Camarón de río Cryphiops caementarius (Molina, 1782) en la costa centro-sur del Perú, 2007

Entre julio y diciembre del 2007, se efectuó el Monitoreo Poblacional del Cryphiops caementarius de los ríos Cañete, Ocoña, Majes-Camaná y Tambo. La calidad del agua evidenció alteraciones en los parámetros fisicoquímicos con respecto al periodo 1996-2007. El río Majes-Camaná alcanzó los mayores valores de densidad (1,87 ind/m2) y biomasa media (21,51 g/m2), en el río Cañete hubo reducción en la densidad (0,25 ind/m2) y biomasa media (2,28 g/m2) que coincidió con mayor número de ejemplares menores a 70 mm.

Reliure de : Le Diverse et artificiose machine del capitano Agostino Ramelli dal ponte della Tresia... Nelle quali si contengono varii et industriosi movimenti... composte in lingua italiana et francese

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Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

Reliure de : Justini, L. Flori et Ruffi Historiae. - "Fol. AAi" : Trogi Pompeii Historia per Justinum in compendium redacta proxime quam emendatissime edita. - "Fol. L ij" : Ad magnificum comitem Petrum Mariam Rubeum Parmensem Philippi Broaldi ["sic"] Bononiensis epistola, in Lucii Flori Gestorum ro. epithoma. - "Fol. P iiij v°" : Sexti Ruffi, viri consularis, Valentiano Augusto de Historia ro. libellus incipit. - "A la fin" : Habes, candide lector, in hoc volumine non minus utilia quam lepida Justini in Trogum et Flori in Livium, insuper Sexti Ruffi, viri consularis, epithomas nuper castigatissime editas Mediolani, ex Minutiana officina. 1520 pridie kalendas augustas

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Algunos Briozos del Cuaternario del Delta del río Llobregat (Barcelona)

Se estudian algunas formas de Briozoos del Cuaternario del delta del Llobregat (tocando a la ciudad de Barcelona). Se reconocen dos especies del gnero Cellaria, una Discoporella, una Cupztladria y una Porclla. Adems de una discusin sistemtica sobre el gnero Cellaria y Porclla se dan datos micromtricos abundantes y se establecen comparaciones con los dados por otros autores insinundose algunas conclusiones.