Ride-Sharing in Medical Transportations: Dealing with Temporal Requirements

The ride-sharing problem aims at optimizing the path from one starting point to one destination point. The problem can be enriched by intermediate stops, spatio-temporal constraints, and external constraints (e.g. traffic congestion), adding uncertainty and increasing the overall complexity. Spatio-temporal networks can properly describe the problem by graphs, helping to identify the optimal or sub-optimal solution. We face here the specific issue, where a driver picks up several patients from their respective pick-up locations and drops them off at one care center. Ride-sharing of patients has specific requirements due to the particular health state of every patient. Indeed, every patient has his/her own constraints, which could be related to the maximum sustainable duration of the trip, according to the patient’s conditions, the maximum waiting time, and the time when the visit or treatment is scheduled. In our approach, we first consider the spatial facets, and then we superimpose the temporal facets, to recommend the best paths and schedules, allowing some kind of temporal uncertainty in the specification of different possible constraints

Unsupervised activity recognition for autonomous water drones

We propose an automatic system aimed at discovering relevant activities for aquatic drones employed in water monitoring applications. The methodology exploits unsupervised time series segmentation to pursue two main goals: i) to support on-line decision making of drones and operators, ii) to support off-line analysis of large datasets collected by drones. The main novelty of our approach consists of its unsupervised nature, which enables to analyze unlabeled data. We investigate different variants of the proposed approach and validate them using an annotated dataset having labels for activity \u201cupstream/downstream navigation\u201d. Obtained results are encouraging in terms of clustering purity and silhouette which reach values greater than 0.94 and 0.20, respectively, in the best models

Critical COVID-19 Patients Through First, Second And Third Wave: Retrospective Observational Study Comparing Outcomes In ICU.

Introduction- The time-course of the COVID-19 pandemic was characterized by subsequent waves identified by peaks of Intensive Care Unit (ICU) admission rates. During these periods, progressive knowledge of the disease led to the development of specific therapeutic strategies. This retrospective study investigates whether this led to improvement in outcomes of COVID-19 patients admitted to ICU. Methods- Outcomes were evaluated in consecutive adult COVID19 patients admitted to our ICU, divided into three waves based on the admission period: the first wave from February 25th, 2020, to July 6th, 2020; the second wave from September 20th, 2020, to February 13th, 2021; the third wave from February 14th, 2021 to April 30th, 2021. Differences were assessed comparing outcomes and by using different multivariable Cox models adjusted for variables related to outcome. Further sensitivity analysis was performed in patients undergoing invasive mechanical ventilation. Results- Overall, 428 patients were included in the analysis: 102, 169 and 157 patients in the first, second and third wave. The ICU and in-hospital crude mortalities were lower by 7% and 10% in the third wave compared to the other 2 waves (p>0.05). A higher number of ICU and hospital free days at day 90 was found in the third wave when compared to the other 2 waves (p=0.001). Overall, 62.6% underwent invasive ventilation, with decreasing requirement during the waves (p=0.002). The adjusted Cox model showed no difference in the Hazard Ratio for mortality among the waves. In the propensity-matched analysis the hospital mortality rate was reduced by 11% in the third wave (p=0.044). Conclusions - With application of best practice as known by the time of the first three waves of the pandemic, our study failed to identify a significant improvement in mortality rate when comparing the different waves of the COVID-19 pandemic, notwithstanding, the sub-analyses showed a trend in mortality reduction in the third wave. Rather, our study identified a possible positive effect of dexamethasone on mortality rate reduction and the increased risk of death related to bacterial infections in the three waves

Cytomegalovirus blood reactivation in COVID-19 critically ill patients: risk factors and impact on mortality.

Purpose: Cytomegalovirus (CMV) reactivation in immunocompetent critically ill patients is common and relates to a worsening outcome. In this large observational study, we evaluated the incidence and the risk factors associated with CMV reactivation and its effects on mortality in a large cohort of COVID-19 patients admitted to the intensive care unit (ICU). Methods: Consecutive patients with confirmed SARS-CoV-2 infection and acute respiratory distress syndrome admitted to three ICUs from February 2020 to July 2021 were included. The patients were screened at ICU admission and once or twice per week for quantitative CMV-DNAemia in the blood. The risk factors associated with CMV blood reactivation and its association with mortality were estimated by adjusted Cox proportional hazards regression models. Results: CMV blood reactivation was observed in 88 patients (20,4%) of the 431 patients studied. SAPS II score (HR 1,031, 95% CI 1,010-1,053, p=0,006), platelet count (HR 0,0996, 95% CI 0,993-0,999, p=0,004), invasive mechanical ventilation (HR 2,611, 95% CI 1,223-5,571, p=0,013) and secondary bacterial infection (HR 5,041; 95% CI 2,852-8,911, p<0,0001) during ICU stay were related to CMV reactivation. Hospital mortality was higher in patients with (67,0%) than in patients without (24,5%) CMV reactivation but the adjusted analysis did not confirm this association (HR 1,141, 95% CI 0,757-1,721, p=0,528). Conclusion: The severity of illness and the occurrence of secondary bacterial infections were associated with an increased risk of CMV blood reactivation, which, however, does not seem to influence the outcome of COVID-19 ICU patients independently

A study of CP violation in B-+/- -> DK +/- and B-+/- -> D pi(+/-) decays with D -> (KSK +/-)-K-0 pi(-/+) final states

A first study of CP violation in the decay modes $B^\pm\to [K^0_{\rm S} K^\pm \pi^\mp]_D h^\pm$ and $B^\pm\to [K^0_{\rm S} K^\mp \pi^\pm]_D h^\pm$, where $h$ labels a $K$ or $\pi$ meson and $D$ labels a $D^0$ or $\overline{D}^0$ meson, is performed. The analysis uses the LHCb data set collected in $pp$ collisions, corresponding to an integrated luminosity of 3 fb$^{-1}$. The analysis is sensitive to the CP-violating CKM phase $\gamma$ through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of $\gamma$ using other decay modes