36 research outputs found

    EVOLUTION OF THE SUBCONTINENTAL LITHOSPHERE DURING MESOZOIC TETHYAN RIFTING: CONSTRAINTS FROM THE EXTERNAL LIGURIAN MANTLE SECTION (NORTHERN APENNINE, ITALY)

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    Our study is focussed on mantle bodies from the External Ligurian ophiolites, within the Monte Gavi and Monte Sant'Agostino areas. Here, two distinct pyroxenite-bearing mantle sections were recognized, mainly based on their plagioclase-facies evolution. The Monte Gavi mantle section is nearly undeformed and records reactive melt infiltration under plagioclase-facies conditions. This process involved both peridotites (clinopyroxene-poor lherzolites) and enclosed spinel pyroxenite layers, and occurred at 0.7–0.8 GPa. In the Monte Gavi peridotites and pyroxenites, the spinel-facies clinopyroxene was replaced by Ca-rich plagioclase and new orthopyroxene, typically associated with secondary clinopyroxene. The reactive melt migration caused increase of TiO2 contents in relict clinopyroxene and spinel, with the latter also recording a Cr2O3 increase. In the Monte Gavi peridotites and pyroxenites, geothermometers based on slowly diffusing elements (REE and Y) record high temperature conditions (1200-1250 °C) related to the melt infiltration event, followed by subsolidus cooling until ca. 900°C. The Monte Sant'Agostino mantle section is characterized by widespread ductile shearing with no evidence of melt infiltration. The deformation recorded by the Monte Sant'Agostino peridotites (clinopyroxene-rich lherzolites) occurred at 750–800 °C and 0.3–0.6 GPa, leading to protomylonitic to ultramylonitic textures with extreme grain size reduction (10–50 μm). Compared to the peridotites, the enclosed pyroxenite layers gave higher temperature-pressure estimates for the plagioclase-facies re-equilibration (870–930 °C and 0.8–0.9 GPa). We propose that the earlier plagioclase crystallization in the pyroxenites enhanced strain localization and formation of mylonite shear zones in the entire mantle section. We subdivide the subcontinental mantle section from the External Ligurian ophiolites into three distinct domains, developed in response to the rifting evolution that ultimately formed a Middle Jurassic ocean-continent transition: (1) a spinel tectonite domain, characterized by subsolidus static formation of plagioclase, i.e. the Suvero mantle section (Hidas et al., 2020), (2) a plagioclase mylonite domain experiencing melt-absent deformation and (3) a nearly undeformed domain that underwent reactive melt infiltration under plagioclase-facies conditions, exemplified by the the Monte Sant'Agostino and the Monte Gavi mantle sections, respectively. We relate mantle domains (1) and (2) to a rifting-driven uplift in the late Triassic accommodated by large-scale shear zones consisting of anhydrous plagioclase mylonites. Hidas K., Borghini G., Tommasi A., Zanetti A. & Rampone E. 2021. Interplay between melt infiltration and deformation in the deep lithospheric mantle (External Liguride ophiolite, North Italy). Lithos 380-381, 105855

    Practical Clinical Andrology

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    This open access book offers a valuable resource for understanding the correct pathways in the context of sexual disorders, couple reproduction, gender identity dysphoria, conditions for which patients commonly ask for consultation and treatment. Based on clinical evidence, international guidelines and experts experience, practical clinical management strategies are presented for each condition. Each clinical care pathway is based on updated algorithm, level of evidence, photos and video-clips that describes the clinical presentations and the best practice management through diagnostic tools and medical or surgical treatment. Leading experts from the most important center of excellence in the field of sexual medicine joined to cover the field of andrology in its entirety, each of them dealing with a single topic from the top of their recognized experience and providing a complete and update textbook that will help urologists and other physicians in their daily clinical practice. This book is thought to be a practical and valuable reference for urologists, gynecologists, endocrinologists, psychiatrics and psychologists, and residents who are not specialty trained in andrology. It is designed for both young fellows training in different specialties and coming into contact with andrological issues for the first time and also more experienced clinicians and surgeons requiring updated guidelines and clear advice on the most controversial issues. This book will represent an invaluable quick consulting tool, updated in its scientific contents and rich in tables, images and video-clips

    Impact of Etna’s volcanic emission on major ions and trace elements composition of the atmospheric deposition

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    Mt. Etna, on the eastern coast of Sicily (Italy), is one of the most active volcanoes on the planet and it is widely recognized as a big source of volcanic gases (e.g., CO2 and SO2), halogens, and a lot of trace elements, to the atmosphere in the Mediterranean region. Especially during eruptive periods, Etna’s emissions can be dispersed over long distances and cover wide areas. A group of trace elements has been recently brought to attention for their possible environmental and human health impacts, the Technology-critical elements. The current knowledge about their geochemical cycles is still scarce, nevertheless, recent studies (Brugnone et al., 2020) evidenced a contribution from the volcanic activity for some of them (Te, Tl, and REE). In 2021, in the framework of the research project “Pianeta Dinamico”, by INGV, a network of 10 bulk collectors was implemented to collect, monthly, atmospheric deposition samples. Four of these collectors are located on the flanks of Mt. Etna, other two are in the urban area of Catania and three are in the industrial area of Priolo, all most of the time downwind of the main craters. The last one, close to Cesarò (Nebrodi Regional Park), represents the regional background. The research aims to produce a database on major ions and trace element compositions of the bulk deposition and here we report the values of the main physical-chemical parameters and the deposition fluxes of major ions and trace elements from the first year of research. The pH ranged from 3.1 to 7.7, with a mean value of 5.6, in samples from the Etna area, while it ranged between 5.2 and 7.6, with a mean value of 6.4, in samples from the other study areas. The EC showed values ranging from 5 to 1032 μS cm-1, with a mean value of 65 μS cm-1. The most abundant ions were Cl- and SO42- for anions, Na+ and Ca+ for cations, whose mean deposition fluxes, considering all sampling sites, were 16.6, 6.8, 8.4, and 6.0 mg m-2 d, respectively. The highest deposition fluxes of volcanic refractory elements, such as Al, Fe, and Ti, were measured in the Etna’s sites, with mean values of 948, 464, and 34.3 μg m-2 d-1, respectively, higher than those detected in the other sampling sites, further away from the volcanic source (26.2, 12.4, 0.5 μg m-2 d-1, respectively). The same trend was also observed for volatile elements of prevailing volcanic origin, such as Tl (0.49 μg m-2 d-1), Te (0.07 μg m-2 d-1), As (0.95 μg m-2 d-1), Se (1.92 μg m-2 d-1), and Cd (0.39 μg m-2 d-1). Our preliminary results show that, close to a volcanic area, volcanic emissions must be considered among the major contributors of ions and trace elements to the atmosphere. Their deposition may significantly impact the pedosphere, hydrosphere, and biosphere and directly or indirectly human health

    Impact of geogenic degassing on C-isotopic composition of dissolved carbon in karst systems of Greece

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    The Earth C-cycle is complex, where endogenic and exogenic sources are interconnected, operating in a multiple spatial and temporal scale (Lee et al., 2019). Non-volcanic CO2 degassing from active tectonic structures is one of the less defined components of this cycle (Frondini et al., 2019). Carbon mass-balance (Chiodini et al., 2000) is a useful tool to quantify the geogenic carbon output from regional karst hydrosystems. This approach has been demonstrated for central Italy and may be valid also for Greece, due to the similar geodynamic settings. Deep degassing in Greece has been ascertained mainly at hydrothermal and volcanic areas, but the impact of geogenic CO2 released by active tectonic areas has not yet been quantified. The main aim of this research is to investigate the possible deep degassing through the big karst aquifers of Greece. Since 2016, 156 karst springs were sampled along most of the Greek territory. To discriminate the sources of carbon, the analysis of the isotopic composition of carbon was carried out. δ13CTDIC values vary from -16.61 to -0.91‰ and can be subdivided into two groups characterized by (a) low δ13CTDIC, and (b) intermediate to high δ13CTDIC with a threshold value of -6.55‰. The composition of the first group can be related to the mixing of organic-derived CO2 and the dissolution of marine carbonates. Springs of the second group, mostly located close to Quaternary volcanic areas, are linked to possible carbon input from deep sources

    Online Super-Resolution For Fibre-Bundle-Based Confocal Laser Endomicroscopy

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    Probe-based Confocal Laser Endomicroscopy (pCLE) produces microscopic images enabling real-time in vivo optical biopsy. However, the miniaturisation of the optical hardware, specifically the reliance on an optical fibre bundle as an imaging guide, fundamentally limits image quality by producing artefacts, noise, and relatively low contrast and resolution. The reconstruction approaches in clinical pCLE products do not fully alleviate these problems. Consequently, image quality remains a barrier that curbs the full potential of pCLE. Enhancing the image quality of pCLE in real-time remains a challenge. The research in this thesis is a response to this need. I have developed dedicated online super-resolution methods that account for the physics of the image acquisition process. These methods have the potential to replace existing reconstruction algorithms without interfering with the fibre design or the hardware of the device. In this thesis, novel processing pipelines are proposed for enhancing the image quality of pCLE. First, I explored a learning-based super-resolution method that relies on mapping from the low to the high-resolution space. Due to the lack of high-resolution pCLE, I proposed to simulate high-resolution data and use it as a ground truth model that is based on the pCLE acquisition physics. However, pCLE images are reconstructed from irregularly distributed fibre signals, and grid-based Convolutional Neural Networks are not designed to take irregular data as input. To alleviate this problem, I designed a new trainable layer that embeds Nadaraya- Watson regression. Finally, I proposed a novel blind super-resolution approach by deploying unsupervised zero-shot learning accompanied by a down-sampling kernel crafted for pCLE. I evaluated these new methods in two ways: a robust image quality assessment and a perceptual quality test assessed by clinical experts. The results demonstrate that the proposed super-resolution pipelines are superior to the current reconstruction algorithm in terms of image quality and clinician preference

    Underwater Vehicles

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    For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

    A New Representation for Spectral Data Applied to Raman Spectroscopy of Brain Cancer

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    Par sa nature infiltrative et son confinement derrière la barrière hémo-encéphalique, le cancer primaire du cerveau est l’une des néoplasies les plus difficiles à diagnostiquer et traiter. Son traitement repose sur la résection chirurgicale maximale. La spectroscopie Raman, capable d’identifier en temps réel des régions cancéreuses qui apparaîtraient normales à l’œil nu, promet d’améliorer considérablement le guidage neurochirurgical et maximiser la résection de la masse tumorale. Cependant, le signal Raman est très complexe à interpréter : les systèmes Raman peuvent maintenant capter des signaux de grande qualité que les méthodes analytiques actuelles ne parviennent pas à interpréter de manière reproductible. Ceci constitue une barrière importante à l’acceptation de la spectroscopie Raman par les médecins et les chercheurs œuvrant sur le cancer du cerveau. L’objectif de ce travail est de développer une méthode robuste d’ingénierie des variables (« Feature engineering ») qui permettrait d’identifier les processus moléculaires exploités par les systèmes Raman pour différentier les régions cancéreuses des régions saines lors de chirurgies cérébrales. Tout d’abord, nous avons identifié les régions Raman ayant une haute spécificité à notre problématique clinique par une revue systématique de la littérature. Un algorithme d’ajustement de courbe a été développé afin d’extraire la forme des pics Raman dans les régions sélectionnées. Puis, nous avons élaboré un modèle mathématique qui tient compte de l’interactivité entre les molécules de l’échantillon interrogé, ainsi qu’entre le signal Raman et l’âge du patient opéré. Pour valider le modèle, nous avons comparé sa capacité à compresser le signal avec celle de l’analyse en composante principale (ACP), le standard en spectroscopie Raman. Finalement, nous avons appliqué la méthode d’ingénierie des variables à des spectres Raman acquis en salle d’opération afin d’identifier quels processus moléculaires indiquaient la présence de cancer. Notre méthode a démontré une meilleure rétention d’information que l’ACP. En l’appliquant aux spectres Raman in vivo, les zones denses en cellules malignes démontrent une expression augmentée d’acides nucléiques ainsi que de certaines protéines, notamment le collagène, le tryptophan et la phénylalanine. De plus, l’âge des patients semble affecter l’impact qu’ont certaines protéines, lipides et acides nucléiques sur le spectre Raman. Nos travaux révèlent l’importance d’une modélisation statistique appropriée pour l’implémentation clinique de systèmes Raman chirurgicaux.----------ABSTRACT Because of its infiltrative nature and concealment behind the blood-brain barrier, primary brain cancer remains one of the most challenging oncological condition to diagnose and treat. The mainstay of treatment is maximal surgical resection. Raman spectroscopy has shown great promise to guide surgeons intraoperatively by identifying, in real-time, dense cancer regions that appear normal to the naked eye. The Raman signal of living tissue is, however, very challenging to interpret, and while most advances in Raman systems targeted the hardware, appropriate statistical modeling techniques are lacking. As a result, there is conflicting evidence as to which molecular processes are captured by Raman probes. This limitation hinders clinical translation and usage of the technology by the cancer-research community. This work focuses on the analytical aspect of Raman-based surgical systems. Its objective is to develop a robust data processing pipeline to confidently identify which molecular phenomena allow Raman systems to differentiate healthy brain and cancer during neurosurgeries. We first selected high-yield Raman regions based on previous literature on the subject, resulting in a list of reproducible Raman bands with high likelihood of brain-specific Raman signal. We then developed a peak-fitting algorithm to extract the shape (height and width) of the Raman signal at those specific bands. We described a mathematical model that accounted for all possible interactions between the selected Raman peaks, and the interaction between the peaks’ shape and the patient’s age. To validate the model, we compared its capacity to compress the signal while maintaining high information content against a Principal Component Analysis (PCA) of the Raman spectra, the fields’ standard. As a final step, we applied the feature engineering model to a dataset of intraoperative human Raman spectra to identify which molecular processes were indicative of brain cancer. Our method showed better information retention than PCA. Our analysis of in vivo Raman measurement showed that areas with high-density of malignant cells had increased expression of nucleic acids and protein compounds, notably collagen, tryptophan and phenylalanine. Patient age seemed to affect the impact of nucleic acids, proteins and lipids on the Raman spectra. Our work demonstrates the importance of appropriate statistical modeling in the implementation of Raman-based surgical devices

    Optics in Our Time

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    Optics, Lasers, Photonics, Optical Devices; Quantum Optics; Popular Science in Physics; History and Philosophical Foundations of Physic
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