Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization

The COVID-19 pandemic is continuously evolving with drastically changing epidemiological situations which are approached with different decisions: from the reduction of fatalities to even the selection of patients with the highest probability of survival in critical clinical situations. Motivated by this, a battery of mortality prediction models with different performances has been developed to assist physicians and hospital managers. Logistic regression, one of the most popular classifiers within the clinical field, has been chosen as the basis for the generation of our models. Whilst a standard logistic regression only learns a single model focusing on improving accuracy, we propose to extend the possibilities of logistic regression by focusing on sensitivity and specificity. Hence, the log-likelihood function, used to calculate the coefficients in the logistic model, is split into two objective functions: one representing the survivors and the other for the deceased class. A multi-objective optimization process is undertaken on both functions in order to find the Pareto set, composed of models not improved by another model in both objective functions simultaneously. The individual optimization of either sensitivity (deceased patients) or specificity (survivors) criteria may be conflicting objectives because the improvement of one can imply the worsening of the other. Nonetheless, this conflict guarantees the output of a battery of diverse prediction models. Furthermore, a specific methodology for the evaluation of the Pareto models is proposed. As a result, a battery of COVID-19 mortality prediction models is obtained to assist physicians in decision-making for specific epidemiological situations.This research is supported by the Basque Government (IT1504- 22, Elkartek) through the BERC 2022–2025 program and BMTF project, and by the Ministry of Science, Innovation and Universities: BCAM Severo Ochoa accreditation SEV-2017-0718 and PID2019-104966GB-I00. Furthermore, the work is also supported by the AXA Research Fund project “Early prognosis of COVID-19 infections via machine learning”

Assessing Distribution Network Flexibility via Reliability-based P-Q Area Segmentation

This paper proposes a framework to assess the flexibility of active distribution networks (ADNs) via P-Q area segmentation, considering the reliability of flexible units (FUs). A mixed-integer quadratically constrained programming (MIQCP) model is formulated to analyse flexible active and reactive power support at the interface with transmission networks, explicitly capturing the contributions and reliability of FUs that provide flexibility services within an ADN. The numerical simulations performed for a real 124-bus UK distribution network demonstrate the optimal flexibility provision by different FUs, as well as the corresponding reliability and the impact of network reconfiguration. Distribution system operators (DSOs) can use the proposed framework to identify critical units, select an adequate combination of flexibility volumes, and manage its reliability.Comment: Submitted to PSCC 2022, then resubmitted to IEEE PowerTech 2023 conferenc

Peaks in the Cosmic Microwave Background: flat versus open models

We present properties of the peaks (maxima) of the CMB anisotropies expected in flat and open CDM models. We obtain analytical expressions of several topological descriptors: mean number of maxima and the probability distribution of the gaussian curvature and the eccentricity of the peaks. These quantities are calculated as functions of the radiation power spectrum, assuming a gaussian distribution of temperature anisotropies. We present results for angular resolutions ranging from 5' to 20' (antenna FWHM), scales that are relevant for the MAP and COBRAS/SAMBA space missions and the ground-based interferometer experiments. Our analysis also includes the effects of noise. We find that the number of peaks can discriminate between standard CDM models, and that the gaussian curvature distribution provides a useful test for these various models, whereas the eccentricity distribution can not distinguish between them.Comment: 13 pages latex file using aasms4.sty + 3 tables + 2 postscript figures, to appear in ApJ (March 1997

Gnathostomosis, an emerging foodborne zoonotic disease in Acapulco, Mexico.

Between 1993 and 1997, 98 gnathostomosis cases were clinically identified in Acapulco, Mexico. Intermittent cutaneous migratory swellings were the commonest manifestation. Larvae were identified in 26 cases, while in 72, final diagnosis was made on the basis of epidemiologic data, food habits, and positive enzyme-linked immunosorbent assay and Western blot results

Development of antimicrobial chitosan based nanofiber dressings for wound healing applications

Objective(s): Chitosan based composite fine fibers were successfully produced via a centrifugal spinning technology. This study evaluates the ability of the composites to function as scaffolds for cell growth while maintaining an antibacterial activity. Materials and Methods: Two sets of chitosan fiber composites were prepared, one filled with anti-microbial silver nanoparticles and another one with cinnamaldeyhde. Chitosan powder was dissolved in trifluoroacetic acid and dichloromethane followed by addition of the fillers. The fiber output was optimized by configuring the polymer weight concentration (7, 8, and 9 w/w% chitosan) and applied angular velocity (6000-9000 RPM) within the spinning process. Results: Scanning electron microscopy revealed fiber diameters ranging from 800-1500 nm. Cinnamaldehyde and silver nanoparticles helped to improve and control the anti-bacterial activity. Through a verified cell counting method and disk diffusion method, it was proven that the chitosan based composite fibers possess an enhanced anti-bacterial/microbial activity against gram-positive Staphylococcus aureus. Both composite systems showed anti-bacterial activity, inhibition zones fluctuating between 5 to 10 mm were observed depending on the size of the fiber mat and no bacteria was found within the mats. The developed fiber scaffolds were found to be noncytotoxic serving as effective three-dimensional substrates for cell adhesion and viability. Conclusion: These results provide potential to use these scaffolds in wound healing and tissue regeneration applications

Comparative ergonomic workflow and user experience analysis of MRI versus fluoroscopy-guided vascular interventions:an iliac angioplasty exemplar case study

Purpose A methodological framework is introduced to assess and compare a conventional fluoroscopy protocol for peripheral angioplasty with a new magnetic resonant imaging (MRI)-guided protocol. Different scenarios were considered during interventions on a perfused arterial phantom with regard to time-based and cognitive task analysis, user experience and ergonomics. Methods Three clinicians with different expertise performed a total of 43 simulated common iliac angioplasties (9 fluoroscopic, 34 MRI-guided) in two blocks of sessions. Six different configurations for MRI guidance were tested in the first block. Four of them were evaluated in the second block and compared to the fluoroscopy protocol. Relevant stages’ durations were collected, and interventions were audio-visually recorded from different perspectives. A cued retrospective protocol analysis (CRPA) was undertaken, including personal interviews. In addition, ergonomic constraints in the MRI suite were evaluated. Results Significant differences were found when comparing the performance between MRI configurations versus fluoroscopy. Two configurations [with times of 8.56 (0.64) and 9.48 (1.13) min] led to reduce procedure time for MRI guidance, comparable to fluoroscopy [8.49 (0.75) min]. The CRPA pointed out the main influential factors for clinical procedure performance. The ergonomic analysis quantified musculoskeletal risks for interventional radiologists when utilising MRI. Several alternatives were suggested to prevent potential low-back injuries. Conclusions This work presents a step towards the implementation of efficient operational protocols for MRI-guided procedures based on an integral and multidisciplinary framework, applicable to the assessment of current vascular protocols. The use of first-user perspective raises the possibility of establishing new forms of clinical training and education