Outdoor work and solar radiation exposure: Evaluation method for epidemiological studies.

Background: The health risk related to an excessive exposure to solar radiation (SR) is well known. The Sun represents the main exposure source for all the frequency bands of optical radiation, that is the part of the electromagnetic spectrum ranging between 100 nm and 1 mm, including infrared (IR), ultraviolet (UV) and visible radiation. According to recent studies, outdoor workers have a relevant exposure to SR but few studies available in scientific literature have attempted to retrace a detailed history of individual exposure. Material and Methods: We propose a new method for the evaluation of SR cumulative exposure both during work and leisure time, integrating subjective and objective data. The former is collected by means of an interviewer administrated questionnaire. The latter is available through the Internet databases for many geographical regions and through individual exposure measurements. The data is integrated into a mathematical algorithm, in order to obtain an esteem of the individual total amount of SR the subjects have been exposed to during their lives. Results: The questionnaire has been tested for 58 voluntary subjects. Environmental exposure data through online databases has been collected for 3 different places in Italy in 2012. Individual exposure by electronic UV dosimeter has been measured in 6 fishermen. A mathematical algorithm integrating subjective and objective data has been elaborated. Conclusions: The method proposed may be used in epidemiological studies to evaluate specific correlations with biological effects of SR and to weigh the role of the personal and environmental factors that may increase or reduce SR exposure

Impact of climate change on occupational exposure to solar radiation

Occupational exposure to solar radiation may induce both acute and long-term effects on skin and eyes. Personal exposure is very difficult to assess accurately, as it depends on environmental, organisational and individual factors. The ongoing climate change interacting with stratospheric ozone dynamics may affect occupational exposure to solar radiation. In addition, tropospheric levels of environmental pollutants interacting with solar radiation may be altered by climate dynamics, so introducing another variable affecting the overall exposure to solar radiation. Given the uncertainties regarding the direction of changes in exposure to solar radiation due to climate change, compliance of outdoor workers with protective measures and a proper health surveillance are crucial. At the same time, education and training, along with the promotion of healthier lifestyles, are of paramount importance

MICROWAVE-ASSISTED BRUCITE AND TALC REACTIONS WITH CO2 AS A PROXY FOR CARBON CAPTURE AND STORAGE BY SERPENTINE

In the last decades many studies have been focusing on Carbon Capture and Storage (CCS) to find a possible remedy to reduce the large increase of anthropogenic carbon dioxide (CO ). Mineral Carbonation (MC) is a potential solution for almost irreversible chemical long-term CCS. It concerns the combination of CaO and MgO with CO forming spontaneously and exothermically dolomite and magnesite. However, kinetic barriers pose sever limitations for the practical exploitation of this reaction. High fractions of MgO are available in silicates such as olivine, orthopyroxene, clinopyroxene and serpentine. To date, data reported that serpentine polymorphs, above all antigorite, is an excellent candidate for fixing the CO as the reaction efficiency is approximately 92% compared to lizardite (40%) and olivine (66%). This is due to the surface reactivity of approximately 18.7 m /g for the dehydrated antigorite compared to10.8 m /g for dehydrated lizardite and 4.6 m /g for olivine. The microwave assisted process for CCS is an innovative technology that can be employed to catalyze the reaction through thermal and non-thermal mechanisms. Some pioneering tests of direct carbonation by microwave hydrothermal equipment have been performed on olivine, lizardite and chrysotile powders [1] but not on antigorite. The structure of serpentine is characterized by corrugated stacked layers of silica and brucite. For this reason, MC involves dissolution of SiO layers, dissolution/dehydration of Mg(OH) layers, and precipitation of magnesium carbonate. To address the chemical response of the single phases, experiments have been performed by both a local microwave-source acting locally on a specific crystal surface and a volume source interacting with an ensemble of grains on synthetic powders and single crystals of pure brucite and talc. In a second step, treatments have been extended to chrysotile, lizardite and antigorite. A characterization of the mechanism and kinetics were performed by scanning probe microscopy on the surface of single crystals phases, supported by Raman spectroscopy and by Scanning and Transmission Electron Microscopy study performed on micro- and nano-sized grains. [1] White, et al. Reaction mechanisms of magnesium silicates with carbon dioxide in microwave fields. Final Report to the U.S. Department ofEnergy, National Energy Technology Laboratory (2004

A novel framework for MR image segmentation and quantification by using MedGA.

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and automatically determining a suitable optimal threshold for bimodal Magnetic Resonance (MR) images, by designing an intelligent image analysis framework tailored to effectively assist the physicians during their decision-making tasks. METHODS: In this work, we present a novel evolutionary framework for image enhancement, automatic global thresholding, and segmentation, which is here applied to different clinical scenarios involving bimodal MR image analysis: (i) uterine fibroid segmentation in MR guided Focused Ultrasound Surgery, and (ii) brain metastatic cancer segmentation in neuro-radiosurgery therapy. Our framework exploits MedGA as a pre-processing stage. MedGA is an image enhancement method based on Genetic Algorithms that improves the threshold selection, obtained by the efficient Iterative Optimal Threshold Selection algorithm, between the underlying sub-distributions in a nearly bimodal histogram. RESULTS: The results achieved by the proposed evolutionary framework were quantitatively evaluated, showing that the use of MedGA as a pre-processing stage outperforms the conventional image enhancement methods (i.e., histogram equalization, bi-histogram equalization, Gamma transformation, and sigmoid transformation), in terms of both MR image enhancement and segmentation evaluation metrics. CONCLUSIONS: Thanks to this framework, MR image segmentation accuracy is considerably increased, allowing for measurement repeatability in clinical workflows. The proposed computational solution could be well-suited for other clinical contexts requiring MR image analysis and segmentation, aiming at providing useful insights for differential diagnosis and prognosis

Health Surveillance and Response to SARS-CoV-2 Mass Testing in Health Workers of a Large Italian Hospital in Verona, Veneto

Italy presented the first largest COVID-19 outbreak outside of China. Veneto currently ranks fourth among the Italian regions for COVID-19 confirmed cases (~19,000). This study presents health surveillance data for SARS-CoV-2 in 6100 health workers (HW) employed in a large public hospital. Workers underwent oropharyngeal and nasopharyngeal swabs, with a total of 5942 participants (97.5% of the population). A total of 11,890 specimens were tested for SARS-CoV-2 infection using PCR, identifying the viral genes E, RdRP, and N. Positive tests were returned for 238 workers (cumulative incidence of 4.0%, similar in both COVID and nonCOVID units). SARS-CoV-2 risk was not affected by gender, age, or job type, whereas work setting and occupation were both predictors of infection. The risk was higher in medical wards (OR 2.7, 95% CI 1.9\u20133.9) and health services (OR 4.3, 95% CI 2.4\u20137.6), and lower in surgical wards and administration areas. To our knowledge, this study represents the largest available HW case list swab-tested for SARS-CoV-2, covering almost the total workforce. Mass screening enabled the isolation of HW, improved risk assessment, allowed for close contacts of and infected HW to return to work, provided evidence of SARS-CoV-2 diffusion, and presented solid ground to prevent nosocomial SARS-CoV-2 infections. The ongoing concurrent sero-epidemiological study aims to enable the improvement of health surveillance to maintain the safety of HWs and the communities they serve

Occupational Exposure to Solar UV Radiation of a Group of Fishermen Working in the Italian North Adriatic Sea

Occupational solar radiation exposure is a relevant heath risk in the fishing sector. Our aim was to provide a detailed evaluation of individual UV exposure in three different fishing activities in Italy, with personal UV dosimeters and a simple formula to calculate the fraction of ambient erythemal UV dose received by the workers. The potential individual UV exposure of the fishermen was between 65 and 542 Joules/m2. The percentages of the ambient exposure were estimated between 2.5% and 65.3%. Workers\u2019 UV exposure was mainly influenced by the characteristics of the work activity, the postures adopted, and the type of boats. Overall, our data showed that 43% of the daily measurements could result largely above the occupational limits of 1\u20131.3 standard erythemal dose (i.e., 100 Joules/m2) per day, in case of exposure of uncovered skin areas. Measurements of individual UV exposure are important not only to assess the risk but also to increase workers\u2019 perception and stimulate the adoption of preventive measures to reduce solar UV risk. Furthermore, the simple method proposed, linking ambient erythemal UV dose to the workers\u2019 exposure, can be a promising tool for a reliable assessment of the UV risk, as time series of environmental UV dose are widely availabl

ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy.

Advances in microscopy imaging technologies have enabled the visualization of live-cell dynamic processes using time-lapse microscopy imaging. However, modern methods exhibit several limitations related to the training phases and to time constraints, hindering their application in the laboratory practice. In this work, we present a novel method, named Automated Cell Detection and Counting (ACDC), designed for activity detection of fluorescent labeled cell nuclei in time-lapse microscopy. ACDC overcomes the limitations of the literature methods, by first applying bilateral filtering on the original image to smooth the input cell images while preserving edge sharpness, and then by exploiting the watershed transform and morphological filtering. Moreover, ACDC represents a feasible solution for the laboratory practice, as it can leverage multi-core architectures in computer clusters to efficiently handle large-scale imaging datasets. Indeed, our Parent-Workers implementation of ACDC allows to obtain up to a 3.7× speed-up compared to the sequential counterpart. ACDC was tested on two distinct cell imaging datasets to assess its accuracy and effectiveness on images with different characteristics. We achieved an accurate cell-count and nuclei segmentation without relying on large-scale annotated datasets, a result confirmed by the average Dice Similarity Coefficients of 76.84 and 88.64 and the Pearson coefficients of 0.99 and 0.96, calculated against the manual cell counting, on the two tested datasets