Advances in therapeutic risk management through signal detection and risk minimisation tool analyses

Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.

Studies on the Nature and Chemistry of Sediments and Water of Periyar and Chalakudy Rivers, Kerala, India

The present study is an attempt to address issues related to sediment properties like texture, mineralogy and geochemistry as well as water quality of two important rivers of central Kerala-the Periyar and the Chalakudy rivers. The main objectives of the study are to investigate the textural and mineralogical characteristics as well as transportation and depositional mechanisms of the sediments of Periyar and Chalakudy rivers, to find out the geochemical variability of organic carbon, phosphorus and certain major (Na,K,Ca and Mg) and minor/trace(Mn,Pb,Ni,Cr, and Zn) elements in the bulk sediments and mud fraction of these rivers, to evaluate the status of heavy metal pollution registered in the sediments of these rivers, to assess the physico-chemical characteristics and water quality of Periyar and Chalakudy rivers and to estimate the dissolved nutrient flux through the Periyar and Chalakudy rivers into the receiving coastal waters. The granulometric characteristics as well as statistical parameters of the sediments of Periyar and Chalakudy rivers depend on the flow pattern controlled by the gradient of the terrain. Compared to Periyar, fluctuations in the dispersal of particles are more in Chalakudy river. In Periyar river, the P and Fe in bulk sediments show a positive correlation with C-org, while in Chalakudy river, both the elements are related to THM concentration. In general, C-org, Fe and P Shows an increasing trend downstream. In Periyar river, the P and Fe in bulk sediments show a positive correlation with C-org, while in Chalakudy river, both the elements are related to THM concentration. Among these two rivers, the pollution of water is several fold higher in Periyar river due to influx due to influx of considerable quantity of liquid and solid wastes of industrial/domestic/urban origin. Nutrient analysis reveals 2-3 times increase in N and P during monsoon season whereas SiO2-Si shows a decreasing trend.

Studies On The Dynamics And Water Quality Of The Muvattupuzha River In Relation To Effluent Discharge

The present study aims at the investigation of the 1ysico—chemical features of a tropical tidal river viz. we Muvattupuzha river. This river is expected to receive Jderate to heavy pollution loads in years to come, from we lone industrial unit, already set up on its bank. ilike other rivers, the geographical disposition of this Lver attains unique importance as regards its dynamics for 3) availability of natural runoff water from catchment :eas, which becomes very heavy during the monsoon season 3) regular steady availability of tail race water from a /dro—electric power station throughout the yearThe study also aims at arriving at the balancing forces of inherent self~purification of the river verses pollution loads from the factory effluents. The investigation period falls ahead of actual pollution occurrence and so the ambient conditions for a period of nearly one-and-a—half years were investigated, the analyses of which providflz to formulate the inter-relations of parameters varying with seasons. Tracer experiments were carried out which revealed the dispersion and dilution characteristics of the river in the vicinity of effluent outfall. The studv covers the trial—cum-capacity production periods of the factory during which effluents of various strength and quantity were discharged into the river; a few computed values arQ’cjmpgrQdl ... with the observed values. The base data along with the profiles of Oxygen sag equation have been utilized fb develop a mathematical model of the river with regard to its water quality

Wind and water power.

Explica las formas tradicionales de utilizar el viento y la fuerza hidráulica como fuente de energía. Se presentan soluciones y alternativas, y se hace énfasis en hacer conscientes a los jóvenes de las medidas que deben tomarse para asegurar que el mundo sigue siendo para las generaciones futuras.

Long-term memory problems in children and adolescents : assessment, intervention, and effective instruction. 'Problemas en la memoria a largo plazo en niños y adolescentes : evaluación, intervención y enseñanza efectiva'.

Incluye un índice alfabético

Explicit and implicit assessment of gender roles

Resumen tomado de la publicaci??n

Applications of hydrodynamic and water quality models to the Sau and Boadella Reservoirs

Applicaciò d'un model de hydrodinàmica i de qualitat de l'aigua als embassaments de Sau i Boadella

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

Response of organically managed grassland to available phosphorus and potassium in the soil and supplementary fertilization: field trials using grass-clover leys cut for silage

Effective use and recycling of manures together with occasional and judicious use of supplementary fertilizing materials forms the basis for management of phosphorus (P) and potassium (K) within organic farming systems. Replicated field trials were established at three sites across the UK to compare the supply of P and K to grass-clover swards cut for silage from a range of fertilizing materials, and to assess the usefulness of routine soil tests for P and K in organic farming systems. None of the fertilizing materials (farmyard manure, rock phosphate, Kali vinasse, volcanic tuff) significantly increased silage yields, nor was P offtake increased. However, farmyard manure and Kali vinasse proved effective sources of K to grass and clover in the short to medium term. Available P (measured as Olsen-P) showed no clear relationship with crop P offtake in these trials. In contrast, available K (measured by ammonium nitrate extraction) proved a useful measurement to predict K availability to crops and support K management decisions.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

Co-kriging when the soil and ancillary data are not co-located

Data such as digitized aerial photographs, electrical conductivity and yield are intensive and relatively inexpensive to obtain compared with collecting soil data by sampling. If such ancillary data are co-regionalized with the soil data they should be suitable for co-kriging. The latter requires that information for both variables is co-located at several locations; this is rarely so for soil and ancillary data. To solve this problem, we have derived values for the ancillary variable at the soil sampling locations by averaging the values within a radius of 15 m, taking the nearest-neighbour value, kriging over 5 m blocks, and punctual kriging. The cross-variograms from these data with clay content and also the pseudo cross-variogram were used to co-krige to validation points and the root mean squared errors (RMSEs) were calculated. In general, the data averaged within 15m and the punctually kriged values resulted in more accurate predictions.