这项研究得到了 jsp 资助的科研项目 (16H02580, 17H03885) 和鸟取大学干旱土地研究中心联合研究项目的财政支持。

本研究的主要目的是利用阵列探地雷达系统来可视化地下水的动态过程, 如水的渗入, 也必须描述如何进行渗透试验。
1. 野外入渗试验
<ol><li>选择具有裸表面的用于渗透测试的站点。 注意:本研究对日本鸟取大学干旱土地研究中心的大型温室设施进行了渗透试验。有关详细信息16, 请参见最近的发布。</li>
	<li>在表面六2.5 米长的多孔管平行的位置在彼此之间的距离, 以确保均匀渗透 (图 2)。</li>
	<li>将管的一端连接到阀门调节的入口, 连接到蓄水池或水龙头, 另一端到出水口以除去多余的水。</li>
	<li>放置一个薄 910 x 1802 毫米2木面板 (略高于天线阵列), 以覆盖多孔管。</li>
	<li>在入渗试验前, 检查木面板对雷达信号的影响。</li>
	<li>在木面板旁边安装土壤湿度传感器, 以监测不同深度土壤含水量的变化。 注意:这些传感器的目的是提供参考数据, 用于交叉检查从雷达数据分析中得到的结果。在这项研究中, 在天线旁边安装了一个棒型土壤水分传感器 (参见材料表), 以监测土壤介电常数在10、20、30、40、60和100厘米深。</li>
</ol>2. 探地雷达测量
<ol><li>将阵列探地雷达天线放在木面板上。 注意:在这项研究中, 天线是静止的, 以确保记录信号的一致性。</li>
	<li>使用同轴电缆将天线连接到控制器。</li>
	<li>将控制器连接到带有以太网电缆的笔记本电脑上。</li>
	<li>确定天线组合及其序列, 以确保共同的偏移收集 (齿轮) 和多偏移收集 (MOG) 无缝收集。 注意:在这项研究中, 所有可能的组合, 为阵列雷达在我们的处置被使用 (110)。通过所有组合执行完整扫描需要少于1.5 秒。</li>
	<li>使用数据收集软件开始记录探地雷达数据。 注意:在向多孔管注入水之前, 开始采集数据是很重要的。</li>
	<li>打开阀门应用水 (即, 开始入渗过程)。 注意:在地基中注水速率可以从目标土的水力特性 (如水力电导率) 中确定。本研究使用的流速为7000厘米3/分钟, 低于沙丘砂的饱和水力电导率。</li>
	<li>在预先确定的水注入量后, 关闭阀门。 注意:连续注入4小时水, 试验中共用1680升水。</li>
	<li>继续与阵列雷达扫描一段时间, 以监测再分配过程, 进一步分析。 注意:在阀门关闭后, 阵列探地雷达一直在收集4小时的数据。然而, 这些数据并没有被分析为这里提出的研究。</li>
</ol>3. 速度估计的数据分析
<ol><li>通过从总体数据立方体中提取相对 Tx Rx 组合来重建齿轮和 CMP 数据。这是通过由作者开发的一些自定义代码完成的, 重新排列雷达剖面, 以便将 Tx-Rx 对与相同的偏移 (齿轮) 和具有相同中点 (CMP) 的两对组合在一起。 注意:由于 SFCW 探地雷达单元用于本研究, 原始数据处于频域;利用雷达系统制造商提供的软件, 对频率转换进行了操作。</li>
	<li>通过拟合计算的双向旅行时间、 tc、在所观测信号的渗透前反射的电磁波, 估计在给定的运行时间内润湿区域中的最佳 EM 波速。启发式确定了最佳曲线拟合速度。 <img alt="Equation 1" src="/files/ftp_upload/56847/56847eq1.jpg">(1) 其中d0是反射点的深度, x是 Tx 和 Rx 之间的距离, vr 是反射平面的根均方速度, t0是零偏移的双向旅行时间由 CMP radargram 确定。 注意:使用 MOG 的最常用速度估计方法是外表分析5,15,17。在表象分析中, 利用速度谱选取根平均平方速度。由于阵列探地雷达数据中观测到的低信噪比不允许我们开发出可靠的速度谱, 所以在本研究中不采用表象分析法进行速度估计。在其他正在进行的研究中, 寻找一种适当的过滤方法来生成可靠的速度谱。在本研究的范围内, 采用曲线拟合方法将 Eq (1) 与 CMP radargrams 相适应。</li>
	<li>使用 Eq (1), 使用估计 EM 速度vr, 在给定的运行时间内计算润湿前深度d0 。 注意:对于数据分析的这一部分, 齿轮数据集使用在等于113毫米的偏移量x上。</li>
</ol>

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本研究利用阵列探地雷达 (鸟取) 在日本沙沙丘附近的一个实验场进行渗透实验, 对湿润锋的深度进行跟踪。本研究采用的阵列探地雷达系统由10发射天线 (Tx) 和11接收天线 (Rx) 组成。系统可以配置为使用多达110种不同的 Tx Rx 组合。在渗透实验中, 所有110种组合都连续扫描1.5 秒, 使阵列固定在水被放置在表面的一些多孔管的位置。从时间推移数据立方体中重建了共偏移集 (齿轮) 和常用中点数据 (CMP)。与传统的双基地探地雷达系统相同的速率采集 CMP 数据几乎是不可能的。在实验中, 将天线留在静止记录中是非常重要的, 以获得重现性和有意义的时间推移数据。
虽然阵列探地雷达数据已被用于估计电磁波速度15, 但仅有少数研究分析了时间推移阵列探地雷达数据, 以估计水渗入等瞬态过程的 em 波速。本研究从时间失效的 CMP 数据中估计出电磁 (EM) 波速结构。将双向行程时间的双曲线曲线与 CMP radargrams 中的反射信号启发式, 以估计湿润区内的平均 EM 波速, 而不是进行表象分析, 因为低信噪比 (S/N) 数据的比率。当 s-/N 比值较低时, 表面分析不能用于生成可靠的速度谱。为了使用表象分析方法, 需要开发一种合适的滤波方法。在探地雷达天线旁安装有杆式土壤水分传感器, 测量土壤含水量在渗透试验过程中的变化;传感器被偏移在深度 10, 20, 30, 40 和 60 cm 并且独立地工作了。
利用估计的 EM 波速, 在渗透过程的1分钟间隔内计算润湿锋的深度。估计润湿锋的时间演化与土壤湿度传感器在20厘米以下深度的观测结果吻合较好。在较浅的深度, 对湿润前沿深度的探地雷达估计与土壤水分传感器的读数有差异。
总体上, 本研究表明, 阵列探地雷达系统能够通过收集时间推移共同中点 (CMP) 数据, 跟踪水渗入土壤中湿润前沿深度的演变过程。由于这种类型的数据不容易收集从传统的表面探地雷达之前, 这项研究获得的数据是第一个, 实际显示如何在一段时间内, 润湿前沿演变。今后的工作将探讨利用数据反演方法估算土壤水力参数的可能性。

了解渗流带的质量和能量传输过程对于许多农业和环境学科的应用都是很重要的。在这些过程中, 可变饱和水流是必不可少的过程, 因为许多其他的过程, 如物理, 地球化学, 生物, 甚至机械过程, 通常与水流相结合。地球物理技术的最新发展使人们得以监测非侵入渗流区的水文过程。在许多地球物理技术中, 探地雷达是最广泛使用的监测和描述土壤水动力学的技术之一, 因为雷达天线发射和接收的电磁波的传播是特征是土壤含水量1,2,3,4。在现有的系统中, 地面表面的探地雷达 (在手稿的其余部分被称为表面探地雷达) 是最常见的在一个领域使用。传统的表面探地雷达系统与一个发射机和一个接收器 (双基地雷达系统) 通常用于扫描地下与恒定的发射机-接收器分离 (偏移)。在此配置中收集的数据集也称为普通偏移收集 (齿轮)。雷达数据以时间序列的方式显示在发射机、最终反射器和回接收机之间的总行程时间上。为了将行程时间转换为深度信息, 需要对地下电磁波的波速进行估计。例如, 可以通过分析多偏移收集 (MOG) 数据集5来完成此操作。
虽然已有多项研究使用探地雷达监测地下渗透过程6,7,8,9, 他们都没有直接确定润湿锋或 EM 波的位置在渗透过程中随时间变化的速度结构。一般的方法是使用被埋在已知深度的物体作为参考反射器, 以确定平均电磁波速度和润湿锋深度。由于润湿锋在浸润过程中动态变化, 必须在短时间内收集时间推移 MOG, 以利用电磁波速度结构的变化而不使用参考对象。利用共同的双基地表面探地雷达天线, 在短间隔时间内收集 MOG 是困难或不可能的, 因为它需要手动移动天线来设置各种偏移配置。最近, 一家天线阵雷达 (简称阵列探地雷达) 已广泛应用于图像的地下快速和准确的10。阵列探地雷达的基本概念是通过电子方式切换安装在单个帧中的多个天线来提供密集的大片。阵列探地雷达系统主要用于快速生成3D 的大面积地下图像。这些系统典型应用的一些例子是公路和桥梁检查11, 考古学展望12和未爆炸弹药和地雷检测13,14。为此目的, 阵列探地雷达主要用于用恒定的天线分离结构扫描地下, 以收集齿轮。虽然已经证明, 用阵列雷达收集的 MOG 可以用于速度估计15, 但这种方法的实际应用仅限于少数情况。通过将天线阵列放置在固定位置, 可以很容易地收集到时间失效的 MOG。正如我们最近发布的16所演示的那样, 用阵列探地雷达系统收集的时间推移 radargrams 在垂直渗透实验中逐渐向下移动时, 很清楚地描绘了润湿前沿的反射信号。在沙丘上进行的。本文的主要目的是演示如何在渗透试验中利用阵列探地雷达收集时间推移 MOG, 以及如何分析这些数据来跟踪润湿前沿的深度。
在本研究中, 我们使用的天线阵列由10发射 (Tx0 Tx9) 和11接收 (Rx0-Rx10) 弓系单极天线组成。数组中天线元素的位移显示在图 1中 (请参见材料表)。天线阵列由一步频连续波形 (SFCW) 雷达单元控制, 其工作频率范围从 100 mhz 到3000兆赫。阵列雷达通过在天线阵列10中使用射频 (RF) 器在用户定义的 Rx-Tx 对序列中进行切换。此特定系统的 Tx Rx 组合的最大数目为110。在这个实验中, 我们配置了阵列探地雷达, 以使用所有110组合, 编程扫描序列, 使每个发射机, 从 Tx0 到 Tx9, 是连续配对的所有11接收机从 Rx0 到 Rx10。在所有110组合中执行扫描所需的时间少于1.5 秒。发射机和接收机之间的偏移量是根据天线元件的进给点之间的距离计算的, 其中垂直偏移量为85毫米, 如图 1所示。

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			<td height="42" style="height:42px;width:216px;">GeoScope Radar Unit</td>
			<td style="width:71px;">3D Radar AS</td>
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			<td style="width:167px;"></td>
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			<td height="42" style="height:42px;width:216px;">DXG1820 antenna</td>
			<td style="width:71px;">3D Radar AS</td>
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			<td height="21" style="height:21px;width:216px;">PR2/6 Profile Probe&#160;</td>
			<td style="width:71px;">Delta-T</td>
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</table>

tracking infiltration front depth using time-lapse multi-offset gathers collected with array antenna ground penetrating radar

在日本鸟取沙丘附近的一个试验场进行的渗透试验中, 利用地面耦合的密集天线阵列的地面穿透雷达系统收集数据。本研究使用的天线阵列由10发射天线 (Tx) 和11接收天线 (Rx) 组成。对于本实验, 系统配置为使用所有可能的 tx rx 配对, 从而产生了由110个 tx rx 组合组成的多偏移收集 (MOG)。该阵列在直接位于渗透区上方的位置处于静止状态, 每1.5 秒使用一个基于时间的触发器收集数据。在后处理过程中, 从 MOG 数据中重建了共偏移集 (齿轮) 和普通中点 (CMP) 数据立方体。很少有研究使用时间推移 CMP 数据来估计传播速度的变化。本文采用双曲线方程, 通过曲线拟合, 估计1分钟启发式的电磁 (EM) 波速。然后, 我们着手计算润湿锋的深度。随着时间的推移, 润湿锋的演变是与土壤水分传感器的观测相一致的, 它被置于20厘米以下的深度。研究结果表明, 这种阵列探地雷达系统能够准确、定量地监测地下动态过程, 如水渗流。

图 3显示了在将数据从频率转换为时间域之后, 在渗透实验的第一60分钟内每1.5 秒获得110个 Tx Rx 组合的时间推移面板图。为了提高反射深度, 采用带通滤波器进行增益补偿。面板图可以分为10节, 每个部分对应于一个特定的 Tx。Tx 的位置由一个白色三角形指示, 每个切片对应于记录为 Rx 的一个延时信号。垂直轴显示双向行程时间或行波管, 即电磁波从发射器到最终反射器和返回接收机所需的时间。配置文件在灰度色图中显示信号振幅。颜色的大对比表明记录的雷达信号有很高的振幅。电磁波反射是在不同介电常数的层间界面或与周围介质不同的电学特性的物体上产生的;高介电对比度将决定高振幅反射。在水的入渗过程中, 有一个区域称为过渡区, 水的含量逐渐从湿润区的边缘增加, 即水渗入到最初的干土中。在水表检测18的研究中观察到, 电磁波可能不在非常边缘, 而是在过渡区内反射。在手稿的其余部分, 这个反射区域被称为润湿锋。在图 3中, 在实验过程中, 随着时间的推移, 出现高振幅信号并稳步向下移动。这种反射确实是由润湿锋产生的, 因为水在地下逐渐向下渗透。从该图中可以重建齿轮和 CMP, 如图 2岩崎et . 所示。16
对每1分钟获得的 CMP 数据进行速度分析。对于每组 CMP 数据, 由 Eq 提供的双向旅行时间 (1) 是通过调整t0和vr(假定在湿区中的统一层) 来安装在润湿前端的反射。用0.3 米/ns 的速度拟合空气波, 纠正了时间零点。图 4以5分钟间隔从已用时间te = 5 分钟到te = 50 分钟显示 CMP 数据, 同时显示为白色线条的最佳曲线 (反射波的实线和空波的虚线)。由于空气波不是反射波, 而是发射机与接收机之间的直接信号, 所以行程时间随偏移量线性增加。所有的曲线都安装在反射波的正峰 (白颜色) 上。所有曲线都适合在所有偏移量的 CMP radargrams 中显示的观测到的反射曲线, 这意味着t0和vr 的估计值很好。对于渗透实验, 在天线和多孔管之间放置了一个干木面板。由于面板的介电常数比湿土低得多, 它对电磁波传播的影响可能是微不足道的, 即使它很薄。然后考虑了二层模型, 除了上述的统一层模型, 假设值为3的介电常数的前 5 cm。另外对于第二个模型, 在润湿锋产生的反射下, 用曲线拟合估计了 EM 波速vr 。
in 图 5中, 估计的润湿前深度被绘制为单层和双层模型的te 的函数。可以理解的是, 润湿前端在两种模型中的时间几乎呈线性向下移动, 除te = 10 分钟和te = 20 分钟之间的慢速之外. 两种模型之间的差异最初不是显著, 但随着时间的推移, 统一模型的估计比两层模型移动得略快。在图 5中, 使用菱形符号来标记来自湿度传感器的读数开始增加的时间, 以及它们后来变得稳定时的次数;这些与每个传感器深度的实线连接。如上所述, 电磁波的反射不一定发生在湿区的边缘;换句话说, 考虑到某种深度, 当传感器读数开始增加时, 不能期望这种反射与时间点相匹配。从这个意义上说, 反射是由于渗透前的深度水平, 达到了一定的水饱和度, 与下面的区域相比。考虑到30、40和60厘米深的传感器, 从探地雷达数据获得的润湿锋深度估计在时间线上的实线显示的范围内很好。探地雷达估计润湿锋到达20厘米深度的时间对应于传感器读数突然增加的时间, 而探地雷达估计达到10厘米的深度远快于湿度传感器所产生的速度。, 虽然在te = 5 分钟 (图 4) 之后, 已清楚地观察到润湿前端的反射信号。另外, 还必须指出, 探地雷达估计曲线的外推不经过原点。虽然不清楚是什么导致了这种差异在浅深度, 可能有几个可能的解释。它可以归因于土壤性质的异质性, 也可能是由于水的不均匀性的应用。如果确实如此, 在渗透过程中, 这种情况在较晚阶段会产生更大的影响。另一个解释可能是表面粗糙度影响时间零的确定。除了木面板和多孔管的作用外, 还应考虑表面粗糙度的影响。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56847/56847fig1.jpg"> 图 1: 本研究中使用的阵列探地雷达天线配置架构.V 形结构是领结单极天线。有10发射天线 (Tx) 和11接收天线 (Rx) 水平对齐。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56847/56847fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56847/56847fig2.jpg"> 图 2:渗透实验的架构。(a) 顶部视图和 (B) 一个侧面视图, 其中阵列天线放置在六250厘米多孔管的顶部, 其排列为15厘米。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56847/56847fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56847/56847fig3.jpg"> 图 3: 在渗透实验的前60分钟内获得的时间推移 radargram.数据包括110天线组合的记录信号。一个切片对应于用单个 Tx Rx 组合收集的时间推移数据。不同的颜色用于信号振幅。垂直黑线分隔每个 tx 的数据. 白色三角形表示 tx 的位置.<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56847/56847fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56847/56847fig4.jpg"> 图 4: Radargrams 的 CMP 在te = 5 分钟到te = 55 分钟5分钟的间隔.白色实线表示人工拟合的反射的双向旅行时间从润湿前面, 而白色虚线代表空气波浪的旅行时间。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56847/56847fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56847/56847fig5.jpg"> 图 5: 润湿前深度.从阵列探地雷达中估计的润湿前深度在时移多偏移量集合中, 作为统一 (三角形) 和双层 (正方形) 模型的经过时间的函数。两端有钻石的黑线显示了读数的初始增加和这些数据在每个传感器深度 (即过渡区域的持续时间) 达到稳定水平之间的时间。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56847/56847fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar at JoVE.com

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

利用阵列天线探地雷达采集的时移多偏移收集跟踪入渗前深度

在这里, 我们提出了一个地面穿透雷达 (雷达) 系统基于地面耦合, 稠密的天线阵列监测地下水渗透的动态过程。渗透过程的时移雷达图像允许在渗透过程中估算润湿锋的深度。

A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration ...

tracking-infiltration-front-depth-using-time-lapse-multi-offset

Nanyang Technological University

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Civil Engineering

Environment

Unit 1

Horizontal and Vertical Curves

SCIENTISTS IN ACTION

7.7K 次观看.  Tokyo University of Agriculture and Technology. 在这里, 我们提出了一个地面穿透雷达 (雷达) 系统基于地面耦合, 稠密的天线阵列监测地下水渗透的动态过程。渗透过程的时移雷达图像允许在渗透过程中估算润湿锋的深度。

视频: Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Tracking Microbial Contamination in Retail Environments Using Fluorescent Powder - A Retail Delicatessen Environment Example

Cross contamination of foodborne pathogens in the retail environment is a significant public health issue contributing to an increased risk for foodborne illness. Ready-to-eat (RTE) processed foods such as deli meats, cheese, and in some cases fresh produce, have been involved in foodborne disease outbreaks due to contamination with pathogens such as Listeria monocytogenes. With respect to L. monocytogenes, deli slicers are often the main source of cross contamination. The goal of this study was to use a fluorescent compound to simulate bacterial contamination and track this contamination in a retail setting. A mock deli kitchen was designed to simulate the retail environment. Deli meat was inoculated with the fluorescent compound and volunteers were recruited to complete a set of tasks similar to those expected of a food retail employee. The volunteers were instructed to slice, package, and store the meat in a deli refrigerator. The potential cross contamination was tracked in the mock retail environment by swabbing specific areas and measuring the optical density of the swabbed area with a spectrophotometer. The results indicated that the refrigerator (i.e. deli case) grip and various areas on the slicer had the highest risk for cross contamination. The results of this study may be used to develop more focused training material for retail employees. In addition, similar methodologies could also be used to track microbial contamination in food production environments (e.g.&#160;small farms), hospitals, nursing homes, cruise ships, and hotels.

The overall goal of this study was to demonstrate the potential cross contamination mechanism of foodborne pathogen Listeria monocytogenes in a retail deli setting. This methodology may be applied to a variety of different environments to track pathogen contamination. &#160;

跟踪微生物污染在零售环境中使用荧光粉 - 零售熟食店环境范例

Cross contamination of foodborne pathogens in the retail environment is a significant public health issue contributing to an increased risk for foodborne ...

科研

环境科学

EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. I. Collection of Virus Samples

EPA Method 1615 was developed with a goal of providing a standard method for measuring enteroviruses and noroviruses in environmental and drinking waters. The standardized sampling component of the method concentrates viruses that may be present in water by passage of a minimum specified volume of water through an electropositive cartridge filter. The minimum specified volumes for surface and finished/ground water are 300 L and 1,500 L, respectively. A major method limitation is the tendency for the filters to clog before meeting the sample volume requirement. Studies using two different, but equivalent, cartridge filter options showed that filter clogging was a problem with 10% of the samples with one of the filter types compared to 6% with the other filter type. Clogging tends to increase with turbidity, but cannot be predicted based on turbidity measurements only. From a cost standpoint one of the filter options is preferable over the other, but the water quality and experience with the water system to be sampled should be taken into consideration in making filter selections.

EPA Method 1615 uses an electropositive filter to concentrate enteroviruses and noroviruses in environmental and drinking waters. This manuscript describes the procedure for collecting samples for Method 1615 analyses.

EPA方法1615测量肠道病毒和诺瓦克病毒发生水由文化和RT-qPCR的了。病毒样本的收集I.

EPA Method 1615 was developed with a goal of providing a standard method for measuring enteroviruses and noroviruses in environmental and drinking waters. ...

EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. Part III. Virus Detection by RT-qPCR

EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. This method was developed with the goal of having a standardized method for use in multiple analytical laboratories during monitoring period 3 of the Unregulated Contaminant Monitoring Rule. Herein we present the protocol for extraction of viral ribonucleic acid (RNA) from water sample concentrates and for quantitatively measuring enterovirus and norovirus concentrations using reverse transcription-quantitative PCR (RT-qPCR). Virus concentrations for the molecular assay are calculated in terms of genomic copies of viral RNA per liter based upon a standard curve. The method uses a number of quality controls to increase data quality and to reduce interlaboratory and intralaboratory variation. The method has been evaluated by examining virus recovery from ground and reagent grade waters seeded with poliovirus type 3 and murine norovirus as a surrogate for human noroviruses. Mean poliovirus recoveries were 20% in groundwaters and 44% in reagent grade water. Mean murine norovirus recoveries with the RT-qPCR assay were 30% in groundwaters and 4% in reagent grade water.

Here we present a procedure to quantify enterovirus and norovirus in environmental and drinking waters using reverse transcription-quantitative PCR. Mean virus recovery from groundwater with this standardized procedure from EPA Method 1615 was 20% for poliovirus and 30% for murine norovirus.

EPA方法1615测量肠道病毒和诺瓦克病毒发生水由文化和RT-qPCR的了。第三部分。病毒检测用RT-qPCR的

EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. This method was developed with the goal of having a ...

How to Create Conditioned Taste Aversion for Grazing Ground Covers in Woody Crops with Small Ruminants

Conditioned taste aversion (CTA) is a learning behavior process where animals are trained to reject certain feed after gastrointestinal discomfort has been produced. Lithium chloride (LiCl) is the preferred agent used in livestock to induce CTA because it specifically stimulates the vomit center. In addition, LiCl is commercially available, and easy to prepare and administer using a drenching gun. Nevertheless, some factors have to be considered to obtain an effective long-lasting CTA, which allows small ruminants to graze during the cropping season. A key aspect is to use animals with no previous contact with the target plant (the plant chosen to be avoided; new feed). Due to their native neophobic feeding behavior, small ruminants can easily associate the negative feedback effects with the new feed, resulting in a strong and persistent CTA. The recommended doses are 200 and 225 mg LiCl/kg body weight (BW) for goats and sheep, respectively. To induce CTA, 100 g of the target plant should be individually offered for at least 30 min, and LiCl administered thereafter if the intake is greater than 10 g. Each time the animal eats the target plant without negative consequences, the CTA becomes weaker. Consequently, to minimize the risk of target plant consumption, it is essential to have sufficient palatable ground cover available. The presence of an alternative feed (of quality and quantity) prevents the accidental consumption of the target plant. A close monitoring of the flock is recommended to remove and re-dose any animal consuming more than 4 bites or 10 g of the target plant. At the beginning of each grazing season, check the CTA status of each animal before moving them to the crop.

Feeding behavior preferences in livestock can be modified to implement a grazing management plan in woody crops. Here, we present a protocol to show a lithium chloride dose after eating a new plant that induces conditioned taste aversion.

如何创建条件性味觉厌恶放牧在地面木本作物与小反刍动物封面

Conditioned taste aversion (CTA) is a learning behavior process where animals are trained to reject certain feed after gastrointestinal discomfort has ...

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

We demonstrate the utility of remotely sensed data and the newly developed Software for Assisted Habitat Modeling (SAHM) in predicting invasive species occurrence on the landscape. An ensemble of predictive models produced highly accurate maps of tamarisk (Tamarix spp.) invasion in Southeastern Colorado, USA when assessed with subsequent field validations.

整合与物种分布模型遥感;映射红柳入侵使用软件进行辅助建模居（SAHM）

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite ...

Video Tracking Protocol to Screen Deterrent Chemistries for Honey Bees

The European honey bee, Apis mellifera L., is an economically and agriculturally important pollinator that generates billions of dollars annually. Honey bee colony numbers have been declining in the United States and many European countries since 1947. A number of factors play a role in this decline, including the unintentional exposure of honey bees to pesticides. The development of new methods and regulations are warranted to reduce pesticide exposures to these pollinators. One approach is the use of repellent chemistries that deter honey bees from a recently pesticide-treated crop. Here, we describe a protocol to discern the deterrence of honey bees exposed to select repellent chemistries. Honey bee foragers are collected and starved overnight in an incubator 15 h prior to testing. Individual honey bees are placed into Petri dishes that have either a sugar-agarose cube (control treatment) or sugar-agarose-compound cube (repellent treatment) placed into the middle of the dish. The Petri dish serves as the arena that is placed under a camera in a light box to record the honey bee locomotor activities using video tracking software. A total of 8 control and 8 repellent treatments were analyzed for a 10 min period with each treatment was duplicated with new honey bees. Here, we demonstrate that honey bees are deterred from the sugar-agarose cubes with a compound treatment whereas honey bees are attracted to the sugar-agarose cubes without an added compound.

The loss of honey bee colonies presents a challenge to crop pollination services. Current pollinator protection practices warrant an alternative approach to minimize the contact of honey bees to harmful pesticides using repellent chemistries. Here, we provide detailed methods for a visual tracking protocol to screen deterrents for bees.

用于蜂蜜蜜蜂筛选化学成分的视频跟踪协议

The European honey bee, Apis mellifera L., is an economically and agriculturally important pollinator that generates billions of dollars annually. Honey ...

Image-based Lagrangian Particle Tracking in Bed-load Experiments

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two action-cameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol.

The manuscript presents a protocol for the conduction of bed-load sediment transport experiments where the moving particles are tracked by image analysis. The experimental facility, the procedures for run realization and data processing, and finally some proof-of-concept results are presented here.

基于图像的拉格朗日粒子跟踪在床载荷实验

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a ...

Characterization of Aquatic Biofilms with Flow Cytometry

Biofilms are dynamic consortia of microorganism that play a key role in freshwater ecosystems. By changing their community structure, biofilms respond quickly to environmental changes and can be thus used as indicators of water quality. Currently, biofilm assessment is mostly based on integrative and functional endpoints, such as photosynthetic or respiratory activity, which do not provide information on the biofilm community structure. Flow cytometry and computational visualization offer an alternative, sensitive, and easy-to-use method for assessment of the community composition, particularly of the photoautotrophic part of freshwater biofilms. It requires only basic sample preparation, after which the entire sample is run through the flow cytometer. The single-cell optical and fluorescent information is used for computational visualization and biological interpretation. Its main advantages over other methods are the speed of analysis and the high-information-content nature. Flow cytometry provides information on several cellular and biofilm traits in a single measurement: particle size, density, pigment content, abiotic content in the biofilm, and coarse taxonomic information. However, it does not provide information on biofilm composition on the species level. We see high potential in the use of the method for environmental monitoring of aquatic ecosystems and as an initial biofilm evaluation step that informs downstream detailed investigations by complementary and more detailed methods.

Flow cytometry in combination with visual clustering offers an easy-to-use and fast method for studying aquatic biofilms. It can be used for biofilm characterization, detection of changes in biofilm community structure, and detection of abiotic particles embedded in the biofilm.

流式细胞仪对水生生物膜的表征

Biofilms are dynamic consortia of microorganism that play a key role in freshwater ecosystems. By changing their community structure, biofilms respond ...

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

As individuals increasingly live in cities, methods to study their everyday movements and the data that can be collected becomes important and valuable. Eye-tracking informatics are known to connect to a range of feelings, health conditions, mental states and actions. But because vision is the result of constant eye-movements, teasing out what is important from what is noise is complex and data intensive. Furthermore, a significant challenge is controlling for what people look at compared to what is presented to them.
The following presents a methodology for combining and analyzing eye-tracking on a video of a natural and complex scene with a machine learning technique for analyzing the content of the video. In the protocol we focus on analyzing data from filmed videos, how a video can be best used to record participants&#39; eye-tracking data, and importantly how the content of the video can be analyzed and combined with the eye-tracking data. We present a brief summary of the results and a discussion of the potential of the method for further studies in complex environments.

The objective of the protocol is to detail how to collect video data for use in the laboratory; how to record eye-tracking data of participants looking at the data and how to efficiently analyze the content of the videos that they were looking at using a machine learning technique.

将眼动追踪数据与从自由观看城市公园环境中的步行视频中获得的视频内容进行分析

As individuals increasingly live in cities, methods to study their everyday movements and the data that can be collected becomes important and valuable. ...

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

We present a protocol related to a video-tracking technique based on the background subtraction and image thresholding that makes it possible to individually track cohoused animals. We tested the tracking routine with four cohoused Norway lobsters (Nephrops norvegicus) under light-darkness conditions for 5 days. The lobsters had been individually tagged. The experimental setup and the tracking techniques used are entirely based on the open source software. The comparison of the tracking output with a manual detection indicates that the lobsters were correctly detected 69% of the times. Among the correctly detected lobsters, their individual tags were correctly identified 89.5% of the times. Considering the frame rate used in the protocol and the movement rate of lobsters, the performance of the video tracking has a good quality, and the representative results support the validity of the protocol in producing valuable data for research needs (individual space occupancy or locomotor activity patterns). The protocol presented here can be easily customized and is, hence, transferable to other species where the individual tracking of specimens in a group can be valuable for answering research questions.

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Here we present a protocol to individually track animals over a long period of time. It uses computer vision methods to identify a set of manually constructed tags by using a group of lobsters as case study, simultaneously providing information on how to house, manipulate, and mark the lobsters.