The purpose of this study was to develop the instructional model and teaching material to change the middle school students'conceptions of electric current into the scientific ones and to investigate the effects of the model in actual classrooms. We identified the students' ideas and their misunderstanding about the concept of eIectic current through reviewing the literatures and our in this study. Based on the above results, we developed the instructional model and designed the teaching sequence and prepare the learning materials about the unit of the electric current in middle school Our instructional model was based on 'learning cycle' developed by Lawson, but the new stage called exploration through qualitative questions to elicit the students' own conceptions was inserted to it. To investigate the effects or the new teaching model, the pre- and post-test using the POE type were administered to experimental group(52 students) taught with learning cycles and control group(52 students) taught with traditional styles. The results are as follows; 1) The rates of correct. predictions was varying according to the kinds of problems. And the rates of the correct. reasons of their predictions were lower than those of the predictions. 2) The mean scores of the post-test of both groups were significantly higher than those of the pre-test. We could not find statistically significant difference in theme an score between experimental group and control group after implementation of the model. But the experimental group gained higher scores than those of the control group on two problem. Therefore, although we cannot show the prominent effects of our teaching model based on learning cycles, there are some effects of our model on changing the middle school students' conceptions of electric current.
When the aspect ratio of a magnet varies, the magnetic field in the magnet also varies. The critical current of a tape-shaped HTS wire varies with the direction and magnitude of applied magnetic field. Consequently when the aspect ration of a HTS magnet varies, the critical current of a HTS magnet varies. This paper shows the relation between the aspect ratio of a magnet and the energy and inductance of a HTS magnet. The critical current is also shown at various aspect ratio of the magnet. The length of the HTS wire, inner diameter of the magnet, and number of pancake are chosen to be variables which varies the shape of the magnet. For a HTS magnet consisting of pancake windings, calculation results show the number of pancake windings are the prime factor which varied the energy and inductance of the magnet. The inner diameter of the magnet varies the energy and inductance of the magnet a little.
Salt model building is a key process for successful subsalt imaging. In complex areas, Reverse Time Migration (RTM) provides better images than One‐way Wave Equation Migration (OWEM) or Kirchhoff Migration (KMIG). With a superior image, RTM can give improved solutions for delineation of salt geometry. The main obstacle in applying RTM to iterative salt model building is that RTM requires substantially more computing power than OWEM or KMIG. However, the cost of RTM can be reduced by localizing the imaging area. First, perform the redatuming of source and receiver wavefields to a certain depth just above the interested subsalt target area. Second, localize the image zone near the steep salt boundary. After then, update salt geometry iteratively using localized RTM (LRTM) images and an interactive salt modeling tool.
We present Ev-NeRF, a Neural Radiance Field derived from event data. While event cameras can measure subtle brightness changes in high frame rates, the measurements in low lighting or extreme motion suffer from significant domain discrepancy with complex noise. As a result, the performance of event-based vision tasks does not transfer to challenging environments, where the event cameras are expected to thrive over normal cameras. We find that the multi-view consistency of NeRF provides a powerful self-supervision signal for eliminating the spurious measurements and extracting the consistent underlying structure despite highly noisy input. Instead of posed images of the original NeRF, the input to Ev-NeRF is the event measurements accompanied by the movements of the sensors. Using the loss function that reflects the measurement model of the sensor, Ev-NeRF creates an integrated neural volume that summarizes the unstructured and sparse data points captured for about 2-4 seconds. The generated neural volume can also produce intensity images from novel views with reasonable depth estimates, which can serve as a high-quality input to various vision-based tasks. Our results show that Ev-NeRF achieves competitive performance for intensity image reconstruction under extreme noise conditions and high-dynamic-range imaging.
Supplementary Figure Legends 1-2 from Selenium Regulates Cyclooxygenase-2 and Extracellular Signal-Regulated Kinase Signaling Pathways by Activating AMP-Activated Protein Kinase in Colon Cancer Cells
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