Objective comparison of particle tracking methods

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers

Trace elements: critical insights from 15 years of monitoring in the Venice Lagoon catchment basin (Italy)

The study focused on selected trace elements (As, Cd, Cr, Hg, Ni, Pb) monitored in surface waters of the Venice Lagoon catchment basin (North East Italy) over the period 2000-2015. The monitoring was undertaken to verify the achievement of the quality objectives set by the European and national legislations. The available results have been analyzed to evaluate the chemical status of water bodies. The limit of quantification (LOQ) of the applied analytic techniques appears critical for the adequate water monitoring; for some parameters, the percentage of not visible values due to non-satisfactory LOQ was higher in the beginning of the period; the subsequent improvement of LOQ allowed assessing the respect of environmental quality standards (EQSs). The study analyzes time trends in single stations and the differences between detected concentrations in the considered stations. Moreover, maximum concentrations and water flows have been considered to understand the potential correlation. Cumulated frequency curves for the most critical parameters have been built to identify situation of potential overtaking of the EQSs in force. The most polluted sampling stations of the drainage basin for the six trace elements were found in Cuori and Fiumazzo rivers. Although LOQs changed over time, the recorded trends show a quality improvement and a good compliance with respect to EQSs set by European legislation, while considering EQSs set by local special legislation, the objectives are not yet satisfied. Arsenic is ubiquitous; thus, it can be supposed to be originated as a background environmental concentration, while nickel appears of industrial origin according to its point and local presence

Statistical analysis of data measured by the HF surface wave radar WERA

Surface wave (SW) over the horizon (OTH) radars have been widely used for remote sensing and oceanic applications. These systems operate continuously for monitoring both sea currents and waves by analyzing the signal backscattered by the rough sea surface. This paper is devoted to the statistical analysis of sea backscattering recorded by the oceanographic Wellen radar (WERA) system, developed at the University of Hamburg. Data were collected on May the 13th 2008 at two different sites in the Bay of Brest, in Brittany, France. The results show that for near range cells the signal amplitude fits well the Rayleigh distribution, while for far cells the data show a more pronounced heavy-tailed behavior. The causes can be traced in man-made (i.e. radio communications) and/or natural (i.e. reflections of the transmitted signal through the ionosphere layers) interferences. A qualitative analysis of the spectral characteristics of the received signal concludes the work

The HF Surface Wave Radar WERA. Part II: Spectral Analysis of Recorded Data

This paper covers the second part of the analysis of data recorded by the surface wave (SW) over-the-horizon (OTH) WEllen RAdar (WERA). Data were collected by two WERA systems, on May 13th 2008, during the NURC experiment in the Bay of Brest, France. The principal aim of this work is to provide an accurate characterization of the spectral components of the received signal. Secondly, this information is exploited in order to provide a simple and reliable spectral modeling tool. For this reason, auto-regressive (AR) models, also known as linear prediction (LP) models have been investigated. Our results show that at long distances, when the clutter-to-noise power ratio (CNR) is small, the main components of the spectrum can be reasonably described by an AR(12) model, with a good compromise between accuracy and simplicity. As the CNR increases higher-orders are instead to be preferred

The HF Surface Wave Radar WERA. Part I: Statistical Analysis of Recorded Data

Surface wave (SW) over-the-horizon (OTH) radars are not only widely used for ocean remote sensing, but they can also be exploited in integrated maritime surveillance systems. This paper represents the first part of the description of the statistical and spectral analysis performed on sea backscattered signals recorded by the oceanographic WEllen RAdar (WERA) system. Data were collected on May 13th 2008 in the Bay of Brest, France. The data statistical analysis, after beamforming, shows that for near range cells the signal amplitude fits well the Rayleigh distribution, while for far cells the data show a more pronounced heavy-tailed behavior. The causes can be traced in man-made (i.e. radio communications) and/or natural (i.e. reflections of the transmitted signal through the ionosphere layers, meteor trails) interferences

Vessel Detection and Classification: An Integrated Maritime Surveillance System in the Tyrrhenian Sea

In recent years a number of organizations, both national and international, have put significant efforts in developing knowledge-based integrated maritime surveillance (IMS) systems. The final aim is to have a clear picture of the position, classification, identification and movement of cooperative and non-cooperative targets entering and leaving the 200 nautical miles limit of the Exclusive Economic Zone (EEZ). Each sensor (i.e. satellite-based, ground-based, shipborne or airborne) has its own task and, in such a context, high frequency (HF) surface wave (SW) radars are inexpensive tools for long range early warning applications in open waters. They allow maximizing the effectiveness in dealing with fisheries protection, drug interdiction, illegal immigration, terrorist threats, search and rescue tasks. This paper focuses on the possibility of combining automatic identification system (AIS) data with HFSWR data for vessel detection and classification purposes. Three algorithms for target detection in compound Gaussian HF sea clutter are presented and their performance evaluated. The combined use of AIS plots provided by cooperative targets can allow the operator to discriminate non-cooperative targets and possible threats. The concurrent exploitation of AIS and HFSWR data is presented and discussed by means of real data recorded during the NURC experiment in the northern Tyrrhenian Sea in May 2009