An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy

Differential Optical Absorption Spectroscopy (DOAS) is commonly used to measure gas emissions from volcanoes. DOAS instruments measure the absorption of solar ultraviolet (UV) radiation scattered in the atmosphere by sulfur dioxide (SO2) and other trace gases contained in volcanic plumes. The standard spectral retrieval methods assume that all measured light comes from behind the plume and has passed through the plume along a straight line. However, a fraction of the light that reaches the instrument may have been scattered beneath the plume and thus has passed around it. Since this component does not contain the absorption signatures of gases in the plume, it effectively “dilutes” the measurements and causes underestimation of the gas abundance in the plume. This dilution effect is small for clean-air conditions and short distances between instrument and plume. However, plume measurements made at long distance and/or in conditions with significant atmospheric aerosol, haze, or clouds may be severely affected. Thus, light dilution is regarded as a major error source in DOAS measurements of volcanic degassing. Several attempts have been made to model the phenomena and the physical mechanisms are today relatively well understood. However, these models require knowledge of the local atmospheric aerosol composition and distribution, parameters that are almost always unknown. Thus, a practical algorithm to quantitatively correct for the dilution effect is still lacking. Here, we propose such an algorithm focused specifically on SO2 measurements. The method relies on the fact that light absorption becomes non-linear for high SO2 loads, and that strong and weak SO2 absorption bands are unequally affected by the diluting signal. These differences can be used to identify when dilution is occurring. Moreover, if we assume that the spectral radiance of the diluting light is identical to the spectrum of light measured away from the plume, a measured clean air spectrum can be used to represent the dilution component. A correction can then be implemented by iteratively subtracting fractions of this clean air spectrum from the measured spectrum until the respective absorption signals on strong and weak SO2 absorption bands are consistent with a single overhead SO2 abundance. In this manner, we can quantify the magnitude of light dilution in each individual measurement spectrum as well as obtaining a dilution-corrected value for the SO2 column density along the line of sight of the instrument. This paper first presents the theory behind the method, then discusses validation experiments using a radiative transfer model, as well as applications to field data obtained under different measurement conditions at three different locations; Fagradalsfjall located on the Reykjanaes peninsula in south Island, Manam located off the northeast coast of mainland Papua New Guinea and Holuhraun located in the inland of north east Island

Advanced endoscopic imaging for diagnosis of inflammatory bowel diseases : present and future perspectives

Crohn's disease and ulcerative colitis are chronic inflammatory bowel diseases (IBD) causing severe damage of the luminal gastrointestinal tract. Differential diagnosis between both disease entities is sometimes awkward requiring a multifactorial pathway, including clinical and laboratory data, radiological findings, histopathology and endoscopy. Apart from disease diagnosis, endoscopy in IBD plays a major role in prediction of disease severity and extent (i.e. mucosal healing) for tailored patient management and for screening of colitis-associated cancer and its precursor lesions. In this state-of-the-art review, we focus on current applications of endoscopy for diagnosis and surveillance of IBD. Moreover, we will discuss the latest guidelines on surveillance and provide an overview of the most recent developments in the field of endoscopic imaging and IBD

Differential Optical Absorption Spectroscopy (DOAS) Measurements of Ozone in the 280--290 nm Wavelength Region

The differential absorption structure of the ozone spectrum between 250 and 330 nm has been investigated in order to determine the optimal wavelength region to be utilized for active differential optical absorption spectroscopy (DOAS) measurements. Considering aspects of atmospheric attenuation and interference from other species as well as the magnitude of the differential absorption cross section, an interval around 283 nm was found to be a good candidate for this application. This result was also verified during 12 months of continuous ozone monitoring in an urban environment

Matrix Effects in Secondary Ion Mass Spectrometric Analysis of Biological Tissue

We have made several observations during the course of our studies that show the presence of matrix effects in soft biological tissue and standards. The sputtering rate of gelatin is approximately twice that of epoxy resin, but the ion yield of lithium in gelatin is an order of magnitude less than in epoxy. Osmium impregnation of freeze-dried material significantly alters the localization of calcium, but not potassium and barium. The absolute count rate for calcium in osmicated tissue is increased several-fold above that in freeze-dried tissue. Scanning electron microscopy of sputtered material shows the formation of cones during sputtering, which is particularly, but not exclusively, associated with melanin granules and red blood cells. These structures are known to be highly emissive for Na, K, and Ca. Boron implanted tissue also exhibits selective boron emission from melanin granules. Relative proportions of monoatomic and polyatomic emission vary in epoxy, gelatin and tissue. Ion images of carbon, chlorine and vanadium in tissue embedded with a vanadium-doped epoxy resin show variations in local regions that correspond to tissue structure. The energy distributions of common secondary ions differed somewhat in resin and two different tissue regions. These examples show the existence of potential matrix effects in soft biological tissue that involve both differential sputtering and ion yield effects

Diagnosis and management of toxicities of immune checkpoint inhibitors in hepatocellular carcinoma

Immune checkpoint inhibitors (ICIs) have reshaped cancer therapy. ICIs enhance T cell activation through various mechanisms and may help reverse the exhausted phenotype of tumour-infiltrating lymphocytes. However, disrupting the key role that checkpoint molecules play in immune homeostasis may result in autoimmune complications. A broad range of immune-related adverse events (irAEs) involve almost every organ but mostly affect the skin, digestive system, lung, endocrine glands, nervous system, kidney, blood cells, and musculoskeletal system. They are usually manageable but can be life-threatening. The incidence of irAEs is not very different in patients with hepatocellular carcinoma (HCC) compared to other tumour types, although there is a trend towards a higher incidence of hepatic irAEs. HCC usually develops on a background of cirrhosis with associated systemic manifestations. Extrahepatic organ dysfunction in cirrhosis may cause signs and symptoms that overlap with irAEs or increase their severity. Available guidelines for the management of irAEs have not specifically considered the assessment of toxicities in the context of patients with liver cancer and cirrhosis. This review addresses the toxicity profile of ICIs in patients with HCC, focusing on the challenges that the underlying liver disease poses to their diagnosis and management. Challenges include late recognition, inadequate work-up and delayed treatment, overdiagnosis and inappropriate interruption of ICIs, complications caused by immunosuppressive therapy, and increased cost. A specific algorithm for the management of hepatic irAEs is provided

Star-Image Centering with Deep Learning: HST/WFPC2 Images

A Deep Learning (DL) algorithm is built and tested for its ability to determine centers of star images on HST/WFPC2 exposures, in filters F555W and F814W. These archival observations hold great potential for proper-motion studies, but the undersampling in the camera's detectors presents challenges for conventional centering algorithms. Two exquisite data sets of over 600 exposures of the cluster NGC 104 in these filters are used as a testbed for training and evaluation of the DL code. Results indicate a single-measurement standard error of from 8.5 to 11 mpix, depending on detector and filter.This compares favorably to the $\sim20$ mpix achieved with the customary ``effective PSF'' centering procedure for WFPC2 images. Importantly, pixel-phase error is largely eliminated when using the DL method. The current tests are limited to the central portion of each detector; in future studies the DL code will be modified to allow for the known variation of the PSF across the detectors.Comment: accepted for publication by PAS

Multi-criteria assessment of the Representative Elementary Watershed approach on the Donga catchment (Benin) using a downward approach of model complexity

International audienceThis study is part of the AMMA – African Multidisciplinary Monsoon Analysis – project and aims at a better understanding and modelling of the Donga catchment (580 km2, Benin) behaviour. For this purpose, we applied the REW concept proposed by Reggiani et al. (1998, 1999), which allows the description of the main local processes at the sub-watershed scale. Such distributed hydrological models, which represent hydrological processes at various scales, should be evaluated not only on the discharge at the outlet but also on each of the represented processes and in several points of the catchment. This kind of multi-criteria evaluation is of importance in order to assess the global behaviour of the models. We applied such multi-criteria strategy to the Donga catchment (586 km2), in Benin. The work is supported by a strategy of observation, undertaken since 1998 consisting in a network of 20 rain gauges, an automatic meteorological station, 6 discharge stations and 18 wells. The first goal of this study is to assess the model ability to reproduce the discharge at the outlet, the water table dynamics in several points of the catchment and the vadose zone dynamics at the sub-catchment scale. We tested two spatial discretisations of increasing resolution. To test the internal structure of the model, we looked at its ability to represent also the discharge at intermediary stations. After adjustment of soil parameters, the model is shown to accurately represent discharge down to a drainage area of 100 km2, whereas poorer simulation is achieved on smaller catchments. We introduced the spatial variability of rainfall by distributing the daily rainfall over the REW and obtained a very low sensitivity of the model response to this variability. Our results suggest that processes in the unsaturated zone should first be improved, in order to better simulate soil water dynamics and represent perched water tables which were not included in this first modelling study

Swimming at the Time of COVID-19: A Cross-Sectional Study among Young Italian Competitive Athletes

During the coronavirus disease 2019 (COVID-19) pandemic, several restriction measures were imposed to control the virus transmission, with important repercussions on different sectors, including sport. This study aimed to explore the effects of the COVID-19 pandemic on Italian competitive swimmers by analyzing how the disease and the restriction measures affected their training. In total, 396 competitive swimmers (mean age 16.0 ± 3.2 years) participated. A questionnaire was used to collect their general information, to assess whether they had had COVID-19 and the number of training days lost due to the disease or to the closure of swimming facilities, and the possible alternative training adopted. Twenty-four (6.1%) participants had had COVID-19 and lost, on average, 32 training days. The closure of facilities caused an interruption in swimming training for about 18% of the participants. The majority of these continued their training, mainly through home-based exercise, but reduced their weekly training time (-8 median hours/week). A positive association was found between regularly adopted weekly training volume and that assumed during pandemic closure (OR 9.433, CI95% 1.644–54.137, p = 0.012), suggesting that the previous level of engagement in sport can represent a predictor of exercise maintenance in challenging situations such as a pandemic. Further studies are needed to identify personal, environmental, and social resources that can help individuals to counteract the negative effects of restriction measures

Are nutrition and physical activity associated with gut microbiota? A pilot study on a sample of healthy young adults

BACKGROUND: The literature shows that gut microbiota composition is related with health, and a lot of individual and outer factors may determine its variability. In particular, nutrition and exercise seem to influence the presence in the gut of the two major bacterial phyla of Firmicutes and Bacteroidetes. STUDY DESIGN: An ongoing cross-sectional investigation is aimed to explore these associations in humans. METHODS: Healthy Caucasian young adults were asked to provide a fecal sample in order to analyze their gut microbiome considering their Body Mass Index (BMI), adherence to Mediterranean diet and Physical Activity (PA) level. RESULTS: A total of 59 participants (49.1% males, mean age 23.1 ± 3.14 years) were enrolled so far. Firmicutes (61.6±14.6) and Bacteroidetes (30.7 ± 13.3) showed the highest relative abundance in fecal samples. The Pearson's analysis showed a significant negative correlation between PA and Firmicutes (r =-0.270, p = 0.03). Linear regression confirmed a significant decrease of this phylum with the increase of PA (R2 = 0.07, p = 0.03). CONCLUSIONS: These preliminary results suggest the association between physical activity and gut microbiota composition in healthy humans

Monitoring weeder robots and anticipating their functioning by using advanced topological data analysis

The present paper aims at analyzing the topological content of the complex trajectories that weeder-autonomous robots follow in operation. We will prove that the topological descriptors of these trajectories are affected by the robot environment as well as by the robot state, with respect to maintenance operations. Most of existing methodologies enabling efficient diagnosis are based on the data analysis, and in particular on some statistical quantities derived from the data. The present work explores the use of an original approach that instead of analyzing quantities derived from the data, analyzes the “shape” of the data, that is, the time series topology based on the homology persistence. We will prove that this procedure is able to extract valuable patterns able to discriminate the trajectories that the robot follows depending on the particular patch in which it operates, as well as to differentiate the robot behavior before and after undergoing a maintenance operation. Even if it is a preliminary work, and it does not pretend to compare its performances with respect to other existing technologies, this work opens new perspectives in considering quite natural and simple descriptors based on the intrinsic information that data contains, with the aim of performing efficient diagnosis and prognosis. Copyright © 2021 Frahi, Sancarlos, Galle, Beaulieu, Chambard, Falco, Cueto and Chinesta