716 resultados para Lesson Planing
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CONTEXT 3β-hydroxysteroid dehydrogenase deficiency (3βHSD) is a rare disorder of sexual development and steroidogenesis. There are two isozymes of 3βHSD, HSD3B1 and HSD3B2. Human mutations are known for the HSD3B2 gene which is expressed in the gonads and the adrenals. Little is known about testis histology, fertility and malignancy risk. OBJECTIVE To describe the molecular genetics, the steroid biochemistry, the (immuno-)histochemistry and the clinical implications of a loss-of-function HSD3B2 mutation. METHODS Biochemical, genetic and immunohistochemical investigations on human biomaterials. RESULTS A 46,XY boy presented at birth with severe undervirilization of the external genitalia. Steroid profiling showed low steroid production for mineralocorticoids, glucocorticoids and sex steroids with typical precursor metabolites for HSD3B2 deficiency. The genetic analysis of the HSD3B2 gene revealed a homozygous c.687del27 deletion. At pubertal age, he showed some virilization of the external genitalia and some sex steroid metabolites appeared likely through conversion of precursors secreted by the testis and converted by unaffected HSD3B1 in peripheral tissues. However, he also developed enlarged breasts through production of estrogens in the periphery. Testis histology in late puberty revealed primarily a Sertoli-cell-only pattern and only few tubules with arrested spermatogenesis, presence of few Leydig cells in stroma, but no neoplastic changes. CONCLUSIONS The testis with HSD3B2 deficiency due to the c.687del27 deletion does not express the defective protein. This patient is unlikely to be fertile and his risk for gonadal malignancy is low. Further studies are needed to obtain firm knowledge on malignancy risk for gonads harboring defects of androgen biosynthesis.
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PREDICT POTENTIAL DISTRIBUTION. Spatial and temporal evolution of the species under different climate scenarios. Generation of habitat suitability models (HSM) high degree of uncertainty and limitations. The importance of their validation has been stressed. In this work we discuss the present potential distribution of P. sylvestris and P. nigra in the Iberian Peninsula by using MaxEnt, and evaluate the influence of the different environmental variables. Our intention is to select a set of environmental variables that explains better their current distribution, to achieve the most accurate and reliable models. Then we project them to the past climatic conditions (21 to 0 kyrs BP), to evaluate the outputs with existing palaeo-ecological data.
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Software testing is a key aspect of software reliability and quality assurance in a context where software development constantly has to overcome mammoth challenges in a continuously changing environment. One of the characteristics of software testing is that it has a large intellectual capital component and can thus benefit from the use of the experience gained from past projects. Software testing can, then, potentially benefit from solutions provided by the knowledge management discipline. There are in fact a number of proposals concerning effective knowledge management related to several software engineering processes. Objective: We defend the use of a lesson learned system for software testing. The reason is that such a system is an effective knowledge management resource enabling testers and managers to take advantage of the experience locked away in the brains of the testers. To do this, the experience has to be gathered, disseminated and reused. Method: After analyzing the proposals for managing software testing experience, significant weaknesses have been detected in the current systems of this type. The architectural model proposed here for lesson learned systems is designed to try to avoid these weaknesses. This model (i) defines the structure of the software testing lessons learned; (ii) sets up procedures for lesson learned management; and (iii) supports the design of software tools to manage the lessons learned. Results: A different approach, based on the management of the lessons learned that software testing engineers gather from everyday experience, with two basic goals: usefulness and applicability. Conclusion: The architectural model proposed here lays the groundwork to overcome the obstacles to sharing and reusing experience gained in the software testing and test management. As such, it provides guidance for developing software testing lesson learned systems.
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This article presents a mathematical method for producing hard-chine ship hulls based on a set of numerical parameters that are directly related to the geometric features of the hull and uniquely define a hull form for this type of ship. The term planing hull is used generically to describe the majority of hard-chine boats being built today. This article is focused on unstepped, single-chine hulls. B-spline curves and surfaces were combined with constraints on the significant ship curves to produce the final hull design. The hard-chine hull geometry was modeled by decomposing the surface geometry into boundary curves, which were defined by design constraints or parameters. In planing hull design, these control curves are the center, chine, and sheer lines as well as their geometric features including position, slope, and, in the case of the chine, enclosed area and centroid. These geometric parameters have physical, hydrodynamic, and stability implications from the design point of view. The proposed method uses two-dimensional orthogonal projections of the control curves and then produces three-dimensional (3-D) definitions using B-spline fitting of the 3-D data points. The fitting considers maximum deviation from the curve to the data points and is based on an original selection of the parameterization. A net of B-spline curves (stations) is then created to match the previously defined 3-D boundaries. A final set of lofting surfaces of the previous B-spline curves produces the hull surface.
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Tema 2. Actividad voluntaria nº 2.
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Tema 3. Actividad evaluable nº 2.
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Tema 4. Actividad voluntaria nº 2.
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Tema 5. Actividad voluntaria nº 3.
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Tema 6: Diseño del entorno visual. Actividad propuesta no. 3.
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Tema 7: Riesgos para lesiones oculares y visuales. Actividad propuesta nº 4.
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Tema 8: Pantallas de visualización de datos. Actividad voluntaria nº 5.
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Tema 9: Visión y conducción. Actividad obligatoria nº 5.
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Tema 10: visión y deporte. Actividad voluntaria 6.