Diseño, desarrollo y validación de una plataforma on-line dirigida a profesores y nutricionistas para dispensar Educación Nutricional a niños: MEAL.

TEMA: Una de las principales causas identificadas por la cual los niños llevan a cabo una alimentación poco saludable es la falta de conocimientos sobre aspectos nutricionales, y por ello que la Educación Nutricional (EN), se plantea como un elemento clave para poder combatir esta seria problemática. Uno de los principales escollos para el desarrollo e implementación de los programas de EN es la falta de formación específica de los profesionales encargados de diseminarla, profesores y nutricionistas. En este aspecto, las tecnologías de la información y pueden ser una herramienta de gran interés para la diseminación de estos conocimientos entre profesionales. Objetivos: El objetivo de esta tesis doctoral es el diseño, desarrollo y validación de una plataforma on-line (MEAL) para formar a profesores y nutricionistas en conocimientos y habilidades para enseñar EN a niños de entre 9 y 12 años. METODOLOGÍA: Se llevó a cabo una extensa revisión de literatura para analizar los principales componentes que se deben de incluir en un programa de Educación Nutricional dirigido a población infantil. Posteriormente se llevaron a cabo grupos focales con maestros, nutricionistas, y niños para analizar los conceptos que consideraban relevantes de aprender en dichos programas, y como les gustaría obtener dichos conocimientos. También se llevaron a cabo encuestas digitales con maestros y nutricionistas en 4 países de Europa (España, Austria, Noruega e Italia), con la finalidad de ampliar la información recabada en la revisión de literatura y los grupos focales. Con la información obtenida se desarrolló la plataforma MEAL, y posteriormente fue evaluada con una muestra de 66 participantes, de los cuales 15 eran maestros de primaria, 12 nutricionistas y 39 estudiantes de magisterio. Se evaluó la percepción de utilidad y aceptabilidad hacia los contenidos y la propia plataforma MEAL. Por otro lado, se evaluó el nivel de aceptabilidad, inmersión y jugabilidad de los Videojuegos Educativos implementados en esta plataforma. Finalmente, se analizó la eficacia de la plataforma para la adquisición de conocimientos nutricionales, así como de los niveles de aceptabilidad, inmersión y jugabilidad por parte de los niños hacia los Videojuegos Educativos de este sistema. Para ello se contó con una muestra de 135 niños en 4 escuelas primarias de la comunidad Valenciana.Topic: One of the main causes identified by which children carry out an unhealthy diet is the lack of knowledge about nutritional aspects, and therefore that the Nutritional Education (NE), arises as a key element in order to combat this serious problem. One of the main obstacles for the development and implementation of the programs is the lack of specific training of professionals responsible for dissemination: teachers and nutritionists. In this aspect, the technologies of the information and Communication (ICT´s) can be a tool of great interest for the dissemination of these knowledge between professionals. Objectives: The aim of this thesis is the design, development and validation of an on-line platform (MEAL) to train teachers and nutritionists in the knowledge and skills to teach NE to children between 9 and 12 years. Methodology: We carried out an extensive review of literature to analyze the main components that must be included in a nutritional education program aimed at child population. Subsequently carried out focus groups with teachers, nutritionists, and children to analyze the concepts that they considered relevant to learn in such programs, and as they would like to obtain such knowledge. It also surveys were carried out with teachers and digital nutritionists in 4 countries in Europe (Spain, Austria, Norway and Italy). With the purpose of expanding the information collected in the literature review and the focus groups. With the information obtained was developed the platform meal, and subsequently it was evaluated with a sample of 66 participants, 15 of whom were primary school teachers, 12 nutritionists and 39 students of education. Was used to evaluate perception of the usefulness and acceptability to the contents and the platform itself meal. On the other hand, it was assessed the level of acceptability, immersion and gameplay of the educational video games implemented on this platform. Finally, we analyzed the effectiveness of the platform for the acquisition of nutritional knowledge. As well as the levels of acceptability, immersion and gameplay on the part of the children into the educational video games of this system. For this we counted with a sample of 135 children in 4 primary schools in the Valencian Community

Profesionalización de la administración pública mediante examen de oposición para ocupar cargos públicos en el gobierno municipal de Puebla

"El siguiente trabajo de investigación surge de la inquietud pero sobre todo de la necesidad de la profesionalización de la administración pública, y más aún en estos momentos, ya que las demandas de la sociedad en cuanto a desarrollo social, desarrollo económico, seguridad pública, servicios básicos entre otros son cada vez más complicados de resolver por la falta de planeación y de visión a largo plazo, falta de continuidad en los programas gubernamentales y en muchas ocasiones falta de preparación o falta de conocimiento en los diseñadores y operadores de políticas públicas, han hecho que muchas fracasen o que aquellas que están dando resultados, no tengan continuidad por cuestiones políticas. En el presente trabajo abordamos los antecedentes que se han hecho por profesionalizar el servicio público, para finalmente llegar a una propuesta de contratación para el Gobierno Municipal de Puebla Capital.

Genetic markers associated with bone composition in Rhode Island Red laying hens

Background Bone damage has welfare and economic impacts on modern commercial poultry and is known as one of the major challenges in the poultry industry. Bone damage is particularly common in laying hens and is probably due to the physiological link between bone and the egg laying process. Previous studies identified and validated quantitative trait loci (QTL) for bone strength in White Leghorn laying hens based on several measurements, including bone composition measurements on the cortex and medulla of the tibia bone. In a previous pedigree-based analysis, bone composition measurements showed heritabilities ranging from 0.18 to 0.41 and moderate to strong genetic correlations with tibia strength and density. Bone composition was measured using infrared spectroscopy and thermogravimetry. The aim of this study was to combine these bone composition measurements with genotyping data via a genome-wide association study (GWAS) to investigate genetic markers that contribute to genetic variance in bone composition in Rhode Island Red laying hens. In addition, we investigated the genetic correlations between bone composition and bone strength. Results We found novel genetic markers that are significantly associated with cortical lipid, cortical mineral scattering, medullary organic matter, and medullary mineralization. Composition of the bone organic matter showed more significant associations than bone mineral composition. We also found interesting overlaps between the GWAS results for tibia composition traits, particularly for cortical lipid and tibia strength. Bone composition measurements by infrared spectroscopy showed more significant associations than thermogravimetry measurements. Based on the results of infrared spectroscopy, cortical lipid showed the highest genetic correlations with tibia density, which was negative (− 0.20 ± 0.04), followed by cortical CO3/PO4 (0.18 ± 0.04). Based on the results of thermogravimetry, medullary organic matter% and mineral% showed the highest genetic correlations with tibia density (− 0.25 ± 0.04 and 0.25 ± 0.04, respectively). Conclusions This study detected novel genetic associations for bone composition traits, particularly those involving organic matter, that could be used as a basis for further molecular genetic investigations. Tibia cortical lipids displayed the strongest genetic associations of all the composition measurements, including a significantly high genetic correlation with tibia density and strength. Our results also highlighted that cortical lipid may be a key measurement for further avian bone studies.Swedish University of Agricultural Sciences.ERANET Grant to ICD (BBSRC BB/ M028291/1)Svenska Forskningsrådet Formas, 2014-01840(Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, 291815Svenska Forskningsrådet Formas (2019-02116 and 2016-01386)The COST Action CA15224 Keel Bone Damag

Double-zero degeneracy and heteroclinic cycles in a perturbation of the Lorenz system

In this paper we consider a 3D three-parameter unfolding close to the normal form of the triple-zero bifurcation exhibited by the Lorenz system. First we study analytically the double-zero degeneracy (a double-zero eigenvalue with geometric multiplicity two) and two Hopf bifurcations. We focus on the more complex case in which the double-zero degeneracy organizes several codimension-one singularities, namely transcritical, pitchfork, Hopf and heteroclinic bifurcations. The analysis of the normal form of a Hopf-transcritical bifurcation allows to obtain the expressions for the corresponding bifurcation curves. A degenerate double-zero bifurcation is also considered. The theoretical information obtained is very helpful to start a numerical study of the 3D system. Thus, the presence of degenerate heteroclinic and homoclinic orbits, T-point heteroclinic loops and chaotic attractors is detected. We find numerical evidence that, at least, four curves of codimension-two global bifurcations are related to the triple-zero degeneracy in the system analyzed.Ministerio de Economía y Competitividad MTM2017-87915-C2-1-PMinisterio de Ciencia, Innovación y Universidades - Fondos FEDER PGC2018-096265-B-I0Consejería de Economía, Innovación, Ciencia y Empleo - Junta de Andalucía FQM-276, TIC-0130, UHU-1260150 y P20_0116

Relationship between Bone Quality, Egg Production and Eggshell Quality in Laying Hens at the End of an Extended Production Cycle (105 Weeks)

(1) Background: Nowadays the industry aims to improve lay persistency for extended cycles (100 weeks or longer) to make egg production more sustainable. However, intensive egg pro‐ duction challenges hen health, inducing severe osteoporosis and the incidence of bone fractures. In this study, the relationship between bone quality and egg production, and/or eggshell quality, was evaluated at the end of an extended laying cycle of 100 weeks, comparing groups of hens with dif‐ ferent production and eggshell quality parameters; (2) Methods: Quality parameters of egg (as weight, egg white height), eggshell (as thickness, weight, breaking strength, elasticity and micro‐ structure) and tibiae bone (weight, diameter, cortical thickness, ash weight, breaking strength, me‐ dullary bone) were determined; (3) Results: Hens from groups with a high egg production and good eggshell quality have poorer bone quality (lower ash weight and lesser amount of medullary bone). However, Pearson’s correlation analysis shows no clearrelationship between bone and egg/eggshell parameters. (4) Conclusions: Bone and egg production/eggshell quality are independent and can be improved separately. Medullary bone has an important contribution to bone mechanical properties, being important to accumulate enough bone medullary bone early in life to maintain skeletal integ‐ rity and eggshell quality in old hens.ITC‐20161169/Ovofortis (MINECO/AEI/FEDER, UE)CGL2015‐64683‐PRNM‐179 group (Junta de Andalucía)UCE PP 2016.05 (Universidad de Granada

Bone quality and composition are influenced by egg production, layer line, and oestradiol-17ß in laying hens

Part of this work was supported by the Spanish Ministerio de Ciencia e Innovacion [grant number CGL2015-64683-P].Keel bone fractures are a serious animal welfare problem in laying hens. The aim of the current study was to assess the influence of egg production, oestradiol-17ß, and selection for high laying performance on bone quality. Hens of two layer lines differing in laying performance (WLA: 320 eggs per year, G11: 200 eggs per year) were allocated to four treatment groups. Group S received a deslorelin acetate implant that suppressed egg production. Group E received an implant with the sexual steroid oestradiol-17ß. Group SE received both implants and group C did not receive any implant. In the 63rd week of age, composition and characteristics of the tibiotarsi were assessed using histological analysis, three-point bending test, thermogravimetric analysis, infrared spectroscopy, and two-dimensional X-ray diffraction, respectively. Non-egg-laying hens showed a higher total bone area and a higher relative amount of cortical bone compared to egg-laying hens. Hens of layer line G11 showed a higher relative amount of medullary bone and a higher degree of mineralization of the cortical bone compared to hens of layer line WLA. These differences in bone composition may explain different susceptibility to keel bone fractures in non-egg-laying compared to egg-laying hens as well as in hens of layer lines differing in laying performance. The effect of exogenous oestradiol-17ß on bone parameters varied between the layer lines indicating a genetic influence on bone physiology and the way it can be modulated by hormone substitution.Instituto de Salud Carlos III Spanish Government CGL2015-64683-

An Automated Fall Detection System Using Recurrent Neural Networks

Falls are the most common cause of fatal injuries in elderly people, causing even death if there is no immediate assistance. Fall detection systems can be used to alert and request help when this type of accident happens. Certain types of these systems include wearable devices that analyze bio-medical signals from the person carrying it in real time. In this way, Deep Learning algorithms could automate and improve the detection of unintentional falls by analyzing these signals. These algorithms have proven to achieve high effectiveness with competitive performances in many classification problems. This work aims to study 16 Recurrent Neural Networks architectures (using Long Short-Term Memory and Gated Recurrent Units) for falls detection based on accelerometer data, reducing computational requirements of previous research. The architectures have been tested on a labeled version of the publicly available SisFall dataset, achieving a mean F1-score above 0.73 and improving state-of-the-art solutions in terms of network complexity.Ministerio de Economía y Competitivida TEC2016-77785-

Semi-wildlife gait patterns classification using Statistical Methods and Artificial Neural Networks

Several studies have focused on classifying behavioral patterns in wildlife and captive species to monitor their activities and so to understanding the interactions of animals and control their welfare, for biological research or commercial purposes. The use of pattern recognition techniques, statistical methods and Overall Dynamic Body Acceleration (ODBA) are well known for animal behavior recognition tasks. The reconfigurability and scalability of these methods are not trivial, since a new study has to be done when changing any of the configuration parameters. In recent years, the use of Artificial Neural Networks (ANN) has increased for this purpose due to the fact that they can be easily adapted when new animals or patterns are required. In this context, a comparative study between a theoretical research is presented, where statistical and spectral analyses were performed and an embedded implementation of an ANN on a smart collar device was placed on semi-wild animals. This system is part of a project whose main aim is to monitor wildlife in real time using a wireless sensor network infrastructure. Different classifiers were tested and compared for three different horse gaits. Experimental results in a real time scenario achieved an accuracy of up to 90.7%, proving the efficiency of the embedded ANN implementation.Junta de Andalucía P12-TIC-1300Ministerio de Economía y Competitividad TEC2016-77785-

Breast Cancer Automatic Diagnosis System using Faster Regional Convolutional Neural Networks

Breast cancer is one of the most frequent causes of mortality in women. For the early detection of breast cancer, the mammography is used as the most efficient technique to identify abnormalities such as tumors. Automatic detection of tumors in mammograms has become a big challenge and can play a crucial role to assist doctors in order to achieve an accurate diagnosis. State-of-the-art Deep Learning algorithms such as Faster Regional Convolutional Neural Networks are able to determine the presence of an object and also its position inside the image in a reduced computation time. In this work, we evaluate these algorithms to detect tumors in mammogram images and propose a detection system that contains: (1) a preprocessing step performed on mammograms taken from the Digital Database for Screening Mammography (DDSM) and (2) the Neural Network model, which performs feature extraction over the mammograms in order to locate tumors within each image and classify them as malignant or benign. The results obtained show that the proposed algorithm has an accuracy of 97.375%. These results show that the system could be very useful for aiding physicians when detecting tumors from mammogram images.Ministerio de Economía y Competitividad TEC2016-77785-

Different Solvents for Organosolv Pulping

Organosolv pulping is a two-stage process involving hydrolysis (decomposition of wood by use of a catalyst) and removal of lignin with an organic solvent (usually a mixture of alcohol and water). The main disadvantage of using an alcohol is its low boiling point, which requires operating at a high pressure and hence using special equipment that is expensive to purchase and operate. One solution to this problem is using alternative organic solvents that afford operation at pressure levels similar to those of classic pulping processes (e.g., the Kraft process). This chapter provides a comprehensive literature review on the organosolv-based production of cellulose pulp by using alternative solvents such as glycols, phenols, esters, organic acids, acetone and amines