Model independent measurements of Standard Model cross sections with Domain Adaptation

With the ever growing amount of data collected by the ATLAS and CMS experiments at the CERN LHC, fiducial and differential measurements of the Higgs boson production cross section have become important tools to test the standard model predictions with an unprecedented level of precision, as well as seeking deviations that can manifest the presence of physics beyond the standard model. These measurements are in general designed for being easily comparable to any present or future theoretical prediction, and to achieve this goal it is important to keep the model dependence to a minimum. Nevertheless, the reduction of the model dependence usually comes at the expense of the measurement precision, preventing to exploit the full potential of the signal extraction procedure. In this paper a novel methodology based on the machine learning concept of domain adaptation is proposed, which allows using a complex deep neural network in the signal extraction procedure while ensuring a minimal dependence of the measurements on the theoretical modelling of the signal.Comment: 16 pages, 10 figure

Sodium-glucose cotransporter 2 inhibition in patients with liver cirrhosis and diabetes: a possible role in ascites control?

The aim of this brief report is to evaluate sodium-glucose cotransporter 2 inhibitors (SGLT2-I) effects on patients with both refractory ascites and type 2 diabetes mellitus (T2D). We consecutively recruited all the diabetic patients with refractory ascites due to decompensated liver cirrhosis admitted between February and May 2023 at the Internal Medicine Unit of the University Hospital of Palermo. Clinical and laboratory data were collected after starting SGLT2-I therapy. SGLT2-I use was associated with a reduction/resolution of ascites and with an improvement in serum albumin and sodium levels and estimated glomerular filtration rate. SGLT2-I might represent a valid therapeutic option in the treatment of patients with refractory ascites and T2D, as already hypothesized by other research groups

Herbal and Dietary Supplements as Adjunctive Treatment for Mild SARS-CoV-2 Infection in Italy

During the COVID-19 pandemic, several observational studies proved a certain efficacy of nutraceuticals, herbal products, and other dietary supplements as adjuvant therapies used alongside antiviral drugs. Although their use has not been widespread in Italy, according to preliminary evidence, many supplements with demonstrated immunomodulatory effects, such as vitamins C and D, herbal medicines and essential oils, might relieve the respiratory symptoms of COVID-19, since SARS-CoV-2 can activate inflammasome-mediated inflammatory signaling pathways. Other observational studies have shown that herbal treatments, such as Echinacea purpurea and ginseng, help alleviate respiratory symptoms and reduce serum levels of inflammatory cytokines, which are typically overexpressed in both adult and pediatric SARS-CoV-2 patients. Further, vitamins C and D can attenuate the immune response thanks to their cytokine suppression ability and to their known antimicrobial activity and potential to modulate T helper cell response. The strong immune response triggered by SARS-CoV-2 infection is responsible for the severity of the disease. Preliminary data have also shown that L-arginine, an endothelial-derived relaxing factor, is able to modulate endothelial damage, which appears to be one of the main targets of this systemic disease. Finally, some essential oils and their isolated compounds, such as eucalyptol, may be helpful in reducing many of the respiratory symptoms of COVID-19, although others, such as menthol, are not recommended, since it can lead to an undervaluation of the clinical status of a patient. In this narrative review, despite the lack of strong evidence in this field, we aimed to give an overview of the current available literature (mainly observational and cross-sectional studies) regarding herbal products and dietary supplements and their use in the treatment of mild disease from SARS-CoV-2 infection. Obviously, dietary supplements and herbal products do not constitute a standardized treatment for COVID-19 disease, but they could represent an adjunctive and useful treatment when used together with antivirals

A Smart Motor Rehabilitation System Based on the Internet of Things and Humanoid Robotics

The Internet of Things (IoT) is gaining increasing attention in healthcare due to its potential to enable continuous monitoring of patients, both at home and in controlled medical environments. In this paper, we explore the integration of IoT with human-robotics in the context of motor rehabilitation for groups of patients performing moderate physical routines, focused on balance, stretching, and posture. Specifically, we propose the I-TROPHYTS framework, which introduces a step-change in motor rehabilitation by advancing towards more sustainable medical services and personalized diagnostics. Our framework leverages wearable sensors to monitor patients’ vital signs and edge computing to detect and estimate motor routines. In addition, it incorporates a humanoid robot that mimics the actions of a physiotherapist, adapting motor routines in real-time based on the patient’s condition. All data from physiotherapy sessions are modeled using an ontology, enabling automatic reasoning and planning of robot actions. In this paper, we present the architecture of the proposed framework, which spans four layers, and discuss its enabling components. Furthermore, we detail the current deployment of the IoT system for patient monitoring and automatic identification of motor routines via Machine Learning techniques. Our experimental results, collected from a group of volunteers performing balance and stretching exercises, demonstrate that we can achieve nearly 100% accuracy in distinguishing between shoulder abduction and shoulder flexion, using Inertial Measurement Unit data from wearable IoT devices placed on the wrist and elbow of the test subjects

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe