Real-time geophysical applications with Android GNSS raw measurements

The number of Android devices enabling access to raw GNSS (Global Navigation Satellite System) measurements is rapidly increasing, thanks to the dedicated Google APIs. In this study, the Xiaomi Mi8, the first GNSS dual-frequency smartphone embedded with the Broadcom BCM47755 GNSS chipset, was employed by leveraging the features of L5/E5a observations in addition to the traditional L1/E1 observations. The aim of this paper is to present two different smartphone applications in Geoscience, both based on the variometric approach and able to work in real time. In particular, tests using both VADASE (Variometric Approach for Displacement Analysis Stand-alone Engine) to retrieve the 3D velocity of a stand-alone receiver in real-time, and VARION (Variometric Approach for Real-Time Ionosphere Observations) algorithms, able to reconstruct real-time sTEC (slant total electron content) variations, were carried out. The results demonstrate the contribution that mass-market devices can offer to the geosciences. In detail, the noise level obtained with VADASE in a static scenario-few mm/s for the horizontal components and around 1 cm/s for the vertical component-underlines the possibility, confirmed from kinematic tests, of detecting fast movements such as periodic oscillations caused by earthquakes. VARION results indicate that the noise level can be brought back to that of geodetic receivers, making the Xiaomi Mi8 suitable for real-time ionosphere monitoring

The Role of Cogeneration in the Electrification Pathways towards Decarbonization

The global call for an environmentally friendly, sustainable, and reliable energy system looks for the optimal integration of different technologies to allow a smooth and economically viable transition towards electrification. In this context, small, medium, and large industrial processes are relevant contributors to global CO2 emissions production due to the simultaneous requirement of electricity, heating, and cooling power generally obtained through fossil fuel combustion. In this context, Combined Heat and Power Energy converters based on internal combustion engines, such as reciprocating engines, gas turbines, and gas turbine combined cycles, and external combustion, such as backpressure and condensing steam power plants, are the most suitable solutions for the efficient and reliable generation of the above-mentioned assets. Typically, the industrial demand for heat and electricity differs in terms of heat-to-power ratio when compared to the heat-to-power ratio of the CHP plant, and this has led to requiring the selection of a control strategy to follow, partially or fully, the heat load or the electric load. In this paper, the authors propose an operating and design strategy addressed to fully covering the heat load demands by the heat generated by the CHP, allowing the system to have an excess of electricity generated. This electricity can be used for different purposes, as regards the novel electrification roadmap. Indeed, the authors have explored four configurations in which the excess of the CHP-generated electricity can be exported to the national grid, used for high-tension fast-charging electromobility systems, for running reverse osmosis desalination plants, and for the production of alternative fuels such as hydrogen. The authors propose a methodology for providing an extensive environmental techno-economic assessment that looks at 2050 CO2 targets. Accordingly, the environmental techno-economic assessment results are presented and discussed by considering the Net Present Value, payback period, and CO2 emission savings

Chelating properties of beer: Implications on calcium homeostasis in PE/CA-PJ15 cells

Abstract Beer contains a large variety of different molecules, of which some can chelate Ca 2+. Here, we show that in PE/CA-PJ15 cells, an experimental model previously employed to investigate Ca 2+ homeostasis, chemical entities with Ca 2+ -chelating properties can markedly impact intra- and extra-cellular levels of the metal ion. This was consistently shown by commercial beers, as well as aliquots of unfinished product taken during the last step (clarification) of the brewing process. Our data suggest that a large number of molecules with chelating properties, can cross the cell membrane and, thus, potentially lead to important biological effects associated with changes in Ca 2+ homeostasis. In this regard, when PE/CA-PJ15 cells were exposed to H 2 O 2 in order to experimentally prompt an oxidative stress, beer antagonized a non-capacitative Ca 2+ entry that was otherwise elicited by H 2 O 2 in its absence. Higher Ca 2+ -chelating activity of stout, as compared to lager beer, suggest that melanoidins, which are generally present in dark malts, are major chelating agents in dark beers. Further, based on dose-response determinations, we report, for the first time, that Ferulic Acid can bind both intra- and extra-cellular Ca 2+ and, as one of the most abundant hydroxycinnamic acids in malted barley, largely account for Ca 2+ chelation. These results support the notion that beer may be considered a natural source of chemical entities that, based on their binding activity to Ca 2+ and, possibly, other metal ions, might be considered as nutritional supplements, detoxification agents, or antibiotics

ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders

The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation

Pandemic Phase-Adjusted Analysis of COVID-19 Outcomes Reveals Reduced Intrinsic Vulnerability and Substantial Vaccine Protection From Severe Acute Respiratory Syndrome Coronavirus 2 in Patients With Breast Cancer

PURPOSE Although representing the majority of newly diagnosed cancers, patients with breast cancer appear less vulnerable to COVID-19 mortality compared with other malignancies. In the absence of patients on active cancer therapy included in vaccination trials, a contemporary real-world evaluation of outcomes during the various pandemic phases, as well as of the impact of vaccination, is needed to better inform clinical practice. METHODS We compared COVID-19 morbidity and mortality among patients with breast cancer across prevaccination (February 27, 2020-November 30, 2020), Alpha-Delta (December 1, 2020-December 14, 2021), and Omicron (December 15, 2021-January 31, 2022) phases using OnCovid registry participants (ClinicalTrials.gov identifier: NCT04393974). Twenty-eight-day case fatality rate (CFR28) and COVID-19 severity were compared in unvaccinated versus double-dosed/boosted patients (vaccinated) with inverse probability of treatment weighting models adjusted for country of origin, age, number of comorbidities, tumor stage, and receipt of systemic anticancer therapy within 1 month of COVID-19 diagnosis. RESULTS By the data lock of February 4, 2022, the registry counted 613 eligible patients with breast cancer: 60.1% (n = 312) hormone receptor-positive, 25.2% (n = 131) human epidermal growth factor receptor 2-positive, and 14.6% (n = 76) triple-negative. The majority (61%; n = 374) had localized/locally advanced disease. Median age was 62 years (interquartile range, 51-74 years). A total of 193 patients (31.5%) presented >= 2 comorbidities and 69% (n = 330) were never smokers. In total, 392 (63.9%), 164 (26.8%), and 57 (9.3%) were diagnosed during the prevaccination, Alpha-Delta, and Omicron phases, respectively. Analysis of CFR28 demonstrates comparable estimates of mortality across the three pandemic phases (13.9%, 12.2%, 5.3%, respectively; P = .182). Nevertheless, a significant improvement in outcome measures of COVID-19 severity across the three pandemic time periods was observed. Importantly, when reported separately, unvaccinated patients from the Alpha-Delta and Omicron phases achieved comparable outcomes to those from the prevaccination phase. Of 566 patients eligible for the vaccination analysis, 72 (12.7%) were fully vaccinated and 494 (87.3%) were unvaccinated. We confirmed with inverse probability of treatment weighting multivariable analysis and following a clustered robust correction for participating center that vaccinated patients achieved improved CFR28 (odds ratio [OR], 0.19; 95% CI, 0.09 to 0.40), hospitalization (OR, 0.28; 95% CI, 0.11 to 0.69), COVID-19 complications (OR, 0.16; 95% CI, 0.06 to 0.45), and reduced requirement of COVID-19-specific therapy (OR, 0.24; 95% CI, 0.09 to 0.63) and oxygen therapy (OR, 0.24; 95% CI, 0.09 to 0.67) compared with unvaccinated controls. CONCLUSION Our findings highlight a consistent reduction of COVID-19 severity in patients with breast cancer during the Omicron outbreak in Europe. We also demonstrate that even in this population, a complete severe acute respiratory syndrome coronavirus 2 vaccination course is a strong determinant of improved morbidity and mortality from COVID-19

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: a voxel-based morphometry approach exploiting Monte Carlo simulations

Purpose: In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment. Methods: We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change. Results: The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment. Conclusions: The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam's Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan

COVID-19 Sequelae and the Host Pro-Inflammatory Response: An Analysis From the OnCovid Registry

Background: Fifteen percent of patients with cancer experience symptomatic sequelae, which impair post–COVID-19 outcomes. In this study, we investigated whether a proinflammatory status is associated with the development of COVID-19 sequelae. / Methods: OnCovid recruited 2795 consecutive patients who were diagnosed with Severe Acute Respiratory Syndrome Coronavirus 2 infection between February 27, 2020, and February 14, 2021. This analysis focused on COVID-19 survivors who underwent a clinical reassessment after the exclusion of patients with hematological malignancies. We evaluated the association of inflammatory markers collected at COVID-19 diagnosis with sequelae, considering the impact of previous systemic anticancer therapy. All statistical tests were 2-sided. / Results: Of 1339 eligible patients, 203 experienced at least 1 sequela (15.2%). Median baseline C-reactive protein (CRP; 77.5 mg/L vs 22.2 mg/L, P < .001), lactate dehydrogenase (310 UI/L vs 274 UI/L, P = .03), and the neutrophil to lymphocyte ratio (NLR; 6.0 vs 4.3, P = .001) were statistically significantly higher among patients who experienced sequelae, whereas no association was reported for the platelet to lymphocyte ratio and the OnCovid Inflammatory Score, which includes albumin and lymphocytes. The widest area under the ROC curve (AUC) was reported for baseline CRP (AUC = 0.66, 95% confidence interval [CI]: 0.63 to 0.69), followed by the NLR (AUC = 0.58, 95% CI: 0.55 to 0.61) and lactate dehydrogenase (AUC = 0.57, 95% CI: 0.52 to 0.61). Using a fixed categorical multivariable analysis, high CRP (odds ratio [OR] = 2.56, 95% CI: 1.67 to 3.91) and NLR (OR = 1.45, 95% CI: 1.01 to 2.10) were confirmed to be statistically significantly associated with an increased risk of sequelae. Exposure to chemotherapy was associated with a decreased risk of sequelae (OR = 0.57, 95% CI: 0.36 to 0.91), whereas no associations with immune checkpoint inhibitors, endocrine therapy, and other types of systemic anticancer therapy were found. / Conclusions: Although the association between inflammatory status, recent chemotherapy and sequelae warrants further investigation, our findings suggest that a deranged proinflammatory reaction at COVID-19 diagnosis may predict for sequelae development

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)