黄河中游水土保持措施保存率分析及措施状况评述──以黄河河龙区间南片为例

本文以土地详查、淤地坝普查成果为基本依据，结合典型调查，研究分析了河龙区间南片水土保持各项措施的保存率，认为在空间尺度上，分行政区给出的保存率较为真实的反映了社会环境、自然环境因素的相对作用程度及其主导关系，且有实际应用意义，据此文中进一步核实评述了该区水保措施的保存面积、措施结构及质量等。该区水保措施的状况在黄河中游干旱半干旱地区具有广泛的代表性，分析结果可作为水沙分析、水保规划、土地资源与环境评价等工作的重要参考依据。     

传统猪场应对非洲猪瘟的生物安全升级改造

洲猪瘟是由非洲猪瘟病毒引起的一种急性、烈性、高度接触性传染病,严重危害全球养猪业的发展。我国将其列为一类动物疫病,属于烈性外来疫病,其强毒力毒株对生猪致病率高,致死率为100%。2018年8月,中国首次报告非洲猪瘟疫情,截止目前内地所有省份均受到非洲猪瘟的影响^[1]。非洲猪瘟作为养猪业的头号杀手,事关国民经济平稳运行和生猪产业持续健康发展。猪场因人员、猪只、物资、饲料等频繁出入,如果生物安全防控不理想,感染风险将极高。     

Identification of two novel B cell epitopes on porcine epidemic diarrhea virus spike protein

S1D (residues 636-789) is a neutralizing epitope region on the spike protein (S) of porcine epidemic diarrhea virus (PEDV). To accurately identify epitopes on S1D, the S1-phage library containing the gene encoding the S1D region of PEDV S protein was micropanned by six specific monoclonal antibodies (McAbs) against the S1D region. These micropanned epitope regions (MER) were focused on 696-779 amino acids of the S protein. To further map epitopes of the MER, seven overlapping mini-fragments covering MER nucleotides were separately synthesized and expressed in Escherichia coli BL21 with a GST tag. These mini-GST fusion proteins were scanned by ELISA and Western blotting with the six McAbs, and the result showed that S1D5 (residues 744-759) and S1D6 (residues 756-771) are two linear epitopes of the PEDV S protein. The antisera of the epitopes S1D5 and S1D6 could react with the native S protein of PEDV. Furthermore, Pepscan of the two linear epitopes demonstrated that SS2 ((748)YSNIGVCK(755)) and SS6 ((764)LQDGQVKI(771)) are two core epitopes on S1D5 and S1D6, respectively, located on the S protein of PEDV.     

猪传染性胃肠炎与猪流行性腹泻二联弱毒疫苗的研究

用TGE及PED克隆化弱毒株以1：1配比制成TGE、PED二联弱毒疫苗,毒价为107.0-7.5TCID50／0.3ml,主动免疫与被动免疫的保护率为97.7％及98％。弱毒株毒力稳定,符合制苗标准。免疫期7个月,疫苗保存期一年,疫苗接种猪对同圈饲养的非免疫猪有低效价（16～32倍）的水平感染。6个猪场的田间试验保护率为95％-98％,对紧急预防接种的防制效果更为明显。     

猪传染性胃肠炎华毒弱毒株纤突蛋白B、C抗原位点片段基因的克隆与序列分析

猪传染性胃肠炎华毒（TGEV H）是我国分离的代表毒株,H弱毒株是我国自行培育成功的具有良好免疫原性的疫苗株。应用RT－PCR方法扩增出1．3kb的目的片段,包括S基因的编码的B、C两个主要抗原位点的片段,目的片段与pUC19质粒载体进行连续,转化,鉴定后得到阳性重组质粒,命名为pTS1,将重组质粒插入的目的基因片段进行序列分析和比较,其结果表明TGEV H株和S基因5’端B、C位点片段1190bp的核苷酸序列与国外的TGEV毒株Miller、Purdue-115、FS772／70及台湾省TFI毒株序列均具有很高的同源性,达94．72以上。推导的氨基酸序列同源性为94．70％以上。编码抗原位点C的序列与其它毒株完全一致,但在B位点发生改变,即第97个氨基酸发生改变,由Trp突变为Ser。该核苷酸该片段全长1261bp,包括起始密码子ATG及基因间的共同序列ACTAAAC。本研究首次报道了国内的TGEV分离株－H弱毒株S基因的RT－PCR扩增及其编码的B、C抗原位点片段的分子克隆及序列分析,为进一步揭示TGEV强弱毒差别的分子机制、开展新型疫苗及进行分子诊断的研究奠定了重要基础。     

Thirty years of fleet dynamics modelling using discrete‐choice models: What have we learned?

Anticipating fisher behaviour is necessary for successful fisheries management. Of the different concepts that have been developed to understand individual fisher behaviour, random utility models (RUMs) have attracted considerable attention in the past three decades, and more particularly so since the 2000s. This study aimed at summarizing and analysing the information gathered from RUMs used during the last three decades around the globe. A methodology has been developed to standardize information across different studies and compare RUM results. The studies selected focused on fishing effort allocation. Six types of fisher behaviour drivers were considered: the presence of other vessels in the same fishing area, tradition, expected revenue, species targeting, costs, and risk‐taking. Analyses were performed using three separate linear modelling approaches to assess the extent to which these different drivers impacted fisher behaviour in three fleet types: fleets fishing for demersal species using active gears, fleets fishing for demersal species using passive gears and fleets fishing for pelagic species. Fishers are attracted by higher expected revenue, tradition, species targeting and presence of others, but avoid choices involving large costs. Results also suggest that fishers fishing for demersal species using active gears are generally more influenced by past seasonal (long‐term) patterns than by the most recent (short‐term) information. Finally, the comparison of expected revenue with other fisher behaviour drivers highlights that demersal fishing vessels are risk‐averse and that tradition and species targeting influence fisher decisions more than expected revenue.