Dynamic Resource Allocation with Integrated Reinforcement Learning for a D2D-Enabled LTE-A Network with Access to Unlicensed Band

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Alia Asheralieva

2016-01-01

Full Text Available We propose a dynamic resource allocation algorithm for device-to-device (D2D communication underlying a Long Term Evolution Advanced (LTE-A network with reinforcement learning (RL applied for unlicensed channel allocation. In a considered system, the inband and outband resources are assigned by the LTE evolved NodeB (eNB to different device pairs to maximize the network utility subject to the target signal-to-interference-and-noise ratio (SINR constraints. Because of the absence of an established control link between the unlicensed and cellular radio interfaces, the eNB cannot acquire any information about the quality and availability of unlicensed channels. As a result, a considered problem becomes a stochastic optimization problem that can be dealt with by deploying a learning theory (to estimate the random unlicensed channel environment. Consequently, we formulate the outband D2D access as a dynamic single-player game in which the player (eNB estimates its possible strategy and expected utility for all of its actions based only on its own local observations using a joint utility and strategy estimation based reinforcement learning (JUSTE-RL with regret algorithm. A proposed approach for resource allocation demonstrates near-optimal performance after a small number of RL iterations and surpasses the other comparable methods in terms of energy efficiency and throughput maximization.

The depth estimation of 3D face from single 2D picture based on manifold learning constraints

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Li, Xia; Yang, Yang; Xiong, Hailiang; Liu, Yunxia

2018-04-01

The estimation of depth is virtual important in 3D face reconstruction. In this paper, we propose a t-SNE based on manifold learning constraints and introduce K-means method to divide the original database into several subset, and the selected optimal subset to reconstruct the 3D face depth information can greatly reduce the computational complexity. Firstly, we carry out the t-SNE operation to reduce the key feature points in each 3D face model from 1×249 to 1×2. Secondly, the K-means method is applied to divide the training 3D database into several subset. Thirdly, the Euclidean distance between the 83 feature points of the image to be estimated and the feature point information before the dimension reduction of each cluster center is calculated. The category of the image to be estimated is judged according to the minimum Euclidean distance. Finally, the method Kong D will be applied only in the optimal subset to estimate the depth value information of 83 feature points of 2D face images. Achieving the final depth estimation results, thus the computational complexity is greatly reduced. Compared with the traditional traversal search estimation method, although the proposed method error rate is reduced by 0.49, the number of searches decreases with the change of the category. In order to validate our approach, we use a public database to mimic the task of estimating the depth of face images from 2D images. The average number of searches decreased by 83.19%.

3D/2D model-to-image registration by imitation learning for cardiac procedures.

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Toth, Daniel; Miao, Shun; Kurzendorfer, Tanja; Rinaldi, Christopher A; Liao, Rui; Mansi, Tommaso; Rhode, Kawal; Mountney, Peter

2018-05-12

In cardiac interventions, such as cardiac resynchronization therapy (CRT), image guidance can be enhanced by involving preoperative models. Multimodality 3D/2D registration for image guidance, however, remains a significant research challenge for fundamentally different image data, i.e., MR to X-ray. Registration methods must account for differences in intensity, contrast levels, resolution, dimensionality, field of view. Furthermore, same anatomical structures may not be visible in both modalities. Current approaches have focused on developing modality-specific solutions for individual clinical use cases, by introducing constraints, or identifying cross-modality information manually. Machine learning approaches have the potential to create more general registration platforms. However, training image to image methods would require large multimodal datasets and ground truth for each target application. This paper proposes a model-to-image registration approach instead, because it is common in image-guided interventions to create anatomical models for diagnosis, planning or guidance prior to procedures. An imitation learning-based method, trained on 702 datasets, is used to register preoperative models to intraoperative X-ray images. Accuracy is demonstrated on cardiac models and artificial X-rays generated from CTs. The registration error was [Formula: see text] on 1000 test cases, superior to that of manual ([Formula: see text]) and gradient-based ([Formula: see text]) registration. High robustness is shown in 19 clinical CRT cases. Besides the proposed methods feasibility in a clinical environment, evaluation has shown good accuracy and high robustness indicating that it could be applied in image-guided interventions.

D2.1 - An EA Active, Problem Based Learning Methodology - EAtrain2

DEFF Research Database (Denmark)

Ryberg, Thomas; Georgsen, Marianne; Buus, Lillian

This deliverable reports on the work undertaken in work package 2 with the key objective to develop a learning methodology for web 2.0 mediated Enterprise Architecture (EA) learning building on a problem based learning (PBL) approach. The deliverable reports not only on the methodology but also...... on the activities leading to its development (literature review, workshops, etc.) and on further outcomes of this work relevant to the platform specification and pilot courses preparation....

Memory and visual search in naturalistic 2D and 3D environments.

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Li, Chia-Ling; Aivar, M Pilar; Kit, Dmitry M; Tong, Matthew H; Hayhoe, Mary M

2016-06-01

The role of memory in guiding attention allocation in daily behaviors is not well understood. In experiments with two-dimensional (2D) images, there is mixed evidence about the importance of memory. Because the stimulus context in laboratory experiments and daily behaviors differs extensively, we investigated the role of memory in visual search, in both two-dimensional (2D) and three-dimensional (3D) environments. A 3D immersive virtual apartment composed of two rooms was created, and a parallel 2D visual search experiment composed of snapshots from the 3D environment was developed. Eye movements were tracked in both experiments. Repeated searches for geometric objects were performed to assess the role of spatial memory. Subsequently, subjects searched for realistic context objects to test for incidental learning. Our results show that subjects learned the room-target associations in 3D but less so in 2D. Gaze was increasingly restricted to relevant regions of the room with experience in both settings. Search for local contextual objects, however, was not facilitated by early experience. Incidental fixations to context objects do not necessarily benefit search performance. Together, these results demonstrate that memory for global aspects of the environment guides search by restricting allocation of attention to likely regions, whereas task relevance determines what is learned from the active search experience. Behaviors in 2D and 3D environments are comparable, although there is greater use of memory in 3D.

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

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Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

2018-01-01

This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and

Learn Unity for 2D game development

CERN Document Server

Thorn, Alan

2013-01-01

The only Unity book specifically covering 2D game development Written by Alan Thorn, experience game developer and author of seven books on game programming Hands-on examples of all major aspects of 2D game development using Unity

Tensor manifold-based extreme learning machine for 2.5-D face recognition

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Chong, Lee Ying; Ong, Thian Song; Teoh, Andrew Beng Jin

2018-01-01

We explore the use of the Gabor regional covariance matrix (GRCM), a flexible matrix-based descriptor that embeds the Gabor features in the covariance matrix, as a 2.5-D facial descriptor and an effective means of feature fusion for 2.5-D face recognition problems. Despite its promise, matching is not a trivial problem for GRCM since it is a special instance of a symmetric positive definite (SPD) matrix that resides in non-Euclidean space as a tensor manifold. This implies that GRCM is incompatible with the existing vector-based classifiers and distance matchers. Therefore, we bridge the gap of the GRCM and extreme learning machine (ELM), a vector-based classifier for the 2.5-D face recognition problem. We put forward a tensor manifold-compliant ELM and its two variants by embedding the SPD matrix randomly into reproducing kernel Hilbert space (RKHS) via tensor kernel functions. To preserve the pair-wise distance of the embedded data, we orthogonalize the random-embedded SPD matrix. Hence, classification can be done using a simple ridge regressor, an integrated component of ELM, on the random orthogonal RKHS. Experimental results show that our proposed method is able to improve the recognition performance and further enhance the computational efficiency.

ROOFN3D: DEEP LEARNING TRAINING DATA FOR 3D BUILDING RECONSTRUCTION

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A. Wichmann

2018-05-01

Full Text Available Machine learning methods have gained in importance through the latest development of artificial intelligence and computer hardware. Particularly approaches based on deep learning have shown that they are able to provide state-of-the-art results for various tasks. However, the direct application of deep learning methods to improve the results of 3D building reconstruction is often not possible due, for example, to the lack of suitable training data. To address this issue, we present RoofN3D which provides a new 3D point cloud training dataset that can be used to train machine learning models for different tasks in the context of 3D building reconstruction. It can be used, among others, to train semantic segmentation networks or to learn the structure of buildings and the geometric model construction. Further details about RoofN3D and the developed data preparation framework, which enables the automatic derivation of training data, are described in this paper. Furthermore, we provide an overview of other available 3D point cloud training data and approaches from current literature in which solutions for the application of deep learning to unstructured and not gridded 3D point cloud data are presented.

Digital Cadavers: Online 2D Learning Resources Enhance Student Learning in Practical Head and Neck Anatomy within Dental Programs

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Mahmoud M. Bakr

2016-01-01

Full Text Available Head and neck anatomy provides core concepts within preclinical dental curricula. Increased student numbers, reduced curricula time, and restricted access to laboratory-based human resources have increased technology enhanced learning approaches to support student learning. Potential advantages include cost-effectiveness, off-campus access, and self-directed review or mastery opportunities for students. This study investigated successful student learning within a first-year head and neck anatomy course at the School of Dentistry and Oral Health, Griffith University, Australia, taught by the same teaching team, between 2010 and 2015. Student learning success was compared, for cohorts before and after implementation of a supplementary, purpose-designed online digital library and quiz bank. Success of these online resources was confirmed using overall students’ performance within the course assessment tasks and Student Evaluation of Course surveys and online access data. Engagement with these supplementary 2D online resources, targeted at improving laboratory study, was positively evaluated by students (mean 85% and significantly increased their laboratory grades (mean difference 6%, P<0.027, despite being assessed using cadaveric resources. Written assessments in final exams were not significantly improved. Expanded use of supplementary online resources is planned to support student learning and success in head and neck anatomy, given the success of this intervention.

Neurochemical Correlates of Accumbal Dopamine D2 and Amygdaloid 5-HT1B Receptor Densities on Observational Learning of Aggression

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Suzuki, Hideo; Lucas, Louis R.

2015-01-01

Social learning theory postulates that individuals learn to engage in aggressive behavior through observing an aggressive social model. Prior studies have shown that repeatedly observing aggression, also called “chronic passive exposure to aggression,” changes accumbal dopamine D2 receptor (D2R) and amygdaloid 5-HT1B receptor (5-HT1BR) densities in observers. But, the association between these outcomes remains unknown. Thus, our study used a rat paradigm to comprehensively examine the linkage between aggression, D2R density in the nucleus accumbens core (AcbC) and shell (AcbSh), and 5-HT1BR density in the medial (MeA), basomedial (BMA), and basolateral (BLA) amygdala following chronic passive exposure to aggression. Male Sprague-Dawley rats (N = 72) were passively exposed to either aggression or non-aggression acutely (1 day) or chronically (23 days). When observer rats were exposed to aggression chronically, they showed increased aggressive behavior and reduced D2R density in the bilateral AcbSh. On the other hand, exposure to aggression, regardless of exposure length, increased 5-HT1BR density in the bilateral BLA. Finally, low D2R in the AcbSh significantly interacted with high 5-HT1BR density in the BLA in predicting high levels of aggression in observer rats. Our results advance our understanding of the neurobiological mechanisms for observational learning of aggression, highlighting that dopamine-serotonin interaction, or AcbSh-BLA interaction, may contribute to a risk factor for aggression in observers who chronically witness aggressive interactions. PMID:25650085

3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

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Montoya, J C; Li, Y; Strother, C; Chen, G-H

2018-05-01

Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral angiograms from a single contrast-enhanced C-arm conebeam CT acquisition in order to reduce image artifacts and radiation dose. A set of 105 3D rotational angiography examinations were randomly selected from an internal data base. All were acquired using a clinical system in conjunction with a standard injection protocol. More than 150 million labeled voxels from 35 subjects were used for training. A deep convolutional neural network was trained to classify each image voxel into 3 tissue types (vasculature, bone, and soft tissue). The trained deep learning angiography model was then applied for tissue classification into a validation cohort of 8 subjects and a final testing cohort of the remaining 62 subjects. The final vasculature tissue class was used to generate the 3D deep learning angiography images. To quantify the generalization error of the trained model, we calculated the accuracy, sensitivity, precision, and Dice similarity coefficients for vasculature classification in relevant anatomy. The 3D deep learning angiography and clinical 3D rotational angiography images were subjected to a qualitative assessment for the presence of intersweep motion artifacts. Vasculature classification accuracy and 95% CI in the testing dataset were 98.7% (98.3%-99.1%). No residual signal from osseous structures was observed for any 3D deep learning angiography testing cases except for small regions in the otic capsule and nasal cavity compared with 37% (23/62) of the 3D rotational angiographies. Deep learning angiography accurately recreated the vascular anatomy of the 3D rotational angiography reconstructions without a mask. Deep learning angiography reduced misregistration artifacts induced by intersweep motion, and it reduced radiation exposure

Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM

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Yi Jin

2014-01-01

Full Text Available In recent years, 3D face recognition has attracted increasing attention from worldwide researchers. Rather than homogeneous face data, more and more applications require flexible input face data nowadays. In this paper, we propose a new approach for cross-modality 2D-3D face recognition (FR, which is called Multiview Smooth Discriminant Analysis (MSDA based on Extreme Learning Machines (ELM. Adding the Laplacian penalty constrain for the multiview feature learning, the proposed MSDA is first proposed to extract the cross-modality 2D-3D face features. The MSDA aims at finding a multiview learning based common discriminative feature space and it can then fully utilize the underlying relationship of features from different views. To speed up the learning phase of the classifier, the recent popular algorithm named Extreme Learning Machine (ELM is adopted to train the single hidden layer feedforward neural networks (SLFNs. To evaluate the effectiveness of our proposed FR framework, experimental results on a benchmark face recognition dataset are presented. Simulations show that our new proposed method generally outperforms several recent approaches with a fast training speed.

Linguistic grammar learning and DRD2-TAQ-IA polymorphism.

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Wong, Patrick C M; Ettlinger, Marc; Zheng, Jing

2013-01-01

As research into the neurobiology of language has focused primarily on the systems level, fewer studies have examined the link between molecular genetics and normal variations in language functions. Because the ability to learn a language varies in adults and our genetic codes also vary, research linking the two provides a unique window into the molecular neurobiology of language. We consider a candidate association between the dopamine receptor D2 gene (DRD2) and linguistic grammar learning. DRD2-TAQ-IA polymorphism (rs1800497) is associated with dopamine receptor D2 distribution and dopamine impact in the human striatum, such that A1 allele carriers show reduction in D2 receptor binding relative to carriers who are homozygous for the A2 allele. The individual differences in grammatical rule learning that are particularly prevalent in adulthood are also associated with striatal function and its role in domain-general procedural memory. Therefore, we reasoned that procedurally-based grammar learning could be associated with DRD2-TAQ-IA polymorphism. Here, English-speaking adults learned artificial concatenative and analogical grammars, which have been respectively associated with procedural and declarative memory. Language learning capabilities were tested while learners' neural hemodynamic responses were simultaneously measured by fMRI. Behavioral learning and brain activation data were subsequently compared with the learners' DRD2 (rs1800497) genotype. Learners who were homozygous for the A2 allele were better at concatenative (but not analogical) grammar learning and had higher striatal responses relative to those who have at least one A1 allele. These results provide preliminary evidence for the neurogenetic basis of normal variations in linguistic grammar learning and its link to domain-general functions.

3D dictionary learning based iterative cone beam CT reconstruction

Directory of Open Access Journals (Sweden)

Ti Bai

2014-03-01

Full Text Available Purpose: This work is to develop a 3D dictionary learning based cone beam CT (CBCT reconstruction algorithm on graphic processing units (GPU to improve the quality of sparse-view CBCT reconstruction with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms of 3 × 3 × 3 was trained from a large number of blocks extracted from a high quality volume image. On the basis, we utilized cholesky decomposition based orthogonal matching pursuit algorithm to find the sparse representation of each block. To accelerate the time-consuming sparse coding in the 3D case, we implemented the sparse coding in a parallel fashion by taking advantage of the tremendous computational power of GPU. Conjugate gradient least square algorithm was adopted to minimize the data fidelity term. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with tight frame (TF by performing reconstructions on a subset data of 121 projections. Results: Compared to TF based CBCT reconstruction that shows good overall performance, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, remove more streaking artifacts and also induce less blocky artifacts. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppress the noise, and hence to achieve high quality reconstruction under the case of sparse view. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application.-------------------------------Cite this article as: Bai T, Yan H, Shi F, Jia X, Lou Y, Xu Q, Jiang S, Mou X. 3D dictionary learning based iterative cone beam CT reconstruction. Int J Cancer Ther Oncol 2014; 2(2:020240. DOI: 10

Reduced Mental Load in Learning a Motor Visual Task with Virtual 3D Method

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Dan, A.; Reiner, M.

2018-01-01

Distance learning is expanding rapidly, fueled by the novel technologies for shared recorded teaching sessions on the Web. Here, we ask whether 3D stereoscopic (3DS) virtual learning environment teaching sessions are more compelling than typical two-dimensional (2D) video sessions and whether this type of teaching results in superior learning. The…

Active learning in the lecture theatre using 3D printed objects [version 2; referees: 2 approved

Directory of Open Access Journals (Sweden)

David P. Smith

2016-06-01

Full Text Available The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

A System for True and False Memory Prediction Based on 2D and 3D Educational Contents and EEG Brain Signals.

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Bamatraf, Saeed; Hussain, Muhammad; Aboalsamh, Hatim; Qazi, Emad-Ul-Haq; Malik, Amir Saeed; Amin, Hafeez Ullah; Mathkour, Hassan; Muhammad, Ghulam; Imran, Hafiz Muhammad

2016-01-01

We studied the impact of 2D and 3D educational contents on learning and memory recall using electroencephalography (EEG) brain signals. For this purpose, we adopted a classification approach that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents. In this approach, EEG brain signals are converted into topomaps and then discriminative features are extracted from them and finally support vector machine (SVM) which is employed to predict brain states. For data collection, half of sixty-eight healthy individuals watched the learning material in 2D format whereas the rest watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (STM) and two months (LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and, in case of LTM, it was 100% for both 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D materials do not have much difference in case of STM and LTM.

2D-Driven 3D Object Detection in RGB-D Images

KAUST Repository

Lahoud, Jean

2017-12-25

In this paper, we present a technique that places 3D bounding boxes around objects in an RGB-D scene. Our approach makes best use of the 2D information to quickly reduce the search space in 3D, benefiting from state-of-the-art 2D object detection techniques. We then use the 3D information to orient, place, and score bounding boxes around objects. We independently estimate the orientation for every object, using previous techniques that utilize normal information. Object locations and sizes in 3D are learned using a multilayer perceptron (MLP). In the final step, we refine our detections based on object class relations within a scene. When compared to state-of-the-art detection methods that operate almost entirely in the sparse 3D domain, extensive experiments on the well-known SUN RGB-D dataset [29] show that our proposed method is much faster (4.1s per image) in detecting 3D objects in RGB-D images and performs better (3 mAP higher) than the state-of-the-art method that is 4.7 times slower and comparably to the method that is two orders of magnitude slower. This work hints at the idea that 2D-driven object detection in 3D should be further explored, especially in cases where the 3D input is sparse.

Linguistic grammar learning and DRD2-TAQ-IA polymorphism.

Directory of Open Access Journals (Sweden)

Patrick C M Wong

Full Text Available As research into the neurobiology of language has focused primarily on the systems level, fewer studies have examined the link between molecular genetics and normal variations in language functions. Because the ability to learn a language varies in adults and our genetic codes also vary, research linking the two provides a unique window into the molecular neurobiology of language. We consider a candidate association between the dopamine receptor D2 gene (DRD2 and linguistic grammar learning. DRD2-TAQ-IA polymorphism (rs1800497 is associated with dopamine receptor D2 distribution and dopamine impact in the human striatum, such that A1 allele carriers show reduction in D2 receptor binding relative to carriers who are homozygous for the A2 allele. The individual differences in grammatical rule learning that are particularly prevalent in adulthood are also associated with striatal function and its role in domain-general procedural memory. Therefore, we reasoned that procedurally-based grammar learning could be associated with DRD2-TAQ-IA polymorphism. Here, English-speaking adults learned artificial concatenative and analogical grammars, which have been respectively associated with procedural and declarative memory. Language learning capabilities were tested while learners' neural hemodynamic responses were simultaneously measured by fMRI. Behavioral learning and brain activation data were subsequently compared with the learners' DRD2 (rs1800497 genotype. Learners who were homozygous for the A2 allele were better at concatenative (but not analogical grammar learning and had higher striatal responses relative to those who have at least one A1 allele. These results provide preliminary evidence for the neurogenetic basis of normal variations in linguistic grammar learning and its link to domain-general functions.

Deep imitation learning for 3D navigation tasks.

Science.gov (United States)

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

Random forest learning of ultrasonic statistical physics and object spaces for lesion detection in 2D sonomammography

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Sheet, Debdoot; Karamalis, Athanasios; Kraft, Silvan; Noël, Peter B.; Vag, Tibor; Sadhu, Anup; Katouzian, Amin; Navab, Nassir; Chatterjee, Jyotirmoy; Ray, Ajoy K.

2013-03-01

Breast cancer is the most common form of cancer in women. Early diagnosis can significantly improve lifeexpectancy and allow different treatment options. Clinicians favor 2D ultrasonography for breast tissue abnormality screening due to high sensitivity and specificity compared to competing technologies. However, inter- and intra-observer variability in visual assessment and reporting of lesions often handicaps its performance. Existing Computer Assisted Diagnosis (CAD) systems though being able to detect solid lesions are often restricted in performance. These restrictions are inability to (1) detect lesion of multiple sizes and shapes, and (2) differentiate between hypo-echoic lesions from their posterior acoustic shadowing. In this work we present a completely automatic system for detection and segmentation of breast lesions in 2D ultrasound images. We employ random forests for learning of tissue specific primal to discriminate breast lesions from surrounding normal tissues. This enables it to detect lesions of multiple shapes and sizes, as well as discriminate between hypo-echoic lesion from associated posterior acoustic shadowing. The primal comprises of (i) multiscale estimated ultrasonic statistical physics and (ii) scale-space characteristics. The random forest learns lesion vs. background primal from a database of 2D ultrasound images with labeled lesions. For segmentation, the posterior probabilities of lesion pixels estimated by the learnt random forest are hard thresholded to provide a random walks segmentation stage with starting seeds. Our method achieves detection with 99.19% accuracy and segmentation with mean contour-to-contour error < 3 pixels on a set of 40 images with 49 lesions.

Web based Interactive 3D Learning Objects for Learning Management Systems

Directory of Open Access Journals (Sweden)

Stefan Hesse

2012-02-01

Full Text Available In this paper, we present an approach to create and integrate interactive 3D learning objects of high quality for higher education into a learning management system. The use of these resources allows to visualize topics, such as electro-technical and physical processes in the interior of complex devices. This paper addresses the challenge of combining rich interactivity and adequate realism with 3D exercise material for distance elearning.

N-methyl-d-aspartate receptors, learning and memory: chronic intraventricular infusion of the NMDA receptor antagonist d-AP5 interacts directly with the neural mechanisms of spatial learning.

Science.gov (United States)

Morris, R G M; Steele, R J; Bell, J E; Martin, S J

2013-03-01

Three experiments were conducted to contrast the hypothesis that hippocampal N-methyl-d-aspartate (NMDA) receptors participate directly in the mechanisms of hippocampus-dependent learning with an alternative view that apparent impairments of learning induced by NMDA receptor antagonists arise because of drug-induced neuropathological and/or sensorimotor disturbances. In experiment 1, rats given a chronic i.c.v. infusion of d-AP5 (30 mm) at 0.5 μL/h were selectively impaired, relative to aCSF-infused animals, in place but not cued navigation learning when they were trained during the 14-day drug infusion period, but were unimpaired on both tasks if trained 11 days after the minipumps were exhausted. d-AP5 caused sensorimotor disturbances in the spatial task, but these gradually worsened as the animals failed to learn. Histological assessment of potential neuropathological changes revealed no abnormalities in d-AP5-treated rats whether killed during or after chronic drug infusion. In experiment 2, a deficit in spatial learning was also apparent in d-AP5-treated rats trained on a spatial reference memory task involving two identical but visible platforms, a task chosen and shown to minimise sensorimotor disturbances. HPLC was used to identify the presence of d-AP5 in selected brain areas. In Experiment 3, rats treated with d-AP5 showed a delay-dependent deficit in spatial memory in the delayed matching-to-place protocol for the water maze. These data are discussed with respect to the learning mechanism and sensorimotor accounts of the impact of NMDA receptor antagonists on brain function. We argue that NMDA receptor mechanisms participate directly in spatial learning. © 2013 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Role of PKA signaling in D2 receptor-expressing neurons in the core of the nucleus accumbens in aversive learning.

Science.gov (United States)

Yamaguchi, Takashi; Goto, Akihiro; Nakahara, Ichiro; Yawata, Satoshi; Hikida, Takatoshi; Matsuda, Michiyuki; Funabiki, Kazuo; Nakanishi, Shigetada

2015-09-08

The nucleus accumbens (NAc) serves as a key neural substrate for aversive learning and consists of two distinct subpopulations of medium-sized spiny neurons (MSNs). The MSNs of the direct pathway (dMSNs) and the indirect pathway (iMSNs) predominantly express dopamine (DA) D1 and D2 receptors, respectively, and are positively and negatively modulated by DA transmitters via Gs- and Gi-coupled cAMP-dependent protein kinase A (PKA) signaling cascades, respectively. In this investigation, we addressed how intracellular PKA signaling is involved in aversive learning in a cell type-specific manner. When the transmission of either dMSNs or iMSNs was unilaterally blocked by pathway-specific expression of transmission-blocking tetanus toxin, infusion of PKA inhibitors into the intact side of the NAc core abolished passive avoidance learning toward an electric shock in the indirect pathway-blocked mice, but not in the direct pathway-blocked mice. We then examined temporal changes in PKA activity in dMSNs and iMSNs in behaving mice by monitoring Förster resonance energy transfer responses of the PKA biosensor with the aid of microendoscopy. PKA activity was increased in iMSNs and decreased in dMSNs in both aversive memory formation and retrieval. Importantly, the increased PKA activity in iMSNs disappeared when aversive memory was prevented by keeping mice in the conditioning apparatus. Furthermore, the increase in PKA activity in iMSNs by aversive stimuli reflected facilitation of aversive memory retention. These results indicate that PKA signaling in iMSNs plays a critical role in both aversive memory formation and retention.

3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

Science.gov (United States)

Su,Chung-Ho; Cheng, Ching-Hsue

2013-01-01

The advancement of game-based learning has encouraged many related studies, such that students could better learn curriculum by 3-dimension virtual reality. To enhance software engineering learning, this paper develops a 3D game-based learning system to assist teaching and assess the students' motivation, satisfaction and learning achievement. A…

Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes

Science.gov (United States)

Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong

2018-01-01

In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.

Joint sparse learning for 3-D facial expression generation.

Science.gov (United States)

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Bu, Jiajun

2013-08-01

3-D facial expression generation, including synthesis and retargeting, has received intensive attentions in recent years, because it is important to produce realistic 3-D faces with specific expressions in modern film production and computer games. In this paper, we present joint sparse learning (JSL) to learn mapping functions and their respective inverses to model the relationship between the high-dimensional 3-D faces (of different expressions and identities) and their corresponding low-dimensional representations. Based on JSL, we can effectively and efficiently generate various expressions of a 3-D face by either synthesizing or retargeting. Furthermore, JSL is able to restore 3-D faces with holes by learning a mapping function between incomplete and intact data. Experimental results on a wide range of 3-D faces demonstrate the effectiveness of the proposed approach by comparing with representative ones in terms of quality, time cost, and robustness.

The effects of 3D interactive animated graphics on student learning and attitudes in computer-based instruction

Science.gov (United States)

Moon, Hye Sun

Visuals are most extensively used as instructional tools in education to present spatially-based information. Recent computer technology allows the generation of 3D animated visuals to extend the presentation in computer-based instruction. Animated visuals in 3D representation not only possess motivational value that promotes positive attitudes toward instruction but also facilitate learning when the subject matter requires dynamic motion and 3D visual cue. In this study, three questions are explored: (1) how 3D graphics affects student learning and attitude, in comparison with 2D graphics; (2) how animated graphics affects student learning and attitude, in comparison with static graphics; and (3) whether the use of 3D graphics, when they are supported by interactive animation, is the most effective visual cues to improve learning and to develop positive attitudes. A total of 145 eighth-grade students participated in a 2 x 2 factorial design study. The subjects were randomly assigned to one of four computer-based instructions: 2D static; 2D animated; 3D static; and 3D animated. The results indicated that: (1) Students in the 3D graphic condition exhibited more positive attitudes toward instruction than those in the 2D graphic condition. No group differences were found between the posttest score of 3D graphic condition and that of 2D graphic condition. However, students in the 3D graphic condition took less time for information retrieval on posttest than those in the 2D graphic condition. (2) Students in the animated graphic condition exhibited slightly more positive attitudes toward instruction than those in the static graphic condition. No group differences were found between the posttest score of animated graphic condition and that of static graphic condition. However, students in the animated graphic condition took less time for information retrieval on posttest than those in the static graphic condition. (3) Students in the 3D animated graphic condition

Pathways for Learning from 3D Technology

Science.gov (United States)

Carrier, L. Mark; Rab, Saira S.; Rosen, Larry D.; Vasquez, Ludivina; Cheever, Nancy A.

2016-01-01

The purpose of this study was to find out if 3D stereoscopic presentation of information in a movie format changes a viewer's experience of the movie content. Four possible pathways from 3D presentation to memory and learning were considered: a direct connection based on cognitive neuroscience research; a connection through "immersion" in that 3D presentations could provide additional sensorial cues (e.g., depth cues) that lead to a higher sense of being surrounded by the stimulus; a connection through general interest such that 3D presentation increases a viewer’s interest that leads to greater attention paid to the stimulus (e.g., "involvement"); and a connection through discomfort, with the 3D goggles causing discomfort that interferes with involvement and thus with memory. The memories of 396 participants who viewed two-dimensional (2D) or 3D movies at movie theaters in Southern California were tested. Within three days of viewing a movie, participants filled out an online anonymous questionnaire that queried them about their movie content memories, subjective movie-going experiences (including emotional reactions and "presence") and demographic backgrounds. The responses to the questionnaire were subjected to path analyses in which several different links between 3D presentation to memory (and other variables) were explored. The results showed there were no effects of 3D presentation, either directly or indirectly, upon memory. However, the largest effects of 3D presentation were on emotions and immersion, with 3D presentation leading to reduced positive emotions, increased negative emotions and lowered immersion, compared to 2D presentations. PMID:28078331

E-Learning 2.0: Learning Redefined

OpenAIRE

Kumar, Rupesh

2009-01-01

The conventional e-learning approach emphasizes a learning system more than a learning environment. While traditional e-learning systems continue to be significant, there is a new set of services emerging, embracing the philosophy of Web 2.0. Known as e-learning 2.0, it aims to create a personalized learning environment. E-learning 2.0 combines the use of discrete but complementary tools and web services to support the creation of ad-hoc learning communities. This paper discusses the influenc...

Distance Learning for Students with Special Needs through 3D Virtual Learning

Science.gov (United States)

Laffey, James M.; Stichter, Janine; Galyen, Krista

2014-01-01

iSocial is a 3D Virtual Learning Environment (3D VLE) to develop social competency for students who have been identified with High-Functioning Autism Spectrum Disorders. The motivation for developing a 3D VLE is to improve access to special needs curriculum for students who live in rural or small school districts. The paper first describes a…

Reactor D and D at Argonne National Laboratory - lessons learned

International Nuclear Information System (INIS)

Fellhauer, C. R.

1998-01-01

This paper focuses on the lessons learned during the decontamination and decommissioning (D and D) of two reactors at Argonne National Laboratory-East (ANL-E). The Experimental Boiling Water Reactor (EBWR) was a 100 MW(t), 5 MSV(e) proof-of-concept facility. The Janus Reactor was a 200 kW(t) reactor located at the Biological Irradiation Facility and was used to study the effects of neutron radiation on animals

Effects of Training Method and Gender on Learning 2D/3D Geometry

Science.gov (United States)

Khairulanuar, Samsudin; Nazre, Abd Rashid; Jamilah, H.; Sairabanu, Omar Khan; Norasikin, Fabil

2010-01-01

This article reports the findings of an experimental study involving 36 primary school students (16 girls, 20 boys, Mean age = 9.5 years, age range: 8-10 years) in geometrical understanding of 2D and 3D objects. Students were assigned into two experimental groups and one control group based on a stratified random sampling procedure. The first…

Perceived Advantages of 3D Lessons in Constructive Learning for South African Student Teachers Encountering Learning Barriers

Science.gov (United States)

de Jager, Thelma

2017-01-01

Research shows that three-dimensional (3D)-animated lessons can contribute to student teachers' effective learning and comprehension, regardless of the learning barriers they experience. Student teachers majoring in the subject Life Sciences in General Subject Didactics viewed 3D images of the heart during lectures. The 3D images employed in the…

Learning 2-Dimensional and 3-Dimensional Geometry with Geogebra: Which Would Students Do Better?

Directory of Open Access Journals (Sweden)

Zaleha Ismail

2017-08-01

Full Text Available The purpose of this study is to examine the geometric thinking of young children who worked with GeoGebra to learn two-dimensional (2-D and three-dimensional (3-D geometry. GeoGebra is an open sourced dynamic mathematics software which is applicable for learning mathematics from primary school to secondary school and to higher education. Thirty pupils studying in second grade (Year 2 at a school located in Pontian, a district in one of the Malaysian state participated in the study. They attended GeoGebra sessions to construct and analyze dynamics of two-dimensional and three-dimensional geometry after learning these topics in the conventional setting. Pretest and posttest on two-dimensional and three-dimensional spatial ability based on Van Hiele level of geometric thinking were administered to the pupils. The comparison between pretest and posttest results demonstrate significant enhancement in visualization and informal deduction for both 2-D and 3-D geometry. Moreover from the intervention, the students benefit most in analyzing 3-D and visualizing 2-D geometry. Interestingly, skills and knowledge acquired through activities using GeoGebra in student-centered learning environment could be successfully transferred to paper and pencil test.

Creating Learning Environment Connecting Engineering Design and 3D Printing

Science.gov (United States)

Pikkarainen, Ari; Salminen, Antti; Piili, Heidi

Engineering education in modern days require continuous development in didactics, pedagogics and used practical methods. 3D printing provides excellent opportunity to connect different engineering areas into practice and produce learning by doing applications. The 3D-printing technology used in this study is FDM (Fused deposition modeling). FDM is the most used 3D-printing technology by commercial numbers at the moment and the qualities of the technology makes it popular especially in academic environments. For achieving the best result possible, students will incorporate the principles of DFAM (Design for additive manufacturing) into their engineering design studies together with 3D printing. This paper presents a plan for creating learning environment for mechanical engineering students combining the aspects of engineering design, 3D-CAD learning and AM (additive manufacturing). As a result, process charts for carrying out the 3D printing process from technological point of view and design process for AM from engineering design point of view were created. These charts are used in engineering design education. The learning environment is developed to work also as a platform for Bachelor theses, work-training environment for students, prototyping service centre for cooperation partners and source of information for mechanical engineering education in Lapland University of Applied Sciences.

H-Ransac a Hybrid Point Cloud Segmentation Combining 2d and 3d Data

Science.gov (United States)

Adam, A.; Chatzilari, E.; Nikolopoulos, S.; Kompatsiaris, I.

2018-05-01

In this paper, we present a novel 3D segmentation approach operating on point clouds generated from overlapping images. The aim of the proposed hybrid approach is to effectively segment co-planar objects, by leveraging the structural information originating from the 3D point cloud and the visual information from the 2D images, without resorting to learning based procedures. More specifically, the proposed hybrid approach, H-RANSAC, is an extension of the well-known RANSAC plane-fitting algorithm, incorporating an additional consistency criterion based on the results of 2D segmentation. Our expectation that the integration of 2D data into 3D segmentation will achieve more accurate results, is validated experimentally in the domain of 3D city models. Results show that HRANSAC can successfully delineate building components like main facades and windows, and provide more accurate segmentation results compared to the typical RANSAC plane-fitting algorithm.

Isorhynchophylline improves learning and memory impairments induced by D-galactose in mice.

Science.gov (United States)

Xian, Yan-Fang; Su, Zi-Ren; Chen, Jian-Nan; Lai, Xiao-Ping; Mao, Qing-Qiu; Cheng, Christopher H K; Ip, Siu-Po; Lin, Zhi-Xiu

2014-10-01

Isorhynchophylline (IRN), an alkaloid isolated from Uncaria rhynchophylla, has been reported to improve cognitive impairment induced by beta-amyloid in rats. However, whether IRN could also ameliorate the D-galactose (D-gal)-induced mouse memory deficits is still not clear. In the present study, we aimed to investigate whether IRN had potential protective effect against the D-gal-induced cognitive deficits in mice. Mice were given a subcutaneous injection of D-gal (100mg/kg) and orally administered IRN (20 or 40mg/kg) daily for 8weeks, followed by assessing spatial learning and memory function by the Morris water maze test. The results showed that IRN significantly improved spatial learning and memory function in the D-gal-treated mice. In the mechanistic studies, IRN significantly increased the level of glutathione (GSH) and the activities of superoxide dismutase (SOD) and catalase (CAT), while decreased the level of malondialdehyde (MDA) in the brain tissues of the D-gal-treated mice. Moreover, IRN (20 or 40mg/kg) significantly inhibited the production of prostaglandin E 2 (PGE2) and nitric oxide (NO), and the mRNA expression of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS), as well as the activation of nuclear factor kappa B (NF-κB) in the brain tissues of D-gal-treated mice. Our results amply demonstrated that IRN was able to ameliorate cognitive deficits induced by D-gal in mice, and the observed cognition-improving action may be mediated, at least in part, through enhancing the antioxidant status and anti-inflammatory effect of brain tissues via NFκB signaling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Teaching-learning: stereoscopic 3D versus Traditional methods in Mexico City.

Science.gov (United States)

Mendoza Oropeza, Laura; Ortiz Sánchez, Ricardo; Ojeda Villagómez, Raúl

2015-01-01

In the UNAM Faculty of Odontology, we use a stereoscopic 3D teaching method that has grown more common in the last year, which makes it important to know whether students can learn better with this strategy. The objective of the study is to know, if the 4th year students of the bachelor's degree in dentistry learn more effectively with the use of stereoscopic 3D than the traditional method in Orthodontics. first, we selected the course topics, to be used for both methods; the traditional method using projection of slides and for the stereoscopic third dimension, with the use of videos in digital stereo projection (seen through "passive" polarized 3D glasses). The main topic was supernumerary teeth, including and diverted from their guide eruption. Afterwards we performed an exam on students, containing 24 items, validated by expert judgment in Orthodontics teaching. The results of the data were compared between the two educational methods for determined effectiveness using the model before and after measurement with the statistical package SPSS 20 version. The results presented for the 9 groups of undergraduates in dentistry, were collected with a total of 218 students for 3D and traditional methods, we found in a traditional method a mean 4.91, SD 1.4752 in the pretest and X=6.96, SD 1.26622, St Error 0.12318 for the posttest. The 3D method had a mean 5.21, SD 1.996779 St Error 0.193036 for the pretest X= 7.82, SD =0.963963, St Error 0.09319 posttest; the analysis of Variance between groups F= 5.60 Prob > 0.0000 and Bartlett's test for equal variances 21.0640 Prob > chi2 = 0.007. These results show that the student's learning in 3D means a significant improvement as compared to the traditional teaching method and having a strong association between the two methods. The findings suggest that the stereoscopic 3D method lead to improved student learning compared to traditional teaching.

A 3D Geometry Model Search Engine to Support Learning

Science.gov (United States)

Tam, Gary K. L.; Lau, Rynson W. H.; Zhao, Jianmin

2009-01-01

Due to the popularity of 3D graphics in animation and games, usage of 3D geometry deformable models increases dramatically. Despite their growing importance, these models are difficult and time consuming to build. A distance learning system for the construction of these models could greatly facilitate students to learn and practice at different…

2D-3D Face Recognition Method Basedon a Modified CCA-PCA Algorithm

Directory of Open Access Journals (Sweden)

Patrik Kamencay

2014-03-01

Full Text Available This paper presents a proposed methodology for face recognition based on an information theory approach to coding and decoding face images. In this paper, we propose a 2D-3D face-matching method based on a principal component analysis (PCA algorithm using canonical correlation analysis (CCA to learn the mapping between a 2D face image and 3D face data. This method makes it possible to match a 2D face image with enrolled 3D face data. Our proposed fusion algorithm is based on the PCA method, which is applied to extract base features. PCA feature-level fusion requires the extraction of different features from the source data before features are merged together. Experimental results on the TEXAS face image database have shown that the classification and recognition results based on the modified CCA-PCA method are superior to those based on the CCA method. Testing the 2D-3D face match results gave a recognition rate for the CCA method of a quite poor 55% while the modified CCA method based on PCA-level fusion achieved a very good recognition score of 85%.

Supersymmetric D2 anti-D2 Strings

OpenAIRE

Bak, Dongsu; Ohta, Nobuyoshi

2001-01-01

We consider the flat supersymmetric D2 and anti-D2 system, which follows from ordinary noncommutative D2 anti-D2 branes by turning on an appropriate worldvolume electric field describing dissolved fundamental strings. We study the strings stretched between D2 and anti-D2 branes and show explicitly that the would-be tachyonic states become massless. We compute the string spectrum and clarify the induced noncommutativity on the worldvolume. The results are compared with the matrix theory descri...

D-cycloserine enhances spatial learning performances of rats ...

African Journals Online (AJOL)

Chronic developmental lead (Pb) exposure has long been associated with cognitive dysfunction in children and animals. N-methyl-D-aspartate (NMDA) receptors, important in the synaptic mechanisms involved in learning and memory, are key target of lead toxicity. D-cycloserine (DCS), a partial agonist of the ...

Comparative Study of 2D and 3D Optical Imaging Systems: Laparoendoscopic Single-Site Surgery in an Ex Vivo Model.

Science.gov (United States)

Vilaça, Jaime; Pinto, José Pedro; Fernandes, Sandra; Costa, Patrício; Pinto, Jorge Correia; Leão, Pedro

2017-12-01

Usually laparoscopy is performed by means of a 2-dimensional (2D) image system and multiport approach. To overcome the lack of depth perception, new 3-dimensional (3D) systems are arising with the added advantage of providing stereoscopic vision. To further reduce surgery-related trauma, there are new minimally invasive surgical techniques being developed, such as LESS (laparoendoscopic single-site) surgery. The aim of this study was to compare 2D and 3D laparoscopic systems in LESS surgical procedures. All participants were selected from different levels of experience in laparoscopic surgery-10 novices, 7 intermediates, and 10 experts were included. None of the participants had had previous experience in LESS surgery. Participants were chosen randomly to begin their experience with either the 2D or 3D laparoscopic system. The exercise consisted of performing an ex vivo pork cholecystectomy through a SILS port with the assistance of a fixed distance laparoscope. Errors, time, and participants' preference were recorded. Statistical analysis of time and errors between groups was conducted with a Student's t test (using independent samples) and the Mann-Whitney test. In all 3 groups, the average time with the 2D system was significantly reduced after having used the 3D system ( P 3D system. This study suggests that the 3D system may improve the learning curve and that learning from the 3D system is transferable to the 2D environment. Additionally, the majority of participants prefer 3D equipment.

M3D (Media 3D): a new programming language for web-based virtual reality in E-Learning and Edutainment

Science.gov (United States)

Chakaveh, Sepideh; Skaley, Detlef; Laine, Patricia; Haeger, Ralf; Maad, Soha

2003-01-01

Today, interactive multimedia educational systems are well established, as they prove useful instruments to enhance one's learning capabilities. Hitherto, the main difficulty with almost all E-Learning systems was latent in the rich media implementation techniques. This meant that each and every system should be created individually as reapplying the media, be it only a part, or the whole content was not directly possible, as everything must be applied mechanically i.e. by hand. Consequently making E-learning systems exceedingly expensive to generate, both in time and money terms. Media-3D or M3D is a new platform independent programming language, developed at the Fraunhofer Institute Media Communication to enable visualisation and simulation of E-Learning multimedia content. M3D is an XML-based language, which is capable of distinguishing between the3D models from that of the 3D scenes, as well as handling provisions for animations, within the programme. Here we give a technical account of M3D programming language and briefly describe two specific application scenarios where M3D is applied to create virtual reality E-Learning content for training of technical personnel.

D.3.3 PLOT Persuasive Learning Design Framework

DEFF Research Database (Denmark)

Gram-Hansen, Sandra Burri

2012-01-01

In this third and final deliverable of WP3: Persuasive Learning Designs, the theoretical cross field between persuasion and learning and the practical analysis of the technological learning tools and products which are currently related to the PLOT project, namely the GLOMaker and the 3ET tool......, are linked together as persuasive learning designs are defined and exemplified through the four e-PLOT cases. Based on the literary study of D.3.1 as well as the subsequent discussions and reflections regarding the theoretical foundation and practical application of persuasive learning technologies......-PLOT work cases. In conclusion, the report presents a number of suggestions regarding the improvement of the two learning tools, which from a theoretical perspective will enhance the persuasive potential, and which can be taken into consideration in WP4 and 5....

Deep Cuboid Detection: Beyond 2D Bounding Boxes

OpenAIRE

Dwibedi, Debidatta; Malisiewicz, Tomasz; Badrinarayanan, Vijay; Rabinovich, Andrew

2016-01-01

We present a Deep Cuboid Detector which takes a consumer-quality RGB image of a cluttered scene and localizes all 3D cuboids (box-like objects). Contrary to classical approaches which fit a 3D model from low-level cues like corners, edges, and vanishing points, we propose an end-to-end deep learning system to detect cuboids across many semantic categories (e.g., ovens, shipping boxes, and furniture). We localize cuboids with a 2D bounding box, and simultaneously localize the cuboid's corners,...

Blended learning in dentistry: 3-D resources for inquiry-based learning

Directory of Open Access Journals (Sweden)

Susan Bridges

2012-06-01

Full Text Available Motivation is an important factor for inquiry-based learning, so creative design of learning resources and materials is critical to enhance students’ motivation and hence their cognition. Modern dentistry is moving towards “electronic patient records” for both clinical treatment and teaching. Study models have long been an essential part of dental records. Traditional plaster casts are, however, among the last type of clinical record in the dental field to be converted into digital media as virtual models. Advantages of virtual models include: simpler storage; reduced risk of damage, disappearance, or misplacement; simpler and effective measuring; and easy transferal to colleagues. In order to support student engagement with the rapidly changing world of digital dentistry, and in order to stimulate the students’ motivation and depth of inquiry, this project aims to introduce virtual models into a Bachelor and Dental Surgery (BDS curriculum. Under a “blended” e-learning philosophy, students are first introduced to the new software then 3-D models are incorporated into inquiry-based problems as stimulus materials. Face-to-face tutorials blend virtual model access via interactive whiteboards (IWBs. Students’ perceptions of virtual models including motivation and cognition as well as the virtual models’ functionality were rated after a workshop introducing virtual models and plaster models in parallel. Initial student feedback indicates that the 3-D models have been generally well accepted, which confirmed the functionality of the programme and the positive perception of virtual models for enhancing students’ learning motivation. Further investigation will be carried out to assess the impact of virtual models on students’ learning outcomes.

PROTECTIVE EFFECT OF TETRAMETHYLPYRAZINE ON LEARNING AND MEMORY FUNCTION IN D-GALACTOSE-LESIONED MICE

Institute of Scientific and Technical Information of China (English)

Chun Zhang; Shi-zhen Wang; Ping-ping Zuo; Xu Cui; Jiong Cai

2004-01-01

Objective To explore the protective effect of tetramethylpyrazine (TMP) on the learning and memory function in D-galactose (D-gal)-lesioned mice.zine A were respectively given by intragastric administration in different groups from the third week. Learning and memory ability was tested with Morris water maze for 5 days at the sixth week. After completion of behavioral test, the mice were sacrificed by decapitation. The brain was rapidly removed, and the cortex and hippocampus were separated. The superoxide dismutase (SOD) activity and malondialdehyde (MDA) content in the cortex were determined. At the same time, the activity of choline acetyltransferase (ChAT) and acetylcholinesterase (AChE), the binding sites (Bmax) and the affinity (KD) of M-cholinergic receptor in the cortex, and Bmax and KD of N-methyl-D-aspartate (NMDA) receptor in the hippocampus were determined.Results In this model group, (1) The deficit of learning and memory ability, (2) elevated MDA content and lowered SOD activity, (3) decreased AChE activity and M-cholinergic receptor binding sites in the cortex, and (4) lowered NMDA receptor binding sites were observed in the hippocampus, as compared with the normal control. TMP could markedly (1)attenuate cognitive dysfunction, (2) lower MDA content and elevate SOD activity, (3) increase the activity of ChAT and AChE, and M-cholinergic receptor binding sites in the cortex in the mice treated with D-gal. NMDA receptor binding sites were also increased in the hippocampus in the treated mice.Conclusion TMP can significantly strengthen antioxidative function, improve central cholinergic system function, protect NMDA receptor activity, and thus enhance the learning and memory ability in D-gal-lesioned mice.

The 3D LAOKOON--Visual and Verbal in 3D Online Learning Environments.

Science.gov (United States)

Liestol, Gunnar

This paper reports on a project where three-dimensional (3D) online gaming environments were exploited for the purpose of academic communication and learning. 3D gaming environments are media and meaning rich and can provide inexpensive solutions for educational purposes. The experiment with teaching and discussions in this setting, however,…

Realistic and efficient 2D crack simulation

Science.gov (United States)

Yadegar, Jacob; Liu, Xiaoqing; Singh, Abhishek

2010-04-01

Although numerical algorithms for 2D crack simulation have been studied in Modeling and Simulation (M&S) and computer graphics for decades, realism and computational efficiency are still major challenges. In this paper, we introduce a high-fidelity, scalable, adaptive and efficient/runtime 2D crack/fracture simulation system by applying the mathematically elegant Peano-Cesaro triangular meshing/remeshing technique to model the generation of shards/fragments. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level-of-detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanism used for mesh element splitting and merging with minimal memory requirements essential for realistic 2D fragment formation. Upon load impact/contact/penetration, a number of factors including impact angle, impact energy, and material properties are all taken into account to produce the criteria of crack initialization, propagation, and termination leading to realistic fractal-like rubble/fragments formation. The aforementioned parameters are used as variables of probabilistic models of cracks/shards formation, making the proposed solution highly adaptive by allowing machine learning mechanisms learn the optimal values for the variables/parameters based on prior benchmark data generated by off-line physics based simulation solutions that produce accurate fractures/shards though at highly non-real time paste. Crack/fracture simulation has been conducted on various load impacts with different initial locations at various impulse scales. The simulation results demonstrate that the proposed system has the capability to realistically and efficiently simulate 2D crack phenomena (such as window shattering and shards generation) with diverse potentials in military and civil M&S applications such as training and mission planning.

Cabri 3D - assisted collaborative learning to enhance junior high school students’ spatial ability

Science.gov (United States)

Muntazhimah; Miatun, A.

2018-01-01

The main purpose of this quasi-experimental study was to determine the enhancement of spatial ability of junior high school students who learned through Cabri-3D assisted collaborative learning. The methodology of this study was the nonequivalent group that was conducted to students of the eighth grade in a junior high school as a population. Samples consisted one class of the experimental group who studied with Cabri-3D assisted collaborative learning and one class as a control group who got regular learning activity. The instrument used in this study was a spatial ability test. Analyzing normalized gain of students’ spatial ability based on mathemathical prior knowledge (MPK) and its interactions was tested by two-way ANOVA at a significance level of 5% then continued with using Post Hoc Scheffe test. The research results showed that there was significant difference in enhancement of the spatial ability between students who learnt with Cabri 3D assisted collaborative learning and students who got regular learning, there was significant difference in enhancement of the spatial ability between students who learnt with cabri 3D assisted collaborative learning and students who got regular learning in terms of MPK and there is no significant interaction between learning (Cabri-3D assisted collaborative learning and regular learning) with students’ MPK (high, medium, and low) toward the enhancement of students’ spatial abilities. From the above findings, it can be seen that cabri-3D assisted collaborative learning could enhance spatial ability of junior high school students.

COMPARISON OF 2D AND 3D VIDEO DISPLAYS FOR TEACHING VITREORETINAL SURGERY.

Science.gov (United States)

Chhaya, Nisarg; Helmy, Omar; Piri, Niloofar; Palacio, Agustina; Schaal, Shlomit

2017-07-11

To compare medical students' learning uptake and understanding of vitreoretinal surgeries by watching either 2D or 3D video recordings. Three vitreoretinal procedures (tractional retinal detachment, exposed scleral buckle removal, and four-point scleral fixation of an intraocular lens [TSS]) were recorded simultaneously with a conventional recorder for two-dimensional viewing and a VERION 3D HD system using Sony HVO-1000MD for three-dimensional viewing. Two videos of each surgery, one 2D and the other 3D, were edited to have the same content side by side. One hundred UMass medical students randomly assigned to a 2D group or 3D, then watched corresponding videos on a MacBook. All groups wore BiAL Red-blue 3D glasses and were appropriately randomized. Students filled out questionnaires about surgical steps or anatomical relationships of the pathologies or tissues, and their answers were compared. There was no significant difference in comprehension between the two groups for the extraocular scleral buckle procedure. However, for the intraocular TSS and tractional retinal detachment videos, the 3D group performed better than 2D (P < 0.05) on anatomy comprehension questions. Three-dimensional videos may have value in teaching intraocular ophthalmic surgeries. Surgical procedure steps and basic ocular anatomy may have to be reviewed to ensure maximal teaching efficacy.

Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition

KAUST Repository

Li, Huibin

2011-10-01

This paper proposes a novel approach for 3D face recognition by learning weighted sparse representation of encoded facial normal information. To comprehensively describe 3D facial surface, three components, in X, Y, and Z-plane respectively, of normal vector are encoded locally to their corresponding normal pattern histograms. They are finally fed to a sparse representation classifier enhanced by learning based spatial weights. Experimental results achieved on the FRGC v2.0 database prove that the proposed encoded normal information is much more discriminative than original normal information. Moreover, the patch based weights learned using the FRGC v1.0 and Bosphorus datasets also demonstrate the importance of each facial physical component for 3D face recognition. © 2011 IEEE.

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

Science.gov (United States)

Spirkovska, Lilly; Reid, Max B.

1994-01-01

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

The Influence of Supervisor's Transformational Leadership on Learning Culture and Learning Transfer of Nuclear R and D Personnel

International Nuclear Information System (INIS)

Min, Sang-Ki; Hwang, Hye-Seon; Jin, You-Rim; Lee, Eui-Jin; Lee, Soo-Jin

2017-01-01

Transformational leadership means that supervisors try to support the members individually, and encourage them to find new methods and approaches. In this study, it was identified empirically that a supervisor's transformational leadership has a strong influence on the learning culture and learning transfer of nuclear R and D personnel. To develop the competency of R and D personnel, not only formal education programs but also informal learning such as workplace learning have been carried out in the nuclear R and D organization. In this situation, transformational leadership has an effect on willingness and behavior of nuclear R and D personnel on the formal and informal learning. Therefore, transformational leadership is crucial factor in the human resource development system. The leadership required by them is not a one-sided order, but rather individual consideration, charisma, and intellectual stimulation for their nuclear R and D members. As a point of nuclear training and education, it is necessary to consider the operation of leadership programs that strengthen the transformational leadership of the project managers.

Modeling student's learning styles in web 2.0 learning systems

Directory of Open Access Journals (Sweden)

Ramon Cabada Zatarain Cabada, M. L. Barron Estrada, L. Zepeda Sanchez, Guillermo Sandoval, J.M. Osorio Velazquez, J.E. Urias Barrientos

2009-12-01

Full Text Available The identification of the best learning style in an Intelligent Tutoring System must be considered essential as part of thesuccess in the teaching process. In many implementations of automatic classifiers finding the right student learning styler e p r e s e n t s t h e h a r d e s t a s s i g n m e n t . T h e r e a s o n i s t h a t m o s t o f t h e t e c h n i q u e s w o r k u s i n g e x p e r t g r o u p s o r a s e t o fquestionnaires which define how the learning styles are assigned to students. This paper presents a novel approach forautomatic learning styles classification using a Kohonen network. The approach is used by an author tool for buildingIntelligent Tutoring Systems running under a Web 2.0 collaborative learning platform. The tutoring systems together withthe neural network can also be exported to mobile devices. We present different results to the approach working under theauthor tool.

A comparison of 1D and 2D LSTM architectures for the recognition of handwritten Arabic

Science.gov (United States)

Yousefi, Mohammad Reza; Soheili, Mohammad Reza; Breuel, Thomas M.; Stricker, Didier

2015-01-01

In this paper, we present an Arabic handwriting recognition method based on recurrent neural network. We use the Long Short Term Memory (LSTM) architecture, that have proven successful in different printed and handwritten OCR tasks. Applications of LSTM for handwriting recognition employ the two-dimensional architecture to deal with the variations in both vertical and horizontal axis. However, we show that using a simple pre-processing step that normalizes the position and baseline of letters, we can make use of 1D LSTM, which is faster in learning and convergence, and yet achieve superior performance. In a series of experiments on IFN/ENIT database for Arabic handwriting recognition, we demonstrate that our proposed pipeline can outperform 2D LSTM networks. Furthermore, we provide comparisons with 1D LSTM networks trained with manually crafted features to show that the automatically learned features in a globally trained 1D LSTM network with our normalization step can even outperform such systems.

Learning to Grasp Unknown Objects Based on 3D Edge Information

DEFF Research Database (Denmark)

Bodenhagen, Leon; Kraft, Dirk; Popovic, Mila

2010-01-01

In this work we refine an initial grasping behavior based on 3D edge information by learning. Based on a set of autonomously generated evaluated grasps and relations between the semi-global 3D edges, a prediction function is learned that computes a likelihood for the success of a grasp using either...... an offline or an online learning scheme. Both methods are implemented using a hybrid artificial neural network containing standard nodes with a sigmoid activation function and nodes with a radial basis function. We show that a significant performance improvement can be achieved....

Learning process for performing and analyzing 3D/4D transperineal ultrasound imaging and interobserver reliability study.

Science.gov (United States)

Siafarikas, F; Staer-Jensen, J; Braekken, I H; Bø, K; Engh, M Ellström

2013-03-01

To evaluate the learning process for acquiring three- and four-dimensional (3D/4D) transperineal ultrasound volumes of the levator hiatus (LH) dimensions at rest, during pelvic floor muscle (PFM) contraction and on Valsalva maneuver, and for analyzing the ultrasound volumes, as well as to perform an interobserver reliability study between two independent ultrasound examiners. This was a prospective study including 22 women. We monitored the learning process of an inexperienced examiner (IE) performing 3D/4D transperineal ultrasonography and analyzing the volumes. The examination included acquiring volumes during three PFM contractions and three Valsalva maneuvers. LH dimensions were determined in the axial plane. The learning process was documented by estimating agreement between the IE and an experienced examiner (E) using the intraclass correlation coefficient. Agreement was calculated in blocks of 10 ultrasound examinations and analyzed volumes. After the learning process was complete the interobserver reliability for the technique was calculated between these two independent examiners. For offline analysis of the first 10 ultrasound volumes obtained by E, good to very good agreement between E and IE was achieved for all LH measurements except for the left and right levator-urethra gap and pubic arc. For the next 10 analyzed volumes, agreement improved for all LH measurements. Volumes that had been obtained by IE and E were then re-evaluated by IE, and good to very good agreement was found for all LH measurements indicating consistency in volume acquisition. The interobserver reliability study showed excellent ICC values (ICC, 0.81-0.97) for all LH measurements except the pubic arc (ICC = 0.67). 3D/4D transperineal ultrasound is a reliable technique that can be learned in a short period of time. Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd.

An Introduction of Zoltán D?rnyei's L2 Motivational Theories%An Introduction of Zoltán Dörnyei's L2 Motivational Theories

Institute of Scientific and Technical Information of China (English)

王晓磊; 周密

2016-01-01

Professor Zoltán D?rnyei is an influential researcher of L2 learning motivation. Since 1990s, he put forward several important L2 learning motivational theories and made special contribution to this field. This paper introduces his four L2 learn-ing motivational theories:1)Three-level framework of L2 motivation;2) Process model of L2 motivation;3)The L2 Motivation-al Self System;4) Directed Motivational Currents (DMC).

2D/3D/4D ULTRASOUND IN INFERTILITY MANAGEMENT

Directory of Open Access Journals (Sweden)

Uršula Reš-Muravec

2018-02-01

. Conclusions: There is an increasing number of ultrasound machines offering us beside 2D, 3D and 4D technology. It is important to learn the applications and use them in our daily practice. The recorded volumes can be examined at any time in any plan. In any unclear pathology the recorded volume can be send for second opinion and discussed further.

Enhancement of Online Robotics Learning Using Real-Time 3D Visualization Technology

Directory of Open Access Journals (Sweden)

Richard Chiou

2010-06-01

Full Text Available This paper discusses a real-time e-Lab Learning system based on the integration of 3D visualization technology with a remote robotic laboratory. With the emergence and development of the Internet field, online learning is proving to play a significant role in the upcoming era. In an effort to enhance Internet-based learning of robotics and keep up with the rapid progression of technology, a 3- Dimensional scheme of viewing the robotic laboratory has been introduced in addition to the remote controlling of the robots. The uniqueness of the project lies in making this process Internet-based, and remote robot operated and visualized in 3D. This 3D system approach provides the students with a more realistic feel of the 3D robotic laboratory even though they are working remotely. As a result, the 3D visualization technology has been tested as part of a laboratory in the MET 205 Robotics and Mechatronics class and has received positive feedback by most of the students. This type of research has introduced a new level of realism and visual communications to online laboratory learning in a remote classroom.

Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views

OpenAIRE

Massa, Francisco; Russell, Bryan; Aubry, Mathieu

2015-01-01

This paper presents an end-to-end convolutional neural network (CNN) for 2D-3D exemplar detection. We demonstrate that the ability to adapt the features of natural images to better align with those of CAD rendered views is critical to the success of our technique. We show that the adaptation can be learned by compositing rendered views of textured object models on natural images. Our approach can be naturally incorporated into a CNN detection pipeline and extends the accuracy and speed benefi...

Coupled Dictionary Learning for the Detail-Enhanced Synthesis of 3-D Facial Expressions.

Science.gov (United States)

Liang, Haoran; Liang, Ronghua; Song, Mingli; He, Xiaofei

2016-04-01

The desire to reconstruct 3-D face models with expressions from 2-D face images fosters increasing interest in addressing the problem of face modeling. This task is important and challenging in the field of computer animation. Facial contours and wrinkles are essential to generate a face with a certain expression; however, these details are generally ignored or are not seriously considered in previous studies on face model reconstruction. Thus, we employ coupled radius basis function networks to derive an intermediate 3-D face model from a single 2-D face image. To optimize the 3-D face model further through landmarks, a coupled dictionary that is related to 3-D face models and their corresponding 3-D landmarks is learned from the given training set through local coordinate coding. Another coupled dictionary is then constructed to bridge the 2-D and 3-D landmarks for the transfer of vertices on the face model. As a result, the final 3-D face can be generated with the appropriate expression. In the testing phase, the 2-D input faces are converted into 3-D models that display different expressions. Experimental results indicate that the proposed approach to facial expression synthesis can obtain model details more effectively than previous methods can.

Measurement of the hyperfine structure of the 4d2D3/2,5/2 levels and isotope shifts of the 4p2P3/2->4d2D3/2 and 4p2P3/2->4d2D5/2 transitions in gallium 69 and 71

International Nuclear Information System (INIS)

Rehse, Steven J.; Fairbank, William M.; Lee, Siu Au

2001-01-01

The hyperfine structure of the 4d 2 D 3/2,5/2 levels of 69,71 Ga is determined. The 4p 2 P 3/2 ->4d 2 D 3/2 (294.50-nm) and 4p 2 P 3/2 ->4d 2 D 5/2 (294.45-nm) transitions are studied by laser-induced fluorescence in an atomic Ga beam. The hyperfine A constant measured for the 4d 2 D 5/2 level is 77.3±0.9 MHz for 69 Ga and 97.9± 0.7 MHz for 71 Ga (3σ errors). The A constant measured for the 4d 2 D 3/2 level is -36.3±2.2 MHz for 69 Ga and -46.2±3.8 MHz for 71 Ga. These measurements correct sign errors in the previous determination of these constants. For 69 Ga the hyperfine B constants measured for the 4d 2 D 5/2 and the 4d 2 D 3/2 levels are 5.3±4.1 MHz and 4.6±4.2 MHz, respectively. The isotope shift is determined to be 114±8 MHz for the 4p 2 P 3/2 ->4d 2 D 3/2 transition and 115±7 MHz for the 4p 2 P 3/2 ->4d 2 D 5/2 transition. The lines of 71 Ga are shifted to the blue. This is in agreement with previous measurement. [copyright] 2001 Optical Society of America

Musical Expression with the D2MMG Interface

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer; Graugaard, Lars

2006-01-01

Distribution in Multiple Musical Gestures (D2MMG) uses a robust interface for detecting simple drawing gestures. The gestures affect low- and high-level aspects of sound and music through inherent modes organized as primary and secondary gestures. This enables expressive live performance...... and improvisation with sequence creation where musical elements such as tonality, chromaticity, rhythm patterns, and melodical sequences can be affected in real-time. We introduce a utility for procedurally controlling note density and chordal alignment. Future papers will focus on D2MMG’s progressive learning......, multi-user, and unconventional performance usage as well as novel aspects of its methods for gesture detection and sound synthesis....

Learning and generalization errors for the 2D binary perceptron

NARCIS (Netherlands)

Klymovskiy, A.

2005-01-01

The statistical mechanics model of the binary perceptron learning is considered. It is proved that under the regularity conditions learning and generalization errors for the binary perceptron with two inputs tend to 0 at the average; the first term of the asymptotics is provided; its behavior with

Versatile, immersive, creative and dynamic virtual 3-D healthcare learning environments: a review of the literature.

Science.gov (United States)

Hansen, Margaret M

2008-09-01

The author provides a critical overview of three-dimensional (3-D) virtual worlds and "serious gaming" that are currently being developed and used in healthcare professional education and medicine. The relevance of this e-learning innovation for teaching students and professionals is debatable and variables influencing adoption, such as increased knowledge, self-directed learning, and peer collaboration, by academics, healthcare professionals, and business executives are examined while looking at various Web 2.0/3.0 applications. There is a need for more empirical research in order to unearth the pedagogical outcomes and advantages associated with this e-learning technology. A brief description of Roger's Diffusion of Innovations Theory and Siemens' Connectivism Theory for today's learners is presented as potential underlying pedagogical tenets to support the use of virtual 3-D learning environments in higher education and healthcare.

Automatic computation of 2D cardiac measurements from B-mode echocardiography

Science.gov (United States)

Park, JinHyeong; Feng, Shaolei; Zhou, S. Kevin

2012-03-01

We propose a robust and fully automatic algorithm which computes the 2D echocardiography measurements recommended by America Society of Echocardiography. The algorithm employs knowledge-based imaging technologies which can learn the expert's knowledge from the training images and expert's annotation. Based on the models constructed from the learning stage, the algorithm searches initial location of the landmark points for the measurements by utilizing heart structure of left ventricle including mitral valve aortic valve. It employs the pseudo anatomic M-mode image generated by accumulating the line images in 2D parasternal long axis view along the time to refine the measurement landmark points. The experiment results with large volume of data show that the algorithm runs fast and is robust comparable to expert.

Organizational Learning Goes Virtual?: A Study of Employees' Learning Achievement in Stereoscopic 3D Virtual Reality

Science.gov (United States)

Lau, Kung Wong

2015-01-01

Purpose: This study aims to deepen understanding of the use of stereoscopic 3D technology (stereo3D) in facilitating organizational learning. The emergence of advanced virtual technologies, in particular to the stereo3D virtual reality, has fundamentally changed the ways in which organizations train their employees. However, in academic or…

Characterization and reconstruction of 3D stochastic microstructures via supervised learning.

Science.gov (United States)

Bostanabad, R; Chen, W; Apley, D W

2016-12-01

The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing-structure-property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user-defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Head First 2D Geometry

CERN Document Server

Fallow), Stray

2009-01-01

Having trouble with geometry? Do Pi, The Pythagorean Theorem, and angle calculations just make your head spin? Relax. With Head First 2D Geometry, you'll master everything from triangles, quads and polygons to the time-saving secrets of similar and congruent angles -- and it'll be quick, painless, and fun. Through entertaining stories and practical examples from the world around you, this book takes you beyond boring problems. You'll actually use what you learn to make real-life decisions, like using angles and parallel lines to crack a mysterious CSI case. Put geometry to work for you, and

Real-time Stereoscopic 3D for E-Robotics Learning

Directory of Open Access Journals (Sweden)

Richard Y. Chiou

2011-02-01

Full Text Available Following the design and testing of a successful 3-Dimensional surveillance system, this 3D scheme has been implemented into online robotics learning at Drexel University. A real-time application, utilizing robot controllers, programmable logic controllers and sensors, has been developed in the “MET 205 Robotics and Mechatronics” class to provide the students with a better robotic education. The integration of the 3D system allows the students to precisely program the robot and execute functions remotely. Upon the students’ recommendation, polarization has been chosen to be the main platform behind the 3D robotic system. Stereoscopic calculations are carried out for calibration purposes to display the images with the highest possible comfort-level and 3D effect. The calculations are further validated by comparing the results with students’ evaluations. Due to the Internet-based feature, multiple clients have the opportunity to perform the online automation development. In the future, students, in different universities, will be able to cross-control robotic components of different types around the world. With the development of this 3D ERobotics interface, automation resources and robotic learning can be shared and enriched regardless of location.

GE3D: A Virtual Campus for Technology-Enhanced Distance Learning

Directory of Open Access Journals (Sweden)

Jean Grieu

2010-09-01

Full Text Available A lot of learning systems platforms are used all over the world. But these conventional E-learning platforms aim at students who are used to work on their own. Our students are young (19 years old – 22 years old, and in their first year at the university. Following extensive interviews with our students, we have designed GE3D, an E-learning platform, according to their expectations and our criteria. In this paper, we describe the students’ demands, resulting from the interviews. Then, we describe our virtual campus. Even if our platform uses some elements coming from the 3D games world, it is always a pedagogical tool. Using this technology, we developed a 3D representation of the real world. GE3D is a multi-users tool, with a synchronous technology, an intuitive interface for end-users and an embedded Intelligent Tutoring System to support learners. We also describe the process of a lecture on the Programmable Logic Controllers (PLC’s in this new universe.

3D interactive augmented reality-enhanced digital learning systems for mobile devices

Science.gov (United States)

Feng, Kai-Ten; Tseng, Po-Hsuan; Chiu, Pei-Shuan; Yang, Jia-Lin; Chiu, Chun-Jie

2013-03-01

With enhanced processing capability of mobile platforms, augmented reality (AR) has been considered a promising technology for achieving enhanced user experiences (UX). Augmented reality is to impose virtual information, e.g., videos and images, onto a live-view digital display. UX on real-world environment via the display can be e ectively enhanced with the adoption of interactive AR technology. Enhancement on UX can be bene cial for digital learning systems. There are existing research works based on AR targeting for the design of e-learning systems. However, none of these work focuses on providing three-dimensional (3-D) object modeling for en- hanced UX based on interactive AR techniques. In this paper, the 3-D interactive augmented reality-enhanced learning (IARL) systems will be proposed to provide enhanced UX for digital learning. The proposed IARL systems consist of two major components, including the markerless pattern recognition (MPR) for 3-D models and velocity-based object tracking (VOT) algorithms. Realistic implementation of proposed IARL system is conducted on Android-based mobile platforms. UX on digital learning can be greatly improved with the adoption of proposed IARL systems.

3D surface parameterization using manifold learning for medial shape representation

Science.gov (United States)

Ward, Aaron D.; Hamarneh, Ghassan

2007-03-01

The choice of 3D shape representation for anatomical structures determines the effectiveness with which segmentation, visualization, deformation, and shape statistics are performed. Medial axis-based shape representations have attracted considerable attention due to their inherent ability to encode information about the natural geometry of parts of the anatomy. In this paper, we propose a novel approach, based on nonlinear manifold learning, to the parameterization of medial sheets and object surfaces based on the results of skeletonization. For each single-sheet figure in an anatomical structure, we skeletonize the figure, and classify its surface points according to whether they lie on the upper or lower surface, based on their relationship to the skeleton points. We then perform nonlinear dimensionality reduction on the skeleton, upper, and lower surface points, to find the intrinsic 2D coordinate system of each. We then center a planar mesh over each of the low-dimensional representations of the points, and map the meshes back to 3D using the mappings obtained by manifold learning. Correspondence between mesh vertices, established in their intrinsic 2D coordinate spaces, is used in order to compute the thickness vectors emanating from the medial sheet. We show results of our algorithm on real brain and musculoskeletal structures extracted from MRI, as well as an artificial multi-sheet example. The main advantages to this method are its relative simplicity and noniterative nature, and its ability to correctly compute nonintersecting thickness vectors for a medial sheet regardless of both the amount of coincident bending and thickness in the object, and of the incidence of local concavities and convexities in the object's surface.

D2D-Enabled Small Cell Network Control Scheme Based on the Dynamic Stackelberg Game

Directory of Open Access Journals (Sweden)

Sungwook Kim

2017-01-01

Full Text Available For current and future cellular networks, small cell structure with licensed and unlicensed bandwidth, caching content provisioning, and device-to-device (D2D communications is seen as a necessary architecture. Recently, a series of control methods have been developed to address a myriad of challenges in next-generation small cell networks. In this study, we focus on the design of novel D2D-enabled small cell network control scheme by allowing caching and unlicensed D2D communications. Motivated by game theory and learning algorithm, the proposed scheme adaptively selects caching contents and splits the available bandwidth for licensed and unlicensed communications. Under dynamically changing network environments, we capture the dynamics of the network system and design a new dynamic Stackelberg game model. Based on a hierarchical and feedback based control manner, small base stations and users can be leaders or followers dynamically while improving 5G network performance. Simulations and performance analysis verify the efficiency of the proposed scheme, showing that our approach can outperform existing schemes by about 5%~15% in terms of bandwidth utilization, cache hit ratio, and system throughput.

24,25,28-Trihydroxyvitamin D2 and 24,25,26-trihydroxyvitamin D2: Novel metabolites of vitamin D2

International Nuclear Information System (INIS)

Reddy, G.S.; Tserng, K.

1990-01-01

Understanding of the inactivation pathways of 25-hydroxyvitamin D 2 and 24-hydroxyvitamin D 2 , the two physiologically significant monohydroxylated metabolites of vitamin D 2 , is of importance, especially during hypervitaminosis D 2 . At present, little information is available regarding the inactivation pathway of 25-hydroxyvitamin D 2 except its further metabolism into 24,25-dihydroxyvitamin D 2 . In our present study, the authors investigated the metabolic fate of 25-hydroxyvitamin D 2 in the isolated perfused rat kidney and demonstrated its conversion not only into 24,25-dihydroxyvitamin D 2 but also into two other new metabolites, namely, 24,25,28-trihydroxyvitamin D 2 and 24,25,26-trihydroxyvitamin D 2 . The structure identification of the new metabolites was established by the techniques of ultraviolet absorption spectrophotometry and mass spectrometry and by the characteristic nature of each new metabolite's susceptibility to sodium metaperiodate oxidation. In order to demonstrate the physiological significance of the two new trihydroxy metabolites of vitamin D 2 , induced hypervitaminosis D 2 in a rat using [3α- 3 H]vitamin D 2 and analyzed its plasma for the various [3α- 3 H]vitamin D 2 metabolites on two different high-pressure liquid chromatography systems. The results indicate that both 24,25,26-trihydroxyvitamin D 2 and 24,25,26-trihydroxyvitamin D 2 circulate in the vitamin D 2 intoxicated rat in significant amounts along with other previously identified monohydroxy and dihydroxy metabolites of vitamin D 2 , namely, 24-hydroxyvitamin D 2 , 25-hydroxyvitamin D 2 , and 24,25-dihydroxyvitamin D 2

Potentiation of latent inhibition by haloperidol and clozapine is attenuated in Dopamine D2 receptor (Drd-2)-deficient mice: Do antipsychotics influence learning to ignore irrelevant stimuli via both Drd-2 and non-Drd-2 mechanisms?

Science.gov (United States)

O’Callaghan, Matthew J; Bay-Richter, Cecilie; O’Tuathaigh, Colm MP; Heery, David M; Waddington, John L; Moran, Paula M

2014-01-01

Whether the dopamine Drd-2 receptor is necessary for the behavioural action of antipsychotic drugs is an important question, as Drd-2 antagonism is responsible for their debilitating motor side effects. Using Drd-2 null mice (Drd2 -/-) it has previously been shown that Drd-2 is not necessary for antipsychotic drugs to reverse D-amphetamine disruption of latent inhibition (LI), a behavioural measure of learning to ignore irrelevant stimuli. Weiner’s ‘two-headed’ model indicates that antipsychotics not only reverse LI disruption, ‘disrupted LI’, but also potentiate LI when low/absent in controls, ‘persistent’ LI. We investigated whether antipsychotic drugs haloperidol or clozapine potentiated LI in wild-type controls or Drd2 -/-. Both drugs potentiated LI in wild-type but not in Drd2-/- mice, suggesting moderation of this effect of antipsychotics in the absence of Drd-2. Haloperidol potentiated LI similarly in both Drd1-/- and wild-type mice, indicating no such moderation in Drd1-/-. These data suggest that antipsychotic drugs can have either Drd-2 or non-Drd-2 effects on learning to ignore irrelevant stimuli, depending on how the abnormality is produced. Identification of the non-Drd-2 mechanism may help to identify novel non-Drd2 based therapeutic strategies for psychosis. PMID:25122042

2D co-ordinate transformation based on a spike timing-dependent plasticity learning mechanism.

Science.gov (United States)

Wu, QingXiang; McGinnity, Thomas Martin; Maguire, Liam; Belatreche, Ammar; Glackin, Brendan

2008-11-01

In order to plan accurate motor actions, the brain needs to build an integrated spatial representation associated with visual stimuli and haptic stimuli. Since visual stimuli are represented in retina-centered co-ordinates and haptic stimuli are represented in body-centered co-ordinates, co-ordinate transformations must occur between the retina-centered co-ordinates and body-centered co-ordinates. A spiking neural network (SNN) model, which is trained with spike-timing-dependent-plasticity (STDP), is proposed to perform a 2D co-ordinate transformation of the polar representation of an arm position to a Cartesian representation, to create a virtual image map of a haptic input. Through the visual pathway, a position signal corresponding to the haptic input is used to train the SNN with STDP synapses such that after learning the SNN can perform the co-ordinate transformation to generate a representation of the haptic input with the same co-ordinates as a visual image. The model can be applied to explain co-ordinate transformation in spiking neuron based systems. The principle can be used in artificial intelligent systems to process complex co-ordinate transformations represented by biological stimuli.

ON SOFT D2-ALGEBRA AND SOFT D2-IDEALS

OpenAIRE

S. Subramanian; S. Seethalaksmi

2018-01-01

In this paper, we have studied some characterization of soft D2-algebra, kernel, intersection, image, quotient D2-algebra’s and relations ship between D2-algebra and D2-ideals with suitable examples.

Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons.

Science.gov (United States)

Yapo, Cedric; Nair, Anu G; Clement, Lorna; Castro, Liliana R; Hellgren Kotaleski, Jeanette; Vincent, Pierre

2017-12-15

Brief dopamine events are critical actors of reward-mediated learning in the striatum; the intracellular cAMP-protein kinase A (PKA) response of striatal medium spiny neurons to such events was studied dynamically using a combination of biosensor imaging in mouse brain slices and in silico simulations. Both D1 and D2 medium spiny neurons can sense brief dopamine transients in the sub-micromolar range. While dopamine transients profoundly change cAMP levels in both types of medium spiny neurons, the PKA-dependent phosphorylation level remains unaffected in D2 neurons. At the level of PKA-dependent phosphorylation, D2 unresponsiveness depends on protein phosphatase-1 (PP1) inhibition by DARPP-32. Simulations suggest that D2 medium spiny neurons could detect transient dips in dopamine level. The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of the dopamine effect on intracellular signalling remains poorly understood. We used genetically encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation levels, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D 1 or D 2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively. Transient dopamine showed similar sub-micromolar efficacies on cAMP in both D1 and D2 MSNs, thus challenging the commonly accepted notion that dopamine efficacy is much higher on D 2 than on D 1 receptors. However, in D2 MSNs, the large decrease in cAMP level triggered by transient dopamine did not translate to a decrease in PKA-dependent phosphorylation level, owing to the efficient inhibition of protein phosphatase 1 by DARPP-32. Simulations further suggested that D2 MSNs can also operate in a 'tone-sensing' mode, allowing them to detect transient dips in basal dopamine

Conceptualization of an R&D Based Learning-to-Innovate Model for Science Education

Science.gov (United States)

Lai, Oiki Sylvia

2013-01-01

The purpose of this research was to conceptualize an R & D based learning-to-innovate (LTI) model. The problem to be addressed was the lack of a theoretical L TI model, which would inform science pedagogy. The absorptive capacity (ACAP) lens was adopted to untangle the R & D LTI phenomenon into four learning processes: problem-solving via…

Activation of dopamine D3 receptors inhibits reward-related learning induced by cocaine.

Science.gov (United States)

Kong, H; Kuang, W; Li, S; Xu, M

2011-03-10

Memories of learned associations between the rewarding properties of drugs and environmental cues contribute to craving and relapse in humans. The mesocorticolimbic dopamine (DA) system is involved in reward-related learning induced by drugs of abuse. DA D3 receptors are preferentially expressed in mesocorticolimbic DA projection areas. Genetic and pharmacological studies have shown that DA D3 receptors suppress locomotor-stimulant effects of cocaine and reinstatement of cocaine-seeking behaviors. Activation of the extracellular signal-regulated kinase (ERK) induced by acute cocaine administration is also inhibited by D3 receptors. How D3 receptors modulate cocaine-induced reward-related learning and associated changes in cell signaling in reward circuits in the brain, however, have not been fully investigated. In the present study, we show that D3 receptor mutant mice exhibit potentiated acquisition of conditioned place preference (CPP) at low doses of cocaine compared to wild-type mice. Activation of ERK and CaMKIIα, but not the c-Jun N-terminal kinase and p38, in the nucleus accumbens, amygdala and prefrontal cortex is also potentiated in D3 receptor mutant mice compared to that in wild-type mice following CPP expression. These results support a model in which D3 receptors modulate reward-related learning induced by low doses of cocaine by inhibiting activation of ERK and CaMKIIα in reward circuits in the brain. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Differentiation of Forebrain and Hippocampal Dopamine 1-Class Receptors, D1R and D5R, in Spatial Learning and Memory

Science.gov (United States)

Sariñana, Joshua; Tonegawa, Susumu

2017-01-01

Activation of prefrontal cortical (PFC), striatal, and hippocampal dopamine 1-class receptors (D1R and D5R) is necessary for normal spatial information processing. Yet the precise role of the D1R versus the D5R in the aforementioned structures, and their specific contribution to the water-maze spatial learning task remains unknown. D1R- and D5R- specific in situ hybridization probes showed that forebrain restricted D1R and D5R KO mice (F-D1R/D5R KO) displayed D1R mRNA deletion in the medial (m)PFC, dorsal and ventral striatum, and the dentate gyrus (DG) of the hippocampus. D5R mRNA deletion was limited to the mPFC, the CA1 and DG hippocampal subregions. F-D1R/D5R KO mice were given water-maze training and displayed subtle spatial latency differences between genotypes and spatial memory deficits during both regular and reversal training. To differentiate forebrain D1R from D5R activation, forebrain restricted D1R KO (F-D1R KO) and D5R KO (F-D5R KO) mice were trained on the water-maze task. F-D1R KO animals exhibited escape latency deficits throughout regular and reversal training as well as spatial memory deficits during reversal training. F-D1R KO mice also showed perseverative behavior during the reversal spatial memory probe test. In contrast, F-D5R KO animals did not present observable deficits on the water-maze task. Because F-D1R KO mice showed water-maze deficits we tested the necessity of hippocampal D1R activation for spatial learning and memory. We trained DG restricted D1R KO (DG-D1R KO) mice on the water-maze task. DG-D1R KO mice did not present detectable spatial memory deficit, but did show subtle deficits during specific days of training. Our data provides evidence that forebrain D5R activation plays a unique role in spatial learning and memory in conjunction with D1R activation. Moreover, these data suggest that mPFC and striatal, but not DG D1R activation are essential for spatial learning and memory. PMID:26174222

Proceedings of the 2nd Workshop on Awareness and Reflection in Technology-Enhanced Learning

NARCIS (Netherlands)

Moore, Adam; Pammer, Viktoria; Pannese, Lucia; Prilla, Michael; Rajagopal, Kamakshi; Reinhardt, Wolfgang; Ullman, Thomas; Voigt, Christian

2013-01-01

Moore, A., Pammer, V., Pannese, L., Prilla, M., Rajagopal, K., Reinhardt, W., Ullman, Th. D., & Voigt, Ch. (Eds.) (2012). Proceedings of the 2nd Workshop on Awareness and Reflection in Technology Enhanced Learning. In conjunction with the 7th European Conference on Technology Enhanced Learning: 21st

Unparticle Example in 2D

International Nuclear Information System (INIS)

Georgi, Howard; Kats, Yevgeny

2008-01-01

We discuss what can be learned about unparticle physics by studying simple quantum field theories in one space and one time dimension. We argue that the exactly soluble 2D theory of a massless fermion coupled to a massive vector boson, the Sommerfield model, is an interesting analog of a Banks-Zaks model, approaching a free theory at high energies and a scale-invariant theory with nontrivial anomalous dimensions at low energies. We construct a toy standard model coupling to the fermions in the Sommerfield model and study how the transition from unparticle behavior at low energies to free particle behavior at high energies manifests itself in interactions with the toy standard model particles

Navigation and wayfinding in learning spaces in 3D virtual worlds

OpenAIRE

Minocha, Shailey; Hardy, Christopher

2016-01-01

There is a lack of published research on the design guidelines of learning spaces in virtual worlds. Therefore, when institutions aspire to create learning spaces in Second Life, there are few studies or guidelines to inform them except for individual case studies. The Design of Learning Spaces in 3D Virtual Environments (DELVE) project, funded by the Joint Information Systems Committee in the UK, was one of the first initiatives that identified through empirical investigations the usability ...

Assessing 3D Virtual World Disaster Training Through Adult Learning Theory

Directory of Open Access Journals (Sweden)

Lee Taylor-Nelms

2014-10-01

Full Text Available As role-play, virtual reality, and simulated environments gain popularity through virtual worlds such as Second Life, the importance of identifying best practices for education and emergency management training becomes necessary. Using a formal needs assessment approach, we examined the extent to which 3D virtual tornado simulation trainings follow the principles of adult learning theory employed by the Federal Emergency Management Agency's (FEMA National Training and Education Division. Through a three-fold methodology of observation, interviews, and reflection on action, 3D virtual world tornado trainings were analyzed for congruence to adult learning theory.

3D Virtual Learning Environments in Education: A Meta-Review

Science.gov (United States)

Reisoglu, I.; Topu, B.; Yilmaz, R.; Karakus Yilmaz, T.; Göktas, Y.

2017-01-01

The aim of this study is to investigate recent empirical research studies about 3D virtual learning environments. A total of 167 empirical studies that involve the use of 3D virtual worlds in education were examined by meta-review. Our findings show that the "Second Life" platform has been frequently used in studies. Among the reviewed…

Web3D Technologies in Learning, Education and Training: Motivations, Issues, Opportunities

Science.gov (United States)

Chittaro, Luca; Ranon, Roberto

2007-01-01

Web3D open standards allow the delivery of interactive 3D virtual learning environments through the Internet, reaching potentially large numbers of learners worldwide, at any time. This paper introduces the educational use of virtual reality based on Web3D technologies. After briefly presenting the main Web3D technologies, we summarize the…

From 2D to 3D turbulence through 2D3C configurations

Science.gov (United States)

Buzzicotti, Michele; Biferale, Luca; Linkmann, Moritz

2017-11-01

We study analytically and numerically the geometry of the nonlinear interactions and the resulting energy transfer directions of 2D3C flows. Through a set of suitably designed Direct Numerical Simulations we also study the coupling between several 2D3C flows, where we explore the transition between 2D and fully 3D turbulence. In particular, we find that the coupling of three 2D3C flows on mutually orthogonal planes subject to small-scale forcing leads to a stationary 3D out-of-equilibrium dynamics at the energy containing scales where the inverse cascade is directly balanced by a forward cascade carried by a different subsets of interactions. ERC AdG Grant No 339032 NewTURB.

Analysis of students’ spatial thinking in geometry: 3D object into 2D representation

Science.gov (United States)

Fiantika, F. R.; Maknun, C. L.; Budayasa, I. K.; Lukito, A.

2018-05-01

The aim of this study is to find out the spatial thinking process of students in transforming 3-dimensional (3D) object to 2-dimensional (2D) representation. Spatial thinking is helpful in using maps, planning routes, designing floor plans, and creating art. The student can engage geometric ideas by using concrete models and drawing. Spatial thinking in this study is identified through geometrical problems of transforming a 3-dimensional object into a 2-dimensional object image. The problem was resolved by the subject and analyzed by reference to predetermined spatial thinking indicators. Two representative subjects of elementary school were chosen based on mathematical ability and visual learning style. Explorative description through qualitative approach was used in this study. The result of this study are: 1) there are different representations of spatial thinking between a boy and a girl object, 2) the subjects has their own way to invent the fastest way to draw cube net.

Activated sludge model No. 2d, ASM2d

DEFF Research Database (Denmark)

Henze, M.

1999-01-01

The Activated Sludge Model No. 2d (ASM2d) presents a model for biological phosphorus removal with simultaneous nitrification-denitrification in activated sludge systems. ASM2d is based on ASM2 and is expanded to include the denitrifying activity of the phosphorus accumulating organisms (PAOs......). This extension of ASM2 allows for improved modeling of the processes, especially with respect to the dynamics of nitrate and phosphate. (C) 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved....

Student perceptions and effectiveness of an innovative learning tool: Anatomy Glove Learning System.

Science.gov (United States)

Lisk, Kristina; McKee, Pat; Baskwill, Amanda; Agur, Anne M R

2015-01-01

A trend in anatomical education is the development of alternative pedagogical approaches to replace or complement experiences in a cadaver laboratory; however, empirical evidence on their effectiveness is often not reported. This study aimed to evaluate the effectiveness of Anatomy Glove Learning System (AGLS), which enables students to learn the relationship between hand structure and function by drawing the structures onto a worn glove with imprinted bones. Massage therapy students (n = 73) were allocated into two groups and drew muscles onto either: (1) the glove using AGLS instructional videos (3D group); or (2) paper with palmar/dorsal views of hand bones during an instructor-guided activity (2D group). A self-confidence measure and knowledge test were completed before, immediately after, and one-week following the learning conditions. Self-confidence of hand anatomy in the 3D group gradually increased (3.2/10, 4.7/10, and 4.8/10), whereas self-confidence in the 2D group began to decline one-week later (3.2/10, 4.4/10, and 3.9/10). Knowledge of hand anatomy improved in both groups immediately after learning, (P learning tool (mean = 8.6 ± 2.2). This study provides evidence demonstrating that AGLS and the traditional 2D learning approach are equally effective in promoting students' self-confidence and knowledge of hand anatomy. © 2014 American Association of Anatomists.

The 3D Digital Story-telling Media on Batik Learning in Vocational High Schools

Science.gov (United States)

Widiaty, I.; Achdiani, Y.; Kuntadi, I.; Mubaroq, S. R.; Zakaria, D.

2018-02-01

The aim of this research is to make 3D digital Story-telling Media on Batik Learning in Vocational High School. The digital story-telling developed in this research is focused on 3D-based story-telling. In contrast to the digital story-telling that has been developed in existing learning, this research is expected to be able to improve understanding of vocational students about the value of local wisdom batik more meaningful and “live”. The process of making 3D digital story-telling media consists of two processes, namely the creation of 3D objects and the creation of 3D object viewer.

Impact of the 3-D model strategy on science learning of the solar system

Science.gov (United States)

Alharbi, Mohammed

The purpose of this mixed method study, quantitative and descriptive, was to determine whether the first-middle grade (seventh grade) students at Saudi schools are able to learn and use the Autodesk Maya software to interact and create their own 3-D models and animations and whether their use of the software influences their study habits and their understanding of the school subject matter. The study revealed that there is value to the science students regarding the use of 3-D software to create 3-D models to complete science assignments. Also, this study aimed to address the middle-school students' ability to learn 3-D software in art class, and then ultimately use it in their science class. The success of this study may open the way to consider the impact of 3-D modeling on other school subjects, such as mathematics, art, and geography. When the students start using graphic design, including 3-D software, at a young age, they tend to develop personal creativity and skills. The success of this study, if applied in schools, will provide the community with skillful young designers and increase awareness of graphic design and the new 3-D technology. Experimental method was used to answer the quantitative research question, are there significant differences applying the learning method using 3-D models (no 3-D, premade 3-D, and create 3-D) in a science class being taught about the solar system and its impact on the students' science achievement scores? Descriptive method was used to answer the qualitative research questions that are about the difficulty of learning and using Autodesk Maya software, time that students take to use the basic levels of Polygon and Animation parts of the Autodesk Maya software, and level of students' work quality.

From eLearning to Digital Transformation: A Framework and Implications for L&D

OpenAIRE

Seufert, Sabine; Meier, Christoph

2016-01-01

How can the learning function (L&D) support learning and innovation ability of the entire organization in times of digital transformation? The core challenges for the learning function are twofold. Competence clarification: What are relevant “digital competences” in terms of knowledge, skills and attitudes that employees need in order to cope with digital transformation? Competence development: How to organize, design and support learning processes contributing to digital competences and digi...

On QCD Q2-evolution of deuteron structure function F2D(xD, Q2) for xD>1

International Nuclear Information System (INIS)

Sidorov, A.V.; Tokarev, M.V.

1995-01-01

The deep-inelastic deuteron structure function (SF) F 2 D (x D ,Q 2 ) in the covariant approach in light-cone variables is considered. The x D and Q 2 -dependences of SF are calculated. The QCD analysis of generated data both for non-cumulative x D D >1 ranges was performed. It was shown that Q 2 -evolution of SF is valid for ranges 0.275 D D D -dependence of SF for the ranges is essentially different. 23 refs., 2 figs., 1 tab

3D vs 2D laparoscopic systems: Development of a performance quantitative validation model.

Science.gov (United States)

Ghedi, Andrea; Donarini, Erica; Lamera, Roberta; Sgroi, Giovanni; Turati, Luca; Ercole, Cesare

2015-01-01

The new technology ensures 3D laparoscopic vision by adding depth to the traditional two dimensions. This realistic vision gives the surgeon the feeling of operating in real space. Hospital of Treviglio-Caravaggio isn't an university or scientific institution; in 2014 a new 3D laparoscopic technology was acquired therefore it led to evaluation of the of the appropriateness in term of patient outcome and safety. The project aims at achieving the development of a quantitative validation model that would ensure low cost and a reliable measure of the performance of 3D technology versus 2D mode. In addition, it aims at demonstrating how new technologies, such as open source hardware and software and 3D printing, could help research with no significant cost increase. For these reasons, in order to define criteria of appropriateness in the use of 3D technologies, it was decided to perform a study to technically validate the use of the best technology in terms of effectiveness, efficiency and safety in the use of a system between laparoscopic vision in 3D and the traditional 2D. 30 surgeons were enrolled in order to perform an exercise through the use of laparoscopic forceps inside a trainer. The exercise consisted of having surgeons with different level of seniority, grouped by type of specialization (eg. surgery, urology, gynecology), exercising videolaparoscopy with two technologies (2D and 3D) through the use of a anthropometric phantom. The target assigned to the surgeon was that to pass "needle and thread" without touching the metal part in the shortest time possible. The rings selected for the exercise had each a coefficient of difficulty determined by depth, diameter, angle from the positioning and from the point of view. The analysis of the data collected from the above exercise has mathematically confirmed that the 3D technique ensures a learning curve lower in novice and greater accuracy in the performance of the task with respect to 2D.

Presynaptic D2 dopamine receptors control long-term depression expression and memory processes in the temporal hippocampus.

Science.gov (United States)

Rocchetti, Jill; Isingrini, Elsa; Dal Bo, Gregory; Sagheby, Sara; Menegaux, Aurore; Tronche, François; Levesque, Daniel; Moquin, Luc; Gratton, Alain; Wong, Tak Pan; Rubinstein, Marcelo; Giros, Bruno

2015-03-15

Dysfunctional mesocorticolimbic dopamine signaling has been linked to alterations in motor and reward-based functions associated with psychiatric disorders. Converging evidence from patients with psychiatric disorders and use of antipsychotics suggests that imbalance of dopamine signaling deeply alters hippocampal functions. However, given the lack of full characterization of a functional mesohippocampal pathway, the precise role of dopamine transmission in memory deficits associated with these disorders and their dedicated therapies is unknown. In particular, the positive outcome of antipsychotic treatments, commonly antagonizing D2 dopamine receptors (D2Rs), on cognitive deficits and memory impairments remains questionable. Following pharmacologic and genetic manipulation of dopamine transmission, we performed anatomic, neurochemical, electrophysiologic, and behavioral investigations to uncover the role of D2Rs in hippocampal-dependent plasticity and learning. Naïve mice (n = 4-21) were used in the different procedures. Dopamine modulated both long-term potentiation and long-term depression in the temporal hippocampus as well as spatial and recognition learning and memory in mice through D2Rs. Although genetic deletion or pharmacologic blockade of D2Rs led to the loss of long-term potentiation expression, the specific genetic removal of presynaptic D2Rs impaired long-term depression and performances on spatial memory tasks. Presynaptic D2Rs in dopamine fibers of the temporal hippocampus tightly modulate long-term depression expression and play a major role in the regulation of hippocampal learning and memory. This direct role of mesohippocampal dopamine input as uncovered here adds a new dimension to dopamine involvement in the physiology underlying deficits associated with neuropsychiatric disorders. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Emergent learning and learning ecologies in Web 2.0

OpenAIRE

Williams, Roy; Karousou, Regina; Mackness, J.

2011-01-01

This paper describes emergent learning and situates it within learning networks and systems and the broader learning ecology of Web 2.0. It describes the nature of emergence and emergent learning and the conditions that enable emergent, self-organised learning to occur and to flourish. Specifically, it explores whether emergent learning can be validated and self-correcting and whether it is possible to link or integrate emergent and prescribed learning. It draws on complexity theory, commu...

Facilitating role of 3D multimodal visualization and learning rehearsal in memory recall.

Science.gov (United States)

Do, Phuong T; Moreland, John R

2014-04-01

The present study investigated the influence of 3D multimodal visualization and learning rehearsal on memory recall. Participants (N = 175 college students ranging from 21 to 25 years) were assigned to different training conditions and rehearsal processes to learn a list of 14 terms associated with construction of a wood-frame house. They then completed a memory test determining their cognitive ability to free recall the definitions of the 14 studied terms immediately after training and rehearsal. The audiovisual modality training condition was associated with the highest accuracy, and the visual- and auditory-modality conditions with lower accuracy rates. The no-training condition indicated little learning acquisition. A statistically significant increase in performance accuracy for the audiovisual condition as a function of rehearsal suggested the relative importance of rehearsal strategies in 3D observational learning. Findings revealed the potential application of integrating virtual reality and cognitive sciences to enhance learning and teaching effectiveness.

The Development of a Virtual 3D Model of the Renal Corpuscle from Serial Histological Sections for E-Learning Environments

Science.gov (United States)

Roth, Jeremy A.; Wilson, Timothy D.; Sandig, Martin

2015-01-01

Histology is a core subject in the anatomical sciences where learners are challenged to interpret two-dimensional (2D) information (gained from histological sections) to extrapolate and understand the three-dimensional (3D) morphology of cells, tissues, and organs. In gross anatomical education 3D models and learning tools have been associated…

A Collaborative Virtual Environment for Situated Language Learning Using VEC3D

Science.gov (United States)

Shih, Ya-Chun; Yang, Mau-Tsuen

2008-01-01

A 3D virtually synchronous communication architecture for situated language learning has been designed to foster communicative competence among undergraduate students who have studied English as a foreign language (EFL). We present an innovative approach that offers better e-learning than the previous virtual reality educational applications. The…

The Effectiveness of a 3D Computerized Tutorial to Enhance Learning of the Canine Larynx and Hyoid Apparatus.

Science.gov (United States)

Nemanic, Sarah; Mills, Serena; Viehdorfer, Matt; Clark, Terri; Bailey, Mike

Teaching the anatomy of the canine larynx and hyoid apparatus is challenging because dissection disassembles and/or damages these structures, making it difficult to understand their three-dimensional (3D) anatomy and spatial interrelationships. This study assessed the effectiveness of an interactive, computerized 3D tutorial for teaching the anatomy of the canine larynx and hyoid apparatus using a randomized control design with students enrolled in the first-year professional program at Oregon State University College of Veterinary Medicine. All first-year students from 2 consecutive years were eligible. All students received the traditional methods of didactic teaching and dissection to learn the anatomy of the canine larynx and hyoid apparatus, after which they were divided into two statistically equal groups based on their cumulative anatomy test scores from the prior term. The tutorial group received an interactive, computerized tutorial developed by the investigators containing 3D images of the canine larynx and hyoid apparatus, while the control group received the same 3D images without the computerized tutorial. Both groups received the same post-learning assessment and survey. Sixty-three first-year students participated in the study, 28 in the tutorial group, and 35 in the control group. Post-learning assessment and survey scores were both significantly higher among students in the computerized tutorial group than those in the control group. This study demonstrates that a 3D computerized tutorial is more effective in teaching the anatomy of the canine hyoid apparatus and larynx than 3D images without a tutorial. Students likewise rated their learning experience higher when using the 3D computerized tutorial.

Manganese-Disrupted Interaction of Dopamine D1 and NMDAR in the Striatum to Injury Learning and Memory Ability of Mice.

Science.gov (United States)

Song, Qifan; Deng, Yu; Yang, Xinxin; Bai, Ying; Xu, Bin; Liu, Wei; Zheng, Wenxue; Wang, Can; Zhang, Meng; Xu, Zhaofa

2016-12-01

Manganese (Mn) is widely regarded as a neurotoxic heavy metal that causes learning and memory deficits. Recently, it has been proved that the striatum is related to memory and learning ability. However, no previous study focused on the effect of Mn-induced learning and memory deficits on the striatum. This study aims to investigate the probable interaction of dopamine D1 receptor (DR1) and N-methyl-D-aspartate receptor (NMDAR), two cognition-related receptors in the striatum during Mn exposure. Mice are randomly divided into four groups, including control group, 12.5 mg/kg MnCl 2 group, 25 mg/kg MnCl 2 group, and 50 mg/kg MnCl 2 group. The mice receive intraperitoneal injections of 0, 12.5, 25, and 50 mg/kg MnCl 2 once daily for 2 weeks. Then, learning and memory ability, pathological changes, expression, and interaction of DR1 and NMDAR are determined. It has been found that Mn disrupted spatial learning and memory ability of mice by Morris water maze test and the passive avoidance test. Pathological and ultrastructure were injured. Mn decreased the immunohistochemical activities, protein levels, and messenger RNA (mRNA) expression of DR1, NR1, and NR2A. Mn exposure inhibited interaction between DR1 and NMDAR in striatum by double immunofluorescent staining and co-immunoprecipitation. In conclusion, our study illustrated that Mn caused learning and memory dysfunction via injury of striatum and inhibition of interaction between DR1 and NMDAR in striatum.

Astrobiology Learning Progressions: Linking Astrobiology Concepts with the 3D Learning Paradigm of NGSS

Science.gov (United States)

Scalice, D.; Davis, H. B.; Leach, D.; Chambers, N.

2016-12-01

The Next Generation Science Standards (NGSS) introduce a Framework for teaching and learning with three interconnected "dimensions:" Disciplinary Core Ideas (DCI's), Cross-cutting Concepts (CCC's), and Science and Engineering Practices (SEP's). This "3D" Framework outlines progressions of learning from K-12 based on the DCI's, detailing which parts of a concept should be taught at each grade band. We used these discipline-based progressions to synthesize interdisciplinary progressions for core concepts in astrobiology, such as the origins of life, what makes a world habitable, biosignatures, and searching for life on other worlds. The final product is an organizing tool for lesson plans, learning media, and other educational materials in astrobiology, as well as a fundamental resource in astrobiology education that serves both educators and scientists as they plan and carry out their programs for learners.

An Annotated Bibliography of Accelerated Learning

Science.gov (United States)

Garcia, GNA

2007-01-01

A rich narrative-style bibliography of accelerated learning (reviewing six articles published between 1995-2003). Articles reviewed include: (1) Accelerative learning and the Emerging Science of Wholeness (D. D. Beale); (2) Effective Teaching in Accelerated Learning Programs (D. Boyd); (3) A Critical Theory Perspective on Accelerated Learning (S.…

Use of Colour and Interactive Animation in Learning 3D Vectors

Science.gov (United States)

Iskander, Wejdan; Curtis, Sharon

2005-01-01

This study investigated the effects of two computer-implemented techniques (colour and interactive animation) on learning 3D vectors. The participants were 43 female Saudi Arabian high school students. They were pre-tested on 3D vectors using a paper questionnaire that consisted of calculation and visualization types of questions. The students…

Synergistic effects of dopamine D2-like receptor antagonist sulpiride and beta-blocker propranolol on learning in the Carousel maze, a dry-land spatial navigation task

Czech Academy of Sciences Publication Activity Database

Prokopová, Iva; Bahník, Štěpán; Doulames, Vanessa; Valeš, Karel; Petrásek, Tomáš; Svoboda, Jan; Stuchlík, Aleš

2012-01-01

Roč. 102, č. 1 (2012), s. 151-156 ISSN 0091-3057 R&D Projects: GA ČR(CZ) GCP303/10/J032; GA ČR(CZ) GBP304/12/G069; GA MZd(CZ) NT13386 Institutional research plan: CEZ:AV0Z50110509 Institutional support: RVO:67985823 Keywords : learning * behavioral pharmacology * behavior Subject RIV: FH - Neurology Impact factor: 2.608, year: 2012

WE-AB-BRA-07: Quantitative Evaluation of 2D-2D and 2D-3D Image Guided Radiation Therapy for Clinical Trial Credentialing, NRG Oncology/RTOG

Energy Technology Data Exchange (ETDEWEB)

Giaddui, T; Yu, J; Xiao, Y [Thomas Jefferson University, Philadelphia, PA (United States); Jacobs, P [MIM Software, Inc, Cleavland, Ohio (United States); Manfredi, D; Linnemann, N [IROC Philadelphia, RTQA Center, Philadelphia, PA (United States)

2015-06-15

Purpose: 2D-2D kV image guided radiation therapy (IGRT) credentialing evaluation for clinical trial qualification was historically qualitative through submitting screen captures of the fusion process. However, as quantitative DICOM 2D-2D and 2D-3D image registration tools are implemented in clinical practice for better precision, especially in centers that treat patients with protons, better IGRT credentialing techniques are needed. The aim of this work is to establish methodologies for quantitatively reviewing IGRT submissions based on DICOM 2D-2D and 2D-3D image registration and to test the methodologies in reviewing 2D-2D and 2D-3D IGRT submissions for RTOG/NRG Oncology clinical trials qualifications. Methods: DICOM 2D-2D and 2D-3D automated and manual image registration have been tested using the Harmony tool in MIM software. 2D kV orthogonal portal images are fused with the reference digital reconstructed radiographs (DRR) in the 2D-2D registration while the 2D portal images are fused with DICOM planning CT image in the 2D-3D registration. The Harmony tool allows alignment of the two images used in the registration process and also calculates the required shifts. Shifts calculated using MIM are compared with those submitted by institutions for IGRT credentialing. Reported shifts are considered to be acceptable if differences are less than 3mm. Results: Several tests have been performed on the 2D-2D and 2D-3D registration. The results indicated good agreement between submitted and calculated shifts. A workflow for reviewing these IGRT submissions has been developed and will eventually be used to review IGRT submissions. Conclusion: The IROC Philadelphia RTQA center has developed and tested a new workflow for reviewing DICOM 2D-2D and 2D-3D IGRT credentialing submissions made by different cancer clinical centers, especially proton centers. NRG Center for Innovation in Radiation Oncology (CIRO) and IROC RTQA center continue their collaborative efforts to enhance

WE-AB-BRA-07: Quantitative Evaluation of 2D-2D and 2D-3D Image Guided Radiation Therapy for Clinical Trial Credentialing, NRG Oncology/RTOG

International Nuclear Information System (INIS)

Giaddui, T; Yu, J; Xiao, Y; Jacobs, P; Manfredi, D; Linnemann, N

2015-01-01

Purpose: 2D-2D kV image guided radiation therapy (IGRT) credentialing evaluation for clinical trial qualification was historically qualitative through submitting screen captures of the fusion process. However, as quantitative DICOM 2D-2D and 2D-3D image registration tools are implemented in clinical practice for better precision, especially in centers that treat patients with protons, better IGRT credentialing techniques are needed. The aim of this work is to establish methodologies for quantitatively reviewing IGRT submissions based on DICOM 2D-2D and 2D-3D image registration and to test the methodologies in reviewing 2D-2D and 2D-3D IGRT submissions for RTOG/NRG Oncology clinical trials qualifications. Methods: DICOM 2D-2D and 2D-3D automated and manual image registration have been tested using the Harmony tool in MIM software. 2D kV orthogonal portal images are fused with the reference digital reconstructed radiographs (DRR) in the 2D-2D registration while the 2D portal images are fused with DICOM planning CT image in the 2D-3D registration. The Harmony tool allows alignment of the two images used in the registration process and also calculates the required shifts. Shifts calculated using MIM are compared with those submitted by institutions for IGRT credentialing. Reported shifts are considered to be acceptable if differences are less than 3mm. Results: Several tests have been performed on the 2D-2D and 2D-3D registration. The results indicated good agreement between submitted and calculated shifts. A workflow for reviewing these IGRT submissions has been developed and will eventually be used to review IGRT submissions. Conclusion: The IROC Philadelphia RTQA center has developed and tested a new workflow for reviewing DICOM 2D-2D and 2D-3D IGRT credentialing submissions made by different cancer clinical centers, especially proton centers. NRG Center for Innovation in Radiation Oncology (CIRO) and IROC RTQA center continue their collaborative efforts to enhance

Acute D2/D3 dopaminergic agonism but chronic D2/D3 antagonism prevents NMDA antagonist neurotoxicity.

Science.gov (United States)

Farber, Nuri B; Nemmers, Brian; Noguchi, Kevin K

2006-09-15

Antagonists of the N-methyl-D-aspartate (NMDA) glutamate receptor, most likely by producing disinhibtion in complex circuits, acutely produce psychosis and cognitive disturbances in humans, and neurotoxicity in rodents. Studies examining NMDA Receptor Hypofunction (NRHypo) neurotoxicity in animals, therefore, may provide insights into the pathophysiology of psychotic disorders. Dopaminergic D2 and/or D3 agents can modify psychosis over days to weeks, suggesting involvement of these transmitter system(s). We studied the ability of D2/D3 agonists and antagonists to modify NRHypo neurotoxicity both after a one-time acute exposure and after chronic daily exposure. Here we report that D2/D3 dopamine agonists, probably via D3 receptors, prevent NRHypo neurotoxicity when given acutely. The protective effect with D2/D3 agonists is not seen after chronic daily dosing. In contrast, the antipsychotic haloperidol does not affect NRHypo neurotoxicity when given acutely at D2/D3 doses. However, after chronic daily dosing of 1, 3, or 5 weeks, haloperidol does prevent NRHypo neurotoxicity with longer durations producing greater protection. Understanding the changes that occur in the NRHypo circuit after chronic exposure to dopaminergic agents could provide important clues into the pathophysiology of psychotic disorders.

TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4

NARCIS (Netherlands)

Sharples, Paul; Popat, Kris; Llobet, Lau; Santos, Patricia; Hernández-Leo, Davinia; Miao, Yongwu; Griffiths, David; Beauvoir, Phillip

2010-01-01

Sharples, P., Popat, K., Llobet, L., Santos, P., Hernandez-Leo, D., Miao, Y., Griffiths, D. & Beauvoir, P. (2009) TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4 This release is composed of three files corresponding to CopperCore Service Integration (CCSI) v3.2-10cv1.4,

Eco-Dialogical Learning and Translanguaging in Open-Ended 3D Virtual Learning Environments: Where Place, Time, and Objects Matter

Science.gov (United States)

Zheng, Dongping; Schmidt, Matthew; Hu, Ying; Liu, Min; Hsu, Jesse

2017-01-01

The purpose of this research was to explore the relationships between design, learning, and translanguaging in a 3D collaborative virtual learning environment for adolescent learners of Chinese and English. We designed an open-ended space congruent with ecological and dialogical perspectives on second language acquisition. In such a space,…

2nd international KES conference on Smart Education and Smart e-Learning

CERN Document Server

Howlett, Robert; Jain, Lakhmi

2015-01-01

This book contains the contributions presented at the 2nd international KES conference on Smart Education and Smart e-Learning, which took place in Sorrento, Italy, June 17-19, 2015. It contains a total of 45 peer-reviewed book chapters that are grouped into several parts: Part 1 - Smart Education, Part 2 – Smart Educational Technology, Part 3 – Smart e-Learning, Part 4 – Smart Professional Training and Teachers’ Education, and Part 5 – Smart Teaching and Training related Topics.  This book can be a useful source of research data and valuable information for faculty, scholars, Ph.D. students, administrators, and practitioners  - those who are interested in innovative areas of smart education and smart e-learning.  .

Experiments with a methodology to model the role of R and D expenditures in energy technology learning processes; first results

International Nuclear Information System (INIS)

Miketa, Asami; Schrattenholzer, Leo

2004-01-01

This paper presents the results of using a stylized optimization model of the global electricity supply system to analyze the optimal research and development (R and D) support for an energy technology. The model takes into account the dynamics of technological progress as described by a so-called two-factor learning curve (2FLC). The two factors are cumulative experience ('learning by doing') and accumulated knowledge ('learning by searching'); the formulation is a straightforward expansion of conventional one-factor learning curves, in which only cumulative experience is included as a factor, which aggregates the effects of accumulated knowledge and cumulative experience, among others. The responsiveness of technological progress to the two factors is quantified using learning parameters, which are estimated using empirical data. Sensitivities of the model results to the parameters are also tested. The model results also address the effect of competition between technologies and of CO 2 constraints. The results are mainly methodological; one of the most interesting is that, at least up to a point, competition between technologies - in terms of both market share and R and D support - need not lead to 'lock-in' or 'crowding-out'

Experiments with a methodology to model the role of R and D expenditures in energy technology learning processes: first results

International Nuclear Information System (INIS)

Miketa, A.; Schrattenholzer, L.

2004-01-01

This paper presents the results of using a stylized optimization model of the global electricity supply system to analyze the optimal research and development (R and D) support for an energy technology. The model takes into account the dynamics of technological progress as described by a so-called two-factor learning curve (2FLC). The two factors are cumulative experience (''learning by doing'') and accumulated knowledge (''learning by searching''); the formulation is a straightforward expansion of conventional one-factor learning curves, in which only cumulative experience is included as a factor, which aggregates the effects of accumulated knowledge and cumulative experience, among others. The responsiveness of technological progress to the two factors is quantified using learning parameters, which are estimated using empirical data. Sensitivities of the model results to the parameters are also tested. The model results also address the effect of competition between technologies and of CO 2 constraints. The results are mainly methodological; one of the most interesting is that, at least up to a point, competition between technologies-in terms of both market share and R and D support-need not lead to ''lock-in'' or ''crowding-out''. (author)

Peer Mentorship and Transformational Learning: PhD Student Experiences

Science.gov (United States)

Preston, Jane P.; Ogenchuk, Marcella J.; Nsiah, Joseph K.

2014-01-01

The purpose of the paper is to describe our peer mentorship experiences and explain how these experiences fostered transformational learning during our PhD graduate program in educational administration. As a literature backdrop, we discuss characteristics of traditional forms of mentorship and depict how our experiences of peer mentorship was…

Immersive Learning Environment Using 3D Virtual Worlds and Integrated Remote Experimentation

Directory of Open Access Journals (Sweden)

Roderval Marcelino

2013-01-01

Full Text Available This project seeks to demonstrate the use of remote experimentation and 3D virtual environments applied to the teaching-learning in the areas of exact sciences-physics. In proposing the combination of remote experimentation and 3D virtual worlds in teaching-learning process, we intend to achieve greater geographic coverage, contributing to the construction of new methodologies of teaching support, speed of access and foremost motivation for students to continue in scientific study of the technology areas. The proposed architecture is based on a model implemented fully featured open source and open hardware. The virtual world was built in OpenSim software and integrated it a remote physics experiment called "electrical panel". Accessing the virtual world the user has total control of the experiment within the 3D virtual world.

Enhancement of Online Robotics Learning Using Real-Time 3D Visualization Technology

OpenAIRE

Richard Chiou; Yongjin (james) Kwon; Tzu-Liang (bill) Tseng; Robin Kizirian; Yueh-Ting Yang

2010-01-01

This paper discusses a real-time e-Lab Learning system based on the integration of 3D visualization technology with a remote robotic laboratory. With the emergence and development of the Internet field, online learning is proving to play a significant role in the upcoming era. In an effort to enhance Internet-based learning of robotics and keep up with the rapid progression of technology, a 3- Dimensional scheme of viewing the robotic laboratory has been introduced in addition to the remote c...

Relating R and D and investment policies to CCS market diffusion through two-factor learning

International Nuclear Information System (INIS)

Lohwasser, Richard; Madlener, Reinhard

2013-01-01

Carbon capture and storage (CCS) has the potential to play a major role in the stabilization of anthropogenic greenhouse gases. To develop the capture technology from its current demonstration phase towards commercial maturity, significant funding is directed to CCS, such as the EU’s €4.5 bn NER300 fund. However, we know little about how this funding relates to market diffusion of CCS. This paper addresses that question. We initially review past learning effects from both capacity installations and R and D efforts for a similar technology using the concept of two-factor learning. We apply the obtained learning-by-doing and learning-by-searching rates to CCS in the electricity market model HECTOR, which simulates 19 European countries hourly until 2040, to understand the impact of learning and associated policies on CCS market diffusion. We evaluate the effectiveness of policies addressing learning-by-doing and learning-by-searching by relating the policy budget to the realized CCS capacity and find that, at lower policy cost, both methods are about equally effective. At higher spending levels, policies promoting learning-by-doing are more effective. Overall, policy effectiveness increases in low CO 2 price scenarios, but the CO 2 price still remains the key prerequisite for the economic competitiveness, even with major policy support. - Highlights: ► Identified two-factor learning rates for CCS through empirical data from flue gas desulphurization. ► Evaluated effectiveness of CCS stimulation policies addressing learning-by-doing and learning-by-researching. ► Both policy types are about equally effective with small policy budgets. ► Policies addressing learning-by-doing, e.g., subsidies to CCS projects, are more effective with large policy budgets. ► Analysis deployed HECTOR power market model that simulates 19 European countries on hourly granularity until 2040.

Infrared spectra and tunneling dynamics of the N2-D2O and OC-D2O complexes in the v2 bend region of D2O.

Science.gov (United States)

Zhu, Yu; Zheng, Rui; Li, Song; Yang, Yu; Duan, Chuanxi

2013-12-07

The rovibrational spectra of the N2-D2O and OC-D2O complexes in the v2 bend region of D2O have been measured in a supersonic slit jet expansion using a rapid-scan tunable diode laser spectrometer. Both a-type and b-type transitions were observed for these two complexes. All transitions are doubled, due to the heavy water tunneling within the complexes. Assuming the tunneling splittings are the same in K(a) = 0 and K(a) = 1, the band origins, all three rotational and several distortion constants of each tunneling state were determined for N2-D2O in the ground and excited vibrational states, and for OC-D2O in the excited vibrational state, respectively. The averaged band origin of OC-D2O is blueshifted by 2.241 cm(-1) from that of the v2 band of the D2O monomer, compared with 1.247 cm(-1) for N2-D2O. The tunneling splitting of N2-D2O in the ground state is 0.16359(28) cm(-1), which is about five times that of OC-D2O. The tunneling splittings decrease by about 26% for N2-D2O and 23% for OC-D2O, respectively, upon excitation of the D2O bending vibration, indicating an increase of the tunneling barrier in the excited vibrational state. The tunneling splittings are found to have a strong dependence on intramolecular vibrational excitation as well as a weak dependence on quantum number K(a).

Assessing the Applicability of 3D Holographic Technology as an Enhanced Technology for Distance Learning

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Pradeep Kalansooriya

2015-08-01

Full Text Available Distance learning has provided an excellent platform for students in geographically remote locations while enabling them to learn at their own pace and convenience. A number of technologies are currently being utilized to conceptualize, design, enhance and foster distance learning. Teleconferences, electronic field trips, podcasts, webinars, video conferencing and online courses are among such technologies used in providing distance learning opportunities. However limitations in those existing technologies have affected to the increase of distance learners dropout rates. As an attempt to overcome the limitations in the currently adopted distance learning practices, the study aims to utilize 3D Hologram Technology (3DHT in the Engineering discipline. 3D hologram facilitates live and life size 3D telepresence that can interact with remote audiences. A survey had been conducted, using Delphi Technique to gather data from the experts in the field to evaluate the potential of 3DHT over existing technologies. Results of the survey suggested that 3DHT as a good distance learning technology and have the potential of overcoming existing limitations. Lack of infrastructure, High initial cost of infrastructure and Lack of technical know how are the main encounters identified by the experts in the sample. It is expected to develop a classroom environment with 3DHT and to evaluate its effectiveness for the distance learning in the next stage of the study.

D2.1 2nd User requirements for gamification of prosocial learning

OpenAIRE

Vuillier, Laura; Cook, Chrissy; Star, Kam; Dimaraki, Evangelia; Cobello, Stefano; Boniface, Michael; Parsons, Sarah

2016-01-01

The document describes the requirements for the gamification of prosocial learning. A conceptual framework is defined that is derived from multidisciplinary perspectives (pedagogy, psychology, teaching practitioners, game designers) of prosociality as the basis for understanding the technical and operational requirements for creating games to teach prosocial skills in schools. The conceptual framework provides the theoretical foundation for technical work developing a platform for prosocial g...

eLearning and eMaking: 3D Printing Blurring the Digital and the Physical

Science.gov (United States)

Loy, Jennifer

2014-01-01

This article considers the potential of 3D printing as an eLearning tool for design education and the role of eMaking in bringing together the virtual and the physical in the design studio. eLearning has matured from the basics of lecture capture into sophisticated, interactive learning activities for students. At the same time, laptops and…

Technological innovation in the energy sector: R and D, deployment, and learning-by-doing

International Nuclear Information System (INIS)

Sagar, Ambuj D.; Zwaan, Bob van der

2006-01-01

Technological innovation is fundamental for rendering the energy economy cleaner and more efficient with concomitant economic, developmental, and environmental benefits. This paper discusses aspects of R and D and 'learning-by-doing,' the main contributors to technological change that are complementary yet inter-linked. The relationship between the level of national energy R and D investments and changes in the trajectory of the country's energy system is complex; targeted efforts to promote deployment of new energy technologies play a major role in translating the results of R and D activities to changes in the energy system. Learning-by-doing is an important element of deployment, but it remains largely poorly understood. Hence this phenomenon needs to be 'unpacked' and its various aspects analyzed in detail, so as to allow better design of early deployment efforts to enhance learning gains. This paper highlights how public R and D and deployment efforts must work in tandem to expand the portfolio, and realize the potential, of new and improved energy technologies

Adolescent changes in dopamine D1 receptor expression in orbitofrontal cortex and piriform cortex accompany an associative learning deficit.

Directory of Open Access Journals (Sweden)

Anna K Garske

Full Text Available The orbitofrontal cortex (OFC and piriform cortex are involved in encoding the predictive value of olfactory stimuli in rats, and neural responses to olfactory stimuli in these areas change as associations are learned. This experience-dependent plasticity mirrors task-related changes previously observed in mesocortical dopamine neurons, which have been implicated in learning the predictive value of cues. Although forms of associative learning can be found at all ages, cortical dopamine projections do not mature until after postnatal day 35 in the rat. We hypothesized that these changes in dopamine circuitry during the juvenile and adolescent periods would result in age-dependent differences in learning the predictive value of environmental cues. Using an odor-guided associative learning task, we found that adolescent rats learn the association between an odor and a palatable reward significantly more slowly than either juvenile or adult rats. Further, adolescent rats displayed greater distractibility during the task than either juvenile or adult rats. Using real-time quantitative PCR and immunohistochemical methods, we observed that the behavioral deficit in adolescence coincides with a significant increase in D1 dopamine receptor expression compared to juvenile rats in both the OFC and piriform cortex. Further, we found that both the slower learning and increased distractibility exhibited in adolescence could be alleviated by experience with the association task as a juvenile, or by an acute administration of a low dose of either the dopamine D1 receptor agonist SKF-38393 or the D2 receptor antagonist eticlopride. These results suggest that dopaminergic modulation of cortical function may be important for learning the predictive value of environmental stimuli, and that developmental changes in cortical dopaminergic circuitry may underlie age-related differences in associative learning.

EEG-based cognitive load of processing events in 3D virtual worlds is lower than processing events in 2D displays.

Science.gov (United States)

Dan, Alex; Reiner, Miriam

2017-12-01

Interacting with 2D displays, such as computer screens, smartphones, and TV, is currently a part of our daily routine; however, our visual system is built for processing 3D worlds. We examined the cognitive load associated with a simple and a complex task of learning paper-folding (origami) by observing 2D or stereoscopic 3D displays. While connected to an electroencephalogram (EEG) system, participants watched a 2D video of an instructor demonstrating the paper-folding tasks, followed by a stereoscopic 3D projection of the same instructor (a digital avatar) illustrating identical tasks. We recorded the power of alpha and theta oscillations and calculated the cognitive load index (CLI) as the ratio of the average power of frontal theta (Fz.) and parietal alpha (Pz). The results showed a significantly higher cognitive load index associated with processing the 2D projection as compared to the 3D projection; additionally, changes in the average theta Fz power were larger for the 2D conditions as compared to the 3D conditions, while alpha average Pz power values were similar for 2D and 3D conditions for the less complex task and higher in the 3D state for the more complex task. The cognitive load index was lower for the easier task and higher for the more complex task in 2D and 3D. In addition, participants with lower spatial abilities benefited more from the 3D compared to the 2D display. These findings have implications for understanding cognitive processing associated with 2D and 3D worlds and for employing stereoscopic 3D technology over 2D displays in designing emerging virtual and augmented reality applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Game-Like Language Learning in 3-D Virtual Environments

Science.gov (United States)

Berns, Anke; Gonzalez-Pardo, Antonio; Camacho, David

2013-01-01

This paper presents our recent experiences with the design of game-like applications in 3-D virtual environments as well as its impact on student motivation and learning. Therefore our paper starts with a brief analysis of the motivational aspects of videogames and virtual worlds (VWs). We then go on to explore the possible benefits of both in the…

Time resolved spectroscopic investigation of SiD2 + D2: kinetic study

Science.gov (United States)

Al-Rubaiey, Najem A.; Walsh, Robin

2017-03-01

Silylenes (silanediyls) have made an important impact on organosilicon chemistry even if it is of more recent foundation than carbenes in organic chemistry and much less complete. These species are highly reactive intermediates. They play a central role in the chemical vapour deposition (CVD) of various silicon-containing thin films which have a technological importance in microelectronics as well as in the dry etching processes of silicon wafers. Spectroscopic methods have been developed to observe these species, a necessary pre-requisite to their direct monitoring. In this work, deuterated phenylsilane precursor, PhSiD3 was chosen for SiD2 because its analogue phenylsilane, PhSiH3 proved to be a good precursor for SiH2 and the high quality decay signals observed revealed that SiD2 be readily detected from PhSiD3 and that if other decomposition pathways (e.g. PhSiD + D2) are occurring, they do not effect measurements of the rate constants for SiD2. The absorption spectrum of SiD2 formed from the flash photolysis of a mixture of PhSiD3 and SF6 at 193nm were found in the region 17384-17391 cm-1 with strong band at 17387.07 cm-1. This single rotational line of pQ1 was chosen to monitor SiD2 removal. Time-resolved studies of SiD2 have been carried out to obtain rate constants for its bimolecular reactions with D2. The reactions were studied over the pressure range 5-100 Torr (in SF6 bath gas) at four temperatures in the range 298-498K. Single decay from 10 photolysis laser shots were averaged and found to give reasonable first-order kinetics fits. Second order kinetics were obtained by pressure dependence of the pseudo first order decay constants and substance D2 pressures within experimental error. The reaction was found to be weakly pressure dependent at all temperatures, consistent with a third-body mediated association process. In addition, SiH2+ H2 reaction is approximately ca. 60% faster than SiD2+D2 reaction. Theoretical extrapolations (using Lindemann

Time resolved spectroscopic investigation of SiD2 + D2: kinetic study

Directory of Open Access Journals (Sweden)

Al-Rubaiey Najem A.

2017-01-01

Full Text Available Silylenes (silanediyls have made an important impact on organosilicon chemistry even if it is of more recent foundation than carbenes in organic chemistry and much less complete. These species are highly reactive intermediates. They play a central role in the chemical vapour deposition (CVD of various silicon-containing thin films which have a technological importance in microelectronics as well as in the dry etching processes of silicon wafers. Spectroscopic methods have been developed to observe these species, a necessary pre-requisite to their direct monitoring. In this work, deuterated phenylsilane precursor, PhSiD3 was chosen for SiD2 because its analogue phenylsilane, PhSiH3 proved to be a good precursor for SiH2 and the high quality decay signals observed revealed that SiD2 be readily detected from PhSiD3 and that if other decomposition pathways (e.g. PhSiD + D2 are occurring, they do not effect measurements of the rate constants for SiD2. The absorption spectrum of SiD2 formed from the flash photolysis of a mixture of PhSiD3 and SF6 at 193nm were found in the region 17384-17391 cm-1 with strong band at 17387.07 cm-1. This single rotational line of pQ1 was chosen to monitor SiD2 removal. Time-resolved studies of SiD2 have been carried out to obtain rate constants for its bimolecular reactions with D2. The reactions were studied over the pressure range 5-100 Torr (in SF6 bath gas at four temperatures in the range 298-498K. Single decay from 10 photolysis laser shots were averaged and found to give reasonable first-order kinetics fits. Second order kinetics were obtained by pressure dependence of the pseudo first order decay constants and substance D2 pressures within experimental error. The reaction was found to be weakly pressure dependent at all temperatures, consistent with a third-body mediated association process. In addition, SiH2+ H2 reaction is approximately ca. 60% faster than SiD2+D2 reaction. Theoretical extrapolations (using

Dissociable Hippocampal and Amygdalar D1-like receptor contribution to Discriminated Pavlovian conditioned approach learning

Science.gov (United States)

Andrzejewski, Matthew E; Ryals, Curtis

2016-01-01

Pavlovian conditioning is an elementary form of reward-related behavioral adaptation. The mesolimbic dopamine system is widely considered to mediate critical aspects of reward-related learning. For example, initial acquisition of positively-reinforced operant behavior requires dopamine (DA) D1 receptor (D1R) activation in the basolateral amygdala (BLA), central nucleus of the amygdala (CeA), and the ventral subiculum (vSUB). However, the role of D1R activation in these areas on appetitive, non-drug-related, Pavlovian learning is not currently known. In separate experiments, microinfusions of the D1-like receptor antagonist SCH-23390 (3.0 nmol/0.5 μL per side) into the amygdala and subiculum preceded discriminated Pavlovian conditioned approach (dPCA) training sessions. D1-like antagonism in all three structures impaired the acquisition of discriminated approach, but had no effect on performance after conditioning was asymptotic. Moreover, dissociable effects of D1-like antagonism in the three structures on components of discriminated responding were obtained. Lastly, the lack of latent inhibition in drug-treated groups may elucidate the role of D1-like in reward-related Pavlovian conditioning. The present data suggest a role for the D1 receptors in the amygdala and hippocampus in learning the significance of conditional stimuli, but not in the expression of conditional responses. PMID:26632336

Cocaine-induced adaptation of dopamine D2S, but not D2L autoreceptors.

Science.gov (United States)

Robinson, Brooks G; Condon, Alec F; Radl, Daniela; Borrelli, Emiliana; Williams, John T; Neve, Kim A

2017-11-20

The dopamine D2 receptor has two splice variants, D2S (Short) and D2L (Long). In dopamine neurons, both variants can act as autoreceptors to regulate neuronal excitability and dopamine release, but the roles of each variant are incompletely characterized. In a previous study we used viral receptor expression in D2 receptor knockout mice to show distinct effects of calcium signaling on D2S and D2L autoreceptor function (Gantz et al., 2015). However, the cocaine-induced plasticity of D2 receptor desensitization observed in wild type mice was not recapitulated with this method of receptor expression. Here we use mice with genetic knockouts of either the D2S or D2L variant to investigate cocaine-induced plasticity in D2 receptor signaling. Following a single in vivo cocaine exposure, the desensitization of D2 receptors from neurons expressing only the D2S variant was reduced. This did not occur in D2L-expressing neurons, indicating differential drug-induced plasticity between the variants.

Emergent Learning and Learning Ecologies in Web 2.0

Directory of Open Access Journals (Sweden)

Roy Williams

2011-03-01

Full Text Available This paper describes emergent learning and situates it within learning networks and systems and the broader learning ecology of Web 2.0. It describes the nature of emergence and emergent learning and the conditions that enable emergent, self-organised learning to occur and to flourish. Specifically, it explores whether emergent learning can be validated and self-correcting and whether it is possible to link or integrate emergent and prescribed learning. It draws on complexity theory, communities of practice, and the notion of connectivism to develop some of the foundations for an analytic framework, for enabling and managing emergent learning and networks in which agents and systems co-evolve. It then examines specific cases of learning to test and further develop the analytic framework.The paper argues that although social networking media increase the potential range and scope for emergent learning exponentially, considerable effort is required to ensure an effective balance between openness and constraint. It is possible to manage the relationship between prescriptive and emergent learning, both of which need to be part of an integrated learning ecology.

L-histidine enhances learning in stressed zebrafish

Directory of Open Access Journals (Sweden)

L.P.V. Cofiel

2009-01-01

Full Text Available The aim of the present study was to determine the effect of the histaminergic precursor L-histidine and the H3 receptor antagonist thioperamide on the learning process of zebrafish submitted or not to confinement stress. On each of the 5 consecutive days of experiment (D1, D2, D3, D4, D5, animals had to associate an interruption of the aquarium air supply with food offering. Non-stressed zebrafish received an intraperitoneal injection of 100 mg/kg L-histidine, 10 mg/kg thioperamide or saline after training. Stressed animals received drug treatment and then were submitted to confinement stress for 1 h before the learning procedure. Time to approach the feeder was measured (in seconds and was considered to be indicative of learning. A decrease in time to approach the feeder was observed in the saline-treated group (D1 = 141.92 ± 13.57; D3 = 55 ± 13.54, indicating learning. A delay in learning of stressed animals treated with saline was observed (D1 = 217.5 ± 25.66. L-histidine facilitated learning in stressed (D1 = 118.68 ± 13.9; D2 = 45.88 ± 8.2 and non-stressed (D1 = 151.11 ± 19.20; D5 = 62 ± 14.68 animals. Thioperamide inhibited learning in non-stressed (D1 = 110.38 ± 9.49; D4 = 58.79 ± 16.83 and stressed animals (D1 = 167.3 ± 26.39; D5 = 172.15 ± 27.35. L-histidine prevented the increase in blood glucose after one session of confinement (L-histidine = 65.88 ± 4.50; control = 53 ± 3.50 mg/dL. These results suggest that the histaminergic system enhances learning and modulates stress responses in zebrafish.

ECO D2.5 Learning analytics requirements and metrics report

NARCIS (Netherlands)

Brouns, Francis; Zorrilla Pantaleón, Marta Elena; Esperanza‎ Álvarez Saiz, Elena; Solana González, Pedro; Cobo Ortega, Ángel; Rocío‎ Rocha Blanco, Eliana; Collantes Viaña, Marta; Rodríguez Hoyo, Carlos; De Lima Silva, Mariana; Marta-Lazo, Carmen; Gabelas Barroso, José Antonio; Arranz, Pilar; García, Luis; Silva, Alejandro; Sáez López, José Manuel; Ventura Expósito, Patricia; Jordano de la Torre, María; María, Felix; Viñuales, Javier

2015-01-01

In MOOCs, learning analytics have to be addressed to the various types of learners that participate. This deliverable describes indicators that enable both teachers and learner to monitor the progress and performance as well as identify whether there are learners at risk of dropping out. How these

d-Cycloserine reduces context specificity of sexual extinction learning.

Science.gov (United States)

Brom, Mirte; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip; Trimbos, Baptist; Both, Stephanie

2015-11-01

d-Cycloserine (DCS) enhances extinction processes in animals. Although classical conditioning is hypothesized to play a pivotal role in the aetiology of appetitive motivation problems, no research has been conducted on the effect of DCS on the reduction of context specificity of extinction in human appetitive learning, while facilitation hereof is relevant in the context of treatment of problematic reward-seeking behaviors. Female participants were presented with two conditioned stimuli (CSs) that either predicted (CS+) or did not predict (CS-) a potential sexual reward (unconditioned stimulus (US); genital vibrostimulation). Conditioning took place in context A and extinction in context B. Subjects received DCS (125mg) or placebo directly after the experiment on day 1 in a randomized, double-blind, between-subject fashion (Placebo n=31; DCS n=31). Subsequent testing for CS-evoked conditioned responses (CRs) in both the conditioning (A) and the extinction context (B) took place 24h later on day 2. Drug effects on consolidation were then assessed by comparing the recall of sexual extinction memories between the DCS and the placebo groups. Post learning administration of DCS facilitates sexual extinction memory consolidation and affects extinction's fundamental context specificity, evidenced by reduced conditioned genital and subjective sexual responses, relative to placebo, for presentations of the reward predicting cue 24h later outside the extinction context. DCS makes appetitive extinction memories context-independent and prevents the return of conditioned response. NMDA receptor glycine site agonists may be potential pharmacotherapies for the prevention of relapse of appetitive motivation disorders with a learned component. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of D-cycloserine on the extinction of appetitive operant learning.

Science.gov (United States)

Vurbic, Drina; Gold, Benjamin; Bouton, Mark E

2011-08-01

Four experiments with rat subjects examined whether D-cycloserine (DCS), a partial NMDA agonist, facilitates the extinction of operant lever-pressing reinforced by food. Previous research has demonstrated that DCS facilitates extinction learning with methods that involve Pavlovian extinction. In the current experiments, operant conditioning occurred in Context A, extinction in Context B, and then testing occurred in both the extinction and conditioning contexts. Experiments 1A and 1B tested the effects of three doses of DCS (5, 15, and 30 mg/kg) on the extinction of lever pressing trained as a free operant. Experiment 2 examined their effects when extinction of the free operant was conducted in the presence of nonresponse-contingent deliveries of the reinforcer (that theoretically reduced the role of generalization decrement in suppressing responding). Experiment 3 examined their effects on extinction of a discriminated operant, that is, one that had been reinforced in the presence of a discriminative stimulus, but not in its absence. A strong ABA renewal effect was observed in all four experiments during testing. However, despite the use of DCS doses and a drug administration procedure that facilitates the extinction of Pavlovian learning, there was no evidence in any experiment that DCS facilitated operant extinction learning assessed in either the extinction or the conditioning context. DCS may primarily facilitate learning processes that underlie Pavlovian, rather than purely operant, extinction. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

Science.gov (United States)

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

Synthesis of 2-acetamido-6-O-(5-acetamido-3,5-dideoxy-β-D-glycero-D-galacto-2-nonulo-pyranosylonic acid)-2-deoxy-D-glucose [2-acetamido-6-O-(N-acetyl-β-D-neuraminyl)-2-deoxy-D-glucose

NARCIS (Netherlands)

Vliegenthart, J.F.G.; Vleugel, D.J.M. van der; Zwikker, J.W.; Boeckel, S.A.A. van; Boom, J.H. van

1982-01-01

Silver triflate-promoted condensation of methyl 5-acetamido-4,7,8,9-tetra-O-acetyl-2-chloro-2,3,5-trideoxy-β-D-glycero-D-galacto -2-nonulopyranosonate (9) with benzyl-2-acetamido-2-deoxy-3,4-O-(1,1,3,3-tetraisopropyldisiloxane-1,3-diyl)-α-D-glucopyranoside, followed by removal of the

D3-??????????????????????? ? ???? ?????????? ?2 ?????? ?????? ?????

OpenAIRE

?????????, ????; ???????, ???????; ??????, ?????????; ?????????????, ????; ??????, ??????

2011-01-01

????? ?????? ??????? ????? ????? ??????????? ?????? ?????? ????? ? ?????? ? ???????? ????? ?????????. ?????????? ???????????? ?????? ?? ?2 ?????? ?????? ????? ??????? ?? D3 ???????????????? ??????? ??????????? ?????? ????????? ????? ?????????? ??? ??? ??????????. ? ????? ????????????? ??????????? ??? ????????? ????????????? ?????????? ???? ?????????? ?????????? ????? ????????? ?????? ???????? ?? D3-????????????????? ???????.

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

Science.gov (United States)

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi

2017-10-01

We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging

Deliverable 2.2

DEFF Research Database (Denmark)

Tarabanis, Konstantinos; Efthimios, Tambouris; Zotou, Maria

2016-01-01

etc. The report also presents the OD-PBL design pathway, which is a further development of the OD-PBL methodological recommendations presented in the D2.1. This design pathway aims to guide educators when designing learning processes that aim to teach OD by utilizing the PBL learning strategy......The work carried out resulted in the description of the LA field and in the presentation of a total of 18 LA tools that can analyse educational data that can be utilized in the project to support multiple PBL aspects, such as feedback, reflection, self-driven learning, collaboration, application....... The pathway consists of 6 main steps, i.e. Analysis, Gathering of inputs, Design, Development, Implementation and Reflection. Each step provides guidelines on how to plan an OD course and learning processes, and combines all previous project results from D1.1, D1.2, D1.3 and D2.1. Finally, the report presents...

Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography.

Science.gov (United States)

Narula, Sukrit; Shameer, Khader; Salem Omar, Alaa Mabrouk; Dudley, Joel T; Sengupta, Partho P

2016-11-29

Machine-learning models may aid cardiac phenotypic recognition by using features of cardiac tissue deformation. This study investigated the diagnostic value of a machine-learning framework that incorporates speckle-tracking echocardiographic data for automated discrimination of hypertrophic cardiomyopathy (HCM) from physiological hypertrophy seen in athletes (ATH). Expert-annotated speckle-tracking echocardiographic datasets obtained from 77 ATH and 62 HCM patients were used for developing an automated system. An ensemble machine-learning model with 3 different machine-learning algorithms (support vector machines, random forests, and artificial neural networks) was developed and a majority voting method was used for conclusive predictions with further K-fold cross-validation. Feature selection using an information gain (IG) algorithm revealed that volume was the best predictor for differentiating between HCM ands. ATH (IG = 0.24) followed by mid-left ventricular segmental (IG = 0.134) and average longitudinal strain (IG = 0.131). The ensemble machine-learning model showed increased sensitivity and specificity compared with early-to-late diastolic transmitral velocity ratio (p 13 mm. In this subgroup analysis, the automated model continued to show equal sensitivity, but increased specificity relative to early-to-late diastolic transmitral velocity ratio, e', and strain. Our results suggested that machine-learning algorithms can assist in the discrimination of physiological versus pathological patterns of hypertrophic remodeling. This effort represents a step toward the development of a real-time, machine-learning-based system for automated interpretation of echocardiographic images, which may help novice readers with limited experience. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Evaluation of Deep Learning Models for Predicting CO2 Flux

Science.gov (United States)

Halem, M.; Nguyen, P.; Frankel, D.

2017-12-01

Artificial neural networks have been employed to calculate surface flux measurements from station data because they are able to fit highly nonlinear relations between input and output variables without knowing the detail relationships between the variables. However, the accuracy in performing neural net estimates of CO2 flux from observations of CO2 and other atmospheric variables is influenced by the architecture of the neural model, the availability, and complexity of interactions between physical variables such as wind, temperature, and indirect variables like latent heat, and sensible heat, etc. We evaluate two deep learning models, feed forward and recurrent neural network models to learn how they each respond to the physical measurements, time dependency of the measurements of CO2 concentration, humidity, pressure, temperature, wind speed etc. for predicting the CO2 flux. In this paper, we focus on a) building neural network models for estimating CO2 flux based on DOE data from tower Atmospheric Radiation Measurement data; b) evaluating the impact of choosing the surface variables and model hyper-parameters on the accuracy and predictions of surface flux; c) assessing the applicability of the neural network models on estimate CO2 flux by using OCO-2 satellite data; d) studying the efficiency of using GPU-acceleration for neural network performance using IBM Power AI deep learning software and packages on IBM Minsky system.

Applying machine learning methods for characterization of hexagonal prisms from their 2D scattering patterns - an investigation using modelled scattering data

Science.gov (United States)

Salawu, Emmanuel Oluwatobi; Hesse, Evelyn; Stopford, Chris; Davey, Neil; Sun, Yi

2017-11-01

Better understanding and characterization of cloud particles, whose properties and distributions affect climate and weather, are essential for the understanding of present climate and climate change. Since imaging cloud probes have limitations of optical resolution, especially for small particles (with diameter < 25 μm), instruments like the Small Ice Detector (SID) probes, which capture high-resolution spatial light scattering patterns from individual particles down to 1 μm in size, have been developed. In this work, we have proposed a method using Machine Learning techniques to estimate simulated particles' orientation-averaged projected sizes (PAD) and aspect ratio from their 2D scattering patterns. The two-dimensional light scattering patterns (2DLSP) of hexagonal prisms are computed using the Ray Tracing with Diffraction on Facets (RTDF) model. The 2DLSP cover the same angular range as the SID probes. We generated 2DLSP for 162 hexagonal prisms at 133 orientations for each. In a first step, the 2DLSP were transformed into rotation-invariant Zernike moments (ZMs), which are particularly suitable for analyses of pattern symmetry. Then we used ZMs, summed intensities, and root mean square contrast as inputs to the advanced Machine Learning methods. We created one random forests classifier for predicting prism orientation, 133 orientation-specific (OS) support vector classification models for predicting the prism aspect-ratios, 133 OS support vector regression models for estimating prism sizes, and another 133 OS Support Vector Regression (SVR) models for estimating the size PADs. We have achieved a high accuracy of 0.99 in predicting prism aspect ratios, and a low value of normalized mean square error of 0.004 for estimating the particle's size and size PADs.

An Interactive 3D Virtual Anatomy Puzzle for Learning and Simulation - Initial Demonstration and Evaluation.

Science.gov (United States)

Messier, Erik; Wilcox, Jascha; Dawson-Elli, Alexander; Diaz, Gabriel; Linte, Cristian A

2016-01-01

To inspire young students (grades 6-12) to become medical practitioners and biomedical engineers, it is necessary to expose them to key concepts of the field in a way that is both exciting and informative. Recent advances in medical image acquisition, manipulation, processing, visualization, and display have revolutionized the approach in which the human body and internal anatomy can be seen and studied. It is now possible to collect 3D, 4D, and 5D medical images of patient specific data, and display that data to the end user using consumer level 3D stereoscopic display technology. Despite such advancements, traditional 2D modes of content presentation such as textbooks and slides are still the standard didactic equipment used to teach young students anatomy. More sophisticated methods of display can help to elucidate the complex 3D relationships between structures that are so often missed when viewing only 2D media, and can instill in students an appreciation for the interconnection between medicine and technology. Here we describe the design, implementation, and preliminary evaluation of a 3D virtual anatomy puzzle dedicated to helping users learn the anatomy of various organs and systems by manipulating 3D virtual data. The puzzle currently comprises several components of the human anatomy and can be easily extended to include additional organs and systems. The 3D virtual anatomy puzzle game was implemented and piloted using three display paradigms - a traditional 2D monitor, a 3D TV with active shutter glass, and the DK2 version Oculus Rift, as well as two different user interaction devices - a space mouse and traditional keyboard controls.

Robots Learn Writing

Directory of Open Access Journals (Sweden)

Huan Tan

2012-01-01

Full Text Available This paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modified ISOMAP-based model. Using this algorithm, the knowledge models are established. Learned motion and knowledge models are stored in a 2D latent space. Gaussian Process (GP method is used to model and represent these models. Practical experiments are carried out on a humanoid robot, named ISAC, to learn the semantic representations of numbers and the movements of writing numbers through imitation and to verify the effectiveness of this framework. This framework is applied into training a humanoid robot, named ISAC. At the learning stage, ISAC not only learns the dynamics of the movement required to write the numbers, but also learns the semantic meaning of the numbers which are related to the writing movements from the same data set. Given speech commands, ISAC recognizes the words and generated corresponding motion trajectories to write the numbers. This imitation learning method is implemented on a cognitive architecture to provide robust cognitive information processing.

Comparison of the neuropsychological mechanisms of 2,6-diisopropylphenol and N-methyl-D-aspartate receptor antagonist against electroconvulsive therapy-induced learning and memory impairment in depressed rats.

Science.gov (United States)

Liu, Gang; Liu, Chao; Zhang, Xue-Ning

2015-09-01

The present study aimed to examine the neurophysiological mechanisms of the 2,6-diisopropylphenol and N-methyl-D-aspartate (NMDA) receptor antagonist against learning and memory impairment, induced by electroconvulsive therapy (ECT). A total of 48 adult depressed rats without olfactory bulbs were randomly divided into six experimental groups: i) saline; ii) 10 mg/kg MK‑801; iii) 10 mg/kg MK‑801 and a course of ECT; iv) 200 mg/kg 2,6‑diisopropylphenol; v) 200 mg/kg 2,6‑diisopropylphenol and a course of ECT; and vi) saline and a course of ECT. The learning and memory abilities of the rats were assessed using a Morris water maze 1 day after a course of ECT. The hippocampus was removed 1 day after assessment using the Morris water maze assessment. The content of glutamate in the hippocampus was detected using high‑performance liquid chromatography. The expression levels of p‑AT8Ser202 and GSK‑3β1H8 in the hippocampus were determined using immunohistochemical staining and western blot analysis. The results demonstrated that the 2,6‑diisopropylphenol NMDA receptor antagonist, MK‑801 and ECT induced learning and memory impairment in the depressed rats. The glutamate content was significantly upregulated by ECT, reduced by 2,6‑diisopropylphenol, and was unaffected by the NMDA receptor antagonist in the hippocampus of the depressed rats. Tau protein hyperphosphorylation in the hippocampus was upregulated by ECT, but was reduced by 2,6‑diisopropylphenol and the MK‑801 NMDA receptor antagonist. It was also demonstrated that 2,6‑diisopropylphenol prevented learning and memory impairment and reduced the hyperphosphorylation of the Tau protein, which was induced by eECT. GSK‑3β was found to be the key protein involved in this signaling pathway. The ECT reduced the learning and memory impairment, caused by hyperphosphorylation of the Tau protein, in the depressed rats by upregulating the glutamate content.

2D or Not 2D? Testing the Utility of 2D Vs. 3D Landmark Data in Geometric Morphometrics of the Sculpin Subfamily Oligocottinae (Pisces; Cottoidea).

Science.gov (United States)

Buser, Thaddaeus J; Sidlauskas, Brian L; Summers, Adam P

2018-05-01

We contrast 2D vs. 3D landmark-based geometric morphometrics in the fish subfamily Oligocottinae by using 3D landmarks from CT-generated models and comparing the morphospace of the 3D landmarks to one based on 2D landmarks from images. The 2D and 3D shape variables capture common patterns across taxa, such that the pairwise Procrustes distances among taxa correspond and the trends captured by principal component analysis are similar in the xy plane. We use the two sets of landmarks to test several ecomorphological hypotheses from the literature. Both 2D and 3D data reject the hypothesis that head shape correlates significantly with the depth at which a species is commonly found. However, in taxa where shape variation in the z-axis is high, the 2D shape variables show sufficiently strong distortion to influence the outcome of the hypothesis tests regarding the relationship between mouth size and feeding ecology. Only the 3D data support previous studies which showed that large mouth sizes correlate positively with high percentages of elusive prey in the diet. When used to test for morphological divergence, 3D data show no evidence of divergence, while 2D data show that one clade of oligocottines has diverged from all others. This clade shows the greatest degree of z-axis body depth within Oligocottinae, and we conclude that the inability of the 2D approach to capture this lateral body depth causes the incongruence between 2D and 3D analyses. Anat Rec, 301:806-818, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Lectures on 2D gravity and 2D string theory

International Nuclear Information System (INIS)

Ginsparg, P.; Moore, G.

1992-01-01

This report the following topics: loops and states in conformal field theory; brief review of the Liouville theory; 2D Euclidean quantum gravity I: path integral approach; 2D Euclidean quantum gravity II: canonical approach; states in 2D string theory; matrix model technology I: method of orthogonal polynomials; matrix model technology II: loops on the lattice; matrix model technology III: free fermions from the lattice; loops and states in matrix model quantum gravity; loops and states in the C=1 matrix model; 6V model fermi sea dynamics and collective field theory; and string scattering in two spacetime dimensions

Enhancing Learning within the 3-D Virtual Learning Environment

OpenAIRE

Shirin Shafieiyoun; Akbar Moazen Safaei

2013-01-01

Today’s using of virtual learning environments becomes more remarkable in education. The potential of virtual learning environments has frequently been related to the expansion of sense of social presence which is obtained from students and educators. This study investigated the effectiveness of social presence within virtual learning environments and analysed the impact of social presence on increasing learning satisfaction within virtual learning environments. Second Life, as an example of ...

HypGrid2D. A 2-d mesh generator

Energy Technology Data Exchange (ETDEWEB)

Soerensen, N N

1998-03-01

The implementation of a hyperbolic mesh generation procedure, based on an equation for orthogonality and an equation for the cell face area is described. The method is fast, robust and gives meshes with good smoothness and orthogonality. The procedure is implemented in a program called HypGrid2D. The HypGrid2D program is capable of generating C-, O- and `H`-meshes for use in connection with the EllipSys2D Navier-Stokes solver. To illustrate the capabilities of the program, some test examples are shown. First a series of C-meshes are generated around a NACA-0012 airfoil. Secondly a series of O-meshes are generated around a NACA-65-418 airfoil. Finally `H`-meshes are generated over a Gaussian hill and a linear escarpment. (au)

Has Web 2.0 Revitalized Informal Learning? The Relationship between Web 2.0 and Informal Learning

Science.gov (United States)

Song, D.; Lee, J.

2014-01-01

Learning is becoming increasingly self-directed and often occurs away from schools and other formal educational settings. The development of a myriad of new technologies for learning has enabled people to learn anywhere and anytime. Web 2.0 technology allows researchers to shed a new light on the importance and prevalence of informal learning.…

2D-Driven 3D Object Detection in RGB-D Images

KAUST Repository

Lahoud, Jean; Ghanem, Bernard

2017-01-01

In this paper, we present a technique that places 3D bounding boxes around objects in an RGB-D scene. Our approach makes best use of the 2D information to quickly reduce the search space in 3D, benefiting from state-of-the-art 2D object detection

From 3 d duality to 2 d duality

Science.gov (United States)

Aharony, Ofer; Razamat, Shlomo S.; Willett, Brian

2017-11-01

In this paper we discuss 3 d N = 2 supersymmetric gauge theories and their IR dualities when they are compactified on a circle of radius r, and when we take the 2 d limit in which r → 0. The 2 d limit depends on how the mass parameters are scaled as r → 0, and often vacua become infinitely distant in the 2 d limit, leading to a direct sum of different 2 d theories. For generic mass parameters, when we take the same limit on both sides of a duality, we obtain 2 d dualities (between gauge theories and/or Landau-Ginzburg theories) that pass all the usual tests. However, when there are non-compact branches the discussion is subtle because the metric on the moduli space, which is not controlled by supersymmetry, plays an important role in the low-energy dynamics after compactification. Generally speaking, for IR dualities of gauge theories, we conjecture that dualities involving non-compact Higgs branches survive. On the other hand when there is a non-compact Coulomb branch on at least one side of the duality, the duality fails already when the 3 d theories are compactified on a circle. Using the valid reductions we reproduce many known 2 d IR dualities, giving further evidence for their validity, and we also find new 2 d dualities.

Learn ggplot2 using Shiny App

CERN Document Server

Moon, Keon-Woong

2016-01-01

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual—"integrating" R, ggplot2, and Shiny—introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to bec...

Development of Interactive Learning Media on Kinetic Gas Theory at SMAN 2 Takalar

Science.gov (United States)

Yanti, M.; Ihsan, N.; Subaer

2017-02-01

Learning media is the one of the most factor in supporting successfully in the learning process. The purpose of this interactive media is preparing students to improve skills in laboratory practice without need for assistance and are not bound by time and place. The subject of this study was 30 students grade XI IPA SMAN 2 Takalar. This paper discuss about the development of learning media based in theory of gas kinetic. This media designed to assist students in learning independently. This media made using four software, they are Microsoft word, Snagit Editor, Macromedia Flash Player and Lectora. This media are interactive, dynamic and could support the users desires to learn and understand course of gas theory. The development produce followed the four D models. Consisted of definition phase, design phase, development phase and disseminate phase. The results showed 1) the media were valid and reliable, 2) learning tools as well as hardcopy and softcopy which links to website 3) activity learners above 80% and 4) according to the test results, the concept of comprehension of student was improved than before given interactive media.

Creative Generation of 3D Objects with Deep Learning and Innovation Engines

DEFF Research Database (Denmark)

Lehman, Joel Anthony; Risi, Sebastian; Clune, Jeff

2016-01-01

Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from st...... creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way....

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

Science.gov (United States)

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Cocaine Inhibits Dopamine D2 Receptor Signaling via Sigma-1-D2 Receptor Heteromers

Science.gov (United States)

Navarro, Gemma; Moreno, Estefania; Bonaventura, Jordi; Brugarolas, Marc; Farré, Daniel; Aguinaga, David; Mallol, Josefa; Cortés, Antoni; Casadó, Vicent; Lluís, Carmen; Ferre, Sergi

2013-01-01

Under normal conditions the brain maintains a delicate balance between inputs of reward seeking controlled by neurons containing the D1-like family of dopamine receptors and inputs of aversion coming from neurons containing the D2-like family of dopamine receptors. Cocaine is able to subvert these balanced inputs by altering the cell signaling of these two pathways such that D1 reward seeking pathway dominates. Here, we provide an explanation at the cellular and biochemical level how cocaine may achieve this. Exploring the effect of cocaine on dopamine D2 receptors function, we present evidence of σ1 receptor molecular and functional interaction with dopamine D2 receptors. Using biophysical, biochemical, and cell biology approaches, we discovered that D2 receptors (the long isoform of the D2 receptor) can complex with σ1 receptors, a result that is specific to D2 receptors, as D3 and D4 receptors did not form heteromers. We demonstrate that the σ1-D2 receptor heteromers consist of higher order oligomers, are found in mouse striatum and that cocaine, by binding to σ1 -D2 receptor heteromers, inhibits downstream signaling in both cultured cells and in mouse striatum. In contrast, in striatum from σ1 knockout animals these complexes are not found and this inhibition is not seen. Taken together, these data illuminate the mechanism by which the initial exposure to cocaine can inhibit signaling via D2 receptor containing neurons, destabilizing the delicate signaling balance influencing drug seeking that emanates from the D1 and D2 receptor containing neurons in the brain. PMID:23637801

Total scattering cross-sections for the systems nH2 + nH2, pH2 + pH2, nD2 + nD2, oD2 + oD2 and HD + HD for relative energies below ten milli-electron volts

International Nuclear Information System (INIS)

Johnson, D.L.

1979-01-01

Relative total scattering cross sections for nH 2 + nH 2 , pH 2 + pH 2 , nD 2 + nD 2 , oD 2 + oD 2 , and HD + HD were measured with inclined nozzle beams derived from nozzle sources and intersecting at 21 0 . Both nozzles could be varied in temperature from 4.2K to 300K to provide the velocity range for the cross sections. The use of a parahydrogen converter allowed the measurement of the pH 2 + pH 2 and oD 2 + oD 2 cross sections. Cross sections for the H 2 + H 2 were measured over a relative velocity range of 200 m/s to 1450 m/s. The nH 2 + nH 2 results show an undulation in the velocity range between 350 m/s and 400 m/s that corresponds to a l = 3 orbiting resonance. Analysis of the pH 2 + pH 2 cross section indicates a l = 4 orbiting resonance near 586 m/s. This resonance has a peak energy of 1.79 meV and a measured energy width of 1.05 meV, both which agree well with theoretical predictions. The D 2 + D 2 cross sections have been measured in the velocity range between 190 m/s and 1000 m/s. No orbiting resonances have been observed, but in the oD 2 + oD 2 cross section a deep minimum between the l = 4 and the l = 5 resonances at low velocities is clearly suggested. Initial measurements of the HD + HD cross section suggests the presence of the l = 4 orbiting resonance near a relative velocity of 300 m/s. The experimental results for each system were normalized to the total cross sections, which were convoluted to account for experimental velocity and angular dispersions. Three different potentials were considered, but a chi-square fit of the data indicates that the Schaefer and Meyer potential, which has been theoretically obtained from first principles, provides the best overall description of the hydrogen systems in the low collisional energy range

Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

2018-01-01

Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

An efficient dictionary learning algorithm and its application to 3-D medical image denoising.

Science.gov (United States)

Li, Shutao; Fang, Leyuan; Yin, Haitao

2012-02-01

In this paper, we propose an efficient dictionary learning algorithm for sparse representation of given data and suggest a way to apply this algorithm to 3-D medical image denoising. Our learning approach is composed of two main parts: sparse coding and dictionary updating. On the sparse coding stage, an efficient algorithm named multiple clusters pursuit (MCP) is proposed. The MCP first applies a dictionary structuring strategy to cluster the atoms with high coherence together, and then employs a multiple-selection strategy to select several competitive atoms at each iteration. These two strategies can greatly reduce the computation complexity of the MCP and assist it to obtain better sparse solution. On the dictionary updating stage, the alternating optimization that efficiently approximates the singular value decomposition is introduced. Furthermore, in the 3-D medical image denoising application, a joint 3-D operation is proposed for taking the learning capabilities of the presented algorithm to simultaneously capture the correlations within each slice and correlations across the nearby slices, thereby obtaining better denoising results. The experiments on both synthetically generated data and real 3-D medical images demonstrate that the proposed approach has superior performance compared to some well-known methods. © 2011 IEEE

From 2D Lithography to 3D Patterning

NARCIS (Netherlands)

Van Zeijl, H.W.; Wei, J.; Shen, C.; Verhaar, T.M.; Sarro, P.M.

2010-01-01

Lithography as developed for IC device fabrication is a high volume high accuracy patterning technology with strong 2 dimensional (2D) characteristics. This 2D nature makes it a challenge to integrate this technology in a 3 dimensional (3D) manufacturing environment. This article addresses the

PhD on Track – designing learning for PhD students

Directory of Open Access Journals (Sweden)

Gunhild Austrheim

2013-12-01

Full Text Available Three years ago we started the project "Information Management for Knowledge Creation". The project was initiated to create online information literacy modules for PhD students. The result of our endeavours, PhD on Track, will be launched in May 2013. The initial stage of the project was mapping out the information behaviour of PhD students, as well as what services they require from the library through a literature review and a focus group study. The findings of these inquiries formed the knowledge base from which we developed our information literacy modules. Our paper will focus on the interaction between content production and user testing when creating PhD on Track. Methods: User testing has been employed throughout the production stage. We have tested navigation and organisation of the web site, content and usability. The project team have conducted expert testing. Analysis: The results from our user testing have played an important part in decisions concerning content production. Our working hypothesis was that the PhD students would want an encyclopaedic website, a place to quickly find answers. However, the user tests revealed that PhD students understood and expected the website to be learning modules. Conclusions: The PhD students in the tests agreed that a site such as this would be useful, especially to new PhD students. They also liked the design, but had some qualms with the level of information. They preferred shorter text, but with more depth. The students would likewise have preferred more practical examples, more illustrations and more discipline specific information. The current content of PhD on Track reflects the feedback from the user testing. We have retained initial ideas such as one section for reviewing and discovering research literature and one section for publishing PhD research work. In addition, we have included more practical examples to indicate efficient workflows or relevant actions in context. Illustrations

Identification of novel CYP2D7-2D6 hybrids: non-functional and functional variants

Directory of Open Access Journals (Sweden)

Andrea Gaedigk

2010-10-01

Full Text Available Polymorphic expression of CYP2D6 contributes to the wide range of activity observed for this clinically important drug metabolizing enzyme. In this report we describe novel CYP2D7/2D6 hybrid genes encoding non-functional and functional CYP2D6 protein and a CYP2D7 variant that mimics a CYP2D7/2D6 hybrid gene. Five kb long PCR products encompassing the novel genes were entirely sequenced. A quantitative assay probing in different gene regions was employed to determine CYP2D6 and 2D7 copy number variations and the relative position of the hybrid genes within the locus was assessed by long-range PCR. In addition to the previously known CYP2D6*13 and *66 hybrids, we describe three novel non-functional CYP2D7-2D6 hybrids with gene switching in exon 2 (CYP2D6*79, intron 2 (CYP2D6*80 and intron 5 (CYP2D6*67. A CYP2D7-specific T-ins in exon 1 causes a detrimental frame shift. One subject revealed a CYP2D7 conversion in the 5’-flanking region of a CYP2D6*35 allele, was otherwise unaffected (designated CYP2D6*35B. Finally, three DNAs revealed a CYP2D7 gene with a CYP2D6-like region downstream of exon 9 (designated CYP2D7[REP6]. Quantitative copy number determination, sequence analyses and long-range PCR mapping were in agreement and excluded the presence of additional gene units. Undetected hybrid genes may cause over-estimation of CYP2D6 activity (CYP2D6*1/*1 vs *1/hybrid, etc, but may also cause results that may interfere with the genotype determination. Detection of hybrid events, ‘single’ and tandem, will contribute to more accurate phenotype prediction from genotype data.

Preparation and luminescence properties of Eu2+-doped CaSi2O2-dN2+2/3d phosphors

International Nuclear Information System (INIS)

Gu Yunxin; Zhang Qinghong; Wang Hongzhi; Li Yaogang

2009-01-01

Eu 2+ -doped CaSi 2 O 2-d N 2+2/3d phosphors for white LED lamps were prepared by solid-state reaction, and the effects of heat-treatment conditions and the overall composition of host lattice on the optical properties have been discussed. Eu 2+ -doped CaSi 2 O 2-d N 2+2/3d displayed a single broad emission band peak at 540 nm, which could be assigned to the allowed transition of Eu 2+ from the lowest crystal field component of 4f 6 5d to 4f 7 ground-state level. The excitation band of samples, extending from UV to blue, is extremely wide, so the phosphors are suitable for white LED lamps in combination with a UV or blue LED dies. The highest PL intensity is found for the sample sintered at 1400 0 C. Moreover, the emission intensity decreases when N partially replaces O. A red shift of emission wavelength did not occur with increasing of the N content.

The Learning Potentials Integrating Social Media or Web 2.0 in a Problem Based Learning (PBL) Approach

DEFF Research Database (Denmark)

Buus, Lillian

2013-01-01

during lectures using a same time web 2.0 tool called Etherpad . This activity is going on during the course and gives the teacher a view of where the students have issues related to the theories or methods introduced during lecture. Interesting perspectives on how to integrate social media or web 2......This abstract relates to my PhD research entitled. The PhD is based on research going on at Aalborg University (AAU) within the Faculty of Social Science, meaning that the learning approach taken in this paper is based on the AAU PBL model (Kolmos, Fink, & Krogh, 2004; Kolmos, 2009). The research...... and collaboration among students, and Facebook was chosen among the students as the platform. Scenario 2b is giving the students a presentation to two web 2.0 tools for sharing and collaboration, enabled to support them in their sharing and collaboration as a group (class) and as smaller groups. The tools presented...

D2-tree

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Sioutas, Spyros; Pantazos, Kostas

2015-01-01

We present a new overlay, called the Deterministic Decentralized tree (D2-tree). The D2-tree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers...

Active learning in the lecture theatre using 3D printed objects.

Science.gov (United States)

Smith, David P

2016-01-01

The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

Web 2.0 in e-Learning

Directory of Open Access Journals (Sweden)

M. Tariq Banday

2013-10-01

Full Text Available Web 2.0 tools have created fresh opportunities for governments, education, businesses and individuals to enhance efficiency and improve effectiveness while executing respective professional duties. The key features of these tools include online character and access through a web browser, supportive for open content licenses, open sharing and social interaction, and often free to use or support free features. These have created novel prospects for teachers to combine face-to-face teaching and online materials via social media such as discussion forums, blogs and wikis. The web 2.0 educational design is based on socio-cultural learning theories such as interaction, joint creation of content, critical thinking, learning by doing and collaboration. This paper makes an appraisal of ICT adoption in education, emergence of Web, improvements in Web and its effect on the e-Learning. It explains gradual integration of ICT into education through various stages. The paper presents the content and communication dimensions of e-learning for its classification. It discusses various opportunities created by Web 2.0 tools in education for effective teacher-learner, learner-learner and teacher-teacher communication, interaction and collaboration. It presents various cases and projects involving use of some Web 2.0 tools for enhancing learning. Furthermore, it lists some challenges for successful implementation of e-learning through Web 2.0 tools and discusses some possible solutions for its control.

Hybridized Plasmons in 2D Nanoslits: From Graphene to Anisotropic 2D Materials

DEFF Research Database (Denmark)

Gonçalves, P. A. D.; Xiao, Sanshui; Peres, N. M. R.

2017-01-01

of arbitrary width, and remains valid irrespective of the 2D conductive material (e.g., doped graphene, 2D transition metal dichalcogenides, or phosphorene). We derive the dispersion relation of the hybrid modes of a 2D nanoslit along with the corresponding induced potential and electric field distributions...

Physical limit of stability in supercooled D2O and D2O+H2O mixtures

Science.gov (United States)

Kiselev, S. B.; Ely, J. F.

2003-01-01

The fluctuation theory of homogeneous nucleation was applied for calculating the physical boundary of metastable states, the kinetic spinodal, in supercooled D2O and D2O+H2O mixtures. The kinetic spinodal in our approach is completely determined by the surface tension and equation of state of the supercooled liquid. We developed a crossover equation of state for supercooled D2O, which predicts a second critical point of low density water-high density water equilibrium, CP2, and represents all available experimental data in supercooled D2O within experimental accuracy. Using Turnbull's expression for the surface tension we calculated with the crossover equation of state for supercooled D2O the kinetic spinodal, TKS, which lies below the homogeneous nucleation temperature, TH. We show that CP2 always lies inside in the so-called "nonthermodynamic habitat" and physically does not exist. However, the concept of a second "virtual" critical point is physical and very useful. Using this concept we have extended this approach to supercooled D2O+H2O mixtures. As an example, we consider here an equimolar D2O+H2O mixture in normal and supercooled states at atmospheric pressure, P=0.1 MPa.

Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides

Directory of Open Access Journals (Sweden)

Stanislawski Jerzy

2013-01-01

Full Text Available Abstract Background Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. Results We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%. The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile to 0.5 CPU-hours (simplified 3D profile to seconds (machine learning. Conclusions We showed that the simplified profile generation method does not introduce an error with regard to the original method, while

Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides.

Science.gov (United States)

Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd

2013-01-17

Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset

2D molybdenum disulphide (2D-MoS2) modified electrodes explored towards the oxygen reduction reaction

Science.gov (United States)

Rowley-Neale, Samuel J.; Fearn, Jamie M.; Brownson, Dale A. C.; Smith, Graham C.; Ji, Xiaobo; Banks, Craig E.

2016-08-01

Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm-2 modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR.Two-dimensional molybdenum disulphide nanosheets

Integrating E-Learning 2.0 into Online Courses

Science.gov (United States)

Yuen, Steve Chi-Yin

2014-01-01

This paper provides an overview of e-learning 2.0 concepts and presents a case study that involves the design, development, and teaching of two online courses based on e-learning 2.0 concepts. The design and the construction of e-learning 2.0 courses, and their effects on the students' learning experience are examined. In addition, students'…

Learning Opportunities in PhD Supervisory Talks: A Social Constructionist Perspective

Science.gov (United States)

Tian, Wenwen; Singhasiri, Wareesiri

2016-01-01

Although PhD supervision has been recognised as an educative process and a complex pedagogy for decades, there is little research into on-site pedagogic processes. Informed by social constructionism and a Foucauldian approach, this qualitative case study explores how learning opportunities were created by analysing both a supervisor's verbal…

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

Energy Technology Data Exchange (ETDEWEB)

Santhanam, A; Min, Y; Beron, P; Agazaryan, N; Kupelian, P; Low, D [UCLA, Los Angeles, CA (United States)

2016-06-15

Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter. To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

International Nuclear Information System (INIS)

Santhanam, A; Min, Y; Beron, P; Agazaryan, N; Kupelian, P; Low, D

2016-01-01

Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter. To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.

The Effect of Perceptual Learning on L2 Vocabulary Learning and Retention

OpenAIRE

BEDİR, Gülay; BEKTAŞ BEDİR, Sevgi

2018-01-01

It is thought that learning styles have an effecton learning foreign language. This study aims to determine effects ofperceptual learning styles on L2 vocabulary learning and retention. Learningstyle preferences were assessed in the current study through the section ofCohen et al.’s Learning Style Survey (LSS) corresponding to the perceptualmodalities and achievement tests developed by the researcher was used to assessvocabulary learning and retention. And an open-ended question is tried toan...

LearnWeb 2.0. Integrating Social Software for Lifelong Learning.

NARCIS (Netherlands)

Marenzi, Ivana; Demidova, Elena; Nejdl, Wolfgang

2008-01-01

Marenzi, I., Demidova, E., & Nejdl, W. (2008). LearnWeb 2.0. Integrating Social Software for Lifelong Learning. Proceedings of the ED-Media 2008. World Conference on Educational Multimedia, Hypermedia & Telecommunications. June, 30 - July, 4, 2008, Austria, Vienna.

Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning.

Science.gov (United States)

Hagita, Katsumi; Higuchi, Takeshi; Jinnai, Hiroshi

2018-04-12

Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.

Wireless Device-to-Device (D2D) Links for Machine-to-Machine (M2M) Communication

DEFF Research Database (Denmark)

Pratas, Nuno; Popovski, Petar

2017-01-01

Device-to-Device (D2D) communications will play an important role in the fifth generation (5G) cellular networks, by increasing the spatial reuse of spectrum resources and enabling communication links with low latency. D2D is composed of two fundamental building blocks: proximity discovery...... and direct communication between nearby users. Another emerging trend in wireless cellular systems is Machine-to-Machine (M2M) communications, often characterized by fixed, low transmission rates. In this chapter we motivate the synergy between D2D and M2M, and present technologies that enable M2M-via-D2D...

Estimating the complexity of 3D structural models using machine learning methods

Science.gov (United States)

Mejía-Herrera, Pablo; Kakurina, Maria; Royer, Jean-Jacques

2016-04-01

Quantifying the complexity of 3D geological structural models can play a major role in natural resources exploration surveys, for predicting environmental hazards or for forecasting fossil resources. This paper proposes a structural complexity index which can be used to help in defining the degree of effort necessary to build a 3D model for a given degree of confidence, and also to identify locations where addition efforts are required to meet a given acceptable risk of uncertainty. In this work, it is considered that the structural complexity index can be estimated using machine learning methods on raw geo-data. More precisely, the metrics for measuring the complexity can be approximated as the difficulty degree associated to the prediction of the geological objects distribution calculated based on partial information on the actual structural distribution of materials. The proposed methodology is tested on a set of 3D synthetic structural models for which the degree of effort during their building is assessed using various parameters (such as number of faults, number of part in a surface object, number of borders, ...), the rank of geological elements contained in each model, and, finally, their level of deformation (folding and faulting). The results show how the estimated complexity in a 3D model can be approximated by the quantity of partial data necessaries to simulated at a given precision the actual 3D model without error using machine learning algorithms.

Off-lattice self-learning kinetic Monte Carlo: application to 2D cluster diffusion on the fcc(111) surface

International Nuclear Information System (INIS)

Kara, Abdelkader; Yildirim, Handan; Rahman, Talat S; Trushin, Oleg

2009-01-01

We report developments of the kinetic Monte Carlo (KMC) method with improved accuracy and increased versatility for the description of atomic diffusivity on metal surfaces. The on-lattice constraint built into our recently proposed self-learning KMC (SLKMC) (Trushin et al 2005 Phys. Rev. B 72 115401) is released, leaving atoms free to occupy 'off-lattice' positions to accommodate several processes responsible for small-cluster diffusion, periphery atom motion and heteroepitaxial growth. This technique combines the ideas embedded in the SLKMC method with a new pattern-recognition scheme fitted to an off-lattice model in which relative atomic positions are used to characterize and store configurations. Application of a combination of the 'drag' and the repulsive bias potential (RBP) methods for saddle point searches allows the treatment of concerted cluster, and multiple- and single-atom, motions on an equal footing. This tandem approach has helped reveal several new atomic mechanisms which contribute to cluster migration. We present applications of this off-lattice SLKMC to the diffusion of 2D islands of Cu (containing 2-30 atoms) on Cu and Ag(111), using the interatomic potential from the embedded-atom method. For the hetero-system Cu/Ag(111), this technique has uncovered mechanisms involving concerted motions such as shear, breathing and commensurate-incommensurate occupancies. Although the technique introduces complexities in storage and retrieval, it does not introduce noticeable extra computational cost.

Conversion of 2-deoxy-D-ribose into 2-amino-5-(2-deoxy-beta-D-ribofuranosyl)pyridine, 2'-deoxypseudouridine, and other C-(2'-deoxyribonucleosides).

Science.gov (United States)

Reese, Colin B; Wu, Qinpei

2003-09-21

The synthesis of 2-amino-5-(2-deoxy-beta-D-ribofuranosyl)pyridine 2a, 2-amino-5-(2-deoxy-alpha-D-ribofuranosyl)-pyridine 23, 2-amino-5-(2-deoxy-beta-D-ribofuranosyl)-3-methylpyridine 2b, 2-amino-5-(2-deoxy-alpha-D-ribofuranosyl)-3-methylpyridine 29 and 5-(2-deoxy-beta-D-ribofuranosyl)-2,4-dioxopyrimidine [2'-deoxypseudouridine] 30a is described. These C-nucleosides are prepared either from 2-deoxy-3,5-O-(1,1,3,3-tetraisopropyldisiloxan-1,3-diyl)-D-ribofuranose 15 or from 2-deoxy-3,5-O-(1,1,3,3-tetraisopropyldisiloxan-1,3-diyl)-D-ribono-1,4-lactone 16, which are themselves prepared from 2-deoxy-D-ribose 13. The sugar derivatives are first allowed to react with the appropriate 5-lithio-pyridine or 5-lithio-pyrimidine derivatives, which are prepared from 5-bromo-2-(dibenzylamino)pyridine 12a, 5-bromo-2-[bis(4-methoxybenzyl)amino]pyridine 12b, 5-bromo-2-dibenzylamino-3-methylpyridine 25 and 5-bromo-2,4-bis(4-methoxybenzyloxy)pyrimidine 33. The products from the reactions between the lithio-derivatives and the lactol 15 are cyclized under Mitsunobu conditions; the products from the reactions between the lithio-derivatives and the lactone 16 are first reduced with L-Selectride before cyclization, also under Mitsunobu conditions. In all cases, the beta-anomers of the protected C-nucleosides are the predominant products. Finally, the separation of the alpha- and beta-anomers and the removal of all of the protecting groups are described.

Laser-probing measurements and calculations of lifetimes of the 5d 2D3 at ∼sol∼ at 2 and 5d 2D5 at ∼sol∼ at 2 metastable levels in Ba II

International Nuclear Information System (INIS)

Gurell, J.; Lundin, P.; Mannervik, S.; Royen, P.; Schef, P.; Biemont, E.; Quinet, P.; Blagoev, K.; Fivet, V.; Norlin, L.-O.; Rostohar, D.

2007-01-01

The two metastable levels 5d 2 D 3 at ∼sol∼ at 2 and 5d 2 D 5 at ∼sol∼ at 2 in Ba II both show extremely long lifetimes of the order of several tens of seconds each. This has been found both by experiments and by theoretical predictions. The small transition probabilities associated with these two levels make them interesting and challenging for theoreticians as well as for experimentalists. Several calculations and measurements of these two lifetimes have been made previously but discrepancies between the results are present. This article presents values of τ=89.4±15.6 s for the 2 D 3 at ∼sol∼ at 2 level and τ=32.0±4.6 s for the 2 D 5 at ∼sol∼ at 2 level measured in a beam-laser experiment performed at the ion storage ring CRYRING. These values are supported by our new calculations resulting in τ=82.0 s for the 2 D 3 at ∼sol∼ at 2 level and τ=31.6 s for the 2 D 5 at ∼sol∼ at 2 level

An Ensemble of 2D Convolutional Neural Networks for Tumor Segmentation

DEFF Research Database (Denmark)

Lyksborg, Mark; Puonti, Oula; Agn, Mikael

2015-01-01

Accurate tumor segmentation plays an important role in radiosurgery planning and the assessment of radiotherapy treatment efficacy. In this paper we propose a method combining an ensemble of 2D convolutional neural networks for doing a volumetric segmentation of magnetic resonance images....... The segmentation is done in three steps; first the full tumor region, is segmented from the background by a voxel-wise merging of the decisions of three networks learned from three orthogonal planes, next the segmentation is refined using a cellular automaton-based seed growing method known as growcut. Finally......, within-tumor sub-regions are segmented using an additional ensemble of networks trained for the task. We demonstrate the method on the MICCAI Brain Tumor Segmentation Challenge dataset of 2014, and show improved segmentation accuracy compared to an axially trained 2D network and an ensemble segmentation...

2D-hahmoanimaation toteuttamistekniikat

OpenAIRE

Smolander, Aku

2009-01-01

Opinnäytetyössä tutkitaan erilaisia 2D-hahmoanimaation toteuttamistekniikoita. Aluksi luodaan yleiskatsaus animoinnin historiaan ja tekniikoihin piirtämisestä mallintamiseen. Alkukatsauksen jälkeen tutkitaan 2D-hahmon suunnittelua ja liikkeitä koskevia sääntöjä. Hahmoanimaation liikkeissä huomionarvoisia asioita ovat muun muassa ajastus, liioittelu, ennakointi ja painovoima. Seuraavaksi perehdytään itse 2D-hahmoanimaation toteuttamistekniikoihin. Tavoitteena on selvittää, tutkia ja vertailla ...

Support for PhD Students: The Impact of Institutional Dynamics on the Pedagogy of Learning Development

Science.gov (United States)

Peelo, Moira

2013-01-01

This paper explores one practitioner's learning development work with PhD students in a changing university context in which managerialism and financial stringency have combined. It questions how learning development practitioners can maintain their professional goals while negotiating issues arising from managerialism, financial stringency,…

Z-Index Parameterization for Volumetric CT Image Reconstruction via 3-D Dictionary Learning.

Science.gov (United States)

Bai, Ti; Yan, Hao; Jia, Xun; Jiang, Steve; Wang, Ge; Mou, Xuanqin

2017-12-01

Despite the rapid developments of X-ray cone-beam CT (CBCT), image noise still remains a major issue for the low dose CBCT. To suppress the noise effectively while retain the structures well for low dose CBCT image, in this paper, a sparse constraint based on the 3-D dictionary is incorporated into a regularized iterative reconstruction framework, defining the 3-D dictionary learning (3-DDL) method. In addition, by analyzing the sparsity level curve associated with different regularization parameters, a new adaptive parameter selection strategy is proposed to facilitate our 3-DDL method. To justify the proposed method, we first analyze the distributions of the representation coefficients associated with the 3-D dictionary and the conventional 2-D dictionary to compare their efficiencies in representing volumetric images. Then, multiple real data experiments are conducted for performance validation. Based on these results, we found: 1) the 3-D dictionary-based sparse coefficients have three orders narrower Laplacian distribution compared with the 2-D dictionary, suggesting the higher representation efficiencies of the 3-D dictionary; 2) the sparsity level curve demonstrates a clear Z-shape, and hence referred to as Z-curve, in this paper; 3) the parameter associated with the maximum curvature point of the Z-curve suggests a nice parameter choice, which could be adaptively located with the proposed Z-index parameterization (ZIP) method; 4) the proposed 3-DDL algorithm equipped with the ZIP method could deliver reconstructions with the lowest root mean squared errors and the highest structural similarity index compared with the competing methods; 5) similar noise performance as the regular dose FDK reconstruction regarding the standard deviation metric could be achieved with the proposed method using (1/2)/(1/4)/(1/8) dose level projections. The contrast-noise ratio is improved by ~2.5/3.5 times with respect to two different cases under the (1/8) dose level compared

Effects of Compound Yi-Zhi on D-galactose-induced learning and memory deficits in mice

Institute of Scientific and Technical Information of China (English)

XUJiang-Ping; WUHang-Yu; LILin

2004-01-01

AIM: To explore the effects of Compound Yi-Zhi (YZC) on learning and memory capacity and free radical metabolism in D-galactose induced mice dementia model. METHODS: The mice dementia model was induced by a daily D-galactose 0.15g/kg sc for 45 days and after 5 days'D-galactose injection, the mice were treated with three doses of YZC

"Let's get physical": advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy.

Science.gov (United States)

Preece, Daniel; Williams, Sarah B; Lam, Richard; Weller, Renate

2013-01-01

Three-dimensional (3D) information plays an important part in medical and veterinary education. Appreciating complex 3D spatial relationships requires a strong foundational understanding of anatomy and mental 3D visualization skills. Novel learning resources have been introduced to anatomy training to achieve this. Objective evaluation of their comparative efficacies remains scarce in the literature. This study developed and evaluated the use of a physical model in demonstrating the complex spatial relationships of the equine foot. It was hypothesized that the newly developed physical model would be more effective for students to learn magnetic resonance imaging (MRI) anatomy of the foot than textbooks or computer-based 3D models. Third year veterinary medicine students were randomly assigned to one of three teaching aid groups (physical model; textbooks; 3D computer model). The comparative efficacies of the three teaching aids were assessed through students' abilities to identify anatomical structures on MR images. Overall mean MRI assessment scores were significantly higher in students utilizing the physical model (86.39%) compared with students using textbooks (62.61%) and the 3D computer model (63.68%) (P < 0.001), with no significant difference between the textbook and 3D computer model groups (P = 0.685). Student feedback was also more positive in the physical model group compared with both the textbook and 3D computer model groups. Our results suggest that physical models may hold a significant advantage over alternative learning resources in enhancing visuospatial and 3D understanding of complex anatomical architecture, and that 3D computer models have significant limitations with regards to 3D learning. © 2013 American Association of Anatomists.

Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition

KAUST Repository

Li, Huibin; Di, Huang; Morvan, Jean-Marie; Chen, Liming

2011-01-01

This paper proposes a novel approach for 3D face recognition by learning weighted sparse representation of encoded facial normal information. To comprehensively describe 3D facial surface, three components, in X, Y, and Z-plane respectively

How Spatial Abilities and Dynamic Visualizations Interplay When Learning Functional Anatomy with 3D Anatomical Models

Science.gov (United States)

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material…

Towards adaptation in e-learning 2.0

Science.gov (United States)

Cristea, Alexandra I.; Ghali, Fawaz

2011-04-01

This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

3-D Whole-Core Transport Calculation with 3D/2D Rotational Plane Slicing Method

Energy Technology Data Exchange (ETDEWEB)

Yoo, Han Jong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)

2014-10-15

Use of the method of characteristics (MOC) is very popular due to its capability of heterogeneous geometry treatment and widely used for 2-D core calculation, but direct extension of MOC to 3-D core is not so attractive due to huge calculational cost. 2-D/1-D fusion method was very successful for 3-D calculation of current generation reactor types (highly heterogeneous in radial direction but piece-wise homogeneous in axial direction). In this paper, 2-D MOC concept is extended to 3-D core calculation with little modification of an existing 2-D MOC code. The key idea is to suppose 3-D geometry as a set of many 2-D planes like a phone-directory book. Dividing 3-D structure into a large number of 2-D planes and solving each plane with a simple 2-D SN transport method would give the solution of a 3-D structure. This method was developed independently at KAIST but it is found that this concept is similar with that of 'plane tracing' in the MCCG-3D code. The method developed was tested on the 3-D C5G7 OECD/NEA benchmark problem and compared with the 2-D/1-D fusion method. Results show that the proposed method is worth investigating further. A new approach to 3-D whole-core transport calculation is described and tested. By slicing 3-D structure along characteristic planes and solving each 2-D plane problem, we can get 3-D solution. The numerical test results indicate that the new method is comparable with the 2D/1D fusion method and outperforms other existing methods. But more fair comparison should be done in similar discretization level.

Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology

Directory of Open Access Journals (Sweden)

Kateryna Shavanova

2016-02-01

Full Text Available The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D materials. After considerable research effort, a distinct “beyond graphene” domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical. A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials.

eLearning and eMaking: 3D Printing Blurring the Digital and the Physical

Directory of Open Access Journals (Sweden)

Jennifer Loy

2014-02-01

Full Text Available This article considers the potential of 3D printing as an eLearning tool for design education and the role of eMaking in bringing together the virtual and the physical in the design studio. eLearning has matured from the basics of lecture capture into sophisticated, interactive learning activities for students. At the same time, laptops and internet enabled phones have made computer-based learning mobile, invading classroom learning, changing communication between students, enabling on the spot research, and making the recording of ideas and activities easier. The barriers between online and offline are becoming blurred in a combined digital and physical learning environment. Three-dimensional printing is part of this unification and can be an empowering learning tool for students, changing their relationship with the virtual and the physical, allowing them to take ideas and thinking from screen to reality and back again in an iterative, connected process, however, from an eLearning point of view it is, more importantly, a transformative technology with the potential to change the relationship of the learner to their learning and the scope and nature of their work. Examples from Griffith Product Design student learning illustrate the potential of eMaking to enhance combined learning in a digital age.

Applications of 2D to 3D conversion for educational purposes

Science.gov (United States)

Koido, Yoshihisa; Morikawa, Hiroyuki; Shiraishi, Saki; Takeuchi, Soya; Maruyama, Wataru; Nakagori, Toshio; Hirakata, Masataka; Shinkai, Hirohisa; Kawai, Takashi

2013-03-01

There are three main approaches creating stereoscopic S3D content: stereo filming using two cameras, stereo rendering of 3D computer graphics, and 2D to S3D conversion by adding binocular information to 2D material images. Although manual "off-line" conversion can control the amount of parallax flexibly, 2D material images are converted according to monocular information in most cases, and the flexibility of 2D to S3D conversion has not been exploited. If the depth is expressed flexibly, comprehensions and interests from converted S3D contents are anticipated to be differed from those from 2D. Therefore, in this study we created new S3D content for education by applying 2D to S3D conversion. For surgical education, we created S3D surgical operation content under a surgeon using a partial 2D to S3D conversion technique which was expected to concentrate viewers' attention on significant areas. And for art education, we converted Ukiyoe prints; traditional Japanese artworks made from a woodcut. The conversion of this content, which has little depth information, into S3D, is expected to produce different cognitive processes from those evoked by 2D content, e.g., the excitation of interest, and the understanding of spatial information. In addition, the effects of the representation of these contents were investigated.

Analysis of ν2 of D 2S

Science.gov (United States)

Gillis, James R.; Blatherwick, Ronald D.; Bonomo, Francis S.

1985-11-01

The infrared spectrum of ν2 of D 2S was recorded from 740 to 1100 cm -1 on the University of Denver 50-cm FTIR spectrometer system. We have assigned 655 transitions from D 232S and 129 from D 234S, and have analyzed them using Watson's A-reduced Hamiltonian evaluated in the I r representation. We used the recently published D 232S and D 234S ground state Hamiltonian constants [C. Camy-Peyret, J. M. Flaud, L. Lechuga-Fossat and J. W. C. Johns, J. Mol. Spectrosc.109, 300-333 (1985)]. Upper state Hamiltonian constants were obtained from a fit of the ν2 transitions, keeping the ground state constants fixed while varying the upper state constants. The standard deviation of the D 232S ν2 fit is 0.0025 cm -1. The standard deviation of the D 234S ν2 fit is 0.0041 cm -1.

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

Science.gov (United States)

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

Realizing a Deflection-type D.C. Bridge-based Thermometer under Project-based Learning Approach

Science.gov (United States)

Warsahemas, T.; Ramadhiansyah; Ulum, A. I. N.; Yuliza, E.; Khairurrijal

2016-08-01

In addition to conventional learning, project-based learning (PBL) helps students developing skills and becoming more engaged in learning as they have a chance to solve real life problems of actual projects. As the name suggests, PBL is a model that organizes learning around projects. In this paper, the project that will be completed by a group of three students is about making a water temperature measuring instrument using a simple deflection-type d.c. bridge circuit. The project was done in the period of January to April 2015 when they was taking the Measurement and Data Processing Techniques, which is a compulsory course in the fourth semester of undergraduate program in Department of Physics at Institut Teknologi Bandung. With the help of a lecturer and a tutor as facilitators, they have followed this series of steps: 1. Start with a driving question, a problem to be solved, 2. Exploring the driving question by participating in authentic, situated inquiry, 3. Engaging collaborative activities with lecturer and tutor to find solutions to the driving question, 4. Scaffolding with learning technologies that help students participating in activities normally beyond their ability, and 5. Creating a set of tangible products that address the driving question. With this series of steps, the students have become easier to understand the lectures that have been given and the instrument has been realized to measure the temperature of water properly. When realizing the project under the PBL method, we learned other materials beside that have been taught in the course. Due to this project, we have had more skills like designing and soldering as well as problem-solving, teamwork, critical thinking, synthesis and analysis.

[Effects of chrysalis oil on learning, memory and oxidative stress in D-galactose-induced ageing model of mice].

Science.gov (United States)

Chen, Weiping; Yang, Qiongjie; Wei, Xing

2013-11-01

To investigate the effects of chrysalis oil on learning, memory and oxidative stress in D-galactose-induced ageing model of mice. Mice were injected intraperitoneally with D-galactose daily and received chrysalis oil intragastrically simultaneously for 30 d. Then mice underwent space navigation test and spatial probe test, superoxide dismutase (SOD), glutathione peroxidase (GSH-PX) activity and malondialdehyde (MDA) contents in mouse brain were measured. Compared to model group, escape latency in mice treated with 6 ml/kg*d chrysalis oil was significantly shorter (Pchrysalis oil were significantly increased (PChrysalis oil treatment (12ml/kg*d) significantly increased SOD and GSH-PX activity and reduced MDA contents in brain of D-galactose-induced aging mice. Chrysalis oil can improve the ability of learning and memory in D-galactose-induced aging mice, and inhibit peroxidation in brain tissue.

1H NMR study of 2-deoxy-D-arabino-hexopyranose (2-deoxy-glucopyranose), 2-deoxy-D-lyxo-hexopyranose (2-deoxy-galactopyranose) and 2'-deoxy lactose

International Nuclear Information System (INIS)

Bruyn, A. de; Anteunis, M.

1975-01-01

Complete analyses of the 1 H n.m.r. spectra at 300 MHz of D 2 O solutions of 2-deoxy-D-arabino-hexopyranose, 2-deoxy-D-lyxo-hexopyranose and 2'-deoxy lactose. Chemical shifts in the deoxy monosaccharides and in 2'-deoxy lactose. Chemical shifts in the deoxy monosaccharides and in 2'-deoxy lactose are compared with those previously obtained in the parent aldeohexopyranoses, glucobioses and D-galactopyranosol-D-glucoses. Increment values are suggested in order to predict chemical shifts in 2-deoxy derivatives from the well known rules for aldohexopyranoses. (author)

Contextual EFL Learning in a 3D Virtual Environment

Science.gov (United States)

Lan, Yu-Ju

2015-01-01

The purposes of the current study are to develop virtually immersive EFL learning contexts for EFL learners in Taiwan to pre- and review English materials beyond the regular English class schedule. A 2-iteration action research lasting for one semester was conducted to evaluate the effects of virtual contexts on learners' EFL learning. 132…

Use of 3D printed models in medical education: A randomized control trial comparing 3D prints versus cadaveric materials for learning external cardiac anatomy.

Science.gov (United States)

Lim, Kah Heng Alexander; Loo, Zhou Yaw; Goldie, Stephen J; Adams, Justin W; McMenamin, Paul G

2016-05-06

Three-dimensional (3D) printing is an emerging technology capable of readily producing accurate anatomical models, however, evidence for the use of 3D prints in medical education remains limited. A study was performed to assess their effectiveness against cadaveric materials for learning external cardiac anatomy. A double blind randomized controlled trial was undertaken on undergraduate medical students without prior formal cardiac anatomy teaching. Following a pre-test examining baseline external cardiac anatomy knowledge, participants were randomly assigned to three groups who underwent self-directed learning sessions using either cadaveric materials, 3D prints, or a combination of cadaveric materials/3D prints (combined materials). Participants were then subjected to a post-test written by a third party. Fifty-two participants completed the trial; 18 using cadaveric materials, 16 using 3D models, and 18 using combined materials. Age and time since completion of high school were equally distributed between groups. Pre-test scores were not significantly different (P = 0.231), however, post-test scores were significantly higher for 3D prints group compared to the cadaveric materials or combined materials groups (mean of 60.83% vs. 44.81% and 44.62%, P = 0.010, adjusted P = 0.012). A significant improvement in test scores was detected for the 3D prints group (P = 0.003) but not for the other two groups. The finding of this pilot study suggests that use of 3D prints do not disadvantage students relative to cadaveric materials; maximally, results suggest that 3D may confer certain benefits to anatomy learning and supports their use and ongoing evaluation as supplements to cadaver-based curriculums. Anat Sci Educ 9: 213-221. © 2015 American Association of Anatomists. © 2015 American Association of Anatomists.

An Incremental Type-2 Meta-Cognitive Extreme Learning Machine.

Science.gov (United States)

Pratama, Mahardhika; Zhang, Guangquan; Er, Meng Joo; Anavatti, Sreenatha

2017-02-01

Existing extreme learning algorithm have not taken into account four issues: 1) complexity; 2) uncertainty; 3) concept drift; and 4) high dimensionality. A novel incremental type-2 meta-cognitive extreme learning machine (ELM) called evolving type-2 ELM (eT2ELM) is proposed to cope with the four issues in this paper. The eT2ELM presents three main pillars of human meta-cognition: 1) what-to-learn; 2) how-to-learn; and 3) when-to-learn. The what-to-learn component selects important training samples for model updates by virtue of the online certainty-based active learning method, which renders eT2ELM as a semi-supervised classifier. The how-to-learn element develops a synergy between extreme learning theory and the evolving concept, whereby the hidden nodes can be generated and pruned automatically from data streams with no tuning of hidden nodes. The when-to-learn constituent makes use of the standard sample reserved strategy. A generalized interval type-2 fuzzy neural network is also put forward as a cognitive component, in which a hidden node is built upon the interval type-2 multivariate Gaussian function while exploiting a subset of Chebyshev series in the output node. The efficacy of the proposed eT2ELM is numerically validated in 12 data streams containing various concept drifts. The numerical results are confirmed by thorough statistical tests, where the eT2ELM demonstrates the most encouraging numerical results in delivering reliable prediction, while sustaining low complexity.

Measurement of the hyperfine structure of the 31D2, 41D2, 51D2 levels of helium 3

International Nuclear Information System (INIS)

Lemery, H.; Hamel, J.; Barrat, J.-P.

1981-01-01

It is well known that, in a discharge in 3 He, the nuclear spins in the ground state can be oriented through metastability exchange, by optical pumping of the metastable 2 3 S 1 atoms. The orientation is transmitted to the other levels excited in the discharge. If the nuclear spins in the ground state are submitted to magnetic resonance, the light emitted from these excited states is modulated at the R.F. field frequency. The degree of modulation is important only near a level crossing, in zero field or in non-zero field. This method has been used to determine the hyperfine structure of the 3 1 D 2 , 4 1 D 2 , 5 1 D 2 levels. The results are in good agreement with those of previous measurements and with theoretical predictions [fr

D.E.E.P. Learning: Promoting Informal STEM Learning through a Popular Gaming Platform

Science.gov (United States)

Simms, E.; Rohrlick, D.; Layman, C.; Peach, C. L.; Orcutt, J. A.

2011-12-01

The research and development of educational games, and the study of the educational value of interactive games in general, have lagged far behind efforts for games created for the purpose of entertainment. But evidence suggests that digital simulations and games have the "potential to advance multiple science learning goals, including motivation to learn science, conceptual understanding, science process skills, understanding of the nature of science, scientific discourse and argumentation, and identification with science and science learning." (NRC, 2011). It is also generally recognized that interactive digital games have the potential to promote the development of valuable learning and life skills, including data processing, decision-making, critical thinking, planning, communication and collaboration (Kirriemuir and MacFarlane, 2006). Video games are now played in 67% of American households (ESA, 2010), and across a broad range of ages, making them a potentially valuable tool for Science, Technology, Engineering and Mathematics (STEM) learning among the diverse audiences associated with informal science education institutions (ISEIs; e.g., aquariums, museums, science centers). We are attempting to capitalize on this potential by developing games based on the popular Microsoft Xbox360 gaming platform and the free Microsoft XNA game development kit. The games, collectively known as Deep-sea Extreme Environment Pilot (D.E.E.P.), engage ISEI visitors in the exploration and understanding of the otherwise remote deep-sea environment. Players assume the role of piloting a remotely-operated vehicle (ROV) to explore ocean observing systems and hydrothermal vent environments, and are challenged to complete science-based objectives in order to earn points under timed conditions. The current games are intended to be relatively brief visitor experiences (on the order of several minutes) that support complementary exhibits and programming, and promote interactive visitor

2D to 3D transition of polymeric carbon nitride nanosheets

Energy Technology Data Exchange (ETDEWEB)

Chamorro-Posada, Pedro [Dpto. de Teoría de la Señal y Comunicaciones e IT, Universidad de Valladolid, ETSI Telecomunicación, Paseo Belén 15, 47011 Valladolid (Spain); Vázquez-Cabo, José [Dpto. de Teoría de la Señal y Comunicaciones, Universidad de Vigo, ETSI Telecomunicación, Lagoas Marcosende s/n, Vigo (Spain); Sánchez-Arévalo, Francisco M. [Instituto de Investigaciones en Materiales (IIM), Universidad Nacional Autónoma de México, Apdo. Postal 70–360, Cd. Universitaria, México D.F. 04510 (Mexico); Martín-Ramos, Pablo [Dpto. de Teoría de la Señal y Comunicaciones e IT, Universidad de Valladolid, ETSI Telecomunicación, Paseo Belén 15, 47011 Valladolid (Spain); Laboratorio de Materiales Avanzados (Advanced Materials Laboratory) ETSIIAA, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia (Spain); Martín-Gil, Jesús; Navas-Gracia, Luis M. [Laboratorio de Materiales Avanzados (Advanced Materials Laboratory) ETSIIAA, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia (Spain); Dante, Roberto C., E-mail: rcdante@yahoo.com [Laboratorio de Materiales Avanzados (Advanced Materials Laboratory) ETSIIAA, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia (Spain)

2014-11-15

The transition from a prevalent turbostratic arrangement with low planar interactions (2D) to an array of polymeric carbon nitride nanosheets with stronger interplanar interactions (3D), occurring for samples treated above 650 °C, was detected by terahertz-time domain spectroscopy (THz-TDS). The simulated 3D material made of stacks of shifted quasi planar sheets composed of zigzagged polymer ribbons, delivered a XRD simulated pattern in relatively good agreement with the experimental one. The 2D to 3D transition was also supported by the simulation of THz-TDS spectra obtained from quantum chemistry calculations, in which the same broad bands around 2 THz and 1.5 THz were found for 2D and 3D arrays, respectively. This transition was also in accordance with the tightening of the interplanar distance probably due to an interplanar π bond contribution, as evidenced also by a broad absorption around 2.6 eV in the UV–vis spectrum, which appeared in the sample treated at 650 °C, and increased in the sample treated at 700 °C. The band gap was calculated for 1D and 2D cases. The value of 3.374 eV for the 2D case is, within the model accuracy and precision, in a relative good agreement with the value of 3.055 eV obtained from the experimental results. - Graphical abstract: 2D lattice mode vibrations and structural changes correlated with the so called “2D to 3D transition”. - Highlights: • A 2D to 3D transition has been detected for polymeric carbon nitride. • THz-TDS allowed us to discover and detect the 2D to 3D transition of polymeric carbon nitride. • We propose a structure for polymeric carbon nitride confirming it with THz-TDS.

2D to 3D transition of polymeric carbon nitride nanosheets

International Nuclear Information System (INIS)

Chamorro-Posada, Pedro; Vázquez-Cabo, José; Sánchez-Arévalo, Francisco M.; Martín-Ramos, Pablo; Martín-Gil, Jesús; Navas-Gracia, Luis M.; Dante, Roberto C.

2014-01-01

The transition from a prevalent turbostratic arrangement with low planar interactions (2D) to an array of polymeric carbon nitride nanosheets with stronger interplanar interactions (3D), occurring for samples treated above 650 °C, was detected by terahertz-time domain spectroscopy (THz-TDS). The simulated 3D material made of stacks of shifted quasi planar sheets composed of zigzagged polymer ribbons, delivered a XRD simulated pattern in relatively good agreement with the experimental one. The 2D to 3D transition was also supported by the simulation of THz-TDS spectra obtained from quantum chemistry calculations, in which the same broad bands around 2 THz and 1.5 THz were found for 2D and 3D arrays, respectively. This transition was also in accordance with the tightening of the interplanar distance probably due to an interplanar π bond contribution, as evidenced also by a broad absorption around 2.6 eV in the UV–vis spectrum, which appeared in the sample treated at 650 °C, and increased in the sample treated at 700 °C. The band gap was calculated for 1D and 2D cases. The value of 3.374 eV for the 2D case is, within the model accuracy and precision, in a relative good agreement with the value of 3.055 eV obtained from the experimental results. - Graphical abstract: 2D lattice mode vibrations and structural changes correlated with the so called “2D to 3D transition”. - Highlights: • A 2D to 3D transition has been detected for polymeric carbon nitride. • THz-TDS allowed us to discover and detect the 2D to 3D transition of polymeric carbon nitride. • We propose a structure for polymeric carbon nitride confirming it with THz-TDS

Effect of 24,25-dihydroxyvitamin D3 on 1,25-dihydroxyvitamin D3 [1,25-(OH)2D3] metabolism in vitamin D-deficient rats infused with 1,25-(OH)2D3

International Nuclear Information System (INIS)

Yamato, H.; Matsumoto, T.; Fukumoto, S.; Ikeda, K.; Ishizuka, S.; Ogata, E.

1989-01-01

Previous studies revealed that administration of 24,25-dihydroxyvitamin D3 [24,25-(OH)2D3] to calcium (Ca)-deficient rats causes a dose-dependent reduction in markedly elevated serum 1,25-(OH)2D3 level. Although the results suggested that the metabolism of 1,25-(OH)2D3 was accelerated by 24,25-(OH)2D3, those experiments could not define whether the enhanced metabolism of 1,25-(OH)2D3 played a role in the reduction in the serum 1,25-(OH)2D3 level. In the present study, in order to address this issue more specifically, serum 1,25-(OH)2D3 was maintained solely by exogenous administration through miniosmotic pumps of 1,25-(OH)2D3 into vitamin D-deficient rats. Thus, by measuring the serum 1,25-(OH)2D3 concentration, the effect of 24,25-(OH)2D3 on the MCR of 1,25-(OH)2D3 could be examined. Administration of 24,25-(OH)2D3 caused a dose-dependent enhancement in the MCR of 1,25-(OH)2D3, and 1 microgram/100 g rat.day 24,25-(OH)2D3, which elevated serum 24,25-(OH)2D3 to 8.6 +/- 1.3 ng/ml, significantly increased MCR and suppressed serum levels of 1,25-(OH)2D3. The effect of 24,25-(OH)2D3 on 1,25-(OH)2D3 metabolism developed with a rapid time course, and the recovery of iv injected [1 beta-3H]1,25-(OH)2D3 in blood was significantly reduced within 1 h. In addition, there was an increase in radioactivity in the water-soluble fraction of serum as well as in urine, suggesting that 1,25-(OH)2D3 is rapidly degraded to a water-soluble metabolite(s). Furthermore, the reduction in serum 1,25-(OH)2D3 was associated with a reduction in both serum and urinary Ca levels. Because the conversion of [3H]24,25-(OH)2D3 to [3H]1,24,25-(OH)2D3 or other metabolites was minimal in these rats, 24,25-(OH)2D3 appears to act without being converted into other metabolites. These results demonstrate that 24,25-(OH)2D3 rapidly stimulates the metabolism of 1,25-(OH)2D3 and reduces its serum level

Digital learning for development in Asia (DL4D) | CRDI - Centre de ...

International Development Research Centre (IDRC) Digital Library (Canada)

Digital learning for development in Asia (DL4D). Education is a pillar of development. The Sustainable Development Goals identify it as a global development priority with a commitment to ensuring inclusive and equitable quality education for all by 2030. The benefits of education are wide-ranging. Asia's strong economic ...

Make2Learn: Fostering Engagement and Creativity in Learning through Making

DEFF Research Database (Denmark)

Giannakos, Michail N.; Divitini, Monica; Iversen, Ole Sejer

2015-01-01

by research- ers to introduce making principles to young students. Making principles enable them foster co-creativity and joy in learning processes and construct knowledge. By involving students in the design decisions they begin to develop technological fluency and the needed competences, in a joyful way....... Make2Learn aims to bring together international researchers, educators, designers, and makers for the ex- ploration of making principles towards the acquisition of 21st Century learning competences, by employing the state art aspects of entertainment technologies, new media, gaming, robotics, toys...... and applications. The main objective is to build a research community around this topical area. In particular, Make2Learn aims to develop a critical discussion about the well-established practices and en- tertainment technologies of the maker movement, and expected outcomes of put- ting them into practice under...

LMS and E-learning 2.0. A Second Life for E-learning

Directory of Open Access Journals (Sweden)

Eng. Cosmin Olteanu

2008-12-01

Full Text Available E-learning 2.0 is a consequence of evolving into Web 2.0. Therefore we can say that Web2.0 : is defined as the “read-write” web which provides all the services and applications to allow individualsto co-create content, collaborate and share it with others that supports user-generated content, that is contentcreated by “users”, rather than specialist authors or publishers using a variety of affordable technologieslike blogs, podcasts and wikis. E-learning 2.0 is about creating and sharing information and knowledgewith others and is about using blogs, wikis, social bookmarking and social networks within an educationalor training context to support a new collaborative approach to learning.

Methane Provenance Determined by CH2D2 and 13CH3D Abundances

Science.gov (United States)

Kohl, I. E.; Giunta, T.; Warr, O.; Ash, J. L.; Ruffine, L.; Sherwood Lollar, B.; Young, E. D.

2017-12-01

Determining the provenance of naturally occurring methane gases is of major interest to energy companies and atmospheric climate modelers, among others. Bulk isotopic compositions and other geochemical tracers sometimes fail to provide definitive determinations of sources of methane due to complications from mixing and complicated chemical pathways of origin. Recent measurements of doubly-substituted isotopologues of methane, CH2D2 (UCLA) and 13CH3D (UCLA, CalTech, and MIT) have allowed for major improvements in sourcing natural methane gases. Early work has focused on formation temperatures obtained when the relative abundances of both doubly-substituted mass-18 species are consistent with internal equilibrium. When methane gases do not plot on the thermodynamic equilibrium curve in D12CH2D2 vs D13CH3D space, temperatures determined from D13CH3D values alone are usually spurious, even when appearing reasonable. We find that the equilibrium case is actually rare and almost exclusive to thermogenic gases produced at temperatures exceeding 100°C. All other relevant methane production processes appear to generate gases that are not in isotopologue-temperature equilibrium. When gases show departures from equilibrium as determined by the relationship between CH2D2 and 13CH3D abundances, data fall within empirically defined fields representing formation pathways. These fields are thus far consistent between different geological settings and and between lab experiments and natural samples. We have now defined fields for thermogenic gas production, microbial methanogenesis, low temperature abiotic (Sabatier) synthesis and higher temperature FTT synthesis. The majority of our natural methane data can be explained by mixing between end members originating within these production fields. Mixing can appear complex, resulting in both hyper-clumped and anti-clumped isotopologue abundances. In systems where mixtures dominate and end-members are difficult to sample, mixing models

From web 2.0 to learning games 2.0

DEFF Research Database (Denmark)

Duus Henriksen, Thomas

2011-01-01

Learning games often fail in taking into account the extensive knowledge adult learners often have on the subject taught. This paper reports from a reconfiguration of a current learning game on leadership styles called LEADER, which on basis of ideas from web 2.0, is reconfigured to include...

Dopamine D/sub 2/ and D/sub 1/ receptors: biochemical characterization

Energy Technology Data Exchange (ETDEWEB)

Niznik, H B

1986-01-01

In order to label dopamine D/sub 2/ receptors reversibly and selectively the potent substituted benzamide neuroleptic, YM-09151-2, was tritium labeled and its binding characteristics to striatal homogenates investigated. (/sup 3/H) YM-09151-2 bound to D/sub 2/ receptors with high affinity in a specific, saturable, reversible and sodium dependent fashion, displaying an appropriate pharmacological D/sub 2/ receptor profile. (/sup 3/H) YM-09151-2 appears to be the ligand of choice for labeling D/sub 2/ receptors since it displays approximately 20-fold lower affinity for serotonergic S/sub 2/ receptors than does (/sup 3/H) spiperone. As an initial step towards the molecular identification of the ligand binding subunit of the striatal D/sub 2/ receptor, photolabile analogues of the substituted benzamide clebopride were synthesized and their reversible and irreversible binding interactions to D/sub 2/ receptors characterized. D/sub 2/ receptor photoinactivation was prevented in a concentration and stereoselective manner by dopaminergic agonists and antagonists. In vivo biodistribution studies with (/sup 125/I) iodoazidoclebopride confirmed the ligand's ability to bind to D/sub 2/ receptor-rich regions and as such, may become a useful tool for the molecular characterization of D/sub 2/ receptor proteins. Digitonin solubilized striatal dopamine D/sub 2/ and D/sub 1/ receptors can be completely separated with full retention of biological activity by steric exclusion High Pressure Liquid Chromatography (HPLC) with corresponding Stokes radii of 7.1 and 5.6 nm.

Valenced action/inhibition learning in humans is modulated by a genetic variant linked to dopamine D2 receptor expression

Directory of Open Access Journals (Sweden)

Anni eRichter

2014-08-01

Full Text Available Motivational salience plays an important role in shaping human behavior, but recent studies demonstrate that human performance is not uniformly improved by motivation. Instead, action has been shown to dominate valence in motivated tasks, and it is particularly difficult for humans to learn the inhibition of an action to obtain a reward, but the neural mechanism behind this behavioral specificity is yet unclear. In all mammals, including humans, the monoamine neurotransmitter dopamine is particularly important in the neural manifestation of appetitively motivated behavior, and the human dopamine system is subject to considerable genetic variability. The well-studied TaqIA restriction fragment length polymorphism (rs1800497 has previously been shown to affect striatal dopamine metabolism. In this study we investigated a potential effect of this genetic variation on motivated action/inhibition learning. Two independent cohorts consisting of 87 and 95 healthy participants, respectively, were tested using the previously described valenced go/no-go learning paradigm in which participants learned the reward-associated no-go condition significantly worse than all other conditions. This effect was modulated by the TaqIA polymorphism, with carriers of the A1 allele showing a diminished learning-related performance enhancement in the rewarded no-go condition compared to the A2 homozygotes. This result highlights a modulatory role for genetic variability of the dopaminergic system in individual learning differences of action-valence interaction.

2D non-separable linear canonical transform (2D-NS-LCT) based cryptography

Science.gov (United States)

Zhao, Liang; Muniraj, Inbarasan; Healy, John J.; Malallah, Ra'ed; Cui, Xiao-Guang; Ryle, James P.; Sheridan, John T.

2017-05-01

The 2D non-separable linear canonical transform (2D-NS-LCT) can describe a variety of paraxial optical systems. Digital algorithms to numerically evaluate the 2D-NS-LCTs are not only important in modeling the light field propagations but also of interest in various signal processing based applications, for instance optical encryption. Therefore, in this paper, for the first time, a 2D-NS-LCT based optical Double-random- Phase-Encryption (DRPE) system is proposed which offers encrypting information in multiple degrees of freedom. Compared with the traditional systems, i.e. (i) Fourier transform (FT); (ii) Fresnel transform (FST); (iii) Fractional Fourier transform (FRT); and (iv) Linear Canonical transform (LCT), based DRPE systems, the proposed system is more secure and robust as it encrypts the data with more degrees of freedom with an augmented key-space.

New and convenient synthesis of 2-deoxy-D-ribose from 2,4-O-ethylidene-D-erythrose

Energy Technology Data Exchange (ETDEWEB)

Hauske, J.R.; Rapoport, H.

1979-01-01

A new synthesis is described of 2-deoxy-D-erythro-pentose (2-deoxy-D-ribose,2-deoxy-D-arabinose (1)), starting from D-glucose. The synthesis proceeds through direct olefination of 2,4-O-ethylidene-D-erythrose (2) by addition of the stabilized ylides generated from dimethylphosphorylmethyl phenyl sulfide (4) and the corresponding sulfoxide 5. These afford the key intermediates, thio-enol ether 7 and ..cap alpha..,..beta..-unsaturated sulfoxide 8, which when subjected to mercuric ion assisted hydrolysis gave high yields of 2-deoxy-D-ribose (1). This facile chain extension of 2 required its existance as a monomer, and conditions effective for obtaining the monomer have been developed. Detailed /sup 1/H and /sup 13/C NMR studies of these compounds are presented.

Vitamin D(3) is more potent than vitamin D(2) in humans.

Science.gov (United States)

Heaney, Robert P; Recker, Robert R; Grote, James; Horst, Ronald L; Armas, Laura A G

2011-03-01

Current unitage for the calciferols suggests that equimolar quantities of vitamins D(2) (D2) and D(3) (D3) are biologically equivalent. Published studies yield mixed results. The aim of the study was to compare the potencies of D2 and D3. The trial used a single-blind, randomized design in 33 healthy adults. Calciferols were dosed at 50,000 IU/wk for 12 wk. Principal outcome variables were area under the curve for incremental total 25-hydroxyvitamin D [25(OH)D] and change in calciferol content of sc fat. Incremental mean (sd) 25(OH)D area under the curve at 12 wk was 1366 ng · d/ml (516) for the D2-treated group and 2136 (606) for the D3 (P < 0.001). Mean (sd) steady-state 25(OH)D increments showed similar differences: 24 ng/ml for D2 (10.3) and 45 ng/ml (16.2) for D3 (P <0.001). Subcutaneous fat content of D2 rose by 50 μg/kg in the D2-treated group, and D3 content rose by 104 μg/kg in the D3-treated group. Total calciferol in fat rose by only 33 ng/kg in the D2-treated, whereas it rose by 104 μg/kg in the D3-treated group. Extrapolating to total body fat D3, storage amounted to just 17% of the administered dose. D3 is approximately 87% more potent in raising and maintaining serum 25(OH)D concentrations and produces 2- to 3-fold greater storage of vitamin D than does equimolar D2. For neither was there evidence of sequestration in fat, as had been postulated for doses in this range. Given its greater potency and lower cost, D3 should be the preferred treatment option when correcting vitamin D deficiency.

Low bioaccessibility of vitamin D2 from yeast-fortified bread compared to crystalline D2 bread and D3 from fluid milks.

Science.gov (United States)

Lipkie, Tristan E; Ferruzzi, Mario G; Weaver, Connie M

2016-11-09

The assessment of the efficacy of dietary and supplemental vitamin D tends to be confounded by differences in the serum 25-hydroxyvitamin D response between vitamin D 2 and vitamin D 3 . Serum response differences from these vitamers may be due to differences in bioavailability. To address this specifically, the bioaccessibility was assessed for vitamin D 2 from breads fortified with UV-treated yeast, and a benchmark against staple vitamin D 3 fortified foods including bovine milks and infant formula, as well as crystalline vitamin D 2 fortified bread. Fortified foods were subjected to a three-stage static in vitro digestion model, and vitamin D was analyzed by HPLC-MS. Vitamin D bioaccessibility was significantly greater from bovine milks and infant formula (71-85%) than from yeast-fortified sandwich breads (6-7%). Bioaccessibility was not different between whole wheat and white wheat bread (p > 0.05), but was ∼4× lower from yeast-fortified bread than from crystalline vitamin D 2 fortified bread (p yeast cells were observed in the digesta of yeast fortified bread. These results indicate that the low bioavailability of yeast D 2 in comparison to other vitamin D 2 sources is likely due to entrapment within a less digestible yeast matrix and not only to metabolic differences between vitamins D 2 and D 3 .

Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea

International Nuclear Information System (INIS)

Hong, Sungjun; Chung, Yanghon; Woo, Chungwon

2015-01-01

South Korea, as the 9th largest energy consuming in 2013 and the 7th largest greenhouse gas emitting country in 2011, established ‘Low Carbon Green Growth’ as the national vision in 2008, and is announcing various active energy policies that are set to gain the attention of the world. In this paper, we estimated the decrease of photovoltaic power generation cost in Korea based on the learning curve theory. Photovoltaic energy is one of the leading renewable energy sources, and countries all over the world are currently expanding R and D, demonstration and deployment of photovoltaic technology. In order to estimate the learning rate of photovoltaic energy in Korea, both conventional 1FLC (one-factor learning curve), which considers only the cumulative power generation, and 2FLC, which also considers R and D investment were applied. The 1FLC analysis showed that the cost of power generation decreased by 3.1% as the cumulative power generation doubled. The 2FCL analysis presented that the cost decreases by 2.33% every time the cumulative photovoltaic power generation is doubled and by 5.13% every time R and D investment is doubled. Moreover, the effect of R and D investment on photovoltaic technology took after around 3 years, and the depreciation rate of R and D investment was around 20%. - Highlights: • We analyze the learning effects of photovoltaic energy technology in Korea. • In order to calculate the learning rate, we use 1FLC (one-factor learning curve) and 2FLC methods, respectively. • 1FLC method considers only the cumulative power generation. • 2FLC method considers both cumulative power generation and knowledge stock. • We analyze a variety of scenarios by time lag and depreciation rate of R and D investment

Biokinetic Analysis and Metabolic Fate of 2,4-D in 2,4-D-Resistant Soybean (Glycine max).

Science.gov (United States)

Skelton, Joshua J; Simpson, David M; Peterson, Mark A; Riechers, Dean E

2017-07-26

The Enlist weed control system allows the use of 2,4-D in soybean but slight necrosis in treated leaves may be observed in the field. The objectives of this research were to measure and compare uptake, translocation, and metabolism of 2,4-D in Enlist (E, resistant) and non-AAD-12 transformed (NT, sensitive) soybeans. The adjuvant from the Enlist Duo herbicide formulation (ADJ) increased 2,4-D uptake (36%) and displayed the fastest rate of uptake (U 50 = 0.2 h) among treatments. E soybean demonstrated a faster rate of 2,4-D metabolism (M 50 = 0.2 h) compared to NT soybean, but glyphosate did not affect 2,4-D metabolism. Metabolites of 2,4-D in E soybean were qualitatively different than NT. Applying 2,4-D-ethylhexyl ester instead of 2,4-D choline (a quaternary ammonium salt) eliminated visual injury to E soybean, likely due to the time required for initial de-esterification and bioactivation. Excessive 2,4-D acid concentrations in E soybean resulting from ADJ-increased uptake may significantly contribute to foliar injury.

Nanometre-scale 3D defects in Cr2AlC thin films.

Science.gov (United States)

Chen, Y T; Music, D; Shang, L; Mayer, J; Schneider, J M

2017-04-20

MAX-phase Cr 2 AlC containing thin films were synthesized by magnetron sputtering in an industrial system. Nanometre-scale 3D defects are observed near the boundary between regions of Cr 2 AlC and of the disordered solid solution (CrAl) x C y . Shrinkage of the Cr-Cr interplanar distance and elongation of the Cr-Al distance in the vicinity of the defects are detected using transmission electron microscopy. The here observed deformation surrounding the defects was described using density functional theory by comparing the DOS of bulk Cr 2 AlC with the DOS of a strained and unstrained Cr 2 AlC(0001) surface. From the partial density of states analysis, it can be learned that Cr-C bonds are stronger than Cr-Al bonds in bulk Cr 2 AlC. Upon Cr 2 AlC(0001) surface formation, both bonds are weakened. While the Cr-C bonds recover their bulk strength as Cr 2 AlC(0001) is strained, the Cr-Al bonds experience only a partial recovery, still being weaker than their bulk counterparts. Hence, the strain induced bond strengthening in Cr 2 AlC(0001) is larger for Cr d - C p bonds than for Cr d - Al p bonds. The here observed changes in bonding due to the formation of a strained surface are consistent with the experimentally observed elongation of the Cr-Al distance in the vicinity of nm-scale 3D defects in Cr 2 AlC thin films.

Calculation of the energy of particles emitted by the reactions {sup 3}{sub 1}T (d,n) {sup 4}{sub 2}He, D (d,n) {sup 3}{sub 2}He and D (d,p) T; Calcul de l'energie des particules emises par les reactions {sup 3}{sub 1}T (d,n) {sup 4}{sub 2}He, D (d,n) {sup 3}{sub 2}He et D (d,p) T

Energy Technology Data Exchange (ETDEWEB)

Oria, M; Sorriaux, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1965-07-01

With a view to ease the work of research workers using 150 kV electrostatic accelerators, we have calculated the energy and the emission angle of particles emitted during the reactions {sub 1}{sup 3}T(d,n){sub 2}{sup 4}He, {sub 1}{sup 2}D(d,n){sub 2}{sup 3}He and {sub 1}{sup 2}D(d,p){sub 1}{sup 3}T. The results are classified in tables and arranged according to the acceleration energy of the deuterons. Since the energies considered are relatively low we have limited our study to the non-relativistic domain; this simplification results in a maximum energy variation with respect to the real energy values of 1 per cent. We give also two curves representing the variations in the total cross-sections for the reactions T (d,n){sub 2}{sup 4}He and D (d,n){sub 2}{sup 3}He. (authors) [French] De facon a faciliter la tache des experimentateurs utilisant des accelerateurs electrostatiques de 150 kV, nous avons calcule l'energie et l'angle d'emission des particules emises lors des reactions {sub 1}{sup 3}T(d,n){sub 2}{sup 4}He, {sub 1}{sup 2}D(d,n){sub 2}{sup 3}He and {sub 1}{sup 2}D(d,p){sub 1}{sup 3}T. Les resultats ont ete classes dans des tableaux, et ordonnes en fonction de l'energie d'acceleration des deuterons. Les energies considerees etant relativement peu elevees, nous avons limite notre etude au domaine non relativiste, cette simplification n'entraine qu'une variation maximale de 1 pour cent sur les valeurs reelles des energies. Nous avons joint a ce calcul deux courbes representant la variation des sections efficaces totales des reactions T (d,n){sub 2}{sup 4}He et D (d,n){sub 2}{sup 3}He. (auteurs)

Analysis of D2D Communications over Gamma/Nakagami Fading Channels

Directory of Open Access Journals (Sweden)

Z. Hussain

2018-04-01

Full Text Available In this paper, we investigate the outage probability, channel capacity and symbol error rate (SER performance of device-to-device (D2D communication systems. The D2D communication system is affected by several co-channel interferers. Gamma fading channel is considered for the D2D communication system. The channel for the co-channel interference is assumed to be Nakagami faded. An expression for the probability density function (PDF of the signal-to-interference ratio (SIR is presented. The PDF is a function of distances between various devices in the D2D system, path-loss, channel fading conditions and signal powers. Based on the PDF expression, we present the expressions for the outage, channel capacity and SER. With the help of numerical results the performance of D2D communication system is discussed under various conditions of interference, path-loss and channel fading.

3D animation model with augmented reality for natural science learning in elementary school

Science.gov (United States)

Hendajani, F.; Hakim, A.; Lusita, M. D.; Saputra, G. E.; Ramadhana, A. P.

2018-05-01

Many opinions from primary school students' on Natural Science are a difficult lesson. Many subjects are not easily understood by students, especially on materials that teach some theories about natural processes. Such as rain process, condensation and many other processes. The difficulty that students experience in understanding it is that students cannot imagine the things that have been taught in the material. Although there is material to practice some theories but is actually quite limited. There is also a video or simulation material in the form of 2D animated images. Understanding concepts in natural science lessons are also poorly understood by students. Natural Science learning media uses 3-dimensional animation models (3D) with augmented reality technology, which offers some visualization of science lessons. This application was created to visualize a process in Natural Science subject matter. The hope of making this application is to improve student's concept. This app is made to run on a personal computer that comes with a webcam with augmented reality. The app will display a 3D animation if the camera can recognize the marker.

2D and 3D stereoscopic videos used as pre-anatomy lab tools improve students' examination performance in a veterinary gross anatomy course.

Science.gov (United States)

Al-Khalili, Sereen M; Coppoc, Gordon L

2014-01-01

The hypothesis for the research described in this article was that viewing an interactive two-dimensional (2D) or three-dimensional (3D) stereoscopic pre-laboratory video would improve efficiency and learning in the laboratory. A first-year DVM class was divided into 21 dissection teams of four students each. Primary variables were method of preparation (2D, 3D, or laboratory manual) and dissection region (thorax, abdomen, or pelvis). Teams were randomly assigned to a group (A, B, or C) in a crossover design experiment so that all students experienced each of the modes of preparation, but with different regions of the canine anatomy. All students were instructed to study normal course materials and the laboratory manual, the Guide, before coming to the laboratory session and to use them during the actual dissection as usual. Video groups were given a DVD with an interactive 10-12 minute video to view for the first 30 minutes of the laboratory session, while non-video groups were instructed to review the Guide. All groups were allowed 45 minutes to dissect the assigned section and find a list of assigned structures, after which all groups took a post-dissection quiz and attitudinal survey. The 2D groups performed better than the Guide groups (p=.028) on the post-dissection quiz, despite the fact that only a minority of the 2D-group students studied the Guide as instructed. There was no significant difference (p>.05) between 2D and 3D groups on the post-dissection quiz. Students preferred videos over the Guide.

Using linked data in Learning Analytics

NARCIS (Netherlands)

Mathieu, d'Aquin; Stefan, Dietze; Eelco, Herder; Drachsler, Hendrik; Davide, Taibi

2014-01-01

d’Aquin, M., Dietze, S., Herder, E., Drachsler, H., & Taibi, D. (2014). Using linked data in learning analytics. eLearning Papers. Nr. 36/2. ISSN: 1887-1542. http://www.openeducationeuropa.eu/en/article/Using-linked-data-in-Learning-Analytics?paper=134810

Cocaine self-administration differentially affects allosteric A2A-D2 receptor-receptor interactions in the striatum. Relevance for cocaine use disorder.

Science.gov (United States)

Pintsuk, Julia; Borroto-Escuela, Dasiel O; Pomierny, Bartosz; Wydra, Karolina; Zaniewska, Magdalena; Filip, Malgorzata; Fuxe, Kjell

2016-05-01

In the current study behavioral and biochemical experiments were performed to study changes in the allosteric A2AR-D2R interactions in the ventral and dorsal striatum after cocaine self-administration versus corresponding yoked saline control. By using ex vivo [(3)H]-raclopride/quinpirole competition experiments, the effects of the A2AR agonist CGS 21680 (100 nM) on the KiH and KiL values of the D2-like receptor (D2-likeR) were determined. One major result was a significant reduction in the D2-likeR agonist high affinity state observed with CGS 21680 after cocaine self-administration in the ventral striatum compared with the yoked saline group. The results therefore support the hypothesis that A2AR agonists can at least in part counteract the motivational actions of cocaine. This action is mediated via the D2-likeR by targeting the A2AR protomer of A2AR-D2-like R heteroreceptor complexes in the ventral striatum, which leads to the reduction of D2-likeR protomer recognition through the allosteric receptor-receptor interaction. In contrast, in the dorsal striatum the CGS 21680-induced antagonistic modulation in the D2-likeR agonist high affinity state was abolished after cocaine self-administration versus the yoked saline group probably due to a local dysfunction/disruption of the A2AR-D2-like R heteroreceptor complexes. Such a change in the dorsal striatum in cocaine self-administration can contribute to the development of either locomotor sensitization, habit-forming learning and/or the compulsive drug seeking by enhanced D2-likeR protomer signaling. Potential differences in the composition and stoichiometry of the A2AR-D2R heteroreceptor complexes, including differential recruitment of sigma 1 receptor, in the ventral and dorsal striatum may explain the differential regional changes observed in the A2A-D2-likeR interactions after cocaine self-administration. Copyright © 2016 Elsevier Inc. All rights reserved.

Thermally activated 3D to 2D structural transformation of [Ni2(en)2(H2O)6(pyr)]·4H2O flexible coordination polymer

International Nuclear Information System (INIS)

Begović, Nebojša N.; Blagojević, Vladimir A.; Ostojić, Sanja B.; Radulović, Aleksandra M.; Poleti, Dejan; Minić, Dragica M.

2015-01-01

Thermally activated 3D to 2D structural transformation of the binuclear [Ni 2 (en) 2 (H 2 O) 6 (pyr)]·4H 2 O complex was investigated using a combination of theoretical and experimental methods. Step-wise thermal degradation (dehydration followed by release of ethylene diamine) results in two layered flexible coordination polymer structures. Dehydration process around 365 K results in a conjugated 2D structure with weak interlayer connectivity. It was shown to be a reversible 3D to 2D framework transformation by a guest molecule, and rehydration of the dehydration product occurs at room temperature in saturated water vapor. Rehydrated complex exhibits lower dehydration temperature, due to decreased average crystalline size, with higher surface area resulting in easier release and diffusion of water during dehydration. Thermal degradation of dehydration around 570 K, results in loss of ethylene diamine, producing a related 2D layered polymer structure, without interconnectivity between individual polymer layers. - Highlights: • Reversible 3D to 2D framework topochemical transformation on dehydration around 365 K. • Resulting polymer exhibits 2D layered structure with weak interlayer connectivity. • Dehydration is fully reversible in saturated water vapor at room temperature. • Further degradation around 570 K yields 2D polymer without interlayer connectivity. • 2D polymer exhibits conjugated electronic system

Dynamic Downlink Spectrum Access for D2D-Enabled Heterogeneous Networks

KAUST Repository

Radaydeh, Redha Mahmoud Mesleh

2018-01-15

This paper proposes new approaches for underlay device- to-device (D2D) communication in spectrum-shared het- erogeneous cellular networks. It considers devices that share downlink resources and have an enabled D2D feature to improve coverage. The mode of operation classifies devices according to their experienced base station (BS) coverage, potential to be served by BS, ability of BS to meet their quality of service (QoS), and their downlink resources occupancy. The initiation of D2D cooperation is conditioned on proposed provisional access by an active device, wherein its serving BS attempts to meet its QoS using as low number of spectrum channels as possible, while treating remaining channels for feasible D2D cooperation. Detailed formulations for the mode of operation and a proposed D2D path allocation scheme are presented under perfect and imperfect operation scenarios. The developed results are generally applicable for any performance metric and network model.

Flood hazard assessment using 1D and 2D approaches

Science.gov (United States)

Petaccia, Gabriella; Costabile, Pierfranco; Macchione, Francesco; Natale, Luigi

2013-04-01

The EU flood risk Directive (Directive 2007/60/EC) prescribes risk assessment and mapping to develop flood risk management plans. Flood hazard mapping may be carried out with mathematical models able to determine flood-prone areas once realistic conditions (in terms of discharge or water levels) are imposed at the boundaries of the case study. The deterministic models are mainly based on shallow water equations expressed in their 1D or 2D formulation. The 1D approach is widely used, especially in technical studies, due to its relative simplicity, its computational efficiency and also because it requires topographical data not as expensive as the ones needed by 2D models. Even if in a great number of practical situations, such as modeling in-channel flows and not too wide floodplains, the 1D approach may provide results close to the prediction of a more sophisticated 2D model, it must be pointed out that the correct use of a 1D model in practical situations is more complex than it may seem. The main issues to be correctly modeled in a 1D approach are the definition of hydraulic structures such as bridges and buildings interacting with the flow and the treatment of the tributaries. Clearly all these aspects have to be taken into account also in the 2D modeling, but with fewer difficulties. The purpose of this paper is to show how the above cited issues can be described using a 1D or 2D unsteady flow modeling. In particular the Authors will show the devices that have to be implemented in 1D modeling to get reliable predictions of water levels and discharges comparable to the ones obtained using a 2D model. Attention will be focused on an actual river (Crati river) located in the South of Italy. This case study is quite complicated since it deals with the simulation of channeled flows, overbank flows, interactions with buildings, bridges and tributaries. Accurate techniques, intentionally developed by the Authors to take into account all these peculiarities in 1D and 2

Vibrational and rotational excitation effects of the N(2D) + D2(X1Σg +) → ND(X3Σ+) + D(2S) reaction

Science.gov (United States)

Zhu, Ziliang; Wang, Haijie; Wang, Xiquan; Shi, Yanying

2018-05-01

The effects of the rovibrational excitation of reactants in the N(2D) + D2(X1Σg+) → ND(X3Σ+) + D(2S) reaction are calculated in a collision energy range from the threshold to 1.0 eV using the time-dependent wave packet approach and a second-order split operator. The reaction probability, integral cross-section, differential cross-section and rate constant of the title reaction are calculated. The integral cross-section and rate constant of the initial states v = 0, j = 0, 1, are in good agreement with experimental data available in the literature. The rotational excitation of the D2 molecule has little effect on reaction probability, integral cross-section and the rate constant, but it increased the sideways and forward scattering signals. The vibrational excitation of the D2 molecule reduced the threshold and broke up the forward-backward symmetry of the differential cross-section; it also increased the forward scattering signals. This may be because the vibrational excitation of the D2 molecule reduced the lifetime of the intermediate complex.

Acute myocarditis with normal wall motion detected with 2D speckle tracking echocardiography

Directory of Open Access Journals (Sweden)

Thomas Sturmberger

2016-05-01

Full Text Available We present the case of a 26-year-old male with acute tonsillitis who was referred for coronary angiography because of chest pain, elevated cardiac biomarkers, and biphasic T waves. The patient had no cardiovascular risk factors. Echocardiography showed no wall motion abnormalities and no pericardial effusion. 2D speckle tracking revealed distinct decreased regional peak longitudinal systolic strain in the lateral and posterior walls. Ischemic disease was extremely unlikely in view of his young age, negative family history regarding coronary artery disease, and lack of regional wall motion abnormalities on the conventional 2D echocardiogram. Coronary angiography was deferred as myocarditis was suspected. To confirm the diagnosis, cardiac magnetic resonance tomography (MRT was performed, showing subepicardial delayed hyperenhancement in the lateral and posterior walls correlating closely with the strain pattern obtained by 2D speckle tracking echocardiography. With a working diagnosis of acute myocarditis associated with acute tonsillitis, we prescribed antibiotics and nonsteroidal anti-inflammatory drugs. The patient’s clinical signs resolved along with normalization of serum creatine kinase (CK levels, and the patient was discharged on the third day after admission. Learning points: • Acute myocarditis can mimic acute coronary syndromes. • Conventional 2D echocardiography lacks specific features for detection of subtle regional wall motion abnormalities. • 2D speckle tracking expands the scope of echocardiography in identifying myocardial dysfunction derived from edema in acute myocarditis.

Boundary Crossing in R&D Projects in Schools: Learning through Cross-Professional Collaboration

Science.gov (United States)

Schenke, Wouter; van Driel, Jan; Geijsel, Femke P.; Volman, Monique L. L.

2017-01-01

Background/Context: School leaders, teachers, and researchers are increasingly involved in collaborative research and development (R&D) projects in schools, which encourage crossing boundaries between the fields of school and research. It is not clear, however, what and how professionals in these projects learn through cross-professional…

Impact of a personal CYP2D6 testing workshop on physician assistant student attitudes toward pharmacogenetics.

Science.gov (United States)

O'Brien, Travis J; LeLacheur, Susan; Ward, Caitlin; Lee, Norman H; Callier, Shawneequa; Harralson, Arthur F

2016-03-01

We assessed the impact of personal CYP2D6 testing on physician assistant student competency in, and attitudes toward, pharmacogenetics (PGx). Buccal samples were genotyped for CYP2D6 polymorphisms. Results were discussed during a 3-h PGx workshop. PGx knowledge was assessed by pre- and post-tests. Focus groups assessed the impact of the workshop on attitudes toward the clinical utility of PGx. Both student knowledge of PGx, and its perceived clinical utility, increased immediately following the workshop. However, exposure to PGx on clinical rotations following the workshop seemed to influence student attitudes toward PGx utility. Personal CYP2D6 testing improves both knowledge and comfort with PGx. Continued exposure to PGx concepts is important for transfer of learning.

3D Anatomy Models and Impact on Learning: A Review of the Quality of the Literature

Directory of Open Access Journals (Sweden)

Samy A. Azer

2016-12-01

Conclusions: There was no solid evidence that the use of 3D models is superior to traditional teaching. However, the studies varied in research quality. More studies are needed to examine the short- and long-term impacts of 3D models on learning using valid and appropriate tools.

3D web based learning of medical equipment employed in intensive care units.

Science.gov (United States)

Cetin, Aydın

2012-02-01

In this paper, both synchronous and asynchronous web based learning of 3D medical equipment models used in hospital intensive care unit have been described over the moodle course management system. 3D medical equipment models were designed with 3ds Max 2008, then converted to ASE format and added interactivity displayed with Viewpoint-Enliven. 3D models embedded in a web page in html format with dynamic interactivity-rotating, panning and zooming by dragging a mouse over images-and descriptive information is embedded to 3D model by using xml format. A pilot test course having 15 h was applied to technicians who is responsible for intensive care unit at Medical Devices Repairing and Maintenance Center (TABOM) of Turkish High Specialized Hospital.

CYP2D7 sequence variation interferes with TaqMan CYP2D6*15 and *35 genotyping

Directory of Open Access Journals (Sweden)

Amanda K Riffel

2016-01-01

Full Text Available TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false positive CYP2D6*15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6*15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6*35 which is also located in exon 1. Although alternative CYP2D6*15 and *35 assays resolved the issue, we discovered a novel CYP2D6*15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6*15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696 SNP of CYP2D6*43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer and/or probe

Seasonal Variation of Provitamin D2 and Vitamin D2 in Perennial Ryegrass (Lolium perenne L.)

DEFF Research Database (Denmark)

Jäpelt, Rie Bak; Didion, Thomas; Smedsgaard, Jørn

2011-01-01

Ergosterol (provitamin D(2)) is converted to vitamin D(2) in grass by exposure to UV light. Six varieties of perennial ryegrass (Lolium perenne L.) were harvested four times during the season, and the contents of vitamin D(2) and ergosterol were analyzed by a sensitive and selective liquid...... chromatography tandem mass spectrometry method. Weather factors were recorded, and a principal component analysis was performed to study which factors were important for the formation of vitamin D(2). The results suggest that a combination of weather factors is involved and that the contents of ergosterol...... and vitamin D(2) change more than a factor of 10 during the season. These results demonstrate that grass potentially can be a significant source of vitamin D for grazing animals and animals fed on silage and hay....

Effects of Boreal Lake Wetlands on Atmospheric 13CH3D and 12CH2D2

Science.gov (United States)

Haghnegahdar, M. A.; Kohl, I. E.; Schauble, E. A.; Walter Anthony, K. M.; Young, E. D.

2017-12-01

Recently, we developed a theoretical model to investigate the potential use of 13CH3D and 12CH2D2 as tools for tracking atmospheric methane budget. We used electronic structure methods to estimate kinetic isotope fractionations associated with the major sink reactions of CH4 in air (reactions with •OH and Cl•), and literature data with reconnaissance measurements of the relative abundances of 13CH3D and 12CH2D2 to estimate the compositions of the largest atmospheric sources. Here we present new methane rare isotopologue data from boreal wetlands, comprising one of the most important sources, in order to evaluate the robustness of the model. Boreal wetlands (>55° N) account for more than half of the wetland area in the Northern hemisphere. We analyzed methane samples from high latitude lakes representing different geographical regions, geological and ecological contexts, methane fluxes, and isotopic signatures. Using clumped isotopes of CH4 we are able to determine the likely production mechanism for natural CH4 samples. So far, all of our analyzed samples except one plot in the microbial pure-culture methanogenesis field (Young et al. 2017) with ranges of -0.2‰ to +1.2‰ for Δ13CH3D, and -29.6‰ to -18.2‰ for Δ12CH2D2. These compositions are far from equilibrium. The one exception, from Lake Doughnut, Alaska, exhibits Δ13CH3D and Δ12CH2D2 values of +5.2‰ and +18.7‰, respectively, which fall near ambient thermodynamic equilibrium values. This may be an effect of methanotrophy. Mean Δ13CH3D and Δ12CH2D2 for all lake samples are +1.7‰ and -15.4‰ respectively, compared to our original estimate of +6.1‰ and +21.2‰ for the wetland methane source based on an assumption of equilibrium. If we assume that these samples are representative of the overall wetland source, Δ13CH3D decreases by 0.8‰ and Δ12CH2D2 decreases by 0.6‰ in our model of bulk atmospheric methane. Δ13CH3D and Δ12CH2D2 values of air (including •OH and Cl• sink

Machine Learning Takes on Health Care: Leonard D'Avolio's Cyft Employs Big Data to Benefit Patients and Providers.

Science.gov (United States)

Mertz, Leslie

2018-01-01

When Leonard D'Avolio (Figure 1) was working on his Ph.D. degree in biomedical informatics, he saw the power of machine learning in transforming multiple industries; health care, however, was not among them. "The reason that Amazon, Netflix, and Google have transformed their industries is because they have embedded learning throughout every aspect of what they do. If we could prove that is possible in health care too, I thought we would have the potential to have a huge impact," he says.

Vitamin D and type 2 diabetes.

Science.gov (United States)

Lips, Paul; Eekhoff, Marelise; van Schoor, Natasja; Oosterwerff, Mirjam; de Jongh, Renate; Krul-Poel, Yvonne; Simsek, Suat

2017-10-01

Vitamin D deficiency is associated with a decreased insulin release, insulin resistance and type 2 diabetes in experimental and epidemiological studies. Animal studies show that 1α,25-dihydroxyvitamin D 3 (1,25(OH) 2 D 3 ) stimulates the pancreatic β-cell to secrete insulin. The relationship between vitamin D deficiency and insulin resistance could develop through inflammation, as vitamin D deficiency is associated with increased inflammatory markers. In addition, genetic polymorphisms of vitamin D -related genes may predispose to impaired glycemic control and type 2 diabetes. Epidemiologic studies showed an association between low serum 25-hydroxyvitamin D 3 (25(OH)D 3 ) concentration and an increased risk for the metabolic syndrome and type 2 diabetes. This may be partly explained by an increased fat mass. A possible causal relationship between vitamin D deficiency and type 2 diabetes should be proven by randomized clinical trials showing that either type 2 diabetes can be prevented or insulin release and insulin sensitivity can be improved by vitamin D supplements. The results of randomized clinical trials on the effect of vitamin D versus placebo, sometimes combined with calcium, in patients with impaired glucose tolerance ("prediabetes") or type 2 diabetes are inconsistent. Some studies showed a slight decrease of fasting plasma glucose or improvement of insulin resistance, but often only in posthoc analyses. These effects are mainly visible in patients with vitamin D deficiency and impaired glucose tolerance at baseline. Meta-analyses of randomized clinical trials in general did not show significant effects of vitamin D supplementation on glycemic control. Currently, several large scale randomized clinical trials with vitamin D supplementation in doses of 1600-4000IU/d are ongoing with glycemic control or incidence of diabetes mellitus as outcome. Vitamin D deficiency needs to be prevented or cured, but until the results of these trials are published, high

Thermodynamics of the localized D2-D6 system

International Nuclear Information System (INIS)

Gomez-Reino, Marta; Naculich, Stephen G.; Schnitzer, Howard J.

2005-01-01

An exact fully-localized extremal supergravity solution for N 2 D2-branes and N 6 D6-branes, which is dual to 3-dimensional supersymmetric SU(N 2 ) gauge theory with N 6 fundamentals, was found by Cherkis and Hashimoto. In order to consider the thermal properties of the gauge theory we present the non-extremal extension of this solution to first order in an expansion near the core of the D6-branes. We compute the Hawking temperature and the black-brane horizon area/entropy. The leading-order entropy, which is proportional to N 2 3/2 N 6 1/2 T H 2 , is not corrected to first order in the expansion. This result is consistent with the analogous weak-coupling result at the correspondence point N 2 similar to N 6

Enhancing Nuclear Newcomer Training with 3D Visualization Learning Tools

International Nuclear Information System (INIS)

Gagnon, V.

2016-01-01

Full text: While the nuclear power industry is trying to reinforce its safety and regain public support post-Fukushima, it is also faced with a very real challenge that affects its day-to-day activities: a rapidly aging workforce. Statistics show that close to 40% of the current nuclear power industry workforce will retire within the next five years. For newcomer countries, the challenge is even greater, having to develop a completely new workforce. The workforce replacement effort introduces nuclear newcomers of a new generation with different backgrounds and affinities. Major lifestyle differences between the two generations of workers result, amongst other things, in different learning habits and needs for this new breed of learners. Interactivity, high visual content and quick access to information are now necessary to achieve a high level of retention. To enhance existing training programmes or to support the establishment of new training programmes for newcomer countries, L-3 MAPPS has devised learning tools to enhance these training programmes focused on the “Practice-by-Doing” principle. L-3 MAPPS has coupled 3D computer visualization with high-fidelity simulation to bring real-time, simulation-driven animated components and systems allowing immersive and participatory, individual or classroom learning. (author

From Web 2.0 to Learning Games 2.0

DEFF Research Database (Denmark)

Duus Henriksen, Thomas

2011-01-01

Learning games often fail in taking into account the extensive knowledge adult learners often have on the subject taught. This paper reports from a reconfiguration of a current learning game on leadership styles called LEADER, which on basis of ideas from web 2.0, is reconfigured to include...... the current and practical understandings brought by its participants. By inviting the participants into a semi-design process, the participants are asked to construct the game-content they would otherwise be playing. Results indicate that apart from being more time-consuming, LEADER 2.0 offers an effective...

Use of 3D Printed Models in Medical Education: A Randomized Control Trial Comparing 3D Prints versus Cadaveric Materials for Learning External Cardiac Anatomy

Science.gov (United States)

Lim, Kah Heng Alexander; Loo, Zhou Yaw; Goldie, Stephen J.; Adams, Justin W.; McMenamin, Paul G.

2016-01-01

Three-dimensional (3D) printing is an emerging technology capable of readily producing accurate anatomical models, however, evidence for the use of 3D prints in medical education remains limited. A study was performed to assess their effectiveness against cadaveric materials for learning external cardiac anatomy. A double blind randomized…

Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

2017-01-01

of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

2D-3D registration for cranial radiation therapy using a 3D kV CBCT and a single limited field-of-view 2D kV radiograph.

Science.gov (United States)

Munbodh, Reshma; Knisely, Jonathan Ps; Jaffray, David A; Moseley, Douglas J

2018-05-01

We present and evaluate a fully automated 2D-3D intensity-based registration framework using a single limited field-of-view (FOV) 2D kV radiograph and a 3D kV CBCT for 3D estimation of patient setup errors during brain radiotherapy. We evaluated two similarity measures, the Pearson correlation coefficient on image intensity values (ICC) and maximum likelihood measure with Gaussian noise (MLG), derived from the statistics of transmission images. Pose determination experiments were conducted on 2D kV radiographs in the anterior-posterior (AP) and left lateral (LL) views and 3D kV CBCTs of an anthropomorphic head phantom. In order to minimize radiation exposure and exclude nonrigid structures from the registration, limited FOV 2D kV radiographs were employed. A spatial frequency band useful for the 2D-3D registration was identified from the bone-to-no-bone spectral ratio (BNBSR) of digitally reconstructed radiographs (DRRs) computed from the 3D kV planning CT of the phantom. The images being registered were filtered accordingly prior to computation of the similarity measures. We evaluated the registration accuracy achievable with a single 2D kV radiograph and with the registration results from the AP and LL views combined. We also compared the performance of the 2D-3D registration solutions proposed to that of a commercial 3D-3D registration algorithm, which used the entire skull for the registration. The ground truth was determined from markers affixed to the phantom and visible in the CBCT images. The accuracy of the 2D-3D registration solutions, as quantified by the root mean squared value of the target registration error (TRE) calculated over a radius of 3 cm for all poses tested, was ICC AP : 0.56 mm, MLG AP : 0.74 mm, ICC LL : 0.57 mm, MLG LL : 0.54 mm, ICC (AP and LL combined): 0.19 mm, and MLG (AP and LL combined): 0.21 mm. The accuracy of the 3D-3D registration algorithm was 0.27 mm. There was no significant difference in mean TRE for the 2D-3D registration

Peningkatan Hasil Belajar Fisika Melalui Model Pembelajaran Kooperatif Tipe Team Assisted Individualization pada Siswa Kelas VII.D SMP Negeri 2 Bangkala Kabupaten Jeneponto

Directory of Open Access Journals (Sweden)

Suhardi Suhardi

2015-12-01

Full Text Available Abstract This research is a class action (Classroom Action Research, which aims to improve learning outcomes Physics VII.D grade students of SMP Negeri 2 Bangkala through Cooperative Learning Model Team Assisted Individualization. The subjects were VII.D grade students of SMP Negeri 2 Bangkala on odd semester 2013/2014 academic year consisting of 36 students. Research conducted two cycles consisting of four activities, namely: planning, action, observation and reflection. In the first cycle was conducted over four sessions and the second cycle was conducted over four sessions. Data collection was done by studying the results of the final tests of learning at the end of the first cycle and the end of the second cycle. The collected data were analyzed quantitatively and qualitatively. The results of the quantitative analysis of physics learning outcome data indicate that the number of students classified as learning completed the first cycle were completed only 22 0rang 61.11% and in the second cycle up to 25 people who completed 69.44%. The results of the qualitative analysis showed an increase in activity of students during the learning process through a model of Cooperative Learning Physics Team Assisted Individualization type. Based on these results it can be concluded that the physics learning through cooperative learning model of Type Team Assisted Individualization can improve student learning outcomes. Keywords: Results Learning, Cooperative Learning Model Team Assisted Individualization, Qualitative, and Student Activities Abstrak Penelitian ini adalah penelitian tindakan kelas (Classroom Action Research yang bertujuan meningkatkan hasil belajar Fisika siswa kelas VII.D SMP Negeri 2 Bangkala melalui Model Pembelajaran Kooperatif Tipe Team Assisted Individualization. Subjek penelitian ini adalah siswa kelas VII.D SMP Negeri 2 Bangkala pada semester ganjil tahun pelajaran 2013/2014 yang terdiri dari 36 siswa. Penelitian dilaksanakan dua

Hybrid 3D-2D printing for bone scaffolds fabrication

Science.gov (United States)

Seleznev, V. A.; Prinz, V. Ya

2017-02-01

It is a well-known fact that bone scaffold topography on micro- and nanometer scale influences the cellular behavior. Nano-scale surface modification of scaffolds allows the modulation of biological activity for enhanced cell differentiation. To date, there has been only a limited success in printing scaffolds with micro- and nano-scale features exposed on the surface. To improve on the currently available imperfect technologies, in our paper we introduce new hybrid technologies based on a combination of 2D (nano imprint) and 3D printing methods. The first method is based on using light projection 3D printing and simultaneous 2D nanostructuring of each of the layers during the formation of the 3D structure. The second method is based on the sequential integration of preliminarily created 2D nanostructured films into a 3D printed structure. The capabilities of the developed hybrid technologies are demonstrated with the example of forming 3D bone scaffolds. The proposed technologies can be used to fabricate complex 3D micro- and nanostructured products for various fields.

D.E.E.P. Learning: Promoting Informal STEM Learning through Ocean Research Simulation Games

Science.gov (United States)

Simms, E.; Rohrlick, D.; Layman, C.; Peach, C. L.; Orcutt, J. A.; Keen, C. S.; Matthews, J.; Nsf Ooi-Ci Education; Public Engagement Team

2010-12-01

It is generally recognized that interactive digital games have the potential to promote the development of valuable learning and life skills, including data processing, decision-making, critical thinking, planning, communication and collaboration (Kirriemuir and MacFarlane, 2006). But the research and development of educational games, and the study of the educational value of interactive games in general, have lagged far behind the same efforts for games created for the purpose of entertainment. Our group is attempting to capitalize on the facts that games are now played in 67% of American households (ESA, 2010), and across a broad range of ages, by developing effective and engaging simulation games that promote Science, Technology, Engineering and Mathematics (STEM) literacy in informal science education institutions (ISEIs; e.g., aquariums, museums, science centers). In particular, we are developing games based on the popular Microsoft Xbox360 gaming platform and the free Microsoft XNA game development kit, which engage ISEI visitors in the exploration and understanding of the deep-sea environment. Known as Deep-sea Extreme Environment Pilot (D.E.E.P.), the games place players in the role of piloting a remotely-operated vehicle (ROV) to complete science-based objectives associated with the exploration of ocean observing systems and hydrothermal vent environments. In addition to creating a unique educational product, our efforts are intended to identify 1) the key elements of a successful STEM-based simulation game experience in an informal science education institution, and 2) which aspects of game design (e.g., challenge, curiosity, fantasy, personal recognition) are most effective at maximizing both learning and enjoyment. We will share our progress to date, including formative assessment results from testing the game prototypes at Birch Aquarium at Scripps, and discuss the potential benefits and challenges to interactive gaming as a tool to support STEM

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

Science.gov (United States)

Qi, Jin; Yang, Zhiyong

2014-01-01

Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

Directory of Open Access Journals (Sweden)

Jin Qi

Full Text Available Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

Functional characterization of a first avian cytochrome P450 of the CYP2D subfamily (CYP2D49.

Directory of Open Access Journals (Sweden)

Hua Cai

Full Text Available The CYP2D family members are instrumental in the metabolism of 20-25% of commonly prescribed drugs. Although many CYP2D isoforms have been well characterized in other animal models, research concerning the chicken CYP2Ds is limited. In this study, a cDNA encoding a novel CYP2D enzyme (CYP2D49 was cloned from the chicken liver for the first time. The CYP2D49 cDNA contained an open reading frame of 502 amino acids that shared 52%-57% identities with other CYP2Ds. The gene structure and neighboring genes of CYP2D49 are conserved and similar to those of human CYP2D6. Additionally, similar to human CYP2D6, CYP2D49 is un-inducible in the liver and expressed predominantly in the liver, kidney and small intestine, with detectable levels in several other tissues. Metabolic assays of the CYP2D49 protein heterologously expressed in E. coli and Hela cells indicated that CYP2D49 metabolized the human CYP2D6 substrate, bufuralol, but not debrisoquine. Moreover, quinidine, a potent inhibitor of human CYP2D6, only inhibited the bufuralol 1'-hydroxylation activity of CYP2D49 to a negligible degree. All these results indicated that CYP2D49 had functional characteristics similar to those of human CYP2D6 but measurably differed in the debrisoquine 4'-hydroxylation and quinidine inhibitory profile. Further structure-function investigations that employed site-directed mutagenesis and circular dichroism spectroscopy identified the importance of Val-126, Glu-222, Asp-306, Phe-486 and Phe-488 in keeping the enzymatic activity of CYP2D49 toward bufuralol as well as the importance of Asp-306, Phe-486 and Phe-488 in maintaining the conformation of CYP2D49 protein. The current study is only the first step in characterizing the metabolic mechanism of CYP2D49; further studies are still required.

Using Competency-Based Digital Open Learning Activities to Facilitate and Promote Health Professions Education (OLAmeD): A Proposal.

Science.gov (United States)

Vaitsis, Christos; Stathakarou, Natalia; Barman, Linda; Zary, Nabil; McGrath, Cormac

2016-07-07

Traditional learning in medical education has been transformed with the advent of information technology. We have recently seen global initiatives to produce online activities in an effort to scale up learning opportunities through learning management systems and massive open online courses for both undergraduate and continued professional education. Despite the positive impact of such efforts, factors such as cost, time, resources, and the specificity of educational contexts restrict the design and exchange of online medical educational activities. The goal is to address the stated issues within the health professions education context while promoting learning by proposing the Online Learning Activities for Medical Education (OLAmeD) concept which builds on unified competency frameworks and generic technical standards for education. We outline how frameworks used to describe a set of competencies for a specific topic in medical education across medical schools in the United States and Europe can be compared to identify commonalities that could result in a unified set of competencies representing both contexts adequately. Further, we examine how technical standards could be used to allow standardization, seamless sharing, and reusability of educational content. The entire process of developing and sharing OLAmeD is structured and presented in a set of steps using as example Urology as a part of clinical surgery specialization. Beyond supporting the development, sharing, and repurposing of educational content, we expect OLAmeD to work as a tool that promotes learning and sets a base for a community of medical educational content developers across different educational contexts.

3D Printing as Learning Activity in Higher Education A case study in a robotics’ prototyping course

OpenAIRE

Drakoulaki, Aikaterini

2017-01-01

This thesis is inspired by the new opportunities new technologies provide in education and more precisely in higher education. There is a general focus in higher education on supporting student learning beyond learning the existing knowledge, so that students are prepared for taking part in knowledge- generating activities in their future working environment. Technologies can offer new opportunities for exploring and constructing knowledge. The focus of this study is on 3D printing as a learn...

Dynamic Downlink Spectrum Access for D2D-Enabled Heterogeneous Networks

KAUST Repository

Radaydeh, Redha Mahmoud Mesleh; Al-Qahtani, Fawaz S.; Celik, Abdulkadir; Alouini, Mohamed-Slim

2018-01-01

This paper proposes new approaches for underlay device- to-device (D2D) communication in spectrum-shared het- erogeneous cellular networks. It considers devices that share downlink resources and have an enabled D2D feature to improve coverage

The Effect of D-Cycloserine on Immediate vs. Delayed Extinction of Learned Fear

Science.gov (United States)

Langton, Julia M.; Richardson, Rick

2010-01-01

We compared the effect of D-cycloserine (DCS) on immediate (10 min after conditioning) and delayed (24 h after conditioning) extinction of learned fear in rats. DCS facilitated both immediate and delayed extinction when the drug was administered after extinction training. However, DCS did not facilitate immediate extinction when administered prior…

Think3d!: Improving mathematics learning through embodied spatial training.

Science.gov (United States)

Burte, Heather; Gardony, Aaron L; Hutton, Allyson; Taylor, Holly A

2017-01-01

Spatial thinking skills positively relate to Science, Technology, Engineering, and Math (STEM) outcomes, but spatial training is largely absent in elementary school. Elementary school is a time when children develop foundational cognitive skills that will support STEM learning throughout their education. Spatial thinking should be considered a foundational cognitive skill. The present research examined the impact of an embodied spatial training program on elementary students' spatial and mathematical thinking. Students in rural elementary schools completed spatial and math assessments prior to and after participating in an origami and pop-up paper engineering-based program, called Think3d!. Think3d! uses embodied tasks, such as folding and cutting paper, to train two-dimensional to three-dimensional spatial thinking. Analyses explored spatial thinking gains, mathematics gains - specifically for problem types expected to show gains from spatial training - and factors predicting mathematics gains. Results showed spatial thinking gains in two assessments. Using a math categorization to target problems more and less likely to be impacted by spatial training, we found that all students improved on real-world math problems and older students improved on visual and spatial math problems. Further, the results are suggestive of developmental time points for implementing embodied spatial training related to applying spatial thinking to math. Finally, the spatial thinking assessment that was most highly related to training activities also predicted math performance gains. Future research should explore developmental issues related to how embodied spatial training might support STEM learning and outcomes.

WHAT ARE AGRICULTURAL ECONOMICS PH.D. STUDENTS LEARNING ABOUT AGRIBUSINESS RESEARCH METHODS AND SUBJECT AREAS?

OpenAIRE

House, Lisa; Sterns, James A.

2002-01-01

This document contains the PowerPoint presentation given by the authors at the 2002 WCC-72 meetings, regarding what agricultural economics Ph.D students are learning about agribusiness research methods and subject areas.

2d index and surface operators

International Nuclear Information System (INIS)

Gadde, Abhijit; Gukov, Sergei

2014-01-01

In this paper we compute the superconformal index of 2d (2,2) supersymmetric gauge theories. The 2d superconformal index, a.k.a. flavored elliptic genus, is computed by a unitary matrix integral much like the matrix integral that computes the 4d superconformal index. We compute the 2d index explicitly for a number of examples. In the case of abelian gauge theories we see that the index is invariant under flop transition and under CY-LG correspondence. The index also provides a powerful check of the Seiberg-type duality for non-abelian gauge theories discovered by Hori and Tong. In the later half of the paper, we study half-BPS surface operators in N=2 superconformal gauge theories. They are engineered by coupling the 2d (2,2) supersymmetric gauge theory living on the support of the surface operator to the 4d N=2 theory, so that different realizations of the same surface operator with a given Levi type are related by a 2d analogue of the Seiberg duality. The index of this coupled system is computed by using the tools developed in the first half of the paper. The superconformal index in the presence of surface defect is expected to be invariant under generalized S-duality. We demonstrate that it is indeed the case. In doing so the Seiberg-type duality of the 2d theory plays an important role

Strategy approach for eLearning 2.0 deployment in Universities

Directory of Open Access Journals (Sweden)

Oskar Casquero

2010-12-01

Full Text Available The institutionally powered Personal Learning Environment (iPLE constitutes our vision of how Web 2.0 technologies, people arrangement and data sharing could be applied for delivering open, flexible, distributed and learner-centred learning environments to university members. Based on the iPLE, this paper explores a strategy approach that universities could follow in order to deploy eLearning 2.0 tools and services. With that aim in mind, we review the patterns that Web 2.0 has successfully applied, and have been proved to encourage people to interact and to share information. Then, we present an eLearning 2.0 provisioning strategy based on iPLEs. Finally, we explain how this strategy can help translating Web 2.0 patterns to learning, and positioning universities as eLearning 2.0 providers.

The effect of image quality, repeated study, and assessment method on anatomy learning.

Science.gov (United States)

Fenesi, Barbara; Mackinnon, Chelsea; Cheng, Lucia; Kim, Joseph A; Wainman, Bruce C

2017-06-01

The use of two-dimensional (2D) images is consistently used to prepare anatomy students for handling real specimen. This study examined whether the quality of 2D images is a critical component in anatomy learning. The visual clarity and consistency of 2D anatomical images was systematically manipulated to produce low-quality and high-quality images of the human hand and human eye. On day 0, participants learned about each anatomical specimen from paper booklets using either low-quality or high-quality images, and then completed a comprehension test using either 2D images or three-dimensional (3D) cadaveric specimens. On day 1, participants relearned each booklet, and on day 2 participants completed a final comprehension test using either 2D images or 3D cadaveric specimens. The effect of image quality on learning varied according to anatomical content, with high-quality images having a greater effect on improving learning of hand anatomy than eye anatomy (high-quality vs. low-quality for hand anatomy P = 0.018; high-quality vs. low-quality for eye anatomy P = 0.247). Also, the benefit of high-quality images on hand anatomy learning was restricted to performance on short-answer (SA) questions immediately after learning (high-quality vs. low-quality on SA questions P = 0.018), but did not apply to performance on multiple-choice (MC) questions (high-quality vs. low-quality on MC questions P = 0.109) or after participants had an additional learning opportunity (24 hours later) with anatomy content (high vs. low on SA questions P = 0.643). This study underscores the limited impact of image quality on anatomy learning, and questions whether investment in enhancing image quality of learning aids significantly promotes knowledge development. Anat Sci Educ 10: 249-261. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

NARCIS (Netherlands)

Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

2009-01-01

Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. Presentation at the 2nd Workshop Mash-Up Personal Learning

2D/ 3D Quantitative Ultrasound of the Breast

Science.gov (United States)

Nasief, Haidy Gerges

Breast cancer is the second leading cause of cancer death of women in the United States, so breast cancer screening for early detection is common. The purpose of this dissertation is to optimize quantitative ultrasound (QUS) methods to improve the specificity and objectivity of breast ultrasound. To pursue this goal, the dissertation is divided into two parts: 1) to optimize 2D QUS, and 2) to introduce and validate 3D QUS. Previous studies had validated these methods in phantoms. Applying our QUS analysis on subcutaneous breast fat demonstrated that QUS parameter estimates for subcutaneous fat were consistent among different human subjects. This validated our in vivo data acquisition methods and supported the use of breast fat as a clinical reference tissue for ultrasound BI-RADSRTM assessments. Although current QUS methods perform well for straightforward cases when assumptions of stationarity and diffuse scattering are well-founded, these conditions often are not present due to the complicated nature of in vivo breast tissue. Key improvements in QUS algorithms to address these challenges were: 1) applying a "modified least squares method (MLSM)" to account for the heterogeneous tissue path between the transducer and the region of interest, ROI; 2) detecting anisotropy in acoustic parameters; and 3) detecting and removing the echo sources that depart from diffuse and stationary scattering conditions. The results showed that a Bayesian classifier combining three QUS parameters in a biased pool of high-quality breast ultrasound data successfully differentiated all fibroadenomas from all carcinomas. Given promising initial results in 2D, extension to 3D acquisitions in QUS provided a unique capability to test QUS for the entire breast volume. QUS parameter estimates using 3D data were consistent with those found in 2D for phantoms and in vivo data. Extensions of QUS technology from 2D to 3D can improve the specificity of breast ultrasound, and thus, could lead to

Quantitative studies of the brain specific antigens GFA, 14-3-2, synaptin C1, D1, D2, D3 and D5 in jimpy mouse

DEFF Research Database (Denmark)

Jacque, C M; Baumann, N A; Bock, E

1976-01-01

Seven antigens specific to the nervous tissue were measured in both Jimpy and control mice. The D5 and the GFA protein, both components of the glia, are strongly increased in the mutant while the neuronal components 14-3-2, synaptin C1, D1, D2 and D3 are unchanged....

High current density 2D/3D MoS2/GaN Esaki tunnel diodes

Science.gov (United States)

Krishnamoorthy, Sriram; Lee, Edwin W.; Lee, Choong Hee; Zhang, Yuewei; McCulloch, William D.; Johnson, Jared M.; Hwang, Jinwoo; Wu, Yiying; Rajan, Siddharth

2016-10-01

The integration of two-dimensional materials such as transition metal dichalcogenides with bulk semiconductors offer interesting opportunities for 2D/3D heterojunction-based device structures without any constraints of lattice matching. By exploiting the favorable band alignment at the GaN/MoS2 heterojunction, an Esaki interband tunnel diode is demonstrated by transferring large area Nb-doped, p-type MoS2 onto heavily n-doped GaN. A peak current density of 446 A/cm2 with repeatable room temperature negative differential resistance, peak to valley current ratio of 1.2, and minimal hysteresis was measured in the MoS2/GaN non-epitaxial tunnel diode. A high current density of 1 kA/cm2 was measured in the Zener mode (reverse bias) at -1 V bias. The GaN/MoS2 tunnel junction was also modeled by treating MoS2 as a bulk semiconductor, and the electrostatics at the 2D/3D interface was found to be crucial in explaining the experimentally observed device characteristics.

A Hybrid 2D/3D User Interface for Radiological Diagnosis.

Science.gov (United States)

Mandalika, Veera Bhadra Harish; Chernoglazov, Alexander I; Billinghurst, Mark; Bartneck, Christoph; Hurrell, Michael A; Ruiter, Niels de; Butler, Anthony P H; Butler, Philip H

2018-02-01

This paper presents a novel 2D/3D desktop virtual reality hybrid user interface for radiology that focuses on improving 3D manipulation required in some diagnostic tasks. An evaluation of our system revealed that our hybrid interface is more efficient for novice users and more accurate for both novice and experienced users when compared to traditional 2D only interfaces. This is a significant finding because it indicates, as the techniques mature, that hybrid interfaces can provide significant benefit to image evaluation. Our hybrid system combines a zSpace stereoscopic display with 2D displays, and mouse and keyboard input. It allows the use of 2D and 3D components interchangeably, or simultaneously. The system was evaluated against a 2D only interface with a user study that involved performing a scoliosis diagnosis task. There were two user groups: medical students and radiology residents. We found improvements in completion time for medical students, and in accuracy for both groups. In particular, the accuracy of medical students improved to match that of the residents.

Effects of vitamin D2-fortified bread v. supplementation with vitamin D2 or D3 on serum 25-hydroxyvitamin D metabolites: an 8-week randomised-controlled trial in young adult Finnish women.

Science.gov (United States)

Itkonen, Suvi T; Skaffari, Essi; Saaristo, Pilvi; Saarnio, Elisa M; Erkkola, Maijaliisa; Jakobsen, Jette; Cashman, Kevin D; Lamberg-Allardt, Christel

2016-04-14

There is a need for food-based solutions for preventing vitamin D deficiency. Vitamin D3 (D3) is mainly used in fortified food products, although the production of vitamin D2 (D2) is more cost-effective, and thus may hold opportunities. We investigated the bioavailability of D2 from UV-irradiated yeast present in bread in an 8-week randomised-controlled trial in healthy 20-37-year-old women (n 33) in Helsinki (60°N) during winter (February-April) 2014. Four study groups were given different study products (placebo pill and regular bread=0 µg D2 or D3/d; D2 supplement and regular bread=25 µg D2/d; D3 supplement and regular bread=25 µg D3/d; and placebo pill and D2-biofortified bread=25 µg D2/d). Serum 25-hydroxyvitamin D2 (S-25(OH)D2) and serum 25-hydroxyvitamin D3 (S-25(OH)D3) concentrations were measured at baseline, midpoint and end point. The mean baseline total serum 25-hydroxyvitamin D (S-25(OH)D=S-25(OH)D2+S-25(OH)D3) concentration was 65·1 nmol/l. In repeated-measures ANCOVA (adjusted for baseline S-25(OH)D as total/D2/D3), D2-bread did not affect total S-25(OH)D (P=0·707) or S-25(OH)D3 (P=0·490), but increased S-25(OH)D2 compared with placebo (PD2 supplement was more effective than bread in increasing S-25(OH)D2 (PD2 and D3 supplementation increased total S-25(OH)D compared with placebo (P=0·030 and P=0·001, respectively), but D2 supplementation resulted in lower S-25(OH)D3 (PD2 from UV-irradiated yeast in bread was not bioavailable in humans. Our results support the evidence that D2 is less potent in increasing total S-25(OH)D concentrations than D3, also indicating a decrease in the percentage contribution of S-25(OH)D3 to the total vitamin D pool.

Thermodynamics of the localized D2-D6 system

Energy Technology Data Exchange (ETDEWEB)

Gomez-Reino, Marta [Martin Fisher School of Physics, Brandeis University, Waltham, MA 02454 (United States)]. E-mail: marta@brandeis.edu; Naculich, Stephen G. [Department of Physics, Bowdoin College, Brunswick, ME 04011 (United States)]. E-mail: naculich@bowdoin.edu; Schnitzer, Howard J. [Martin Fisher School of Physics, Brandeis University, Waltham, MA 02454 (United States)]. E-mail: schnitzer@brandeis.edu

2005-05-02

An exact fully-localized extremal supergravity solution for N{sub 2} D2-branes and N{sub 6} D6-branes, which is dual to 3-dimensional supersymmetric SU(N{sub 2}) gauge theory with N{sub 6} fundamentals, was found by Cherkis and Hashimoto. In order to consider the thermal properties of the gauge theory we present the non-extremal extension of this solution to first order in an expansion near the core of the D6-branes. We compute the Hawking temperature and the black-brane horizon area/entropy. The leading-order entropy, which is proportional to N{sub 2}{sup 3/2}N{sub 6}{sup 1/2}T{sub H}{sup 2}, is not corrected to first order in the expansion. This result is consistent with the analogous weak-coupling result at the correspondence point N{sub 2} similar to N{sub 6}.

Enhancing Collaborative Learning in Web 2.0-Based E-Learning Systems: A Design Framework for Building Collaborative E-Learning Contents

Science.gov (United States)

El Mhouti, Abderrahim; Nasseh, Azeddine; Erradi, Mohamed; Vasquèz, José Marfa

2017-01-01

Today, the implication of Web 2.0 technologies in e-learning allows envisaging new teaching and learning forms, advocating an important place to the collaboration and social interaction. However, in e-learning systems, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning courses can be that…

Definitive difference among [DS-D2O], [DS-H2O] and [Bulk-D2O] cells in the deuterization and deuterium-reaction

International Nuclear Information System (INIS)

Arata, Yoshiaki; Zhang, Yue Chang

2000-01-01

We observed a new phenomena that the enormous amount of deuterium/hydrogen can be absorbed quickly as a 'solute-atom' into fine metal powders embedded inside a double-structure (DS) cathode in the electrolyses of D 2 O and H 2 O-electrolytes, respectively, but such highly deuterated powders can be produced only using DS-cathode immersed in D 2 O-electrolyte; [DS-D 2 O], and never generated in H 2 O-electrolyte even using the DS-cathode; [DS-H 2 O]. On the other hand, [Bulk-D 2 O] with bulk-cathode made by the bulk Pd metal never produces highly deuterated metal as mentioned above even though using D 2 O-electrolyte. In short, the deuterium-concentration generating in [Bulk-D 2 O] is found to be much lower than that in [DS-D 2 O]. As a result, because of reason mentioned above, in marked contrast to the case with the [DS-D 2 O], neither excess heat nor 4 He production are observed with both [DS-H 2 O] and [Bulk-D 2 O]. (author)

A 2D driven 3D vessel segmentation algorithm for 3D digital subtraction angiography data

International Nuclear Information System (INIS)