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Current quantum systems have significant limitations affecting the processing of large datasets with high dimensionality, typical of high energy physics. In the present paper, feature and data prototype selection techniques were studied to tackle this challenge. A grid search was performed and quantum machine learning models were trained and benchmarked against classical shallow machine learning methods, trained both in the reduced and the complete datasets. The performance of the quantum algorithms was found to be comparable to the classical ones, even when using large datasets. Sequential Backward Selection and Principal Component Analysis techniques were used for feature's selection and while the former can produce the better quantum machine learning models in specific cases, it is more unstable. Additionally, we show that such variability in the results is caused by the use of discrete variables, highlighting the suitability of Principal Component analysis transformed data for quantum machine learning applications in the high energy physics context., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor ML declared a past co-authorship/collaboration with authors NC and IO. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Peixoto, Castro, Crispim Romão, Oliveira and Ochoa.)

Introduction: COVID-19 is a severe respiratory syndrome caused by the SARS-CoV-2 virus. In Brazil the highest infection rates are associated with socially vulnerable populations. This study therefore sought to analyze the spatial distribution of the disease and its relation with geographic, socioeconomic and public health policy characteristics associated with quilombola communities in Salvaterra municipality, state of Pará, for the period of March to September, 2020., Methodology: This cross-sectional and ecological study used data from the Disease Notification System and the National Registry of Health Establishments of the Ministry of Health, the Income Transfer Registry of the Ministry of Citizenship and the 2010 census of the Brazilian Institute of Geography and Statistics. Statistical and spatial analysis of the data was done through percentages of cases and Flow and Kernel map techniques., Results: Seventy-five notified cases of COVID-19 distributed among 7 quilombola communities in the municipality were analyzed. The epidemiological profile followed a national trend, with a higher percentage of cases among persons who were female, adults with low schooling levels, working as family farmers and with an outcome ending in recovery. The spatial distribution of the disease was not homogenous and showed clusters of cases and high incidence rates, especially in communities close to the municipal seat or to highways., Conclusions: The use of data analysis techniques was satisfactory for providing an understanding of the socioeconomic production of the disease in the areas studied. Accordingly, the need for intensifying epidemiological survey actions in the quilombola communities of the municipality is emphasized., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2021 Nelson Veiga Goncalves, Joao Simao de Melo Neto, Selma Kazumi da Trindade Noguchi, Andrey Silva Machado, Alcindo da Silva Martins Junior, Maira Cibelle da Silva Peixoto, Alba Lucia Ribeiro Raithy, Camylle Maia Costa Faria, Tainara Carvalho Garcia Miranda Filgueiras, Alex Baima Amaral Junior, Claudia do Socorro Carvalho Miranda.)

Unlabelled: Amusia is a disorder that affects the processing of music. Part of this processing happens in the primary auditory cortex. The study of this condition allows us to evaluate the central auditory pathways., Objective: To explore the diagnostic evaluation tests of amusia., Method: The authors propose an evaluation protocol for patients with suspected amusia (after brain injury or complaints of poor musical perception), in parallel with the assessment of central auditory processing, already implemented in the department. The Montreal Evaluation of Battery of amusia was the basis for the selection of the tests. From this comprehensive battery of tests we selected some of the musical examples to evaluate different musical aspects, including memory and perception of music, ability concerning musical recognition and discrimination. In terms of memory there is a test for assessing delayed memory, adapted to the Portuguese culture. Prospective study., Results and Conclusions: Although still experimental, with the possibility of adjustments in the assessment, we believe that this assessment, combined with the study of central auditory processing, will allow us to understand some central lesions, congenital or acquired hearing perception limitations.

The frequency of myopathy in hypothyroidism ranges from 30 to 80%. The major symptoms related are weakness, muscular cramps and myalgia. The pseudohyperthrophic form is called Hoffman's syndrome. The electrophysiological study reveals myopathy, neuropathy or mixed pattern. Laboratorial investigation generally shows increased levels of muscle enzymes and low serum thyroid hormones, with thyrotrophic-stimulating hormone (TSH) elevated. The treatment consists in hormone replacement and the prognosis is good in most of the cases. We report an adult male who developed muscular cramps, myalgia, weakness, pseudohyperthrophy, associated with facial edema and alteration of his voice. The muscle enzymes were increased and T4 was undetectable with a raised level of TSH. The myopathy was the initial manifestation of hypothyroidism in this case.