Unified deep learning model for predicting fundus fluorescein angiography image from fundus structure image

The prediction of fundus fluorescein angiography(FFA)images from fundus structural images is a cutting-edge research topic in ophthalmological image processing.Prediction comprises estimating FFA from fundus camera imaging,single-phase FFA from scanning laser ophthalmoscopy(SLO),and three-phase FFA also from SLO.Although many deep learning models are available,a single model can only perform one or two of these prediction tasks.To accomplish three prediction tasks using a unified method,we propose a unified deep learning model for predicting FFA images from fundus structure images using a supervised generative adversarial network.The three prediction tasks are processed as follows:data preparation,network training under FFA supervision,and FFA image prediction from fundus structure images on a test set.By comparing the FFA images predicted by our model,pix2pix,and CycleGAN,we demonstrate the remarkable progress achieved by our proposal.The high performance of our model is validated in terms of the peak signal-to-noise ratio,structural similarity index,and mean squared error.

Generalized Pareto Distribution Model and Its Application to Hydrocarbon Resource Structure Prediction of the Huanghua Depression

The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variable, resource density, such model can describe not only different types of basins, but also any exploration samples at different phases of exploration, up to the parent population. It is a dynamic distribution model with profound geological significance and wide applicability. Its basic principle and the process of resource assessment are described in this paper. The petroleum accumulation system is an appropriate assessment unit for such method. The hydrocarbon resource structure of the Huanghua Depression in Bohai Bay Basin was predicted by using this model. The prediction results accord with the knowledge of exploration in the Huanghua Depression, and point out the remaining resources potential and structure of different petroleum accumulation systems, which are of great significance for guiding future exploration in the Huanghua Depression.

Generalized structural equation modeling:Symptom heterogeneity in attention-deficit/hyperactivity disorder leading to poor treatment efficacy

BACKGROUND Treatment efficacy for attention-deficit/hyperactivity disorder(ADHD)is reported to be poor,possibly due to heterogeneity of ADHD symptoms.Little is known about poor treatment efficacy owing to ADHD heterogeneity.AIM To use generalized structural equation modeling(GSEM)to show how the heterogeneous nature of hyperactivity/impulsivity(H/I)symptoms in ADHD,irritable oppositional defiant disorder(ODD),and the presentation of aggression in children interferes with treatment responses in ADHD.METHODS A total of 231 children and adolescents completed ADHD inattention and H/I tests.ODD scores from the Swanson,Nolan,and Pelham,version IV scale were obtained.The child behavior checklist(CBCL)and parent’s satisfaction questionnaire were completed.The relationships were analyzed by GSEM.RESULTS GSEM revealed that the chance of ADHD remission was lower in children with a combination of H/I symptoms of ADHD,ODD symptoms,and childhood aggressive behavior.ODD directly mediated ADHD symptom severity.The chance of reaching remission based on H/I symptoms of ADHD was reduced by 13.494%[=exp(2.602)]in children with comorbid ADHD and ODD[odds ratio(OR)=2.602,95%confidence interval(CI):1.832-3.373,P=0.000]after adjusting for the effects of other factors.Childhood aggression mediated ODD symptom severity.The chance of reaching remission based on ODD symptoms was lowered by 11.000%[=1-exp(-0.117)]in children with more severe baseline symptoms of aggression based on the CBCL score at study entry[OR=-0.117,95%CI:(-0.190)-(-0.044),P=0.002].CONCLUSION Mediation through ODD symptoms and aggression may influence treatment effects in ADHD after adjusting for the effects of baseline ADHD symptom severity.More attention could be directed to the early recognition of risks leading to ineffective ADHD treatment,e.g.,symptoms of ODD and the presentation of aggressive or delinquent behaviors and thought problems in children with ADHD.

Multi-scale fatigue damage model for steel structures working under high temperature

In order to better understand the fatigue mechanisms of steel structures working under high temperature, a multi-scale fatigue damage model at high temperature is developed. In the developed model, the macroscopic fatigue damage of metallic materials due to the collective behavior of micro-cracks is quantified by using the generalized self-consistent method. The influence of temperature on fatigue damage of steel structures is quantified by using the previous creep damage model. In addition, the fatigue damage at room temperature and creep damage is coupled in the multi-scale fatigue damage model. The validity of the developed multi-scale damage model is verified by comparing the predicted damage evolution curve with the experimental data. It shows that the developed model is effectiveness. Finally, the fatigue analysis on steel crane runway girders (CRGs) of industrial steel melt shop is performed based on the developed model.

Validation of general linear modeling for identifying factors associated with Quality of Life: A comparison with structural equation modeling

Purpose: General linear modeling (GLM) is usually applied to investigate factors associated with the domains of Quality of Life (QOL). A summation score in a specific sub-domain is regressed by a statistical model including factors that are associated with the sub-domain. However, using the summation score ignores the influence of individual questions. Structural equation modeling (SEM) can account for the influence of each question’s score by compositing a latent variable from each question of a sub-domain. The objective of this study is to determine whether a conventional approach such as GLM, with its use of the summation score, is valid from the standpoint of the SEM approach. Method: We used the Japanese version of the Maugeri Foundation Respiratory Failure Questionnaire, a QOL measure, on 94 patients with heart failure. The daily activity sub-domain of the questionnaire was selected together with its four accompanying factors, namely, living together, occupation, gender, and the New York Heart Association’s cardiac function scale (NYHA). The association level between individual factors and the daily activity sub-domain was estimated using SEM?and GLM, respectively. The standard partial regression coefficients of GLM and standardized path coefficients of SEM were compared. If?these coefficients were similar (absolute value of the difference -0.06 and -0.07 for the GLM and SEM. Likewise, the estimates of occupation, gender, and NYHA were -0.18 and -0.20, -0.08 and -0.08, 0.51 and 0.54, respectively. The absolute values of the difference for each factor were 0.01, 0.02, 0.00, and 0.03, respectively. All differences were less than 0.05. This means that these two approaches lead to similar conclusions. Conclusion: GLM is a valid method for exploring association factors with a domain in QOL.

GENERALIZED STOCHASTIC DURATION INMARKOVIAN HEATH-JARROW-MORTONFRAMEWORK

This paper focuses on how to measure the interest rate risk. The conventional measure methods of interest rate risk are reviewed and the duration concept is generalized to stochastic duration in the Markovian HJM framework. The generalized stochastic duration of the coupon bond is defined as the time to maturity of a zero coupon bond having the same instantaneous variance as the coupon bond. According to this definition., the authors first present the framework of Markovian HJM model, then deduce the measures of stochastic duration in some special cases which cover some extant interest term structure.

A Novel Unsupervised Change Detection Method with Structure Consistency and GFLICM Based on UAV Images

With the rapid development of Unmanned Aerial Vehicle(UAV)technology,change detection methods based on UAV images have been extensively studied.However,the imaging of UAV sensors is susceptible to environmental interference,which leads to great differences of same object between UAV images.Overcoming the discrepancy difference between UAV images is crucial to improving the accuracy of change detection.To address this issue,a novel unsupervised change detection method based on structural consistency and the Generalized Fuzzy Local Information C-means Clustering Model(GFLICM)was proposed in this study.Within this method,the establishment of a graph-based structural consistency measure allowed for the detection of change information by comparing structure similarity between UAV images.The local variation coefficient was introduced and a new fuzzy factor was reconstructed,after which the GFLICM algorithm was used to analyze difference images.Finally,change detection results were analyzed qualitatively and quantitatively.To measure the feasibility and robustness of the proposed method,experiments were conducted using two data sets from the cities of Yangzhou and Nanjing.The experimental results show that the proposed method can improve the overall accuracy of change detection and reduce the false alarm rate when compared with other state-of-the-art change detection methods.

Model/data comparison of typhoon-generated noise

Ocean noise recorded during a typhoon can be used to monitor the typhoon and investigate the mechanism of the wind- generated noise. An analytical expression for the typhoon-generated noise intensity is derived as a function of wind speed. A ＂bi-peak＂ structure was observed in an experiment during which typhoon-generated noise was recorded. Wind speed dependence and frequency dependence were also observed in the frequency range of 100 Hz-1000 Hz. The model/data comparison shows that results of the present model of 500 Hz and 1000 Hz are in reasonable agreement with the exper- imental data, and the typhoon-generated noise intensity has a dependence on frequency and a power-law dependence on wind speed.

Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter

Since the main power source of hybrid electric vehicle（HEV） is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge（SOC） estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter（VSEKF）-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model（GLM）,which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics（HPPC） test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour（Ah） integration method and the extended Kalman filter（EKF） method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

A parameterization scheme of vertical mixing due to inertial internal wave breaking in the ocean general circulation model

Based on the theoretical spectral model of inertial internal wave breaking （fine structure） proposed previ- ously, in which the effects of the horizontal Coriolis frequency component f-tilde on a potential isopycnal are taken into account, a parameterization scheme of vertical mixing in the stably stratified interior be- low the surface mixed layer in the ocean general circulation model （OGCM） is put forward preliminarily in this paper. Besides turbulence, the impact of sub-mesoscale oceanic processes （including inertial internal wave breaking product） on oceanic interior mixing is emphasized. We suggest that adding the inertial inter- hal wave breaking mixing scheme （F-scheme for short） put forward in this paper to the turbulence mixing scheme of Canuto et al. （T-scheme for short） in the OGCM, except the region from 15°S to 15°N. The numeri- cal results ofF-scheme by usingWOA09 data and an OGCM （LICOM, LASG/IAP climate system ocean model） over the global ocean are given. A notable improvement in the simulation of salinity and temperature over the global ocean is attained by using T-scheme adding F-scheme, especially in the mid- and high-latitude regions in the simulation of the intermediate water and deep water. We conjecture that the inertial internal wave breaking mixing and inertial forcing of wind might be one of important mechanisms maintaining the ventilation process. The modeling strength of the Atlantic meridional overturning circulation （AMOC） by using T-scheme adding F-scheme may be more reasonable than that by using T-scheme alone, though the physical processes need to be further studied, and the overflow parameterization needs to be incorporated. A shortcoming in F-scheme is that in this paper the error of simulated salinity and temperature by using T-scheme adding F-scheme is larger than that by using T-scheme alone in the subsurface layer.

The Chapman-Richards Distribution and its Relationship to the Generalized Beta

Background: The Chapman-Richards distribution is developed as a special case of the equilibrium solution to the McKendrick-Von Foerster equation. The Chapman-Richards distribution incorporates the vital rate assumptions of the Chapman-Richards growth function, constant mortality and recruitment into the mathematical form of the distribution. Therefore, unlike 'assumed' distribution models, it is intrinsically linked with the underlying vital rates for the forest area under consideration. Methods: It is shown that the Chapman-Richards distribution can be recast as a subset of the generalized beta distribution of the first kind, a rich family of assumed probability distribution models with known properties. These known properties for the generalized beta are then immediately available for the Chapman-Richards distribution, such as the form of the compatible basal area-size distribution. A simple two-stage procedure is proposed for the estimation of the model parameters and simulation experiments are conducted to validate the procedure for four different possible distribution shapes. Results: The simulations explore the efficacy of the two-stage estimation procedure;these cover the estimation of the growth equation and mortality-recruitment derives from the equilibrium assumption. The parameter estimates are shown to depend on both the sample size and the amount of noise imparted to the synthetic measurements. The results vary somewhat by distribution shape, with the smaller, noisier samples providing less reliable estimates of the vital rates and final distribution forms. Conclusions: The Chapman-Richards distribution in its original form, or recast as a generalized beta form, presents a potentially useful model integrating vital rates and stand diameters into a flexible family of resultant distributions shapes. The data requirements are modest, and parameter estimation is straightforward provided the minimal recommended sample sizes are obtained.

Hydrocarbon-Generating Model of the Area Covered With Volcanic Rock

The distribution of Oil & gas fields shows their close relationship with the most active tectonic regions. This is not a coincidence but having a scientific reasons. The crustal active regions, refer to the places where the active natural earthquake, volcanic activities, underground water happened, and the areas of the leaking Off of natural gas to the surface of the crust. The magma of volcanic activities brings the organic "kitchen range body" hydrocarbon - generating model and inorganic genetic hydrocarbon to the regions covered by volcanic rock. Underground water brings a catalytic hydrocarbon generating model for organic matter, and the leaking - off of H2 and CO2 contributes a synthetic hydrocarbon - generating model. Volcanic activities bring the assemblage of Source, Reservoir and Seal formed by the sediments and magma the sedimentary basins, and the hydrocarbon - generating system with a "water - volcano" binary structure is formed. All these conditions are favorable and excellent for the formation of oil & gas fields. The distribution of AInerican oil & gas fields have very close relationship with the mines of Fe, Mn, Cr, Mo, W and V, deposits of Zn, Cu, V, Pb, Al and Hg, and the deposits of fluorite, sulfur, potassium salt, phosphate and halite, and the distribution of sulfate - chloride of river water. The reason why few oil & gas fields discovered in the regions covered by volcanic rock in western America maybe because of the view of "inconsistency between petroleum and volcano". Further more, It’s very difficult to carry out a geophysical exploration in such kinds of regions. This paper examined a few hydrocarbon - generating models (systems) mentioned above and came up with some flesh ideas on the exploration in the areas covered with volcanic rocks.

Structure-preserving approach for infinite dimensional nonconservative system

The current structure-preserving theory, including the symplectic method and the multisymplectic method, pays most attention on the conservative properties of the continuous systems because that the conservative properties of the conservative systems can be formulated in the mathematical form. But, the nonconservative characteristics are the nature of the systems existing in engineering. In this letter, the structure-preserving approach for the infinite dimensional nonconservative systems is proposed based on the generalized multi-symplectic method to broaden the application fields of the current structure-preserving idea. In the numerical examples,two nonconservative factors, including the strong excitation on the string and the impact on the cantilever, are considered respectively. The vibrations of the string and the cantilever are investigated by the structure-preserving approach and the good long-time numerical behaviors as well as the high numerical precision of which are illustrated by the numerical results presented.

Open Volumetric Mesh-An Efficient Data Structure for Tetrahedral and Hexahedral Meshes

This work introduces a scalable and efficient topological structure for tetrahedral and hexahedral meshes. The design of the data structure aims at maximal flexibility and high performance. It provides a high scalability by using hierarchical representa-tions of topological elements. The proposed data structure is array-based, and it is a compact representation of the half-edge data structure for volume elements and half-face data structure for volumetric meshes. This guarantees constant access time to the neighbors of the topological elements. In addition, an open-source implementation named Open Volumetric Mesh （OVM） of the pro-posed data structure is written in C＋＋ using generic programming concepts.

市场激励型环境规制与区域绿色创新效率——基于产业结构优化的中介作用和财政分权的调节作用

市场激励型环境规制是解决环境治理负外部性、推进区域绿色创新效率的重要途径。以2005~2020年省级面板数据为研究对象,采用系统广义矩模型(GMM)法检验市场激励型环境规制对区域绿色创新效率的影响效应及作用机理。结果表明:市场激励型环境规制能够显著促进区域绿色创新效率的提升;从影响机制来看,市场激励型环境规制可以通过促进产业结构合理化和产业结构高级化显著促进区域绿色创新效率的提升。此外,有效的财政分权环境能够正向调节市场激励型环境规制与区域绿色创新效率的关系。

计及复杂换位结构的百万千瓦级汽轮发电机定子流固耦合传热研究

百万千瓦级汽轮发电机的定子绕组通常采用多根空、实心股线并绕的复杂编织换位结构,针对尺寸相差悬殊的复杂结构使得其定子流固耦合模型的数值求解存在网格数量多、容易出现奇异解的难点问题,该文提出三维区段式流固耦合网格划分方法,根据不同区段股线的结构及传热特点,通过非均匀网格划分方法大大降低求解模型的网格数量,实现计及复杂换位结构的定子流固耦合模型的数值求解,并通过一台124万kW水氢氢冷汽轮发电机的短路型式实验进行验证。在此基础上,提出定子绕组的新型交叉换位方法并与传统换位方法的温度进行对比,结果表明,新型交叉换位方法使定子绕组股线以及绝缘的温度分布更加均匀,并且能够有效降低定子绕组最高温度。

构造序次及其在找矿预测中的应用——以华南热液型铀矿床为例

构造序次是地质力学和构造地质学的重要概念。构造序次是指在同一场地壳运动中,岩块或地块在遭受同一时期、同一动力作用方式持续作用下,所形成的不同性质和排列方位的各项结构面先后出现的次序,或者是由于边界条件的局部改变,各项构造形迹挨次控制关系。构造序次强调了构造形迹之间的成生联系,是厘定构造型式、建立构造体系的基础。构造序次关系是非常多见的,它不同于构造级别,不同序次构造之间具有时差性、派生性、绝对性、可隐性等特点,低序次构造往往展布在高一序次构造所影响的范围内,受局部构造应力场控制。控矿构造研究要从低序次到高序次,从含矿构造入手,开展力学性质和组合规律分析,厘定控矿构造型式,总结构造控矿规律;找矿预测要从高序次到低序次,根据构造控矿型式和序次的挨次控制规律,分析低序次含矿构造可能出现的位置和方向,开展找矿预测。通过控矿构造的序次分析,认为江西相山邹家山铀矿床不是受NE向的邹家山石洞断裂控制,而是受NEE向、中低倾角倾向NNW的隐性构造带控制,找矿方向是沿现有矿带SWW方向、中等倾角的深部。长江铀矿田不是受棉花坑断裂和油洞断裂控制,而是受NNW(近SN)向陡倾角构造带控制,浅部次级断裂含(储)矿、其下延归并的主构造带起导矿、运(配)矿作用,找矿方向是沿NNW(近SN)向含矿构造的延伸、延深部位以及地表矿带内空白区的深部。在进行构造序次分析时要特别注意构造形迹的成生联系,也要注重构造期次,更要区分成矿前、成矿期和成矿后构造,对具体的矿田、矿床或矿化带,对导矿、运矿(配矿)、储矿(含矿)构造间的关系(也即控矿构造与含矿构造的关系)要进行客观分析,厘定控矿构造型式,构建构造控矿模型,指导找矿预测实践。

自动化建模与优化平台开发及其在切削吸能结构的应用

传统优化设计受限于几何参数化和六面体单元生成困难等问题,优化过程繁琐,效率低下。为规范开发流程,提高优化设计效率,本文搭建以MOO(multi-objective optimization)系统为核心,集成了几何、有限元建模、数据处理以及代理优化等模块的自动化建模与优化平台。自动化建模模块以CAE为核心,基于三次样条函数构造特征截面和映射路径实现自动几何参数化建模,并在扫掠法和模型分解法的基础上,提出基于多截面扫掠法的六面体网格自动化生成方法;此外,在常规基于代理模型的优化流程上,通过数据转换和处理算法实现从数值计算结果提取到代理优化的自动化。研究结果表明:该平台能建立具有较小几何误差和高质量单元的有限元模型,结构耐撞性指标整体上有一定提升,可以显著地提高优化工作流程的效率。

基于特征和公差重构的结构化多态模型集成方法研究

针对当前航天器结构产品设计制造一体化需求,在新一代GPS标准体系框架下,研究并提出了基于特征和公差重构的结构化多态模型集成方法,对现有三维数字化设计模型信息解构和重构,对现有三维数字化设计模型信息解构和重构,形成符合新一代GPS标准体系的多态设计模型和充分表征设计信息的结构化数据集,突破数字化检定认证手段难以与设计信息关联复用的困难,为航天器结构产品设计制造一体化推广应用提供有益借鉴。

基于随机循环网络的汉字骨架生成

汉字骨架是汉字字形的重要拓扑描述,提供了汉字字形结构的重要信息。汉字骨架可以视为点序列,运用具有序列输出的循环神经网络(RNN)等生成。然而当前输出长序列的深度神经网络通常面临诸如梯度消失或爆炸,需要大量训练样本和训练时间长等问题,导致此类方法生成的汉字骨架蕴含的书写细节较少,同时缺乏对汉字结构的准确描述。文中将汉字的结构信息与神经网络方法相结合,使用多个并行的随机循环网络(RRN)生成汉字骨架,生成过程在两个层面进行,字符层面包括一连串的笔画,而笔画层面包括一连串的点。生成模型仅需小规模的训练数据即可完成训练,同时避免了梯度消失或爆炸的问题,不仅增强了对汉字结构的描述,而且保留了更多的骨架特征点。实验结果表明,该方法生成的汉字骨架具有更丰富的书写细节特征,可用于快速生成大规模、高质量的汉字骨架。