Agronomic characterization of pigmented native corn populations (Zea mays L.)

ABSTRACT Objective: We performed the agronomical characterization of 52 pigmented corn populations from the state of Coahuila in order to identify those with outstanding agronomical potential and also to establish the genetic background of a breeding program focused in the improvement of varieties with grain yield potential, adaptation capacity to the regional production conditions and of superior nutritional and bioactive contents. Design/methodology: Through an incomplete block design in an alpha lattice arrangement, we evaluated two experiments in two representative locations of the southeastern agricultural area of Coahuila: a) Yellow populations, mostly from Tuxpeño, Ratón and Tuxpeño Norteño races and b) Anthocyanic populations (blue, red and purple), mainly represented by Cónico Norteño, Elotes Cónicos and Ratón races. Results: The results showed a contrasting environmental effect between locations, with differences in grain yield up to 78 %; a 25 days’ difference in flowering, 53 cm in plant height and up to 8 plants without ear; this performance was due to the agricultural potential of each location. We observed that in both locations the yellow populations outstanding by their superior performance were: from the Tuxpeño race: COAH068, COAH089, COAH177 and COAH215, and Celaya race: COAH075. The outstanding anthocyanin populations were: Ratón race: COAH23 and COAH203, Elotes Cónicos race: COAH246 and COAH019, and Elotes Occidentales race: COAH021. Also we found populations with adaptation to a location. Conclusions: We consider that among the diversity of the pigmented corn from Coahuila there are populations of superior agronomic expression that could be used as the genetic background to improve the production and the nutritional quality of the grain and the food products that can be derived from them.Objective: To characterize agronomically 52 populations of pigmented native corn (Zea mays L.) from Coahuila, Mexico, in order to identify varieties with outstanding agronomic potential and to establish an improvement program with potential for grain yield, with the ability to adapt, and superior nutritional bioactive content. Design/Methodology: Two experiments were evaluated through an incomplete block design in lattice alpha arrangement, in two localities that are representative of the agricultural area of southeastern Coahuila: a) Yellow populations, mostly of Tuxpeño, Ratón and Tuxpeño Norteño; and b) Anthocyanin populations (blue, red and purple), represented primarily by Cónico Norteño, Elotes Cónicos and Ratón. Results: There is an environmental effect that contrasts between localities, with differences in grain yield of up to 78%; 25 days of difference in flowering, 53 cm in plant height, and up to seven plants without cobs. The response was product of the agricultural potential in each locality. The outstanding yellow populations due to their superior yield expression in both localities were the landraces Tuxpeño: COAH068, COAH089, COAH177 and COAH215, and Celaya: COAH075. The outstanding anthocyanin populations were Ratón: COAH23 and COAH203; Elotes Cónicos: COAH246 and COAH019; and Elotes Occidentales: COAH021; in addition, the study found populations adapted to a locality. Conclusion: Among the diversity of the pigmented native corn in Coahuila, there are populations with superior agronomic expression that can be the basis for improving the production, the nutritional quality of the grain, and therefore, of its byproducts

Comparación de dos métodos usados para el reconocimiento de arritmias: experimento educativo controlado en estudiantes de medicina

Antecedentes. La habilidad para reconocer arritmias es esencial para los proveedores de reanimación cardiopulmonar avanzada. El desarrollo de esta habilidad es dispendioso y no se han identificado las mejores estrategias educativas para optimizar este proceso.Objetivo. Evaluar y comparar la efectividad y recordación de dos métodos de aprendizaje usados por estudiantes de medicina para reconocer arritmias cardíacas.Material y métodos. El estudio incluyó 99 estudiantes de medicina que se asignaron aleatoriamente a dos grupos. En un grupo se enseñó un método de cuatro pasos (n=51) y en el otro un método de diez pasos (n=48). En cada grupo se enseñó el método respectivo en una conferencia de 60 minutos de duración. Después se realizó una prueba específica para cada grupo con el fin de evaluar la percepción de “facilidad”, el uso y la recordación de cada método. Adicionalmente se evaluó la capacidad para reconocer arritmias en una prueba práctica general para los dos grupos.Resultados. Las características de base no eran diferentes entre los dos grupos antes de la asignación aleatoria. La capacidad para reconocer arritmias fue mejor en el grupo de cuatro pasos, porque aumenta la proporción de estudiantes con puntajes mayor o igual a 30 puntos sobre 50 (82% vs 19%; RR 4.39, IC 95% 2.40-8.02; NNT 2), aumenta la mediana de puntajes (34 ± 8 vs 23 ± 8; valor

Carbón vegetal como mejorador de un Acrisol cultivado con caña de azúcar (Saccharum spp.)

Objective: To analyze the effect of the addition of charcoal residues on physical and chemical properties of an Acrisol cultivated with sugar cane in the savannah of Huimanguillo, Tabasco, Mexico. Design/methodology/approach: Unmarketable waste charcoal were used, from the company "El Cocoite", from Villahermosa, Tabasco, Mexico. An incubation with charcoal mixed with 300 g of soil was performed for different treatments: 0, 1.2g, 1.8g, 2.4g, 3.0g, 3.6 g, 4.2 g and 4.8 g. Two samples were made at 45 and 90 days, in each sample the soil moisture (SM), bulk density (Bd), pH (H2O), organic carbon (OC), C / N, cation exchange capacity was measured (CEC), exchangeables bases, and exchangeable acidity were evaluating. Results: The soil was improved in physical properties: by increasing soil moisture and keeping an appropriate Bd. The chemical properties such as CO, pH, CIC, Ca 2+, Mg 2+ Na+ and K+, were improved, and the exchangeable acidity reduced. Limitations/study implications: Low crop yield in Acrisols used for sugar cane cultivation, limit the sustainability of this high economic impact agricultural activity in the Southeast of Mexico. Findings/conclusions: This would help improve the availability of plant nutrients in the Ferric Acrisol cultivated with sugar cane.Objetivo: Analizar el efecto de la adición de residuos de carbón vegetal sobre las propiedades físicas y químicas de un suelo Acrisol cultivado con caña de azúcar en la sabana de Huimanguillo, Tabasco, México. Diseño/metodología/aproximación: Se utilizaron residuos de carbón vegetal no comercializable, proveniente de la empresa “El Cocoite”, de Villahermosa, Tabasco, México. Para ello se realizó una incubación con los tratamientos: 0, 1.2g, 1.8 g, 2.4 g, 3.0g, 3.6 g, 4.2 g y 4.8 g, de carbón mezclado con 300 g de suelo. Se realizaron dos muestreos, a los 45 y 90 días, en cada muestreo se midió la humedad aprovechable (Ha), densidad aparente (Da), pH (H2O), carbono orgánico (CO), C/N, capacidad intercambió catiónico (CIC), bases intercambiables y acidez intercambiable. Resultados: Se mejoraron las propiedades físicas del suelo, aumentando la Ha y conservando una Da apropiada. Las propiedades químicas del suelo mejoraron y se redujo la acidez intercambiable. Limitaciones/implicaciones del estudio: Los bajos rendimientos en los Acrisoles utilizados para el cultivo de caña de azúcar, suponen una dificultad para la sustentabilidad de esta actividad agrícola de alta importancia económica en el Sureste de México. Hallazgos/conclusiones: Esto ayudaría a mejorar la disponibilidad de nutrientes a la planta en el Acrisol férrico cultivado con caña de azúcar

Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

Role of age and comorbidities in mortality of patients with infective endocarditis

Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Latitude dictates plant diversity effects on instream decomposition

Running waters contribute substantially to global carbon fluxes through decomposition of terrestrial plant litter by aquatic microorganisms and detritivores. Diversity of this litter may influence instream decomposition globally in ways that are not yet understood. We investigated latitudinal differences in decomposition of litter mixtures of low and high functional diversity in 40 streams on 6 continents and spanning 113 degrees of latitude. Despite important variability in our dataset, we found latitudinal differences in the effect of litter functional diversity on decomposition, which we explained as evolutionary adaptations of litter-consuming detritivores to resource availability. Specifically, a balanced diet effect appears to operate at lower latitudes versus a resource concentration effect at higher latitudes. The latitudinal pattern indicates that loss of plant functional diversity will have different consequences on carbon fluxes across the globe, with greater repercussions likely at low latitudes