Predicting Stream Nitrogen Concentration From Watershed Features Using Neural Networks

The present work describes the development and validation of an artificial neural network (ANN) for the purpose of estimating inorganic and total nitrogen concentrations. The ANN approach has been developed and tested using 927 nonpoint source watersheds studied for relationships between macro-drainage area characteristics and nutrient levels in streams. The ANN had eight independent input variables of watershed parameters (five on land use features, mean annual precipitation, animal unit density and mean stream flow) and two dependent output variables (total and inorganic nitrogen concentrations in the stream). The predictive quality of ANN models was judged with “hold-out” validation procedures. After ANN learning with the training set of data, we obtained a correlation coefficient r of about 0.85 in the testing set. Thus, ANNs are capable of learning the relationships between drainage area characteristics and nitrogen levels in streams, and show a high ability to predict from the new data set. On the basis of the sensitivity analyses we established the relationship between nitrogen concentration and the eight environmental variables

Differential pharmacokinetics and pharmacokinetic/pharmacodynamic modelling of robenacoxib and ketoprofen in a feline model of inflammation

Robenacoxib and ketoprofen are acidic nonsteroidal anti‐inflammatory drugs (NSAIDs). Both are licensed for once daily administration in the cat, despite having short blood half‐lives. This study reports the pharmacokinetic/pharmacodynamic (PK/PD) modelling of each drug in a feline model of inflammation. Eight cats were enrolled in a randomized, controlled, three‐period cross‐over study. In each period, sterile inflammation was induced by the injection of carrageenan into a subcutaneously implanted tissue cage, immediately before the subcutaneous injection of robenacoxib (2 mg/kg), ketoprofen (2 mg/kg) or placebo. Blood samples were taken for the determination of drug and serum thromboxane (Tx)B2 concentrations (measuring COX‐1 activity). Tissue cage exudate samples were obtained for drug and prostaglandin (PG)E2 concentrations (measuring COX‐2 activity). Individual animal pharmacokinetic and pharmacodynamic parameters for COX‐1 and COX‐2 inhibition were generated by PK/PD modelling. S(+) ketoprofen clearance scaled by bioavailability (CL/F) was 0.114 L/kg/h (elimination half‐life = 1.62 h). For robenacoxib, blood CL/F was 0.684 L/kg/h (elimination half‐life = 1.13 h). Exudate elimination half‐lives were 25.9 and 41.5 h for S(+) ketoprofen and robenacoxib, respectively. Both drugs reduced exudate PGE2 concentration significantly between 6 and 36 h. Ketoprofen significantly suppressed (>97%) serum TxB2 between 4 min and 24 h, whereas suppression was mild and transient with robenacoxib. In vivoIC50COX‐1/IC50COX‐2 ratios were 66.9:1 for robenacoxib and 1:107 for S(+) ketoprofen. The carboxylic acid nature of both drugs may contribute to the prolonged COX‐2 inhibition in exudate, despite short half‐lives in blood

La distance cognitive avec le territoire d’origine du produit alimentaire

Les consommateurs sont sensibles aux Produits d’origine géographique (POG). Le territoire de provenance est aussi l’élément déterminant du choix du produit. Quelle sensibilité ou affection au territoire les individus peuvent-ils avoir en fonction de leur niveau de connaissance et leur degré d’attachement au territoire ? Cette question est analysée avec la méthode des réseaux de neurones artificiels et la carte auto-organisatrice de Kohonen. Les résultats montrent une forte relation entre connaissance réelle de l’espace et identification des produits correspondants. L’article utilise la notion de distance cognitive pour analyser cette relation.Consumers are sensitive to the Products of Geographical Origin. The source’s territory is frequently the element determining of product’s choice. What is the sensitivity of consumers about territory of origin? Individuals can accord some interests about products to their level of knowledge and their degree of attachment to the territory. These problems are analyzed by artificial neural networks (Kohonen Self Organizing Map). Results show a strong relation between real knowledge of space and identification of the corresponding products. We apply the cognitive distance to analyze this relationship

Mapping the species richness and composition of tropical forests from remotely sensed data with neural networks

The understanding and management of biodiversity is often limited by a lack of data. Remote sensing has considerable potential as a source of data on biodiversity at spatial and temporal scales appropriate for biodiversity management. To-date, most remote sensing studies have focused on only one aspect of biodiversity, species richness, and have generally used conventional image analysis techniques that may not fully exploit the data's information content. Here, we report on a study that aimed to estimate biodiversity more fully from remotely sensed data with the aid of neural networks. Two neural network models, feedforward networks to estimate basic indices of biodiversity and Kohonen networks to provide information on species composition, were used. Biodiversity indices of species richness and evenness derived from the remotely sensed data were strongly correlated with those derived from field survey. For example, the predicted tree species richness was significantly correlated with that observed in the field (r=0.69, significant at the 95% level of confidence). In addition, there was a high degree of correspondence (?83%) between the partitioning of the outputs from Kohonen networks applied to tree species and remotely sensed data sets that indicated the potential to map species composition. Combining the outputs of the two sets of neural network based analyses enabled a map of biodiversity to be produce

Modeling of Large Pharmacokinetic Data Using Nonlinear Mixed-Effects: A Paradigm Shift in Veterinary Pharmacology. A Case Study With Robenacoxib in Cats

The objective of this study was to model the pharmacokinetics (PKs) of robenacoxib in cats using a nonlinear mixed‐effects (NLME) approach, leveraging all available information collected from cats receiving robenacoxib s.c. and/or i.v.: 47 densely sampled laboratory cats and 36 clinical cats sparsely sampled preoperatively. Data from both routes were modeled sequentially using Monolix 4.3.2. Influence of parameter correlations and available covariates (age, gender, bodyweight, and anesthesia) on population parameter estimates were evaluated by using multiple samples from the posterior distribution of the random effects. A bicompartmental disposition model with simultaneous zero and first‐order absorption best described robenacoxib PKs in blood. Clearance was 0.502 L/kg/h and the bioavailability was high (78%). The absorption constant point estimate (Ka = 0.68 h−1) was lower than beta (median, 1.08 h−1), unveiling flip‐flop kinetics. No dosing adjustment based on available covariates information is advocated. This modeling work constitutes the first application of NLME in a large feline population

Paw Inflammation Model in Dogs for Preclinical Pharmacokinetic/Pharmacodynamic Investigations of Nonsteroidal Anti-Inflammatory Drugs

The goal of the present study was to develop and validate a new canine model of inflammation. The motivation was to make available a scientifically appropriate and ethically acceptable model to conduct pharmacokinetic/pharmacodynamic investigations for testing nonsteroidal anti-inflammatory drugs in dogs. A kaolin-induce paw inflammation model previously developed in cats was adapted to the dog. The paw inflammation developed within a few hours, reached maximum values 24 h and up to 3 days after kaolin administration, and then progressively resolved over 2 months. Five end points of clinical interest (body temperature, creeping time under a tunnel, paw withdrawal latency to a standardized thermal stimulus, lameness score, and vertical force developed during walking on a force plate) were measured regularly over the next 24 h and beyond to characterize the time development of the inflammation either in control conditions (placebo period) or after the administration of meloxicam (test period) according to a crossover design. Pharmacodynamic data were modeled using an indirect response pharmacokinetic/pharmacodynamic model. This model described three effects of meloxicam, namely, classic anti-inflammatory, analgesic, and antipyretic effects. The mean plasma meloxicam IC(50) values were 210 ng/ml for the antipyretic effect, 390 ng/ml for the analgesic effect, and 546 ng/ml for the vertical force exerted by the paw on the ground as measured by force plates. These in vivo IC(50) values require approximately 80 (antipyretic effect) to 90% (all other effects) cyclooxygenase-2 inhibition as calculated ex vivo whole-blood assay data

Les cartes auto-organisatrices de Kohonen appliquées à l'étude des communautés de micro-algues des cours d'eau

Les cartes auto-organisatrices de Kohonen appliquées à l'étude des communautés de micro-algues des cours d'ea

Nouvelle approche expérimentale pour l'analyse de la recouvrance viscoélastique d'un polymère vitreux non transparent

L'objectif de cette étude est la compréhension des mécanismes rhéologiques pilotant la recouvrance d'une surface polymère ou composite préalablement soumise à une contrainte normale par un indenteur sphérique rigide. Pour réaliser cette étude, le premier point clé est la méthode de caractérisation expérimentale de la recouvrance. Notre équipe a développé un ensemble de dispositifs expérimentaux dédiés à l'étude des mécanismes physiques pilotant la mécanique du contact sur surfaces de polymères transparents sans être modèle dépendant dans l'analyse. L'étape actuelle est d'étendre cette étude aux polymères non transparents ou aux nanocomposites avec un second montage où l'application de la charge est assurée par un appareil UMT (Bruker) et la mesure de la recouvrance de l'empreinte est obtenue par une technique de déflectométrie optique Holomap® développée par le CRITT Holo3. Ce montage permet d'étudier les cinétiques de recouvrance viscoélastique/viscoplastique