大型渡槽槽身施工技术进展

阐述我国大型渡槽槽身施工技术的若干最新进展，并探讨了大型梁式渡槽槽身施工中的支撑浇筑系统、伸缩缝止水、预应力张拉等问题，提出大型渡槽槽身施工中支撑系统、施工方法、预应力张拉次序的选择，可供实际工程施工借鉴。     

畦田灌溉水流演进计算简化模型研究

在对水量平衡模型进行修改的基础上,结合零惯量运动方程,以水量平衡方程为基础,对畦灌水流演进模型的结构进行了研究。应用无因次系统模型,求得了模型的显式和隐式解。该模型可以用来计算畦灌水流演进距离。对山东省陈垓引黄灌区畦灌水流演进计算结果表明,该模型比以往使用的模型简单,计算精度与较复杂的零惯量模型的计算精度相当。模型计算不需编程,可以用手算完成全部计算过程,解决了传统的水量平衡模型无法解决的问题。     

基于烟叶致香成分建立烤烟香型分类模型方法研究

为筛选出基于烟叶致香成分数据建立烤烟香型分类的最优模型,以便于较好地对烤烟的香型进行正确分类。首先对142 个烤烟烟叶样品中的45 个指标采用行业标准进行检测,然后采用逐步回归法筛选出14 个烟叶致香成分,依据这14 个指标采用判别分析法、Logistic 回归、高斯混合模型、分类树、K最邻近法、人工神经网络和支持向量机7种方法进行建模。通过对不同方法建立的模型采用100次随机抽取训练集样本和测试样本计算错误分类率,选择错误分类率较低的模型作为优选模型。结果表明,线性判别法和高斯混和模型建立的2 种香型函数能较好地对未知样品的香型进行正确分类,且效果较好（正确率可达90%以上）。研究筛选出的2种优选模型对于烤烟香型分类研究具有一定的应用价值。     

自然植被净第一性生产力模型的改进

在Miami模型和Thornthwaite模型的基础上，采用直接搜索法改进了自然植被净第一性生产力模型，该模型优于Miami模型和Thornthwaite模型，便于估算自然植被的净第一性生产力，为合理利用气候资源，充分发挥气候生产潜力，最大限度地提高植物的产量提供了理论依据。     

采摘机器人位置校正方法研究——基于无线传感网络和超带宽调频方法

超带宽雷达是新近出现的一种高分辨率雷达,当信号带宽和其发射中心频率的比大于0.25时,就被称作超带宽,带宽越大,雷达对目标的分辨能力越高。超带宽雷达具有高分辩能力,如果将其使用在采摘机器人定位导航系统中,可以有效地提高采摘机器人的定位导航精度和效率。为此,提出了一种基于无线传感网络和超带宽调频技术的采摘机器人位置校正方法,并以实际采摘环境作为研究对象,对采摘机器人的位置校正过程进行了测试。测试结果表明:采用超带宽调频无线传感网络方法,定位校正精度要高于传统的定位算法,且定位效率高,对于新型自动化采摘作业机器人的研究具有重要的指导意义。     

Technical efficiency of different farm sizes for tilapia farming in China

China is the world's largest tilapia producer. This study uses the stochastic frontier function in the Cobb–Douglas model to evaluate a production frontier for tilapia aquaculture and analyses the relationship between farm size and production efficiency in China. A random sample of 300 tilapia farmers was surveyed in the main tilapia‐producing areas to study their economic efficiencies. The percentage distribution of tilapia farm technical efficiency was determined, with an average efficiency of 79%, which showed that the sample tilapia farmers operate at 21% below the production frontier and hence that they still have a chance to achieve targeted yields. The technical efficiencies of two categories (≤1 ha and >1 ha) were 78.82% and 79.27% respectively. A second‐stage analysis investigated the relationship between farm size and technical efficiency and showed a positive relationship between farm size and production efficiency based on the ordinary least‐squares model. The optimal farm size was found to be 7.50 ha. This study proposes strategies such as enlarging the farming scale moderately, thereby achieving the advantage of economies of scale, and enhancing the competitiveness of the tilapia industry in China.     

汉语自动分词中的神经网络技术研究

本文讨论了人工神经网络技术应用于汉语自动分词的映射模型和性能，着重分析网络结构和学习算法对歧义词切分的影响，在大量仿真实验的基础上，对其性能进行评价。     

奶牛杂交群体及其遗传评估的模拟研究

为验证在奶牛杂交群体中将品种组成和杂合度作为协变量的遗传评估理论,为奶牛杂交模式选择和杂交群体遗传评估等实际问题提供理论依据,结合我国奶业现状,本研究模拟了在低产荷斯坦牛群引入法系蒙贝利亚牛、德系西门塔尔牛进行杂交,采用随机交配和三品种轮回杂交模式、群体世代重叠17年的繁育过程.群体杂合度在第7年后趋于平衡,轮回杂交模式的群体杂合度高于随机交配.经过杂交,原中低产荷斯坦牛群体在产奶性能、生长性能方面都有进展,轮回杂交提高幅度相对略高.此外,利用品种效应和杂合度效应剖分杂种优势,采用单性状和多性状动物模型对模拟群体进行遗传评估,效果基本一致,都可以很好地用于杂交群体的遗传评估.结果表明,对荷斯坦牛中低产群体进行杂交,可实现生产性能和效益的提高,回归模型可用于多元群体的遗传评估.     

Analysis of risk factors associated with bovine leukemia virus seropositivity within dairy and beef breeding farms in Japan: A nationwide survey

This cross-sectional study evaluated risk factors associated with farm-level bovine leukemia virus (BLV) seropositivity in 563 dairy and 490 beef farms throughout Japan. Twenty randomly selected cattle on each farm were serologically tested, and farm epidemiologiocal information was obtained through face-to-face interviews. Due to the large number of zero-prevalence dairy and beef farms, data analysis was performed using a zero-inflated negative binomial model, which revealed that the common risk factors associated with higher within-farm seroprevalence were past detection of clinical leukemia and presence of blood-sucking insects. Loose housing on dairy farms and direct contact between calves and adult cattle on beef farms were also identified as risk factors. With regard to farm-level presence of BLV, the presence of purchased cattle was found to be a risk factor in both sectors. Sending heifers to a common ranch was identified as an additional risk factor for dairy farms.     

A multi-analysis approach for space–time and economic evaluation of risks related with livestock diseases: The example of FMD in Peru

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI–II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI–III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I–IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5 km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru.