Scales of predator detection behavior and escape in Fissurella limbata: A field and laboratory assessment

The consumptive effects of predators are widely acknowledged, but predation can also impact prey populations through non‐consumptive effects (NCEs) such as costly antipredator behavioral responses. The magnitude of antipredator behavioral responses by prey is determined by an assessment of risk using sensory cues, which in turn is modulated by the environmental context. We studied the detection behavior and escape response of the keyhole limpet Fissurella limbata from the predatory sea star Heliaster helianthus. Through laboratory and field experimental trials, we quantified the distance and time of predator detection behavior by the prey, and measured their active escape responses when elicited. We found that predator detection by the limpet was chiefly mediated by distance, with experimental individuals capable of detecting predator presence effectively up to distances of at least 50 cm in the field and 70 cm under laboratory conditions. Our results indicate that this prey species is able to evaluate the proximity of its predator and use it as an indication of predation risk; therefore, predator–prey distance appears to be a primary predictor of the magnitude of the antipredator response. Given the tight relationship between predator distance and prey movement and the important role herbivores can play, particularly in this ecosystem, we expect that NCEs will cascade to the patterns of abundance and composition of rocky shore communities through changes in prey foraging behavior under risk.     

差应变法地应力测量——以汶川地震断裂带科学钻探WFSD-1钻孔为例

岩心差应变分析法是汶川地震断层科学钻探(WFSD)项目地应力测量的主要手段之一, 该技术通过高压容器对取之于钻孔不同深度的实验样品施加围压, 观察先前由于失去地层应力而膨胀产生的裂纹重新闭合, 并通过裂纹闭合过程差应变曲线分析, 确定主应力大小和方向。WFSD-1孔12个岩心样品的DSA测试结果表明:断层上下盘的应力状态有明显差异, 区域地应力不仅随深度增加, 还与地质结构和岩石的物理性质等因素有关。      

一种多孔径SAR图像目标检测方法

提出了一种多孔径SAR图像目标检测方法,充分利用SAR图像幅度和相位信息来区分人造目标和杂波。由于人造目标的回波能量往往集中在部分方位角范围内,当该部分方位角范围所对应的多个子孔径图像中存在目标时,其局部相关性较强,因此,该方法利用多个子孔径图像之间的相干系数检测目标。实验结果表明,该方法有效地提高了目标检测概率,同时降低了虚警概率。     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys

The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High‐resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process‐based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.     

轨道扣件病害自动化检测研究及应用

传统扣件检查基本采用人工检查方式,不仅工作效率低、劳动强度大,而且人为干扰因素多、检查采样率低.针对以上问题,本文提出了一种基于线结构光传感器的轨道扣件损伤和松动检测方法,并开发了轨道扣件智能监测系统以实现扣件病害自动检测.最终将研究成果应用于徐州市某地铁区间轨道扣件检测,验证了该方法的可行性和准确率,为地铁轨道扣件检...     

转换波方位各向异性裂缝检测技术研究及应用

HTI裂缝各向异性介质中,转换波随方位角的变化比较复杂,目前还没有解析公式可以表达其变化特征,只能通过物理实验或数值模拟来分析其应用的可能性.数值模拟结果表明,转换波在裂缝各向异性介质中传播时,其R分量和T分量的振幅属性都具有明显的方位各向异性特征,R分量振幅方位各向异性拟合椭圆的长轴方向指示裂缝方位,这与纵波方位各向异性特征相似;根据P波AVAZ方位各向异性分析原理,对转换波R分量振幅方位各向异性曲线进行方位椭圆拟合,寻找椭圆的长轴方向,即裂缝主方位,再由P波AVAZ技术中振幅响应与炮检方向和裂缝走向之间的夹角关系式得到裂缝的发育密度,从而构建转换波方位各向异性AVAZ裂缝检测技术.该技术已用于川西新场气田某区块的裂缝储层预测,取得了较好的应用效果.     

抽油机悬点投影测量仪

油田抽油机的抽油杆幌动幅度过大，是引起抽油杆断裂的一个重要因素，检测这种幌动幅度是防止抽油杆断裂的一种有效手段。设计了一种基于面阵CCD和普通半导体激光器（LD）测量这种幌动的悬点投影测量方法，通过数字卷积滤波，达到了范围为0－40mm，误差＜0.2mm的技术检测指标。     

CSAMT与CYT联合探测法在深部盐穴储气库建设中的应用

针对深部盐穴探测问题的特殊性,结合平顶山叶县盐田储气工程,简要探讨了可控源音频大地电磁法(CSAMT)与大地电场岩性探测法(CYT)的理论基础、探测原理以及解译方法,并对试验区盐穴的几何形态、空间分布以及物性信息反馈特征展开了研究。首先应用CSAMT法进行初探,大致圈定目标体的空间范围; 其次在CSAMT法探测结果基础上选择有利地段,采用CYT法进行精探,详细圈定目标体的空间形态。探测结果表明,试验区盐穴空间形态复杂,剖面上呈现不规则的空穴群,埋深大约为 -1400～-1000m; 但单个溶腔体积较小,半径大致为8～60m。研究成果可用于指导地下盐穴储气库址的选择和建设,为我国深部盐穴探测方法和电场岩性解译提供了参考。     

Use of multitemporal remote sensing data for mapping the Alfios River network changes from 1977 to 2000

Alfios is the biggest river of the Peloponnese and the ninth longest river in Greece. It drains an area of almost 2575 km² in Western Peloponnese and discharges at Kiparissiakos Gulf. Due to its extent, the Alfios basin presents complex physiography and geomorphology.

During the last 50 years, major direct human activities have had an important impact on the river network shape and on the valley floor morphology. The most important human activities were the channel straightening caused by meander cut-offs in 1950, the construction of two dams: the Ladonas dam in 1955 and the Flokas dam in 1968 and the illegal in-stream gravel extraction that started in the 1960s and continues until today. As a result, the Alfios riverbed has presented very rapid vertical and horizontal (lateral) erosion and significant changes to its network shape. The drainage network follows a straighter course, the number of meanders has been reduced and the seventh order branch is deeply incised. Besides the morphological impacts to the river network shape there are also serious economic damages caused by human activity. During the winter of 1999, the Flokas dam bridge was closed for a long period due to damages at its foundation caused by the heavy rain and illegal gravel extraction. Transportation between the villages in the area became extremely difficult and time consuming and the cost of the repairs was estimated at 500 000 euros. In this study, there is an effort to map the network shape transformation for the period 1977–2000 using multitemporal and multisensor satellite images. One Landsat MSS image, three Landsat TM images, two Landsat ETM images, and one Terra ASTER image have been orthorectified and processed in order to cover the specific period. Principal Component Analysis (PCA) method and Geographical Information System (GIS) techniques have been applied to map the changes in the Alfios River channel. The drainage network straightening and the cut-off of five big meanders were detected and mapped. These changes occurred between 1986 and 2000.