分析,并采用非参数预测误差估计的方法对闭环控制系统中的执行机构模块进行辨识,以证明辨识得到的模型与实际模型无偏;其次,阐明了无人机安全性的含义,并在闭环控制系统的辨识模型的基础上,对无人机的安全控制器进行了设计;最后,以无人机飞行姿态角中的俯仰通道为例,对安全控制器性能进行了仿真验证。实验结果证明了无人机安全控制器的有效性,能够将无人机的飞行性能控制在安全范围内,为飞行安全提供保障。

基于瓦片分区的雷达动态定量降水估测方法研究

雷达定量降水估测(QPE)考虑雨滴谱的时空变异性,是提高QPE的有效途径。雷达采用Z-R关系开展降水估测时,雨滴谱的差异,主要表现为Z-R关系式不同;利用瓦片分区方法,将降水估测区域进行瓦片分区,每个瓦片内利用雷达和自动站数据动态拟合Z-R关系式开展QPE。文中利用六次天气过程对瓦片分区降水估测方法进行评估,从QPE各项评价指标看,误差较传统的固定Z-R关系法和全域动态Z-R关系法,有很好的提升,降水估测结果与强降水中心基本一致,各项误差指标均最小;结果表明瓦片分区降水估测方法是提升雷达QPE的有效方式。

Bootstrap抽样下基于贝叶斯估计的地震人员死亡评估研究

选取1950-2022年中国内地地区历史震例数据信息,以极震区烈度、发震时间及人口密度为主要影响因素,建立三级场景,运用Bootstrap抽样方法对各场景下的历史震例进行扩充,进而采用贝叶斯估计给出不同场景下地震人员死亡变化分布函数,再根据实际情况对此分布函数进行截断分析,以明确地震人员死亡的不确定性变化范围及死亡率区间概率值,最后随机选取历史地震灾害事件验证模型精度。结果表明:①各场景的死亡率均值及95%死亡率区间基本符合在极震区烈度相等并且人口密度条件下夜间死亡率大于白天死亡率的规律;②模型估计死亡人数区间能够较好覆盖实际上报的死亡人数。

量子核判别分析算法

核判别分析法通过核函数扩展了线性判别分析对非线性数据的处理能力,成为模式识别领域中一个重要的分支。然而,随着数据的指数增长,经典核判别分析算法在提取特征时会消耗大量计算资源。针对这一问题,利用量子叠加性和并行性提出了一种量子核判别分析算法。首先,借助量子随机存储器技术与控制旋转操作构造需要的类间矩阵和类内矩阵所对应的密度算子;然后,融入线性方程的求解思路并行获取特征态。理论分析表明,所提算法与经典算法相比具有指数级加速。

石家庄S波段和X波段双偏振雷达定量降水估测应用研究

基于石家庄S波段雷达和X波段雷达、雨滴谱仪观测资料以及地面雨量计数据,分析两种雷达的R(ZH)、R(ZH,ZDR)、R(KDP)和R(KDP,ZDR)四种定量降水估测方法。结果表明,利用雨滴谱仪数据计算出的雷达反射率因子与雷达实测具有较好的一致性,但整体偏大5 dB;两种雷达使用R(KDP,ZDR)方法估测降水结果优于其他方法,使用偏振参量KDP能明显提高降雨估测结果,使用ZDR后,测雨公式较单参量提高不明显;使用R(KDP)和R(KDP,ZDR)方法,利用X波段雷达估测降水的准确度略高于S波段雷达,可提升约10%,利用高空间分辨率的X波段雷达可以提升城市降水估测的精确度。

基于POI数据的城市功能识别与分布特征研究——以长春市区为例

长春市是国家新型城镇化综合试点城市,识别长春市中心城区功能,针对当前存在的问题提出对策建议,对城市空间的优化与协调具有重要意义。以兴趣点(Point of Interest,POI)数据及开放街道地图(Open Street Map,OSM)数据为基础,结合核密度分析、实地调查验证等方法,识别长春市中心城区城市功能类型。结果表明:单一功能区中,商业功能区数量最多,居住功能区最少;主导—混合功能区中的商业主导功能区及交通主导功能区形成对商业聚集区与轨道交通系统的重要补充;细分—混合功能区特征显示功能混合程度从市中心向周边逐渐加大。经验证,城市功能识别结果符合长春市实际,由此提出对策建议:未来长春市中心城区应注重多中心发展格局,并加强绿地空间和公共服务设施建设。

A deep-learning-based prediction method of the estimated ultimate recovery(EUR)of shale gas wells

The estimated ultimate recovery(EUR)of shale gas wells is influenced by many factors,and the accurate prediction still faces certain challenges.As an artificial intelligence algorithm,deep learning yields notable advantages in nonlinear regression.Therefore,it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm.In this paper,according to geological evaluation data,hydraulic fracturing data,production data and EUR evaluation results of 282 wells in the WY shale gas field,a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized.First,the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed.Second,the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed.Finally,by means of real data obtained from the WY shale gas field,several different cases were applied to testify the validity and accuracy of the proposed approach.The results show that the EUR prediction with high accuracy.In addition,the results are affected by the variety and number of input parameters,the network structure and hyperparameters.The proposed approach can be extended to other shale fields using the similar technic process.

煤矿电网功率因数在线提高方法研究

针对如何在线实现煤矿电网功率因数提高问题,本文提出了一种实时在线提高功率因数的方法,首先,通过电网监测系统,建立实时数据库,对电网系统的运行状况进行实时跟踪。其次,在此基础上,对系统进行实时状态估计,纠正系统在线上传数据信息的错误。最后,对系统进行潮流计算,得到系统功率因数,并对功率因数不合格的节点进行无功补偿,实现功率因数的提高。通过对某一煤矿电网实例进行仿真,验证了本文提出方法的正确性。

The First Quantitative Slip-Rate Estimated Along the Ashikule Fault at the Western Segment of the Altyn Tagh Fault System

As one of the longest strike-slip fault in Asia,the Altyn Tagh Fault（ATF）defines the northern boundary of the Tibetan Plateau and plays a significant role inaccommodating the deformation resulting from the IndiaAsia convergence.

Plasma hemoglobin concentration was related to estimated glomerular filtration rate in elderly patients with ischemic cardiomyopathy

Objectives To study the relationship between plasma hemoglobin concentration and estimated glomerular filtration rate （eGFR） in elderly patients with ischemic cardiomyopathy （ICM）.Methods Clinical data of patients with coronary heart disease who were discharged from The First Affiliated Hospital,Chongqing Medical University between 2005 and 2007 were analyzed retrospectively. Echocardiography results,plasma hemoglobin and creatinine concentration were abstracted from the medical records.The study included 235 Chinese Hart patients with age 60 years and older with angiography confirmed coronary heart disease,silent myocardial ischemia or angina pectoris,of whom 154 had ICM defined as left ventricular end-diastolic diameter （LVDd）,male≥56 mm,female≥51 mm （63. 51±7.70 mm） measured by M-mode echocardiography.The differences in plasma hemoglobin concentration were analyzed retrospec- tively between patients with and without ICM,and between patients with an eGFR【60 ml·min-1·1.73m-2 and those with an eGFR≥60 ml·min-1·1.73m-2.Results There were no significant differences in plasma hemoglobin concentration and eGFR between ICM and non-ICM group (118.49±20.52 g·L-1 vs.115.80±23.32 g·L-1 and 75.13±24.21 ml·min-1·1.73m-2 vs.79.09±28.41 ml·min- 1·1.73m-2,respectively,both P】0.05).However,in both ICM and non-ICM groups,plasma hemoglobin concentration was lower in those with an eGFR【60 ml·min-1·1.73m-2 compared with compared with those with an eGFR≥60 ml·min-1·1.73m-2 group (112. 29±18.61 g·L-1 vs.119.92±20.74L-1,P【0.05);plasma hemoglobin concentration was related positively to eGFR.Conclusions There were no significant changes in plasma hemoglobin concentration and eGFR;however,plasma hemoglobin concentration was related to eGFR significantly positively in elderly patients with ICM due to coronary heart

随机时滞复Ginzburg-Landau方程的遍历性

讨论定义在整数集上的随机时滞复Ginzburg-Landau方程的遍历性.当非线性漂移项和扩散项是局部Lipschitz连续时,运用一致估计、二分法、Arzela-Ascoli定理建立有限维到无限维连续函数空间内解的概率分布的胎紧性,从而证明不变测度的存在性.当非线性飘移和扩散项的Lipschitz系数足够小时,证明不变测度的唯一性.