923 resultados para Survival and adaptational strategies
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Glial cell line-derived neurotrophic factor (GDNF) promotes survival of midbrain dopaminergic neurons and motoneurons. Expression of GDNF mRNA in cerebellum raises the possibility that cells within this structure might also respond to GDNF. To examine potential trophic activities of GDNF, dissociated cultures of gestational day 18 rat cerebellum were grown for < or = 21 days in the presence of factor. GDNF increased Purkinje cell number without affecting the overall number of neurons or glial cells. A maximal response (50% above control) was elicited with GDNF at 1 pg/ml. Effects of GDNF on Purkinje cell differentiation were examined by scoring the morphologic maturation of cells in treated and control cultures. GDNF increased the proportion of Purkinje cells that displayed relatively mature morphologies, characterized by dendritic thickening and the development of spines and filopodial extensions. Morphologic maturation of the overall neuronal population was unaffected. In sum, our data indicate that GDNF is a potent survival and differentiation factor for Purkinje cells, the efferent neurons of cerebellar cortex. Together with its other actions, these findings raise the possibility that GDNF might be a critical trophic factor at multiple loci in neuronal circuits that control motor function.
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This work presents the main theories and models formulated with the purpose of offering a global overview on the acquisition of knowledge and skills involved in the initial development of expert competence. Setting from this background, we developed an empirical work whose main purpose is to define those factors in a complex learning situation such as chapter-sized in a knowledge-rich domain. The results obtained in a sample of Master students reveal that the several variables intervening, such as the qualitative organization of knowledge, intellectual ability, motivation, the deliberate use of strategies, and a rich learning environment, contribute in an independent way to provide an explanation for the acquired knowledge.
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As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.
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Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a “demographic inverse problem” and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.
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In the last few years, one of the lines of research of great interest in the field of emotional intelligence (EI) has been the analysis of the role of emotions in the educational context and, in particular, their influence on learning strategies. The aims of this study are to identify the existence of different EI profiles and to determine possible statistically significant differences in learning strategies between the obtained profiles. The study involved 1253 Chilean school students from 14 to 18 years (M = 15.10, SD = 1.30), who completed the Trait Meta-Mood Scale-24 (TMMS-24) and the Inventory of Learning and Study Strategies—High School version (LASSI-HS). Cluster analysis identified four EI profiles: a group of adolescents with a high EI profile, a group with predominance of low emotional attention and high repair skills, a group with high scores on attention and low scores on clarity and repair, and a final group of adolescents with low EI. Also, students in groups with high overall scores in EI and low attention and high repair emotional obtained higher scores on the different learning strategies; however, the effect size analysis showed that these differences had no empirical relevance.
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Due to changing internal and external conditions, the German arms industry is facing serious challenges as are its counterparts across Europe. The arms sales market in Germany is contracting – orders from the Bundeswehr are slowing down and the Federal Ministry of Defence is planning to change the way it cooperates with German arms producers. In addition, member states of NATO and the EU, major customers of German arms manufacturers, are reducing their defence spending, which will spell a fall in their orders for new armament and military equipment. In response to the new circumstances, the German arms industry is beginning to organise itself and increase its lobbying efforts in Berlin and, with the support of the federal government, it has been implementing specific measures in several areas. German companies are interested in securing new markets outside NATO and the EU and are also exploring opportunities for mergers and joint ventures with other German and foreign companies, and are seeking to create more conducive conditions for business on the EU and NATO markets.
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The first part of the paper addresses the theoretical background of economic growth and competitive advantage models. Although there is a whole set of research on a relationship between foreign direct investments and economic growth, little has been said on foreign direct investments and national competitive advantage with respect to economic growth of oil and gas abundant countries of Middle East and Central Asia. The second part of our paper introduces the framework of the so-called "Dubai Model" in detail and outlines the key components necessary to develop sustainable comparative advantage for the oil-rich economies. The third part proceeds with the methodology employed to measure the success of the "Dubai Model" in the UAE and in application to other regions. The last part brings the results and investigates the degree to which other oil and gas countries in the region (i.e. Saudi Arabia, Kuwait, Qatar, Iran) have adopted the so-called "Dubai Model". It also examines if the Dubai Model is being employed in the Eurasian (Central Asian) oil and gas regions of Kazakhstan, Azerbaijan, Turkmenistan and Uzbekistan. The objective is to gauge if the Eurasian economies are employing the traditional growth strategies of oil-rich non-OECD countries in managing their natural resources or are they adopting the newer non-traditional model of economic growth, such as the "Dubai Model."
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National Highway Traffic Safety Administration, Washington, D.C.
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