39 research outputs found
Planning Methods in Ecuador’s Indigenous People
Sexual and reproductive health (SRH) is a fundamental human right that implies knowledge and exercise of sexual and reproductive rights (SSR). Among the latter are access to knowledge and use of contraceptive methods; therefore, SSR should be experienced as a constant experience that allows women to achieve full satisfaction and security in their sexual and reproductive sphere through their subjectivity, their body, and their social and cultural life. Knowing about family planning allows having the desired number of children determining the interval between pregnancies and choosing the contraceptive method according to the social, cultural and psychological beliefs, needs and conditions of each woman. However, indigenous women from Canton Cañar (Ecuador) have less access and knowledge to contraceptive methods, mainly due to the influence of social, cultural, religious and economic factors, among others. The lack of information about family planning in indigenous populations of the South of Ecuador has motivated this study; through a medical-anthropological approach, it is intended to determine what is the preference regarding contraceptive methods in indigenous Cañari women in the context of the Cañari culture and what are their perceptions regarding such methods
An artificial-vision- and statistical-learning-based method for studying the biodegradation of type I collagen scaffolds in bone regeneration systems
[Abstract]
This work proposes a method based on image analysis and machine and statistical learning to model and estimate osteocyte growth (in type I collagen scaffolds for bone regeneration systems) and the collagen degradation degree due to cellular growth. To achieve these aims, the mass of collagen -subjected to the action of osteocyte growth and differentiation from stem cells- was measured on 3 days during each of 2 months, under conditions simulating a tissue in the human body. In addition, optical microscopy was applied to obtain information about cellular growth, cellular differentiation, and collagen degradation. Our first contribution consists of the application of a supervised classification random forest algorithm to image texture features (the structure tensor and entropy) for estimating the different regions of interest in an image obtained by optical microscopy: the extracellular matrix, collagen, and image background, and nuclei. Then, extracellular-matrix and collagen regions of interest were determined by the extraction of features related to the progression of the cellular growth and collagen degradation (e.g., mean area of objects and the mode of an intensity histogram). Finally, these critical features were statistically modeled depending on time via nonparametric and parametric linear and nonlinear models such as those based on logistic functions. Namely, the parametric logistic mixture models provided a way to identify and model the degradation due to biological activity by estimating the corresponding proportion of mass loss. The relation between osteocyte growth and differentiation from stem cells, on the one hand, and collagen degradation, on the other hand, was determined too and modeled through analysis of image objects’ circularity and area, in addition to collagen mass loss. This set of imaging techniques, machine learning procedures, and statistical tools allowed us to characterize and parameterize type I collagen biodegradation when collagen acts as a scaffold in bone regeneration tasks. Namely, the parametric logistic mixture models provided a way to identify and model the degradation due to biological activity and thus to estimate the corresponding proportion of mass loss. Moreover, the proposed methodology can help to estimate the degradation degree of scaffolds from the information obtained by optical microscopy.Ministerio de Asuntos Económicos y Transformación Digital; MTM2014-52876-RMinisterio de Asuntos Económicos y Transformación Digital; MTM2017-82724-RXunta de Galicia; ED431C-2016-015Xunta de Galicia; ED431G/0
An expert system based on computer vision and statistical modelling to support the analysis of collagen degradation
[Abstract] The poly(DL-lactide-co-glycolide) (PDLGA) copolymers have been specifically designed
and performed as biomaterials, taking into account their biodegradability and biocompatibility properties. One of the applications of statistical degradation models in material
engineering is the estimation of the materials degradation level and reliability. In some
reliability studies, as the present case, it is possible to measure physical degradation (mass
loss, water absorbance, pH) depending on time. To this aim, we propose an expert system
able to provide support in collagen degradation analysis through computer vision methods and statistical modelling techniques. On this base, the researchers can determine
which statistical model describes in a better way the biomaterial behaviour. The expert
system was trained and evaluated with a corpus of 63 images (2D photographs obtained
by electron microscopy) of human mesenchymal stem cells (CMMh-3A6) cultivated in a
laboratory experiment lasting 44 days. The collagen type-1 sponges were arranged in 3
groups of 21 samples (each image was obtained in intervals of 72 hours)
Exploring the impact of accessibility in MOOC and OER: a multivocal literature review
Conferência realizada em Lisboa, de 21-23 de outubro de 2020.This report presents a review of the accessibility models in Learning Resources
and MOOCs with the aim of establishing common terms in the research of the
EduTech project and other projects associated with virtual accessibility in
member HEIs. This study is based on the search and analysis of articles and
publications related to the subject following the MLR format. The results
showed a lack of applicability and data that support the current situation in Latin
America, however, the experiences of European projects and regulations that
support their sustainability, establish guidelines that could guide
implementation processes in higher education institutions in partner countriesCo-funded by the Erasmus+ Programme of the European Union, project EduTech (609785-EPP-1-2019-1-ES-EPPKA2-CBHE-JP)info:eu-repo/semantics/publishedVersio
Accessibility challenges in OER and MOOC: MLR analysis considering the pandemic years
The review of state of the art on creating and managing learning resources and accessible
Open Educational Resources (OER) and Massive Open Online Courses (MOOC) is a topic that
cannot only consider formal literature. The evidence and lack of a measurement consensus require
the inclusion of contextual information, corroborating scientific results with practical experiences.
For this reason, this article presents a review of accessibility models, OER and MOOC, considering
the gray literature to capture experiences and trying to establish a shared understanding of the
terminology commonly used in research on virtual accessibility and its impact on higher education.
The bibliographic review relies on analyzing articles and scientific publications related to the topic
following the Multivocal Literature Review (MLR) format. The results of this review establish that
it is possible to apply accessibility review methodologies with transversal actions in the creation
and management of learning resources and MOOCs. The research is related to one of the seventeen
sustainable development goals defined by the United Nations to ensure inclusive and equitable
quality education and promote lifelong learning opportunities for all.This research work has been co-funded by the Erasmus+ Programme of the European
Union, project EduTech (609785-EPP-1-2019-1-ES-EPPKA2-CBHE-JP).info:eu-repo/semantics/publishedVersio
Inclusión, discapacidad y educación: Enfoque práctico desde las Tecnologías Emergentes
El CIEE 2017 comparte posibilidades tecnológicas en un marco de inclusión social, educativa, cultural, laboral; el abordaje desde el servicio y por las personas que más requieren está marcado no por la energía potencial que la ciencia proyecta a través de sus artefactos tecnológicos, sino por la energía cinética que se obtiene cuando movilizamos a grandes masas de personas buscando un fin común llamado equidad. El CIEE espera una cobertura amplia en cuanto número de científicos, profesores universitarios, estudiantes; pero también de personas con discapacidad y otras con necesidades específicas de apoyo educativo. La ciencia de la inclusión con tecnologías se construye en común; es congruente la esencia inclusiva, expresada en la participación de todos, con la forma llamada tecnología. En esta línea, el presente libro recoge más de 50 contribuciones de diversos autores de Argentina, Ecuador, Chile, Colombia y Perú. Estos se organizan en tres partes: artículos científicos, pósters y resúmenes de charlas magistrales. Los artículos científicos se organizan en seis mesas temáticas que agrupan el trabajo de los autores considerando su contenido y objetivos: accesibilidad y uso, desarrollo de software educativo y entornos virtuales de aprendizaje; estimulación multisensorial; inclusión de las TIC en la educación especial; los nuevos modelos de intermediación con TIC y metodología de aprendizaje apoyado con las TIC
Disruption of ribosome biogenesis triggers a p21/p53-mediated cell cycle checkpoint
Cell cycle entry requires a dramatic increase in protein production. In order to cope with
this demand, the cell must upregulate ribosome biogenesis. Given that ribosome
biogenesis is the most energy-consuming anabolic process in a growing cell, and that
changes in cellular ribosome content can alter the genetic program, we hypothesized
that control mechanisms must exist to synchronize ribosome biogenesis and cell cycle
progression. Here I report on a novel cell cycle checkpoint which is activated on the
disruption of ribosome biogenesis and blocks cell cycle progression. Our studies, both
in vitro and in vivo, show p21 and p53 as key mediators of this response
Evaluation of an expert system for the generation of speech and language therapy plans
Background: Speech and language pathologists (SLPs) deal with a wide spectrum of disorders, arising from many different conditions, that affect voice, speech, language, and swallowing capabilities in different ways. Therefore, the outcomes of Speech and Language Therapy (SLT) are highly dependent on the accurate, consistent, and complete design of personalized therapy plans. However, SLPs often have very limited time to work with their patients and to browse the large (and growing) catalogue of activities and specific exercises that can be put into therapy plans. As a consequence, many plans are suboptimal and fail to address the specific needs of each patient. Objective: We aimed to evaluate an expert system that automatically generates plans for speech and language therapy, containing semiannual activities in the five areas of hearing, oral structure and function, linguistic formulation, expressive language and articulation, and receptive language. The goal was to assess whether the expert system speeds up the SLPs’ work and leads to more accurate, consistent, and complete therapy plans for their patients. Methods: We examined the evaluation results of the SPELTA expert system in supporting the decision making of 4 SLPs treating children in three special education institutions in Ecuador. The expert system was first trained with data from 117 cases, including medical data; diagnosis for voice, speech, language and swallowing capabilities; and therapy plans created manually by the SLPs. It was then used to automatically generate new therapy plans for 13 new patients. The SLPs were finally asked to evaluate the accuracy, consistency, and completeness of those plans. A four-fold cross-validation experiment was also run on the original corpus of 117 cases in order to assess the significance of the results. Results:
The evaluation showed that 87% of the outputs provided by the SPELTA expert system were considered valid therapy plans for the different areas. The SLPs rated the overall accuracy, consistency, and completeness of the proposed activities with 4.65, 4.6, and 4.6 points (to a maximum of 5), respectively. The ratings for the subplans generated for the areas of hearing, oral structure and function, and linguistic formulation were nearly perfect, whereas the subplans for expressive language and articulation and for receptive language failed to deal properly with some of the subject cases. Overall, the SLPs indicated that over 90% of the subplans generated automatically were “better than” or “as good as” what the SLPs would have created manually if given the average time they can devote to the task. The cross-validation experiment yielded very similar results. Conclusions: The results show that the SPELTA expert system provides valuable input for SLPs to design proper therapy plans for their patients, in a shorter time and considering a larger set of activities than proceeding manually. The algorithms worked well even in the presence of a sparse corpus, and the evidence suggests that the system will become more reliable as it is trained with more subjects.Fondo Europeo de Desarrollo RegionalXunta de GaliciaMinisterio de Economía y Competitividad | Ref. TIN2013-42774-
CREAMINKA: An Intelligent Ecosystem for Supporting Management and Information Discovery in Research and Innovation Fields in Universities
This chapter presents a new proposal for supporting the management of research processes in universities and higher education centers. To this aim, the authors have developed a comprehensive ecosystem that implements a knowledge model that addresses three innovative aspects of research: (i) acceleration of knowledge production, (ii) research valorization and (iii) discovery of improbable peers. The ecosystem relies on ontologies and intelligent modules and is able to automatically retrieve information of major scientific databases such as SCOPUS and Science Direct to infer new information. Currently, the system is able to provide guidelines to create improbable research peers as well as automatically generate resilience graphics and reports from more than 17,000 tuples of the ontological database. In this work, the authors describe in detail an important aspect of support systems for research management in higher education: the development and valorization of competences of students collaborating in research process and startUPS of universities. Furthermore, a knowledge model of entrepreneurship (startUPS) as well as an analyzer of general and specific competences based on data mining processes is presented