Standing Passenger Comfort: A New Scale for Evaluating the Real-Time Driving Style of Bus Transit Services

On-board bus comfort is a key factor affecting the quality of transit service. Thus, its assessment is crucial for public transport companies, as it can support the monitoring, evaluation and implementation of specific actions to improve their services. Previous research mainly focused on separate subjective and objective measurements of on-board comfort. Furthermore, even if concurrent measurements of objective and subjective on-board comfort have been collected, no study has built a gradual scale for the real-time measurement of comfort. This paper covers this gap by integrating subjective measurements of driving style with objective measurements of longitudinal and transversal accelerations collected by intelligent transportation system tools. These findings are very useful because they represent the first contribution for establishing a comfort scale in a real operational environment as a tool to regulate driver behavior, i.e., each driver will be able to recognize when passengers experience conditions of discomfort and acts to improve comfort

Variational quantum eigensolver for causal loop Feynman diagrams and acyclic directed graphs

We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping of the causal representation of multiloop Feynman diagrams in the Loop-Tree Duality (LTD) or, equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on the adjacency matrix describing a multiloop topology, and whose different energy levels correspond to the number of cycles, is minimized by VQE to identify the causal or acyclic configurations. The algorithm has been adapted to select multiple degenerated minima and thus achieves higher detection rates. A performance comparison with a Grover's based algorithm is discussed in detail. The VQE approach requires, in general, fewer qubits and shorter circuits for its implementation, albeit with lesser success rates.Comment: 32 pages, 7 figures. Improved discussion and success rates of multi-run VQ

The influence of bias in randomized controlled trials on rehabilitation intervention effect estimates: what we have learned from meta-epidemiological studies

This study aimed to synthesize evidence from studies that addressed the influence of bias domains in randomized controlled trials on rehabilitation intervention effect estimates and discuss how these findings can maximize the trustworthiness of an RCT in rehabilitation. We screened studies about the influence of bias on rehabilitation intervention effect estimates published until June 2023. The characteristics and results of the included studies were categorized based on methodological characteristics and summarized narratively. We included seven studies with data on 227,806 RCT participants. Our findings showed that rehabilitation intervention effect estimates are likely exaggerated in trials with inadequate/unclear sequence generation and allocation concealment when using continuous outcomes. The influence of blinding was inconsistent and different from the rest of medical science, as meta-epidemiological studies showed overestimation, underestimation, or neutral associations for different types of blinding on rehabilitation treatment effect estimates. Still, it showed a more consistent pattern when looking at patient-reported outcomes. The impact of attrition bias and intention to treat has been analyzed only in two studies with inconsistent results. The risk of reporting bias seems to be associated with overestimation of treatment effects. Bias domains can influence rehabilitation treatment effects in different directions. The evidence is mixed and inconclusive due to the poor methodological quality of RCTs and the limited number and quality of studies looking at the influence of bias and treatment effects in rehabilitation. Further studies about the influence of bias in RCTs on rehabilitation intervention effect estimates are needed

Applying the Risk of Bias Tool in a Systematic Review of Combination Long-Acting Beta-Agonists and Inhaled Corticosteroids for Persistent Asthma

Background: The Risk of Bias (RoB) tool is used to assess internal validity of randomized controlled trials (RCTs). Our objectives were to: 1) evaluate inter-rater agreement of the RoB tool; 2) determine the time to access supplemental study information; 3) compare the RoB tool with the Jadad scale and Schulz allocation concealment (AC); and 4) examine the relationship between RoB and effect estimates. Methods: We conducted a systematic review of long-acting beta agonists (LABA) combined with inhaled corticosteroids (ICS) for adults with persistent asthma. Two reviewers independently assessed 107 trials using RoB, Jadad, and AC. One reviewer searched for study protocols. We assessed inter-rater agreement using weighted Kappa (k) and the correlation between tools using Kendall’s Tau (t). Mean differences in effect sizes for RCTs with different RoB were calculated using inverse variance method and random effects model. Results: Trials had good Jadad scores (median 4, IQR 3-4); however, 85 % had unclear AC and 87 % high RoB. The factor that most influenced RoB was the potential inappropriate influence of study sponsors (95 % industry funded). Agreement on RoB domains was fair (k = 0.40) to almost perfect (k = 0.86), and moderate for overall RoB (k = 0.41). Median time to complete RoB assessments was 21 minutes (IQR 14-27) and 12 minutes (IQR 9-16) to search for protocols. Protocols were identified for 5/42 studies (12%); in 3 cases the assessment of selective outcome reporting changed. There was low correlation between overall RoB vs. Jadad (t =0.04

Covid-19 And Rheumatic Autoimmune Systemic Diseases: Role of Pre-Existing Lung Involvement and Ongoing Treatments

The Covid-19 pandemic may have a deleterious impact on patients with autoimmune systemic diseases (ASD) due to their deep immune-system alterations

COVID-19 in rheumatic diseases in Italy: first results from the Italian registry of the Italian Society for Rheumatology (CONTROL-19)

OBJECTIVES: Italy was one of the first countries significantly affected by the coronavirus disease 2019 (COVID-19) epidemic. The Italian Society for Rheumatology promptly launched a retrospective and anonymised data collection to monitor COVID-19 in patients with rheumatic and musculoskeletal diseases (RMDs), the CONTROL-19 surveillance database, which is part of the COVID-19 Global Rheumatology Alliance. METHODS: CONTROL-19 includes patients with RMDs and proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) updated until May 3rd 2020. In this analysis, only molecular diagnoses were included. The data collection covered demographic data, medical history (general and RMD-related), treatments and COVID-19 related features, treatments, and outcome. In this paper, we report the first descriptive data from the CONTROL-19 registry. RESULTS: The population of the first 232 patients (36% males) consisted mainly of elderly patients (mean age 62.2 years), who used corticosteroids (51.7%), and suffered from multi-morbidity (median comorbidities 2). Rheumatoid arthritis was the most frequent disease (34.1%), followed by spondyloarthritis (26.3%), connective tissue disease (21.1%) and vasculitis (11.2%). Most cases had an active disease (69.4%). Clinical presentation of COVID-19 was typical, with systemic symptoms (fever and asthenia) and respiratory symptoms. The overall outcome was severe, with high frequencies of hospitalisation (69.8%), respiratory support oxygen (55.7%), non-invasive ventilation (20.9%) or mechanical ventilation (7.5%), and 19% of deaths. Male patients typically manifested a worse prognosis. Immunomodulatory treatments were not significantly associated with an increased risk of intensive care unit admission/mechanical ventilation/death. CONCLUSIONS: Although the report mainly includes the most severe cases, its temporal and spatial trend supports the validity of the national surveillance system. More complete data are being acquired in order to both test the hypothesis that RMD patients may have a different outcome from that of the general population and determine the safety of immunomodulatory treatments

Coherent LIDAR systems for measurements of absorption in precise agriculture

Optical LIDAR (Light Detection and Ranging) systems, developed in the context of ICT (Information and Communications Technologies), represent a methodology that allows the exploration of different physical elements i.e. the forest heritage and of the atmosphere. They are often used in environment monitoring systems, as for example precision agriculture. In recent years, experimental and theoretical investigation has shown that LIDAR is a powerful tool to measure absorption level, range and Doppler effect. This work reports the activity carried out for the architectural design, the implementation and the simulation of a LIDAR sensing system specifically engineered for precision agriculture (PA), to face the urgent requirements of non-invasive timely and enhanced retrieving of high-quality and heterogeneous information. The aim of the present thesis is to submit a LIDAR architecture, different from the well-known commercial LIDAR. Commercial systems are large, expensive, based on a non-coherent detection and with high-quality photodiodes in the architecture. The new model of LIDAR aims to be smaller and low-cost, to use cheaper photodiodes and to provide a coherent architecture to increase its performance. This work aims at developing the design and the implementation of a new lidar, with innovative features as frequency agility, coherence, and multi-frequency operation, for an enhanced, adaptable and multi-feature observation of crop and soil enabling insights on new parameters (soil structure, canopy density, products load, disease presence) for key advances of PA approach. Particular focus will be given to the problems of simulation and implementation. The designed and implemented system will be tested during an experimental campaign carried out in the Institute of Communication, Information and Perception Technologies (TeCIP) of the Advanced Studies Sant’Anna School (SSSA). These measurements will be important to test the architecture for measurements of absorption to understand the problems shown by our system during its working and how to solve them

Sustainable carbon dioxide photoreduction by a cooperative effect of reactor design and titania metal promotion

An effective process based on the photocatalytic reduction of CO2to face on the one hand, the crucial problem of environmental pollution, and, on the other hand, to propose an efficient way to product clean and sustainable energy sources has been developed in this work. Particular attention has been paid to the sustainability of the process by using a green reductant (water) and TiO2as a photocatalyst under very mild operative conditions (room temperature and atmospheric pressure). It was shown that the efficiency in carbon dioxide photoreduction is strictly related to the process parameters and to the catalyst features. In order to formulate a versatile and high performing catalyst, TiO2was modified by oxide or metal species. Copper (in the oxide CuO form) or gold (as nanoparticles) were employed as promoting metal. Both photocatalytic activity and selectivity displayed by CuO-TiO2and Au-TiO2were compared, and it was found that the nature of the promoter (either Au or CuO) shifts the selectivity of the process towards two strategic products: CH4or H2. The catalytic results were discussed in depth and correlated with the physicochemical features of the photocatalysts