57 resultados para learning and teaching processes


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Three extended families live around a lake. One family are rice farmers, the second family are vegetable farmers, and the third are a family of livestock herders. All of them depend on the use of lake water for their production, and all of them need large quantities of water. All are dependent on the use of the lake water to secure their livelihood. In the game, the families are represented by their councils of elders. Each of the councils has to find means and ways to increase production in order to keep up with the growth of its family and their demands. This puts more and more pressure on the water resources, increasing the risk of overuse. Conflicts over water are about to emerge between the families. Each council of elders must try to pursue its families interests, while at the same time preventing excessive pressure on the water resources. Once a council of elders is no longer able to meet the needs of its family, it is excluded from the game. Will the parties cooperate or compete? To face the challenge of balancing economic well-being, sustainable resource management, and individual and collective interests, the three parties have a set of options for action at hand. These include power play to safeguard their own interests, communication and cooperation to negotiate with neighbours, and searching for alternatives to reduce pressure on existing water resources. During the game the players can experience how tensions may arise, increase and finally escalate. They realise what impact power play has and how alliances form, and the importance of trust-building measures, consensus and cooperation. From the insights gained, important conflict prevention and mitigation measures are derived in a debriefing session. The game is facilitated by a moderator, and lasts for 3-4 hours. Aim of the game: Each family pursues the objective of serving its own interests and securing its position through appropriate strategies and skilful negotiation, while at the same time optimising use of the water resources in a way that prevents their degradation. The end of the game is open. While the game may end by one or two families dropping out because they can no longer secure their subsistence, it is also possible that the three families succeed in creating a situation that allows them to meet their own needs as well as the requirements for sustainable water use in the long term. Learning objectives The game demonstrates how tension builds up, increases, and finally escalates; it shows how power positions work and alliances are formed; and it enables the players to experience the great significance of mutual agreement and cooperation. During the game and particularly during the debriefing and evaluation session it is important to link experiences made during the game to the players’ real-life experiences, and to discuss these links in the group. The resulting insights will provide a basis for deducing important conflict prevention and transformation measures.

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Copper, zinc, manganese, iron, nickel and molybdenum are essential micronutrients for plants. However, when present in excess they may damage the plant or decrease the quality of harvested plant products. Some other heavy metals such as cadmium, lead or mercury are not needed by plants and represent pollutants. The uptake into the roots, the loading into the xylem, the acropetal transport to the shoot with the transpiration stream and the further redistribution in the phloem are crucial for the distribution in aerial plant parts. This review is focused on long-distance transport of heavy metals via xylem and phloem and on interactions between the two transport systems. Phloem transport is the basis for the redistribution within the shoot and for the accumulation in fruits and seeds. Solutes may be transferred from the xylem to the phloem (e.g., in the small bundles in stems of cereals, in minor leaf veins). Nickel is highly phloem-mobile and directed to expanding plant parts. Zinc and to a lesser degree also cadmium are also mobile in the phloem and accumulate in meristems (root tips, shoot apex, axillary buds). Iron and manganese are characterized by poor phloem mobility and are retained in older leaves.

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Foliar samples were harvested from two oaks, a beech, and a yew at the same site in order to trace the development of the leaves over an entire vegetation season. Cellulose yield and stable isotopic compositions (δ13C, δ18O, and δD) were analyzed on leaf cellulose. All parameters unequivocally define a juvenile and a mature period in the foliar expansion of each species. The accompanying shifts of the δ13C-values are in agreement with the transition from remobilized carbohydrates (juvenile period), to current photosynthates (mature phase). While the opponent seasonal trends of δ18O of blade and vein cellulose are in perfect agreement with the state-of-art mechanistic understanding, the lack of this discrepancy for δD, documented for the first time, is unexpected. For example, the offset range of 18 permil (oak veins) to 57 permil (oak blades) in δD may represent a process driven shift from autotrophic to heterotrophic processes. The shared pattern between blade and vein found for both oak and beech suggests an overwhelming metabolic isotope effect on δD that might be accompanied by proton transfer linked to the Calvin-cycle. These results provide strong evidence that hydrogen and oxygen are under different biochemical controls even at the leaf level.

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Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

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Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

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Conversation is central to the process of organizational learning and change. Drawing on the notion of reflective conversation, we describe an action research project, "learning through listening" in Omega, a residential healthcare organization. In this project, service users, staff, members of management committees, trustees, managers, and central office staff participated in listening to each other and in working together towards building capacity for creating their own vision of how the organization could move into the future, according to its values and ethos. In doing so they developed ways of engaging in reflective conversation that enabled progress towards a strategic direction.

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The purpose of this review is to investigate how transcranial direct current stimulation(tDCS)can modulate implicit motor sequence learning and consolidation. So far, most of the studies have focused on the modulating effect of tDCS for explicit motor learning. Here, we focus explicitly on implicit motor sequence learning and consolidation in order to improve our understanding about the potential of tDCS to affect this kind of unconscious learning. Specifically, we concentrate on studies with the serial reaction time task (SRTT), the classical paradigm for measuring implicit motor sequence learning. The influence of tDCS has been investigated for the primary motor cortex, the premotor cortex, the prefrontal cortex, and the cerebellum. The results indicate that tDCS above the primary motor cortex gives raise to the most consistent modulating effects for both implicit motor sequence learning and consolidation.

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The aim of this paper is to provide a review of general processes related to plasma sources, their transport, energization, and losses in the planetary magnetospheres. We provide background information as well as the most up-to-date knowledge of the comparative studies of planetary magnetospheres, with a focus on the plasma supply to each region of the magnetospheres. This review also includes the basic equations and modeling methods commonly used to simulate the plasma sources of the planetary magnetospheres. In this paper, we will describe basic and common processes related to plasma supply to each region of the planetary magnetospheres in our solar system. First, we will describe source processes in Sect. 1. Then the transport and energization processes to supply those source plasmas to various regions of the magnetosphere are described in Sect. 2. Loss processes are also important to understand the plasma population in the magnetosphere and Sect. 3 is dedicated to the explanation of the loss processes. In Sect. 4, we also briefly summarize the basic equations and modeling methods with a focus on plasma supply processes for planetary magnetospheres.

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As a complement to experimental and theoretical approaches, numerical modeling has become an important component to study asteroid collisions and impact processes. In the last decade, there have been significant advances in both computational resources and numerical methods. We discuss the present state-of-the-art numerical methods and material models used in "shock physics codes" to simulate impacts and collisions and give some examples of those codes. Finally, recent modeling studies are presented, focussing on the effects of various material properties and target structures on the outcome of a collision.

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Western honey bees (Apis mellifera) face an increasing number of challenges that in recent years have led to significant economic effects on apiculture, with attendant consequences for agriculture. Nosemosis is a fungal infection of honey bees caused by either Nosema apis or N. ceranae. The putative greater virulence of N. ceranae has spurred interest in understanding how it differs from N. apis. Little is known of effects of N. apis or N. ceranae on honey bee learning and memory. Following a Pavlovian model that relies on the proboscis extension reflex, we compared acquisition learning and long-term memory recall of uninfected (control) honey bees versus those inoculated with N. apis, N. ceranae, or both. We also tested whether spore intensity was associated with variation in learning and memory. Neither learning nor memory differed among treatments. There was no evidence of a relationship between spore intensity and learning, and only limited evidence of a negative effect on memory; this occurred only in the co-inoculation treatment. Our results suggest that if Nosema spp. are contributing to unusually high colony losses in recent years, the mechanism by which they may affect honey bees is probably not related to effects on learning or memory, at least as assessed by the proboscis extension reflex.

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Variations in barium (Ba) stable isotope abundances measured in low and high temperature environments have recently received increasing attention. The actual processes controlling Ba isotope fractionation, however, remain mostly elusive. In this study, we present the first experimental approach to quantify the contribution of diffusion and adsorption on mass- dependent Ba isotope fractionation during transport of aqueous Ba2+ ions through a porous medium. Experiments have been carried out in which a BaCl2 solution of known isotopic composition diffused through u-shaped glass tubes filled with silica hydrogel at 10 C and 25 C for up to 201 days. The diffused Ba was highly fractionated by up to -2.15‰ in d137/134Ba, despite the low relative difference in atomic mass. The time-dependent isotope fractionation can be successfully reproduced by a diffusive transport model accounting for mass-dependent differences in the effective diffusivities of the Ba isotope species (D137Ba/D134Ba = (m134/m137)^b). Values of b extracted from the transport model were in the range of 0.010–0.011. Independently conducted batch experiments revealed that adsorption of Ba onto the surface of silica hydrogel favoured the heavier Ba isotopes (a = 1.00015 ± 0.00008). The contribution of adsorption on the overall isotope fractionation in the diffusion experiments, however, was found to be small. Our results contribute to the understanding of Ba isotope fractionation pro- cesses, which is crucial for interpreting natural isotope variations and the assessment of Ba isotope ratios as geochemical proxies.