村干部禀赋结构对“精准扶贫”绩效影响的性量分析

基于2018年全国大学博士团暑期湘西扶贫调研及大数据,将村干部禀赋结构与贫困户数据运用Logit模型和Probit模型对特征变量作分类别、总体样本及边际效应回归分析,研究结果表明村干部禀赋结构对精准扶贫绩效影响显著。

脑电图反应性定量分析对脑梗死患者预后的预测价值

目的 探讨脑电图反应性定量(QEEG)分析对脑梗死患者预后的预测价值。方法 前瞻性选取2020年3月至2023年10月在湖州市第一人民医院就诊的脑梗死患者276例。根据治疗30 d后改良Rankin量表(mRS)评分将患者分为预后良好组和预后不良组。分析两组患者基线资料、实验室检查指标和QEEG参数。采用多因素Logistic回归分析影响预后的因素,绘制受试者工作特征(ROC)曲线分析QEEG参数对预后的预测价值。结果 随访期间,失访5例,最终纳入271例,其中预后良好组42例,预后不良组229例。两组美国国立卫生研究院卒中量表(NIHSS)、急性生理与慢性健康(APACHE Ⅱ)评分、格拉斯哥昏迷(GCS)评分、白细胞计数(WBC)、C反应蛋白(CRP)、D-二聚体水平、侧脑室受压、基底池受压、其他区域受累占比、DTABR、DAR及梗死体积差异均有统计学意义(均P<0.05);多因素Logistic回归分析显示:NIHSS评分、APACHE Ⅱ评分、GCS评分、白细胞计数、梗死体积、DTABR及DAR是脑梗死患者预后的影响因素(均P<0.05);ROC曲线显示DTABR、DAR预测脑梗死患者预后的去线下面积为0.893、0.834,高于其他指标。结论 DTABR及DAR是脑梗死患者预后的影响因素,且可预测脑梗死患者的预后。

自适性向量分析法在优化科技人才结构中的应用

根据优化人才结构产生协同效用的思想，提出了人才要素结构体系模型，运用自适性向量分析法对组织中的科技人才结构进行优化。

眼底造影荧光强度的计算机定量分析

目的 :建立眼底血管荧光造影 (fundusfluoresceinangiography ,FFA)中荧光强度定量图像分析方法 ,以评价眼底病变的病变程度和预后。方法 :分析湿性增龄性黄斑变性 (age -relatedmaculardegeneration ,AMD)患者FFA图像脉络膜新生血管膜 (choroidalneovascularizition ,CNV)渗漏强度在造影各期的变化趋势 ,分析正常眼底后极部 6.2 0mm2 区域的FFA荧光强度在造影各期的变化趋势 ,二者进行比较 ,验证荧光强度定量分析方法的客观性、有效性和实用性。结果 :湿性AMD患者的FFA图像CNV荧光素渗漏强度造影各期均显著高于正常眼底后极部 6.2 0mm2 区(P <0 .0 5或P <0 .0 1) ,动静脉期至 72 0秒差别具有非常显著性意义 (P <0 .0 1)。 180秒～ 3 0 0秒差别最明显。结论 :对眼底疾病的病变程度和预后进行评估 ,荧光强度计算机定量图像分析方法是比较客观。

多天线频谱共享CR-NOMA系统安全中断性能分析

认知无线电(CR)非正交多址接入(NOMA)网络(记为CR-NOMA)已是无线通信领域的研究热点之一。由于无线信道的开放性,使得无线网络的安全通信成为当前急需解决的问题。该文研究了频谱共享多天线CR-NOMA网络安全中断性能,首先分析了最优天线选择(OAS)方案的安全中断概率(SOP),并推导了其精确的闭合表达式。其次,分析了空时传输(STT)方案的SOP,并推导了其精确的闭合表达式。最后,对次用户两种方案的SOP渐近性能进行了分析,揭示了系统参数对SOP的影响。最后,采用Monte Carlo仿真验证了理论分析的正确性。研究发现,两种方案基站分别存在一个最优峰值发射功率,使得远距离次用户的安全中断性能最佳。仿真结果表明增大基站峰值发射功率,OAS方案的近距离次用户的SOP会始终优于STT方案,远距离次用户的SOP会劣于STT方案。

地形作战性能的研究

本文从地形在战争中的地位与作用出发,提出了地形作战性能概念,分析了它的内涵,并进行了层次区分,研究了分析地形作战性能的方法、步骤与手段,对辅助决策具有重要的意义。

A GIS-based Study on Suitability Estimation of Tea Cultivation in Qimen County

On the basis of data from Soil Test and Formula Fertilization project in Qimen county,we employed Geographic Information System Software ArcGIS 9.2 and CLRMIS（Cultivated Land Resource Management Information System at County Scale） to establish region-specific estimation index system for tea cultivation in Qimen County by determining the estimation units,and carried out quantitative estimation analysis on tea cultivation there via comprehensive evaluation indices for natural elements of cultivated land.The results showed that the highly suitable,suitable,reluctantly suitable and unsuitable acreages are 5 665.8,8 327.1,8 415.9 and 11 979.9 hm2 respectively,accounting for 24.0%,35.3%,35.7% and 5.1% of the total acreage of cultivated land.These results would facilitate the production of high yield and quality tea in Qimen County.

Modified algorithm of principal component analysis for face recognition

In principal component analysis （PCA） algorithms for face recognition, to reduce the influence of the eigenvectors which relate to the changes of the illumination on abstract features, a modified PCA （MPCA） algorithm is proposed. The method is based on the idea of reducing the influence of the eigenvectors associated with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation. The Yale face database and Yale face database B are used to verify the method. The simulation results show that, for front face and even under the condition of limited variation in the facial poses, the proposed method results in better performance than the conventional PCA and linear discriminant analysis （LDA） approaches, and the computational cost remains the same as that of the PCA, and much less than that of the LDA.

Finite element analysis of stress at implant-bone interface of dental implants with different structures

The effect of structure,elastic modulus and thickness of lower modulus layer in porous titanium implants on the stress distribution at the implant-bone interface was investigated.Three-dimensional finite element models of different titanium implants were constructed.The structures of the implants included the whole lower modulus style （No.1）,bio-mimetic style （No.2）,the whole lower modulus style in cancellous bone （No.3） and the whole dense style No.4.The stress distributions at bone-implant interface under static loading were analyzed using Ansys Workbench 10.0 software.The results indicated that the distribution of interface stress is strongly depended on the structure of the implants.The maximum stresses in cancellous bone and root region of implant No.2 are lower than those in the other three implants.A decrease in the modulus of the low modulus layer facilitates the interface stress transferring.Increasing the thickness of the low modulus layer can reduce the stress and induce a more uniform stress distribution at the interface.Among the four implants,biomimetic style implant No.2 is superior in transferring implant-bone interface stress to surrounding bones.

Analysis of Correlation between Yield and Quality Traits of Quality Hybrid Rapeseed

[Objective] This study aimed to investigate the correlation between yield and quality traits of rape. [Method] Taking ＂Sanbei 98＂ and ＂Youyan 599＂ as ex- periment materials, correlation between yield and quality traits of Brassica napus L. cultivars was explored by orthogonal rotation method. [Result] The results showed that： 1 In both the two varieties-Sanbei98 and Youyan599, erucic acid content had the largest coefficient of variation, but its average content was lower than 2% in both the two varieties （0.90% in Sanbei98 and 1.24% in Youyan599）, and the palmitic acid content had the smallest coefficient of variation. 2 In terms of the dif- ferences in quality traits at different yield levels, only the mean of eicosenoic acid content revealed significant difference in Sanbei98, and only the mean of seed-pro- tein content revealed significant difference in Youyan599, and there was no signifi- cant difference in any combined quality traits in both the two varieties. 3 The yield was negatively correlated with the erucic acid content or oil content, and posi- tively correlated with the content of seed-protein, linoleic acid, or linolenic acid, and the coefficient of correlation between the yield and either of the contents of glucosi- nolates, oleic acid, palmitic acid, stearic acid, and eicosenoic acid was smaller. ~, when the yield of a variety increased considerably, there was a certain decreasing trend in erucic acid content, oil content, the total amount of erucic chain fatty acids （El ＆ Er）, while there was an increasing trend in seed-protein content, linoleic acid content, linolenic acid content, saturated fatty acids （SFA）, the total amount of fat and protein （P ＆ F）, unsaturation index （IUFA）, unsaturated fatty acids （UFA）, the total amount of 18 carbon fatty acids （18-C FA）, unsaturated fatty acids [UFA/（Ei ＆ Er） ], and the sum of oleic acid and linoleic acid （OI ＆ Li）. 5 When the seed-pro- tein content is increased, the quality of rape oil cake is also improved; when the unsaturated index is increased, the oil stability is decreased. The increase in the total amount of unsaturated fatty acids, oleic acid and linoleic acid helps to increase in the total amount of fatty acids absorbed by human bodies. [Conclusion] This study provides a theoretical foundation for the cultivation of high-yielding and top- quality hybrid rape cultivars.

Correlations Between Plant Biomass and Soil Respiration in a Leymus chinensis Community in the Xilin River Basin of Inner Mongolia

This paper reports on two years of measurement of soil respiration and canopy-root biomass in a Leymus chinensis community in the Xilin River basin of Inner Mongolia. Correlations between components of plant biomass and soil respiration rates were examined. From respiration data based on CO2 uptake by NaOH and corresponding root biomass values for each run of 10 plots, a linear regression of CO2 evolution rates on root dry weights has been achieved for every ten days. By applying the approach of extrapolating the regressive line to zero root biomass, the proportion of the total soil respiration flux that is attributable to live root respiration was estimated to be about 27% on average, ranging from 14% to 39% in the growing season in 1998. There were no evident relations between the total canopy biomass or root biomass and CO2 evolution rates, but a significant exponential relation did exist between tire live-canopy biomass and CO2 evolution rates.

Qualitative and Quantitative Analysis of Rhizoma of Polygonum cuspidatum

Aim To establish reliable methods for evaluating the quality of rhizoma of Polygonum cuspidatum( Huzhang in Chinese). Methods TLC and HPLC were employed for the chemical identification and content determination,respectively. Results A qualitative TLC method and a quantitative HPLC method with piceid as the reference substance were established, respectively. With piceid as the reference substance and ethyl acetate-methanol-formic acid-water ( 19:3:0.5:1) as the mobile phase, a TLC method for the identification of Huzhang from the commonly used crude drugs of the same family was also set up. Conclusion The established TLC method can reasonably appraise the quality of the drug and easily distinguish Huzhang from the other commonly used crude drugs of the same family. The HPLC method for determining piceid is simple, reproducible, accurate, and feasible.

Conserved quantities from Lie symmetries for nonholonomic systems

This paper presents a new method to seek the conserved quantity from a Lie symmetry without using either Lagrangians or Hamiltonians for nonholonomic systems. The differential equations of motion of the systems are established. The definition of the Lie symmetrical transformations of the systems is given, which only depends upon the infinitesimal transformations of groups for the generalized coordinates. The conserved quantity is directly constructed in terms of the Lie symmetry of the systems. The condition under which the Lie symmetry can lead to the conserved quantity and the form of the conserved quantity are obtained. Finally, an example is given to illustrate the application of the result.

Discovering hidden information of gene ontology based on complex networks analysis

To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empirical studies of the gene ontology with various perspectives, this paper shows that the whole gene ontology displays the same topological features as complex networks including ＂small world＂ and ＂scale-free＂,while some sub-ontologies have the ＂scale-free＂ property but no ＂small world＂ effect.The potential important terms in an ontology are discovered by some famous complex network centralization methods.An evaluation method based on information retrieval in MEDLINE is designed to measure the effectiveness of the discovered important terms.According to the relevant literature of the gene ontology terms,the suitability of these centralization methods for ontology important concepts discovering is quantitatively evaluated.The experimental results indicate that the betweenness centrality is the most appropriate method among all the evaluated centralization measures.

生物样品定量分析方法验证中试验样品再分析的意义和对策

目的介绍试验样品再分析(incurred sample reanalysis,ISR)的法规要求、意义和对策。方法综述国际上关于试验样品再分析的指导原则、研究论文和统计数据,通过实例来总结试验样品再分析失败的原因及预防措施。结果与结论试验样品再分析有助于改善生物分析方法的重现性,已经成为法规生物样品分析的一项重要内容。采取适当的对策,可以防止试验样品再分析失败造成的损失。

Correlation and Principal Component Analysis on Main Agronomic Traits of New Waxy Corn Varieties

[Objective] This study was conducted to provide certain theoretical reference for the comprehensive evaluation and breeding of new fresh waxy corn vari- eties. [Method] With 5 good fresh waxy corn varieties as experimental materials, correlation analysis and principal component anatysis were performed on 13 agronomic traits, i.e., plant height, ear position, ear weight, ear diameter, axis diameter, ear length, bald tip length, ear row number, number of grains per row, 100-kernel weight, fresh ear yield, tassel length, and tassel branch number. [Result] The principal component analysis performed to the 13 agronomic traits showed that the first three principal components, i.e., the fresh ear yield factors, the tassel factors and the bald top factors, had an accumulative contribution rate over 87.2767%, and could basically represent the genetic information represented by the 13 traits. The first principal component is the main index for the selection and evaluation of good corn varieties which should have large ear, large ear diameter but small axis diameter, i.e., longer grains, larger number of grains per ear, higher, 100-grain weight and higher plant height. As to the second principal component, the plants of fresh corn varieties are best to have longer tassel and not too many branches, and under the premise of ensuring enough pollen for the female spike, the varieties with fewer tassel branches shoud be selected as far as possible. From the point of the third principal component, bald tip length affects the marketing quality of fresh corn, and during fariety evaluation and breeding, the bald top length should be control at the Iowest standard. [Conclusion] The fresh ear yield of corn is in close positive correlation with ear weight, 100-grain weight, ear diameter, number of grains per row and ear length, and plant height also affects fresh ear yield.

Determination of Melamine by Infrared Spectroscopy Based on Nonlinear Modeling

[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According to dynamics,mathematical modeling and optimization theory,linear and nonlinear models were respectively set up by taking an absorption peak of 1 550 cm-1 as characteristic absorption peak. [Result] The correlation coefficient of nonlinear model was 0.922 7 and the recovery was 96%,which showed that the nonlinear model was more accurate than linearity model with correlation coefficient of 0.904 9 and recovery of 557%. [Conclusion] It is feasible to determine melamine content by using the nonlinear model quantitatively.

Correlation Analysis and Path Analysis between Yield and Yield-Related Traits of Yunmai 52

[Objective] This study was tween yield-related traits and yield of conducted to understand the relationship be- Yunmai 52 which is a high-quality high-yield multi-resistant new wheat variety, and make contribution of yield-related traits to the yield of Yunmai 52 clear. [Method] Wheat variety regional trial data in Yunnan Province in 2005-2007 were subjected to correlation analysis and path analysis in the paper. [Result] Correlationanalysis showed that the yield of Yunmai 52 was in- very significant positive correlation with spikelet number per ear, maximum tiller number and grains per ear （r=0.726^＊＊, 0.717^＊＊ and 0.695^＊＊, respectively）, in signif- icant positive correlation with 1 000-grain weight （r=0.491^＊）, but in significant nega- tive correlation with sterile spikelet number per ear, and in non-significant correlation with basic seedlings, effective ears and percentage of ear bearing tillers. Partial correlation analysis showed that the yield of Yunmai 52 was in very significant posi- tive correlation with spikelet number per ear （r=0.711^＊＊）, significant positive correla- tion with 1 000-grain weight （r=0.641 =）, but in non-significant correlation with other 6 traits. Path analysis showed that spikelet number per ear （P=-0.595）, maximum tiller number （P=0.462） and t 000-grain weight （P=0.263） had more contribution to yield of Yunmai 52. [Conclusion] Therefore, in extension and application of Yunmal 52 that is a high-quality high-yield multi-resistant new wheat variety, supply of fertilizer and water should be increased in tillering stage and jointing stage, to ensure its characteristics of high tilledng ability and large ear, as well as high 1 000-grain weight, and coordinated development of other yield-related traits is beneficial to im- provement of yield of Yunmai 52.

Predicting pillar stability for underground mine using Fisher discriminant analysis and SVM methods

The purpose of this study is to apply some statistical and soft computing methods such as Fisher discriminant analysis （FDA） and support vector machines （SVMs） methodology to the determination of pillar stability for underground mines selected from various coal and stone mines by using some index and mechanical properties, including the width, the height, the ratio of the pillar width to its height, the uniaxial compressive strength of the rock and pillar stress. The study includes four main stages： sampling, testing, modeling and assessment of the model performances. During the modeling stage, two pillar stability prediction models were investigated with FDA and SVMs methodology based on the statistical learning theory. After using 40 sets of measured data in various mines in the world for training and testing, the model was applied to other 6 data for validating the trained proposed models. The prediction results of SVMs were compared with those of FDA as well as the measured field values. The general performance of models developed in this study is close; however, the SVMs exhibit the best performance considering the performance index with the correct classification rate Prs by re-substitution method and Pcv by cross validation method. The results show that the SVMs approach has the potential to be a reliable and practical tool for determination of pillar stability for underground mines.

Application of support vector machine in trip chaining pattern recognition and analysis of explanatory variable effects

In order to improve the accuracy of travel demand forecast and considering the distribution of travel behaviors within time dimension, a trip chaining pattern recognition model was established based on activity purposes by applying three methods： the support vector machine （SVM） model, the radial basis function neural network （RBFNN） model and the multinomial logit （MNL） model. The effect of explanatory factors on trip chaining behaviors and their contribution to model performace were investigated by sensitivity analysis. Results show that the SVM model has a better performance than the RBFNN model and the MNL model due to its higher overall and partial accuracy, indicating its recognition advantage under a smai sample size scenario. It is also proved that the SVM model is capable of estimating the effect of multi-category factors on trip chaining behaviors more accurately. The different contribution of explanatory, factors to trip chaining pattern recognition reflects the importance of refining trip chaining patterns ad exploring factors that are specific to each pattern. It is shown that the SVM technology in travel demand forecast modeling and analysis of explanatory variable effects is practical.