Integrazione e validazione di OMNeT++ e Gazebo per sistemi multi-robot mediante un caso d'uso

Sistemi multi-robot a mobilità autonoma necessitano di simulatori che simulino in maniera accurata entrambi gli aspetti di gestione della rete di comunicazione e interazione dei robot con l'ambiente. Strumenti di questi tipo si ricavano dall'integrazione di simulatori specializzati nella simulazione di un singolo aspetto. In questa tesi viene descritta la realizzazione di un sistema integrato formato dall'unione di OMNeT++ e Gazebo. Il sistema viene quindi validato mediante un caso d'uso, una forma di mobilità basata sulle molle virtuali. Uno sciame di droni, connesso dalle molle virtuali, viene condotto da un drone leader in un ambiente cittadino. Dato che tale ambiente presenta degli ostacoli, i droni sono equipaggiati con sensori di prossimità allo scopo di evitare collisioni, prendendo decisioni su come muoversi per evitare l'ostacolo utilizzando anche qui le molle virtuali. Viene quindi valutata tale forma di mobilità

The Palliative Prognostic (PaP) Score without Clinical Evaluation Predicts Early Mortality among Advanced NSCLC Patients Treated with Immunotherapy

Background: An acceptable risk-benefit ratio may encourage the prescription of immune checkpoint inhibitors (ICI) near the late stage of life. The lung immune prognostic index (LIPI) was validated in advanced non-small cell lung cancer (NSCLC) patients treated with ICIs. The palliative prognostic (PaP) score without clinical prediction of survival (PaPwCPS) predicts early mortality probability in terminal cancer patients. Methods: We performed a retrospective study including 182 deceased advanced NSCLC patients, treated with single-agent ICI at our Institution. Two prognostic categories of high and low mortality risk were identified through ROC curve analysis for PaPwCPS and LIPI scores. Results: Most were >65 years of age (68.3%) and received second-line ICI (61.2%). A total of 29 (15.9%) and 131 (72.0%) patients died within 30 and 90 days from treatment start, respectively. A total of 81 patients (44.5%) received ICI during the last month of life. Baseline PaPwCPS and LIPI scores were assessable for 78 patients. The AUC of ROC curves was significantly increased for PaPwCPS as compared with LIPI score for both 30-day and 90-day mortality. A high PaPwCPS score was associated in multivariate analysis with increased 30-day (HR 2.69, p = 0.037) and 90-day (HR 4.01, p < 0.001) mortality risk. A high LIPI score was associated with increased 90-day mortality risk (p < 0.001). Conclusion: We found a tendency towards ICI prescription near the late stage of life. The PaPwCPS score was a reliable predictor of 30- and 90-day mortality

Characteristics, comorbidities and laboratory measures associated with disease severity and poor prognosis in young and elderly patients with COVID-19 admitted to medical wards in Emilia-Romagna region, Italy: a multicentre retrospective study

Background and Objectives. A relatively small number of studies have investigated the characteristics, comorbidities and laboratory measures associated with prognosis in patients with COVID-19, admitted to Internal Medicine Units (IMU) in Italy. Therefore, we performed a retrospective multicentre study to identify baseline features, predisposing to severe disease and poor outcomes, in adult individuals with SARS-CoV2 infection, hospitalized in 5 IMUs in the Emilia-Romagna region (Italy). Materials and Methods. We included 129 consecutive patients (male 75, median age 68 years) from 1st March 2020 to 31st October 2021. Patients' baseline characteristics, comorbidities, laboratory measures, and outcomes were collected. Results. At admission, the factors significantly associated with a higher risk of in-hospital mortality included: age (median 68 vs. 83 years in survived vs. dead patients, P=0.000), diabetes [Odds Ratio (OR) 4.00, P=0.016], chronic obstructive pulmonary disease (OR 4.60, P=0.022), cancer (OR 5.81, P=0.021), acute- (OR 9.88, P=0.000) and chronicrenal failure (OR 6.76, P=0.004). During the study period, 16 individuals died (12.4%), all over 70 years old. In deceased vs. non-deceased patients were detected: i) more elevated white blood cells and neutrophils-counts and lower lymphocytes count; ii) higher levels of total/direct bilirubin, creatinine, C-reactive-protein, lactate-dehydrogenase, ferritin, but only a slight Interleukin-6 increase; iii) a trend of lower vitamin D values. Conclusions. We proposed a new I index, a modified form of the Age-Adjusted Charlson Comorbidity Index, by considering pO(2)/FiO(2) ratio, to better characterize the severity of COVID-19. Furthermore, we critically discuss our results with the current assumption which considers COVID-19 as a pathological condition associated with cytokine storm

Ottimizzazione, guidata dall'applicazione, della scansione di canali WiFi in kernel Linux

La tesi ha visto la creazione di una applicazione in grado di inviare e ricevere messaggi verso un kernel Linux 3.6.8, che e' stato modificato nel modulo net/mac80211. Lo scopo e' stato permettere all'applicazione di attivare/disattivare comportamenti alternativi del metodo di scansione di canali Wi-Fi. Sono rese possibili le seguenti funzionalita': disattivare la scansione, rendere non interrompibile la scansione software, ricevere notifiche a completamento di una scansione software. Per la comunicazione sono stati usati i socket netlink

ATR-FTIR Spectroscopy, a New Non-Destructive Approach for the Quantitative Determination of Biogenic Silica in Marine Sediments

Biogenic silica is the major component of the external skeleton of marine micro-organisms, such as diatoms, which, after the organisms death, settle down onto the seabed. These micro-organisms are involved in the CO2 cycle because they remove it from the atmosphere through photosynthesis. The biogenic silica content in marine sediments, therefore, is an indicator of primary productivity in present and past epochs, which is useful to study the CO2 trends. Quantification of biosilica in sediments is traditionally carried out by wet chemistry followed by spectrophotometry, a time-consuming analytical method that, besides being destructive, is affected by a strong risk of analytical biases owing to the dissolution of other silicatic components in the mineral matrix. In the present work, the biosilica content was directly evaluated in sediment samples, without chemically altering them, by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. Quantification was performed by combining the multivariate standard addition method (MSAM) with the net analyte signal (NAS) procedure to solve the strong matrix effect of sediment samples. Twenty-one sediment samples from a sediment core and one reference standard sample were analyzed, and the results (extrapolated concentrations) were found to be comparable to those obtained by the traditional wet method, thus demonstrating the feasibility of the ATR-FTIR-MSAM-NAS approach as an alternative method for the quantification of biosilica. Future developments will cover in depth investigation on biosilica from other biogenic sources, the extension of the method to sediments of other provenance, and the use higher resolution IR spectrometers

How to get the best from low-cost particulate matter sensors: Guidelines and practical recommendations

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44\u25e6 30\u2032 N, 11\u25e6 21\u2032 E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30′ N, 11°21′ E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution