Relational distance,neoliberalism and the regulation of animal health

Using quantitative and qualitative data, this paper contributes to debates on the uneven geographies of neoliberal animal disease regulation. Specifically, the paper analyses the impacts of neoliberal reforms to animal disease regulation in Great Britain. Focussing on the case of bovine tuberculosis (bTB), the paper analyses how changes to ‘relational distance’ in animal disease regulation have led to closer relationships between regulators (veterinarians) and regulatees (farmers) which in turn has led to a departure from standardised disease regulation to approaches that emphasise greater flexibility and judgement. The paper presents quantitative analysis of bTB testing data revealing the gradual erosion of government control of bTB regulation and significant variations in disease diagnosis between vets in the private and public sectors. Drawing on interviews with senior veterinarians in Government and veterinary organisations, the paper shows how these regulatory structures evolved and came to be accepted despite their limitations. The paper concludes by considering how relational distance contributes to an understanding of the nature of disease and its implications for the wider regulation of animal disease.     

Challenges to global surveillance of disease patterns

Surveillance systems for foodborne disease vary in capacity by country, especially for marine-related illnesses. Generally, the more developed the country is, the more funding that is put into its surveillance programs, but no country has an outstanding system that could serve as a model for all others. An additional problem is lack of consistency. Approaches to surveillance and available resources change over time, so that apparent trends may reflect more of an administrative function. Most countries have some passive system that allows data on foodborne illnesses to be sent to centralized authorities where summaries are generated. However, these depend on the uneven quality of the source data that vary according to the resources allocated at the local level. Active surveillance systems collect data targeted to answer specific epidemiological questions more efficiently, but at such a high cost that most countries do not have the resources, except on a occasional basis. There is also the issue of what to do with the collected data. There has to be a conscious effort to translate the problems identified from the surveillance programs to consider strategies for prevention and control of foodborne disease. Otherwise, there is little value in having these kinds of monitoring programs. Another problem is lack of coordination in surveillance systems between most countries, so that information can be rapidly and efficiently shared. That being said, surveillance over the years had generated much interesting information on how disease agents are transmitted through the food supply, and where contamination and growth by pathogens in the food production and preparation chain typically occur. In addition, attempts are being made to create regional networks in different parts of the world usually initiated by organizations like WHO and PAHO. The kinds of information collected and programs being introduced are discussed in examples taken from both the developed and less developed world, followed by a series of recommendations for improving surveillance on a global basis. A recent burden in the surveillance system is the potential for a deliberate attack on the food supply with agents not usually involved with foodborne illness. At least in the US, a major concern is for the rapid detection and containment of a massive contamination of the food supply.     

无人机影像辅助下的路桥病害智能检测

路桥表面病害状况评估是路桥养护的一项重要内容。目前病害检测主要基于移动测量车和目视判断,具有工作量大、获取危险度高的缺点,而低空飞行的六旋翼无人机能够拍摄到人工无法获取到的多角度路桥照片,在路桥检测方面具有巨大的优势。本文基于无人机影像开展路桥病害检测相关研究,提出了一种新的路桥病害检测方法。首先通过多部件形变模型模拟病害目标,并在无人机影像中全局搜索,检测出潜在路桥病害区域。试验表明,本文算法在复杂背景下能够有效检测病害,目标检测精度达80%,具有很高的效率和鲁棒性。     

利用三维激光扫描技术进行地铁隧道施工质量管控及病害检测

三维激光扫描技术具有不接触、高密度、高精度和数字化等特点，可实现地铁隧道全息、全面、快速三维测量。在土建施工阶段，分别对隧道初支及二衬进行三维扫描，可快速获取初支断面的超欠挖情况及二衬限界情况；将初支与二衬扫描获取的点云进行叠加计算，可分析隧道施工二衬的厚度。在地铁隧道运营阶段，采用移动三维激光扫描技术对隧道进行扫描，可快速获取隧道的全息数据，从点云中可分析、提取隧道渗水、裂缝、管片错台等病害信息。本文采用三维激光扫描技术对青岛地铁部分工点的施工质量及病害检测进行了测试、应用，介绍了其数据采集流程及点云分析处理，为三维激光扫描技术在地铁隧道的推广应用提供了一定的借鉴意义。     

兰州市呼吸道疾病与沙尘天气关系的分析

利用 1996～ 1998年春季兰州市某医院呼吸道门诊逐日病例资料和同期甘肃河西 19站沙尘暴、扬沙及兰州站浮尘逐日资料 ,对兰州市呼吸道疾病发病人数与沙尘天气的关系进行了分析。分析结果表明 ,两者之间呈显著的正相关 ,当甘肃河西发生沙尘暴、扬沙天气或兰州出现浮尘天气且无明显降水后的 1～ 2d ,兰州市呼吸道疾病呈现高发趋势。     

吉林省心脑血管疾病与气象条件关系分析和预报研究

利用吉林省部分地区医院病例资料及气象资料,分析了吉林省心脑血管疾病与气象条件的关系。结果发现:心脑血管疾病的复发、加重与气象条件有一定的关系,但不同的患者对天气变化的敏感性有一定的差异。在各种天气条件中,以气压低、感觉闷热的影响最为显著,确认率达74%。不论冬半年还是夏半年,长春市气压和气温的大幅变化都易引起冠心病复发,较大幅度的气压升高、气温下降对脑出血、脑梗塞不利,高血压主要与气压的波动、相对湿度关系较为密切。辽源市心脑血管疾病在日平均气温和极端气温下降、气压上升时发病人数增加。气象要素影响心脑血管疾病的机理分析表明:高温、高湿天气将造成心排出量增加,心功能减弱,心排血量降低;强降温将导致人体内的肾上腺素水平上升,从而造成心律加快,血压升高,同时寒冷刺激可使交感神经过度兴奋,诱发冠状动脉痉挛甚至心肌梗死。最后,建立了长春市和辽源市医疗气象预报模型。     

小麦赤霉病发生量预测预报

采用单因子相关法和多因子线性回归法对豫西地区1985－1999年15年的小麦赤霉病系统观测资料及相关气象资料进行统计分析，经比较，筛选出春季玉米残体菌率、4月下旬－5月下旬雨日、4月下旬－5月下旬雨量3个对小麦赤霉病发生量影响显著的因子，建立预测模型，经回验与预测验证，结果与实际相吻合。     

一种新的疾病发病人数预测模型研究

以体感温度为自变量,将一元线性回归、自然正交函数和逐步回归结合起来,分别建立了炎热和凉爽季节下南京幼年感冒和金华老年脑血管病的旬发病人数预测模型。并将模型的预测结果与逐步回归模型进行了比较。比较得出:模型的预测效果比逐步回归模型的好。     

鱼淋巴囊肿病毒研究进展

淋巴囊肿病毒是最早发现的鱼类病毒,广泛分布于世界各地的淡水、盐水和海水中,可感染140种以上鱼类,危害巨大。本文对该病毒的形态结构特征、化学组成和理化特性、基因组及编码多肽、细胞培养特性和该病的致病机理、传播方式、诊断防治等方面进行了综述。     

地震CT与FBG传感器技术在隧道结构诊断中的应用

针对飞鱼泽隧道的上行线二衬拱顶靠档墙处出现裂缝,经地震CT技术查清隧道上所覆盖岩体的工程地质结构结果表明,沿隧道轴向存在三个岩体破碎带,其中在小里程入口段,岩体完整性较差。在隧道病害治理和隧道健康监测中,经光纤Bragg光栅（FBG）传感器的监测结果表明,松散破碎岩体的地质情况得到了相应的加固。因此,地震CT和FBG两者的检测结论是相互印证的。