El perfil profesional del directivo de enfermeria como gestor organizativo y los nuevos retos del espacio europeo de educación superior

En este artículo se reflexiona sobre las funciones de los directivos enfermería y sobre las dificultades que obstaculizan su desempeño profesional. A su vez, plantea los retos profesionales que en cuanto a funciones, y a su formación están vigentes en la actualidad, presentando una serie de estrategias en pro de una mejora en la formación y en el desarrollo profesional. Estos cambios pueden verse potenciados por el reciente cambio en el marco legislativo profesional y por el nuevo modelo educativo propiciado por el Espacio Europeo Educativo Superior.______________________________This manuscript is the result of a thought about the nursing managers' mission and the difficulties found in their performance appraisal. At the same time, it introduces the current professional challenges related to mission and training. Different strategies to improve both training and professional development are shown. Such changes may be upgraded by the recent changes in the professional regulatory frame and also by the new educational model promoted by the European Higher Education Area

Cups products in Z2-cohomology of 3D polyhedral complexes

Let I=(Z3,26,6,B) be a 3D digital image, let Q(I) be the associated cubical complex and let ∂Q(I) be the subcomplex of Q(I) whose maximal cells are the quadrangles of Q(I) shared by a voxel of B in the foreground -- the object under study -- and by a voxel of Z3∖B in the background -- the ambient space. We show how to simplify the combinatorial structure of ∂Q(I) and obtain a 3D polyhedral complex P(I) homeomorphic to ∂Q(I) but with fewer cells. We introduce an algorithm that computes cup products on H∗(P(I);Z2) directly from the combinatorics. The computational method introduced here can be effectively applied to any polyhedral complex embedded in R3

Human gait recognition using topological information

This paper shows an image/video application using topological invariants in human gait recognition. The 3D volume of a gait cycle is built stacking silhouettes extracted using a background substraction approach. Ideally, the border cell complex is obtained from the 3D volume with one connected component and one cavity. Then, it is necessary to apply a topological enrichment strategy in order to obtain a robust and discriminative representation for person recognition. Using a sliding cutter plane normal to some direction of view it is possible to divide the border cell complex in different parts. The incremental algorithm is used to compute the homology on each part. A vectorial representation is built ordering the number of connected components and tunnels obtained for each cut. In order to evaluate the robustness of this representation the silhouettes were diminished to a quarter of the original size. At the same time, this is considered a simulation of a human gait captured at long distance. Even, under these difficult conditions it was possible to get a 74% of correct classification rates on CASIA-B database

Characterizing Configurations of critical points through LBP Extended Abstract

In this abstract we extend ideas and results submitted to [3] in which a new codification of Local Binary Patterns (LBP) is given using combinatorial maps and a method for obtaining a representative LBP image is developed based on merging regions and Minimum Contrast Algorithm. The LBP code characterizes the topological category (max, min, slope, saddle) of the 2D gray level landscape around the center region. We extend the result studying how to merge non-singular slopes with one of its neighbors and how to extend the results to nonwell formed images/maps. Some ideas related to robust LBP and isolines are also given in last section

Persistent-homology-based gait recognition

Gait recognition is an important biometric technique for video surveillance tasks, due to the advantage of using it at distance. In this paper, we present a persistent homology-based method to extract topological features (the so-called topological gait signature) from the the body silhouettes of a gait sequence. It has been used before in sev- eral conference papers of the same authors for human identi cation, gender classi cation, carried object detection and monitoring human activities at distance. The novelty of this paper is the study of the sta- bility of the topological gait signature under small perturbations and the number of gait cycles contained in a gait sequence. In other words, we show that the topological gait signature is robust to the presence of noise in the body silhouettes and to the number of gait cycles con- tained in a given gait sequence. We also show that computing our topological gait signature of only the lowest fourth part of the body silhouette, we avoid the upper body movements that are unrelated to the natural dynamic of the gait, caused for example by carrying a bag or wearing a coat.Ministerio de Economía y Competitividad MTM2015-67072-

Persistent homology-based gait recognition robust to upper body variations

Gait recognition is nowadays an important biometric technique for video surveillance tasks, due to the advantage of using it at distance. However, when the upper body movements are unrelated to the natural dynamic of the gait, caused for example by carrying a bag or wearing a coat, the reported results show low accuracy. With the goal of solving this problem, we apply persistent homology to extract topological features from the lowest fourth part of the body silhouettes. To obtain the features, we modify our previous algorithm for gait recognition, to improve its efficacy and robustness to variations in the amount of simplices of the gait complex. We evaluate our approach using the CASIA-B dataset, obtaining a considerable accuracy improvement of 93:8%, achieving at the same time invariance to upper body movements unrelated with the dynamic of the gait.Ministerio de Economía y Competitividad MTM2015-67072-

An application for gait recognition using persistent homology

This Demo presents an application for gait recognition using persistent homology. Using a background subtraction approach, a silhouette sequence is obtained from a camera in a controlled environment. A border simplicial complex is built stacking silhouettes aligned by their gravity center. A multifiltration is applied on the border simplicial complex which captures relations among the parts of the human body when walking. Finally, the topological gait signature is extracted from the persistence barcode according to each filtration. The measure cosine is used to give a similarity value between topological signatures. The input of this Demo are videos with resolution 320x240 to 25f ps. The videos in CASIA-B database are used to prove the efficacy and efficiency. A computer with 2Gb of RAM memory and a DualCore processor was used to test the implementation of the proposed algorithm. In this Demo all related tasks have been programmed by the authors in the C++ programming language. OpenCV library has been used for the image processing part

Decision system based on neural networks to optimize the energy efficiency of a petrochemical plant

The energy efficiency of industrial plants is an important issue in any type of business but particularly in the chemical industry. Not only is it important in order to reduce costs, but also it is necessary even more as a means of reducing the amount of fuel that gets wasted, thereby improving productivity, ensuring better product quality, and generally increasing profits. This article describes a decision system developed for optimizing the energy efficiency of a petrochemical plant. The system has been developed after a data mining process of the parameters registered in the past. The designed system carries out an optimization process of the energy efficiency of the plant based on a combined algorithm that uses the following for obtaining a solution: On the one hand, the energy efficiency of the operation points occurred in the past and, on the other hand, a module of two neural networks to obtain new interpolated operation points. Besides, the work includes a previous discriminant analysis of the variables of the plant in order to select the parameters most important in the plant and to study the behavior of the energy efficiency index. This study also helped ensure an optimal training of the neural networks. The robustness of the system as well as its satisfactory results in the testing process (an average rise in the energy efficiency of around 7%, reaching, in some cases, up to 45%) have encouraged a consulting company (ALIATIS) to implement and to integrate the decision system as a pilot software in an SCADA

CONOCIMIENTOS SOBRE EL USO DE MÉTODOS ANTICONCEPTIVOS EN MUJERES EN POSTPARTO DEL ÁREA DE GINECO-OBSTETRICIA DEL HOSPITAL HOMERO CASTANIER CRESPO, 2022-2023

Antecedentes: El puerperio es una etapa de gran relevancia para las mujeres, en donde la planificación familiar es fundamental para realizar un control de la natalidad y prevenir diversas enfermedades sexuales, por lo que, contar con un método anticonceptivo es un recurso de gran valor para cumplir esta dinámica. Objetivo: Analizar los conocimientos sobre el uso de métodos anticonceptivos en mujeres en postparto del área de Gineco-obstetricia del Hospital Homero Castanier Crespo, 2022- 2023. Metodología: La metodología utilizada en este estudio tiene un enfoque cuantitativo tipo observacional-descriptivo y de corte transversal. El universo de estudio está conformado por mujeres hospitalizadas en el área de Gineco- obstetricia del Hospital Homero Castanier Crespo y la muestra será seleccionada de forma aleatoria tomando en cuenta los criterios de inclusión y exclusión. Los datos serán recopilados a través de una encuesta estructurada realizada por las autoras y la tutora, siendo previamente validada mediante una prueba piloto. El instrumento está conformado por 34 preguntas, divididas en dos secciones, la primera consta de datos sociodemográficos y la segunda aborda aspectos relacionados con el uso de métodos anticonceptivos. Resultados: Del total de mujeres que participaron en el estudio un 49,4% tiene un nivel medio de conocimientos sobre métodos anticonceptivos y el 44,9% tiene un nivel alto de conocimientos. Además, se identifica una asociación estadísticamente significativa entre el nivel de conocimientos sobre métodos anticonceptivos y las variables sociodemográficas como: edad (valor p=0.016), remuneración económica (valor p=0.007) y nivel de instrucción (valor p=0.013).Background: The postpartum period is of significant importance for women, where family planning is essential for birth control and prevention of various sexual diseases. Having access to contraceptive methods is a valuable resource to fulfill this dynamic. Objective: To analyze the knowledge about contraceptive methods among postpartum women in the Gynecology and Obstetrics area of Homero Castanier Crespo Hospital, 2022-2023.Methodology: The methodology employed in this study follows a quantitative observational-descriptive approach with a cross-sectional design. The study population comprises women hospitalized in the Gynecology and Obstetrics area of Homero Castanier Crespo Hospital, with the sample being randomly selected based on inclusion and exclusion criteria. Data will be collected through a structured survey administered by the authors and the tutor, validated through a pilot test. The survey consists of 34 questions, divided into two sections: the first gathering socio-demographic data, and the second addressing aspects related to contraceptive methods usage. Results: Out of the total women who participated, 49.4% exhibit a moderate level of knowledge about contraceptive methods, while 44.9% possess a high level of knowledge. Moreover, a statistically significant association is observed between the level of knowledge regarding contraceptive methods and socio-demographic variables such as age (p-value=0.016), economic remuneration (p-value=0.007), and educational level (p-value=0.013).0000-0002-1473-788