Guía de diseño para portales web transparentes

ManualLa Guía de diseño para portales web transparentes es una herramienta para facilitar el proceso de construcción de las secciones de transparencia a las personas encargadas de actualizar el contenido de los sitios web de las instituciones y organizaciones. El usuario de esta guía no requerirá tener conocimientos previos en comunicación, diseño gráfico, diseño web ni programación para poder comprender e implementar cada uno de los apartados de la guía. Sin embargo, si los posee, encontrará en ella una herramienta para definir la estructura, estilo visual y contenido de transparencia de manera ágil, contando con estándares y buenas prácticas definidas a nivel internacional.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Sociales::Centro de Investigación y Capacitación en Administración Pública (CICAP

A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation

Latent fingerprint identification is attracting increasing interest because of its important role in law enforcement. Although the use of various fingerprint features might be required for successful latent fingerprint identification, methods based on minutiae are often readily applicable and commonly outperform other methods. However, as many fingerprint feature representations exist, we sought to determine if the selection of feature representation has an impact on the performance of automated fingerprint identification systems. In this paper, we review the most prominent fingerprint feature representations reported in the literature, identify trends in fingerprint feature representation, and observe that representations designed for verification are commonly used in latent fingerprint identification. We aim to evaluate the performance of the most popular fingerprint feature representations over a common latent fingerprint database. Therefore, we introduce and apply a protocol that evaluates minutia descriptors for latent fingerprint identification in terms of the identification rate plotted in the cumulative match characteristic (CMC) curve. From our experiments, we found that all the evaluated minutia descriptors obtained identification rates lower than 10% for Rank-1 and 24% for Rank-100 comparing the minutiae in the database NIST SD27, illustrating the need of new minutia descriptors for latent fingerprint identification.This work was supported in part by the National Council of Science and Technology of Mexico (CONACYT) under Grant PN-720 and Grant 63894

Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level

In more recent years, a significant increase in the number of available biological experiments has taken place due to the widespread use of massive sequencing data. Furthermore, the continuous developments in the machine learning and in the high performance computing areas, are allowing a faster and more efficient analysis and processing of this type of data. However, biological information about a certain disease is normally widespread due to the use of different sequencing technologies and different manufacturers, in different experiments along the years around the world. Thus, nowadays it is of paramount importance to attain a correct integration of biologically-related data in order to achieve genuine benefits from them. For this purpose, this work presents an integration of multiple Microarray and RNA-seq platforms, which has led to the design of a multiclass study by collecting samples from the main four types of leukemia, quantified at gene expression. Subsequently, in order to find a set of differentially expressed genes with the highest discernment capability among different types of leukemia, an innovative parameter referred to as coverage is presented here. This parameter allows assessing the number of different pathologies that a certain gen is able to discern. It has been evaluated together with other widely known parameters under assessment of an ANOVA statistical test which corroborated its filtering power when the identified genes are subjected to a machine learning process at multiclass level. The optimal tuning of gene extraction evaluated parameters by means of this statistical test led to the selection of 42 highly relevant expressed genes. By the use of minimum- Redundancy Maximum-Relevance (mRMR) feature selection algorithm, these genes were reordered and assessed under the operation of four different classification techniques. Outstanding results were achieved by taking exclusively the first ten genes of the ranking into consideration. Finally, specific literature was consulted on this last subset of genes, revealing the occurrence of practically all of them with biological processes related to leukemia. At sight of these results, this study underlines the relevance of considering a new parameter which facilitates the identification of highly valid expressed genes for simultaneously discerning multiple types of leukemia.This work was supported by Project TIN2015-71873-R (Spanish Ministry of Economy and Competitiveness -MINECO- and the European Regional Development Fund -ERDF) and Junta de Andalucı´a (P12–TIC–2082)

Seroprevalencia y factores asociados a la brucelosis bovina en la provincia de Pinar del Río, Cuba

The objective of this study was to determine the seroprevalence of bovine brucellosis and identify risk factors for brucellosis in Pinar del Río province, Cuba. A cross-sectional study was performed based on the results of the epidemiological surveillance programme. Geospatial distribution was analyzed by calculating the standardized incidence ratio (SIR) at the municipality level. In addition, the association between diagnostic results and factors such as the productive system, sex and age groups (<12, 12-24, 24-36, >36 months) was assessed. A total of 12 760 blood samples were processed and 113 were positive; thus, the estimated seroprevalence in the province was 0.89% (95 % CI 0.74-1.06). The disease was present in three out of eight municipalities in the province (Los Palacios, Consolación del Sur and Pinar del Río), although only in Los Palacios the prevalence was significantly higher than that expected: 2.40 (1.30-3.28). Furthermore, the prevalence ratio in animals younger than 12 months was 8.33 (1.41-49.42) times higher than in animals between 12 and 24 months of age. In conclusion, the municipality of origin and age category are relevant factors that should be considered by the health authorities to design disease control strategies in the province.El objetivo del estudio fue determinar la seroprevalencia de brucelosis bovina e identificar factores de riesgo para brucelosis en la provincia de Pinar del Río, Cuba. Se realizó un estudio transversal basado en los resultados del programa de vigilancia epidemiológica. La distribución geoespacial se analizó mediante el cálculo de la razón de incidencia estandarizada (SIR) a nivel de municipio. Además, se evaluó la asociación entre los resultados del diagnóstico y factores como el sistema productivo, el sexo y los grupos de edad (<12, 12-24, 24-36, >36 meses). Se procesaron 12 760 muestras de sangre y 113 resultaron positivas; así, la seroprevalencia estimada en la provincia fue de 0.89% (IC 95 % 0.74-1.06). La enfermedad estuvo presente en tres de los ocho municipios de la provincia (Los Palacios, Consolación del Sur y Pinar del Río), aunque solo en Los Palacios la prevalencia fue significativamente superior a la esperada: 2.40 (1.30-3.28). Además, la razón de prevalencia en animales menores de 12 meses fue 8.33 (1.41-49.42) veces mayor que en animales entre 12 y 24 meses. En conclusión, el municipio de procedencia y la categoría de edad son factores relevantes que deben ser considerados por las autoridades de salud para diseñar estrategias de control de enfermedades en la provincia

DETECCIÓN DE OVINOS PREÑADOS USANDO ALGORITMOS DE INTELIGENCIA Y VISIÓN ARTIFICIAL (SHEEP PREGNANCY DETECTION USING ARTIFICIAL INTELLIGENT AND ARTIFICIAL VISION ALGORITHMS)

El estado de preñez en ovejas es un suceso importante en la producción ovina que exige a los productores realizar cuidados oportunos como: atenciones sanitarias, vigilancia veterinaria y cambio de dieta alimenticia, con el objetivo de garantizar la obtención de una cría sana; por lo cual, detectar de manera temprana este estado es esencial para la toma de decisiones en la práctica pecuaria. Considerando que las formas tradicionales de detección de preñez son invasivas y afectan el bienestar animal, el presente trabajo propone la detección automática de patrones térmicos que permitan determinar si una oveja se encuentra o no preñada a través de imágenes termográficas capturadas de la zona ventral en diferentes etapas de gestación. La propuesta del algoritmo se dividió en dos partes esenciales: segmentación y detección. Se segmentaron los componentes caloríficos presentes en la imagen termográfica por intervalos de temperatura, haciendo uso del algoritmo supervisado de segmentación K-means. Por otra parte, la detección del espectro fetal, se llevó acabo con la implementación del algoritmo Haar-Cascade propuesto por Viola y Jones, entrenado con los conjuntos de imágenes obtenidas de la segmentación; un conjunto de 500 imágenes positivas que contienen la zona de interés, y un grupo de 1000 imágenes negativas donde se muestra la ausencia del feto. Con el método propuesto se obtuvo un porcentaje de asertividad del 80% en la detección automática de espectros térmicos fetales, incluso logrando una múltiple detección de la zona de interés, que permitirá incrementar el índice de asertividad en la etapa de identificación del feto.Palabras clave: Ovino, Preñez, imagen infrarroja, K-means, Haar-Cascade. AbstractThe state of pregnancy in sheep is an important event in ovine production that requires producers to take timely cares such as: health care, veterinary surveillance and change of diet, with the aim of guaranteeing a healthy breeding; therefore, early detection of this condition is essential for decision-making in livestock practice. Considering that the traditional forms of pregnancy detection are invasive and affect animal welfare, the present work proposes the automatic detection of thermal patterns that allow determining if a sheep is pregnant or not through thermographic images captured from the ventral area in different gestation stages. The algorithm proposal was divided into two essential parts: segmentation and detection. The calorific components present in the thermographic image were segmented by temperature intervals, making use of the supervised K-means segmentation algorithm. On the other hand, the detection of the fetal spectrum was carried out with the implementation of the Haar-Cascade algorithm proposed by Viola and Jones, trained with the sets of images obtained from the segmentation; a set of 500 positive images that contain the area of interest, and a group of 1000 negative images showing the absence of the fetus. With the proposed method, 80% of accuracy was obtained in the automatic detection of fetal thermal spectra, even achieving a multiple detection of the area of interest, which will allow to increase the accuracy index in fetus identification stage.Keywords: Ovine, Pregnancy, Infrared image, K-means, Haar-Cascade

Sistema de indicadores y mapa de resultados esperados del proyecto RESISOR

págs. 39-59.Capítulo incluido en el libro: Informe de Evaluación del Proyecto RESISOR "Regional Single Social Record". M.ª Dolores Muñoz de Dios y José Ignacio García Pérez (autores). Sevilla: Universidad Internacional de Andalucía, 2019. ISBN 978-84-7993-344-9. Enlace: http://hdl.handle.net/10334/3938. En este capítulo se muestra el resultado del trabajo realizado por el grupo de personas expertas en la elaboración del Sistema de Indicadores y Mapa de Resultados del Proyecto RESISOR. Incluye el Marco lógico de Indicadores como propuesta metodológica establecida así como el sistema de indicadores según los grupos de trabajo establecidos para la realización del proyecto: Gestión y Coordinación, Definición de la HSUE, Desarrollo de la HSUE, Implementación de la HSUE,8 Evaluación y Comunicación. También se incorpora tanto el marco lógico de indicadores RESISOR como el mapa de resultados esperados del proyecto

Las ciencias sociales en el noreste de México.

Texto colectivo que incluye seis ensayos donde se reflexiona sobre el estado que guardan las ciencias sociales en el noreste de México: antropología, comunicación, economía, geografía, historia y sociología.Redactado por miembros del Grupo Gente (Grupo de Estudios sobre el Noreste de México y Texas) bajo la coordinación de César Morado y Lucila Hinojosa

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

The Helicobacter pylori Genome Project : insights into H. pylori population structure from analysis of a worldwide collection of complete genomes

Helicobacter pylori, a dominant member of the gastric microbiota, shares co-evolutionary history with humans. This has led to the development of genetically distinct H. pylori subpopulations associated with the geographic origin of the host and with differential gastric disease risk. Here, we provide insights into H. pylori population structure as a part of the Helicobacter pylori Genome Project (HpGP), a multi-disciplinary initiative aimed at elucidating H. pylori pathogenesis and identifying new therapeutic targets. We collected 1011 well-characterized clinical strains from 50 countries and generated high-quality genome sequences. We analysed core genome diversity and population structure of the HpGP dataset and 255 worldwide reference genomes to outline the ancestral contribution to Eurasian, African, and American populations. We found evidence of substantial contribution of population hpNorthAsia and subpopulation hspUral in Northern European H. pylori. The genomes of H. pylori isolated from northern and southern Indigenous Americans differed in that bacteria isolated in northern Indigenous communities were more similar to North Asian H. pylori while the southern had higher relatedness to hpEastAsia. Notably, we also found a highly clonal yet geographically dispersed North American subpopulation, which is negative for the cag pathogenicity island, and present in 7% of sequenced US genomes. We expect the HpGP dataset and the corresponding strains to become a major asset for H. pylori genomics