Importance of Weighting for Multi-Variable Habitat Suitability Index Model: A Case Study of Winter- Spring Cohort of Ommastrephes bartramii in the Northwestern Pacific Ocean

Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.

HABITAT SUITABILITY INDEX MODELS: GREY HERON NESTING IN ZHALONG NATIONAL NATURE RESERVE

Grey heron (Ardea cimerca) is one kind of the great birds which are often seen in the northeast marsh area of P.R.China, and there are many grey herons to reproduce in Zhalong Nature Reserve from March to August annually. In this paper, through the inveingation of the grey herons nesting habitat and according to the water depth, vegetation type, cover density and plan heigh of the nesting place, the grey heron’s nesting habitat suitability index medes are established. The main model is s=(s1xs2xs3xs4)1/4,where s1 is the water depth suitability index, s2 is the vegetation type suitability index, s3 is the cover density index, sa is the plant height suitability index. These models provide a kind of reliable method for evaluating the habitat quality of the grey heron’s nesting.

Comparing of Aviation Network Structure of Mid-south,Northwest and Southwest of China Based on Hierarchical Index Model

In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.

ASYMPTOTIC PROPERTIES OF ESTIMATORS IN PARTIALLY LINEAR SINGLE-INDEX MODEL FOR LONGITUDINAL DATA

In this article, a partially linear single-index model /or longitudinal data is investigated. The generalized penalized spline least squares estimates of the unknown parameters are suggested. All parameters can be estimated simultaneously by the proposed method while the feature of longitudinal data is considered. The existence, strong consistency and asymptotic normality of the estimators are proved under suitable conditions. A simulation study is conducted to investigate the finite sample performance of the proposed method. Our approach can also be used to study the pure single-index model for longitudinal data.

An analysis of single-index model with monotonic link function

The single-index model with monotonic link function is investigated. Firstly, it is showed that the link function h（.） can be viewed by a graphic method. That is, the plot with the fitted response y on the horizontal axis and the observed y on the vertical axis can be used to visualize the link function. It is pointed out that this graphic approach is also applicable even when the link function is not monotonic. Note that many existing nonparametric smoothers can also be used to assess h（.）. Therefore, the I-spline approximation of the link function via maximizing the covariance function with a penalty function is investigated in the present work. The consistency of the criterion is constructed. A small simulation is carried out to evidence the efficiency of the approach proposed in the paper.

Statistical Diagnostic for Varying-Coefficient Single-Index Models Based on Empirical Likelihood Method

Varying-coefficient single-index model( VCSIM) avoids the so-called "curse of dimensionality " and is flexible enough to include several important statistical models. This paper considers statistical diagnosis for VCSIM. First,the parametric estimation equation is established based on empirical likelihood. Then,some diagnosis statistics are defined. At last, an example is given to illustrate all the results.

Simulating of marble subjected to uni-axial loading using index-parabola damage model

The limitations of several existing classical rock damage models were critically appraised. Thereafter, a description of a new model to estimate the response of rock was provided. The results of an investigation lead to the development and confirmation of a new index parabola damage model. The new model is divided into two parts, fictitious damage and real damage and bordered by the critical damage point. In fictitious damage, the damage variable follows the index distribution, while in the real damage a parabolic distribution is used. Thus, the so called index parabola damage model is derived. The proposed damage model is applied to simulate the damage procedure of marble under uni axial loading. The results of the tests show that the proposed model is in excellent agreement with experimental data, in particular the nonlinear characteristic of rock deformation is adequately represented. [

Growth models and site index table of natural Korean pine forests

According to the growth characteristics of natural Korean pine (Pinus Koraiensis) forests, 6 equations such as Chapman-Richards equation, Logistic equation, Power equation, and so on were selected to ftt for the growth modeIs for Korean pine forest. The growth models were developed based on 208 random trees and 24o dominant trees. Results show that the Chapman-Richards equation is the best model for estimating tree height by age and DBH, while the Parabola equation is fittest for predicting DBH by age or estimating age from DBH. The site index table of Korean pine forest was compiled by using the proportional method with the Chapman-Richards equation as the guide curve and vaIidated by accuracy test.

Study on comparison of different methods to calculating sensitivity index of Jensen model

Real coded Accelerating Genetic Algorithm （RAGA）, Chaos Algorithm （CA） were used to solve the sensitivity index of Jensen model which is one of models of crop water production function. After comparing with the outcome of Least Square Regression （LSR）, the result showed that RAGA not only had high accuracy and more effective, but also saved calculating time. The authors provides new effective methods for calculating index of crop water production function.

Variable Selection of Partially Linear Single-index Models

In this article, we study the variable selection of partially linear single-index model(PLSIM). Based on the minimized average variance estimation, the variable selection of PLSIM is done by minimizing average variance with adaptive l1 penalty. Implementation algorithm is given. Under some regular conditions, we demonstrate the oracle properties of aLASSO procedure for PLSIM. Simulations are used to investigate the effectiveness of the proposed method for variable selection of PLSIM.

Performance and Analysis of a Model for Describing Layered Leaf Area Index of Rice

Layered leaf area index （LAIk） is one of the major determinants for rice canopy. The objective of this study is to attain rice LAI k using morphological traits especially leaf traits that affected plant type. A theoretical model based on rice geometrical structure was established to describe LAI k of rice with leaf length （Li）, width （Wi）, angle （Ai）, and space （Si）, and plant pole height （H） at booting and heading stages. In correlation with traditional manual measurement, the model was performed by high R2-values （0.95-0.89, n=24） for four rice hybrids （Liangyoupeijiu, Liangyou E32, Liangyou Y06, and Shanyou 63） with various plant types and four densities （3 750, 2 812, 1 875, and 1 125 plants per 100 m2） of a particular hybrid （Liangyoupeijiu）. The analysis of leaf length, width, angle, and space on LAI k for two hybrids （Liangyoupeijiu and Shanyou 63） showed that leaves length and space exhibited greater effects on the change of rice LAI k . The radiation intensity showed a significantly negative exponential relation to the accumulation of LAI k , which agreed to the coefficient of light extinction （K）. Our results suggest that plant type regulates radiation distribution through changing LAI k . The present model would be helpful to acquire leaf distribution and judge canopy structure of rice field by computer system after a simple and less-invasive measurement of leaf length, width, angle （by photo）, and space at field with non-dilapidation of plants.

Study on the After-evaluation Index System and Evaluation Model of Industrial Estate Land Development Project

According to the modem management theories and the characters of industrial estate land development project, this paper studies the after-evaluation＇s content and method of industrial estate land development project and puts forward the index system of course after-evaluation, finance after-evaluation and society after-evaluation. Moreover, this paper also brings forward the method and model of synthetic after-evaluation.

Forecasting S&P 500 Stock Index Using Statistical Learning Models

Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.

Introducing a drought index to a crop model can help to reduce the gap between the simulated and statistical yield

A well-established and pre-calibrated crop model can normally represent the overall characteristics of crop growth and yield.However,it can hardly include all relevant factors that affect the yield,and usually overestimates the crop yield when extreme weather conditions occur.In this study,the authors first introduced a drought index(the Standardized Precipitation Evapotranspiration Index)into a process-based crop model(the Agro-C model).Then,the authors evaluated the model’s performance in simulating the historical crop yields in a double cropping system in the Huang-Huai-Hai Plain of China,by comparing the model simulations to the statistical records.The results showed that the adjusted Agro-C model significantly improved its performance in simulating the yields of both maize and wheat as affected by drought events,compared with its original version.It can be concluded that incorporating a drought index into a crop model is feasible and can facilitate closing the gap between simulated and statistical yields.

The Construction of Tiankeng Landscape Evaluation Model and the Index System

Based on researches done by other scholars,this paper summarized tiankeng's landscape characteristics and analyzed them.By referring to the methods and standards of tourism resources evaluation,tiankeng landscape evaluation model has been built.The evaluation index system was built in terms of the model and tiankeng's characters.After the evaluating factors and index were established,the weights of them have been figured out by AHP method.For the first time tiankeng has been studied from the view of landscape.However,this primary study about tiankeng landscape evaluation will offer reference for its tourism development and protection.It also lays the foundation for the construction of a better system.

Finite Mixture of Heteroscedastic Single-Index Models

In many applications a heterogeneous population consists of several subpopulations. When each subpopulation can be adequately modeled by a heteroscedastic single-index model, the whole population is characterized by a finite mixture of heteroscedastic single-index models. In this article, we propose an estimation algorithm for fitting this model, and discuss the implementation in detail. Simulation studies are used to demonstrate the performance of the algorithm, and a real example is used to illustrate the application of the model.

Study on Index System of the Environmental Change and Ecological Security for a River Basin Based on DPSIR Model

[ Objective] The research aimed to study index system of the environmental change and ecological security for a river basin based on DPSIR model. [Method] Based on considering each influence factor of the environmental change and ecological security for a river basin, DPSIR model as framework, the basic framework, principle and related method of index system of the environmental change and ecological security for a river basin under influence of the multi-level development were put forward. [ ]Result] Index system of the environmental change and ecological se- curity for a river basin based on DPSIR model included driving force indicator, pressure indicator, state indicator, influence indicator and response indicator. Each indicator type also had many sub-indicators. [ Conclusion] The research provided theoretical support and method reference for as- sessment of the ecological security and execution of the ecological environment management for a river basin in China.

Automatic Variable Selection for Single-Index Random Effects Models with Longitudinal Data

We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method shares some of the desired features of existing variable selection methods: the resulting estimator enjoys the oracle property;the proposed procedure avoids the convex optimization problem and is flexible and easy to implement. Moreover, we use the penalized weighted deviance criterion for a data-driven choice of the tuning parameters. Simulation studies are carried out to assess the performance of our method, and a real dataset is analyzed for further illustration.

Effect of successive irrigation of subarachnoid cavity on body temperature and cerebrospinal fluid-related index in suppurative meningitis model dogs

BACKGROUND： At present, suppurative meningitis is mainly treated through anti-infection with antibiotics, depressing encephalic pressure with mannitol , lowering body temperature with drugs , supporting treatment, etc. However, Jt takes a long course of treatment and has poor therapeutic effect. Successive irrigation of subarachnoid cavity maybe have better effect on suppurative meningitis.OBJECTIVE： We compared the successive irrigation of subbarachnoid cavity with routine therapeutic methods to observe the effect of successive irrigation of subarachnoid cavity on the body temperature, cerebrospinal fluid pressure, the number of white blood cell and the level of protein of suppurative meningitis dogs. DESIGN： A randomized and controlled animal experiment SETTING： Institute of Neuroscience, Taihe Hospital Affiliated to Yunyang Medical College MATERIALS： Totally 17 healthy adult male Beagle dogs, of common grade, weighing 9 to 10 kg, were involved in the experiment, and raised in the 20 ℃ temperature with relative humidity of 50% for 1 week. They were randomized into 3 groups： normal group （n=5）, control group （n=5） and irrigation group （n=6）. Artificial cerebrospinal fluid was prepared according to the level of glucose and chloride of cerebrospinal fluid of normal dogs, and then it was sterilized with high pressure. METHODS ： This experiment was carried out in the experimental animal center of Yunyang Medical College from April to August 2001. ① After the dogs were anesthetized,1 mL fresh staphylococcus aureus liquid [（1.5-1.6）× 10^9 L 1] was injected into medullary cistern to establish suppurative meningitis models. ② After models were successfully established, intravenous drip infusion of 1.2 ×10^6 U/（kg.d）, muscular injection of sulfadiazine sodium of 100 mg/（kg.d ）and intravenous injection of 200 g/L mannitol of 5 g/（kg .time） for 3 times a day were performed in the control group. The irrigation of subarachnoid meningitis was conducted in the irrigation group besides the routine treatments in the control group： Artificial cerebrospinal fluid was successively injected into the epidural catheter in the waist part. The mixtures of artificial cerebrospinal fluid and inflammatory cerebrospinal fluid flowed out incessantly from epidural catheter of medullary cistern. Irrigation was ended 48 hours later. Dogs were routinely raised in the control group. ③ From the first day after being modeled to the 14^th day after treatment, the rectal temperatures were daily measured in the morning, at noon and in the evening respectively, then the mean temperatures were calculated. From the 2^nd day after being modeled to the 14^th day after treatment, puncture at waist was given once, and the cerebrospinal fluid pressure, the number of white blood cells and the level of protein were measured. MAIN OUTCOME MEASURES ： The body temperature, cerebrospinal fluid pressure, the number of white blood cells and the level of protein were measured on suppurative meningitis model dogs. RESULTS＂ Totally 17 Beagle dogs were involved in this study.①The body temperatures of dogs were significantly reduced in the control group and in irrigation group on the 1^st day after treatment and lower than suppurative meningitis model dogs on the 2^nd day after being modeled （P 〈 0.05）. The body temperatures were gradually decreased in control group from the 2^nd day after being modeled to the 14^th day after treatment （P 〈 0.01）, but were significantly higher than those of dogs in normal group on the 14^th day after treatment （P 〈 0.05）. The body temperatures of dogs were gradually decreased in irrigation group on the 2^nd day or 3^rd day after treatment （P 〈 0.01） and then were close to the normal body temperature on the 14^th day after treatment. ②There was the same cerebrospinal fluid pressure in control group as in irrigation group on the 2^nd day after being modeled （P 〉 0.05）, but significantly decreased in two groups from the 1s＇ day or 2^nd day after treatment （P 〈 0.01）, and cerebrospinal fluid pressure was close to the normal level in irrigation group. Although the cerebrospinal fluid pressure raised a little on the 3^rd day or 4^th day after treatment in the irrigation group （P〈 0.05）, but recovered to the normal level on the 9^th day after treatment again. It decreased slowly in the control group and still was sig- nificantly higher than normal group on the 14^hd day after treatment （P〈 0.01 ）. ③No significant difference existed in number of white blood cell and the level of protein between control group and irrigation group on the 2^nd day following modeled. Both of them began to significantly decrease on the 1^st and 2^nd day after treatment （P 〈 0.01 ）. Although the number of white blood cell and the level of protein rebounded a little in irrigation group 3 or 4 days after treatment （P〈 0.05）, they were gradually decreased and recovered to normal levels on the 13^th day after treatment. The number of white blood cell and the level of protein slowly decreased in the control group compared with irrigation group and were still significantly higher than normal group on the 14^th day （P〈 0.01 ）. EONELUSEON ： Irrigation of subarachnoid cavity can decrease the body temperature, cerebrospinal fluid pressure, the number of white blood cells and the level of protein at early stage of suppurative meningitis, and the therapeutic effect is better than that of routine treatment.

Development of Empirical Models for the Estimation of CBR Value of Soil from Their Index Properties: A Case Study of the Ogbia-Nembe Road in Niger Delta Region of Nigeria

This study developed empirical-mathematical models to predict the California Bearing Ratio (CBR) using soil index properties in Ogbia-Nembe road in the Niger Delta region of Nigeria. The determination of CBR of soil is a laborious operation that requires a longer time and materials leading to increased cost and schedule;this can be reduced by adopting an empirical-mathematical model that can predict the CBR using other simpler soil index properties such as Plastic Limit (PL), the Liquid Limit (LL), the Plasticity Index (PI) and the Moisture Content (MC), which are less laborious and take lesser time to obtain. Thirteen models were developed to understand the relationship between these soil index properties: the independent variable and the California Bearing Ratio (CBR): the dependent variable;Six linear, Six quadratic and One multiple linear regression models were developed for this relationship. Analysis of variance (ANOVA) on the thirteen models showed that the Optimum Moisture Content (OMC) and the Maximum Dry Density (MDD) are better independent variables for the prediction of the CBR value of Ogbia-Nembe soil generating a quadratic model and a multiple linear regression model having a better coefficient of determination R2 = 0.96 and 0.94 respectively, mean square error (MSE) of 0.74 and 1.152 respectively with Root mean square errors of 0.861 and 1.073 accordingly. These models were used to predict the CBR of the soil. The CBR values predicted by the model were further compared with those of the actual experimental test and found to be relatively consistent with minimal variance. This establishes that CBR of any soil can be predicted from the Index Property of the soil and this is more economical and takes lesser time and can be universally adopted for soil investigation.