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The ATL2MED demonstration experiment involved two autonomous surface vehicles from Saildrone Inc. (SD) which travelled a route from the eastern tropical North Atlantic to the Adriatic Sea between October 2019 and July 2020 (see Table A6). This 9-month experiment in a transition zone between the temperate and tropical belts represents a major challenge for the SD's operations. The sensors on board were exposed to varying degrees of degradation and biofouling depending on the geographical area and season, which led to a deterioration in the measurements. As a result, some maintenance measures were required during the mission. We address the difficulty of correcting the data during a period of COVID-19 restrictions, which significantly reduced the number of discrete samples planned for the SD salinity and dissolved oxygen validation. This article details alternative correction methods for salinity and dissolved oxygen. Due to the lack of in situ data, model products have been used to correct the salinity data acquired by the SD instruments, and then the resulting corrected salinity was validated with data from fixed ocean stations, gliders, and Argo floats. In addition, dissolved oxygen data acquired from the SD instruments after correction using air oxygen measurements were tested and found to be coherent with the variation in oxygen concentrations expected from changes in temperature and phytoplankton abundance (from chlorophyll a). The correction methods are relevant and useful in situations where validation capabilities are lacking, which was the case during the ATL2MED demonstration experiment. For future experiments, a more frequent sample collection would improve the data qualification and validation. [ABSTRACT FROM AUTHOR]

River inlets, deltas, and estuaries represent delicate ecosystems highly susceptible to climate change impacts. While significant progress has been made in understanding the morphodynamics of these environments in recent decades, the development of models still requires thorough testing and data integration. In this context, remote sensing emerges as a potent tool, providing crucial data and the ability to monitor temporal changes. In this paper, an integrated approach combining remote sensing and morphodynamic modeling is proposed to assess river systems comprehensively. By utilizing multispectral or RGB optical imagery from satellites or UAVs for river classification and remotely derived bathymetry, echo sounder data for ground truth, and photogrammetric modeling of emerged areas, we outline a procedure to create an integrated and continuous digital terrain model (DTM) of a riverbed, paying particular attention to the wet–dry interface. This method enables us to identify the river centerline, its width, and its slope variations. Additionally, by applying a linear morphodynamic model that considers the spatial variability of river morphology commonly found in estuarine environments, it is possible to predict the wavelength and migration rate of sediment bars. This approach has been successfully applied to recreate the DTM and monitor the morphodynamics of the seaward reach of the Roya River (Italy). [ABSTRACT FROM AUTHOR]

We provide a concise overview of the literature concerning the factors influencing preferences for redistribution, with particular attention to works that have integrated considerations of gender and/or cohort heterogeneity into their analyses. We then present a series of stylized facts on preferences for redistribution based on data from the European Social Survey for a wide array of European countries over the period spanning from 2002 to 2022. We document that, since 2002, the average preferences for redistribution have increased. While the gender gap has remained substantially unchanged, the generational gap has widened over time. Distinguishing women and men by a set of individual characteristics, instead, there exists a not negligible heterogeneity both 'between' and 'within' women and men. At the country level, the overall gender gap in preferences for redistribution increases as the country's per capita income or gender equality increase. Conversely, the gender gap decreases in more income, unequal, and religious countries. Finally, looking at the two exogenous shocks, that is, the 2008 financial and economic crisis and the Covid-19 pandemic, we observe that average individual attitudes towards redistribution react to both events but in a surprisingly opposite way, with a relevant heterogeneity across different sub-groups of women and men. [ABSTRACT FROM AUTHOR]

Several landslide susceptibility (LS) maps at various scales of analysis have been performed with specific zoning purposes and techniques. Supervised machine learning algorithms (ML) have become one of the most diffused techniques for landslide prediction, whose reliability is firmly based on the quality of input data. Site-specific landslide inventories are often more accurate and complete than national or worldwide databases. For these reasons, detailed landslide inventory and predisposing variables must be collected to derive reliable LS products. However, high-quality data are often rare, and risk managers must consider lower-resolution available products with no more than informative purposes. In this work, we compared different ML models to select the most accurate for large-scale LS assessment within the Municipality of Rome. The ExtraTreesClassifier outperformed the others reaching an average F1-score of 0.896. Thereafter, we addressed the reliability of open-source LS maps at different scales of analysis (global to regional) by means of statistical and spatial analysis. The obtained results shed light on the difference in hazard zoning depending on the scale and mapping unit. An approach for low-resolution LS data fusion was attempted, assessing the importance of the adopted criteria, which increased the ability to detect occurred landslides while maintaining precision. [ABSTRACT FROM AUTHOR]

In the last decades, microalgae have gained a lot of interest in the energy and chemical industry thanks to their higher biofuel productivity potential rather than other land plants. To better exploit their green nature and renewable power, anaerobic digestion (AD) fits perfectly for the scope. AD is a metabolic process that generates a methane-rich gas, the biogas, which can then be used for clean electricity and chemicals production. High interest has arisen in the field of AD in industrial practice, and a lot of experiments were done to produce biogas from different types of feedstocks. In this manner, microalgae represent a promising opportunity to produce biogas from renewable and self-sustainable organisms. Biogas is mostly used to produce electrical energy and heat through cogeneration cycles or is upgraded to biomethane through the removal of CO2 and impurities, reaching a CH4 purity above 95-97% vol. On the other hand, an interesting perspective of biogas exploitation is its conversion in biofuels such as methanol or dimethyl-ether. This new concept of bio-refining lays the ground for two aspects: The economical valorisation of the biomass with a more valuable product as bio-methanol and the conversion of biogas to biofuel to fix part of the carbon in a chemical molecule, avoiding the re-emission in the atmosphere of CO2. The scope of this work is to present and technically analyse a conceptual design of a circular bio-refinery based on microalgae biomass feedstock with the final output of methanol production. Biogas production from microalgae is modelled with PythonTM (v3.9) while process simulations are computed using state of the art industrial simulation packages like Aspen HYSIS® v11. Interesting factors to analyse are carbon emission, the field of use for functional production, the global process yield and preliminary feasibility analysis.

This paper presents a methodology tuned to support the management of underground pipelines (sewer and aqueduct networks) in Rome, often threatened by the sudden formation of sinkholes related to the upward migration of existing underground cavities. The methodology integrates data coming from the assessment of susceptibility to sinkhole formation and the advanced processing of satellite-based SAR imagery. The former, performed through the multivariate logistic regression technique, relies on a detailed database of stratigraphic and other thematic (i.e. sinkhole inventory and density of underground cavities) information. A-DInSAR processing of satellite images, for which we developed on-purpose algorithms to filter only data relevant for the process under study, allowed us to provide density maps of subsiding reflectors whose likelihood to be precursors of sinkhole collapses is rated based on the integration with the susceptibility map. The procedure is addressed to point out potentially critical ‘hotspots’ that the company managing the underground networks should pay attention to by means of further detailed investigations. Recent (i.e. occurred after the finalization of the products shown in this paper) sinkholes validated the reliability of the procedure adopted, whose strength is the data fusion able to produce refined and focused information starting from independent and more generic datasets.

This work deals with the landslides affecting the area surrounding the village of San Martino sulla Marrucina and involving the neighboring municipalities of Casacanditella and Filetto. The geological and geomorphological settings of this area are being discussed. The enclosed maps have been realized following a multidisciplinary approach, based on morphometric, geological, and geomorphological analyses and supported by air-photo interpretation, dendrochronology, and satellite SAR interferometry (InSAR). The map is organized in four sections: orography (on the upper part), geological map (on the upper right part), main geomorphological map (in the central left part, 1:7,500 scale), and multitemporal analysis (in the lower part). The aforementioned multi-temporal assessment of landslides was performed according to the geomorphological evidence-based criteria and the past ground displacement measurements were obtained by dendrochronology and InSAR. The aim of the study is to understand the evolution in time and space of this landslide area, focusing on the corresponding kinematics.

Abstract Background The persistence of HIV-1 in reservoir cells is one of the major obstacles to eradicating the virus in infected individuals receiving combination antiretroviral therapy (ART). HIV-1 persists in infected cells as a stable integrated genome and more labile unintegrated DNA (uDNA), which includes linear, 1-LTR and 2-LTR circular DNA. 2-LTR circle DNA, although less abundant, is considered a surrogate marker of recent infection events and is currently used instead of the other unintegrated species as a diagnostic tool. This pilot study aimed to investigate how to best achieve the measurement of uDNA. Methods A comparative analysis of two qPCR-based methods (U-assay and 2-LTR assay) was performed on the blood of 12 ART-naïve, 14 viremic and 29 aviremic On-ART patients and 20 untreated spontaneous controllers (HIC), sampled at a single time point. Results The U-assay, which quantified all unintegrated DNA species, showed greater sensitivity than the 2-LTR assay (up to 75%, p

The aim of this work is to evaluate the potential application of a new sustainable technology, called Acid Gas to Syngas, on steam reforming process in order to reduce the carbon dioxide emissions. Indeed, steam reforming has high emissions of carbon dioxide, at almost 7 kg of carbon dioxide per 1 kg of hydrogen produced. The key idea of the new technology is to convert carbon dioxide and hydrogen sulfide coming from natural gas desulfurization into additional hydrogen. Coupling different software, i.e. Aspen HYSYS and MATLAB, a complete plant model, able to manage the recycle of unconverted acid gases, has been developed. The importance of introduced innovations is highlighted and a comparison between the old process and the new one with Acid Gas to Syngas technology is built up. With Acid Gas to Syngas technology the natural gas consumption and carbon dioxide emissions can be reduced up to 3%.

The quantification of proviral DNA is raising interest in view of clinical management and functional HIV eradication. Measures of all unintegrated HIV DNA (uDNA) forms in infected reservoir cells provides information on recent replication events that is not found from other proviral DNA assays. To evaluate its actual relevance in a cohort of perinatally-infected adult HIV patients (PHIV), we studied how peripheral blood mononuclear cell uDNA levels correlated with total HIV DNA (tDNA) and with overall replication or innate immune control parameters including NK cell activation/exhaustion and lymphoid turnover. Twenty-two PHIV were included, with successfully controlled HIV (HIV RNA

The growing attention regarding a more sustainable future, and thus into energy recovery and waste reduction technologies, has intensified the interest towards processes which allow to exploit waste and biomasses to generate energy, such as the anaerobic digestion. Improving the efficiency of this industrial application is crucial to increase methane production, and is essential from the economic, environmental and safety point of view. This study focuses on the thermodynamic modelling of a steady-state reactor as a flash unit, in order to determine the best operating conditions to produce the maximum amount of pure bio-methane. To this purpose, a new hybrid approach based on the Peng–Robinson cubic equation of state and on the Multi-Parameter Helmholtz-Energy EoS has been proposed. The simulations, performed using the developed algorithm at temperatures between 20 and 55 °C and at pressure values between 0.3 atm and 1.5 atm, point out that the fugacity of the mixture evaluated with the proposed technique is much more accurate and reliable than the one calculated with the PR EoS. In addition, this research has shown not only that the purity and the production of the biogas can be optimised by working at mesophilic conditions and at pressure between 1 atm and 1.5 atm, but also that it is not convenient to operate in a temperature range of 42 °C–45 °C, since about 20 % more H2S goes into the exiting biogas, reducing the CH4 amount and raising the post-treatment costs. Lastly, it has been seen that there is a significant water content in the vapour phase (∼5 %wt.), and this is a factor to be taken into account in order to improve the process.

Echo-sounders and Vessel-Mounted Acoustic Doppler Current Profilers (VM-ADCP) are widely operating onboard research vessels with the aim of providing real-time backscatter and ocean current profiles along the route, while the vessel is moving. Backscatter data are exploited to infer important information about zooplankton presence and distribution. Nevertheless, as these organisms daily vertically migrate even below the depth of the instrument range, the combination of space and time variability make their mapping from a moving vessel quite complex. The objective of this work is to describe a GIS application developed for the management and analysis of these data. The GIS capability as a tool to facilitate zooplankton investigations is assessed by means of a test-case in the area of the Ligurian Sea (Western Mediterranean) by using VM-ADCP backscatter data made available during oceanographic campaigns. The system, which includes a high-resolution bathymetry, environmental parameters, ephemeris, allows to select and visualize data sorted according to all the possible layer combinations. Moreover, different backscatter profiles, characterizing the identified migration phases can be enlightened by means of false color scale representation.

Introduction: A potential overlap in symptoms between post-acute COVID-19 syndrome and post-COVID-19 vaccination syndrome has been noted. We report a paired description of patients presenting with similar manifestations involving the central (CNS) or peripheral nervous system (PNS) following SARS-CoV-2 infection or vaccination, suggesting that both may have triggered similar immune-mediated neurological disorders in the presence of anti-idiotype antibodies directed against the ACE2 protein. Patients and methods: Four patients exhibited overlapping neurological manifestations following SARS-CoV-2 infection or vaccination: radiculitis, Guillain -- Barré syndrome, and MRI-negative myelitis, respectively, sharing positivity for anti-ACE2 antibodies. Autoantibodies against AQP-4, MOG, GlyR, GAD, and amphiphysin, onconeural antibodies for CNS syndromes, and anti-ganglioside antibodies for PNS syndromes tested negative in all patients. Discussion: Anti-idiotype antibodies against ACE2 have been detected in patients who recovered from COVID-19 infection, and it has been hypothesized that such antibodies may mediate adverse events following SARS-CoV-2 infection or vaccination, resulting in the activation of the immune system against cells expressing ACE2, such as neurons. Our data reveal clinically overlapping syndromes triggered by SARS-CoV-2 infection or vaccination, sharing positivity for anti-ACE2 antibodies. Their presence, in the absence of other classic autoimmune markers of CNS or PNS involvement, suggests that they might play an active role in the context of an aberrant immune response. Conclusion: Anti-idiotype antibodies directed against ACE2 may be triggered by both SARS-CoV-2 infection and vaccination, possibly contributing to neurological autoimmune manifestations. Their pathogenic role, however, remains to be demonstrated in large-scale, more structured studies. [ABSTRACT FROM AUTHOR]

Monitoring slow-moving landslides is a crucial task for socioeconomic risk prevention and/or mitigation. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) is an advanced remote sensing method for monitoring ground deformation. In this research, PS-InSAR time series derived from COSMO-SkyMed (descending orbit) and Sentinel-1 (ascending orbit) are analyzed for a region in Central Apennines in Italy. The sequential turning point detection method (STPD) is implemented to detect the trend turning dates and their directions in the PS-InSAR time series within areas of interest susceptible to landslides. The monthly maps of significant turning points and their directions for years 2018, 2019, 2020, and 2021 are produced and classified for four Italian administrative regions, namely, Marche, Umbria, Abruzzo, and Lazio. Monthly global precipitation measurement (GPM) images at 0. 1 ∘ × 0. 1 ∘ spatial resolution and four local precipitation time series are also analyzed by STPD to investigate when the precipitation rate has changed and how they might have reactivated slow-moving landslides. Generally, a strong correlation ( r ≥ 0.7 ) is observed between GPM (satellite-based) and local precipitation (station-based) with similar STPD results. Marche and Abruzzo (the coastal regions) have an insignificant precipitation rate while Umbria and Lazio have a significant increase in precipitation from 2017 to 2023. The coastal regions also exhibit relatively lower precipitation amounts. The results indicate a strong correlation between the trend turning dates of the accumulated precipitation and displacement time series, especially for Lazio during summer and fall 2020, where relatively more significant precipitation rate of change is observed. The findings of this study may guide stakeholders and responsible authorities for risk management and mitigating damage to infrastructures. [ABSTRACT FROM AUTHOR]

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Biogas has emerged as a valid feedstock for biomethanol production from steam reforming. This study investigates an alternative layout based on an auto-thermal electrified reforming assuming a 1 MW equivalent anaerobic digestion plant as a source for methanol synthesis. The process considers an oxy-steam combustion of biogas and direct carbon sequestration with the presence of a reverse water–gas shift reactor to convert CO2 and H2 produced by a solid oxide electrolyzer cell to syngas. Thermal auto-sufficiency is ensured for the reverse water–gas shift reaction through the biogas oxy-combustion, and steam production is met with the integration of heat network recovery, with an overall process total electrical demand. This work compares the proposed process of electrification with standard biogas reforming and data available from the literature. To compare the results, some key performance indicators have been introduced, showing a carbon impact of only 0.04 kgCO2/kgMeOH for the electrified process compared to 1.38 kgCO2/kgMeOH in the case of biogas reforming technology. The auto-thermal electrified design allows for the recovery of 66.32% of the carbon available in the biogas, while a similar electrified process for syngas production reported in literature reaches only 15.34%. The overall energy impact of the simulated scenarios shows 94% of the total energy demand for the auto-thermal scenario associated with the electrolyzer. Finally, the introduction of the new layout is taken into consideration based on the country's carbon intensity, proving carbon neutrality for values lower than 75 gCO2/kWh and demonstrating the role of renewable energies in the industrial application of the process. [ABSTRACT FROM AUTHOR]

Breast metastasis originating from a primary lung tumor is exceedingly rare and can present challenges in distinguishing it from primary breast cancer. This case report discusses the management of a 64-year-old woman who initially presented with a nodule in her left breast. A biopsy revealed an infiltrating ductal carcinoma. Despite negative BRCA genetic testing, her significant family history of cancer and the presence of a newly detected right breast lesion led to a bilateral mastectomy. Post-operative imaging identified multiple hypodense nodules and a spiculated pulmonary nodule, necessitating further investigation. An endoscopic lung biopsy confirmed a primary pulmonary carcinoma with histological features similar to the breast carcinoma, suggesting the lung as the primary source. This case highlights the complexity of differentiating breast metastasis originating from a lung tumor and primary breast cancer. It underscores the importance of comprehensive diagnostic evaluations and the consideration of extramammary origins in metastatic cases. The findings emphasize the role of multidisciplinary teams in managing such rare and challenging cases and highlight the necessity for thorough and repeated assessments in atypical breast cancer presentations. [ABSTRACT FROM AUTHOR]

The Architecture Analysis and Design Language (AADL) is a SAE Standardfor the modeling of both the hardware and the software of embedded systems. The AADL standard is now mature and is today employed by numerous stakeholders in the domain of critical embedded real-time systems to address a large set of concerns: performances (latency, schedulability), safety, or security, ... The ADEPT workshop aims to present and report on current projects in the field of design, implementation, and verification of critical systems where AADL is a first-citizen technology. This article is a summary of the ADEPT 2022 workshop. [ABSTRACT FROM AUTHOR]

Designing food processes and keep them updated at the pace of innovation to face competition, consumers’ trends and sustainability precepts is all but an easy task to accomplish. The complexity is steadily increasing and, with it, the need to adopt a systemic, as well as systematic, approach in designing and maintaining food processes to avoid compromising their survival and to guarantee their steady efficiency. The use of scenarios to exploring the uncertainty associated with that complexity becomes essential to support designers and, even more broadly, all decision makers involved in the design and operation of a technological process. Risk engineering can play an important role in that direction as it allows to account for hazards and threats associated with the identified opportunities. In the food industry hazards related to the safety of food production are identified and assessed through the well-known, widely used and regulated methodology “Hazards Analysis and Critical Control Point (HACCP)”, whose application is nowadays fostered by the international standard ISO 22000. Yet, the HACCP, as many other methodologies applied in other sectors, fails to capture the complexity associated with food processes, thus leaving space for grey zones where inter-functional risks can grow and manifest. The manuscript presents how the Holistic Risk Analysis and Modelling (HoRAM) method can be conveniently applied to provide decision makers with the necessary information (scenario analysis) by assessing the technological element jointly with the human and organizational ones (i.e., a systemic approach). Further, the manuscript also explains how HoRAM allows to systemically and systematically account for the consequences that might be generated by each scenario and for the entire universe as a whole, thus allowing to include in the decision both the possibility of the unwanted outcomes and the associated effort needed to make them less likely or less severe. Finally, it explains how the scenarios produced can be managed at different level of abstraction to allow the analyst better understanding the problem analysed and the decision-maker the profile of the opportunity to pursue.