25 resultados para Design based learning

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

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Quantitative data obtained by means of design-based stereology can add valuable information to studies performed on a diversity of organs, in particular when correlated to functional/physiological and biochemical data. Design-based stereology is based on a sound statistical background and can be used to generate accurate data which are in line with principles of good laboratory practice. In addition, by adjusting the study design an appropriate precision can be achieved to find relevant differences between groups. For the success of the stereological assessment detailed planning is necessary. In this review we focus on common pitfalls encountered during stereological assessment. An exemplary workflow is included, and based on authentic examples, we illustrate a number of sampling principles which can be implemented to obtain properly sampled tissue blocks for various purposes.

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The assumption that social skills are necessary ingredients of collaborative learning is well established but rarely empirically tested. In addition, most theories on collaborative learning focus on social skills only at the personal level, while the social skill configurations within a learning group might be of equal importance. Using the integrative framework, this study investigates which social skills at the personal level and at the group level are predictive of task-related e-mail communication, satisfaction with performance and perceived quality of collaboration. Data collection took place in a technology-enhanced long-term project-based learning setting for pre-service teachers. For data collection, two questionnaires were used, one at the beginning and one at the end of the learning cycle which lasted 3 months. During the project phase, the e-mail communication between group members was captured as well. The investigation of 60 project groups (N = 155 for the questionnaires; group size: two or three students) and 33 groups for the e-mail communication (N = 83) revealed that personal social skills played only a minor role compared to group level configurations of social skills in predicting satisfaction with performance, perceived quality of collaboration and communication behaviour. Members from groups that showed a high and/or homogeneous configuration of specific social skills (e.g., cooperation/compromising, leadership) usually were more satisfied and saw their group as more efficient than members from groups with a low and/or heterogeneous configuration of skills.

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Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

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n learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.

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Social learning approaches have become a prominent focus in studies related to sustainable agriculture. In order to better understand the potential of social learning for more sustainable development, the present study assessed the processes, effects and facilitating elements of interaction related to social learning in the context of Swiss soil protection and the innovative ‘From Farmer - To Farmer’ project. The study reveals that social learning contributes to fundamental transformations of patterns of interactions. However, the study also demonstrates that a learning-oriented understanding of sustainable development implies including analysis of the institutional environments in which the organizations of the individual representatives of face-to-face-based social learning processes are operating. This has shown to be a decisive element when face-to-face-based learning processes of the organisations’ representatives are translated into organisational learning. Moreover, the study revealed that this was achieved not directly through formalisation of new lines of institutionalised cooperation but by establishing links in a ‘boundary space’ trying out new forms of collaboration, aiming at social learning and co-production of knowledge. It is argued that further research on social learning processes should give greater emphasis to this intermediary level of ‘boundary spaces’.

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The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While jobshadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.

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A compact adjustable focusing system for a 2 MeV H- RFQ Linac is designed, constructed and tested based on four permanent magnet quadrupoles (PMQ). A PMQ model is realised using finite element simulations, providing an integrated field gradient of 2.35 T with a maximal field gradient of 57 T/m. A prototype is constructed and the magnetic field is measured, demonstrating good agreement with the simulation. Particle track simulations provide initial values for the quadrupole positions. Accordingly, four PMQs are constructed and assembled on the beam line, their positions are then tuned to obtain a minimal beam spot size of (1.2 x 2.2) mm^2 on target. This paper describes an adjustable PMQ beam line for an external ion beam. The novel compact design based on commercially available NdFeB magnets allows high flexibility for ion beam applications.

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The impact of nanoparticles (NPs) in medicine and biology has increased rapidly in recent years. Gold NPs have advantageous properties such as chemical stability, high electron density and affinity to biomolecules, making them very promising candidates as drug carriers and diagnostic tools. However, diverse studies on the toxicity of gold NPs have reported contradictory results. To address this issue, a triple cell co-culture model simulating the alveolar lung epithelium was used and exposed at the air-liquid interface. The cell cultures were exposed to characterized aerosols with 15 nm gold particles (61 ng Au/cm2 and 561 ng Au/cm2 deposition) and incubated for 4 h and 24 h. Experiments were repeated six times. The mRNA induction of pro-inflammatory (TNFalpha, IL-8, iNOS) and oxidative stress markers (HO-1, SOD2) was measured, as well as protein induction of pro- and anti-inflammatory cytokines (IL-1, IL-2, IL-4, IL-6, IL-8, IL-10, GM-CSF, TNFalpha, INFgamma). A pre-stimulation with lipopolysaccharide (LPS) was performed to further study the effects of particles under inflammatory conditions. Particle deposition and particle uptake by cells were analyzed by transmission electron microscopy and design-based stereology. A homogeneous deposition was revealed, and particles were found to enter all cell types. No mRNA induction due to particles was observed for all markers. The cell culture system was sensitive to LPS but gold particles did not cause any synergistic or suppressive effects. With this experimental setup, reflecting the physiological conditions more precisely, no adverse effects from gold NPs were observed. However, chronic studies under in vivo conditions are needed to entirely exclude adverse effects.

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Glycan-binding antibodies form a significant subpopulation of both natural and acquired antibodies and play an important role in various immune processes. They are for example involved in innate immune responses, cancer, autoimmune diseases, and neurological disorders. In the present study, a microsphere-based flow-cytometric immunoassay (suspension array) was applied for multiplexed detection of glycan-binding antibodies in human serum. Several approaches for immobilization of glycoconjugates onto commercially available fluorescent microspheres were compared, and as the result, the design based on coupling of end-biotinylated glycopolymers has been selected. This method requires only minute amounts of glycans, similar to a printed glycan microarray. The resulting glyco-microspheres were used for detection of IgM and IgG antibodies directed against ABO blood group antigens. The possibility of multiplexing this assay was demonstrated with mixtures of microspheres modified with six different ABO related glycans. Multiplexed detection of anti-glycan IgM and IgG correlated well with singleplex assays (Pearson's correlation coefficient r = 0.95-0.99 for sera of different blood groups). The suspension array in singleplex format for A/B trisaccharide, H(di) and Le(x) microspheres corresponded well to the standard ELISA (r > 0.94). Therefore, the described method is promising for rapid, sensitive, and reproducible detection of anti-glycan antibodies in a multiplexed format.

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Content-centric networking is a novel paradigm for the Future Internet that treats content as a first class citizen. This paper argues that content-centric networking should be generalized towards a service-centric networking scheme. We propose a service-centric networking design based on an object-oriented approach, in which content and services are considered objects. We show implementation architectures for example services and how these can benefit from service-oriented networking.

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Hepatocyte growth factor (HGF) is involved in development and regeneration of the lungs. Human HGF, which was expressed specifically by alveolar epithelial type II cells after gene transfer, attenuated the bleomycin-induced pulmonary fibrosis in an animal model. As there are also regions that appear morphologically unaffected in fibrosis, the effects of this gene transfer to normal lungs is of interest. In vitro studies showed that HGF inhibits the formation of the basal lamina by cultured alveolar epithelial cells. Thus we hypothesized that, in the healthy lung, cell-specific expression of HGF induces a remodeling within septal walls. Electroporation of a plasmid of human HGF gene controlled by the surfactant protein C promoter was applied for targeted gene transfer. Using design-based stereology at light and electron microscopic level, structural alterations were analyzed and compared with a control group. HGF gene transfer increased the volume of distal air spaces, as well as the surface area of the alveolar epithelium. The volume of septal walls, as well as the number of alveoli, was unchanged. Volumes per lung of collagen and elastic fibers were unaltered, but a marked reduction of the volume of residual extracellular matrix (all components other than collagen and elastic fibers) and interstitial cells was found. A correlation between the volumes of residual extracellular matrix and distal air spaces, as well as total surface area of alveolar epithelium, could be established. Cell-specific expression of HGF leads to a remodeling of the connective tissue within the septal walls in the healthy lung, which is associated with more pronounced stretching of distal air spaces at a given hydrostatic pressure during instillation fixation.

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Lung stereology has a long and successful tradition. From mice to men, the application of new stereological methods at several levels (alveoli, parenchymal cells, organelles, proteins) has led to new insights into normal lung architecture, parenchymal remodelling in emphysema-like pathology, alveolar type II cell hyperplasia and hypertrophy and intracellular surfactant alterations as well as distribution of surfactant proteins. The Euler number of the network of alveolar openings, estimated using physical disectors at the light microscopic level, is an unbiased and direct estimate of alveolar number. Surfactant-producing alveolar type II cells can be counted and sampled for local size estimation with physical disectors at a high magnification light microscopic level. The number of their surfactant storage organelles, lamellar bodies, can be estimated using physical disectors at the EM level. By immunoelectron microscopy, surfactant protein distribution can be analysed with the relative labelling index. Together with the well-established classical stereological methods, these design-based methods now allow for a complete quantitative phenotype analysis in lung development and disease, including the structural characterization of gene-manipulated mice, at the light and electron microscopic level.