Scattering Models in Remote Sensing: Application to SAR Despeckling and Sea Target Detection from GNSS-R Imagery

Imaging sensors are an essential tool for the observation of the Earth’ surface and the study of other celestial bodies. The capability to produce radar images of the illuminated surface is strictly related with the complex phenomenology of the radiation-matter interaction. The electromagnetic scattering theory is a well-established and well-assessed topic in electromagnetics. However, its usage in the remote sensing field is not adequately investigated and studied. This Ph.D. Thesis addresses the exploitation of electromagnetic scattering models suitable for natural surfaces in two applications of remotely sensed data, namely despeckling of synthetic aperture radar (SAR) imagery, and the detection of sea targets in delay-Doppler Maps (DDM) acquired from spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R). The first issue was addressed by conceiving, developing, implementing and validating two despeckling algorithms for SAR images. The developed algorithms introduce some a priori information about the electromagnetic behavior of the resolution cell in the despeckling chain and were conceived as a scattering-based version of pre-existing filters, namely the Probabilistic Patch-Based (PPB) and SAR-Block-Matching 3-D (SARBM3D) algorithms. The scattering behavior of the sensed surface is modeled assuming a fractal surface roughness and using the Small Perturbation Method (SPM) to describe the radar cross section (RCS) of the surface. Performances of the proposed algorithms have been assessed using both canonical test (simulated) and actual images acquired from the COSMO\SkyMed constellation. The robustness of the proposed filters against different error sources, such as the scattering behavior of the surface, surface parameters, Digital Elevation Model (DEM) resolution and the SAR image-DEM coregistration step, has been evaluated via an experimental sensitivity analysis. The problem of detecting sea targets from GNSS-R data in near real-time has been investigated by analyzing the revisit time achieved by constellations of GNSS-R instruments. A statistical analysis of the global revisit time has been performed by means of mission simulation, in which three realistic scenario have been defined. Time requirements for near real-time ship detection purposes are shown to be fulfilled in multi-GNSS constellation scenarios. A four-step sea target has been developed. The detector is a Constant False Alarm Rate (CFAR) algorithm and is based on the suppression of the sea clutter contribution, modeled via the Geometrical Optics (GO) approach. Performance assessment is performed by deriving the Receiver Operating Curves (ROC) of the detector. Finally, the proposed sea target detection algorithm has been tested using actual UK TechDemoSat-1 data

Diversity of cervical microbiota in asymptomatic chlamydia trachomatis genital infection: a pilot study

Chlamydia trachomatis genital infection continues to be an important public health problem worldwide due to its increasing incidence. C. trachomatis infection can lead to severe sequelae, such as pelvic inflammatory disease, obstructive infertility, and preterm birth. Recently, it has been suggested that the cervico-vaginal microbiota may be an important defense factor toward C. trachomatis infection as well as the development of chronic sequelae. Therefore, the investigation of microbial profiles associated to chlamydial infection is of the utmost importance. Here we present a pilot study aiming to characterize, through the metagenomic analysis of sequenced 16s rRNA gene amplicons, the cervical microbiota from reproductive age women positive to C. trachomatis infection. The main finding of our study showed a marked increase in bacterial diversity in asymptomatic C. trachomatis positive women as compared to healthy controls in terms of Shannon's diversity and Shannon's evenness (P = 0.031 and P = 0.026, respectively). More importantly, the cervical microbiota from C. trachomatis positive women and from healthy controls significantly separated into two clusters in the weighted UniFrac analysis (P = 0.0027), suggesting that differences between the two groups depended entirely on the relative abundance of bacterial taxa rather than on the types of bacterial taxa present. Furthermore, C. trachomatis positive women showed an overall decrease in Lactobacillus spp. and an increase in anaerobes. These findings are part of an ongoing larger epidemiological study that will evaluate the potential role of distinct bacterial communities of the cervical microbiota in C. trachomatis infection

Sea target detection using spaceborne GNSS-R delay-doppler maps: theory and experimental proof of concept using TDS-1 data

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This study addresses a novel application of global navigation satellite system-reflectometry (GNSS-R) delay-Doppler maps (DDMs), namely sea target detection. In contrast with other competing remote sensing technologies, such as synthetic aperture radar and optical systems, typically exploited in the field of sea target detection, GNSS-R systems could be employed as satellite constellations, so as to fulfill the temporal requirements for near real-time ships and sea ice sheets monitoring. In this study, the revisit time offered by GNSS-R systems is quantitatively evaluated by means of a simulation analysis, in which three different realistic GNSS-R missions are simulated and analyzed. Then, a sea target detection algorithm from spaceborne GNSS-R DDMs is described and assessed. The algorithm is based on a sea clutter compensation step and uses an adaptive threshold to take into account spatial variations in the sea background and/or noise statistics. Finally, the sea target detector algorithm is tested and validated for the first time ever using experimental GNSS-R data from the U.K. TechDemoSat-1 dataset. Performance is assessed by providing the receiver operating characteristic curves, and some preliminary experimental results are presented.Peer ReviewedPostprint (published version

Computerized system for staging peritoneal surface malignancies

Background: Peritoneal surface malignancies (PSMs) are usually staged using Sugarbaker's Peritoneal Cancer Index (PCI) and completeness of cytoreduction score (CC-s). Although these staging tools are essential for selecting patients and evaluating outcome after cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC), both scoring models lack some anatomic information, thus making staging laborious and unreliable. Maintaining Sugarbaker's original concepts, we therefore developed a computerized digital tool, including a new anatomic scheme for calculating PCI and CC-s corresponding closely to patients' real anatomy. Our new anatomic model belongs in a web-based application known as the PSM Staging System, which contains essential clinical and pathological data for the various PSMs currently treated. Methods: The new digital tool for staging PSM runs on a personal computer or tablet and comprises male and female colored anatomic models for the 13 endoabdominal regions, with borders defined according to real anatomic landmarks. A drag-and-drop tool allows users to compute the PCI and CC-s, making it easier to localize and quantify disease at diagnosis and throughout treatment, and residual disease after CRS. Conclusions: Once tested online by registered users, our computerized application should provide a modern, shareable, comprehensive, user-friendly PSM staging system. Its anatomic features, along with the drag-and-drop tool, promise to make it easier to compare preoperative and postoperative PCIs, thus improving the criteria for selecting patients to undergo CRS plus HIPEC. By specifying the size, site, and number of residual lesions after CRS plus HIPEC, our digital tool should help stratify patients into outcome classes

Spotting Insects from Satellites: Modeling the Presence of Culicoides Imicola Through Deep CNNs

Nowadays, Vector-Borne Diseases (VBDs) raise a severe threat for public health, accounting for a considerable amount of human illnesses. Recently, several surveillance plans have been put in place for limiting the spread of such diseases, typically involving on-field measurements. Such a systematic and effective plan still misses, due to the high costs and efforts required for implementing it. Ideally, any attempt in this field should consider the triangle vectors-host-pathogen, which is strictly linked to the environmental and climatic conditions. In this paper, we exploit satellite imagery from Sentinel-2 mission, as we believe they encode the environmental factors responsible for the vector's spread. Our analysis - conducted in a data-driver fashion - couples spectral images with ground-truth information on the abundance of Culicoides imicola. In this respect, we frame our task as a binary classification problem, underpinning Convolutional Neural Networks (CNNs) as being able to learn useful representation from multi-band images. Additionally, we provide a multi-instance variant, aimed at extracting temporal patterns from a short sequence of spectral images. Experiments show promising results, providing the foundations for novel supportive tools, which could depict where surveillance and prevention measures could be prioritized

Cyclic fatigue of NiTi instruments used in complex curvatures with continuous or reciprocating rotation

Aim: The aim of present study was to compare cyclic fatigue resistance of Twisted files (TF, Sybron Endo, Glendora, CA) instrument used with continuous rotation and the new Motion (TFAdaptive rotating reciprocation), to evaluate if the new reciprocating motion could affect the lifespan of tested instruments. Methodology: 30 new TF instruments were submitted to cyclic fatigue tests. Group 1 instruments were tested using a TFA motion (TFA) while group 2 instruments were used in continuous rotation at 500 rpm (CR). The cyclic fatigue testing device used in the present study has been used for studies on cyclic fatigue resistance previously. The artificial canal was manufactured to provide the instrument with a very challenging trajectory 60° curvature, with a 2 mm radius. All instruments were rotated or reciprocated until fracture occurred. The time to fracture was recorded. All data were subjected to statistical evaluation with analysis of variance test. Results: TFA reciprocating motion showed a significant increase (p < 0.05) in the time to failure when compared to continuous rotation. Mean time to failure was 131 s (SD ±25.2) for group 1 (TFA), and was 68 s (SD ±14.8) for continuous rotation group (CR). Conclusions: In accordance with those findings, the results of the present study showed a significant increase of cyclic fatigue resistance of instruments used with the TFA motion. This can be explained by the alternance of engaging/disengaging movements, since the motion can be defined as a non-continuous rotation, while the traditional continuous rotation movement continuously engages and stresses the instruments

Carbonic anhydrase VII is S-glutathionylated without loss of catalytic activity and affinity for sulfonamide inhibitors

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Specific capture and whole‑genome phylogeography of Dolphin morbillivirus

Dolphin morbillivirus (DMV) is considered an emerging threat having caused several epidemics worldwide. Only few DMV genomes are publicly available. Here, we report the use of target enrichment directly from cetacean tissues to obtain novel DMV genome sequences, with sequence comparison and phylodynamic analysis. RNA from 15 tissue samples of cetaceans stranded along the Italian and French coasts (2008–2017) was purified and processed using custom probes (by bait hybridization) for target enrichment and sequenced on Illumina MiSeq. Data were mapped against the reference genome, and the novel sequences were aligned to the available genome sequences. The alignment was then used for phylogenetic and phylogeographic analysis using MrBayes and BEAST. We herein report that target enrichment by specific capture may be a successful strategy for whole-genome sequencing of DMV directly from field samples. By this strategy, 14 complete and one partially complete genomes were obtained, with reads mapping to the virus up to 98% and coverage up to 7800X. The phylogenetic tree well discriminated the Mediterranean and the NE-Atlantic strains, circulating in the Mediterranean Sea and causing two different epidemics (2008–2015 and 2014–2017, respectively), with a limited time overlap of the two strains, sharing a common ancestor approximately in 1998