Probabilistic Regression and Anomaly Detection for Latency Assessment in Mobile Radio Networks

This thesis provides a thorough examination and empirical results on the use of machine learning for predicting latency in mobile radio networks, specifically emphasizing probabilistic regression and anomaly detection tasks. After a ML-aided selection of the Key Performance Indicators that most influence the latency, different models are compared for both probabilistic regression and anomaly detection. Such models present network designers with a valuable instrument to explore the correlations that exist between particular network Key Performance Indicators and latency

Real-time rain rate evaluation via satellite downlink signal attenuation measurement

We present the NEFOCAST project (named by the contraction of "Nefeleâ", which is the Italian spelling for the mythological cloud nymph Nephele, and "forecast"), funded by the Tuscany Region, about the feasibility of a system for the detection and monitoring of precipitation fields over the regional territory based on the use of a widespread network of new-generation Eutelsat "SmartLNB" (smart low-noise block converter) domestic terminals. Though primarily intended for interactive satellite services, these devices can also be used as weather sensors, as they have the capability of measuring the rain-induced attenuation incurred by the downlink signal and relaying it on an auxiliary return channel. We illustrate the NEFOCAST system architecture, consisting of the network of ground sensor terminals, the space segment, and the service center, which has the task of processing the information relayed by the terminals for generating rain field maps. We discuss a few methods that allow the conversion of a rain attenuation measurement into an instantaneous rainfall rate. Specifically, we discuss an exponential model relating the specific rain attenuation to the rainfall rate, whose coefficients were obtained from extensive experimental data. The above model permits the inferring of the rainfall rate from the total signal attenuation provided by the SmartLNB and from the link geometry knowledge. Some preliminary results obtained from a SmartLNB installed in Pisa are presented and compared with the output of a conventional tipping bucket rain gauge. It is shown that the NEFOCAST sensor is able to track the fast-varying rainfall rate accurately with no delay, as opposed to a conventional gauge

Fonti per la storia degli archivi degli antichi Stati italiani (Rome: Ministero dei beni e delle attività culturali e del turismo, 2016), vol. 49 of the ‘Fonti’ (Sources) series of the Pubblicazioni degli Archivi di Stato, edited with Andrea Guidi and Alessandro Silvestri

A collection of 330 documents on the history of Italian archives, 1200-1800. The collection is prefaced by a general introduction and the documents are divided into six thematic chapters: the politics of archives; the organisation and arrangement of archives; the material culture of archives; the social history of archivists; the uses of archives; and pre-modern scholarly research in archives. Each chapter is prefaced by an introduction and each document is edited, introduced and annotated with extensive references. The case studies include: the Republic of Venice, the Duchy of Milan, the Duchy of Ferrara-Modena, the Republic of Florence and the Duchy of Tuscany, the papacy, the Kingdom of Naples, the Kingdom of Sicily

A budget impact model and a cost–utility analysis of reducer device (Neovasc) in patients with refractory angina

BackgroundRefractory angina (RA) is a chronic condition characterized by the presence of debilitating angina symptoms due to established reversible ischemia in the presence of obstructive coronary artery disease (CAD). Treatments for this condition have undergone major developments in recent decades; however, the treatment for RA remains a challenge for medicine. In this sense, the Coronary Sinus Reducer System (CSRS) stands as the last line of therapy for ineligible patients for revascularization with reversible ischemia. The purpose of this report is to evaluate the potential burden on the National Health Service (NHS) and measure the health effects in terms of both quantity (life years) and quality-of-life aspects related to the reducer.MethodsTwo different economic evaluation models were developed as part of the analysis. The budget impact was developed to estimate the potential burden on the NHS from incremental uptake of the use of the reducer in the target population. The utility cost analysis compares and evaluates the quality of life and health resource use and costs between the two alternatives, based on the research of Gallone et al. A deterministic and probabilistic sensitivity analysis was carried out to characterize the uncertainty around the parameters of the model.ResultsIn the budget impact analysis (BIA), the reducer is shown to be more expensive in the first 2 years of the model, due to the gradual uptake in the market and the cost of the device. Starting from the third year, assuming maintenance of effectiveness, there are savings in terms of resource absorption in direct healthcare costs arising from hospitalizations, emergency department accesses, coronarography, and visits avoided.ConclusionThe BIA and cost-effectiveness model show that the reducer device, despite an increase in resources absorbed in the first years of implementation and use, has the potential to result in increased quality of life in patients with RA. These costs are largely offset in the short term by the improved clinical outcomes achievable leading to savings from the third year onward in the BIA and a dominance ratio in the cost–utility analysis

Rainfall Field Reconstruction by Opportunistic Use of the Rain-Induced Attenuation on Microwave Satellite Signals: The July 2021 Extreme Rain Event in Germany as a Case Study

This paper presents a practical application of an opportunistic technique for the estimation of rainfall intensity and accumulated precipitation. The proposed technique is based upon signal strength measurements made by commercial-grade interactive satellite terminals. By applying some processing, the rain-induced attenuation on the microwave downlink from the satellite is first evaluated; then the rain attenuation is eventually mapped into a rainfall rate estimate via a tropospheric model. This methodology has been applied to a test area of 30×30 km2 around the city of Dortmund (North Rhine-Westphalia, upper basin of Ermscher river), for the heavy rain event that devastated western Germany in July, 2021. A rainfall map on this area is obtained from the measurements collected by a set of satellite terminals deployed in the region, and successfully compared with a map obtained with a conventional weather radar

Correction to: The TANDEM investigation: efficacy and tolerability of levodopa-carbidopa intestinal gel in (LCIG) advanced Parkinson's disease patients

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Assessment of diagnostic criteria for multifocal motor neuropathy in patients included in the Italian database

Background and purposeThis study aimed to assess the diagnostic criteria, ancillary investigations and treatment response using real-life data in multifocal motor neuropathy (MMN) patients.MethodsClinical and laboratory data were collected from 110 patients enrolled in the Italian MMN database through a structured questionnaire. Twenty-six patients were excluded due to the unavailability of nerve conduction studies or the presence of clinical signs and symptoms and electrodiagnostic abnormalities inconsistent with the MMN diagnosis. Analyses were conducted on 73 patients with a confirmed MMN diagnosis and 11 patients who did not meet the diagnostic criteria.ResultsThe European Federation of Neurological Societies/Peripheral Nerve Society (EFNS/PNS) diagnostic criteria were variably applied. AUTHOR:When applying the American Association of Electrodiagnostic Medicine criteria, an additional 17% of patients fulfilled the criteria for probable/definite diagnosis whilst a further 9.5% missed the diagnosis. In 17% of the patients only compound muscle action potential amplitude, but not area, was measured and subsequently recorded in the database by the treating physician. Additional investigations, including anti-GM1 immunoglobulin M antibodies, cerebrospinal fluid analysis, nerve ultrasound and magnetic resonance imaging, supported the diagnosis in 46%-83% of the patients. Anti-GM1 immunoglobulin M antibodies and nerve ultrasound demonstrated the highest sensitivity. Additional tests were frequently performed outside the EFNS/PNS guideline recommendations.ConclusionsThis study provides insights into the real-world diagnostic and management strategies for MMN, highlighting the challenges in applying diagnostic criteria

A microbially produced AhR ligand promotes a Tph1-driven tolerogenic program in multiple sclerosis

Multiple sclerosis is a debilitating autoimmune disease, characterized by chronic inflammation of the central nervous system. While the significance of the gut microbiome on multiple sclerosis pathogenesis is established, the underlining mechanisms are unknown. We found that serum levels of the microbial postbiotic tryptophan metabolite indole-3-carboxaldehyde (3-IAld) inversely correlated with disease duration in multiple sclerosis patients. Much like the host-derived tryptophan derivative l-Kynurenine, 3-IAld would bind and activate the Aryl hydrocarbon Receptor (AhR), which, in turn, controls endogenous tryptophan catabolic pathways. As a result, in peripheral lymph nodes, microbial 3-IAld, affected mast-cell tryptophan metabolism, forcing mast cells to produce serotonin via Tph1. We thus propose a protective role for AhR–mast-cell activation driven by the microbiome, whereby natural metabolites or postbiotics will have a physiological role in immune homeostasis and may act as therapeutic targets in autoimmune diseases

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The population of merging compact binaries inferred using gravitational waves through GWTC-3

We report on the population properties of 76 compact binary mergers detected with gravitational waves below a false alarm rate of 1 per year through GWTC-3. The catalog contains three classes of binary mergers: BBH, BNS, and NSBH mergers. We infer the BNS merger rate to be between 10 $\rm{Gpc^{-3} yr^{-1}}$ and 1700 $\rm{Gpc^{-3} yr^{-1}}$ and the NSBH merger rate to be between 7.8 $\rm{Gpc^{-3}\, yr^{-1}}$ and 140 $\rm{Gpc^{-3} yr^{-1}}$ , assuming a constant rate density versus comoving volume and taking the union of 90% credible intervals for methods used in this work. Accounting for the BBH merger rate to evolve with redshift, we find the BBH merger rate to be between 17.9 $\rm{Gpc^{-3}\, yr^{-1}}$ and 44 $\rm{Gpc^{-3}\, yr^{-1}}$ at a fiducial redshift (z=0.2). We obtain a broad neutron star mass distribution extending from $1.2^{+0.1}_{-0.2} M_\odot$ to $2.0^{+0.3}_{-0.3} M_\odot$. We can confidently identify a rapid decrease in merger rate versus component mass between neutron star-like masses and black-hole-like masses, but there is no evidence that the merger rate increases again before 10 $M_\odot$. We also find the BBH mass distribution has localized over- and under-densities relative to a power law distribution. While we continue to find the mass distribution of a binary's more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above $\sim 60 M_\odot$. The rate of BBH mergers is observed to increase with redshift at a rate proportional to $(1+z)^{\kappa}$ with $\kappa = 2.9^{+1.7}_{-1.8}$ for $z\lesssim 1$. Observed black hole spins are small, with half of spin magnitudes below $\chi_i \simeq 0.25$. We observe evidence of negative aligned spins in the population, and an increase in spin magnitude for systems with more unequal mass ratio