<p>La ruptura súbita en los sistemas de distribución de agua provoca gran pérdida de este recurso natural, interrumpe el abastecimiento, daña las calles y edificaciones y aumenta la transmisión de enfermedades infecciosas. En este artículo se propone un nuevo algoritmo que permite la detección y localización automática de rupturas súbitas en los sistemas de distribución de agua. En cuanto a la detección, la novedad consiste en usar el criterio de correlación wavelet para computar la decisión estadística y compararla con un umbral de detección. La novedad en la localización consiste en usar el operador estadístico correlación cruzada. El algoritmo se implementó en Octave y fue validado con 32 señales adquiridas en el laboratorio en una tubería de acero de 26.7 m de longitud. En 16 señales se provocó ruptura súbita las cuales fueron detectadas bajo una probabilidad de falsos positivos de 2 %. No se presentaron falsos positivos en las 16 señales donde solamente estaba la presencia de ruido.</p>

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Sleep quality is related to daily performance and stress. The working conditions imposed by the coronavirus disease 2019 (COVID-19) pandemic have impacted individuals and families. To analyze the relationship between sleep quality, daily activities, and stress of workers during the pandemic, a study of activity diaries of 113 workers in Havana, Cuba, in August 2020, with data collected by telephone, was carried out. Descriptive and inferential statistics, regression, and social microsequence analysis were used to study the data. Women slept 8.64 hours a day, dedicated 5.30 hours to leisure, 3.53 hours to work, and 3.40 hours to household chores. Men slept 8.33 hours a day, dedicated 6.64 hours to leisure, 4.12 hours to work, 2.32 hours to personal needs, and 1.99 hours to household chores. There were statistically significant differences by sex in terms of role changes, time spent on leisure activities and on household chores, and the number of roles experienced. Women had a positive and statistically significant relationship between the level of rest and time spent sleeping, while men had a negative and statistically significant relationship between the level of rest and hours in household chores. Men slept and rested more than women. The findings corroborate different behaviors by sex, according to the activities and roles they perform in different environments, and their influence on sleep quality and stress.

Digital images are used for evaluation and diagnosis of a diabetic foot ulcer. Selecting the wound region (segmentation) in an image is a preliminary step for subsequent analysis. Most of the time, manual segmentation isn't very reliable because specialists could have different opinions over the ulcer border. This fact encourages researchers to find and test different automatic segmentation techniques. This paper presents a computer-aided ulcer region segmentation algorithm for diabetic foot images. The proposed algorithm has two stages: ulcer region segmentation, and post-processing of segmentation results. For the first stage, a trained machine learning model was selected to classify pixels inside the ulcer's region, after a comparison of five learning models. Exhaustive experiments have been performed with our own annotated dataset from images of Cuban patients. The second stage is needed because of the presence of some misclassified pixels. To solve this, we applied the DBSCAN clustering algorithm, together with dilation, and closing morphological operators. The best-trained model after the post-processing stage was the logistic regressor (Jaccard Index $0.81$, accuracy $0.94$, recall $0.86$, precision $0.91$, and F1 score $0.88$). The trained model was sensitive to irrelevant objects in the scene, but the patient foot. Physicians found these results promising to measure the lesion area and to follow-up the ulcer healing process over treatments, reducing errors.