Utilization of Ground-Penetrating Radar and Frequency Domain Electromagnetic for Investigation of Sewage Leaks

Fact 1: Underground sewage pipe systems deteriorate over time, developing cracks and joint defects; therefore, leakage is inevitable. Fact 2: The massive worldwide urbanization process, together with rural development, has meaningfully increased the length of sewage pipelines. Result: The concomitant risk of sewage leaks exposes the surrounding land to potential contamination and environmental harm. It is therefore important to locate such leaks in a timely manner, enabling damage control. Advances in active remote-sensing technologies (GPR and FDEM: ground-penetration radar and frequency domain electromagnetic) were used to identify sewage leaks that might cause pollution and to identify minor spills before they cause widespread damage

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions

Laboratory Measurements of Subsurface Spatial Moisture Content by Ground-Penetrating Radar (GPR) Diffraction and Reflection Imaging of Agricultural Soils

Soil moisture content (SMC) down to the root zone is a major factor for the efficient cultivation of agricultural crops, especially in arid and semi-arid regions. Precise SMC can maximize crop yields (both quality and quantity), prevent crop damage, and decrease irrigation expenses and water waste, among other benefits. This study focuses on the subsurface spatial electromagnetic mapping of physical properties, mainly moisture content, using a ground-penetrating radar (GPR). In the laboratory, GPR measurements were carried out using an 800 MHz central-frequency antenna and conducted in soil boxes with loess soil type (calcic haploxeralf) from the northern Negev, hamra soil type (typic rhodoxeralf) from the Sharon coastal plain, and grumusol soil type (typic chromoxerets) from the Jezreel valley, Israel. These measurements enabled highly accurate, close-to-real-time evaluations of physical soil qualities (i.e., wave velocity and dielectric constant) connected to SMC. A mixture model based mainly on soil texture, porosity, and effective dielectric constant (permittivity) was developed to measure the subsurface spatial volumetric soil moisture content (VSMC) for a wide range of moisture contents. The analysis of the travel times for GPR reflection and diffraction waves enabled calculating electromagnetic velocities, effective dielectric constants, and spatial SMC under laboratory conditions, where the required penetration depth is low (root zone). The average VSMC was determined with an average accuracy of ±1.5% and was correlated to a standard oven-drying method, making this spatial method useful for agricultural practice and for the design of irrigation plans for different interfaces

Frequency Domain Electromagnetic Method (FDEM) as a Tool to Study Contamination at the Sub-Soil Layer

Traditional sheep and cattle grazing in natural semiarid Mediterranean, Asian and African regions is based on night corrals, where animal secretions accumulate. Lack of management and disregard for the long-term effects of using the same sites for corrals on underground soil characters may negatively affect soil values. This locally increases the content of organic matter and nutrients such as nitrogen, potassium, phosphorus and others that are stockpiled in the corrals. As these activities are long-lasting, they affect the soil parameters, leading to nutrient leakage and contamination of the upper and sub-soil surface. This alarming situation demands a technique to reveal and estimate sub-soil contamination in corrals by using the frequency domain electromagnetic method (FDEM) for measuring soil salinity. The aim of this study is to correlate electrical conductivity measurement with the FDEM to study the influence of sheep corrals on the changes within the sub-soils of corrals in the semiarid region of the northern Negev desert. The results show that a correlation was found between the laboratory soil analysis and the electromagnetic analysis in all sites. Plugot forest site results found to be anomalous indicated sub-surface conductivity resulting from the presence of the corral, with a higher conductivity value of about 230 mS/m, while no differences were found between the soil layers outside the active corral and the corral edge. High values were found in the center of the active corral: 960 mS/m by the laboratory analysis and 200 mS/m by the FDEM. The values obtained in the abandoned corral in the laboratory were about 10 times lower than those obtained from the active corral and six times lower that those found with the FDEM. At the Beit Nir site, high values were found in the center of the active corral: 300 mS/m by the laboratory analysis and 130 mS/m by the FDEM. With different sources of manure, cattle and sheep have shown similar patterns of electrical conductivity (EC) obtained in the sub-soil layers between active and abandoned corrals: high in the center and low at the edge and outside the corral and decreased with depth

The Anthropogenic Affect—Humans and Geology: An Example from Tel Dor, Israel

Geology usually deals with rocks formed long ago, which are static and stable over the span of human lifetime. This study aims to analyze anthropogenic influence on the formation of geological features in the southeastern Mediterranean. Tel Dor, along Israel’s northern coast, was chosen due to the continuous presence of humans in the area for over 4000 years and the protective environment of its natural bays that preserve geomorphological changes. This allows for the examination of whether and how humans affect their (geological) environment. Three rocky platforms were chosen in the shallow waters of the South Bay adjacent to the Tel, and four cores were extracted. Results show the extent of the direct and indirect anthropological influences on the landscape. The presence of building stones consisting of dolomite, which is not found along the Carmel coast, is an example of direct influence (importation). The evolution of a biological and non-biological reef upon the sturdy base of the port constructions is an indirect influence. The formation of a non-biological reef upon an archaeological feature is a unique process. It would not have consolidated without the presence of anthropogenic activity. This study shows how human interference in the coastal area can trigger a chain reaction of geological processes lasting more than 2000 years

Inferring plant-plant interactions using remote sensing

1. Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. 2. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. 3. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. 4. $Synthesis$. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.ISSN:0022-047

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions

Apixaban compared with warfarin in patients with atrial fibrillation and previous stroke or transient ischaemic attack: A subgroup analysis of the ARISTOTLE trial

Background: In the ARISTOTLE trial, the rate of stroke or systemic embolism was reduced by apixaban compared with warfarin in patients with atrial fibrillation (AF). Patients with AF and previous stroke or transient ischaemic attack (TIA) have a high risk of stroke. We therefore aimed to assess the efficacy and safety of apixaban compared with warfarin in prespecified subgroups of patients with and without previous stroke or TIA. Methods: Between Dec 19, 2006, and April 2, 2010, patients were enrolled in the ARISTOTLE trial at 1034 clinical sites in 39 countries. 18 201 patients with AF or atrial flutter were randomly assigned to receive apixaban 5 mg twice daily or warfarin (target international normalised ratio 2·0-3·0). The median duration of follow-up was 1·8 years (IQR 1·4-2·3). The primary efficacy outcome was stroke or systemic embolism, analysed by intention to treat. The primary safety outcome was major bleeding in the on-treatment population. All participants, investigators, and sponsors were masked to treatment assignments. In this subgroup analysis, we estimated event rates and used Cox models to compare outcomes in patients with and without previous stroke or TIA. The ARISTOTLE trial is registered with ClinicalTrials.gov, number NTC00412984. Findings: Of the trial population, 3436 (19%) had a previous stroke or TIA. In the subgroup of patients with previous stroke or TIA, the rate of stroke or systemic embolism was 2·46 per 100 patient-years of follow-up in the apixaban group and 3·24 in the warfarin group (hazard ratio [HR] 0·76, 95% CI 0·56 to 1·03); in the subgroup of patients without previous stroke or TIA, the rate of stroke or systemic embolism was 1·01 per 100 patient-years of follow-up with apixaban and 1·23 with warfarin (HR 0·82, 95% CI 0·65 to 1·03; p for interaction=0·71). The absolute reduction in the rate of stroke and systemic embolism with apixaban versus warfarin was 0·77 per 100 patient-years of follow-up (95% CI -0·08 to 1·63) in patients with and 0·22 (-0·03 to 0·47) in those without previous stroke or TIA. The difference in major bleeding with apixaban compared with warfarin was 1·07 per 100 patient-years (95% CI 0·09-2·04) in patients with and 0·93 (0·54-1·32) in those without previous stroke or TIA. Interpretation: The effects of apixaban versus warfarin were consistent in patients with AF with and without previous stroke or TIA. Owing to the higher risk of these outcomes in patients with previous stroke or TIA, the absolute benefits of apixaban might be greater in this population. Funding: Bristol-Myers Squibb and Pfizer. © 2012 Elsevier Ltd