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1.
Heliyon ; 5(11): e02722, 2019 Nov.
Article in English | MEDLINE | ID: mdl-31763467

ABSTRACT

Eco-connectivist communities are groups of individuals with similar characteristics, which emerge in a connectivist learning process within a knowledge ecology. ARMAGAeco-c is a reflexive and autonomic middleware for the management and optimization of eco-connectivist knowledge ecologies using description, prediction and prescription models. Adaptive Learning Objects are autonomic components that seek to personalize Learning Objects according to certain contextual information, such as learning styles of the learner's, technological restrictions, among other aspects. MALO is a system that allows the management of Adaptive Learning Objects. One of the main challenges of the connectivist learning process is the adaptation of the educational context to the student needs. One of them is the learning objects. For this reason, this work has two objectives, specifying a data analytics task to determine the learning style of a student in an eco-connectivist community and, adapting instances of Adaptive Learning Objects using the learning styles of the students in the communities. We use graph theory to identify the referential member of each eco-connectivist community, and a learning paradigm detection algorithm to identify the set of activities, strategies, and tools that Adaptive Learning Objects instances should have, according to the learning style of the referential member. To test our approach, a case study is presented, which demonstrates the validity of our approach.

2.
Worldviews Evid Based Nurs ; 12(6): 364-9, 2015 Dec.
Article in English | MEDLINE | ID: mdl-26574663

ABSTRACT

BACKGROUND: It is well established that extra virgin olive oil (EVOO), applied to the skin, has healing and anti-inflammatory properties. AIM: To evaluate the effectiveness of EVOO in the prevention of nipple cracking in lactating women. METHODS: Experimental, prospective, randomized study of 300 lactating women, admitted to the postpartum unit of the city's general hospital (Cienfuegos, Cuba). The study was carried out in 2012. Eligible patients were randomized into two groups of 150 women. In Group 1, EVOO was applied on the nipple after feeding, and in Group 2, drops of breast milk were applied to the nipple after feeding. Clinical evaluations were made during the first week of treatment and after the first month. All women who initiated breastfeeding were considered eligible to be included in this study; breastfeeding was characterized as the moment of mother-child interaction with suction on the nipple. Efficacy was evaluated quantitatively, as the absence of cracks in the nipple during the first 2 weeks of lactation using as the proportion of women with or without nipple cracks, and if present, whether they were moderate or slight. RESULTS: The quantitative efficacy was 97.3% and no adverse effects occurred in mothers and newborns during the administration of EVOO. DISCUSSION AND CONCLUSIONS: EVOO helps prevent nipple cracking in lactating women. It has been shown to have protective effects when breastfeeding presents technical difficulties. This conclusion is borne out by the frequency distribution results obtained, which reflect a significantly higher proportion of nipple cracking in the population that was not treated with EVOO. LINKING EVIDENCE TO ACTION: Use EVOO to prevent nipple cracking during breastfeeding by administering 3 drops on each nipple after each feeding. Decreased nipple cracking will reduce pain and enhance breastfeedinging by administering 3 drops on each nipple after each feeding, improving the health of mothers and infants.


Subject(s)
Administration, Cutaneous , Lactation/drug effects , Nipples/injuries , Olive Oil/therapeutic use , Adult , Cuba , Female , Humans , Pregnancy , Prospective Studies
3.
REMHU ; 20(38): 27-43, jun. 2012.
Article in Spanish | Index Psychology - journals | ID: psi-51531

ABSTRACT

La diversidad cultural constituye un asunto central y de importancia cada vez más creciente en la dinámica y evolución de las sociedades actuales. La gestión de este hecho, sin embargo, se realiza desde perspectivas y respuestas muy variadas y, no pocas veces, de dudosa eficacia en el terreno de la convivencia ciudadana para una ciudadanía inclusiva. En este artículo se analizan las tres respuestas más comunes aeste desafío, que se han denominado y caracterizado como “asimilación subalterna”, “racismo culturalista” y “estética intercultural”. Asimismo, se han identificado algunas de las limitaciones, carencias y problemas que estas respuestas evidencian. Frente a estas se destaca la necesidad de desarrollar una respuesta interculturalista crítica y transformadora, que se considera una alternativa válida para el desarrollo de una convivencia basada en el diálogo, la igualdad y el reconocimiento de las diferencias.(AU)


Cultural diversity is a central issue with ever-increasing importance in the dynamics and evolution of current societies. However its management is done from very different perspectives and responses, not infrequently, of dubious effectiveness in the field of civic coexistence for an inclusive citizenship. In this article the three most common responses to this challenge are analyzed, which have been named and characterized as “subordinate assimilation”, “culturalist racism” and “intercultural esthetics”. This way, some limitations, shortcomings and problems highlighted by these challenges were identified. In this context, there is the need of developing an intercultural, critical and transformative response, which consists in a valid alternative for the development of a coexistence based on dialogue, equality and recognition of differences.(AU)

4.
Neural Netw ; 11(4): 731-737, 1998 Jun.
Article in English | MEDLINE | ID: mdl-12662811

ABSTRACT

In this paper, we propose a general energy function for a new neural model, the random neural model of Gelenbe. This model proposes a scheme of interaction between the neurons and not a dynamic equation of the system. We then apply this general energy function on different optimization problems: the graph partitionning problem and the minimum node covering problem.

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