Modeling Rice rgMT as a Plant Metallothionein-Like Protein by the Distance Geometry and Homology Methods

Rice metallothionein-like protein (rgMT) shows characteristics of a three-section pattern composed of two highly conserved cysteine rich (CR) domains in the terminals and a spacer without cysteine (cys) residues in the center of the molecule. In this paper, the two CR domains and the spacer region were modeled by the distance geometry and homology methods separately. For the CR domains, twenty random models were generated for each cys combination based on the constraint conditions of CXC (C represents cys, X represents any amino acid other than cys), and CXXC motifs and a metal-sulfur chelating cluster. Four models for the N-terminal and two for C-terminal CR domain containing metal chelating structures formed by different combinations of cys were selected from 900 possible conformations. The GOR method was used to predict the secondary structure of the spacer region and its model was built by the homology method. After three parts of the protein were modeled, they were connected to form a three-dimensional structure model of rgMT. The whole conformation showed that rgMT could form two independent metal-sulfur chelating structures connected by a spacer peptide, without a structural or energy barrier for them to form two independent metal-chelating clusters just as mammalian metallothionein (MT) proteins. As all plant metallothionein-like (MT-L) proteins have the same primary structural characteristic, two CR domains connected by a spacer region, and many have the same cys arrangement pattern as rgMT, the three-dimensional structure model of rgMT will provide an important reference for the structural study of other plant MT-L proteins.

A prediction model for horizontal run-out distance of landslides triggered by Wenchuan earthquake

The peak ground acceleration （PGA）, the volume of a sliding mass V, the height of a mountain HL and the slope angle θ of a mountain are four important parameters affecting the horizontal run-out distance of a landslide L. Correlations among them are studied statistically based on field investigations from 67 landslides triggered by the ground shaking and other factors during the Wenchuan earthquake, and then a prediction model for horizontal run-out distance L is developed in this study. This model gives due consideration to the implications of the above four parameters on the horizontal run-out distance L and the validity of the model is verified by the Donghekou and Magong Woqian landslides. At the same time, the advantages of the model are shown by comparing it with two other common prediction methods. The major findings drawn from the analyses and comparisons are： （1） an exponential relationship exists between L and log V, L and log HL, L and log PGA separately, but a negative exponential relationship exists between L and log tan0, which agrees with the statistical results; and （2） according to the analysis results of the relative relationship between the height of a mountain （H） and the place where the landslides occur, the probabilities at distances of2H/3-H, H/3-2H/3, and O-H/3 are 70.8%, 15.4%, and 13.8%, respectively, revealing that most landslides occurred at a distance of H/2-H. This prediction model can provide an effective technical support for the prevention and mitigation of landslide hazards.

Distance Measurement Model Based on RSSI in WSN

The relationship between RSSI (Received Signal Strength Indication) values and distance is the foundation and the key of ranging and positioning technologies in wireless sensor networks. Log-normal shadowing model (LNSM), as a more general signal propagation model, can better describe the relationship between the RSSI value and distance, but the parameter of variance in LNSM is depended on experiences without self-adaptability. In this paper, it is found that the variance of RSSI value changes along with distance regu- larly by analyzing a large number of experimental data. Based on the result of analysis, we proposed the relationship function of the variance of RSSI and distance, and established the log-normal shadowing model with dynamic variance (LNSM-DV). At the same time, the method of least squares(LS) was selected to es- timate the coefficients in that model, thus LNSM-DV might be adjusted dynamically according to the change of environment and be self-adaptable. The experimental results show that LNSM-DV can further reduce er- ror, and have strong self-adaptability to various environments compared with the LNSM.

Enhancing Collaborative Filtering via Topic Model Integrated Uniform Euclidean Distance

Recommendation system can greatly alleviate the "information overload" in the big data era. Existing recommendation methods, however, typically focus on predicting missing rating values via analyzing user-item dualistic relationship, which neglect an important fact that the latent interests of users can influence their rating behaviors. Moreover, traditional recommendation methods easily suffer from the high dimensional problem and cold-start problem. To address these challenges, in this paper, we propose a PBUED(PLSA-Based Uniform Euclidean Distance) scheme, which utilizes topic model and uniform Euclidean distance to recommend the suitable items for users. The solution first employs probabilistic latent semantic analysis(PLSA) to extract users' interests, users with different interests are divided into different subgroups. Then, the uniform Euclidean distance is adopted to compute the users' similarity in the same interest subset; finally, the missing rating values of data are predicted via aggregating similar neighbors' ratings. We evaluate PBUED on two datasets and experimental results show PBUED can lead to better predicting performance and ranking performance than other approaches.

The walking distance decay law of amenity selection based on binary logistic model

The current measuring methods of walkability,such as the walk score,consider that walking distance decay laws for all amenities are the same,which is not applicable to typical communities in China with plentiful resources.Therefore,the walking distance decay laws of multi-type and multi-scale facilities are studied.Firstly,based on the residents'amenity selection survey,the walking distance decay law of residents'choice of amenity was studied from three aspects,including the law of all amenities,the laws of different types of amenities and the laws of different scales of amenities.It was proved that the walking distance decay laws of different kinds of amenities showed a significant difference.Secondly,different amenities'acceptable walking distance and optimum walking distance were obtained according to previous studies and the decay curve.Amenities with higher attraction and/or a larger scale showed a longer acceptable walking distance and optimum walking distance.Finally,the binary logistic model was used to describe the relationships between walking distance,amenity type,amenity scale and the probability of one amenity being selected,the prediction accuracy of which reached 80.4%.The calculated probability obtained from the model can be used as the decay coefficient of amenities in the measurement of walkability,providing a reference for the site selection and evaluation of amenities.

Regional landslide hazard assessment based on Distance Evaluation Model

There are many factors influencing landslide occurrence.The key for landslide control is to confirm the regional landslide hazard factors.The Cameron Highlands of Malaysia was selected as the study area.By bivariate statistical analysis method with GIS software the authors analyzed the relationships among landslides and environmental factors such as lithology,geomorphy,elevation,road and land use.Distance Evaluation Model was developed with Landslide Density(LD).And the assessment of landslide hazard of Cameron Highlands was performed.The result shows that the model has higher prediction precision.

Model tests on uplift capacity of double-belled pile influenced by distance between bells

To optimize the distance between the bells in pile design,this paper reports a series of small scale tests on the uplift capacity of double belled piles embedded in dry dense sand considering different bell space ratios.Finite element modelling is also performed to evaluate the range of soil failure around the piles during pile uplift displacement.Test results show that when bell space ratio is 6 or 8,the uplift capacity reaches the peak value.The upper bell bears more load than the lower one for the piles with bell space ratio less than 6,while the lower bell bears more load than the upper one for the piles with bell space ratio larger than 8.

Long-distance propagation of pseudo-partially coherent Gaussian Schell-model beams in atmospheric turbulence

Propagation properties of spatially pseudo-partially coherent Gaussian Schell-model beams through the atmo- spheric turbulence over a long-distance uplink path are studied by numerical simulation. A linear coordination trans- formation is introduced to overcome the window effect and the loss-of-resolution problem. The beam spreading, beam wandering, and intensity scintillation as functions of turbulence strength, source correlation length, and change fre- quency of random phase that models the partial coherence of the source are analyzed. It is found that the beam spreading and the intensity scintillation of the partially coherent beam are less affected by the turbulence than those of the coherent one, but it suffers from a more severe diffractive effect, and the change frequency of random phase has no evident influence on it. The beam wandering is insensitive to the variation of source correlation length, and decreases firstly then goes to a fixed value as the change frequency increases.

Time-Domain Protection for Transmission Lines Connected to Wind Power Plant based on Model Matching and Hausdorff Distance

The system impedance instability,high-order harmonics,and frequency offset are main fault characteristics of wind power system.Moreover,the measurement angle of faulty phase is affected by rotation speed frequency component,which causes traditional directional protections based on angle comparison between voltage and current to operate incorrectly.In this paper,a time-domain protection for connected to wind power plant based on model matching is proposed,which compares the calculated current and the measured current to identify internal faults and external faults.Under external faults,the calculated current and measured current waveform are quite similar because the protected transmission lines is equivalent to a lumped parameter model and the model itself is not damaged.However,the similarity of calculated current and measured current is quite low,due to destroyed integrity of model under internal faults.Additionally,Hausdorff distance is introduced to obtain the similarity of the calculated current and measured current.Since the proposed protection scheme is applied in time domain,it is independent from current frequency offsets of wind energy system,high-order harmonics,and system impedance variations.Comprehensive case studies are undertaken through Power Systems Computer Aided Design(PSCAD),while simulation results verify the accuracy and efficiency of the proposed approach in fault identification.

Calibration of parallel kinematics machine using generalized distance error model

This paper focus on the accuracy enhancement of parallel kinematics machine through kinematics calibration. In the calibration processing, well-structured identification Jacobian matrix construction and end-effector position and orientation measurement are two main difficulties. In this paper, the identification Jacobian matrix is constructed easily by numerical calculation utilizing the unit virtual velocity method. The generalized distance errors model is presented for avoiding measuring the position and orientation directly which is difficult to be measured. At last, a measurement tool is given for acquiring the data points in the calibration processing. Experimental studies confirmed the effectiveness of method. It is also shown in the paper that the proposed approach can be applied to other typed parallel manipulators.

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

Solid model edit distance: a multi-application and multi-level schema for CAD model retrieval

We present the solid model edit distance(SMED),a powerful and flexible paradigm for exploiting shape similarities amongst CAD models.It is designed to measure the magnitude of distortions between two CAD models in boundary representation(B-rep).We give the formal definition by analogy with graph edit distance,one of the most popular graph matching methods.To avoid the expensive computational cost potentially caused by exact computation,an approximate procedure based on the alignment of local structure sets is provided in addition.In order to verify the flexibility,we make intensive investigations on three typical applications in manufacturing industry,and describe how our method can be adapted to meet the various requirements.Furthermore,a multilevel method is proposed to make further improvements of the presented algorithm on both effectiveness and efficiency,in which the models are hierarchically segmented into the configurations of features.Experiment results show that SMED serves as a reasonable measurement of shape similarity for CAD models,and the proposed approach provides remarkable performance on a real-world CAD model database.

基于一种距离相关的超高维生存数据Model-Free特征筛选

随着大数据时代的来临,数据维度爆炸式增长,超高维数据的降维问题逐渐成为众多研究领域的热点话题。由于响应变量通常存在右删失,处理超高维完全数据的降维方法在右删失数据中将不再适用。本研究提出一种新的基于距离相关能有效处理超高维右删失数据的特征筛选方法。首先利用距离相关系数计算每个协变量对响应变量的边际效应,建立与该系数有关的筛选指标,然后再根据事先确立的筛选准则进行特征筛选。提出的特征筛选方法不依赖任何模型结构假定,因此可以有效避免模型指定错误带来的不良后果。此外,该方法采用的距离协方差估计量是总体距离协方差的一个无偏估计,统计准确性和计算精度高。模拟和实证研究表明,提出的方法能在保留所有重要变量的前提下快速剔除与响应变量相关程度较弱的协变量,从而达到降低参数维数的目的。

Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

The projection matrix model is used to describe the physical relationship between reconstructed object and projection.Such a model has a strong influence on projection and backprojection,two vital operations in iterative computed tomographic reconstruction.The distance-driven model（DDM） is a state-of-the-art technology that simulates forward and back projections.This model has a low computational complexity and a relatively high spatial resolution;however,it includes only a few methods in a parallel operation with a matched model scheme.This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations.Our proposed model has been implemented on a GPU（graphic processing unit） platform and has achieved satisfactory computational efficiency with no approximation.The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop,respectively,with an image size of 256×256×256 and 360 projections with a size of 512×512.We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation.The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction.

Comparison of Analyses of Genetic Structure among Chinese Indigenous Chicken Breeds using Distance-based and Model-based Methods

The Nei's improved genetic distance(DA)and gene flow(Nm)were measured using sixteen microsatellite markers.Dendograms based on DA genetic distance using the neighbor-joining(NJ)method and STRUCTURE program were constructed to analyze the genetic structure and relationship among 10 Chinese indigenous chicken breeds.The results showed that dendograms of DA genetic distance using the NJ method divided the 10 chicken breeds into two main clusters;one consisted of breeds of low weight body(CHA,TTB,XIA,GUS and BAI),the other contained heavier breeds(LAN,DAG,YOU,XIS and LUY).In the lighter breeds,TIB and CHA clustered together,as did XIA and GUS.In the heavier breeds,XIS and LUY was clustered together in one branch,but LAN,DAG and YOU clustered in independent branches.The results were consistent with Nm estimates among the 10 indigenous chicken breeds.The STRUCTURE program properly inferred the presence of genetic structure despite not pre-defining the origin of individuals.The genetic cluster inferred by STRUCTURE was basically the same as that from the DA distance clustering method.An advantage of the STRUCTURE program was its ability to identify the migrants and admixed individuals in the 10 chicken populations;this could not be achieved by use of the DA distance clustering method.

Simplifying Triangular Mesh Model by Modified Distance Criterion

Model simplification is used in a variety of disciplines, such as vir'tUal reality, CAD anddynamic simulation. The method of model simplification is an important problem. This paperpresents a new method to delete vertex from mesh model for simplification, in which the modifieddistance actS as deletion criterion. In order to improve the mesh quality, the poyer uses an optimalmethod based on swapping diagonal for retriangulating the local polygon. By the method. thesimplified model can approximate original model very well. An example to illustrate the efficiencyof the method is given.

无线传感器网络动态加权DV-Distance算法

无线传感器网络DV-Distance定位算法,采用未知节点与锚节点间的累计跳段距离代替欧式距离计算节点位置,存在较大的定位误差。针对这一问题,提出一种动态加权DV-Distance改进定位算法,基于未知节点的修正模式,保证定位网络中每个未知节点具有不同的修正系数;通过动态加权修正模型,用锚节点间距离、跳数等信息计算修正系数,采用动态加权的方法将不同方向上的修正系数进行整合,修正未知节点与锚节点间累计跳段距离,提高算法的定位精度。通过仿真验证了算法具有更高的定位精度;并进一步通过实验验证了算法的有效性和可行性。

Characteristics and influencing factors of proximity distance index on the northern Shaanxi Loess Plateau in China

Topographic feature points and lines are the framework of topography,and their spatial distance relationship is an breakthrough in the study of topographical geometry,internal structure and development level.Proximity distance(PD)is an indicator to describe the distance between the gully source point(GSP)and the watershed boundary.In the upstream catchment area,PDs can be expressed by the streamline proximity distance(SPD),as well as by the horizontal proximity distance(HPD)and the vertical proximity distance(VPD)in the horizontal and vertical dimensions,respectively.The series of indicators(e.g.,SPD,HPD and VPD)are important for quantifying the geomorphological development process of a loess basin because of the headward erosion of loess gullies.In this study,the digital elevation model data with 5 m resolution and a digital topographic analysis method are used for the statistical analyses of the SPD,VPD and HPD in 50 sample areas of 6 geomorphic types in the Loess Plateau of northern Shaanxi.The spatial characteristics and the influencing factors are also analysed.Results show that:1)Central tendencies for the HPDs and the VPDs for the whole study area and the six typical loess landforms are evident.2)Spatial patterns of the HPDs and the VPDs exhibit evident trends and zonal distributions over the whole study area.3)The HPDs have a strong positive correlation with gully density(GD)and hypsometric integral.The VPDs also correlates with GD to an extent.Vegetation cover,mean annual precipitation and loess thickness have stronger effects on the VPD than on the HPD.