Low frequency of inversion-carrying chromosomes in a population of Drosophila melanogaster from a cellar habitat

International audienc

Detecting vapour bubbles in simulations of metastable water

International audienceThe investigation of cavitation in metastable liquids with molecular simulations requires an appropriate definition of the volume of the vapour bubble forming within the metastable liquid phase. Commonly used approaches for bubble detection exhibit two significant flaws: first, when applied to water they often identify the voids within the hydrogen bond network as bubbles thus masking the signature of emerging bubbles and, second, they lack thermodynamic consistency. Here, we present two grid-based methods, the M-method and the V-method, to detect bubbles in metastable water specifically designed to address these shortcomings. The M-method incorporates information about neighbouring grid cells to distinguish between liquid- and vapour-like cells, which allows for a very sensitive detection of small bubbles and high spatial resolution of the detected bubbles. The V-method is calibrated such that its estimates for the bubble volume correspond to the average change in system volume and are thus thermodynamically consistent. Both methods are computationally inexpensive such that they can be used in molecular dynamics and Monte Carlo simulations of cavitation. We illustrate them by computing the free energy barrier and the size of the critical bubble for cavitation in water at negative pressure

Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms

To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has to be increased. Consequently, the training computational cost is unaffordable for very low objective function value estimations, and the use of Importance Sampling (IS) techniques becomes convenient. The study of three different objective functions is considered, which implies the proposal of estimators of the objective function using IS techniques: the Mean-Square error, the Cross Entropy error and the Misclassification error criteria. The values of these functions are estimated by IS techniques, and the results are used to train NNs by the application of Genetic Algorithms. Results for a binary detection in Gaussian noise are provided. These results show the evolution of the parameters during the training and the performances of the proposed detectors in terms of error probability and Receiver Operating Characteristics curves. At the end of the study, the obtained results justify the convenience of using IS in the training

Enhanced Parallel Generation of Tree Structures for the Recognition of 3D Images

Segmentations of a digital object based on a connectivity criterion at n-xel or sub-n-xel level are useful tools in image topological analysis and recognition. Working with cell complex analogous of digital objects, an example of this kind of segmentation is that obtained from the combinatorial representation so called Homological Spanning Forest (HSF, for short) which, informally, classifies the cells of the complex as belonging to regions containing the maximal number of cells sharing the same homological (algebraic homology with coefficient in a field) information. We design here a parallel method for computing a HSF (using homology with coefficients in Z/2Z) of a 3D digital object. If this object is included in a 3D image of m1 × m2 × m3 voxels, its theoretical time complexity order is near O(log(m1 + m2 + m3)), under the assumption that a processing element is available for each voxel. A prototype implementation validating our results has been written and several synthetic, random and medical tridimensional images have been used for testing. The experiments allow us to assert that the number of iterations in which the homological information is found varies only to a small extent from the theoretical computational time.Ministerio de Economía y Competitividad MTM2016-81030-

Utilización de subproductos industriales en la alimentación de cerdos de engorde en Cuba

Fifty-four pigs averaging 75 days of age and ± 22.0 kg live weight. The pigs were allotted according to a random blocks design in three treatments, two replicas (house side) and nine repetitions for treatment in each replica. The effect of a foodstuffs "B" (balanced feed of medium quality with soybean and corn and 30% of the wheat Cuban byproduct)1 in diets of sugar cane molasses type B (MB), and the inclusion in the diet of 10% of distiller dried grains with soluble obtained from the maize (DDGS)2, on the animal performance traits in comparison with a concentrated feedstuffs3, was studied. There were no significant differences for the consumptions of MB in the diets of feedstuffs B + MB and the diet with 10% of DDGS inclusion; there were significant differences (P< 0.01) for the animals fed with the concentrated feedstuffs. The alimentary conversion was very significant (P< 0.001). The slaughter weight had significant differences (P< 0.01) among treatments. It is concluded, that diets of a feedstuffs B plus MB of sugar cane and diets including 10% of DDGS generate excellent productive indexes and constitute alternative sources under tropical conditions that substitute imports of cereals in the Cuban pig feeding

Surrogate-based optimization of tidal turbine arrays: a case study for the Faro-Olhão inlet

This paper presents a study for estimating the size of a tidal turbine array for the Faro-Olhão Inlet (Potugal) using a surrogate optimization approach. The method compromises problem formulation, hydro-morphodynamic modelling, surrogate construction and validation, and constraint optimization. A total of 26 surrogates were built using linear RBFs as a function of two design variables: number of rows in the array and Tidal Energy Converters (TECs) per row. Surrogates describe array performance and environmental effects associated with hydrodynamic and morphological aspects of the multi inlet lagoon. After validation, surrogate models were used to formulate a constraint optimization model. Results evidence that the largest array size that satisfies performance and environmental constraints is made of 3 rows and 10 TECs per row.Eduardo González-Gorbeña has received funding for the OpTiCA project (http://msca-optica.eu/) from the Marie Skłodowska-Curie Actions of the European Union's H2020-MSCA-IF-EF-RI-2016 / GA#: 748747. The paper is a contribution to the SCORE pro-ject, funded by the Portuguese Foundation for Science and Technology (FCT–PTDC/AAG-TEC/1710/2014). André Pacheco was supported by the Portuguese Foun-dation for Science and Technology under the Portuguese Researchers’ Programme 2014 entitled “Exploring new concepts for extracting energy from tides” (IF/00286/2014/CP1234).info:eu-repo/semantics/publishedVersio

Construyendo dominios de encuentro para problematizar acerca de las prácticas pedagógicas de profesores secundarios de Ciencias: Incorporando el modelo de Investigación-Acción como plan de formación continua

Frente a la actual crisis de la educación científica, la capacidad docente de transformar sus prácticas para mejorar el logro de aprendizajes parece ser fundamental. Los programas de formación docente continua tradicionales, generalmente prescriptivos y descontextualizados del aula, han tenido bajo impacto en los procesos de transformación de las prácticas docentes. El presente trabajo describe la primera fase de un programa de formación continua consistente en la construcción de dominios de encuentro entre el saber académico generado en la Universidad y el saber profesional de 16 profesores secundarios de Ciencias a través de un proceso de investigación-acción conjunta, basado en el trabajo colaborativo, la reflexión y la retroalimentación. Los resultados dan cuenta de la complejidad de generar significados comunes, los que una vez logrados, permiten fortalecer el razonamiento científico, la autoeficacia y conformación de una comunidad de aprendizaje que posibilita una actitud indagatoria hacia sus prácticas en Ciencias. / Considering the current scientific education crisis, teachers' capacity to transform their practice in order to improve learning achievement seems fundamental. The traditional programs of continuous professional development, generally prescriptive and uncontextualized from the classroom, have had a low impact on processes of teachers' practice transformation. This work describes the first stage of continuous development program, consisting on building encounter domains between the academic knowledge of Universities, and professional knowledge of 16 secondary science teachers, through a joint action-research process, based on collaborative work, reflection and feedback. The results show the complexity of building shared sense which, once achieved, allows strong scientific reasoning, self-efficacy and the construction of a learning community facilitating an inquiry-driven attitude towards their science teaching practice

Color image segmentation using perceptual spaces through applets for determining and preventing diseases in chili peppers

Plant pathogens cause disease in plants. Chili peppers are one of the most important crops in the world. There are currently disease detection techniques classified as: biochemical, microscopy, immunology, nucleic acid hybridization, identification by visual inspection in vitro or in situ but these have the following disadvantages: they require several days, their implementation is costly and highly trained. This paper proposes a method for knowing and preventing the disease in chili peppers plant through a color image processing, using online system developed in Java applets. This system gets results in real time and remotely (Internet). The images are converted to perceptual spaces [hue, saturation and lightness (HSL), hue, saturation, and intensity (HSI) and hue saturation and value (HSV)]. Sequence was applied to the proposed method. HSI color space was the best detected disease. The percentage of disease in the leaf is of 12.42%. HSL and HSV do not expose the exact area of the disease compared to the HSI color space. Finally, images were analyzed and the disease is known by the expert in plant pathology to take preventive or corrective actions.Keywords: Applets, knowing disease, color image segmentation, perceptual spacesAfrican Journal of Biotechnology Vol. 12(7), pp. 679-68

CAMBIO DE COBERTURA Y USO DEL SUELO EN LA CUENCA DEL RIO MOLOLOA, NAYARIT

Los cambios de cobertura y uso del suelo se han reconocido en muchos países como una de las principales causas de deterioro ambiental, por ello están ubicados en el centro de la investigación ambiental y representan un punto importante en diferentes ámbitos como medio para entender los mecanismos de este proceso de deterioro y guía para la toma razo- nable de decisiones sobre el uso del territorio. En el estado de Nayarit, la cuenca del río Mo- loloa ha proveído de un conjunto de bienes y servicios a las localidades que involucra; des- afortunadamente, esta relación ha repercutido en un deterioro acelerado de sus recursos na- turales. En este trabajo se analizan los cambios de cobertura y uso del suelo en la cuenca del río Mololoa, entre 1995 y 2005, a partir de la interpretación de ortofotos digitales y manejo de la información en un SIG. Los resultados muestran que el paisaje de la cuenca está dominado en 83.01% por la vegetación natural y tierras de cultivo. La dinámica de cambio está centrada en los tipos de cobertura “vegetación natural” y “construcciones”, la primera disminuye a una tasa de 41.67 ha/año, y la segunda, aumenta 74.86 ha/año. La tasa de deforestación de los bosques y selvas de la región fue de 0.1 y 0.36%, menor a las reportadas por diferentes autores a nivel nacional y estatal

Quantification of virus syndrome in chili peppers

One of the most important problems to produce chili crops is the presence of diseases caused by pathogen agents, such as viruses, therefore, there is a substantial necessity to better predict the behavior of the diseases of these crops, determining a more precise quantification of the disease’s syndrome that allows the investigators to evaluate better practices, from handling to the experimental level and will permit producers to take opportunistic corrective action thereby, reducing production loses and increasing the quality of the crop. This review discussed methods that have been used for the quantification of disease in plants, specifically for chili peppers crops, thereby, suggesting a better alternative for the quantification of the disease’ syndromes in regards to this crop. The result of these reflections indicates that most methods used for quantification are based on visual assessments, discarding differences of data between distinctive evaluators. These methods generate subjective results.Key words: Quantification, plant diseases, severity, syndrome, viruses