Meta‐analysis of the energy and protein requirements of hair sheep raised in the tropical region of Brazil

The objective of this study was to estimate, through mathematical models, energy and protein requirements for maintenance and gain of hair sheep raised in the tropical region of Brazil. To determine the equation parameters, a meta‐analysis of seven independent experiments of nutrient requirements was performed, comprising a total of 243 experimental units (animals), which were conducted under tropical conditions, using hair sheep in growing and finishing phases and endowed of the following quantitative data for each animal: body weight (BW ), empty body weight (EBW ), average daily gain (ADG ), empty body gain (EBG ), heat production (HP ), metabolizable energy intake (MEI ), retained energy (RE ), metabolizable protein intake (MPI ) and body protein content. The regression equations generated were as follows: for Net Energy for maintenance, (NE _m): ; for Net Energy for gain, (NE _g): ; for Metabolizable Protein for maintenance,(MP _m): MPI _(g/day) = 24.8470 (±7.3646) + 560.28 (±99.6582) × EBG _(kg/day); for Net Protein for gain, (NP _g): . The NE _m requirement was 0.246 MJ EBW^?0.75 day^?1. The metabolizable energy for maintenance requirement was 0.391 MJ EBW^?0.75 day^?1. Considering an ADG of 100 g, the NE _g requirement ranged from 0.496 to 1.701 MJ/day for animals with BW ranging from 10 to 40 kg respectively. The efficiencies of use of the metabolizable energy for maintenance and gain were 0.63 and 0.36 respectively. The MP _m requirement was 3.097 g EBW^?0.75 day^?1. Considering an ADG of 100 g, the NP _g requirement ranged from 12.4 to 10.5 g/day for animals with BW ranging from 10 to 40 kg respectively. The total metabolizable energy and protein requirements were lower than those reported by the NRC and AFRC systems. Thus, our results support the hypothesis that nutrient requirements of hair sheep raised in tropical regions differ from wool sheep raised in temperate regions. Therefore, the use of the equations designed in this study is recommended.     

广西5种人工林地土壤微生物数量及土壤酶活性分析

为当地珍贵速生树种人工林的发展及合理利用提供理论依据。分析广西5种珍贵树种人工林土壤微生物数量及土壤酶活性差异,以相同立地条件下12年生的黑木相思(Acacia melanoxylon)、老排(Mytilaria laosensis)、红椎(Castanopsis hystrix)、黧蒴椎(Castanopsis fissa)和火力楠(Michelia macelurei)人工纯林为研究对象,采用稀释平板涂布法和土壤酶活性测定法,测定和分析该5种人工林地土壤微生物数量及酶活性。结果表明:5种林地的土壤微生物总数和细菌数量大小均为:火力楠黧蒴锥红椎黑木相思米老排。但5种林地的土壤酶活性大小不一,蔗糖酶、脲酶、蛋白酶、酸性磷酸酶活性在5种林地之间的差异极其显著,而过氧化氢酶活性不显著。5种林地中土壤酶活性相对较强的是米老排人工林,较弱的是黑木相思林和火力楠林。土壤酶活性与微生物数量的相关分析表明,土壤中蔗糖酶活性与放线菌数量呈极显著正相关关系,其余相关性没有达到显著水平。     

Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

国土空间详细规划现状底图底数转换方法研究

统一底图底数是编制各类空间规划的重要前提和基础,第三次国土调查数据作为当前权威性最高、现势性最强的国土空间利用现状数据,所采用的工作分类与国土空间规划采用的用地用海分类存在较大差异。本文通过对工作分类和用地用海分类进行衔接分析,提出了基于第三次国土调查数据的国土空间详细规划现状底图底数转换的总体技术思路、关键技术方法。     

基于“3S”技术的辽宁省某尾矿库扩容工程生态影响预测与评价

以辽宁省某尾矿库为例,基于GIS技术,利用2010年的TM遥感影像及地形图,预测该尾矿库扩容后的生态影响。分析结果显示:尾矿库扩容工程对生态的影响主要体现在土地利用、植被、生态景观和地形地貌的变化4个方面。     

Bioinformatics Analysis of Bone Morphogenetic Protein 4 (BMP4) of Sheep

The assay was aimed to explore the biological characteristics of bone morphogenetic protein 4 (BMP4) of sheep,NCBI,DNAMAN DNAStar,TMHMM Server v.2.0,PsortⅡ,SignalP various bioinformatical softwares were used to speculate the physical and chemical properties,hydrophobic property,phosphorylation site,conservative structure domain,protein secondary structure of BMP4 protein.Also,the three-dimensional structure was forecasted with the SWISS-MODEL Workspace software.The results indicated that the BMP4 of sheep had high homologies with the BMP4 of various species.The encoded protein was a hydrophilic protein which was unstable.There was no transmembrane regions and it was likely to be located in the nucleus.What was more,there was signal peptide and eighteen phosphorylation sites.Through the forecast of functional domains,the protein had two functional domains,including the transforming growth factor-beta (TGF-beta) superfamily and TGF-beta propeptide superfamily.The result was consistent with the function of BMP4 gene family,it also demonstrated that BMP4 was a growth factor and it had the function of signal transduction.The amino acid homology between the predicted 3D structure of protein and template 3bmp.1.A was 88.29%.The bioinformatics analysis of BMP4 gene could provide reference for the further study in practice.     

基于贡献度随机森林模型的公司债信用风险实证分析

运用贡献度随机森林方法（CRF）方法探讨公司债财务指标比率与其违约率的关系.运用连续属性离散化方法（OB）进行财务指标最优降维；运用WOE变换进行模型变量约简.研究表明，CRF模型的分类性能显著优于其他模型，测试集评估总体正确率达90.47%，AUC统计量、AR比率及K-S值分别提升了2.6%、7.6%、4.38%，变量贡献度量化了各财务指标对违约率影响，为诠释随机森林预测机制提供了依据.     

基于Lasso和BP神经网络的组合预测及其应用——以居民消费支出预测为例

在变量选择的基础上，构建基于Lasso方法和BP神经网络的预测模型，并对我国城乡居民的消费支出进行预测，结果显示：基于Lasso方法和BP神经网络的组合预测精度要明显高于BP神经网络、Lasso方法的预测精度；在2014~2020年，我国农村居民消费增长率有所提升，城镇居民消费增长率减缓，城乡居民消费增长率之间的差距呈下降趋势，但短期内城乡居民消费差距依然难以缓和。     

花生黄曲霉生长预测模型的研究

通过对分离自花生的黄曲霉LYYSS03-3在不同温度(15-35℃)、不同相对湿度(水活度分别为0.5,0.7,0.9)下的菌落生长特性进行检测,采用Boltzmann和Logistic 模型对黄曲霉的生长曲线进行拟合,结果表明,在适宜温湿度阶段,花生黄曲霉的生长曲线更适合用Boltzmann模型拟合.     

土耳其斯坦裂体吸虫23kDa蛋白基因的序列分析及抗原表位预测

为研究土耳其斯坦裂体吸虫23 kDa蛋白的生物学特性,以土耳其斯坦裂体吸虫cDNA为模版,利用PCR对23 kDa基因进行扩增,并将其克隆到T-easy载体后进行序列测定。利用生物信息学对其结构、抗原指数进行分析,并对其抗原表位进行预测。序列分析结果表明,该虫体的23 kDa基因长度为657 bp,A+T含量为57.38%,与曼氏血吸虫、埃及血吸虫和日本血吸虫的23 kDa基因的相似性分别为85.24%、83.71%和81.89%。蛋白二级结构分析表明,23 kDa蛋白经过4次跨膜,主要由6个α-螺旋、3个β-折叠、7个β转角和若干个无规则卷曲构成。抗原表位预测结果表明,该蛋白有3个B细胞抗原表位。综合分析土耳其斯坦裂体吸虫23 kDa蛋白是一种较好的抗原分子,是土耳其斯坦裂体吸虫疫苗的重要候选分子。