基于Downhill-Simplex算法的观测数据与作物生长模型同化方法研究

以夏玉米叶面积指数(LAI)、贮存器官干重(WSO)、地上总干重(TAGP)以及土壤水分含量(SM)为结合点,建立了基于Downhill-Simplex算法的作物生长模型WOFOST同化多种地面观测数据的一般方法或流程:开展观测数据与作物生长模型同化方法的正确性验证→利用Downhill-Simplex算法进行WOFOST模型的敏感性分析→选择敏感参数组合→通过优化效果确定待优化参数→利用新的观测数据对待优化参数进行优化,从而实现了观测数据与作物生长模型的同化,提升了模型的模拟能力。同化过程中遴选出的WOFOST模型的待优化参数主要包括比叶面积、最大CO2同化速率、初始地上部总干物重、根深最大日增量和初始土壤有效水等。

关于Uphill和Downhill悖论的解释

近年来，国际资本流动发生了逆转，由之前的发达国家流向发展中国家转为由发展中国家流向发达国家。资本流动方向与传统的经济学理论相悖，有关悖论的解释成为国际经济学领域一大挑战。本文拟从制度环境、人口结构、资本市场完善程度、外资利用水平、国际金融秩序领域进行悖论解释。

Downhill Zagreb Topological Indices and <i>M<SUB>dn</SUB></i>-Polynomial of Some Chemical Structures Applied for the Treatment of COVID-19 Patients

A graphical index is a numeric value corresponding to a graph which is structurally invariant and in molecular graph theory these invariants are known as topological indices. In the field of Chemical and Medical Sciences, the topological indices are used to study the chemical, biological, medical and pharmaceutical features of drugs. With reference to the previous deadly diseases, the COVID-19 pandemic has considered to be the biggest life threatening issue that modern medicines have ever tackled. COVID-19 is immedicable and even the existing treatments are only helping the certain group of sufferers. Scientists have tested available antiviral agents and got a favorable impact on recovering from pandemic. Some of these antiviral agents are remdesivir, chloroquine, hydroxychloroquine, theaflavin and dexamethasone. Keeping in view of the importance of topological indices in the study of pharmaceutical and chemical drugs, in this paper, we calculate the Mdn-Polynomial, some downhill Zagreb topological indices and some downhill Zagreb polynomials of some of the anti viral agents remdesivir, chloroquine, hydroxychloroquine, theaflavin and dexamethasone. The results thus obtained may be useful for the finding new medicine and vaccine for the treatment of COVID-19.

Location method of ill-conditioned microseismic source and its engineering application

Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial factors,the geometry of the sensor installation will be close to linear,which makes the localization equation suffer from the pathological problem,and the localization accuracy is greatly reduced.To address this problem,the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix.The pathological problem is caused by the combined effect of the poorer sensor array and data errors,and its residual isosurface shows a conical distribution,and as the residual value decreases,the apex of the isosurface gradually extends to the far side,and the localization results do not converge.For this reason,an improved regularized Newton downhill localization algorithm is proposed.In this method,firstly,the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same,and the condition number of the coefficient matrix is reduced;then,the L-curve method is used to calculate the regularization factor for the pathological equations,and the coefficient matrix is improved;finally,the pathological equations are regularized,and the seismic source coordinates are obtained by the improved Newtonian downhill method.The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking,the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7%,and the localization accuracy is substantially improved.The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival.The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.

3-D fracture network dynamic simulation based on error analysis in rock mass of dam foundation

Accurate 3-D fracture network model for rock mass in dam foundation is of vital importance for stability,grouting and seepage analysis of dam foundation.With the aim of reducing deviation between fracture network model and measured data,a 3-D fracture network dynamic modeling method based on error analysis was proposed.Firstly,errors of four fracture volume density estimation methods(proposed by ODA,KULATILAKE,MAULDON,and SONG)and that of four fracture size estimation methods(proposed by EINSTEIN,SONG and TONON)were respectively compared,and the optimal methods were determined.Additionally,error index representing the deviation between fracture network model and measured data was established with integrated use of fractal dimension and relative absolute error(RAE).On this basis,the downhill simplex method was used to build the dynamic modeling method,which takes the minimum of error index as objective function and dynamically adjusts the fracture density and size parameters to correct the error index.Finally,the 3-D fracture network model could be obtained which meets the requirements.The proposed method was applied for 3-D fractures simulation in Miao Wei hydropower project in China for feasibility verification and the error index reduced from 2.618 to 0.337.

An embedded ReS_(2)@MAPbBr_(3) heterostructure with downhill interfacial charge transfer for photocatalytic upgrading of biomass-derived alcohols to aldehydes and H_(2)

Solar-driven selective upgrading of lignocellulosic biomass-derived alcohols to value-added chemicals and clean fuel hydrogen(H_(2))shows great potential for tackling the energy crisis and environmental pollu-tion issues.Here,we construct a MAPbBr_(3)/ReS_(2) heterostructure by embedding distorted tetragonal(1T)phase ReS_(2) nanoflowers into large-sized MAPbBr_(3) for green value-added utilization of biomass-derived alcohols.The embedded structure effectively enlarges the contact interface between the ReS_(2) and the MAPbBr_(3),and importantly,induces a strong built-in electric field aligned between the spatially well-defined MAPbBr_(3) and ReS_(2) nanoflowers.Moreover,the distorted 1T phase ReS_(2) with low work function well matches the energy band of MAPbBr_(3),forming a heterostructure with a downward band bending at the interface.These features empower the MAPbBr_(3)/ReS_(2) photocatalyst with high capability to promote charge separation and expedite the surface redox reaction.Consequently,optimal BAD and H_(2) production rates of about 1220 μmol h-1 g-1 are realized over a MAPbBr_(3)/ReS_(2) 2%sample,which are approximately 9 times greater than those of blank MAPbBr_(3).This work demonstrates the great potential of constructing an embedded transition metal dichalcogenide@metal halide perovskites heterostructure with downhill interfacial charge transfer for photocatalytic upgrading of biomass-derived alcohols.

An unusual cause of hematemesis:Goiter

Downhill varices are located in the upper part of the esophagus and are usually related to superior vena cava obstruction. Bleeding from these varices is extremely rare. We describe a 77-year-old patient with hematemesis due to downhill varices as a result of recurrent goiter. A right lobe thyroidectomy was carried out with disappearance of the varices.

A MNCIE method for registration of ultrasound images

A new approach to the problem of registration of ultrasound images is presented, using a concept of Nonlinear Correlation Information Entropy (NCIE) as the matching criterion. The proposed method applies NCIE to measure the correlation degree between the image intensities of corresponding voxel in the floating and reference images. Registration is achieved by adjustment of the relative position until NCIE between the images is maximized. However, unlike mutual information (MI), NCIE varies in the closed interval [0, 1], and around the extremum it varies sharply, which makes it possible that thresholds of NCIE can be used to boost the search for the registration transformation. Using this feature of NCIE, we combine the downhill simplex searching algorithm to register the ultrasound images. The simulations are conducted to testify the effectiveness and rapidity of the proposed registration method, in which the ultrasound floating images are aligned to the reference images with required registration accuracy. Moreover, the NCIE based method can overcome local minima problem by setting thresholds and can take care of the differences in contrast between the floating and reference images.

Optimization of Linear Filtering Model to Predict Post-LASIK Corneal Smoothing Based on Training Data Sets

Laser vision correction is a rapidly growing field for correcting nearsightedness, farsightedness as well as astigmatism with dominating laser-assisted in situ keratomileusis (LASIK) procedures. While the technique works well for correcting spherocylindrical aberrations, it does not fully correct high order aberrations (HOAs), in particular spherical aberration (SA), due to unexpected induction of HOAs post-surgery. Corneal epithelial remodeling was proposed as one source to account for such HOA induction process. This work proposes a dual-scale linear filtering kernel to model such a process. Several retrospective clinical data sets were used as training data sets to construct the model, with a downhill simplex algorithm to optimize the two free parameters of the kernel. The performance of the optimized kernel was testedon new clinical data sets that were not previously used for the optimization.

Effects of Trekking Pole Use on Metabolic Cost in Novice Hikers on Steep Terrains

PURPOSE： This study examined whether the use of trekking poles alters metabolic cost in steep hiking by novice hikers and whether the response would be dependent on the grade of the terrain. METHODS： Twelve participants completed two trekking trials （with poles [WP] and without trekking poles [NP]） with round trips comprising three grades： 7.0 ± 0.7°, 12.9 ± 0.7°, and 18.8 ± 1.3°） over a steep mountain at self-paced speeds. During the trials, time spent for trekking （TT）, oxygen consumption （VO2）, heart rate （HR）, ratings of perceived exertion （RPE）, and step frequency （Sf） were measured, and step efficiency （Se） and oxygen pulse （OP） were calculated. RESULTS： TT tended to be longer in the WP than NP for both terrains （P 〈 0.05）. HR, VO2, and RPE were the same for the WP and NP. Sfwas lower in WP going uphill （P 〈 0.05） but was unchanged going downhill. Se in the WP was higher than in the NP for both terrains （P 〈 0.01）. When analyzed by slope, VO2 during uphill at 18.8° was lower in WP （37.2 ± 6.3） than in NP （38.6 ± 7.1 ml .kg-1 .min-1, P 〈 0.05）, but no difference in VO2 was found between WP and NP at the 12.9° and 7.0°. TT during uphill was slower in WP than NP at 12.9°（7.9± 1.1 vs. 7.4 ± 1.0） and 18.8° （5.3 ± 1.3 vs. 4.9± 1.0 min, respectively, P 〈 0.05）. No differences were noticed in HR and OP during uphill at every grade. CONCLUSIONS： Pole use decreased metabolic cost in the novice hikers only in the highest grade but not in the other two lower grades.

Numerical Efficient Thermal Network for Calculating the Brake Disc Temperature

The simulation of the brake disc temperature is an important tool in the development of passenger cars.Nowadays thermal models of brake discs are real-time applications,running on electronic control units(ECUs)of cars to improve the vehicle safety in several ways.These models are often working with full empirical methods,leading to large deviations between calculation and measurement.To meet the requirements of automotive safety integrity levels(ASILs),these thermal models cannot rely on the state of the art ambient air temperature sensors,which causes unacceptable deviations.Focusing on numerical efficient thermal simulations,a new approach of a semi-analytical thermal network for simulating the brake disc temperature with minimal effort is proposed.The thermal network is based on lumped parameters,using two thermal capacity nodes and a constant ambient temperature.Using semi-analytical correlations,the model can be adapted to different geometries and car lines effortlessly.The empirical parameters of the model result only from two standardized tests.These parameters are used to evaluate the estimation accuracy in real driving situations.Additionally,the adaptability is tested for two different car lines and four brake disc dimensions.These tests are initially performed with unchanged parameters and afterwards with refitted parameters.The model shows a good estimation for the tested load cases.Compared to the state of the art,the proposed model is less accurate than complex finite element method(FEM)models and computational fluid dynamic(CFD)approaches,but shows a higher accuracy and better adaptability than other lumped parameter models with comparable numerical effort.Hence,possible applications can be dimensioning the brake system in the development process of new car lines or a real-time simulation on the latest ECU in the vehicle.

Application of Neural Network to Downhill Shift Strategy for Automatic Transmission

＂ A method is proposed to estimate the longitudinal road gradient with a concept ＂general gradient force （GGF）＂, in which uncertain factors such as additional vertical load, road surface change, and strong wind are also taken into account. An adaptive downhill shift control system is then developed to help driver to use the engine brake with lower gears while downhill driving. In the adaptive system, a three-layer neural network is built to evaluate the necessity to make use of engine brake capability in current downhill situation, and the neural network is trained with samples from experienced drivers. Field test results of the adaptive system are introduced to verify the effectiveness of the approach mentioned above.

Optimal Energy-Efficient Operation of a Metro Train on a Long and Steep Downhill Segment

Because the standard four-stage operation and con-trol strategy cannot fully utilize the gravitational potential energy of a train operating on a long and steep downhill segment,this paper further improves the method for train operation and control strategy.The improved operation includes three stages of acceleration,coasting-speed limit cruising,and brak-ing.Taking the speed limit,time limit,and distance limit as the constraints,the coasting condition switching point,braking condition switching point,traction coefficient,and braking force coefficient are used as the decision variables.Then,an improved train traction energy consumption model is constructed,and an improved differential evolution algorithm is designed to solve this model.The improved method is used to simulate two long and steep downhill segments of the Nanning metro.The results show that the improved method can meet the requirements of speed limit,time limit,and distance limit.Compared with the standard four-stage operation,the improved train operation and control strategy can reduce train energy consumption by more than 40%on the two long and steep downhill segments;compared with other similar algorithms,the improved algorithm is more suitable for solving the model.

Adaptive hybrid global inversion algorithm

Most geophysical inversions can be regarded as multiparameter, nonlinear, and multiminimum discontinuous optimization problems. An adaptive hybrid global inversion algorithm based on simulated annealing, downhill simplex method, uniform design, and adaptive annealing rule is formulated. Numeral test and model computation show that this algorithm has very fast speed and high efficiency in searching for global minimum.