Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Physical and numerical modeling of horizontal gas-hydrate wells

Methane hydrate, which is usually found under deep seabed or permafrost zones, is a potential energy resource for future years. Depressurization of horizontal wells bored in methane hydrate layer is considered as one possible method for hydrate dissociation and methane extraction from the hosting soil. Since hydrate is likely to behave as a bonding material to sandy soils, supported well construction is necessary to avoid well-collapse due to the loss of the apparent cohesion during depressurization. This paper describes both physical and numerical modeling of such horizontal support wells. The experimental part involves depressurization of small well models in a large pressure cell, while the numerical part simulates the corresponding problem. While the experiment models simulate only gas saturated initial conditions, the numerical analysis simulates both gas-saturated and more realistic water-saturated conditions based on effective stress coupled flow-deformation formulation of these three phases. © 2006 Taylor & Francis Group.

Estudio del proceso formativo que siguen un grupo de docentes para realizar un diagnóstico de necesidades en deporte escolar

[Es] En este artículo se relata el proceso formativo que han seguido tres profesores de educación física coordinadores de deporte escolar en el curso 2004/2005. En éste curso se realizó un diagnóstico en tres ikastolas de Bizkaia para lo que se crearon diferentes grupos de trabajo en los que se dieron procesos formativos a distintos niveles. Las personas que posibilitaron el desarrollo de la investigación fueron profesores de educación física coordinadores de deporte escolar. Éstos, a través de la investigación-acción, han iniciado su formación como investigadores en el propio proceso de realización del diagnóstico. La formación que han recibido ha partido de considerarles objeto y sujeto de la investigación y de formales en la elaboración y utilización de técnicas adecuadas a la realización de procesos de investigación de naturaleza cualitativa.

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).