A fast process development flow by applying design technology co-optimization

NASA Astrophysics Data System (ADS)

Chen, Yi-Chieh; Yeh, Shin-Shing; Ou, Tsong-Hua; Lin, Hung-Yu; Mai, Yung-Ching; Lin, Lawrence; Lai, Jun-Cheng; Lai, Ya Chieh; Xu, Wei; Hurat, Philippe

2017-03-01

Beyond 40 nm technology node, the pattern weak points and hotspot types increase dramatically. The typical patterns for lithography verification suffers huge turn-around-time (TAT) to handle the design complexity. Therefore, in order to speed up process development and increase pattern variety, accurate design guideline and realistic design combinations are required. This paper presented a flow for creating a cell-based layout, a lite realistic design, to early identify problematic patterns which will negatively affect the yield. A new random layout generating method, Design Technology Co-Optimization Pattern Generator (DTCO-PG), is reported in this paper to create cell-based design. DTCO-PG also includes how to characterize the randomness and fuzziness, so that it is able to build up the machine learning scheme which model could be trained by previous results, and then it generates patterns never seen in a lite design. This methodology not only increases pattern diversity but also finds out potential hotspot preliminarily. This paper also demonstrates an integrated flow from DTCO pattern generation to layout modification. Optical Proximity Correction, OPC and lithographic simulation is then applied to DTCO-PG design database to detect hotspots and then hotspots or weak points can be automatically fixed through the procedure or handled manually. This flow benefits the process evolution to have a faster development cycle time, more complexity pattern design, higher probability to find out potential hotspots in early stage, and a more holistic yield ramping operation.

You're Not Listening Loud Enough

ERIC Educational Resources Information Center

Lloyd-Zannini, Lou

2005-01-01

Essentially, communication style flows naturally from personality, just like behavior style and teaching/learning style. One can break down personality distinctions into four significant patterns or groups: commanders, cheerleaders, caregivers, and contemplators. In this article, the author describes each of these groups and discusses how to…

ClimateNet: A Machine Learning dataset for Climate Science Research

NASA Astrophysics Data System (ADS)

Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

2017-12-01

Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.

Altitude control in honeybees: joint vision-based learning and guidance.

PubMed

Portelli, Geoffrey; Serres, Julien R; Ruffier, Franck

2017-08-23

Studies on insects' visual guidance systems have shed little light on how learning contributes to insects' altitude control system. In this study, honeybees were trained to fly along a double-roofed tunnel after entering it near either the ceiling or the floor of the tunnel. The honeybees trained to hug the ceiling therefore encountered a sudden change in the tunnel configuration midways: i.e. a "dorsal ditch". Thus, the trained honeybees met a sudden increase in the distance to the ceiling, corresponding to a sudden strong change in the visual cues available in their dorsal field of view. Honeybees reacted by rising quickly and hugging the new, higher ceiling, keeping a similar forward speed, distance to the ceiling and dorsal optic flow to those observed during the training step; whereas bees trained to follow the floor kept on following the floor regardless of the change in the ceiling height. When trained honeybees entered the tunnel via the other entry (the lower or upper entry) to that used during the training step, they quickly changed their altitude and hugged the surface they had previously learned to follow. These findings clearly show that trained honeybees control their altitude based on visual cues memorized during training. The memorized visual cues generated by the surfaces followed form a complex optic flow pattern: trained honeybees may attempt to match the visual cues they perceive with this memorized optic flow pattern by controlling their altitude.

Patterns in Liberal Arts Curricula: A Survey of Program Models.

ERIC Educational Resources Information Center

Kolling, Orland W.

Characteristics of liberal arts education and different approaches to educational modeling are examined. Attention is directed to: applications of graphic depictions; Venn-Euler diagrams to represent inclusion-exclusion phenomena as well as areas of commonality in learning processes and liberal education; the uses of flow charts for describing…

Misconceived Causal Explanations for Emergent Processes

ERIC Educational Resources Information Center

Chi, Michelene T. H.; Roscoe, Rod D.; Slotta, James D.; Roy, Marguerite; Chase, Catherine C.

2012-01-01

Studies exploring how students learn and understand science processes such as "diffusion" and "natural selection" typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes' necks get longer over generations, or how ink dropped into water appears to "flow"). Instead of…

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

A neural network with modular hierarchical learning

NASA Technical Reports Server (NTRS)

Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

1994-01-01

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

Shifting Patterns of International Higher Education: Ebb and Flow or Sea Change?

ERIC Educational Resources Information Center

Middlehurst, Robin

2013-01-01

In November 2012, the US Department of Education published its first-ever "fully articulated international strategy." Its two strategic goals are to strengthen US education and advance the international priorities of the US through increasing the global competencies of students, learning from other countries, and engaging in education…

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Fengli; Li, Qinghua

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Networkmore » and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.« less

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

A comparative Study of Circulation Patterns at Active Lava Lakes

NASA Astrophysics Data System (ADS)

Lev, Einat; Oppenheimer, Clive; Spampinato, Letizia; Hernandez, Pedro; Unglert, Kathi

2016-04-01

Lava lakes present a rare opportunity to study magma dynamics in a large scaled-up "crucible" and provide a unique natural laboratory to ground-truth dynamic models of magma circulation. The persistence of lava lakes allows for long-term observations of flow dynamics and of lava properties, especially compared to surface lava flows. There are currently five persistent lava lakes in the world: Halemaumau in Kilauea (Hawaii, USA), Erta Ale (Ethiopia), Nyiragongo (Congo), Erebus (Antarctica), and Villarica (Chile). Marum and Benbow craters of Ambrym volcano (Vanuatu) and Masaya (Nicaragua) have often hosted lava lakes as well. We use visible-light and thermal infrared time-lapse and video footage collected at all above lakes (except Villarica, where the lake is difficult to observe), and compare the circulation patterns recorded. We calculate lake surface motion from the footage using the optical flow method (Lev et al., 2012) to produce 2D velocity fields. We mined both the surface temperature field and the surface velocity field for patterns using machine learning techniques such as "self-organizing maps (SOMs)" and "principle component analysis (PCA)". We use automatic detection technique to study the configuration of crustal plates at the lakes' surface. We find striking differences among the lakes, in flow direction, flow speed, frequency of changes in flow direction and speed, location and consistency of upwelling and downwelling, and crustal plate configuration. We relate the differences to lake size, shallow conduit geometry, lava viscosity, crystal and gas content, and crust integrity.

Mechanisms before Reactions: A Mechanistic Approach to the Organic Chemistry Curriculum Based on Patterns of Electron Flow

ERIC Educational Resources Information Center

Flynn, Alison B.; Ogilvie, William W.

2015-01-01

A significant redesign of the introductory organic chemistry curriculum at the authors' institution is described. There are two aspects that differ greatly from a typical functional group approach. First, organic reaction mechanisms and the electron-pushing formalism are taught before students have learned a single reaction. The conservation of…

An Analysis of Conceptual Flow Patterns and Structures in the Physics Classroom

NASA Astrophysics Data System (ADS)

Eshach, Haim

2010-03-01

The aim of the current research is to characterize the conceptual flow processes occurring in whole-class dialogic discussions with a high level of interanimation; in the present case, of a high-school class learning about image creation on plane mirrors. Using detailed chains of interaction and conceptual flow discourse maps-both developed for the purpose of this research-the classroom discourse, audio-taped and transcribed verbatim, was analyzed and three discussion structures were revealed: accumulation around budding foci concepts, zigzag between foci concepts, and concept tower. These structures as well as two additional factors, suggest the Two-Space Model of the whole class discussion proposed in the present article. The two additional factors are: (1) the teacher intervention; and (2) the conceptual barriers observed among the students, namely, materialistic thinking, and the tendency to attribute "unique characteristics" to optical devices. This model might help teachers to prepare and conduct efficient whole-class discussions which accord with the social constructivist perspective of learning.

Electrical comparison of iN7 EUV hybrid and EUV single patterning BEOL metal layers

NASA Astrophysics Data System (ADS)

Larivière, Stéphane; Wilson, Christopher J.; Kutrzeba Kotowska, Bogumila; Versluijs, Janko; Decoster, Stefan; Mao, Ming; van der Veen, Marleen H.; Jourdan, Nicolas; El-Mekki, Zaid; Heylen, Nancy; Kesters, Els; Verdonck, Patrick; Béral, Christophe; Van den Heuvel, Dieter; De Bisschop, Peter; Bekaert, Joost; Blanco, Victor; Ciofi, Ivan; Wan, Danny; Briggs, Basoene; Mallik, Arindam; Hendrickx, Eric; Kim, Ryoung-han; McIntyre, Greg; Ronse, Kurt; Bömmels, Jürgen; Tőkei, Zsolt; Mocuta, Dan

2018-03-01

The semiconductor scaling roadmap shows the continuous node to node scaling to push Moore's law down to the next generations. In that context, the foundry N5 node requires 32nm metal pitch interconnects for the advanced logic Back- End of Line (BEoL). 193immersion usage now requires self-aligned and/or multiple patterning technique combinations to enable such critical dimension. On the other hand, EUV insertion investigation shows that 32nm metal pitch is still a challenge but, related to process flow complexity, presents some clear motivations. Imec has already evaluated on test chip vehicles with different patterning approaches: 193i SAQP (Self-Aligned Quadruple Patterning), LE3 (triple patterning Litho Etch), tone inversion, EUV SE (Single Exposure) with SMO (Source-mask optimization). Following the run path in the technology development for EUV insertion, imec N7 platform (iN7, corresponding node to the foundry N5) is developed for those BEoL layers. In this paper, following technical motivation and development learning, a comparison between the iArF SAQP/EUV block hybrid integration scheme and a single patterning EUV flow is proposed. These two integration patterning options will be finally compared from current morphological and electrical criteria.

Misconceived causal explanations for emergent processes.

PubMed

Chi, Michelene T H; Roscoe, Rod D; Slotta, James D; Roy, Marguerite; Chase, Catherine C

2012-01-01

Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes' necks get longer over generations, or how ink dropped into water appears to "flow"). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as being caused by controlling agents with intentional goals, as well as express a variety of many other misconceived notions. In this article, we provide a hypothesis for what constitutes a misconceived explanation; why misconceived explanations are so prevalent, robust, and resistant to instruction; and offer one approach of how they may be overcome. In particular, we hypothesize that students misunderstand many science processes because they rely on a generalized version of narrative schemas and scripts (referred to here as a Direct-causal Schema) to interpret them. For science processes that are sequential and stage-like, such as cycles of moon, circulation of blood, stages of mitosis, and photosynthesis, a Direct-causal Schema is adequate for correct understanding. However, for science processes that are non-sequential (or emergent), such as diffusion, natural selection, osmosis, and heat flow, using a Direct Schema to understand these processes will lead to robust misconceptions. Instead, a different type of general schema may be required to interpret non-sequential processes, which we refer to as an Emergent-causal Schema. We propose that students lack this Emergent Schema and teaching it to them may help them learn and understand emergent kinds of science processes such as diffusion. Our study found that directly teaching students this Emergent Schema led to increased learning of the process of diffusion. This article presents a fine-grained characterization of each type of Schema, our instructional intervention, the successes we have achieved, and the lessons we have learned. Copyright © 2011 Cognitive Science Society, Inc.

Information flow in layered networks of non-monotonic units

NASA Astrophysics Data System (ADS)

Schittler Neves, Fabio; Martim Schubert, Benno; Erichsen, Rubem, Jr.

2015-07-01

Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information.

Marshburn works with Marangoni Experiment Hardware in Kibo

NASA Image and Video Library

2013-03-19

ISS035e006147 (19 March 2013) --- NASA astronaut Tom Marshburn, Expedition 35 flight engineer, works on the Marangoni Inside core cleaning in the Kibo Japanese Experiment Module onboard the Earth-orbiting International Space Station. Marangoni convection is the flow driven by the presence of a surface tension gradient which can be produced by temperature difference at a liquid/gas interface. The convection in liquid bridge of silicone oil is generated by heating the one disc higher than the other. Scientists are observing flow patterns of how fluids move to learn more about how heat is transferred in microgravity.

Learned Vocal Variation Is Associated with Abrupt Cryptic Genetic Change in a Parrot Species Complex

PubMed Central

Ribot, Raoul F. H.; Buchanan, Katherine L.; Endler, John A.; Joseph, Leo; Bennett, Andrew T. D.; Berg, Mathew L.

2012-01-01

Contact zones between subspecies or closely related species offer valuable insights into speciation processes. A typical feature of such zones is the presence of clinal variation in multiple traits. The nature of these traits and the concordance among clines are expected to influence whether and how quickly speciation will proceed. Learned signals, such as vocalizations in species having vocal learning (e.g. humans, many birds, bats and cetaceans), can exhibit rapid change and may accelerate reproductive isolation between populations. Therefore, particularly strong concordance among clines in learned signals and population genetic structure may be expected, even among continuous populations in the early stages of speciation. However, empirical evidence for this pattern is often limited because differences in vocalisations between populations are driven by habitat differences or have evolved in allopatry. We tested for this pattern in a unique system where we may be able to separate effects of habitat and evolutionary history. We studied geographic variation in the vocalizations of the crimson rosella (Platycercus elegans) parrot species complex. Parrots are well known for their life-long vocal learning and cognitive abilities. We analysed contact calls across a ca 1300 km transect encompassing populations that differed in neutral genetic markers and plumage colour. We found steep clinal changes in two acoustic variables (fundamental frequency and peak frequency position). The positions of the two clines in vocal traits were concordant with a steep cline in microsatellite-based genetic variation, but were discordant with the steep clines in mtDNA, plumage and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, can coincide with areas of restricted gene flow across geographically continuous populations. Our results suggest that traits that evolve culturally can be strongly associated with reduced gene flow between populations, and therefore may promote speciation, even in the absence of other barriers. PMID:23227179

The Corticohippocampal Circuit, Synaptic Plasticity, and Memory

PubMed Central

Basu, Jayeeta; Siegelbaum, Steven A.

2015-01-01

Synaptic plasticity serves as a cellular substrate for information storage in the central nervous system. The entorhinal cortex (EC) and hippocampus are interconnected brain areas supporting basic cognitive functions important for the formation and retrieval of declarative memories. Here, we discuss how information flow in the EC–hippocampal loop is organized through circuit design. We highlight recently identified corticohippocampal and intrahippocampal connections and how these long-range and local microcircuits contribute to learning. This review also describes various forms of activity-dependent mechanisms that change the strength of corticohippocampal synaptic transmission. A key point to emerge from these studies is that patterned activity and interaction of coincident inputs gives rise to associational plasticity and long-term regulation of information flow. Finally, we offer insights about how learning-related synaptic plasticity within the corticohippocampal circuit during sensory experiences may enable adaptive behaviors for encoding spatial, episodic, social, and contextual memories. PMID:26525152

Learning partial differential equations via data discovery and sparse optimization

NASA Astrophysics Data System (ADS)

Schaeffer, Hayden

2017-01-01

We investigate the problem of learning an evolution equation directly from some given data. This work develops a learning algorithm to identify the terms in the underlying partial differential equations and to approximate the coefficients of the terms only using data. The algorithm uses sparse optimization in order to perform feature selection and parameter estimation. The features are data driven in the sense that they are constructed using nonlinear algebraic equations on the spatial derivatives of the data. Several numerical experiments show the proposed method's robustness to data noise and size, its ability to capture the true features of the data, and its capability of performing additional analytics. Examples include shock equations, pattern formation, fluid flow and turbulence, and oscillatory convection.

Learning partial differential equations via data discovery and sparse optimization.

PubMed

Schaeffer, Hayden

2017-01-01

We investigate the problem of learning an evolution equation directly from some given data. This work develops a learning algorithm to identify the terms in the underlying partial differential equations and to approximate the coefficients of the terms only using data. The algorithm uses sparse optimization in order to perform feature selection and parameter estimation. The features are data driven in the sense that they are constructed using nonlinear algebraic equations on the spatial derivatives of the data. Several numerical experiments show the proposed method's robustness to data noise and size, its ability to capture the true features of the data, and its capability of performing additional analytics. Examples include shock equations, pattern formation, fluid flow and turbulence, and oscillatory convection.

Learning partial differential equations via data discovery and sparse optimization

PubMed Central

2017-01-01

We investigate the problem of learning an evolution equation directly from some given data. This work develops a learning algorithm to identify the terms in the underlying partial differential equations and to approximate the coefficients of the terms only using data. The algorithm uses sparse optimization in order to perform feature selection and parameter estimation. The features are data driven in the sense that they are constructed using nonlinear algebraic equations on the spatial derivatives of the data. Several numerical experiments show the proposed method's robustness to data noise and size, its ability to capture the true features of the data, and its capability of performing additional analytics. Examples include shock equations, pattern formation, fluid flow and turbulence, and oscillatory convection. PMID:28265183

Harnessing wake vortices for efficient collective swimming via deep reinfrcement learning

NASA Astrophysics Data System (ADS)

Verma, Siddartha; Novati, Guido; Koumoutsakos, Petros; ChairComputing Science Team

2017-11-01

Collective motion may bestow evolutionary advantages to a number of animal species. Soaring flocks of birds, teeming swarms of insects, and swirling masses of schooling fish, all to some extent enjoy anti-predator benefits, increased foraging success, and enhanced problem-solving abilities. Coordinated activity may also provide energetic benefits, as in the case of large groups of fish where swimmers exploit unsteady flow-patterns generated in the wake. Both experimental and computational investigations of such scenarios are hampered by difficulties associated with studying multiple swimmers. Consequentially, the precise energy-saving mechanisms at play remain largely unknown. We combine high-fidelity numerical simulations of multiple, self propelled swimmers with novel deep reinforcement learning algorithms to discover optimal ways for swimmers to interact with unsteady wakes, in a fully unsupervised manner. We identify optimal flow-interaction strategies devised by the resulting autonomous swimmers, and use it to formulate an effective control-logic. We demonstrate, via 3D simulations of controlled groups that swimmers exploiting the learned strategy exhibit a significant reduction in energy-expenditure. ERC Advanced Investigator Award 341117.

The impact of chewing gum resistance on immediate free recall.

PubMed

Rickman, Sarah; Johnson, Andrew; Miles, Christopher

2013-08-01

Although the facilitative effects of chewing gum on free recall have proved contentious (e.g., Tucha, Mecklinger, Maier, Hammerl, & Lange, 2004; Wilkinson, Scholey, & Wesnes, 2002), there are strong physiological grounds, for example, increased cerebral activity and blood flow following the act of mastication, to suppose facilitation. The present study manipulated resistance to mastication, that is, chewing four pellets versus one pellet of gum, with the assumption that increased resistance will accentuate cerebral activity and blood flow. Additionally, chewing rate was recorded for all participants. In a within-participants design, participants performed a series of immediate free recall tasks while chewing gum at learning (one or four pellets) and recall (one or four pellets). Increased chewing resistance was not associated with increased memory performance, despite consistent chewing rates for both the one and four pellet conditions at both learning and recall. However, a pattern of recall consistent with context-dependent memory was observed. Here, participants who chewed the equivalent number of gum pellets at both learning and recall experienced significantly superior word recall compared to those conditions where the number of gum pellets differed. ©2012 The British Psychological Society.

Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

PubMed Central

Neymotin, Samuel A.; Chadderdon, George L.; Kerr, Cliff C.; Francis, Joseph T.; Lytton, William W.

2014-01-01

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement. PMID:24047323

Electrical failure debug using interlayer profiling method

NASA Astrophysics Data System (ADS)

Yang, Thomas; Shen, Yang; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh

2017-03-01

It is very well known that as technology nodes move to smaller sizes, the number of design rules increases while design structures become more regular and the process manufacturing steps have increased as well. Normal inspection tools can only monitor hard failures on a single layer. For electrical failures that happen due to inter layers misalignments, we can only detect them through testing. This paper will present a working flow for using pattern analysis interlayer profiling techniques to turn multiple layer physical info into group linked parameter values. Using this data analysis flow combined with an electrical model allows us to find critical regions on a layout for yield learning.

Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

NASA Technical Reports Server (NTRS)

Shewhart, Mark

1991-01-01

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

Holographic aids for internal combustion engine flow studies

NASA Technical Reports Server (NTRS)

Regan, C.

1984-01-01

Worldwide interest in improving the fuel efficiency of internal combustion (I.C.) engines has sparked research efforts designed to learn more about the flow processes of these engines. The flow fields must be understood prior to fuel injection in order to design efficient valves, piston geometries, and fuel injectors. Knowledge of the flow field is also necessary to determine the heat transfer to combustion chamber surfaces. Computational codes can predict velocity and turbulence patterns, but experimental verification is mandatory to justify their basic assumptions. Due to their nonintrusive nature, optical methods are ideally suited to provide the necessary velocity verification data. Optical sytems such as Schlieren photography, laser velocimetry, and illuminated particle visualization are used in I.C. engines, and now their versatility is improved by employing holography. These holographically enhanced optical techniques are described with emphasis on their applications in I.C. engines.

A Study of Flow Theory in the Foreign Language Classroom.

ERIC Educational Resources Information Center

Egbert, Joy

2003-01-01

Focuses on the relationship between flow experiences and language learning. Flow theory suggests that flow experiences can lead to optimal learning. Findings suggest flow does exist in the foreign language classroom and that flow theory offers an interesting and useful framework for conceptualizing and evaluating language learning activities.…

Modeling study on the flow patterns of gas-liquid flow for fast decarburization during the RH process

NASA Astrophysics Data System (ADS)

Li, Yi-hong; Bao, Yan-ping; Wang, Rui; Ma, Li-feng; Liu, Jian-sheng

2018-02-01

A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber: boiling pattern (BP), transition pattern (TP), and wave pattern (WP). The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.

A deep learning framework for causal shape transformation.

PubMed

Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik

2018-02-01

Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of Deep Learning and Supervised Learning Methods to Recognize Nonlinear Hidden Pattern in Water Stress Levels from Spatiotemporal Datasets across Rural and Urban US Counties

NASA Astrophysics Data System (ADS)

Eisenhart, T.; Josset, L.; Rising, J. A.; Devineni, N.; Lall, U.

2017-12-01

In the wake of recent water crises, the need to understand and predict the risk of water stress in urban and rural areas has grown. This understanding has the potential to improve decision making in public resource management, policy making, risk management and investment decisions. Assuming an underlying relationship between urban and rural water stress and observable features, we apply Deep Learning and Supervised Learning models to uncover hidden nonlinear patterns from spatiotemporal datasets. Results of interest includes prediction accuracy on extreme categories (i.e. urban areas highly prone to water stress) and not solely the average risk for urban or rural area, which adds complexity to the tuning of model parameters. We first label urban water stressed counties using annual water quality violations and compile a comprehensive spatiotemporal dataset that captures the yearly evolution of climatic, demographic and economic factors of more than 3,000 US counties over the 1980-2010 period. As county-level data reporting is not done on a yearly basis, we test multiple imputation methods to get around the issue of missing data. Using Python libraries, TensorFlow and scikit-learn, we apply and compare the ability of, amongst other methods, Recurrent Neural Networks (testing both LSTM and GRU cells), Convolutional Neural Networks and Support Vector Machines to predict urban water stress. We evaluate the performance of those models over multiple time spans and combine methods to diminish the risk of overfitting and increase prediction power on test sets. This methodology seeks to identify hidden nonlinear patterns to assess the predominant data features that influence urban and rural water stress. Results from this application at the national scale will assess the performance of deep learning models to predict water stress risk areas across all US counties and will highlight a predominant Machine Learning method for modeling water stress risk using spatiotemporal data.

A Neural Circuit Model of Flexible Sensori-motor Mapping: Learning and Forgetting on Multiple Timescales

PubMed Central

Fusi, Stefano; Asaad, Wael F.; Miller, Earl K.; Wang, Xiao-Jing

2007-01-01

Summary Volitional behavior relies on the brain’s ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically-based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuo-motor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well established sensorimotor associations. PMID:17442251

A neural circuit model of flexible sensorimotor mapping: learning and forgetting on multiple timescales.

PubMed

Fusi, Stefano; Asaad, Wael F; Miller, Earl K; Wang, Xiao-Jing

2007-04-19

Volitional behavior relies on the brain's ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuomotor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well-established sensorimotor associations.

Two-phase flow patterns in adiabatic and diabatic corrugated plate gaps

NASA Astrophysics Data System (ADS)

Polzin, A.-E.; Kabelac, S.; de Vries, B.

2016-09-01

Correlations for two-phase heat transfer and pressure drop can be improved considerably, when they are adapted to specific flow patterns. As plate heat exchangers find increasing application as evaporators and condensers, there is a need for flow pattern maps for corrugated plate gaps. This contribution presents experimental results on flow pattern investigations for such a plate heat exchanger background, using an adiabatic visualisation setup as well as a diabatic setup. Three characteristic flow patterns were observed in the considered range of two-phase flow: bubbly flow, film flow and slug flow. The occurrence of these flow patterns is a function of mass flux, void fraction, fluid properties and plate geometry. Two different plate geometries having a corrugation angle of 27° and 63°, respectively and two different fluids (water/air and R365mfc liquid/vapor) have been analysed. A flow pattern map using the momentum flux is presented.

Deep learning of unsteady laminar flow over a cylinder

NASA Astrophysics Data System (ADS)

Lee, Sangseung; You, Donghyun

2017-11-01

Unsteady flow over a circular cylinder is reconstructed using deep learning with a particular emphasis on elucidating the potential of learning the solution of the Navier-Stokes equations. A deep neural network (DNN) is employed for deep learning, while numerical simulations are conducted to produce training database. Instantaneous and mean flow fields which are reconstructed by deep learning are compared with the simulation results. Fourier transform of flow variables has been conducted to validate the ability of DNN to capture both amplitudes and frequencies of flow motions. Basis decomposition of learned flow is performed to understand the underlying mechanisms of learning flow through DNN. The present study suggests that a deep learning technique can be utilized for reconstruction and, potentially, for prediction of fluid flow instead of solving the Navier-Stokes equations. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(Ministry of Science, ICT and Future Planning) (No. 2014R1A2A1A11049599, No. 2015R1A2A1A15056086, No. 2016R1E1A2A01939553).

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed Central

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students. PMID:28559866

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students.

Multivariate analysis of flow cytometric data using decision trees.

PubMed

Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

2012-01-01

Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

An Examination of the Effects of Flow on Learning in a Graduate-Level Introductory Operations Management Course

ERIC Educational Resources Information Center

Klein, Barbara D.; Rossin, Don; Guo, Yi Maggie; Ro, Young K.

2010-01-01

The authors investigated the effects of flow on learning outcomes in a graduate-level operations management course. Flow was assessed through an overall flow score, four dimensions of flow, and three characteristics of flow activities. Learning outcomes were measured objectively through multiple-choice quiz scores and subjectively using measures…

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China

PubMed Central

Yang, Jie; Tang, Chongjun; Chen, Lihua; Liu, Yaojun; Wang, Lingyun

2017-01-01

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land) in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface flows associated with bare land. PMID:28792507

Baghdad, Iraq as seen from STS-60

NASA Image and Video Library

1994-02-09

STS060-92-082 (3-11 Feb 1994) --- This cloud-free view is centered on the city of Baghdad, Iraq. Baghdad has had a reputation for scholarship and learning from ancient times in the Islamic world. Modern Baghdad is a city with a typical urban land use patterns. The color of Tigris river flowing through the city indicates the heavily sediment laden waters of the river. Agricultural land uses are evident in the surrounding areas of the city.

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

DTIC Science & Technology

2015-12-31

AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J...Journal Article Postprint 01 October 2013 – 22 June 2015 4. TITLE AND SUBTITLE FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING...networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments

Graphical User Interface Development for Representing Air Flow Patterns

NASA Technical Reports Server (NTRS)

Chaudhary, Nilika

2004-01-01

In the Turbine Branch, scientists carry out experimental and computational work to advance the efficiency and diminish the noise production of jet engine turbines. One way to do this is by decreasing the heat that the turbine blades receive. Most of the experimental work is carried out by taking a single turbine blade and analyzing the air flow patterns around it, because this data indicates the sections of the turbine blade that are getting too hot. Since the cost of doing turbine blade air flow experiments is very high, researchers try to do computational work that fits the experimental data. The goal of computational fluid dynamics is for scientists to find a numerical way to predict the complex flow patterns around different turbine blades without physically having to perform tests or costly experiments. When visualizing flow patterns, scientists need a way to represent the flow conditions around a turbine blade. A researcher will assign specific zones that surround the turbine blade. In a two-dimensional view, the zones are usually quadrilaterals. The next step is to assign boundary conditions which define how the flow enters or exits one side of a zone. way of setting up computational zones and grids, visualizing flow patterns, and storing all the flow conditions in a file on the computer for future computation. Such a program is necessary because the only method for creating flow pattern graphs is by hand, which is tedious and time-consuming. By using a computer program to create the zones and grids, the graph would be faster to make and easier to edit. Basically, the user would run a program that is an editable graph. The user could click and drag with the mouse to form various zones and grids, then edit the locations of these grids, add flow and boundary conditions, and finally save the graph for future use and analysis. My goal this summer is to create a graphical user interface (GUI) that incorporates all of these elements. I am writing the program in Java, a language that is portable among platforms, because it can run on different operating systems such as Windows and Unix without having to be rewritten. I had no prior experience of programming in Java at the start of my internship; I am continuously learning as I create the program. I have written the part of the program that enables a user to draw several zones, edit them, and store their locations. The next phase of my project is to allow the user to click on the side of a zone and create a boundary condition for it. A previous intern wrote a program that allows the user to input boundary conditions. I can integrate the two programs to create a larger, more usable program. After that, I will develop a way for the user to save the graph for future reference. Another eventual goal is to make the GUI capable of creating three-dimensional zones as well. Researchers such as my mentor, Dr. David Ashpis, need a quick, user-friendly

Optimization of RET flow using test layout

NASA Astrophysics Data System (ADS)

Zhang, Yunqiang; Sethi, Satyendra; Lucas, Kevin

2008-11-01

At advanced technology nodes with extremely low k1 lithography, it is very hard to achieve image fidelity requirements and process window for some layout configurations. Quite often these layouts are within simple design rule constraints for a given technology node. It is important to have these layouts included during early RET flow development. Most of RET developments are based on shrunk layout from the previous technology node, which is possibly not good enough. A better methodology in creating test layout is required for optical proximity correction (OPC) recipe and assists feature development. In this paper we demonstrate the application of programmable test layouts in RET development. Layout pattern libraries are developed and embedded in a layout tool (ICWB). Assessment gauges are generated together with patterns for quick correction accuracy assessment. Several groups of test pattern libraries have been developed based on learning from product patterns and a layout DOE approach. The interaction between layout patterns and OPC recipe has been studied. Correction of a contact layer is quite challenge because of poor convergence and low process window. We developed test pattern library with many different contact configurations. Different OPC schemes are studied on these test layouts. The worst process window patterns are pinpointed for a given illumination condition. Assist features (AF) are frequently placed according to pre-determined rules to improve lithography process window. These rules are usually derived from lithographic models and experiments. Direct validation of AF rules is required at development phase. We use the test layout approach to determine rules in order to eliminate AF printability problem.

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Studies on Normal and Microgravity Annular Two Phase Flows

NASA Technical Reports Server (NTRS)

Balakotaiah, V.; Jayawardena, S. S.; Nguyen, L. T.

1999-01-01

Two-phase gas-liquid flows occur in a wide variety of situations. In addition to normal gravity applications, such flows may occur in space operations such as active thermal control systems, power cycles, and storage and transfer of cryogenic fluids. Various flow patterns exhibiting characteristic spatial and temporal distribution of the two phases are observed in two-phase flows. The magnitude and orientation of gravity with respect to the flow has a strong impact on the flow patterns observed and on their boundaries. The identification of the flow pattern of a flow is somewhat subjective. The same two-phase flow (especially near a flow pattern transition boundary) may be categorized differently by different researchers. Two-phase flow patterns are somewhat simplified in microgravity, where only three flow patterns (bubble, slug and annular) have been observed. Annular flow is obtained for a wide range of gas and liquid flow rates, and it is expected to occur in many situations under microgravity conditions. Slug flow needs to be avoided, because vibrations caused by slugs result in unwanted accelerations. Therefore, it is important to be able to accurately predict the flow pattern which exists under given operating conditions. It is known that the wavy liquid film in annular flow has a profound influence on the transfer of momentum and heat between the phases. Thus, an understanding of the characteristics of the wavy film is essential for developing accurate correlations. In this work, we review our recent results on flow pattern transitions and wavy films in microgravity.

A Model for Predicting Learning Flow and Achievement in Corporate e-Learning

ERIC Educational Resources Information Center

Joo, Young Ju; Lim, Kyu Yon; Kim, Su Mi

2012-01-01

The primary objective of this study was to investigate the determinants of learning flow and achievement in corporate online training. Self-efficacy, intrinsic value, and test anxiety were selected as learners' motivational factors, while perceived usefulness and ease of use were also selected as learning environmental factors. Learning flow was…

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

NASA Astrophysics Data System (ADS)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Adaptive Effects on Locomotion Performance Following Exposure to a Rotating Virtual Environment

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Richards, J. T.; Marshburn, A. M.; Bucello, R.; Bloomberg, J. J.

2003-01-01

During long-duration spaceflight, astronauts experience alterations in vestibular and somatosensory cues that result in adaptive disturbances in balance and coordination upon return to Earth. These changes can pose a risk to crew safety and to mission objectives if nominal or emergency vehicle egress is required immediately following long-duration spaceflight. At present, no operational countermeasure is available to mitigate the adaptive sensorimotor component underlying the locomotor disturbances that occur after spaceflight. Therefore, the goal of this study is to develop an inflight training regimen that facilitates recovery of locomotor function after long-duration spaceflight. The countermeasure we are proposing is based on the concept of adaptive generalization. During this type of training the subject gains experience producing the appropriate adaptive motor behavior under a variety of sensory conditions and response constraints. As a result of this training a subject learns to solve a class of motor problems, rather than a specific motor solution to one problem, i.e., the subject learns response generalizability or the ability to "learn to learn." under a variety of environmental constraints. We are developing an inflight countermeasure built around treadmill exercise activities. By manipulating the sensory conditions of exercise by varying visual flow patterns, body load and speed we will systematically and repeatedly promote adaptive change in locomotor behavior. It has been shown that variable practice training increases adaptability to novel visuo-motor situations. While walking over ground in a stereoscopic virtual environment that oscillated in roll, subjects have shown compensatory torso rotation in the direction of scene rotation that resulted in positional variation away from a desired linear path. Thus, postural sway and locomotor stability in 1-g can be modulated by visual flow patterns and used during inflight treadmill training to promote adaptive generalization. The purpose of this study was to determine if adaptive modification in locomotor performance could be achieved by viewing simulated self-motion in a passive-immersive virtual ' environment over a prolonged period during treadmill locomotion.

Experimental investigation of two-phase flow patterns in minichannels at horizontal orientation

NASA Astrophysics Data System (ADS)

Saljoshi, P. S.; Autee, A. T.

2017-09-01

Two-phase flow is the simplest case of multiphase flow in which two phases are present for a pure component. The mini channel is considered as diameter below 3.0-0.2 mm and conventional channel is considered diameter above 3.0 mm. An experiment was conducted to study the adiabatic two-phase flow patterns in the circular test section with inner diameter of 1.1, 1.63, 2.0, 2.43 and 3.0 mm for horizontal orientation using air and water as a fluid. Different types of flow patterns found in the experiment. The parameters that affect most of these patterns and their transitions are channel size, phase superficial velocities (air and liquid) and surface tension. The superficial velocity of liquid and gas ranges from 0.01 to 66.70 and 0.01 to 3 m/s respectively. Two-phase flow pattern photos were recorded using a high speed CMOS camera. In this experiment different flow patterns were identified for different tube diameters that confirm the diameter effect on flow patterns in two-phase flows. Stratified flow was not observed for tube diameters less than 3.0 mm. Similarly, wavy-annular flow pattern was not observed in 1.6 and 1.0 mm diameter tubes due to the surface-tension effect and decrease in tube diameter. Buoyancy effects were clearly visible in 2.43 and 3.0 mm diameter tubes flow pattern. It has also observed that as the test-section diameter decreases the transition lines shift towards the higher gas and liquid velocity. However, the result of flow pattern lines in the present study has good agreement with the some of the existing flow patterns maps.

A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qing; Xu, Jing; Wei, Jun

2018-04-01

Two algorithms based on machine learning neural networks are proposed—the shallow learning (S-L) and deep learning (D-L) algorithms—that can potentially be used in atmosphere-only typhoon forecast models to provide flow-dependent typhoon-induced sea surface temperature cooling (SSTC) for improving typhoon predictions. The major challenge of existing SSTC algorithms in forecast models is how to accurately predict SSTC induced by an upcoming typhoon, which requires information not only from historical data but more importantly also from the target typhoon itself. The S-L algorithm composes of a single layer of neurons with mixed atmospheric and oceanic factors. Such a structure is found to be unable to represent correctly the physical typhoon-ocean interaction. It tends to produce an unstable SSTC distribution, for which any perturbations may lead to changes in both SSTC pattern and strength. The D-L algorithm extends the neural network to a 4 × 5 neuron matrix with atmospheric and oceanic factors being separated in different layers of neurons, so that the machine learning can determine the roles of atmospheric and oceanic factors in shaping the SSTC. Therefore, it produces a stable crescent-shaped SSTC distribution, with its large-scale pattern determined mainly by atmospheric factors (e.g., winds) and small-scale features by oceanic factors (e.g., eddies). Sensitivity experiments reveal that the D-L algorithms improve maximum wind intensity errors by 60-70% for four case study simulations, compared to their atmosphere-only model runs.

The Case of Flow and Learning Revisited

ERIC Educational Resources Information Center

Ro, Young K.; Guo, Yi Maggie; Klein, Barbara D.

2018-01-01

Many business schools are criticized for being ineffective in helping students learn proper management skills and knowledge. Flow theory has been cited as being helpful in many learning environments in that flow experience can enhance student learning. The authors conducted a study of 315 students in an undergraduate operations management (OM)…

An Examination of Game-Based Learning from Theories of Flow Experience and Cognitive Load

ERIC Educational Resources Information Center

Lai, Chih-Hung; Chu, Chih-Ming; Liu, Hsiang-Hsuan; Yang, Shun-Bo; Chen, Wei-Hsuan

2013-01-01

This study aims to discuss whether game-based learning with the integration of games and digital learning could enhance not only the flow experience in learning but achieve the same flow experience in pure games. In addition, the authors discovered that whether the game-based learning could make learners to reveal higher cognitive load. The…

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

PubMed

Tan, C; Liu, W L; Dong, F

2016-06-28

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

PubMed Central

Liu, W. L.; Dong, F.

2016-01-01

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

Experimental investigation on the heat transfer characteristics and flow pattern in vertical narrow channels heated from one side

NASA Astrophysics Data System (ADS)

Huang, Lihao; Li, Gang; Tao, Leren

2016-07-01

Experimental investigation for the flow boiling of water in a vertical rectangular channel was conducted to reveal the boiling heat transfer mechanism and flow patterns map aspects. The onset of nucleate boiling went upward with the increasing of the working fluid mass flow rate or the decreasing of the inlet working fluid temperature. As the vapour quality was increased, the local heat transfer coefficient increased first, then decreased, followed by various flow patterns. The test data from other researchers had a similar pattern transition for the bubble-slug flow and the slug-annular flow. Flow pattern transition model analysis was performed to make the comparison with current test data. The slug-annular and churn-annular transition models showed a close trend with current data except that the vapor phase superficial velocity of flow pattern transition was much higher than that of experimental data.

Using pattern based layout comparison for a quick analysis of design changes

NASA Astrophysics Data System (ADS)

Huang, Lucas; Yang, Legender; Kan, Huan; Zou, Elain; Wan, Qijian; Du, Chunshan; Hu, Xinyi; Liu, Zhengfang

2018-03-01

A design usually goes through several versions until achieving a most successful one. These changes between versions are not a complete substitution but a continual improvement, either fixing the known issues of its prior versions (engineering change order) or a more optimized design substitution of a portion of the design. On the manufacturing side, process engineers care more about the design pattern changes because any new pattern occurrence may be a killer of the yield. An effective and efficient way to narrow down the diagnosis scope appeals to the engineers. What is the best approach of comparing two layouts? A direct overlay of two layouts may not always work as even though most of the design instances will be kept in the layout from version to version, the actual placements may be different. An alternative way, pattern based layout comparison, comes to play. By expanding this application, it makes it possible to transfer the learning in one cycle to another and accelerate the process of failure analysis. This paper presents a solution to compare two layouts by using Calibre DRC and Pattern Matching. The key step in this flow is layout decomposition. In theory, with a fixed pattern size, a layout can always be decomposed into limited number of patterns by moving the pattern center around the layout, the number is limited but may be huge if the layout is not processed smartly! A mathematical answer is not what we are looking for but an engineering solution is more desired. Layouts must be decomposed into patterns with physical meaning in a smart way. When a layout is decomposed and patterns are classified, a pattern library with unique patterns inside is created for that layout. After individual pattern libraries for each layout are created, run pattern comparison utility provided by Calibre Pattern Matching to compare the pattern libraries, unique patterns will come out for each layout. This paper illustrates this flow in details and demonstrates the advantage of combining Calibre DRC and Calibre Pattern Matching.

Controlling flows in microchannels with patterned surface charge and topography.

PubMed

Stroock, Abraham D; Whitesides, George M

2003-08-01

This Account reviews two procedures for controlling the flow of fluids in microchannels. The first procedure involves patterning the density of charge on the inner surfaces of a channel. These patterns generate recirculating electroosmotic flows in the presence of a steady electric field. The second procedure involves patterning topography on an inner surface of a channel. These patterns generate recirculation in the cross-section of steady, pressure-driven flows. This Account summarizes applications of these flow to mixing and to controlling dispersion (band broadening).

Flow patterns and transition characteristics for steam condensation in silicon microchannels

NASA Astrophysics Data System (ADS)

Ma, Xuehu; Fan, Xiaoguang; Lan, Zhong; Hao, Tingting

2011-07-01

This study investigated the two-phase flow patterns and transition characteristics for steam condensation in silicon microchannels with different cross-sectional geometries. Novel experimental techniques were developed to determine the local heat transfer rate and steam quality by testing the temperature profile of a copper cooler. Flow regime maps for different microchannels during condensation were established in terms of steam mass flux and steam quality. Meanwhile, the correlation for the flow pattern transition was obtained using different geometrical and dimensionless parameters for steam condensation in microchannels. To better understand the flow mechanisms in microchannels, the condensation flow patterns, such as annular flow, droplet flow, injection flow and intermittent flow, were captured and analyzed. The local heat transfer rate showed the nonlinear variations along the axial direction during condensation. The experimental results indicate that the flow patterns and transition characteristics strongly depend on the geometries of microchannels. With the increasing steam mass flux and steam quality, the annular/droplet flow expands and spans over a larger region in the microchannels; otherwise the intermittent flow occupies the microchannels. The dimensionless fitting data also reveal that the effect of surface tension and vapor inertia dominates gravity and viscous force at the specified flow pattern transitional position.

Patterns in Teacher Learning in Different Phases of the Professional Career

ERIC Educational Resources Information Center

Vermunt, Jan D.; Endedijk, Maaike D.

2011-01-01

This paper reviews recent research on learning patterns of student teachers and experienced teachers, mostly in the context of educational innovation and teachers' professional development. The discussion is structured along a model of teacher learning patterns comprising learning activities, regulation of learning, beliefs on own learning about…

Gas liquid flow at microgravity conditions - Flow patterns and their transitions

NASA Technical Reports Server (NTRS)

Dukler, A. E.; Fabre, J. A.; Mcquillen, J. B.; Vernon, R.

1987-01-01

The prediction of flow patterns during gas-liquid flow in conduits is central to the modern approach for modeling two phase flow and heat transfer. The mechanisms of transition are reasonably well understood for flow in pipes on earth where it has been shown that body forces largely control the behavior observed. This work explores the patterns which exist under conditions of microgravity when these body forces are suppressed. Data are presented which were obtained for air-water flow in tubes during drop tower experiments and Learjet trajectories. Preliminary models to explain the observed flow pattern map are evolved.

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

DTIC Science & Technology

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

A Learning Patterns Perspective on Student Learning in Higher Education: State of the Art and Moving Forward

ERIC Educational Resources Information Center

Vermunt, Jan D.; Donche, Vincent

2017-01-01

The aim of this article is to review the state of the art of research and theory development on student learning patterns in higher education and beyond. First, the learning patterns perspective and the theoretical framework are introduced. Second, research published since 2004 on student learning patterns is systematically identified and…

Application of graph-based semi-supervised learning for development of cyber COP and network intrusion detection

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romano, John; Eslami, Mohammed

2017-05-01

The United States increasingly relies on cyber-physical systems to conduct military and commercial operations. Attacks on these systems have increased dramatically around the globe. The attackers constantly change their methods, making state-of-the-art commercial and military intrusion detection systems ineffective. In this paper, we present a model to identify functional behavior of network devices from netflow traces. Our model includes two innovations. First, we define novel features for a host IP using detection of application graph patterns in IP's host graph constructed from 5-min aggregated packet flows. Second, we present the first application, to the best of our knowledge, of Graph Semi-Supervised Learning (GSSL) to the space of IP behavior classification. Using a cyber-attack dataset collected from NetFlow packet traces, we show that GSSL trained with only 20% of the data achieves higher attack detection rates than Support Vector Machines (SVM) and Naïve Bayes (NB) classifiers trained with 80% of data points. We also show how to improve detection quality by filtering out web browsing data, and conclude with discussion of future research directions.

The Effects of Domestic Energy Consumption on Urban Development Using System Dynamics

NASA Astrophysics Data System (ADS)

Saryazdi, M. D.; Homaei, N.; Arjmand, A.

2018-05-01

In developed countries, people have learned to follow efficient consumption patterns, while in developing countries, such as Iran, these patterns are not well executed. A large amount of energy is almost consumed in buildings and houses and though the consumption patterns varies in different societies, various energy policies are required to meet the consumption challenges. So far, several papers and more than ten case studies have worked on the relationship between domestic energy consumption and urban development, however these researches did not analyzed the impact of energy consumption on urban development. Therefore, this paper attempts to examine the interactions between the energy consumption and urban development by using system dynamics as the most widely used methods for complex problems. The proposed approach demonstrates the interactions using causal loop and flow diagrams and finally, suitable strategies will be proposed for urban development through simulations of different scenarios.

Ferrofluid-in-oil two-phase flow patterns in a flow-focusing microchannel

NASA Astrophysics Data System (ADS)

Sheu, T. S.; Chen, Y. T.; Lih, F. L.; Miao, J. M.

This study investigates the two-phase flow formation process of water-based Fe3O4 ferrofluid (dispersed phase) in a silicon oil (continuous phase) flow in the microfluidic flow-focusing microchannel under various operational conditions. With transparent PDMS chip and optical microscope, four main two-phase flow patterns as droplet flow, slug flow, ring flow and churn flow are observed. The droplet shape, size, and formation mechanism were also investigated under different Ca numbers and intended to find out the empirical relations. The paper marks an original flow pattern map of the ferrofluid-in-oil flows in the microfluidic flow-focusing microchannels. The flow pattern transiting from droplet flow to slug flow appears for an operational conditions of QR < 1 and Lf / W < 1. The power law index that related Lf / W to QR was 0.36 in present device.

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

An Assessment of Stream Confluence Flow Dynamics using Large Scale Particle Image Velocimetry Captured from Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Lewis, Q. W.; Rhoads, B. L.

2017-12-01

The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.

An artificial intelligence based improved classification of two-phase flow patterns with feature extracted from acquired images.

PubMed

Shanthi, C; Pappa, N

2017-05-01

Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing. The textural and shape features extracted using image processing are applied as inputs to various classification schemes namely fuzzy logic, SVM and SVM with PCA in order to identify the type of flow pattern. The results obtained are compared and it is observed that SVM with features reduced using PCA gives the better classification accuracy and computationally less intensive than other two existing schemes. This study results cover industrial application needs including oil and gas and any other gas-liquid two-phase flows. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Doctoral Student Learning Patterns: Learning about Active Knowledge Creation or Passive Production

ERIC Educational Resources Information Center

Vekkaila, Jenna; Pyhältö, Kirsi

2016-01-01

Doctoral studies are about learning to create new knowledge and to become a researcher. Yet surprisingly little is known about the individual learning patterns of doctoral students. The study aims to explore learning patterns among natural science doctoral students. The participants included 19 doctoral students from a top-level natural science…

Application of artificial neural networks to identify equilibration in computer simulations

NASA Astrophysics Data System (ADS)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

2017-02-01

We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

Self-aligned quadruple patterning using spacer on spacer integration optimization for N5

NASA Astrophysics Data System (ADS)

Thibaut, Sophie; Raley, Angélique; Mohanty, Nihar; Kal, Subhadeep; Liu, Eric; Ko, Akiteru; O'Meara, David; Tapily, Kandabara; Biolsi, Peter

2017-04-01

To meet scaling requirements, the semiconductor industry has extended 193nm immersion lithography beyond its minimum pitch limitation using multiple patterning schemes such as self-aligned double patterning, self-aligned quadruple patterning and litho-etch / litho etch iterations. Those techniques have been declined in numerous options in the last few years. Spacer on spacer pitch splitting integration has been proven to show multiple advantages compared to conventional pitch splitting approach. Reducing the number of pattern transfer steps associated with sacrificial layers resulted in significant decrease of cost and an overall simplification of the double pitch split technique. While demonstrating attractive aspects, SAQP spacer on spacer flow brings challenges of its own. Namely, material set selections and etch chemistry development for adequate selectivities, mandrel shape and spacer shape engineering to improve edge placement error (EPE). In this paper we follow up and extend upon our previous learning and proceed into more details on the robustness of the integration in regards to final pattern transfer and full wafer critical dimension uniformity. Furthermore, since the number of intermediate steps is reduced, one will expect improved uniformity and pitch walking control. This assertion will be verified through a thorough pitch walking analysis.

Exploring the Role of Flow Experience, Learning Performance and Potential Behavior Clusters in Elementary Students' Game-Based Learning

ERIC Educational Resources Information Center

Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse

2016-01-01

Well-designed game-based learning can provide students with an innovative environment that may enhance students' motivation and engagement in learning and thus improve their learning performance. The purpose of this study was to examine the relationships among elementary school students' flow experience and learning performances. We also…

Novice medical students: individual patterns in the use of learning strategies and how they change during the first academic year.

PubMed

Fabry, Götz; Giesler, Marianne

2012-01-01

Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. We identified four different patterns in approaches to learning among novice medical students ("easy-going", "flexible", "problematic" and "hardworking" learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students' learning.

Novice medical students: Individual patterns in the use of learning strategies and how they change during the first academic year

PubMed Central

Fabry, Götz; Giesler, Marianne

2012-01-01

Background: Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Methods: Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. Results: We identified four different patterns in approaches to learning among novice medical students (“easy-going”, “flexible”, “problematic” and “hardworking” learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Conclusion: Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students’ learning. PMID:22916082

4D flow MRI assessment of right atrial flow patterns in the normal heart – influence of caval vein arrangement and implications for the patent foramen ovale

PubMed Central

Parikh, Jehill D.; Kakarla, Jayant; Keavney, Bernard; O’Sullivan, John J.; Ford, Gary A.; Blamire, Andrew M.; Hollingsworth, Kieren G.

2017-01-01

Aim To investigate atrial flow patterns in the normal adult heart, to explore whether caval vein arrangement and patency of the foramen ovale (PFO) may be associated with flow pattern. Materials and Methods Time-resolved, three-dimensional velocity encoded magnetic resonance imaging (4D flow) was employed to assess atrial flow patterns in thirteen healthy subjects (6 male, 40 years, range 25–50) and thirteen subjects (6 male, 40 years, range 21–50) with cryptogenic stroke and patent foramen ovale (CS-PFO). Right atrial flow was defined as vortical, helico-vortical, helical and multiple vortices. Time-averaged and peak systolic and diastolic flows in the caval and pulmonary veins and their anatomical arrangement were compared. Results A spectrum of right atrial flow was observed across the four defined categories. The right atrial flow patterns were strongly associated with the relative position of the caval veins. Right atrial flow patterns other than vortical were more common (p = 0.015) and the separation between the superior and inferior vena cava greater (10±5mm versus 3±3mm, p = 0.002) in the CS-PFO group. In the left atrium all subjects except one had counter-clockwise vortical flow. Vortex size varied and was associated with left lower pulmonary vein flow (systolic r = 0.61, p = 0.001, diastolic r = 0.63 p = 0.002). A diastolic vortex was less common and time-averaged left atrial velocity was greater in the CS-PFO group (17±2cm/sec versus 15±1, p = 0.048). One CS-PFO subject demonstrated vortical retrograde flow in the descending aortic arch; all other subjects had laminar descending aortic flow. Conclusion Right atrial flow patterns in the normal heart are heterogeneous and are associated with the relative position of the caval veins. Patterns, other than ‘typical’ vortical flow, are more prevalent in the right atrium of those with cryptogenic stroke in the context of PFO. Left atrial flow patterns are more homogenous in normal hearts and show a relationship with flow arising from the left pulmonary veins. PMID:28282389

The flow patterning capability of localized natural convection.

PubMed

Huang, Ling-Ting; Chao, Ling

2016-09-14

Controlling flow patterns to align materials can have various applications in optics, electronics, and biosciences. In this study, we developed a natural-convection-based method to create desirable spatial flow patterns by controlling the locations of heat sources. Fluid motion in natural convection is induced by the spatial fluid density gradient that is caused by the established spatial temperature gradient. To analyze the patterning resolution capability of this method, we used a mathematical model combined with nondimensionalization to correlate the flow patterning resolution with experimental operating conditions. The nondimensionalized model suggests that the flow pattern and resolution is only influenced by two dimensionless parameters, and , where Gr is the Grashof number, representing the ratio of buoyancy to the viscous force acting on a fluid, and Pr is the Prandtl number, representing the ratio of momentum diffusivity to thermal diffusivity. We used the model to examine all of the flow behaviors in a wide range of the two dimensionless parameter group and proposed a flow pattern state diagram which suggests a suitable range of operating conditions for flow patterning. In addition, we developed a heating wire with an angular configuration, which enabled us to efficiently examine the pattern resolution capability numerically and experimentally. Consistent resolutions were obtained between the experimental results and model predictions, suggesting that the state diagram and the identified operating range can be used for further application.

Two-phase gas-liquid flow characteristics inside a plate heat exchanger

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nilpueng, Kitti; Wongwises, Somchai

In the present study, the air-water two-phase flow characteristics including flow pattern and pressure drop inside a plate heat exchanger are experimentally investigated. A plate heat exchanger with single pass under the condition of counter flow is operated for the experiment. Three stainless steel commercial plates with a corrugated sinusoidal shape of unsymmetrical chevron angles of 55 and 10 are utilized for the pressure drop measurement. A transparent plate having the same configuration as the stainless steel plates is cast and used as a cover plate in order to observe the flow pattern inside the plate heat exchanger. The air-watermore » mixture flow which is used as a cold stream is tested in vertical downward and upward flow. The results from the present experiment show that the annular-liquid bridge flow pattern appeared in both upward and downward flows. However, the bubbly flow pattern and the slug flow pattern are only found in upward flow and downward flow, respectively. The variation of the water and air velocity has a significant effect on the two-phase pressure drop. Based on the present data, a two-phase multiplier correlation is proposed for practical application. (author)« less

Oil-flow separation patterns on an ogive forebody

NASA Technical Reports Server (NTRS)

Keener, E. R.

1981-01-01

Oil flow patterns on a symmetric tangent ogive forebody having a fineness ratio of 3.5 are presented for angles of attack up to 88 deg at a transitional Reynolds number of 8 million (based on base diameter) and a Mach number of 0.25. Results show typical surface flow separation patterns, the magnitude of surface flow angles, and the extent of laminar and turbulent flow for symmetric, asymmetric, and wakelike flow regimes.

Effect of diastolic flow patterns on the function of the left ventricle

NASA Astrophysics Data System (ADS)

Seo, Jung Hee; Mittal, Rajat

2013-11-01

Direct numerical simulations are used to study the effect of intraventricular flow patterns on the pumping efficiency and the blood mixing and transport characteristics of the left ventricle. The simulations employ a geometric model of the left ventricle which is derived from contrast computed tomography. A variety of diastolic flow conditions are generated for a fixed ejection fraction in order to delineate the effect of flow patterns on ventricular performance. The simulations indicate that the effect of intraventricular blood flow pattern on the pumping power is physiologically insignificant. However, diastolic flow patterns have a noticeable effect on the blood mixing as well as the residence time of blood cells in the ventricle. The implications of these findings on ventricular function are discussed.

Habenula and interpeduncular nucleus differentially modulate predator odor-induced innate fear behavior in rats.

PubMed

Vincenz, Daniel; Wernecke, Kerstin E A; Fendt, Markus; Goldschmidt, Jürgen

2017-08-14

Fear is an important behavioral system helping humans and animals to survive potentially dangerous situations. Fear can be innate or learned. Whereas the neural circuits underlying learned fear are already well investigated, the knowledge about the circuits mediating innate fear is still limited. We here used a novel, unbiased approach to image in vivo the spatial patterns of neural activity in odor-induced innate fear behavior in rats. We intravenously injected awake unrestrained rats with a 99m-technetium labeled blood flow tracer (99mTc-HMPAO) during ongoing exposure to fox urine or water as control, and mapped the brain distribution of the trapped tracer using single-photon emission computed tomography (SPECT). Upon fox urine exposure blood flow increased in a number of brain regions previously associated with odor-induced innate fear such as the amygdala, ventromedial hypothalamus and dorsolateral periaqueductal grey, but, unexpectedly, decreased at higher significance levels in the interpeduncular nucleus (IPN). Significant flow changes were found in regions monosynaptically connected to the IPN. Flow decreased in the dorsal tegmentum and entorhinal cortex. Flow increased in the habenula (Hb) and correlated with odor effects on behavioral defensive strategy. Hb lesions reduced avoidance of but increased approach to the fox urine while IPN lesions only reduced avoidance behavior without approach behavior. Our study identifies a new component, the IPN, of the neural circuit mediating odor-induced innate fear behavior in mammals and suggests that the evolutionarily conserved Hb-IPN system, which has recently been implicated in cued fear, also forms an integral part of the innate fear circuitry. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

PubMed

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

CFD Simulation of flow pattern in a bubble column reactor for forming aerobic granules and its development.

PubMed

Fan, Wenwen; Yuan, LinJiang; Li, Yonglin

2018-06-22

The flow pattern is considered to play an important role in the formation of aerobic granular sludge in a bubble column reactor; therefore, it is necessary to understand the behavior of the flow in the reactor. A three-dimensional computational fluid dynamics (CFD) simulation for bubble column reactor was established to visualize the flow patterns of two-phase air-liquid flow and three-phase air-liquid-sludge flow under different ratios of height to diameter (H/D ratio) and superficial gas upflow velocities (SGVs). Moreover, a simulation of the three-phase flow pattern at the same SGV and different characteristics of the sludge was performed in this study. The results show that not only SGV but also properties of sludge involve the transformation of flow behaviors and relative velocity between liquid and sludge. For the original activated sludge floc to cultivate aerobic granules, the flow pattern has nothing to do with sludge, but is influenced by SGV, and the vortices is occurred and the relative velocity is increased with an increase in SGV; the two-phase flow can simplify the three-phase flow that predicts the flow pattern development in bubble column reactor (BCR) for aerobic granulation. For the aerobic granules, the liquid flow behavior developed from the symmetrical circular flow to numbers and small-size vortices with an increase in the sludge diameter, the relative velocity is amount up to u r  = 5.0, it is 29.4 times of original floc sludge.

Street Viewer: An Autonomous Vision Based Traffic Tracking System.

PubMed

Bottino, Andrea; Garbo, Alessandro; Loiacono, Carmelo; Quer, Stefano

2016-06-03

The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

NASA Astrophysics Data System (ADS)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

Involvement of Working Memory in College Students' Sequential Pattern Learning and Performance

ERIC Educational Resources Information Center

Kundey, Shannon M. A.; De Los Reyes, Andres; Rowan, James D.; Lee, Bern; Delise, Justin; Molina, Sabrina; Cogdill, Lindsay

2013-01-01

When learning highly organized sequential patterns of information, humans and nonhuman animals learn rules regarding the hierarchical structures of these sequences. In three experiments, we explored the role of working memory in college students' sequential pattern learning and performance in a computerized task involving a sequential…

Optimizing a Workplace Learning Pattern: A Case Study from Aviation

ERIC Educational Resources Information Center

Mavin, Timothy John; Roth, Wolff-Michael

2015-01-01

Purpose: This study aims to contribute to current research on team learning patterns. It specifically addresses some negative perceptions of the job performance learning pattern. Design/methodology/approach: Over a period of three years, qualitative and quantitative data were gathered on pilot learning in the workplace. The instructional modes…

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

NASA Astrophysics Data System (ADS)

Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

2017-11-01

Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

Implicit learning in cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia).

PubMed

Locurto, Charles; Fox, Maura; Mazzella, Andrea

2015-06-01

There is considerable interest in the conditions under which human subjects learn patterned information without explicit instructions to learn that information. This form of learning, termed implicit or incidental learning, can be approximated in nonhumans by exposing subjects to patterned information but delivering reinforcement randomly, thereby not requiring the subjects to learn the information in order to be reinforced. Following acquisition, nonhuman subjects are queried as to what they have learned about the patterned information. In the present experiment, we extended the study of implicit learning in nonhumans by comparing two species, cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia), on an implicit learning task that used an artificial grammar to generate the patterned elements for training. We equated the conditions of training and testing as much as possible between the two species. The results indicated that both species demonstrated approximately the same magnitude of implicit learning, judged both by a random test and by choice tests between pairs of training elements. This finding suggests that the ability to extract patterned information from situations in which such learning is not demanded is of longstanding origin.

Instructional Patterns: Strategies for Maximizing Student Learning [with CD-ROM

ERIC Educational Resources Information Center

Holt, Larry Charles; Kysilka, Marcella L.

2005-01-01

"Instructional Patterns: Strategies for Maximizing Student Learning" examines instruction from the learners' point of view by showing how instructional patterns can be used to maximize the potential for students to learn. This book explores the interactive patterns that exist in today's classroom and demonstrates how teachers can…

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

NASA Astrophysics Data System (ADS)

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-04-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions.

Experimental resource pulses influence social-network dynamics and the potential for information flow in tool-using crows

PubMed Central

St Clair, James J. H.; Burns, Zackory T.; Bettaney, Elaine M.; Morrissey, Michael B.; Otis, Brian; Ryder, Thomas B.; Fleischer, Robert C.; James, Richard; Rutz, Christian

2015-01-01

Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow—a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures. PMID:26529116

Qualitative CFD for Rapid Learning in Industrial and Academic Applications

NASA Astrophysics Data System (ADS)

Variano, Evan

2010-11-01

We present a set of tools that allow CFD to be used at an early stage in the design process. Users can rapidly explore the qualitative aspects of fluid flow using real-time simulations that react immediately to design changes. This can guide the design process by fostering an intuitive understanding of fluid dynamics at the prototyping stage. We use an extremely stable Navier-Stokes solver that is available commercially (and free to academic users) plus a custom user interface. The code is designed for the animation and gaming industry, and we exploit the powerful graphical display capabilities to develop a unique human-machine interface. This interface allows the user to efficiently explore the flow in 3D + real time, fostering an intuitive understanding of steady and unsteady flow patterns. There are obvious extensions to use in an academic setting. The trade-offs between accuracy and speed will be discussed in the context of CFD's role in design and education.

A mechanistic model of heat transfer for gas-liquid flow in vertical wellbore annuli.

PubMed

Yin, Bang-Tang; Li, Xiang-Fang; Liu, Gang

2018-01-01

The most prominent aspect of multiphase flow is the variation in the physical distribution of the phases in the flow conduit known as the flow pattern. Several different flow patterns can exist under different flow conditions which have significant effects on liquid holdup, pressure gradient and heat transfer. Gas-liquid two-phase flow in an annulus can be found in a variety of practical situations. In high rate oil and gas production, it may be beneficial to flow fluids vertically through the annulus configuration between well tubing and casing. The flow patterns in annuli are different from pipe flow. There are both casing and tubing liquid films in slug flow and annular flow in the annulus. Multiphase heat transfer depends on the hydrodynamic behavior of the flow. There are very limited research results that can be found in the open literature for multiphase heat transfer in wellbore annuli. A mechanistic model of multiphase heat transfer is developed for different flow patterns of upward gas-liquid flow in vertical annuli. The required local flow parameters are predicted by use of the hydraulic model of steady-state multiphase flow in wellbore annuli recently developed by Yin et al. The modified heat-transfer model for single gas or liquid flow is verified by comparison with Manabe's experimental results. For different flow patterns, it is compared with modified unified Zhang et al. model based on representative diameters.

Reaction patterns in a blinking vortex flow

NASA Astrophysics Data System (ADS)

Nugent, Carolyn

2005-11-01

We study the patterns formed by the excitable Belousov-Zhabotinsky reaction in a blinking vortex flow produced by magnetohydrodynamic forcing. Mixing in this flow is chaotic, as has been documented extensively in previous studies. The reaction is triggered by a silver wire, and the result is a pulse (``trigger wave'') that propagates through the system. We investigate the patterns formed by the propagating pulse and compare them with theoriesootnotetextT. Tel, A. de Moura, C. Grebogi and G. Karolyi, Phys. Rep. 413, 91 (2005). that predict fractal patterns determined by the unstable manifolds of the flow. We also consider ``burn-like'' reaction fronts, and compare the results with previous experiments for patterns of oscillatory reactions in this flow.

Convex Grooves in Staggered Herringbone Mixer Improve Mixing Efficiency of Laminar Flow in Microchannel.

PubMed

Kwak, Tae Joon; Nam, Young Gyu; Najera, Maria Alejandra; Lee, Sang Woo; Strickler, J Rudi; Chang, Woo-Jin

2016-01-01

The liquid streams in a microchannel are hardly mixed to form laminar flow, and the mixing issue is well described by a low Reynolds number scheme. The staggered herringbone mixer (SHM) using repeated patterns of grooves in the microchannel have been proved to be an efficient passive micro-mixer. However, only a negative pattern of the staggered herringbone mixer has been used so far after it was first suggested, to the best of our knowledge. In this study, the mixing efficiencies from negative and positive staggered herringbone mixer patterns as well as from opposite flow directions were tested to investigate the effect of the micro-structure geometry on the surrounding laminar flow. The positive herringbone pattern showed better mixing efficiency than the conventionally used negative pattern. Also, generally used forward flow gives better mixing efficiency than reverse flow. The mixing was completed after two cycles of staggered herringbone mixer with both forward and reverse flow in a positive pattern. The traditional negative pattern showed complete mixing after four and five cycles in forward and reverse flow direction, respectively. The mixing effect in all geometries was numerically simulated, and the results confirmed more efficient mixing in the positive pattern than the negative. The results can further enable the design of a more efficient microfluidic mixer, as well as in depth understanding of the phenomena of positive and negative patterns existing in nature with regards to the surrounding fluids.

Convex Grooves in Staggered Herringbone Mixer Improve Mixing Efficiency of Laminar Flow in Microchannel

PubMed Central

Nam, Young Gyu; Najera, Maria Alejandra; Lee, Sang Woo; Strickler, J. Rudi; Chang, Woo-Jin

2016-01-01

The liquid streams in a microchannel are hardly mixed to form laminar flow, and the mixing issue is well described by a low Reynolds number scheme. The staggered herringbone mixer (SHM) using repeated patterns of grooves in the microchannel have been proved to be an efficient passive micro-mixer. However, only a negative pattern of the staggered herringbone mixer has been used so far after it was first suggested, to the best of our knowledge. In this study, the mixing efficiencies from negative and positive staggered herringbone mixer patterns as well as from opposite flow directions were tested to investigate the effect of the micro-structure geometry on the surrounding laminar flow. The positive herringbone pattern showed better mixing efficiency than the conventionally used negative pattern. Also, generally used forward flow gives better mixing efficiency than reverse flow. The mixing was completed after two cycles of staggered herringbone mixer with both forward and reverse flow in a positive pattern. The traditional negative pattern showed complete mixing after four and five cycles in forward and reverse flow direction, respectively. The mixing effect in all geometries was numerically simulated, and the results confirmed more efficient mixing in the positive pattern than the negative. The results can further enable the design of a more efficient microfluidic mixer, as well as in depth understanding of the phenomena of positive and negative patterns existing in nature with regards to the surrounding fluids. PMID:27814386

Internal flow patterns on heat transfer characteristics of a closed-loop oscillating heat-pipe with check valves using ethanol and a silver nano-ethanol mixture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhuwakietkumjohn, N.; Rittidech, S.

The aim of this research was to investigate the internal flow patterns and heat transfer characteristics of a closed-loop oscillating heat-pipe with check valves (CLOHP/CV). The ratio of number of check valves to meandering turns was 0.2. Ethanol and a silver nano-ethanol mixture were used as working fluids with a filling ratio of 50% by total volume of tube. The CLOHP/CV was made of a glass tube with an inside diameter of 2.4 mm. The evaporator section was 50 mm and 100 mm in length and there were 10 meandering turns. An inclination angle of 90 from horizontal axis wasmore » established. The evaporator section was heated by an electric heater and the condenser section was cooled by distilled water. Temperature at the evaporator section was controlled at 85 C, 105 C and 125 C. The inlet and outlet temperatures were measured. A digital camera and video camera were used to observe the flow patterns at the evaporator. The silver nano-ethanol mixture gave higher heat flux than ethanol. When the temperature at the evaporator section was increased from 85 C to 105 C and 125 C. It was found that, the flow patterns occurred as annular flow + slug flow, slug flow + bubble flow and dispersed bubble flow + bubble flow respectively. The main regime of each flow pattern can be determined from the flow pattern map ethanol and a silver nano-ethanol mixture. Each of the two working fluids gave corresponding flow patterns. (author)« less

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

NASA Astrophysics Data System (ADS)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

Effects of Presence, Copresence, and Flow on Learning Outcomes in 3D Learning Spaces

ERIC Educational Resources Information Center

Hassell, Martin D.; Goyal, Sandeep; Limayem, Moez; Boughzala, Imed

2012-01-01

The level of satisfaction and effectiveness of 3D virtual learning environments were examined. Additionally, 3D virtual learning environments were compared with face-to-face learning environments. Students that experienced higher levels of flow and presence also experienced more satisfaction but not necessarily more effectiveness with 3D virtual…

Issues in Researching Self-Regulated Learning as Patterns of Events

ERIC Educational Resources Information Center

Winne, Philip H.

2014-01-01

New methods for gathering and analyzing data about events that comprise self-regulated learning (SRL) support discoveries about patterns among events and tests of hypotheses about roles patterns play in learning. Five such methodologies are discussed in the context of four key questions that shape investigations into patterns in SRL. A framework…

Cognitive Characteristics of Children with Genetic Syndromes

PubMed Central

Simon, Tony J.

2008-01-01

The cognitive profile of several different populations of children, each with a distinct neurogenetic disorder that has been described as fitting the pattern of a “nonverbal learning disorder”, is examined. In particular, this paper presents the view that a cognitive endophenotype, specified in terms of specific cognitive processes involving the spatial, temporal and attentional domains, can be used to generate an explanation of the neurocognitive foundation of the common impairments found in these disorders. Methods for evaluating cognitive impairments are first compared and contrasted and the concept of “nonverbal learning disorders” is described. The paper then examines data from experimental tests of spatiotemporal and executive cognitive function acquired from children with one of several disorders to determine whether such a cognitive endophenotype holds promise for moving from descriptions of to explanations for the impairments observed and whether prescriptions for therapeutic interventions might flow from such an account. Synopsis This paper presents the cognitive profile observed in children with one of several common genetic syndromes associated with “nonverbal learning disorders”. It introduces the concept of a cognitive endophenotype in order to help explain the similar pattern of impairments across the syndromes. It explores the explanation of diverse impairments in higher-order visual, spatial, temporal, numerical and executive cognitive competencies deriving from origins in more basic attentional and spatial cognitive dysfunctions. The importance of a developmental approach to understanding dysfunction is stressed. PMID:17562581

Two-phase flow patterns of a top heat mode closed loop oscillating heat pipe with check valves (THMCLOHP/CV)

NASA Astrophysics Data System (ADS)

Thongdaeng, S.; Bubphachot, B.; Rittidech, S.

2016-11-01

This research is aimed at studying the two-phase flow pattern of a top heat mode closed loop oscillating heat pipe with check valves. The working fluids used are ethanol and R141b and R11 coolants with a filling ratio of 50% of the total volume. It is found that the maximum heat flux occurs for the R11 coolant used as the working fluid in the case with the inner diameter of 1.8 mm, inclination angle of -90°, evaporator temperature of 125°C, and evaporator length of 50 mm. The internal flow patterns are found to be slug flow/disperse bubble flow/annular flow, slug flow/disperse bubble flow/churn flow, slug flow/bubble flow/annular flow, slug flow/disperse bubble flow, bubble flow/annular flow, and slug flow/annular flow.

A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

PubMed

Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

2007-01-01

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

Breathing simulator of workers for respirator performance test.

PubMed

Yuasa, Hisashi; Kumita, Mikio; Honda, Takeshi; Kimura, Kazushi; Nozaki, Kosuke; Emi, Hitoshi; Otani, Yoshio

2015-01-01

Breathing machines are widely used to evaluate respirator performance but they are capable of generating only limited air flow patterns, such as, sine, triangular and square waves. In order to evaluate the respirator performance in practical use, it is desirable to test the respirator using the actual breathing patterns of wearers. However, it has been a difficult task for a breathing machine to generate such complicated flow patterns, since the human respiratory volume changes depending on the human activities and workload. In this study, we have developed an electromechanical breathing simulator and a respiration sampling device to record and reproduce worker's respiration. It is capable of generating various flow patterns by inputting breathing pattern signals recorded by a computer, as well as the fixed air flow patterns. The device is equipped with a self-control program to compensate the difference in inhalation and exhalation volume and the measurement errors on the breathing flow rate. The system was successfully applied to record the breathing patterns of workers engaging in welding and reproduced the breathing patterns.

An Exploratory Study Comparing the Effectiveness of Lecturing versus Team-Based Learning

ERIC Educational Resources Information Center

Huggins, Christopher M.; Stamatel, Janet P.

2015-01-01

Lecturing has been criticized for fostering a passive learning environment, emphasizing a one-way flow of information, and not adequately engaging students. In contrast, active-learning approaches, such as team-based learning (TBL), prioritize student interaction and engagement and create multidirectional flows of information. This paper presents…

Implementation of a Learning Design Run-Time Environment for the .LRN Learning Management System

ERIC Educational Resources Information Center

del Cid, Jose Pablo Escobedo; de la Fuente Valentin, Luis; Gutierrez, Sergio; Pardo, Abelardo; Kloos, Carlos Delgado

2007-01-01

The IMS Learning Design specification aims at capturing the complete learning flow of courses, without being restricted to a particular pedagogical model. Such flow description for a course, called a Unit of Learning, must be able to be reproduced in different systems using a so called run-time environment. In the last few years there has been…

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

Motor learning in childhood reveals distinct mechanisms for memory retention and re-learning.

PubMed

Musselman, Kristin E; Roemmich, Ryan T; Garrett, Ben; Bastian, Amy J

2016-05-01

Adults can easily learn and access multiple versions of the same motor skill adapted for different conditions (e.g., walking in water, sand, snow). Following even a single session of adaptation, adults exhibit clear day-to-day retention and faster re-learning of the adapted pattern. Here, we studied the retention and re-learning of an adapted walking pattern in children aged 6-17 yr. We found that all children, regardless of age, showed adult-like patterns of retention of the adapted walking pattern. In contrast, children under 12 yr of age did not re-learn faster on the next day after washout had occurred-they behaved as if they had never adapted their walking before. Re-learning could be improved in younger children when the adaptation time on day 1 was increased to allow more practice at the plateau of the adapted pattern, but never to adult-like levels. These results show that the ability to store a separate, adapted version of the same general motor pattern does not fully develop until adolescence, and furthermore, that the mechanisms underlying the retention and rapid re-learning of adapted motor patterns are distinct. © 2016 Musselman et al.; Published by Cold Spring Harbor Laboratory Press.

Discharge-nitrate data clustering for characterizing surface-subsurface flow interaction and calibration of a hydrologic model

NASA Astrophysics Data System (ADS)

Shrestha, R. R.; Rode, M.

2008-12-01

Concentration of reactive chemicals has different chemical signatures in baseflow and surface runoff. Previous studies on nitrate export from a catchment indicate that the transport processes are driven by subsurface flow. Therefore nitrate signature can be used for understanding the event and pre-event contributions to streamflow and surface-subsurface flow interactions. The study uses flow and nitrate concentration time series data for understanding the relationship between these two variables. Unsupervised artificial neural network based learning method called self organizing map is used for the identification of clusters in the datasets. Based on the cluster results, five different pattern in the datasets are identified which correspond to (i) baseflow, (ii) subsurface flow increase, (iii) surface runoff increase, (iv) surface runoff recession, and (v) subsurface flow decrease regions. The cluster results in combination with a hydrologic model are used for discharge separation. For this purpose, a multi-objective optimization tool NSGA-II is used, where violation of cluster results is used as one of the objective functions. The results show that the use of cluster results as supplementary information for the calibration of a hydrologic model gives a plausible simulation of subsurface flow as well total runoff at the catchment outlet. The study is undertaken using data from the Weida catchment in the North-Eastern Germany, which is a sub-catchment of the Weisse Elster river in the Elbe river basin.

False Lumen Flow Patterns and their Relation with Morphological and Biomechanical Characteristics of Chronic Aortic Dissections. Computational Model Compared with Magnetic Resonance Imaging Measurements

PubMed Central

Segers, Patrick; Pineda, Victor; Cuellar, Hug; García-Dorado, David; Evangelista, Arturo

2017-01-01

Aortic wall stiffness, tear size and location and the presence of abdominal side branches arising from the false lumen (FL) are key properties potentially involved in FL enlargement in chronic aortic dissections (ADs). We hypothesize that temporal variations on FL flow patterns, as measured in a cross-section by phase-contrast magnetic resonance imaging (PC-MRI), could be used to infer integrated information on these features. In 33 patients with chronic descending AD, instantaneous flow profiles were quantified in the FL at diaphragm level by PC-MRI. We used a lumped-parameter model to assess the changes in flow profiles induced by wall stiffness, tear size/location, and the presence of abdominal side branches arising from the FL. Four characteristic FL flow patterns were identified in 31/33 patients (94%) based on the direction of flow in systole and diastole: BA = systolic biphasic flow and primarily diastolic antegrade flow (n = 6); BR = systolic biphasic flow and primarily diastolic retrograde flow (n = 14); MA = systolic monophasic flow and primarily diastolic antegrade flow (n = 9); MR = systolic monophasic flow and primarily diastolic retrograde flow (n = 2). In the computational model, the temporal variation of flow directions within the FL was highly dependent on the position of assessment along the aorta. FL flow patterns (especially at the level of the diaphragm) showed their characteristic patterns due to variations in the cumulative size and the spatial distribution of the communicating tears, and the incidence of visceral side branches originating from the FL. Changes in wall stiffness did not change the temporal variation of the flows whereas it importantly determined intraluminal pressures. FL flow patterns implicitly codify morphological information on key determinants of aortic expansion in ADs. This data might be taken into consideration in the imaging protocol to define the predictive value of FL flows. PMID:28125720

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

PubMed Central

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-01-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions. PMID:28402332

Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance.

PubMed

Cheng, Yung-Ming

2013-01-01

To provide safe and competent patient care, it is very important that medical institutions should provide nurses with continuing education by using appropriate learning methods. As compared to traditional learning, electronic learning (e-learning) is a more flexible method for nurses' in-service learning. Hence, e-learning is expected to play a pivotal role in providing continuing education for nurses. This study's purpose was to explore the role and relevance of interaction factors, intrinsic motivator (i.e., flow), and extrinsic motivators (i.e., perceived usefulness (PU) and perceived ease of use (PEOU)) in explaining nurses' intention to use the e-learning system. Based on the technology acceptance model (TAM) with the flow theory, this study's research model presents three types of interaction factors, learner-system interaction, instructor-learner interaction, and learner-learner interaction to construct an extended TAM to explore nurses' intention to use the e-learning system. Sample data were gathered from nurses at two regional hospitals in Taiwan. A total of 320 questionnaires were distributed, 254 (79.375%) questionnaires were returned. Consequently, 218 usable questionnaires were analyzed in this study, with a usable response rate of 68.125%. First, confirmatory factor analysis was used to develop the measurement model. Second, to explore the causal relationships among all constructs, the structural model for the research model was tested by using structural equation modeling. First, learner-system interaction, instructor-learner interaction, and learner-learner interaction respectively had significant effects on PU, PEOU, and flow. Next, flow had significant effects on PU and PEOU, and PEOU had a significant effect on PU. Finally, the effects of flow, PU, and PEOU on intention to use were significant. Synthetically speaking, learner-system interaction, instructor-learner interaction, and learner-learner interaction can indirectly make significant impacts on nurses' usage intention of the e-learning system via their extrinsic motivators (i.e., PU and PEOU) and intrinsic motivator (i.e., flow). Copyright © 2012 Elsevier Ltd. All rights reserved.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1995-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1993-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Measuring Flow Experience in an Immersive Virtual Environment for Collaborative Learning

ERIC Educational Resources Information Center

van Schaik, P.; Martin, S.; Vallance, M.

2012-01-01

In contexts other than immersive virtual environments, theoretical and empirical work has identified flow experience as a major factor in learning and human-computer interaction. Flow is defined as a "holistic sensation that people feel when they act with total involvement". We applied the concept of flow to modeling the experience of…

Learning New Letter-like Writing Patterns Explicitly and Implicitly in Children and Adults.

PubMed

Jongbloed-Pereboom, M; Overvelde, A; Nijhuis-van der Sanden, M W G; Steenbergen, B

2017-12-15

A handwriting task was used to test the assumption that explicit learning is dependent on age and working memory, while implicit learning is not. The effect of age was examined by testing both, typically developing children (5-12 years old, n = 81) and adults (n = 27) in a counterbalanced within-subjects design. Participants were asked to repeatedly write letter-like patterns on a digitizer with a non-inking pen. Reproduction of the pattern was better after explicit learning compared to implicit learning. Age had positive effects on both explicit and implicit learning; working memory did not affect learning in either conditions. These results show that it may be more effective to learn writing new letter-like patterns explicitly and that an explicit teaching method is preferred in mainstream primary education.

Flow patterns and bathymetric signatures on the delta front of a prograding river delta

NASA Astrophysics Data System (ADS)

Shaw, J.; Mohrig, D. C.; Wagner, R. W.

2016-02-01

The transition of water between laterally confined channels and the unchannelized delta front controls the growth pattern of river deltas, but is difficult to measure on field-scale deltas. We quantify flow patterns, bathymetry and bathymetric evolution for the subaqueous delta front on the Wax Lake Delta (WLD), a rapidly prograding delta in coastal Louisiana. The flow direction field, mapped using streaklines composed of biogenic slicks on the water surface, shows that a significant portion of flow ( 59%) departs subaqueous channels laterally over the subaqueous margins of the channel seaward of the shoreline. Synoptic datasets of bathymetry and flow direction allow spatial changes in flow velocity to be quantified. Most lateral flow divergence and deceleration occurs within 3-8 channel widths outboard of subaqueous channel margins, rather than downstream of channel tips. In interdistributary bays, deposit elevation decreases with a basinward slope of 2.4 x 10-4 with distance from a channel margin along any flow path. Flow patterns and this slope produce constructional features called interdistributary troughs - topographic lows in the center of interdistributary bays. These data show that flow patterns and bathymetry on the delta front are coupled both at the transition from channelized to unchannelized flow and in the depositional regions outside the distributary network.

Factors Impacting Corporate E-Learners' Learning Flow, Satisfaction, and Learning Persistence

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyong; Kim, Nam Hee; Chung, Hyun Min

2012-01-01

This study aimed to investigate the structural relationships among teaching presence, cognitive presence, usage, learning flow, satisfaction, and learning persistence in corporate e-learners. The research participants were 462 e-learners registered for e-lectures through an electronics company in South Korea. First, the sense of teaching presence,…

Negotiating Energy Dynamics through Embodied Action in a Materially Structured Environment

ERIC Educational Resources Information Center

Scherr, Rachel E.; Close, Hunter G.; Close, Eleanor W.; Flood, Virginia J.; McKagan, Sarah B.; Robertson, Amy D.; Seeley, Lane; Wittmann, Michael C.; Vokos, Stamatis

2013-01-01

We provide evidence that a learning activity called Energy Theater engages learners with key conceptual issues in the learning of energy, including disambiguating matter flow and energy flow and theorizing mechanisms for energy transformation. A participationist theory of learning, in which learning is indicated by changes in speech and behavior,…

Observation of airplane flow fields by natural condensation effects

NASA Technical Reports Server (NTRS)

Campbell, James F.; Chambers, Joseph R.; Rumsey, Christopher L.

1988-01-01

In-flight condensation patterns can illustrate a variety of airplane flow fields, such as attached and separated flows, vortex flows, and expansion and shock waves. These patterns are a unique source of flow visualization that has not been utilized previously. Condensation patterns at full-scale Reynolds number can provide useful information for researchers experimenting in subscale tunnels. It is also shown that computed values of relative humidity in the local flow field provide an inexpensive way to analyze the qualitative features of the condensation pattern, although a more complete theoretical modeling is necessary to obtain details of the condensation process. Furthermore, the analysis revealed that relative humidity is more sensitive to changes in local static temperature than to changes in pressure.

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Parametric Study of Flow Patterns behind the Standing Accretion Shock Wave for Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Iwakami, Wakana; Nagakura, Hiroki; Yamada, Shoichi

2014-05-01

In this study, we conduct three-dimensional hydrodynamic simulations systematically to investigate the flow patterns behind the accretion shock waves that are commonly formed in the post-bounce phase of core-collapse supernovae. Adding small perturbations to spherically symmetric, steady, shocked accretion flows, we compute the subsequent evolutions to find what flow pattern emerges as a consequence of hydrodynamical instabilities such as convection and standing accretion shock instability for different neutrino luminosities and mass accretion rates. Depending on these two controlling parameters, various flow patterns are indeed realized. We classify them into three basic patterns and two intermediate ones; the former includes sloshing motion (SL), spiral motion (SP), and multiple buoyant bubble formation (BB); the latter consists of spiral motion with buoyant-bubble formation (SPB) and spiral motion with pulsationally changing rotational velocities (SPP). Although the post-shock flow is highly chaotic, there is a clear trend in the pattern realization. The sloshing and spiral motions tend to be dominant for high accretion rates and low neutrino luminosities, and multiple buoyant bubbles prevail for low accretion rates and high neutrino luminosities. It is interesting that the dominant pattern is not always identical between the semi-nonlinear and nonlinear phases near the critical luminosity; the intermediate cases are realized in the latter case. Running several simulations with different random perturbations, we confirm that the realization of flow pattern is robust in most cases.

Gas-water two-phase flow characterization with Electrical Resistance Tomography and Multivariate Multiscale Entropy analysis.

PubMed

Tan, Chao; Zhao, Jia; Dong, Feng

2015-03-01

Flow behavior characterization is important to understand gas-liquid two-phase flow mechanics and further establish its description model. An Electrical Resistance Tomography (ERT) provides information regarding flow conditions at different directions where the sensing electrodes implemented. We extracted the multivariate sample entropy (MSampEn) by treating ERT data as a multivariate time series. The dynamic experimental results indicate that the MSampEn is sensitive to complexity change of flow patterns including bubbly flow, stratified flow, plug flow and slug flow. MSampEn can characterize the flow behavior at different direction of two-phase flow, and reveal the transition between flow patterns when flow velocity changes. The proposed method is effective to analyze two-phase flow pattern transition by incorporating information of different scales and different spatial directions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The Implications of Null Patterns and Output Unit Activation Functions on Simulation Studies of Learning: A Case Study of Patterning

ERIC Educational Resources Information Center

Yaremchuk, V.; Willson, L.R.; Spetch, M.L.; Dawson, M.R.W.

2005-01-01

Animal learning researchers have argued that one example of a linearly nonseparable problem is negative patterning, and therefore they have used more complicated multilayer networks to study this kind of discriminant learning. However, it is shown in this paper that previous attempts to define negative patterning problems to artificial neural…

Experimental Study on the Flow Regimes and Pressure Gradients of Air-Oil-Water Three-Phase Flow in Horizontal Pipes

PubMed Central

Al-Hadhrami, Luai M.; Shaahid, S. M.; Tunde, Lukman O.; Al-Sarkhi, A.

2014-01-01

An experimental investigation has been carried out to study the flow regimes and pressure gradients of air-oil-water three-phase flows in 2.25 ID horizontal pipe at different flow conditions. The effects of water cuts, liquid and gas velocities on flow patterns and pressure gradients have been studied. The experiments have been conducted at 20°C using low viscosity Safrasol D80 oil, tap water and air. Superficial water and oil velocities were varied from 0.3 m/s to 3 m/s and air velocity varied from 0.29 m/s to 52.5 m/s to cover wide range of flow patterns. The experiments were performed for 10% to 90% water cuts. The flow patterns were observed and recorded using high speed video camera while the pressure drops were measured using pressure transducers and U-tube manometers. The flow patterns show strong dependence on water fraction, gas velocities, and liquid velocities. The observed flow patterns are stratified (smooth and wavy), elongated bubble, slug, dispersed bubble, and annular flow patterns. The pressure gradients have been found to increase with the increase in gas flow rates. Also, for a given superficial gas velocity, the pressure gradients increased with the increase in the superficial liquid velocity. The pressure gradient first increases and then decreases with increasing water cut. In general, phase inversion was observed with increase in the water cut. The experimental results have been compared with the existing unified Model and a good agreement has been noticed. PMID:24523645

Experimental study on the flow regimes and pressure gradients of air-oil-water three-phase flow in horizontal pipes.

PubMed

Al-Hadhrami, Luai M; Shaahid, S M; Tunde, Lukman O; Al-Sarkhi, A

2014-01-01

An experimental investigation has been carried out to study the flow regimes and pressure gradients of air-oil-water three-phase flows in 2.25 ID horizontal pipe at different flow conditions. The effects of water cuts, liquid and gas velocities on flow patterns and pressure gradients have been studied. The experiments have been conducted at 20 °C using low viscosity Safrasol D80 oil, tap water and air. Superficial water and oil velocities were varied from 0.3 m/s to 3 m/s and air velocity varied from 0.29 m/s to 52.5 m/s to cover wide range of flow patterns. The experiments were performed for 10% to 90% water cuts. The flow patterns were observed and recorded using high speed video camera while the pressure drops were measured using pressure transducers and U-tube manometers. The flow patterns show strong dependence on water fraction, gas velocities, and liquid velocities. The observed flow patterns are stratified (smooth and wavy), elongated bubble, slug, dispersed bubble, and annular flow patterns. The pressure gradients have been found to increase with the increase in gas flow rates. Also, for a given superficial gas velocity, the pressure gradients increased with the increase in the superficial liquid velocity. The pressure gradient first increases and then decreases with increasing water cut. In general, phase inversion was observed with increase in the water cut. The experimental results have been compared with the existing unified Model and a good agreement has been noticed.

Two-phase flow characteristics of liquid nitrogen in vertically upward 0.5 and 1.0 mm micro-tubes: Visualization studies

NASA Astrophysics Data System (ADS)

Zhang, P.; Fu, X.

2009-10-01

Application of liquid nitrogen to cooling is widely employed in many fields, such as cooling of the high temperature superconducting devices, cryosurgery and so on, in which liquid nitrogen is generally forced to flow inside very small passages to maintain good thermal performance and stability. In order to have a full understanding of the flow and heat transfer characteristics of liquid nitrogen in micro-tube, high-speed digital photography was employed to acquire the typical two-phase flow patterns of liquid nitrogen in vertically upward micro-tubes of 0.531 and 1.042 mm inner diameters. It was found from the experimental results that the flow patterns were mainly bubbly flow, slug flow, churn flow and annular flow. And the confined bubble flow, mist flow, bubble condensation and flow oscillation were also observed. These flow patterns were characterized in different types of flow regime maps. The surface tension force and the size of the diameter were revealed to be the major factors affecting the flow pattern transitions. It was found that the transition boundaries of the slug/churn flow and churn/annular flow of the present experiment shifted to lower superficial vapor velocity; while the transition boundary of the bubbly/slug flow shifted to higher superficial vapor velocity compared to the results of the room-temperature fluids in the tubes with the similar hydraulic diameters. The corresponding transition boundaries moved to lower superficial velocity when reducing the inner diameter of the micro-tubes. Time-averaged void fraction and heat transfer characteristics for individual flow patterns were presented and special attention was paid to the effect of the diameter on the variation of void fraction.

Breathing simulator of workers for respirator performance test

PubMed Central

YUASA, Hisashi; KUMITA, Mikio; HONDA, Takeshi; KIMURA, Kazushi; NOZAKI, Kosuke; EMI, Hitoshi; OTANI, Yoshio

2014-01-01

Breathing machines are widely used to evaluate respirator performance but they are capable of generating only limited air flow patterns, such as, sine, triangular and square waves. In order to evaluate the respirator performance in practical use, it is desirable to test the respirator using the actual breathing patterns of wearers. However, it has been a difficult task for a breathing machine to generate such complicated flow patterns, since the human respiratory volume changes depending on the human activities and workload. In this study, we have developed an electromechanical breathing simulator and a respiration sampling device to record and reproduce worker’s respiration. It is capable of generating various flow patterns by inputting breathing pattern signals recorded by a computer, as well as the fixed air flow patterns. The device is equipped with a self-control program to compensate the difference in inhalation and exhalation volume and the measurement errors on the breathing flow rate. The system was successfully applied to record the breathing patterns of workers engaging in welding and reproduced the breathing patterns. PMID:25382381

Classification of pulsating flow patterns in curved pipes.

PubMed

Tada, S; Oshima, S; Yamane, R

1996-08-01

The fully developed periodic laminar flow of incompressible Newtonian fluids through a pipe of circular cross section, which is coiled in a circle, was simulated numerically. The flow patterns are characterized by three parameters: the Womersley number Wo, the Dean number De, and the amplitude ratio beta. The effect of these parameters on the flow was studied in the range 2.19 < or = Wo < or = 50.00, 15.07 < or = De < or = 265.49 and 0.50 < or = beta < or = 2.00, with the curvature ratio delta fixed to be 0.05. The way the secondary flow evolved with increasing Womersley number and Dean number is explained. The secondary flow patterns are classified into three main groups: the viscosity-dominated type, the inertia-dominated type, and the convection-dominated type. It was found that when the amplitude ratio of the volumetric flow rate is equal to 1.0, four to six vortices of the secondary flow appear at high Dean numbers, and the Lyne-type flow patterns disappear at beta > or = 0.50.

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun; Spires, Hiller A.

2014-01-01

This mixed methods study examined 73 5th graders' flow experience in a game-based science learning environment using two gameplay approaches (solo and collaborative gameplay). Both survey and focus group interview findings revealed that students had high flow experience; however, there were no flow experience differences that were contingent upon…

A Study of Flow Theory in the Foreign Language Classroom

ERIC Educational Resources Information Center

Egbert, Joy

2004-01-01

This article focuses on the relationship between flow experiences and language learning. Flow Theory suggests that flow experiences (characterized by a balance between challenge and skills and by a person's interest, control, and focused attention during a task) can lead to optimal learning. This theory has not yet been tested in the area of…

Magnetic field induced flow pattern reversal in a ferrofluidic Taylor-Couette system

PubMed Central

Altmeyer, Sebastian; Do, Younghae; Lai, Ying-Cheng

2015-01-01

We investigate the dynamics of ferrofluidic wavy vortex flows in the counter-rotating Taylor-Couette system, with a focus on wavy flows with a mixture of the dominant azimuthal modes. Without external magnetic field flows are stable and pro-grade with respect to the rotation of the inner cylinder. More complex behaviors can arise when an axial or a transverse magnetic field is applied. Depending on the direction and strength of the field, multi-stable wavy states and bifurcations can occur. We uncover the phenomenon of flow pattern reversal as the strength of the magnetic field is increased through a critical value. In between the regimes of pro-grade and retrograde flow rotations, standing waves with zero angular velocities can emerge. A striking finding is that, under a transverse magnetic field, a second reversal in the flow pattern direction can occur, where the flow pattern evolves into pro-grade rotation again from a retrograde state. Flow reversal is relevant to intriguing phenomena in nature such as geomagnetic reversal. Our results suggest that, in ferrofluids, flow pattern reversal can be induced by varying a magnetic field in a controlled manner, which can be realized in laboratory experiments with potential applications in the development of modern fluid devices. PMID:26687638

Magnetic field induced flow pattern reversal in a ferrofluidic Taylor-Couette system.

PubMed

Altmeyer, Sebastian; Do, Younghae; Lai, Ying-Cheng

2015-12-21

We investigate the dynamics of ferrofluidic wavy vortex flows in the counter-rotating Taylor-Couette system, with a focus on wavy flows with a mixture of the dominant azimuthal modes. Without external magnetic field flows are stable and pro-grade with respect to the rotation of the inner cylinder. More complex behaviors can arise when an axial or a transverse magnetic field is applied. Depending on the direction and strength of the field, multi-stable wavy states and bifurcations can occur. We uncover the phenomenon of flow pattern reversal as the strength of the magnetic field is increased through a critical value. In between the regimes of pro-grade and retrograde flow rotations, standing waves with zero angular velocities can emerge. A striking finding is that, under a transverse magnetic field, a second reversal in the flow pattern direction can occur, where the flow pattern evolves into pro-grade rotation again from a retrograde state. Flow reversal is relevant to intriguing phenomena in nature such as geomagnetic reversal. Our results suggest that, in ferrofluids, flow pattern reversal can be induced by varying a magnetic field in a controlled manner, which can be realized in laboratory experiments with potential applications in the development of modern fluid devices.

Disruption of intracardiac flow patterns in the newborn infant.

PubMed

Groves, Alan M; Durighel, Giuliana; Finnemore, Anna; Tusor, Nora; Merchant, Nazakat; Razavi, Reza; Hajnal, Jo V; Edwards, A David

2012-04-01

Consistent patterns of rotational intracardiac flow have been demonstrated in the healthy adult human heart. Intracardiac rotational flow patterns are hypothesized to assist in the maintenance of kinetic energy of inflowing blood, augmenting cardiac function. Newborn cardiac function is known to be suboptimal secondary to decreased receptor number and sympathetic innervation, increased afterload, and increased reliance on atrial contraction to support ventricular filling. Patterns of intracardiac flow in the newborn have not previously been examined. Whereas 5 of the 13 infants studied showed significant evidence of rotational flow within the right atrium, 8 infants showed little or no rotational flow. Presence or absence of rotational flow was not related to gestational age, birth weight, postnatal age, atrial size, or image quality. Despite absence of intra-atrial rotational flow, atrioventricular valve flow into the left and right ventricles later in the cardiac cycle could be seen, suggesting that visualization techniques were adequate. While further study is required to assess its exact consequences on cardiac mechanics and energetics, disruption to intracardiac flow patterns could be another contributor to the multifactorial sequence that produces newborn circulatory failure. We studied 13 newborn infants, using three-dimensional (3D) cardiac magnetic resonance phase-contrast imaging (spatial resolution 0.84 mm, temporal resolution 22.6 ms) performed without sedation/anesthesia.

Reduplicated Words Are Easier to Learn

ERIC Educational Resources Information Center

Ota, Mitsuhiko; Skarabela, Barbora

2016-01-01

Infants' disposition to learn repetitions in the input structure has been demonstrated in pattern generalization (e.g., learning the pattern ABB from the token "ledidi"). This study tested whether a repetition advantage can also be found in lexical learning (i.e., learning the word "lele" vs. "ledi"). Twenty-four…

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods

DTIC Science & Technology

2017-05-22

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods 5b. GRANT NUMBER...of these effects varies with the elevation patterns (level, duration, temporal fluctuation) achieved by different administration methods . In general...learning varies with elevation patterns and administration methods Dragana I. Claflin a, Kevin D. Schmidt a, Zachary D. Vallandingham b, Michal

A Preliminary Analysis of the Theoretical Parameters of Organizaational Learning.

DTIC Science & Technology

1995-09-01

PARAMETERS OF ORGANIZATIONAL LEARNING THESIS Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air...Organizational Learning Parameters in the Knowledge Acquisition Category 2~™ 2-3. Organizational Learning Parameters in the Information Distribution Category...Learning Refined Scale 4-94 4-145. Composition of Refined Scale 4 Knowledge Flow 4-95 4-146. Cronbach’s Alpha Statistics for the Complete Knowledge Flow

Patterns in clinical students' self-regulated learning behavior: a Q-methodology study.

PubMed

Berkhout, Joris J; Teunissen, Pim W; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P M; Jaarsma, Debbie A D C

2017-03-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in undergraduate students' self-regulated learning behavior in the clinical environment, to improve tailored supervision, using Q-methodology. Q-methodology uses features of both qualitative and quantitative methods for the systematic investigation of subjective issues by having participants sort statements along a continuum to represent their opinion. We enrolled 74 students between December 2014 and April 2015 and had them characterize their learning behavior by sorting 52 statements about self-regulated learning behavior and explaining their response. The statements used for the sorting were extracted from a previous study. The data was analyzed using by-person factor analysis to identify clusters of individuals with similar sorts of the statements. The resulting factors and qualitative data were used to interpret and describe the patterns that emerged. Five resulting patterns were identified in students' self-regulated learning behavior in the clinical environment, which we labelled: Engaged, Critically opportunistic, Uncertain, Restrained and Effortful. The five patterns varied mostly regarding goals, metacognition, communication, effort, and dependence on external regulation for learning. These discrete patterns in students' self-regulated learning behavior in the clinical environment are part of a complex interaction between student and learning context. The results suggest that developing self-regulated learning behavior might best be supported regarding individual students' needs.

Research Issues in Evaluating Learning Pattern Development in Higher Education

ERIC Educational Resources Information Center

Richardson, John T. E.

2013-01-01

This article concludes the special issue of "Studies in Educational Evaluation" concerned with "Evaluating learning pattern development in higher education" by discussing research issues that have emerged from the previous contributions. The article considers in turn: stability versus variability in learning patterns; old versus new analytic…

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning

PubMed Central

Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-01-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. Here we show that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) are dynamically reformatted in the network at the timescale of a single breath, giving rise to separated patterns of activity in ensemble of output neurons (mitral/tufted cells; M/T). Strikingly, the extent of pattern separation in M/T assemblies predicts behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimuli distinction, a process that is sculpted by synaptic inhibition. PMID:26301325

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning.

PubMed

Gschwend, Olivier; Abraham, Nixon M; Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-10-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features, thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. We found that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) were dynamically reformatted in the network on the timescale of a single breath, giving rise to separated patterns of activity in an ensemble of output neurons, mitral/tufted (M/T) cells. Notably, the extent of pattern separation in M/T assemblies predicted behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimulus distinction, a process that is sculpted by synaptic inhibition.

Proactive transfer of learning depends on the evolution of prior learned task in memory.

PubMed

Tallet, Jessica; Kostrubiec, Viviane; Zanone, Pier-Giorgio

2010-06-01

The aim of the present study was to investigate the processes underlying the proactive interference effect using bimanual coordination. Our rationale was that interference would only occur when the prior learned A coordination pattern enters in competition with the required subsequent B pattern. We hypothesized that competition would arise only if the A pattern persists in memory before introducing the B pattern. In the experimental group, both A and B patterns were practiced and recalled, whereas in the control group only the B pattern was practiced and recalled. In Experiment 1, which involved initially bistable participants, the persistence of the A pattern led to interference, while, surprisingly, the A pattern forgetting entailed facilitation. In Experiment 2, which involved initially tristable participants, no such transfer effect was found. The apparently contradictory results can be interpreted coherently in the light of dynamical principles of learning. (c) 2010 Elsevier B.V. All rights reserved.

The influence of different diffusion pattern to the sub- and super-critical fluid flow in brown coal

NASA Astrophysics Data System (ADS)

Peng, Peihuo

2018-03-01

Sub- and super-critical CO2 flowing in nanoscale pores are recently becoming of great interest due to that it is closely related to many engineering applications, such as geological burial and sequestration of carbon dioxide, Enhanced Coal Bed Methane recovery ( ECBM), super-critical CO2 fracturing and so on. Gas flow in nanopores cannot be described simply by the Darcy equation. Different diffusion pattern such as Fick diffusion, Knudsen diffusion, transitional diffusion and slip flow at the solid matrix separate the seepage behaviour from Darcy-type flow. According to the principle of different diffusion pattern, the flow of sub- and super-critical CO2 in brown coal was simulated by numerical method, and the results were compared with the experimental results to explore the contribution of different diffusion pattern and swelling effect in sub- and super-critical CO2 flow in nanoscale pores.

Flow regimes of adiabatic gas-liquid two-phase under rolling conditions

NASA Astrophysics Data System (ADS)

Yan, Chaoxing; Yan, Changqi; Sun, Licheng; Xing, Dianchuan; Wang, Yang; Tian, Daogui

2013-07-01

Characteristics of adiabatic air/water two-phase flow regimes under vertical and rolling motion conditions were investigated experimentally. Test sections are two rectangular ducts with the gaps of 1.41 and 10 mm, respectively, and a circular tube with 25 mm diameter. Flow regimes were recorded by a high speed CCD-camera and were identified by examining the video images. The experimental results indicate that the characteristics of flow patterns in 10 mm wide rectangular duct under vertical condition are very similar to those in circular tube, but different from the 1.41 mm wide rectangular duct. Channel size has a significant influence on flow pattern transition, boundary of which in rectangular channels tends asymptotically towards that in the circular tube with increasing the width of narrow side. Flow patterns in rolling channels are similar to each other, nevertheless, the effect of rolling motion on flow pattern transition are significantly various. Due to the remarkable influences of the friction shear stress and surface tension in the narrow gap duct, detailed flow pattern maps of which under vertical and rolling conditions are indistinguishable. While for the circular tube with 25 mm diameter, the transition from bubbly to slug flow occurs at a higher superficial liquid velocity and the churn flow covers more area on the flow regime map as the rolling period decreases.

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

ERIC Educational Resources Information Center

Hung, Jui-Long; Crooks, Steven M.

2009-01-01

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

Comprehensive assessment of dam impacts on flow regimes with consideration of interannual variations

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Shao, Quanxi; Zhao, Tongtiegang

2017-09-01

Assessing the impact of human intervention on flow regimes is important in policy making and resource management. Previous impact assessments of dam regulation on flow regimes have focused on long-term average patterns, but interannual variations, which are important characteristics to be considered, have been ignored. In this study, the entire signatures of hydrograph variations of Miyun Reservoir in northern China were described by forty flow regime metrics that incorporate magnitude, variability and frequency, duration, timing, and rate of change for flow events based on a long-term synchronous observation series of inflow and outflow. Principal component analysis and cluster analysis were used to reduce the multidimensionality of the metrics and time and to determine impact patterns and their interannual shifts. Statistically significant driving factors of impact pattern variations were identified. We found that dam regulation resulted in four main impact classes on the flow regimes and that the regulated capacity was interannually attenuated from 1973 to 2010. The impact patterns alternated between the highly regulated class with extremely decreasing flow magnitude, slight variability, and extreme intermittency and the slightly regulated class with extremely increasing flow magnitude, slight variability, and extreme intermittency from 1973 to 1987 and then stabilized in the latter class from 1988 to 2001. After 2001, the pattern gradually changed from the moderately regulated class with moderately decreasing flow magnitude, extreme variability, and extreme intermittency to the slightly regulated class with slightly decreasing flow magnitude, slight variability, and no intermittency. Decreasing precipitation and increasing drought were the primary drivers for the interannual variations of the impact patterns, and inflow variability was the most significant factor affecting the patterns, followed by flow event frequency and duration, magnitude, and timing. This study shows that the use of interannual characteristics can help to gain more insight into the impact of dam regulation on flow regimes and will provide important information to scientifically guide the multi-purpose regulation of dams.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Gustavsson, Kristian; Celani, Antonio; Biferale, Luca

2017-04-01

Smart active particles can acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. Their goal is to learn the best way to navigate by exploiting the underlying flow whenever possible. As an example, we focus our attention on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, given the constraints enforced by fluid mechanics. By means of numerical experiments, we show that swimmers indeed learn nearly optimal strategies just by experience. A reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This Letter illustrates the potential of reinforcement learning algorithms to model adaptive behavior in complex flows and paves the way towards the engineering of smart microswimmers that solve difficult navigation problems.

Identifying Learning Patterns of Children at Risk for Specific Reading Disability

PubMed Central

Barbot, Baptiste; Krivulskaya, Suzanna; Hein, Sascha; Reich, Jodi; Thuma, Philip E.; Grigorenko, Elena L.

2016-01-01

Differences in learning patterns of vocabulary acquisition in children at risk (+SRD) and not at risk (SRD) for Specific Reading Disability (SRD) were examined using a microdevelopmental paradigm applied to the multi-trial Foreign Language Learning Task (FLLT; Baddeley et al., 1995). The FLLT was administered to 905 children from rural Chitonga-speaking Zambia. A multi-group Latent Growth Curve Model (LGCM) was implemented to study interindividual differences in intraindividual change across trials. Results showed that the +SRD group recalled fewer words correctly in the first trial, learned at a slower rate during the subsequent trials, and demonstrated a more linear learning pattern compared to the SRD group. This study illustrates the promise of LGCM applied to multi-trial learning tasks, by isolating three components of the learning process (initial recall, rate of learning, and functional pattern of learning). Implications of this microdevelopmental approach to SRD research in low-to-middle income countries are discussed. PMID:26037654

Identifying learning patterns of children at risk for Specific Reading Disability.

PubMed

Barbot, Baptiste; Krivulskaya, Suzanna; Hein, Sascha; Reich, Jodi; Thuma, Philip E; Grigorenko, Elena L

2016-05-01

Differences in learning patterns of vocabulary acquisition in children at risk (+SRD) and not at risk (-SRD) for Specific Reading Disability (SRD) were examined using a microdevelopmental paradigm applied to the multi-trial Foreign Language Learning Task (FLLT; Baddeley et al., 1995). The FLLT was administered to 905 children from rural Chitonga-speaking Zambia. A multi-group Latent Growth Curve Model (LGCM) was implemented to study interindividual differences in intraindividual change across trials. Results showed that the +SRD group recalled fewer words correctly in the first trial, learned at a slower rate during the subsequent trials, and demonstrated a more linear learning pattern compared to the -SRD group. This study illustrates the promise of LGCM applied to multi-trial learning tasks, by isolating three components of the learning process (initial recall, rate of learning, and functional pattern of learning). Implications of this microdevelopmental approach to SRD research in low-to-middle income countries are discussed. © 2015 John Wiley & Sons Ltd.

Flow pattern changes influenced by variation of viscosities of a heterogeneous gas-liquid mixture flow in a vertical channel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keska, Jerry K.; Hincapie, Juan; Jones, Richard

In the steady-state flow of a heterogeneous mixture such as an air-liquid mixture, the velocity and void fraction are space- and time-dependent parameters. These parameters are the most fundamental in the analysis and description of a multiphase flow. The determination of flow patterns in an objective way is extremely critical, since this is directly related to sudden changes in spatial and temporal changes of the random like characteristic of concentration. Flow patterns can be described by concentration signals in time, amplitude, and frequency domains. Despite the vital importance and countless attempts to solve or incorporate the flow pattern phenomena intomore » multiphase models, it has still been a very challenging topic in the scientific community since the 1940's and has not yet reached a satisfactory solution. This paper reports the experimental results of the impact of fluid viscosity on flow patterns for two-phase flow. Two-phase flow was created in laboratory equipment using air and liquid as phase medium. The liquid properties were changed by using variable concentrations of glycerol in water mixture which generated a wide-range of dynamic viscosities ranging from 1 to 1060 MPa s. The in situ spatial concentration vs. liquid viscosity and airflow velocity of two-phase flow in a vertical ID=50.8 mm pipe were measured using two concomitant computer-aided measurement systems. After acquiring data, the in situ special concentration signals were analyzed in time (spatial concentration and RMS of spatial concentration vs. time), amplitude (PDF and CPDF), and frequency (PSD and CPSD) domains that documented broad flow pattern changes caused by the fluid viscosity and air velocity changes. (author)« less

Parametric study of flow patterns behind the standing accretion shock wave for core-collapse supernovae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iwakami, Wakana; Nagakura, Hiroki; Yamada, Shoichi, E-mail: wakana@heap.phys.waseda.ac.jp

2014-05-10

In this study, we conduct three-dimensional hydrodynamic simulations systematically to investigate the flow patterns behind the accretion shock waves that are commonly formed in the post-bounce phase of core-collapse supernovae. Adding small perturbations to spherically symmetric, steady, shocked accretion flows, we compute the subsequent evolutions to find what flow pattern emerges as a consequence of hydrodynamical instabilities such as convection and standing accretion shock instability for different neutrino luminosities and mass accretion rates. Depending on these two controlling parameters, various flow patterns are indeed realized. We classify them into three basic patterns and two intermediate ones; the former includes sloshingmore » motion (SL), spiral motion (SP), and multiple buoyant bubble formation (BB); the latter consists of spiral motion with buoyant-bubble formation (SPB) and spiral motion with pulsationally changing rotational velocities (SPP). Although the post-shock flow is highly chaotic, there is a clear trend in the pattern realization. The sloshing and spiral motions tend to be dominant for high accretion rates and low neutrino luminosities, and multiple buoyant bubbles prevail for low accretion rates and high neutrino luminosities. It is interesting that the dominant pattern is not always identical between the semi-nonlinear and nonlinear phases near the critical luminosity; the intermediate cases are realized in the latter case. Running several simulations with different random perturbations, we confirm that the realization of flow pattern is robust in most cases.« less

Compatibility of information and mode of control: The case for natural control systems

NASA Technical Reports Server (NTRS)

Owen, Dean H.

1993-01-01

The operation of control systems has been determined largely by mechanical constraints. Compatibility with the characteristics of the operator is a secondary consideration, with the result that control may never be optimal, control workload may interfere with performance of secondary tasks, and learning may be more difficult and protracted than necessary. With the introduction of a computer in the control loop, the mode of operation can be adapted to the operator, rather than vice versa. The concept of natural control is introduced to describe a system that supports control of the information used by the operator in achieving an intended goal. As an example, control of speed during simulated approach to a pad by helicopter pilots is used to contrast path-speed control with direct control of global optical flow-pattern information. Differences are evidenced in the performance domains of control activity, speed, and global optical flow velocity.

Experimental Measurements of Heat Transfer through a Lunar Regolith Simulant in a Vibro-Fluidized Reactor Oven

NASA Technical Reports Server (NTRS)

Nayagam, Vedha; Berger, Gordon M.; Sacksteder, Kurt R.; Paz, Aaron

2012-01-01

Extraction of mission consumable resources such as water and oxygen from the planetary environment provides valuable reduction in launch-mass and potentially extends the mission duration. Processing of lunar regolith for resource extraction necessarily involves heating and chemical reaction of solid material with processing gases. Vibrofluidization is known to produce effective mixing and control of flow within granular media. In this study we present experimental results for vibrofluidized heat transfer in lunar regolith simulants (JSC-1 and JSC-1A) heated up to 900 C. The results show that the simulant bed height has a significant influence on the vibration induced flow field and heat transfer rates. A taller bed height leads to a two-cell circulation pattern whereas a single-cell circulation was observed for a shorter height. Lessons learned from these test results should provide insight into efficient design of future robotic missions involving In-Situ Resource Utilization.

How pattern is selected in drift wave turbulence: Role of parallel flow shear

NASA Astrophysics Data System (ADS)

Kosuga, Y.

2017-12-01

The role of parallel shear flow in the pattern selection problem in drift wave turbulence is discussed. Patterns of interest here are E × B convective cells, which include poloidally symmetric zonal flows and radially elongated streamers. The competition between zonal flow formation and streamer formation is analyzed in the context of modulational instability analysis, with the parallel flow shear as a parameter. For drift wave turbulence with k⊥ρs ≲ O (1 ) and without parallel flow coupling, zonal flows are preferred structures. While increasing the magnitude of parallel flow shear, streamer growth overcomes zonal flow growth. This is because the self-focusing effect of the modulational instability becomes more effective for streamers through density and parallel velocity modulation. As a consequence, the bursty release of free energy may result as the parallel flow shear increases.

On the structure of cellular solutions in Rayleigh-Benard-Marangoni flows in small-aspect-ratio containers

NASA Technical Reports Server (NTRS)

Dijkstra, Henk A.

1992-01-01

Multiple steady flow patterns occur in surface-tension/buoyancy-driven convection in a liquid layer heated from below (Rayleigh-Benard-Marangoni flows). Techniques of numerical bifurcation theory are used to study the multiplicity and stability of two-dimensional steady flow patterns (rolls) in rectangular small-aspect-ratio containers as the aspect ratio is varied. For pure Marangoni flows at moderate Biot and Prandtl number, the transitions occurring when paths of codimension 1 singularities intersect determine to a large extent the multiplicity of stable patterns. These transitions also lead, for example, to Hopf bifurcations and stable periodic flows for a small range in aspect ratio. The influence of the type of lateral walls on the multiplicity of steady states is considered. 'No-slip' lateral walls lead to hysteresis effects and typically restrict the number of stable flow patterns (with respect to 'slippery' sidewalls) through the occurrence of saddle node bifurcations. In this way 'no-slip' sidewalls induce a selection of certain patterns, which typically have the largest Nusselt number, through secondary bifurcation.

The role of consolidation in learning context-dependent phonotactic patterns in speech and digital sequence production.

PubMed

Anderson, Nathaniel D; Dell, Gary S

2018-04-03

Speakers implicitly learn novel phonotactic patterns by producing strings of syllables. The learning is revealed in their speech errors. First-order patterns, such as "/f/ must be a syllable onset," can be distinguished from contingent, or second-order, patterns, such as "/f/ must be an onset if the vowel is /a/, but a coda if the vowel is /o/." A metaanalysis of 19 experiments clearly demonstrated that first-order patterns affect speech errors to a very great extent in a single experimental session, but second-order vowel-contingent patterns only affect errors on the second day of testing, suggesting the need for a consolidation period. Two experiments tested an analogue to these studies involving sequences of button pushes, with fingers as "consonants" and thumbs as "vowels." The button-push errors revealed two of the key speech-error findings: first-order patterns are learned quickly, but second-order thumb-contingent patterns are only strongly revealed in the errors on the second day of testing. The influence of computational complexity on the implicit learning of phonotactic patterns in speech production may be a general feature of sequence production.

Computational Analysis of Intra-Ventricular Flow Pattern Under Partial and Full Support of BJUT-II VAD.

PubMed

Zhang, Qi; Gao, Bin; Chang, Yu

2017-02-27

BACKGROUND Partial support, as a novel support mode, has been widely applied in clinical practice and widely studied. However, the precise mechanism of partial support of LVAD in the intra-ventricular flow pattern is unclear. MATERIAL AND METHODS In this study, a patient-specific left ventricular geometric model was reconstructed based on CT data. The intra-ventricular flow pattern under 3 simulated conditions - "heart failure", "partial support", and "full support" - were simulated by using fluid-structure interaction (FSI). The blood flow pattern, wall shear stress (WSS), time-average wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT) were calculated to evaluate the hemodynamic effects. RESULTS The results demonstrate that the intra-ventricular flow pattern is significantly changed by the support level of BJUT-II VAD. The intra-ventricular vortex was enhanced under partial support and was eliminated under full support, and the high OSI and RRT regions changed from the septum wall to the cardiac apex. CONCLUSIONS In brief, the support level of the BJUT-II VAD has significant effects on the intra-ventricular flow pattern. The partial support mode of BJUT-II VAD can enhance the intra-ventricular vortex, while the distribution of high OSI and RRT moved from the septum wall to the cardiac apex. Hence, the partial support mode of BJUT-II VAD can provide more benefit for intra-ventricular flow pattern.

Surface Patterning: Controlling Fluid Flow Through Dolphin and Shark Skin Biomimicry

NASA Astrophysics Data System (ADS)

Gamble, Lawren; Lang, Amy; Bradshaw, Michael; McVay, Eric

2013-11-01

Dolphin skin is characterized by circumferential ridges, perpendicular to fluid flow, present from the crest of the head until the tail fluke. When observing a cross section of skin, the ridges have a sinusoidal pattern. Sinusoidal grooves have been proven to induce vortices in the cavities that can help control flow separation which can reduce pressure drag. Shark skin, however, is patterned with flexible scales that bristle up to 50 degrees with reversed flow. Both dolphin ridges and shark scales are thought to help control fluid flow and increase swimming efficiency by delaying the separation of the boundary layer. This study investigates how flow characteristics can be altered with bio-inspired surface patterning. A NACA 4412 hydrofoil was entirely patterned with transverse sinusoidal grooves, inspired by dolphin skin but scaled so the cavities on the model have the same Reynolds number as the cavities on a swimming shark. Static tests were conducted at a Reynolds number of approximately 100,000 and at varying angles of attack. The results were compared to the smooth hydrofoil case. The flow data was quantified using Digital Particle Image Velocimetry (DPIV). The results of this study demonstrated that the patterned hydrofoil experienced greater separation than the smooth hydrofoil. It is hypothesize that this could be remediated if the pattern was placed only after the maximum thickness of the hydrofoil. Funding through NSF REU grant 1062611 is gratefully acknowledged.

Sheared bioconvection in a horizontal tube

NASA Astrophysics Data System (ADS)

Croze, O. A.; Ashraf, E. E.; Bees, M. A.

2010-12-01

The recent interest in using microorganisms for biofuels is motivation enough to study bioconvection and cell dispersion in tubes subject to imposed flow. To optimize light and nutrient uptake, many microorganisms swim in directions biased by environmental cues (e.g. phototaxis in algae and chemotaxis in bacteria). Such taxes inevitably lead to accumulations of cells, which, as many microorganisms have a density different to the fluid, can induce hydrodynamic instabilites. The large-scale fluid flow and spectacular patterns that arise are termed bioconvection. However, the extent to which bioconvection is affected or suppressed by an imposed fluid flow and how bioconvection influences the mean flow profile and cell transport are open questions. This experimental study is the first to address these issues by quantifying the patterns due to suspensions of the gravitactic and gyrotactic green biflagellate alga Chlamydomonas in horizontal tubes subject to an imposed flow. With no flow, the dependence of the dominant pattern wavelength at pattern onset on cell concentration is established for three different tube diameters. For small imposed flows, the vertical plumes of cells are observed merely to bow in the direction of flow. For sufficiently high flow rates, the plumes progressively fragment into piecewise linear diagonal plumes, unexpectedly inclined at constant angles and translating at fixed speeds. The pattern wavelength generally grows with flow rate, with transitions at critical rates that depend on concentration. Even at high imposed flow rates, bioconvection is not wholly suppressed and perturbs the flow field.

Learning Cue Phrase Patterns from Radiology Reports Using a Genetic Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, Robert M; Beckerman, Barbara G; Potok, Thomas E

2009-01-01

Various computer-assisted technologies have been developed to assist radiologists in detecting cancer; however, the algorithms still lack high degrees of sensitivity and specificity, and must undergo machine learning against a training set with known pathologies in order to further refine the algorithms with higher validity of truth. This work describes an approach to learning cue phrase patterns in radiology reports that utilizes a genetic algorithm (GA) as the learning method. The approach described here successfully learned cue phrase patterns for two distinct classes of radiology reports. These patterns can then be used as a basis for automatically categorizing, clustering, ormore » retrieving relevant data for the user.« less

Do Online Learning Patterns Exhibit Regional and Demographic Differences?

ERIC Educational Resources Information Center

Hsieh, Tsui-Chuan; Yang, Chyan

2012-01-01

This paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are…

Patterns of Learning in a Sample of Adult Returners to Higher Education

ERIC Educational Resources Information Center

Anderson, Anthony; Johnston, Bill; McDonald, Alexandra

2014-01-01

This article presents empirical research exploring adult returner students' patterns of learning via qualitative analysis of a series of semi-structured interviews. Interviewees' comments shed light on the relation between patterns of learning on the one hand, and study skills, epistemological issues and attitudes to peer interaction on the other.…

The role of transvaginal power Doppler ultrasound in the differential diagnosis of benign intrauterine focal lesions.

PubMed

Cogendez, Ebru; Eken, Meryem Kurek; Bakal, Nuray; Gun, Ismet; Kaygusuz, Ecmel Isik; Karateke, Ates

2015-10-01

The purpose of this prospective study was to assess the role of power Doppler imaging in the differential diagnosis of benign intrauterine focal lesions such as endometrial polyps and submucous myomas using the characteristics of power Doppler flow mapping. A total of 480 premenopausal patients with abnormal uterine bleeding were evaluated by transvaginal ultrasonography (TVS) searching for intrauterine pathology. Sixty-four patients with a suspicious focal endometrial lesion received saline infusion sonography (SIS) after TVS. Fifty-eight patients with focal endometrial lesions underwent power Doppler ultrasound (PDUS). Three different vascular flow patterns were defined: Single vessel pattern, multiple vessel pattern, and circular flow pattern. Finally, hysteroscopic resection was performed in all cases, and Doppler flow characteristics were then compared with the final histopathological findings. Histopathological results were as follows: endometrial polyp: 40 (69 %), submucous myoma: 18 (31 %). Of the cases with endometrial polyps, 80 % demonstrated a single vessel pattern, 7.5 % a multiple vessel pattern, and 0 % a circular pattern. Vascularization was not observed in 12.5 % of patients with polyps. Of the cases with submucousal myomas, 72.2 % demonstrated a circular flow pattern, 27.8 % a multiple vessel pattern, and none of them showed a single vessel pattern. The sensitivity, specificity, and positive and negative predictive values of the single vessel pattern in diagnosing endometrial polyps were 80, 100, 100, and 69.2 %, respectively; and for the circular pattern in diagnosing submucous myoma, these were 72.2, 100, 100, and 88.9 %, respectively. Power Doppler blood flow mapping is a useful, practical, and noninvasive diagnostic method for the differential diagnosis of benign intrauterine focal lesions. Especially in cases of recurrent abnormal uterine bleeding, recurrent abortion, and infertility, PDUS can be preferred as a first-line diagnostic method.

Eliciting design patterns for e-learning systems

NASA Astrophysics Data System (ADS)

Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

2006-06-01

Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

Patterns in Elementary School Students' Strategic Actions in Varying Learning Situations

ERIC Educational Resources Information Center

Malmberg, Jonna; Järvenoja, Hanna; Järvelä, Sanna

2013-01-01

This study uses log file traces to examine differences between high-and low-achieving students' strategic actions in varying learning situations. In addition, this study illustrates, in detail, what strategic and self-regulated learning constitutes in practice. The study investigates the learning patterns that emerge in learning situations…

An Active, Collaborative Approach to Learning Skills in Flow Cytometry

ERIC Educational Resources Information Center

Fuller, Kathryn; Linden, Matthew D.; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N.; Röhrig, Kimberley J.

2016-01-01

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow…

Observing Flow in Young Children's Music Learning.

ERIC Educational Resources Information Center

Custodero, Lori A.

1998-01-01

Explores a study that quantifies preschool children's music learning preferences in teacher-intitiated environments by observing the children on video to determine their flow experiences where the challenge level and skill level are both high. Stresses that using flow to measure music experiences provides a means for teachers to evaluate student…

Correlation of the flow patterns among the four pulmonary veins as assessed by transesophageal echocardiography: influence of significant mitral regurgitation.

PubMed

Hwang, J J; Lin, J M; Hsu, K L; Lai, L P; Tseng, Y Z; Lee, Y T; Lien, W P

1999-01-01

To evaluate the correlation of the flow patterns of the four pulmonary veins as assessed by transesophageal echocardiography and the influence of significant mitral regurgitation on this correlation. Eighty-eight patients with normal sinus rhythm and variable underlying cardiovascular diseases underwent transthoracic and transesophageal echocardiographic studies. Doppler flow of the four pulmonary veins could not be adequately interpreted in 19 patients (22%). The left atrial dimension of these patients was significantly larger than that of the patients with complete study of the flow in the four pulmonary veins (49 +/- 6 vs. 43 +/- 7 mm; p < 0.05). Of the 69 patients with complete evaluation of the four pulmonary veins, 48 patients without significant mitral regurgitation were analyzed as group A, and the remaining 21 patients as group B. The peak systolic and diastolic forward flow velocities of the four pulmonary veins were measured and the ratio of peak systolic (S) to diastolic (D) flow velocity was calculated. Group A had a significantly larger S/D ratio in all four pulmonary veins than group B (p < 0.05 in each pulmonary vein measurement). There was good correlation of the flow pattern represented as S/D ratio between left upper and lower pulmonary veins (r = 0.90) and between right upper and lower pulmonary veins (r = 0.89) in group A. The correlation of the flow pattern among the four pulmonary veins deteriorated in group B. Pulmonary veins on the same side share rather similar flow patterns in comparison with pulmonary veins on the opposite sides. The correlation of flow patterns among the four pulmonary veins is good in subjects without significant mitral regurgitation, but it worsens in patients with significant mitral regurgitation. Therefore, cautious interpretation of flow patterns of the four pulmonary veins in patients with significant regurgitation is indicated for grading the severity of mitral regurgitation.

Modelling human mobility patterns using photographic data shared online.

PubMed

Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah

2015-08-01

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns.

Modelling human mobility patterns using photographic data shared online

PubMed Central

Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah

2015-01-01

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns. PMID:26361545

Grammatical pattern learning by human infants and cotton-top tamarin monkeys

PubMed Central

Saffran, Jenny; Hauser, Marc; Seibel, Rebecca; Kapfhamer, Joshua; Tsao, Fritz; Cushman, Fiery

2008-01-01

There is a surprising degree of overlapping structure evident across the languages of the world. One factor leading to cross-linguistic similarities may be constraints on human learning abilities. Linguistic structures that are easier for infants to learn should predominate in human languages. If correct, then (a) human infants should more readily acquire structures that are consistent with the form of natural language, whereas (b) non-human primates’ patterns of learning should be less tightly linked to the structure of human languages. Prior experiments have not directly compared laboratory-based learning of grammatical structures by human infants and non-human primates, especially under comparable testing conditions and with similar materials. Five experiments with 12-month-old human infants and adult cotton-top tamarin monkeys addressed these predictions, employing comparable methods (familiarization-discrimination) and materials. Infants rapidly acquired complex grammatical structures by using statistically predictive patterns, failing to learn structures that lacked such patterns. In contrast, the tamarins only exploited predictive patterns when learning relatively simple grammatical structures. Infant learning abilities may serve both to facilitate natural language acquisition and to impose constraints on the structure of human languages. PMID:18082676

Machine Learning and Inverse Problem in Geodynamics

NASA Astrophysics Data System (ADS)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

2017-12-01

During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques can successfully predict the magnitude of the mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex problems in mantle dynamics by employing deep learning algorithms for estimation of mantle properties such as viscosity, elastic parameters, and thermal and chemical anomalies.

Preferential flow from pore to landscape scales

NASA Astrophysics Data System (ADS)

Koestel, J. K.; Jarvis, N.; Larsbo, M.

2017-12-01

In this presentation, we give a brief personal overview of some recent progress in quantifying preferential flow in the vadose zone, based on our own work and those of other researchers. One key challenge is to bridge the gap between the scales at which preferential flow occurs (i.e. pore to Darcy scales) and the scales of interest for management (i.e. fields, catchments, regions). We present results of recent studies that exemplify the potential of 3-D non-invasive imaging techniques to visualize and quantify flow processes at the pore scale. These studies should lead to a better understanding of how the topology of macropore networks control key state variables like matric potential and thus the strength of preferential flow under variable initial and boundary conditions. Extrapolation of this process knowledge to larger scales will remain difficult, since measurement technologies to quantify macropore networks at these larger scales are lacking. Recent work suggests that the application of key concepts from percolation theory could be useful in this context. Investigation of the larger Darcy-scale heterogeneities that generate preferential flow patterns at the soil profile, hillslope and field scales has been facilitated by hydro-geophysical measurement techniques that produce highly spatially and temporally resolved data. At larger regional and global scales, improved methods of data-mining and analyses of large datasets (machine learning) may help to parameterize models as well as lead to new insights into the relationships between soil susceptibility to preferential flow and site attributes (climate, land uses, soil types).

Fast interactive exploration of 4D MRI flow data

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Friman, O.; Schumann, C.; Bock, J.; Drexl, J.; Huellebrand, M.; Markl, M.; Peitgen, H.-O.

2011-03-01

1- or 2-directional MRI blood flow mapping sequences are an integral part of standard MR protocols for diagnosis and therapy control in heart diseases. Recent progress in rapid MRI has made it possible to acquire volumetric, 3-directional cine images in reasonable scan time. In addition to flow and velocity measurements relative to arbitrarily oriented image planes, the analysis of 3-dimensional trajectories enables the visualization of flow patterns, local features of flow trajectories or possible paths into specific regions. The anatomical and functional information allows for advanced hemodynamic analysis in different application areas like stroke risk assessment, congenital and acquired heart disease, aneurysms or abdominal collaterals and cranial blood flow. The complexity of the 4D MRI flow datasets and the flow related image analysis tasks makes the development of fast comprehensive data exploration software for advanced flow analysis a challenging task. Most existing tools address only individual aspects of the analysis pipeline such as pre-processing, quantification or visualization, or are difficult to use for clinicians. The goal of the presented work is to provide a software solution that supports the whole image analysis pipeline and enables data exploration with fast intuitive interaction and visualization methods. The implemented methods facilitate the segmentation and inspection of different vascular systems. Arbitrary 2- or 3-dimensional regions for quantitative analysis and particle tracing can be defined interactively. Synchronized views of animated 3D path lines, 2D velocity or flow overlays and flow curves offer a detailed insight into local hemodynamics. The application of the analysis pipeline is shown for 6 cases from clinical practice, illustrating the usefulness for different clinical questions. Initial user tests show that the software is intuitive to learn and even inexperienced users achieve good results within reasonable processing times.

Movement Pattern and Parameter Learning in Children: Effects of Feedback Frequency

ERIC Educational Resources Information Center

Goh, Hui-Ting; Kantak, Shailesh S.; Sullivan, Katherine J.

2012-01-01

Reduced feedback during practice has been shown to be detrimental to movement accuracy in children but not in young adults. We hypothesized that the reduced accuracy is attributable to reduced movement parameter learning, but not pattern learning, in children. A rapid arm movement task that required the acquisition of a motor pattern scaled to…

Eye Gaze and Production Accuracy Predict English L2 Speakers' Morphosyntactic Learning

ERIC Educational Resources Information Center

McDonough, Kim; Trofimovich, Pavel; Dao, Phung; Dio, Alexandre

2017-01-01

This study investigated the relationship between second language (L2) speakers' success in learning a new morphosyntactic pattern and characteristics of one-on-one learning activities, including opportunities to comprehend and produce the target pattern, receive feedback from an interlocutor, and attend to the meaning of the pattern through self-…

Effects of refraction by means flow velocity gradients on the standing wave pattern in three-dimensional, rectangular waveguides

NASA Technical Reports Server (NTRS)

Hersh, A. S.

1979-01-01

The influence of a mean vortical flow on the connection between the standing wave pattern in a rectangular three dimensional waveguide and the corresponding duct axial impedance was determined analytically. The solution was derived using a perturbation scheme valid for low mean flow Mach numbers and plane wave sound frequencies. The results show that deviations of the standing wave pattern due to refraction by the mean flow gradients are small.

Optic flow improves adaptability of spatiotemporal characteristics during split-belt locomotor adaptation with tactile stimulation

PubMed Central

Anthony Eikema, Diderik Jan A.; Chien, Jung Hung; Stergiou, Nicholas; Myers, Sara A.; Scott-Pandorf, Melissa M.; Bloomberg, Jacob J.; Mukherjee, Mukul

2015-01-01

Human locomotor adaptation requires feedback and feed-forward control processes to maintain an appropriate walking pattern. Adaptation may require the use of visual and proprioceptive input to decode altered movement dynamics and generate an appropriate response. After a person transfers from an extreme sensory environment and back, as astronauts do when they return from spaceflight, the prolonged period required for re-adaptation can pose a significant burden. In our previous paper, we showed that plantar tactile vibration during a split-belt adaptation task did not interfere with the treadmill adaptation however, larger overground transfer effects with a slower decay resulted. Such effects, in the absence of visual feedback (of motion) and perturbation of tactile feedback, is believed to be due to a higher proprioceptive gain because, in the absence of relevant external dynamic cues such as optic flow, reliance on body-based cues is enhanced during gait tasks through multisensory integration. In this study we therefore investigated the effect of optic flow on tactile stimulated split-belt adaptation as a paradigm to facilitate the sensorimotor adaptation process. Twenty healthy young adults, separated into two matched groups, participated in the study. All participants performed an overground walking trial followed by a split-belt treadmill adaptation protocol. The tactile group (TC) received vibratory plantar tactile stimulation only, whereas the virtual reality and tactile group (VRT) received an additional concurrent visual stimulation: a moving virtual corridor, inducing perceived self-motion. A post-treadmill overground trial was performed to determine adaptation transfer. Interlimb coordination of spatiotemporal and kinetic variables was quantified using symmetry indices, and analyzed using repeated-measures ANOVA. Marked changes of step length characteristics were observed in both groups during split-belt adaptation. Stance and swing time symmetry were similar in the two groups, suggesting that temporal parameters are not modified by optic flow. However, whereas the TC group displayed significant stance time asymmetries during the post-treadmill session, such aftereffects were absent in the VRT group. The results indicated that the enhanced transfer resulting from exposure to plantar cutaneous vibration during adaptation was alleviated by optic flow information. The presence of visual self-motion information may have reduced proprioceptive gain during learning. Thus, during overground walking, the learned proprioceptive split-belt pattern is more rapidly overridden by visual input due to its increased relative gain. The results suggest that when visual stimulation is provided during adaptive training, the system acquires the novel movement dynamics while maintaining the ability to flexibly adapt to different environments. PMID:26525712

Study of two-phase flow in helical and spiral coils

NASA Technical Reports Server (NTRS)

Keshock, Edward G.; Yan, AN; Omrani, Adel

1990-01-01

The principal purposes of the present study were to: (1) observe and develop a fundamental understanding of the flow regimes and their transitions occurring in helical and spiral coils; and (2) obtain pressure drop measurements of such flows, and, if possible, develop a method for predicting pressure drop in these flow geometries. Elaborating upon the above, the general intent is to develop criteria (preferably generalized) for establishing the nature of the flow dynamics (e.g. flow patterns) and the magnitude of the pressure drop in such configurations over a range of flow rates and fluid properties. Additionally, the visualization and identification of flow patterns were a fundamental objective of the study. From a practical standpoint, the conditions under which an annular flow pattern exists is of particular practical importance. In the possible practical applications which would implement these geometries, the working fluids are likely to be refrigerant fluids. In the present study the working fluids were an air-water mixture, and refrigerant 113 (R-113). In order to obtain records of flow patterns and their transitions, video photography was employed extensively. Pressure drop measurements were made using pressure differential transducers connected across pressure taps in lines immediately preceding and following the various test sections.

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Development of a Countermeasure to Enhance Postflight Locomotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, Jacob J.

2006-01-01

Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. We have previously confirmed that subjects participating in adaptive generalization training programs using a variety of visuomotor distortions can enhance their ability to adapt to a novel sensorimotor environment. Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. Our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. Our laboratory is currently developing adaptive generalization training procedures and the associated flight hardware to implement such a training program during regular inflight treadmill operations. A visual display system will provide variation in visual flow patterns during treadmill exercise. Crewmembers will be exposed to a virtual scene that can translate and rotate in six-degrees-of freedom during their regular treadmill exercise period. Associated ground based studies are focused on determining optimal combinations of sensory manipulations (visual flow, body loading and support surface variation) and training schedules that will produce the greatest potential for adaptive flexibility in gait function during exposure to challenging and novel environments. An overview of our progress in these areas will be discussed during the presentation.

Characteristics of Evaporator with a Lipuid-Vapor Separator

NASA Astrophysics Data System (ADS)

Ikeguchi, Masaki; Tanaka, Naoki; Yumikura, Tsuneo

Flow pattern of refrigerant in a heat exchanger tube changes depending on vapor quality, tube diameter, refrigerant flow rate and refrigerant properties. High flow rate causes mist flow where the quality is from 0.8 to 1.0. 1n this flow pattern, the liquid film detaches from the tube wall so that the heat flow is intervened. The heat transfer coefficient generally increases with the flow rate. But the pressure drop of refrigerant flow simultaneously increases and the region of the mist flow enlarges. In order to reduce the pressure drop and suppress the mist flow, we have developped a small liquid-vapor separator that removes the vapor from the evaporating refrigerant flow. This separator is equipped in the middle of the evaporator where the flow pattern is annular. The experiments to evaluate the effect of this separator were carried out and the following conclutions were obtained. (1) Average heat transfer coefficient increases by 30-60 %. (2) Pressure drop reduces by 20-30 %. (3) Cooling Capacity increases by 2-9 %.

Constrained paths based on the Farey sequence in learning to juggle.

PubMed

Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji

2015-12-01

In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

Transport in Physical Space: The Example of Pedestrians, Cars, and Molecular Motors

NASA Astrophysics Data System (ADS)

Appert-Rolland, Cécile; Klein, Sarah; Ebbinghaus, Maximilian; Santen, Ludger

Transport systems in physical space exhibit various phenomena which may have some counterparts in socio- or econo-systems. We review here several of them. In highway vehicular traffic, the introduction of a reaction time leads to metastability and hysteresis. Pattern formation occurs in pedestrian flows. At a microscopic scale, we can learn from molecular pedestrians that transporting an object by opposite teams can be more efficient in a crowded environment and allow for an easy control of the system. Besides, we will show that the interplay between transport and the dynamics of the underlying network can sometimes lead to positive effects in terms of efficiency of transport.

Flow Patterns in the Jugular Veins of Pulsatile Tinnitus Patients

PubMed Central

Kao, Evan; Kefayati, Sarah; Amans, Matthew R.; Faraji, Farshid; Ballweber, Megan; Halbach, Van; Saloner, David

2017-01-01

Pulsatile Tinnitus (PT) is a pulse-synchronous sound heard in the absence of an external source. PT is often related to abnormal flow in vascular structures near the cochlea. One vascular territory implicated in PT is the internal jugular vein (IJV). Using computational fluid dynamics (CFD) based on patient-specific Magnetic Resonance Imaging (MRI), we investigated the flow within the IJV of seven subjects, four symptomatic and three asymptomatic of PT. We found that there were two extreme anatomic types classified by the shape and position of the jugular bulbs: elevated and rounded. PT patients had elevated jugular bulbs that led to a distinctive helical flow pattern within the proximal internal jugular vein. Asymptomatic subjects generally had rounded jugular bulbs that neatly redirected flow from the sigmoid sinus directly into the jugular vein. These two flow patterns were quantified by calculating the length-averaged streamline curvature of the flow within the proximal jugular vein: 130.3 ± 8.1 m-1 for geometries with rounded bulbs, 260.7 ± 29.4 m-1 for those with elevated bulbs (P < 0.005). Our results suggest that variations in the jugular bulb geometry lead to distinct flow patterns that are linked to PT, but further investigation is needed to determine if the vortex pattern is causal to sound generation. PMID:28057349

Flow Theory and GIS: Is There a Connection for Learning?

ERIC Educational Resources Information Center

Smith, Janet S.

2005-01-01

This paper examines how Geographic Information Systems (GIS) can potentially capture a student's imagination, facilitate active learning, and create a state of "flow" in geography classrooms. The paper is organised in four sections. First, the author provides a condensed overview to the major tenets of "FlowTheory." Second, a short discussion…

The effects of academic literacy instruction on engagement and conceptual understanding of biology of ninth-grade students

NASA Astrophysics Data System (ADS)

Larson, Susan C.

Academic language, discourse, vocabulary, motivation, and comprehension of complex texts and concepts are keys to learning subject-area content. The need for a disciplinary literacy approach in high school classrooms accelerates as students become increasing disengaged in school and as content complexity increases. In the present quasi-experimental mixed-method study, a ninth-grade biology unit was designed with an emphasis on promoting academic literacy skills, discourse, meaningful constructivist learning, interest development, and positive learning experiences in order to learn science content. Quantitative and qualitative analyses on a variety of measures completed by 222 students in two high schools revealed that those who received academic literacy instruction in science class performed at significantly higher levels of conceptual understanding of biology content, academic language and vocabulary use, reasoned thought, engagement, and quality of learning experience than control-group students receiving traditionally-organized instruction. Academic literacy was embedded into biology instruction to engage students in meaning-making discourses of science to promote learning. Academic literacy activities were organized according the phases of interest development to trigger and sustain interest and goal-oriented engagement throughout the unit. Specific methods included the Generative Vocabulary Matrix (GVM), scenario-based writing, and involvement in a variety of strategically-placed discourse activities to sustain or "boost" engagement for learning. Traditional instruction for the control group included teacher lecture, whole-group discussion, a conceptual organizer, and textbook reading. Theoretical foundations include flow theory, sociocultural learning theory, and interest theory. Qualitative data were obtained from field notes and participants' journals. Quantitative survey data were collected and analyzed using the Experience Sampling Method (ESM) to measure cognitive and emotional states, revealing patterns of engagement, quality of experience, and flow over the course of the instructional unit. Conceptual understanding was measured using the state persuasive writing rubric to analyze science essays in which students supported a claim with scientific evidence. The study contributes an Engagement Model of Academic Literacy for Learning (EngageALL), a Rubric for Academic Persuasive Writing (RAPW), a unique classification system for analyzing academic vocabulary, and suggestions for situated professional development around a research-based planning framework. A discussion addresses a new direction for future research that explores academic identity development.

Morphology-Patterned Anisotropic Wetting Surface for Fluid Control and Gas-Liquid Separation in Microfluidics.

PubMed

Wang, Shuli; Yu, Nianzuo; Wang, Tieqiang; Ge, Peng; Ye, Shunsheng; Xue, Peihong; Liu, Wendong; Shen, Huaizhong; Zhang, Junhu; Yang, Bai

2016-05-25

This article shows morphology-patterned stripes as a new platform for directing flow guidance of the fluid in microfluidic devices. Anisotropic (even unidirectional) spreading behavior due to anisotropic wetting of the underlying surface is observed after integrating morphology-patterned stripes with a Y-shaped microchannel. The anisotropic wetting flow of the fluid is influenced by the applied pressure, dimensions of the patterns, including the period and depth of the structure, and size of the channels. Fluids with different surface tensions show different flowing anisotropy in our microdevice. Moreover, the morphology-patterned surfaces could be used as a microvalve, and gas-water separation in the microchannel was realized using the unidirectional flow of water. Therefore, benefiting from their good performance and simple fabrication process, morphology-patterned surfaces are good candidates to be applied in controlling the fluid behavior in microfluidics.

Learning builds on learning: Infants' use of native language sound patterns to learn words

PubMed Central

Graf Estes, Katharine

2014-01-01

The present research investigated how infants apply prior knowledge of environmental regularities to support new learning. The experiments tested whether infants could exploit experience with native language (English) phonotactic patterns to facilitate associating sounds with meanings during word learning. Fourteen-month-olds heard fluent speech that contained cues for detecting target words; they were embedded in sequences that occur across word boundaries. A separate group heard the target words embedded without word boundary cues. Infants then participated in an object label-learning task. With the opportunity to use native language patterns to segment the target words, infants subsequently learned the labels. Without this experience, infants failed. Novice word learners can take advantage of early learning about sounds scaffold lexical development. PMID:24980741

Prediction of slug-to-annular flow pattern transition (STA) for reducing the risk of gas-lift instabilities and effective gas/liquid transport from low-pressure reservoirs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toma, P.R.; Vargas, E.; Kuru, E.

Flow-pattern instabilities have frequently been observed in both conventional gas-lifting and unloading operations of water and oil in low-pressure gas and coalbed reservoirs. This paper identifies the slug-to-annular flow-pattern transition (STA) during upward gas/liquid transportation as a potential cause of flow instability in these operations. It is recommended that the slug-flow pattern be used mainly to minimize the pressure drop and gas compression work associated with gas-lifting large volumes of oil and water. Conversely, the annular flow pattern should be used during the unloading operation to produce gas with relatively small amounts of water and condensate. New and efficient artificialmore » lifting strategies are required to transport the liquid out of the depleted gas or coalbed reservoir level to the surface. This paper presents held data and laboratory measurements supporting the hypothesis that STA significantly contributes to flow instabilities and should therefore be avoided in upward gas/liquid transportation operations. Laboratory high-speed measurements of flow-pressure components under a broad range of gas-injection rates including STA have also been included to illustrate the onset of large STA-related flow-pressure oscillations. The latter body of data provides important insights into gas deliquification mechanisms and identifies potential solutions for improved gas-lifting and unloading procedures. A comparison of laboratory data with existing STA models was performed first. Selected models were then numerically tested in field situations. Effective field strategies for avoiding STA occurrence in marginal and new (offshore) field applications (i.e.. through the use of a slug or annular flow pattern regimen from the bottomhole to wellhead levels) are discussed.« less

Blood flow patterns during incremental and steady-state aerobic exercise.

PubMed

Coovert, Daniel; Evans, LeVisa D; Jarrett, Steven; Lima, Carla; Lima, Natalia; Gurovich, Alvaro N

2017-05-30

Endothelial shear stress (ESS) is a physiological stimulus for vascular homeostasis, highly dependent on blood flow patterns. Exercise-induced ESS might be beneficial on vascular health. However, it is unclear what type of ESS aerobic exercise (AX) produces. The aims of this study are to characterize exercise-induced blood flow patterns during incremental and steady-state AX. We expect blood flow pattern during exercise will be intensity-dependent and bidirectional. Six college-aged students (2 males and 4 females) were recruited to perform 2 exercise tests on cycleergometer. First, an 8-12-min incremental test (Test 1) where oxygen uptake (VO2), heart rate (HR), blood pressure (BP), and blood lactate (La) were measured at rest and after each 2-min step. Then, at least 48-hr. after the first test, a 3-step steady state exercise test (Test 2) was performed measuring VO2, HR, BP, and La. The three steps were performed at the following exercise intensities according to La: 0-2 mmol/L, 2-4 mmol/L, and 4-6 mmol/L. During both tests, blood flow patterns were determined by high-definition ultrasound and Doppler on the brachial artery. These measurements allowed to determine blood flow velocities and directions during exercise. On Test 1 VO2, HR, BP, La, and antegrade blood flow velocity significantly increased in an intensity-dependent manner (repeated measures ANOVA, p<0.05). Retrograde blood flow velocity did not significantly change during Test 1. On Test 2 all the previous variables significantly increased in an intensity-dependent manner (repeated measures ANOVA, p<0.05). These results support the hypothesis that exercise induced ESS might be increased in an intensity-dependent way and blood flow patterns during incremental and steady-state exercises include both antegrade and retrograde blood flows.

Learning to Learn Differently

ERIC Educational Resources Information Center

Olsen, Trude Høgvold; Glad, Tone; Filstad, Cathrine

2018-01-01

Purpose: This paper aims to investigate whether the formal and informal learning patterns of community health-care nurses changed in the wake of a reform that altered their work by introducing new patient groups, and to explore whether conditions in the new workplaces facilitated or impeded shifts in learning patterns. Design/methodology/approach:…

Beyond Metrics? The Role of Hydrologic Baseline Archetypes in Environmental Water Management.

PubMed

Lane, Belize A; Sandoval-Solis, Samuel; Stein, Eric D; Yarnell, Sarah M; Pasternack, Gregory B; Dahlke, Helen E

2018-06-22

Balancing ecological and human water needs often requires characterizing key aspects of the natural flow regime and then predicting ecological response to flow alterations. Flow metrics are generally relied upon to characterize long-term average statistical properties of the natural flow regime (hydrologic baseline conditions). However, some key aspects of hydrologic baseline conditions may be better understood through more complete consideration of continuous patterns of daily, seasonal, and inter-annual variability than through summary metrics. Here we propose the additional use of high-resolution dimensionless archetypes of regional stream classes to improve understanding of baseline hydrologic conditions and inform regional environmental flows assessments. In an application to California, we describe the development and analysis of hydrologic baseline archetypes to characterize patterns of flow variability within and between stream classes. We then assess the utility of archetypes to provide context for common flow metrics and improve understanding of linkages between aquatic patterns and processes and their hydrologic controls. Results indicate that these archetypes may offer a distinct and complementary tool for researching mechanistic flow-ecology relationships, assessing regional patterns for streamflow management, or understanding impacts of changing climate.

Undirected learning styles and academic risk: Analysis of the impact of stress, strain and coping.

PubMed

Kimatian, Stephen; Lloyd, Sara; Berger, Jeffrey; Steiner, Lorraine; McKay, Robert; Schwengal, Deborah

2017-01-01

Learning style inventories used in conjunction with a measure of academic achievement consistently show an association of meaning directed learning patterns with academic success, but have failed to show a clear association of undirected learning styles with academic failure. Using survey methods with anesthesia residents, this study questioned whether additional assessment of factors related to stress, strain, and coping help to better define the association between undirected learning styles and academic risk. Pearson chi squared tests. 296 subjects were enrolled from eight institutions with 142 (48%) completing the study. American Board of Anesthesiologists In Training Examinations (ITE) percentiles (ITE%) were used as a measure of academic achievement. The Vermunt Inventory of Learning Styles (ILS) was used to identify four learning patterns and 20 strategies, and the Osipow Stress Inventory-Revised (OSI-R) was used as a measure of six scales of occupational stress, four of personal strain, and four coping resources. Two learning patterns had significant relationship with ITE scores. As seen in previous studies, Meaning Directed Learning was beneficial for academic achievement while Undirected Learning was the least beneficial. Higher scores on Meaning Directed Learning correlated positively with higher ITE scores while higher Undirected and lower Meaning Directed patterns related negatively to ITE%. OSI-R measures of stress, strain and coping indicated that residents with Undirected learning patterns had higher scores on three scales related to stress, and 4 related to strain, while displaying lower scores on two scales related to coping. Residents with higher Meaning Directed patterns scored lower on two scales of stress and two scales of strain, with higher scores on two scales for coping resources. Low Meaning Directed and high Undirected learning patterns correlated with lower ITE percentiles, higher scores for stress and strain, and lower coping resources. This association suggests that successful remediation of at-risk residents must address stress, strain and coping if long term academic improvement is expected. Further research to identify the value of stress, strain, and coping screening and education is warranted.

Four cells or two? Are four convection cells really necessary?

NASA Technical Reports Server (NTRS)

Reiff, P. H.; Heelis, R. A.

1994-01-01

This paper addresses the question whether a four-cell convection pattern in the polar cap ionosphere is required by observations, or whether the data are fully explainable by a (perhaps highly distorted) two-cell convection pattern. We present convection data from Atmosphere Explorer C, which, if only the flow component in the sunward-antisunward direction were measured, could be explained either as one of two possible distorted two-cell patterns or as a full four-cell pattern. However, neither of the distorted two-cell patterns that are consistent with the sunward-antisunward flow component can be made consistent with the dawn-dusk flow component over the entire spacecraft trajectory, without postulating a severe flow kink and extra field-aligned currents sunward of the spacecraft track. In addition, the zero potential point (which in a four-cell model would mark the division between the two reverse convection cells) also exactly corresponded to the location of the reversal of the east-west component in the flow, a feature predicted from the four-cell model but more difficult to explain in a distorted two-cell model. Because the pattern was repeated on two consecutive passes, time variations can probably be ruled out as a cause of the sunward flow. Between the two northern hemisphere dayside passes, a southern hemisphere nightside pass also showed a region of sunward flow in the polar cap. The fact that in this case the sunward flow was not confined to the dayside also favors a four-cell explanation.

PIV measurements in a compact return diffuser under multi-conditions

NASA Astrophysics Data System (ADS)

Zhou, L.; Lu, W. G.; Shi, W. D.

2013-12-01

Due to the complex three-dimensional geometries of impellers and diffusers, their design is a delicate and difficult task. Slight change could lead to significant changes in hydraulic performance and internal flow structure. Conversely, the grasp of the pump's internal flow pattern could benefit from pump design improvement. The internal flow fields in a compact return diffuser have been investigated experimentally under multi-conditions. A special Particle Image Velocimetry (PIV) test rig is designed, and the two-dimensional PIV measurements are successfully conducted in the diffuser mid-plane to capture the complex flow patterns. The analysis of the obtained results has been focused on the flow structure in diffuser, especially under part-load conditions. The vortex and recirculation flow patterns in diffuser are captured and analysed accordingly. Strong flow separation and back flow appeared at the part-load flow rates. Under the design and over-load conditions, the flow fields in diffuser are uniform, and the flow separation and back flow appear at the part-load flow rates, strong back flow is captured at one diffuser passage under 0.2Qdes.

Some observations of separated flow on finite wings

NASA Technical Reports Server (NTRS)

Winkelmann, A. E.; Ngo, H. T.; De Seife, R. C.

1982-01-01

Wind tunnel test results for aspects of flow over airfoils exhibiting single and multiple trailing edge stall 'mushroom' cells are reported. Rectangular wings with aspect ratios of 4.0 and 9.0 were tested at Reynolds numbers of 480,000 and 257,000, respectively. Surface flow patterns were visualized by means of a fluorescent oil flow technique, separated flow was observed with a tuft wand and a water probe, spanwise flow was studied with hot-wire anemometry, smoke flow and an Ar laser illuminated the centerplane flow, and photographs were made of the oil flow patterns. Swirl patterns on partially and fully stalled wings suggested vortex flow attachments in those regions, and a saddle point on the fully stalled AR=4.0 wing indicated a secondary vortex flow at the forward region of the separation bubble. The separation wake decayed downstream, while the tip vortex interacted with the separation bubble on the fully stalled wing. Three mushroom cells were observed on the AR=9.0 wing.

Patterns from drying drops.

PubMed

Sefiane, Khellil

2014-04-01

The objective of this review is to investigate different deposition patterns from dried droplets of a range of fluids: paints, polymers and biological fluids. This includes looking at mechanisms controlling the patterns and how they can be manipulated for use in certain applications such as medical diagnostics and nanotechnology. This review introduces the fundamental properties of droplets during evaporation. These include profile evolution (constant contact angle regime (CCAR) and constant radius regime (CRR)) and the internal flow (Marangoni and Capillary flow (Deegan et al. [22])). The understanding of these processes and the basic physics behind the phenomenon are crucial to the understanding of the factors influencing the deposition patterns. It concludes with the applications that each of these fluids can be used in and how the manipulation of the deposition pattern is useful. The most commonly seen pattern is the coffee-ring deposit which can be seen frequently in real life from tea/coffee stains and in water colour painting. This is caused by an outward flow known as capillary flow which carries suspended particles out to the edge of the wetted area. Other patterns that were found were uniform, central deposits and concentric rings which are caused by inward Marangoni flow. Complex biological fluids displayed an array of different patterns which can be used to diagnose patients. Copyright © 2013 Elsevier B.V. All rights reserved.

Patterns and Rates of Learning in Two Problem-Based Learning Courses Using Outcome Based Assessment and Elaboration Theory

ERIC Educational Resources Information Center

Kuruganti, Usha; Needham, Ted; Zundel, Pierre

2012-01-01

The concept of "practice makes perfect" was examined in this work in the context of effective learning. Specifically, we wanted to know how much practice was needed for students to demonstrate mastery of learning outcomes. Student learning patterns in two different university courses that use a similar education approach involving…

Understanding Individual Patterns of Learning: Implications for the Well-Being of Students

ERIC Educational Resources Information Center

O'Toole, Linda

2008-01-01

This article analyses the link between learning and well-being from the perspective that it is important to take into account the individual patterns of how young people learn and to encourage ways in which they can learn how they learn. Consideration is first given to recent insights and research in education and the cognitive and natural…

Controls on Thermal Discharge in Yellowstone NAtional Park, Wyoming

NASA Astrophysics Data System (ADS)

Mohrmann, Jacob Steven

2007-10-01

Significant fluctuations in discharge occur in hot springs in Yellowstone National Park on a seasonal to decadal scale (Ingebritsen et al., 2001) and an hourly scale (Vitale, 2002). The purpose of this study was to determine the interval of the fluctuations in discharge and to explain what causes those discharge patterns in three thermally influenced streams in Yellowstone National Park. By monitoring flow in these streams, whose primary source of input is thermal discharge, we were able to find several significant patterns of discharge fluctuations. Patterns were found by using two techniques of spectral analysis. The spectral analyses completed involved using the program "R" as well as Microsoft Excel, both of which use Fourier transforms. The Fourier transform is a linear operator that identifies frequencies in the original function. Stream flow data were collected using a FloDar open channel flow monitor. The flow meter collected data at15-minute intervals at White Creek and Rabbit Creek for a period of approximately two weeks each during the Fall. Flow data were also used from 15-minute data interval from a USGS gaging station at Tantalus Creek. Patterns of discharge fluctuation were found in each stream. By comparing spectral analysis results of flow data with spectral analysis of published tide data and barometric pressure data, connections were drawn between fluctuations in tidal and barometric-pressure patterns and flow patterns. Also, visual comparisons used to identify potential correspondence with earthquakes and precipitation events. At Tantalus Creek, patterns were affected only by barometric pressure changes. At White Creek, one pattern was attributed to barometric pressure fluctuations, and another pattern was found that could be associated with earth-tide forces. At Rabbit Creek, these patterns were absent. A pattern at 8.55 hours, which could not be attributed to barometric pressure or earth tide forces, was found at Rabbit and White Creeks. The 8.55 hour pattern in discharge found at both Rabbit and White Creeks may suggest a physical link between the sites, which are close (2.5 km). The time pattern could be a result of a shared hydrothermal aquifer, convectively heating and discharging at both streams. However, the common time pattern could also be the result of independent factors, which coincidentally caused a similar time pattern.

Patterning flows and polymers

NASA Astrophysics Data System (ADS)

Stroock, Abraham Duncan

This thesis presents the use of patterned surfaces for controlling fluid dynamics on a sub-millimeter scale, and for fabricating a new class of polymeric materials. In chapters 1--4, chemical and mechanical structures were used to control the form of flows of fluids in microchannels. This work was done in the context of the development of microfluidic technology for performing chemical tasks in portable, integrated devices. Chapter 1 reviews this work for an audience of chemists who are potential users of these techniques in the development of micro-analytical and micro-synthetic devices. Appendix 1 contains a more general review of microfluidics. Chapter 2 presents experimental results on the use of patterned surface charge density to create new electroosmotic (EO) flows in microchannels; the chapter includes a successful model of the observed flows. In Chapter 3, patterns of topography on the wall of a microchannel were used to generate recirculation in pressure-driven flows. The design and characterization of an efficient mixer based on these flows is presented. A theoretical treatment of these flows is given in Appendix 2. The experimental methods used for the work with both EO and pressure-driven flows are presented in Chapter 4. In Chapter 5, a pattern of asymmetrical grooves in a heated plate was used to perturb Marangoni-Benard (M-B) convection, a dynamic system that spontaneously forms patterned flows. The interaction of the imposed pattern and the inherent pattern of the M-B convection led to a net flow in the plane of convecting layer of fluid. The direction of this flow depended on the orientation of the asymmetrical grooves, the temperature difference across the layer, and the thickness of the layer. A phenomenological model is presented to explain this ratchet effect in which local recirculation was coupled into a global flow. In Chapter 6, surfaces patterned by microcontact printing were used as a workbench on which to build molecularly thin polymer films of well-defined lateral size and shape for subsequent release into solution; the released structures are referred to as two-dimensional (2D) polymers. This type of structure has been a theoretical curiosity and an experimental challenge for several decades. The key element of this method was the use of hydrophobic interactions as a "switchable" adhesive that attached the films to the surface during growth in water and then allowed the completed films to be removed in air. The structure and chemical composition of the films was characterized.

Prefrontal hemodynamic responses and the degree of flow experience among occupational therapy students during their performance of a cognitive task.

PubMed

Hirao, Kazuki

2014-01-01

Although flow experience is positively associated with motivation to learn, the biological basis of flow experience is poorly understood. Accumulation of evidence on the underlying brain mechanisms related to flow is necessary for a deeper understanding of the motivation to learn. The purpose of this study is to investigate the relationship between flow experience and brain function using near-infrared spectroscopy (NIRS) during the performance of a cognitive task. Sixty right-handed occupational therapy (OT) students participated in this study. These students performed a verbal fluency test (VFT) while 2-channel NIRS was used to assess changes in oxygenated hemoglobin concentration (oxygenated hemoglobin [oxy-Hb]) in the prefrontal cortex. Soon after that, the OT students answered the flow questionnaire (FQ) to assess the degree of flow experience during the VFT. Average oxy-Hb in the prefrontal cortex had a significant negative correlation with the satisfaction scores on the FQ. Satisfaction during the flow experience correlated with prefrontal hemodynamic suppression. This finding may assist in understanding motivation to learn and related flow experience.

Direct visualization of hemolymph flow in the heart of a grasshopper (Schistocerca americana)

PubMed Central

Lee, Wah-Keat; Socha, John J

2009-01-01

Background Hemolymph flow patterns in opaque insects have never been directly visualized due to the lack of an appropriate imaging technique. The required spatial and temporal resolutions, together with the lack of contrast between the hemolymph and the surrounding soft tissue, are major challenges. Previously, indirect techniques have been used to infer insect heart motion and hemolymph flow, but such methods fail to reveal fine-scale kinematics of heartbeat and details of intra-heart flow patterns. Results With the use of microbubbles as high contrast tracer particles, we directly visualized hemolymph flow in a grasshopper (Schistocerca americana) using synchrotron x-ray phase-contrast imaging. In-vivo intra-heart flow patterns and the relationship between respiratory (tracheae and air sacs) and circulatory (heart) systems were directly observed for the first time. Conclusion Synchrotron x-ray phase contrast imaging is the only generally applicable technique that has the necessary spatial, temporal resolutions and sensitivity to directly visualize heart dynamics and flow patterns inside opaque animals. This technique has the potential to illuminate many long-standing questions regarding small animal circulation, encompassing topics such as retrograde heart flow in some insects and the development of flow in embryonic vertebrates. PMID:19272159

Learning with imperfectly labeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Learning new meanings for known words: Biphasic effects of prior knowledge.

PubMed

Fang, Xiaoping; Perfetti, Charles; Stafura, Joseph

2017-01-01

In acquiring word meanings, learners are often confronted by a single word form that is mapped to two or more meanings. For example, long after how to roller-"skate", one may learn that "skate" is also a kind of fish. Such learning of new meanings for familiar words involves two potentially contrasting processes, relative to new form-new meaning learning: 1) Form-based familiarity may facilitate learning a new meaning, and 2) meaning-based interference may inhibit learning a new meaning. We examined these two processes by having native English speakers learn new, unrelated meanings for familiar (high frequency) and less familiar (low frequency) English words, as well as for unfamiliar (novel or pseudo-) words. Tracking learning with cued-recall tasks at several points during learning revealed a biphasic pattern: higher learning rates and greater learning efficiency for familiar words relative to novel words early in learning and a reversal of this pattern later in learning. Following learning, interference from original meanings for familiar words was detected in a semantic relatedness judgment task. Additionally, lexical access to familiar words with new meanings became faster compared to their exposure controls, but no such effect occurred for less familiar words. Overall, the results suggest a biphasic pattern of facilitating and interfering processes: Familiar word forms facilitate learning earlier, while interference from original meanings becomes more influential later. This biphasic pattern reflects the co-activation of new and old meanings during learning, a process that may play a role in lexicalization of new meanings.

Combined effects of complex magnetic fields and agmatine for contextual fear learning deficits in rats.

PubMed

McKay, B E; Persinger, M A

2003-04-18

Acute post-training exposures to weak intensity theta-burst stimulation (TBS) patterned complex magnetic fields attenuated the magnitude of conditioned fear learning for contextual stimuli. A similar learning impairment was evoked in a linear and dose-dependent manner by pre-conditioning injections of the polyamine agmatine. The present study examined the hypothesis that whole-body applications of the TBS complex magnetic field pattern when co-administered with systemic agmatine treatment may combine to evoke impairments in contextual fear learning. Within minutes of 4 mg/kg agmatine injections, male Wistar rats were fear conditioned to contextual stimuli and immediately exposed for 30 min to the TBS patterned complex magnetic field or to sham conditions. TBS patterned complex magnetic field treatment was found to linearly summate with the contextual fear learning impairment evoked by agmatine treatment alone. Furthermore, we report for sham-treated rats, but not rats exposed to the synthetic magnetic field pattern, that the magnitude of learned fear decreased and the amount of variability in learning increased, as the K-index (a measure of change in intensity of the time-varying ambient geomagnetic field) increased during the 3-hr intervals over which conditioning and testing sessions were conducted.

Experimental investigation on flow patterns of RP-3 kerosene under sub-critical and supercritical pressures

NASA Astrophysics Data System (ADS)

Wang, Ning; Zhou, Jin; Pan, Yu; Wang, Hui

2014-02-01

Active cooling with endothermic hydrocarbon fuel is proved to be one of the most promising approaches to solve the thermal problem for hypersonic aircraft such as scramjet. The flow patterns of two-phase flow inside the cooling channels have a great influence on the heat transfer characteristics. In this study, phase transition processes of RP-3 kerosene flowing inside a square quartz-glass tube were experimentally investigated. Three distinct phase transition phenomena (liquid-gas two phase flow under sub-critical pressures, critical opalescence under critical pressure, and corrugation under supercritical pressures) were identified. The conventional flow patterns of liquid-gas two phase flow, namely bubble flow, slug flow, churn flow and annular flow are observed under sub-critical pressures. Dense bubble flow and dispersed flow are recognized when pressure is increased towards the critical pressure whilst slug flow, churn flow and annular flow disappear. Under critical pressure, the opalescence phenomenon is observed. Under supercritical pressures, no conventional phase transition characteristics, such as bubbles are observed. But some kind of corrugation appears when RP-3 transfers from liquid to supercritical. The refraction index variation caused by sharp density gradient near the critical temperature is thought to be responsible for this corrugation.

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

NASA Astrophysics Data System (ADS)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Integral Mindflow: A Process of Mindfulness-in-Flow to Enhance Individual and Organization Learning

ERIC Educational Resources Information Center

Cacioppe, Ron Lewis

2017-01-01

Purpose: This paper aims to examine the differences in mindfulness, meditation and flow and the conditions in which each occurs. It summarizes research that demonstrates positive benefits of these three for employee and organizational learning. While mindfulness focuses awareness on what is occurring in the moment, flow involves total immersion in…

Active Learning in Fluid Mechanics: Youtube Tube Flow and Puzzling Fluids Questions

ERIC Educational Resources Information Center

Hrenya, Christine M.

2011-01-01

Active-learning exercises appropriate for a course in undergraduate fluid mechanics are presented. The first exercise involves an experiment in gravity-driven tube flow, with small groups of students partaking in a contest to predict the experimental flow rates using the mechanical energy balance. The second exercise takes the form of an…

The Role of Statistical Learning and Working Memory in L2 Speakers' Pattern Learning

ERIC Educational Resources Information Center

McDonough, Kim; Trofimovich, Pavel

2016-01-01

This study investigated whether second language (L2) speakers' morphosyntactic pattern learning was predicted by their statistical learning and working memory abilities. Across three experiments, Thai English as a Foreign Language (EFL) university students (N = 140) were exposed to either the transitive construction in Esperanto (e.g., "tauro…

Political Learning among Youth: Exploring Patterns of Students' First Political Awakening

ERIC Educational Resources Information Center

Solhaug, Trond; Kristensen, Niels Nørgaard

2013-01-01

This article focuses on students' first political learning and explores the research question, "What dynamic patterns of political learning can be explored among a sample of young, diverse Danish students' first political interests?" The authors use theories of learning in their analytical approach to students' stories. A group of 10…

Poorer Phonetic Perceivers Show Greater Benefit in Phonetic-Phonological Speech Learning

ERIC Educational Resources Information Center

Ingvalson, Erin M.; Barr, Allison M.; Wong, Patrick C. M.

2013-01-01

Purpose: Previous research has demonstrated that native English speakers can learn lexical tones in word context (pitch-to-word learning), to an extent. However, learning success depends on learners' pre-training sensitivity to pitch patterns. The aim of this study was to determine whether lexical pitch-pattern training given before lexical…

Learning Patterns as Criterion for Forming Work Groups in 3D Simulation Learning Environments

ERIC Educational Resources Information Center

Maria Cela-Ranilla, Jose; Molías, Luis Marqués; Cervera, Mercè Gisbert

2016-01-01

This study analyzes the relationship between the use of learning patterns as a grouping criterion to develop learning activities in the 3D simulation environment at University. Participants included 72 Spanish students from the Education and Marketing disciplines. Descriptive statistics and non-parametric tests were conducted. The process was…

Temporal Patterns and Dynamics of E-Learning Usage in Medical Education

ERIC Educational Resources Information Center

Panzarasa, Pietro; Kujawski, Bernard; Hammond, Edward J.; Roberts, C. Michael

2016-01-01

Despite the increasing popularity of e-learning systems across a variety of educational programmes, there is relatively little understanding of how students and trainees distribute their learning efforts over time. This study aimed to analyse the usage patterns of an e-learning resource designed to support specialty training. Data were collected…

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun

2012-01-01

This mixed methods study examined the flow experience of 5th graders in the CRYSTAL ISLAND game-based science learning environment. Participants were 73 5th graders from a suburban public school in the southeastern US. Quantitative data about students' science content learning and attitudes towards science was collected via pre-and post surveys.…

A Flow Theory Perspective on Learner Motivation and Behavior in Distance Education

ERIC Educational Resources Information Center

Liao, Li-Fen

2006-01-01

Motivating learners to continue to study and enjoy learning is one of the critical factors in distance education. Flow theory is a useful framework for studying the individual experience of learning through using computers. In this study, I examine students' emotional and cognitive responses to distance learning systems by constructing two models…

Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture.

PubMed

Corbacho, Fernando; Nishikawa, Kiisa C; Weerasuriya, Ananda; Liaw, Jim-Shih; Arbib, Michael A

2005-12-01

A motor action often involves the coordination of several motor synergies and requires flexible adjustment of the ongoing execution based on feedback signals. To elucidate the neural mechanisms underlying the construction and selection of motor synergies, we study prey-capture in anurans. Experimental data demonstrate the intricate interaction between different motor synergies, including the interplay of their afferent feedback signals (Weerasuriya 1991; Anderson and Nishikawa 1996). Such data provide insights for the general issues concerning two-way information flow between sensory centers, motor circuits and periphery in motor coordination. We show how different afferent feedback signals about the status of the different components of the motor apparatus play a critical role in motor control as well as in learning. This paper, along with its companion paper, extend the model by Liaw et al. (1994) by integrating a number of different motor pattern generators, different types of afferent feedback, as well as the corresponding control structure within an adaptive framework we call Schema-Based Learning. We develop a model of the different MPGs involved in prey-catching as a vehicle to investigate the following questions: What are the characteristic features of the activity of a single muscle? How can these features be controlled by the premotor circuit? What are the strategies employed to generate and synchronize motor synergies? What is the role of afferent feedback in shaping the activity of a MPG? How can several MPGs share the same underlying circuitry and yet give rise to different motor patterns under different input conditions? In the companion paper we also extend the model by incorporating learning components that give rise to more flexible, adaptable and robust behaviors. To show these aspects we incorporate studies on experiments on lesions and the learning processes that allow the animal to recover its proper functioning.

Polygon patterns on Europa

NASA Technical Reports Server (NTRS)

Smalley, I. J.

1981-01-01

The formation of polygon patterns in the development of crack networks in cooling basalt flows and similar contracting systems, and under natural conditions in an essentially unbounded basalt flow, are analyzed, and the characteristics of hexagonal and pentagonal patterns in isotropic stress fields are discussed.

Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model

PubMed Central

Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.

2015-01-01

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997

Independent voluntary correction and savings in locomotor learning.

PubMed

Leech, Kristan A; Roemmich, Ryan T

2018-06-14

People can acquire new walking patterns in many different ways. For example, we can change our gait voluntarily in response to instruction or adapt by sensing our movement errors. Here we investigated how acquisition of a new walking pattern through simultaneous voluntary correction and adaptive learning affected the resulting motor memory of the learned pattern. We studied adaptation to split-belt treadmill walking with and without visual feedback of stepping patterns. As expected, visual feedback enabled faster acquisition of the new walking pattern. However, upon later re-exposure to the same split-belt perturbation, participants exhibited similar motor memories whether they had learned with or without visual feedback. Participants who received feedback did not re-engage the mechanism used to accelerate initial acquisition of the new walking pattern to similarly accelerate subsequent relearning. These findings reveal that voluntary correction neither benefits nor interferes with the ability to save a new walking pattern over time. © 2018. Published by The Company of Biologists Ltd.

What We Can Learn from the Data: A Multiple-Case Study Examining Behavior Patterns by Students with Different Characteristics in Using a Serious Game

ERIC Educational Resources Information Center

Liu, Min; Lee, Jaejin; Kang, Jina; Liu, Sa

2016-01-01

Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our…

Experiment of flow regime map and local condensing heat transfer coefficients inside three dimensional inner microfin tubes

NASA Astrophysics Data System (ADS)

Du, Yang; Xin, Ming Dao

1999-03-01

This paper developed a new type of three dimensional inner microfin tube. The experimental results of the flow patterns for the horizontal condensation inside these tubes are reported in the paper. The flow patterns for the horizontal condensation inside the new made tubes are divided into annular flow, stratified flow and intermittent flow within the test conditions. The experiments of the local heat transfer coefficients for the different flow patterns have been systematically carried out. The experiments of the local heat transfer coefficients changing with the vapor dryness fraction have also been carried out. As compared with the heat transfer coefficients of the two dimensional inner microfin tubes, those of the three dimensional inner microfin tubes increase 47-127% for the annular flow region, 38-183% for the stratified flow and 15-75% for the intermittent flow, respectively. The enhancement factor of the local heat transfer coefficients is from 1.8-6.9 for the vapor dryness fraction from 0.05 to 1.

Flow visualization methods for field test verification of CFD analysis of an open gloveport

DOE PAGES

Strons, Philip; Bailey, James L.

2017-01-01

Anemometer readings alone cannot provide a complete picture of air flow patterns at an open gloveport. Having a means to visualize air flow for field tests in general provides greater insight by indicating direction in addition to the magnitude of the air flow velocities in the region of interest. Furthermore, flow visualization is essential for Computational Fluid Dynamics (CFD) verification, where important modeling assumptions play a significant role in analyzing the chaotic nature of low-velocity air flow. A good example is shown Figure 1, where an unexpected vortex pattern occurred during a field test that could not have been measuredmore » relying only on anemometer readings. Here by, observing and measuring the patterns of the smoke flowing into the gloveport allowed the CFD model to be appropriately updated to match the actual flow velocities in both magnitude and direction.« less

Two-phase flow pattern measurements with a wire mesh sensor in a direct steam generating solar thermal collector

NASA Astrophysics Data System (ADS)

Berger, Michael; Mokhtar, Marwan; Zahler, Christian; Willert, Daniel; Neuhäuser, Anton; Schleicher, Eckhard

2017-06-01

At Industrial Solar's test facility in Freiburg (Germany), two phase flow patterns have been measured by using a wire mesh sensor from Helmholtz Zentrum Dresden-Rossendorf (HZDR). Main purpose of the measurements was to compare observed two-phase flow patterns with expected flow patterns from models. The two-phase flow pattern is important for the design of direct steam generating solar collectors. Vibrations should be avoided in the peripheral piping, and local dry-outs or large circumferential temperature gradients should be prevented in the absorber tubes. Therefore, the choice of design for operation conditions like mass flow and steam quality are an important step in the engineering process of such a project. Results of a measurement with the wire mesh sensor are the flow pattern and the plug or slug frequency at the given operating conditions. Under the assumption of the collector power, which can be assumed from previous measurements at the same collector and adaption with sun position and incidence angle modifier, also the slip can be evaluated for a wire mesh sensor measurement. Measurements have been performed at different mass flows and pressure levels. Transient behavior has been tested for flashing, change of mass flow, and sudden changes of irradiation (cloud simulation). This paper describes the measurements and the method of evaluation. Results are shown as extruded profiles in top view and in side view. Measurement and model are compared. The tests have been performed at low steam quality, because of the limits of the test facility. Conclusions and implications for possible future measurements at larger collectors are also presented in this paper.

Studies of Two-Phase Flow Dynamics and Heat Transfer at Reduced Gravity Conditions

NASA Technical Reports Server (NTRS)

Witte, Larry C.; Bousman, W. Scott; Fore, Larry B.

1996-01-01

The ability to predict gas-liquid flow patterns is crucial to the design and operation of two-phase flow systems in the microgravity environment. Flow pattern maps have been developed in this study which show the occurrence of flow patterns as a function of gas and liquid superficial velocities as well as tube diameter, liquid viscosity and surface tension. The results have demonstrated that the location of the bubble-slug transition is affected by the tube diameter for air-water systems and by surface tension, suggesting that turbulence-induced bubble fluctuations and coalescence mechanisms play a role in this transition. The location of the slug-annular transition on the flow pattern maps is largely unaffected by tube diameter, liquid viscosity or surface tension in the ranges tested. Void fraction-based transition criteria were developed which separate the flow patterns on the flow pattern maps with reasonable accuracy. Weber number transition criteria also show promise but further work is needed to improve these models. For annular gas-liquid flows of air-water and air- 50 percent glycerine under reduced gravity conditions, the pressure gradient agrees fairly well with a version of the Lockhart-Martinelli correlation but the measured film thickness deviates from published correlations at lower Reynolds numbers. Nusselt numbers, based on a film thickness obtained from standard normal-gravity correlations, follow the relation, Nu = A Re(sup n) Pr(exp l/3), but more experimental data in a reduced gravity environment are needed to increase the confidence in the estimated constants, A and n. In the slug flow regime, experimental pressure gradient does not correlate well with either the Lockhart-Martinelli or a homogeneous formulation, but does correlate nicely with a formulation based on a two-phase Reynolds number. Comparison with ground-based correlations implies that the heat transfer coefficients are lower at reduced gravity than at normal gravity under the same flow conditions. Nusselt numbers can be correlated in a fashion similar to Chu and Jones.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strons, Philip; Bailey, James L.

Anemometer readings alone cannot provide a complete picture of air flow patterns at an open gloveport. Having a means to visualize air flow for field tests in general provides greater insight by indicating direction in addition to the magnitude of the air flow velocities in the region of interest. Furthermore, flow visualization is essential for Computational Fluid Dynamics (CFD) verification, where important modeling assumptions play a significant role in analyzing the chaotic nature of low-velocity air flow. A good example is shown Figure 1, where an unexpected vortex pattern occurred during a field test that could not have been measuredmore » relying only on anemometer readings. Here by, observing and measuring the patterns of the smoke flowing into the gloveport allowed the CFD model to be appropriately updated to match the actual flow velocities in both magnitude and direction.« less

Complex magnetohydrodynamic low-Reynolds-number flows.

PubMed

Xiang, Yu; Bau, Haim H

2003-07-01

The interaction between electric currents and a magnetic field is used to produce body (Lorentz) forces in electrolyte solutions. By appropriate patterning of the electrodes, one can conveniently control the direction and magnitude of the electric currents and induce spatially and temporally complicated flow patterns. This capability is useful, not only for fundamental flow studies, but also for inducing fluid flow and stirring in minute devices in which the incorporation of moving components may be difficult. This paper focuses on a theoretical and experimental study of magnetohydrodynamic flows in a conduit with a rectangular cross section. The conduit is equipped with individually controlled electrodes uniformly spaced at a pitch L. The electrodes are aligned transversely to the conduit's axis. The entire device is subjected to a uniform magnetic field. The electrodes are divided into two groups A and C in such a way that there is an electrode of group C between any two electrodes of group A. We denote the various A and C electrodes with subscripts, i.e., A(i) and C(i), where i=0,+/-1,+/-2, .... When positive and negative potentials are, respectively, applied to the even and odd numbered A electrodes, opposing electric currents are induced on the right and left hand sides of each A electrode. These currents generate transverse forces that drive cellular convection in the conduit. We refer to the resulting flow pattern as A. When electrodes of group C are activated, a similar flow pattern results, albeit shifted in space. We refer to this flow pattern as C. By alternating periodically between patterns A and C, one induces Lagrangian chaos. Such chaotic advection may be beneficial for stirring fluids, particularly in microfluidic devices. Since the flow patterns A and C are shifted in space, they also provide a mechanism for Lagrangian drift that allows net migration of passive tracers along the conduit's length.

Assessing Airflow Sensitivity to Healthy and Diseased Lung Conditions in a Computational Fluid Dynamics Model Validated In Vitro.

PubMed

Sul, Bora; Oppito, Zachary; Jayasekera, Shehan; Vanger, Brian; Zeller, Amy; Morris, Michael; Ruppert, Kai; Altes, Talissa; Rakesh, Vineet; Day, Steven; Robinson, Risa; Reifman, Jaques; Wallqvist, Anders

2018-05-01

Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry (PIV). The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy and one COPD) and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root-mean-square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates but markedly different for COPD (minimum R, 0.26; maximum Drms, ten times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contributes to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.

Imaging Electron Motion in a Few Layer MoS2 Device

NASA Astrophysics Data System (ADS)

Bhandari, S.; Wang, K.; Watanabe, K.; Taniguchi, T.; Kim, P.; Westervelt, R. M.

2017-06-01

Ultrathin sheets of MoS2 are a newly discovered 2D semiconductor that holds great promise for nanoelectronics. Understanding the pattern of current flow will be crucial for developing devices. In this talk, we present images of current flow in MoS2 obtained with a Scanned Probe Microscope (SPM) cooled to 4 K. We previously used this technique to image electron trajectories in GaAs/AlGaAs heterostructures and graphene. The charged SPM tip is held just above the sample surface, creating an image charge inside the device that scatters electrons. By measuring the change in resistance ΔR while the tip is raster scanned above the sample, an image of electron flow is obtained. We present images of electron flow in an MoS2 device patterned into a hall bar geometry. A three-layer MoS2 sheet is encased by two hBN layers, top and bottom, and patterned into a hall-bar with multilayer graphene contacts. An SPM image shows the current flow pattern from the wide contact at the end of the device for a Hall density n = 1.3×1012 cm-2. The SPM tip tends to block flow, increasing the resistance R. The pattern of flow was also imaged for a narrow side contact on the sample. At density n = 5.4×1011 cm-2; the pattern seen in the SPM image is similar to the wide contact. The ability to image electron flow promises to be very useful for the development of ultrathin devices from new 2D materials.

Visualization of flows in a motored rotary combustion engine using holographic interferometry

NASA Technical Reports Server (NTRS)

Hicks, Y. R.; Schock, H. J.; Craig, J. E.; Umstatter, H. L.; Lee, D. Y.

1986-01-01

The use of holographic interferometry to view the small- and large-scale flow field structures in the combustion chamber of a motored Wankel engine assembly is described. In order that the flow patterns of interest could be observed, small quantities of helium were injected with the intake air. Variation of the air flow patterns with engine speed, helium flow rate, and rotor position are described. The air flow at two locations within the combustion chamber was examined using this technique.

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media.

PubMed

Zhao, Jian; Cao, Nan; Wen, Zhen; Song, Yale; Lin, Yu-Ru; Collins, Christopher

2014-12-01

We present FluxFlow, an interactive visual analysis system for revealing and analyzing anomalous information spreading in social media. Everyday, millions of messages are created, commented, and shared by people on social media websites, such as Twitter and Facebook. This provides valuable data for researchers and practitioners in many application domains, such as marketing, to inform decision-making. Distilling valuable social signals from the huge crowd's messages, however, is challenging, due to the heterogeneous and dynamic crowd behaviors. The challenge is rooted in data analysts' capability of discerning the anomalous information behaviors, such as the spreading of rumors or misinformation, from the rest that are more conventional patterns, such as popular topics and newsworthy events, in a timely fashion. FluxFlow incorporates advanced machine learning algorithms to detect anomalies, and offers a set of novel visualization designs for presenting the detected threads for deeper analysis. We evaluated FluxFlow with real datasets containing the Twitter feeds captured during significant events such as Hurricane Sandy. Through quantitative measurements of the algorithmic performance and qualitative interviews with domain experts, the results show that the back-end anomaly detection model is effective in identifying anomalous retweeting threads, and its front-end interactive visualizations are intuitive and useful for analysts to discover insights in data and comprehend the underlying analytical model.

Network structure of subway passenger flows

NASA Astrophysics Data System (ADS)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

Flow-driven instabilities during pattern formation of Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

Gholami, A.; Steinbock, O.; Zykov, V.; Bodenschatz, E.

2015-06-01

The slime mold Dictyostelium discoideum is a well known model system for the study of biological pattern formation. In the natural environment, aggregating populations of starving Dictyostelium discoideum cells may experience fluid flows that can profoundly change the underlying wave generation process. Here we study the effect of advection on the pattern formation in a colony of homogeneously distributed Dictyostelium discoideum cells described by the standard Martiel-Goldbeter model. The external flow advects the signaling molecule cyclic adenosine monophosphate (cAMP) downstream, while the chemotactic cells attached to the solid substrate are not transported with the flow. The evolution of small perturbations in cAMP concentrations is studied analytically in the linear regime and by corresponding numerical simulations. We show that flow can significantly influence the dynamics of the system and lead to a flow-driven instability that initiate downstream traveling cAMP waves. We also show that boundary conditions have a significant effect on the observed patterns and can lead to a new kind of instability.

Doing ecohydrology backward: Inferring wetland flow and hydroperiod from landscape patterns

NASA Astrophysics Data System (ADS)

Acharya, Subodh; Kaplan, David A.; Jawitz, James W.; Cohen, Matthew J.

2017-07-01

Human alterations to hydrology have globally impacted wetland ecosystems. Preventing or reversing these impacts is a principal focus of restoration efforts. However, restoration effectiveness is often hampered by limited information on historical landscape properties and hydrologic regime. To help address this gap, we developed a novel statistical approach for inferring flows and inundation frequency (i.e., hydroperiod, HP) in wetlands where changes in spatial vegetation and geomorphic patterns have occurred due to hydrologic alteration. We developed an analytical expression for HP as a transformation of the landscape-scale stage-discharge relationship. We applied this model to the Everglades "ridge-slough" (RS) landscape, a patterned, lotic peatland in southern Florida that has been drastically degraded by compartmentalization, drainage, and flow diversions. The new method reliably estimated flow and HP for a range of RS landscape patterns. Crucially, ridge-patch anisotropy and elevation above sloughs were strong drivers of flow-HP relationships. Increasing ridge heights markedly increased flow required to achieve sufficient HP to support peat accretion. Indeed, ridge heights inferred from historical accounts would require boundary flows 3-4 times greater than today, which agrees with restoration flow estimates from more complex, spatially distributed models. While observed loss of patch anisotropy allows HP targets to be met with lower flows, such landscapes likely fail to support other ecological functions. This work helps inform restoration flows required to restore stable ridge-slough patterning and positive peat accretion in this degraded ecosystem, and, more broadly, provides tools for exploring interactions between landscape and hydrology in lotic wetlands and floodplains.

Seeing the Errors You Feel Enhances Locomotor Performance but Not Learning.

PubMed

Roemmich, Ryan T; Long, Andrew W; Bastian, Amy J

2016-10-24

In human motor learning, it is thought that the more information we have about our errors, the faster we learn. Here, we show that additional error information can lead to improved motor performance without any concomitant improvement in learning. We studied split-belt treadmill walking that drives people to learn a new gait pattern using sensory prediction errors detected by proprioceptive feedback. When we also provided visual error feedback, participants acquired the new walking pattern far more rapidly and showed accelerated restoration of the normal walking pattern during washout. However, when the visual error feedback was removed during either learning or washout, errors reappeared with performance immediately returning to the level expected based on proprioceptive learning alone. These findings support a model with two mechanisms: a dual-rate adaptation process that learns invariantly from sensory prediction error detected by proprioception and a visual-feedback-dependent process that monitors learning and corrects residual errors but shows no learning itself. We show that our voluntary correction model accurately predicted behavior in multiple situations where visual feedback was used to change acquisition of new walking patterns while the underlying learning was unaffected. The computational and behavioral framework proposed here suggests that parallel learning and error correction systems allow us to rapidly satisfy task demands without necessarily committing to learning, as the relative permanence of learning may be inappropriate or inefficient when facing environments that are liable to change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patterns in Clinical Students' Self-Regulated Learning Behavior: A Q-Methodology Study

ERIC Educational Resources Information Center

Berkhout, Joris J.; Teunissen, Pim W.; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P.; Jaarsma, Debbie A.

2017-01-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in…

An Examination into the Learning Pattern Preferences of Students in Special Education

ERIC Educational Resources Information Center

Thone, Jaime L.

2013-01-01

As educational professionals strive to help students become efficient and effective learners, they must assist in the development of student learning strategies and a greater understanding of the learning process. The purpose of this study was to analyze and compare the learning pattern preferences of middle and high school students in general…

Relationships between Hong Kong Students' Perceptions of the Learning Environment and Their Learning Patterns in Post-Secondary Education

ERIC Educational Resources Information Center

Law, Dennis C. S.; Meyer, Jan H. F.

2011-01-01

The present study aims to analyse the complex relationships between the relevant constructs of students' demographic background, perceptions, learning patterns and (proxy measures of) learning outcomes in order to delineate the possible direct, indirect, or spurious effects among them. The analytical methodology is substantively framed against the…

Magnetic fields and flows between 1 AU and 0.3 AU during the primary mission of HELIOS 1

NASA Technical Reports Server (NTRS)

Burlaga, L. F.; Ness, N. F.; Mariani, F.; Bavassano, B.; Villante, U.; Rosenbauer, H.; Schwenn, R.; Harvey, J.

1978-01-01

The recurrent flow and field patterns observed by HELIOS 1, and the relation between these patterns and coronal holes are discussed. Four types of recurrent patterns were observed: a large recurrent stream, a recurrent slow (quiet) flow, a rapidly evolving flow, and a recurrent compound stream. There recurrent streams were not stationary, for although the sources recurred at approximately the same longitudes on successive rotations, the shapes and latitudinal patterns changed from one rotation to the next. A type of magnetic field and plasma structure characterized by a low ion temperature and a high magnetic field intensity is described as well as the structures of stream boundaries between the sun at approximately 0.3 AU.

Incremental Implicit Learning of Bundles of Statistical Patterns

PubMed Central

Qian, Ting; Jaeger, T. Florian; Aslin, Richard N.

2016-01-01

Forming an accurate representation of a task environment often takes place incrementally as the information relevant to learning the representation only unfolds over time. This incremental nature of learning poses an important problem: it is usually unclear whether a sequence of stimuli consists of only a single pattern, or multiple patterns that are spliced together. In the former case, the learner can directly use each observed stimulus to continuously revise its representation of the task environment. In the latter case, however, the learner must first parse the sequence of stimuli into different bundles, so as to not conflate the multiple patterns. We created a video-game statistical learning paradigm and investigated 1) whether learners without prior knowledge of the existence of multiple “stimulus bundles” — subsequences of stimuli that define locally coherent statistical patterns — could detect their presence in the input, and 2) whether learners are capable of constructing a rich representation that encodes the various statistical patterns associated with bundles. By comparing human learning behavior to the predictions of three computational models, we find evidence that learners can handle both tasks successfully. In addition, we discuss the underlying reasons for why the learning of stimulus bundles occurs even when such behavior may seem irrational. PMID:27639552

Results of oil flow visualization tests of an 0.010-scale model (52-OT) of the space shuttle orbiter-tank mated and orbiter configurations in the AEDC VKF tunnel B (IA17B)

NASA Technical Reports Server (NTRS)

Daileda, J. J.

1975-01-01

An 0.010-scale model of the space shuttle (orbiter-tank mated and orbiter configurations) was tested in the AEDC VKF Tunnel B to investigate aerodynamic flow patterns. The tests utilized oil flow techniques to visualize the flow patterns. Tunnel free stream Mach number was 7.95 and nominal unit Reynolds number was 3.7 million per foot. Model angle of attack was varied from -5 deg through 10 deg and angle of sideslip was 0 deg and 2 deg. Photographs of resulting oil flow patterns are presented.

The Effects of Game Strategy and Preference-Matching on Flow Experience and Programming Performance in Game-Based Learning

ERIC Educational Resources Information Center

Wang, Li-Chun; Chen, Ming-Puu

2010-01-01

Learning to program is difficult for novices, even for those undergraduates who have majored in computer science. The study described in this paper has investigated the effects of game strategy and preference-matching on novice learners' flow experience and performance in learning to program using an experiential gaming activity. One hundred and…

Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder

PubMed Central

Mercado, Eduardo; Church, Barbara A.; Coutinho, Mariana V. C.; Dovgopoly, Alexander; Lopata, Christopher J.; Toomey, Jennifer A.; Thomeer, Marcus L.

2015-01-01

Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets. PMID:26157368

Effect of aorto-iliac bifurcation and iliac stenosis on flow dynamics in an abdominal aortic aneurysm

NASA Astrophysics Data System (ADS)

Patel, Shivam; Usmani, Abdullah Y.; Muralidhar, K.

2017-06-01

Physiological flows in rigid diseased arterial flow phantoms emulating an abdominal aortic aneurysm (AAA) under rest conditions with aorto-iliac bifurcation and iliac stenosis are examined in vitro through 2D PIV measurements. Flow characteristics are first established in the model resembling a symmetric AAA with a straight outlet tube. The influence of aorto-iliac bifurcation and iliac stenosis on AAA flow dynamics is then explored through a comparison of the nature of flow patterns, vorticity evolution, vortex core trajectory and hemodynamic factors against the reference configuration. Specifically, wall shear stress and oscillatory shear index in the bulge portion of the models are of interest. The results of this investigation indicate overall phenomenological similarity in AAA flow patterns across the models. The pattern is characterized by a central jet and wall-bounded vortices whose strength increases during the deceleration phase as it moves forward. The central jet impacts the wall of AAA at its distal end. In the presence of an aorto-iliac bifurcation as well as iliac stenosis, the flow patterns show diminished strength, expanse and speed of propagation of the primary vortices. The positions of the instantaneous vortex cores, determined using the Q-function, correlate with flow separation in the bulge, flow resistance due to a bifurcation, and the break in symmetry introduced by a stenosis in one of the legs of the model. Time-averaged WSS in a healthy aorta is around 0.70 N m-2 and is lowered to the range ±0.2 N m-2 in the presence of the downstream bifurcation with a stenosed common iliac artery. The consequence of changes in the flow pattern within the aneurysm on disease progression is discussed.

Flow Pattern Phenomena in Two-Phase Flow in Microchannels

NASA Astrophysics Data System (ADS)

Keska, Jerry K.; Simon, William E.

2004-02-01

Space transportation systems require high-performance thermal protection and fluid management techniques for systems ranging from cryogenic fluid management devices to primary structures and propulsion systems exposed to extremely high temperatures, as well as for other space systems such as cooling or environment control for advanced space suits and integrated circuits. Although considerable developmental effort is being expended to bring potentially applicable technologies to a readiness level for practical use, new and innovative methods are still needed. One such method is the concept of Advanced Micro Cooling Modules (AMCMs), which are essentially compact two-phase heat exchangers constructed of microchannels and designed to remove large amounts of heat rapidly from critical systems by incorporating phase transition. The development of AMCMs requires fundamental technological advancement in many areas, including: (1) development of measurement methods/systems for flow-pattern measurement/identification for two-phase mixtures in microchannels; (2) development of a phenomenological model for two-phase flow which includes the quantitative measure of flow patterns; and (3) database development for multiphase heat transfer/fluid dynamics flows in microchannels. This paper focuses on the results of experimental research in the phenomena of two-phase flow in microchannels. The work encompasses both an experimental and an analytical approach to incorporating flow patterns for air-water mixtures flowing in a microchannel, which are necessary tools for the optimal design of AMCMs. Specifically, the following topics are addressed: (1) design and construction of a sensitive test system for two-phase flow in microchannels, one which measures ac and dc components of in-situ physical mixture parameters including spatial concentration using concomitant methods; (2) data acquisition and analysis in the amplitude, time, and frequency domains; and (3) analysis of results including evaluation of data acquisition techniques and their validity for application in flow pattern determination.

Avoid cruising on the uroflowmeter: evaluation of cruising artifact on spinning disc flowmeters in an experimental setup.

PubMed

Addla, Sanjai Kumar; Marri, Rajender Reddy; Daayana, Sai Lakshmi; Irwin, Paul

2010-09-01

The aim of our study was to access the variability of maximum flow rate (Q(max)), average flow rate (Q(av)) and flow pattern while varying the point of impact of flow on the flowmeter. Water was delivered through a motorised tube holder in a standardised experimental set up. Flow was directed in 4 different directions on the funnel; 1) Periphery, 2) Base, 3) Centre and, 4) in a cruising motion from the periphery of the funnel to the centre and back again. The variation in the Q(max), Q(av) and the flow pattern were studied at 4 different flow rates. The variables recorded when the flow was directed at the centre of the funnel was taken as baseline. There was a significant difference in the Q(max) and Q(av)when the point of impact was at the periphery or in a cruising motion compared to the centre. The difference was more marked with cruising motion with a characteristic flow pattern. The maximum percentage difference in Q(av) was 4.1%, whereas the difference in Q(max) was higher at 16.6% on comparing crusing motion with the values from the centre. We have demonstrated a significant variation in Q(max), Q(av) and flow pattern with change in the point of impact on the flowmeter. Though the changes in Q(av) were statistically significant, the alteration in the recorded Q(max) values was more striking. Our study emphasizes the importance of combining Q(av) and flow pattern along with Q(max) in interpretation of results of uroflowmetry. © 2010 Wiley-Liss, Inc.

The art and learning patterns of knowing in nursing.

PubMed

Baixinho, Cristina Lavareda; Ferraz, Isabel Carvalho Beato; Ferreira, Óscar Manuel Ramos; Rafael, Helga Marilia da Silva

2014-12-01

Objective To identify the perception of the students about the use of art as a pedagogical strategy in learning the patterns of knowing in nursing; to identify the dimensions of each pattern valued in the analysis of pieces of art. Method Descriptive mixed study. Data collection used a questionnaire applied to 31 nursing students. Results In the analysis of the students' discourse, it was explicit that empirical knowledge includes scientific knowledge, tradition and nature of care. The aesthetic knowledge implies expressiveness, subjectivity and sensitivity. Self-knowledge, experience, reflective attitude and relationships with others are the subcategories of personal knowledge and the moral and ethics support ethical knowledge. Conclusion It is possible to learn patterns of knowledge through art, especially the aesthetic, ethical and personal. It is necessary to investigate further pedagogical strategies that contribute to the learning patterns of nursing knowledge.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

PubMed

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Design space exploration for early identification of yield limiting patterns

NASA Astrophysics Data System (ADS)

Li, Helen; Zou, Elain; Lee, Robben; Hong, Sid; Liu, Square; Wang, JinYan; Du, Chunshan; Zhang, Recco; Madkour, Kareem; Ali, Hussein; Hsu, Danny; Kabeel, Aliaa; ElManhawy, Wael; Kwan, Joe

2016-03-01

In order to resolve the causality dilemma of which comes first, accurate design rules or real designs, this paper presents a flow for exploration of the layout design space to early identify problematic patterns that will negatively affect the yield. A new random layout generating method called Layout Schema Generator (LSG) is reported in this paper, this method generates realistic design-like layouts without any design rule violation. Lithography simulation is then used on the generated layout to discover the potentially problematic patterns (hotspots). These hotspot patterns are further explored by randomly inducing feature and context variations to these identified hotspots through a flow called Hotspot variation Flow (HSV). Simulation is then performed on these expanded set of layout clips to further identify more problematic patterns. These patterns are then classified into design forbidden patterns that should be included in the design rule checker and legal patterns that need better handling in the RET recipes and processes.

Learning new meanings for known words: Biphasic effects of prior knowledge

PubMed Central

Fang, Xiaoping; Perfetti, Charles; Stafura, Joseph

2017-01-01

In acquiring word meanings, learners are often confronted by a single word form that is mapped to two or more meanings. For example, long after how to roller-“skate”, one may learn that “skate” is also a kind of fish. Such learning of new meanings for familiar words involves two potentially contrasting processes, relative to new form-new meaning learning: 1) Form-based familiarity may facilitate learning a new meaning, and 2) meaning-based interference may inhibit learning a new meaning. We examined these two processes by having native English speakers learn new, unrelated meanings for familiar (high frequency) and less familiar (low frequency) English words, as well as for unfamiliar (novel or pseudo-) words. Tracking learning with cued-recall tasks at several points during learning revealed a biphasic pattern: higher learning rates and greater learning efficiency for familiar words relative to novel words early in learning and a reversal of this pattern later in learning. Following learning, interference from original meanings for familiar words was detected in a semantic relatedness judgment task. Additionally, lexical access to familiar words with new meanings became faster compared to their exposure controls, but no such effect occurred for less familiar words. Overall, the results suggest a biphasic pattern of facilitating and interfering processes: Familiar word forms facilitate learning earlier, while interference from original meanings becomes more influential later. This biphasic pattern reflects the co-activation of new and old meanings during learning, a process that may play a role in lexicalization of new meanings. PMID:29399593

Three-dimensional vortex patterns in a starting flow

NASA Astrophysics Data System (ADS)

Freymuth, P.; Finaish, F.; Bank, W.

1985-12-01

Freymuth et al. (1983, 1984, 1985) have conducted investigations involving chordwise vortical-pattern visualizations in a starting flow of constant acceleration around an airfoil. Detailed resolution of vortical shapes in two dimensions could be obtained. No visualization in the third spanwise dimension is needed as long as the flow remains two-dimensional. However, some time after flow startup, chordwise vortical patterns become blurred, indicating the onset of turbulence. The present investigation is concerned with an extension of the flow visualization from a chordwise cross section to the spanwise dimension. The investigation has the objective to look into the two-dimensionality of the initial vortical developments and to resolve three-dimensional effects during the transition to turbulence. Attention is given to the visualization method, the chordwise vs spanwise visualization in the two-dimensional regime, the spanwise visualization of transition, and the visualization of vortical patterns behind the trailing edge.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Biferale, Luca; Celani, Antonio; Gustavsson, Kristian

2017-11-01

We have numerically modeled active particles which are able to acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. We show that those swimmers can learn effective strategies just by experience, using a reinforcement learning algorithm. As an example, we focus on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, exploiting the underlying flow whenever possible. The reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This work paves the way towards the engineering of smart microswimmers that solve difficult navigation problems. ERC AdG NewTURB 339032.

A portable pattern-based design technology co-optimization flow to reduce optical proximity correction run-time

NASA Astrophysics Data System (ADS)

Chen, Yi-Chieh; Li, Tsung-Han; Lin, Hung-Yu; Chen, Kao-Tun; Wu, Chun-Sheng; Lai, Ya-Chieh; Hurat, Philippe

2018-03-01

Along with process improvement and integrated circuit (IC) design complexity increased, failure rate caused by optical getting higher in the semiconductor manufacture. In order to enhance chip quality, optical proximity correction (OPC) plays an indispensable rule in the manufacture industry. However, OPC, includes model creation, correction, simulation and verification, is a bottleneck from design to manufacture due to the multiple iterations and advanced physical behavior description in math. Thus, this paper presented a pattern-based design technology co-optimization (PB-DTCO) flow in cooperation with OPC to find out patterns which will negatively affect the yield and fixed it automatically in advance to reduce the run-time in OPC operation. PB-DTCO flow can generate plenty of test patterns for model creation and yield gaining, classify candidate patterns systematically and furthermore build up bank includes pairs of match and optimization patterns quickly. Those banks can be used for hotspot fixing, layout optimization and also be referenced for the next technology node. Therefore, the combination of PB-DTCO flow with OPC not only benefits for reducing the time-to-market but also flexible and can be easily adapted to diversity OPC flow.

An active, collaborative approach to learning skills in flow cytometry.

PubMed

Fuller, Kathryn; Linden, Matthew D; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N; Röhrig, Kimberley J

2016-06-01

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula. Copyright © 2016 The American Physiological Society.

Slug to churn transition analysis using wire-mesh sensor

NASA Astrophysics Data System (ADS)

H. F. Velasco, P.; Ortiz-Vidal, L. E.; Rocha, D. M.; Rodriguez, O. M. H.

2016-06-01

A comparison between some theoretical slug to churn flow-pattern transition models and experimental data is performed. The flow-pattern database considers vertical upward air-water flow at standard temperature and pressure for 50 mm and 32 mm ID pipes. A briefly description of the models and its phenomenology is presented. In general, the performance of the transition models is poor. We found that new experimental studies describing objectively both stable and unstable slug flow-pattern are required. In this sense, the Wire Mesh Sensor (WMS) can assist to that aim. The potential of the WMS is outlined.

Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.

A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins

NASA Astrophysics Data System (ADS)

Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R.

2011-09-01

Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells.

A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins

PubMed Central

Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R.

2011-01-01

Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells. PMID:21974603

A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins.

PubMed

Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R

2011-09-01

Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells. © 2011 American Institute of Physics

Investigation of the effect of pilot burner on lean blow out performance of a staged injector

NASA Astrophysics Data System (ADS)

Yang, Jinhu; Zhang, Kaiyu; Liu, Cunxi; Ruan, Changlong; Liu, Fuqiang; Xu, Gang

2014-12-01

The staged injector has exhibited great potential to achieve low emissions and is becoming the preferable choice of many civil airplanes. Moreover, it is promising to employ this injector design in military engine, which requires most of the combustion air enters the combustor through injector to reduce smoke emission. However, lean staged injector is prone to combustion instability and extinction in low load operation, so techniques for broadening its stable operation ranges are crucial for its application in real engine. In this work, the LBO performance of a staged injector is assessed and analyzed on a single sector test section. The experiment was done in atmospheric environment with optical access. Kerosene-PLIF technique was used to visualize the spray distribution and common camera was used to record the flame patterns. Emphasis is put on the influence of pilot burner on LBO performance. The fuel to air ratios at LBO of six injectors with different pilot swirler vane angle were evaluated and the obtained LBO data was converted into data at idle condition. Results show that the increase of pilot swirler vane angle could promote the air assisted atomization, which in turn improves the LBO performance slightly. Flame patterns typical in the process of LBO are analyzed and attempts are made to find out the main factors which govern the extinction process with the assistance of spray distribution and numerical flow field results. It can be learned that the flame patterns are mainly influenced by structure of the flow field just behind the pilot burner when the fuel mass flow rate is high; with the reduction of fuel, atomization quality become more and more important and is the main contributing factor of LBO. In the end of the paper, conclusions are drawn and suggestions are made for the optimization of the present staged injector.

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

PubMed

Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

Testing the limits of long-distance learning: Learning beyond a three-segment window

PubMed Central

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones since long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ('sh') and triggered a suffix that was either [−su] or [−∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. PMID:22303815

The selective serotonin reuptake inhibitor, escitalopram, enhances inhibition of prepotent responding and spatial reversal learning

PubMed Central

Brown, Holden D.; Amodeo, Dionisio A.; Sweeney, John A.; Ragozzino, Michael E.

2011-01-01

Previous findings indicate treatment with a selective serotonin reuptake inhibitor (SSRI) facilitates behavioral flexibility when conditions require inhibition of a learned response pattern. The present experiment investigated whether acute treatment with the SSRI, escitalopram, affects behavioral flexibility when conditions require inhibition of a naturally-biased response pattern (elevated conflict test) and/or reversal of a learned response pattern (spatial reversal learning). An additional experiment was carried out to determine whether escitalopram, at doses that affected behavioral flexibility, also reduced anxiety as tested in the elevated plus-maze. In each experiment, Long-Evans rats received an intraperitoneal injection of either saline or escitalopram (0.03, 0.3 or 1.0 mg/kg) 30 minutes prior to behavioral testing. Escitalopram, at all doses tested, enhanced acquisition in the elevated conflict test, but did not affect performance in the elevated plus-maze. Escitalopram (0.3 and 1.0 mg/kg) did not alter acquisition of the spatial discrimination, but facilitated reversal learning. In the elevated conflict and spatial reversal learning test, escitalopram enhanced the ability to maintain the relevant strategy after being initially selected. The present findings suggest that enhancing serotonin transmission with a SSRI facilitates inhibitory processes when conditions require a shift away from either a naturally-biased response pattern or a learned choice pattern. PMID:22219222

Gas-liquid-liquid three-phase flow pattern and pressure drop in a microfluidic chip: similarities with gas-liquid/liquid-liquid flows.

PubMed

Yue, Jun; Rebrov, Evgeny V; Schouten, Jaap C

2014-05-07

We report a three-phase slug flow and a parallel-slug flow as two major flow patterns found under the nitrogen-decane-water flow through a glass microfluidic chip which features a long microchannel with a hydraulic diameter of 98 μm connected to a cross-flow mixer. The three-phase slug flow pattern is characterized by a flow of decane droplets containing single elongated nitrogen bubbles, which are separated by water slugs. This flow pattern was observed at a superficial velocity of decane (in the range of about 0.6 to 10 mm s(-1)) typically lower than that of water for a given superficial gas velocity in the range of 30 to 91 mm s(-1). The parallel-slug flow pattern is characterized by a continuous water flow in one part of the channel cross section and a parallel flow of decane with dispersed nitrogen bubbles in the adjacent part of the channel cross section, which was observed at a superficial velocity of decane (in the range of about 2.5 to 40 mm s(-1)) typically higher than that of water for each given superficial gas velocity. The three-phase slug flow can be seen as a superimposition of both decane-water and nitrogen-decane slug flows observed in the chip when the flow of the third phase (viz. nitrogen or water, respectively) was set at zero. The parallel-slug flow can be seen as a superimposition of the decane-water parallel flow and the nitrogen-decane slug flow observed in the chip under the corresponding two-phase flow conditions. In case of small capillary numbers (Ca ≪ 0.1) and Weber numbers (We ≪ 1), the developed two-phase pressure drop model under a slug flow has been extended to obtain a three-phase slug flow model in which the 'nitrogen-in-decane' droplet is assumed as a pseudo-homogeneous droplet with an effective viscosity. The parallel flow and slug flow pressure drop models have been combined to obtain a parallel-slug flow model. The obtained models describe the experimental pressure drop with standard deviations of 8% and 12% for the three-phase slug flow and parallel-slug flow, respectively. An example is given to illustrate the model uses in designing bifurcated microchannels that split the three-phase slug flow for high-throughput processing.

Transient global amnesia: implicit/explicit memory dissociation and PET assessment of brain perfusion and oxygen metabolism in the acute stage.

PubMed

Eustache, F; Desgranges, B; Petit-Taboué, M C; de la Sayette, V; Piot, V; Sablé, C; Marchal, G; Baron, J C

1997-09-01

To assess explicit memory and two components of implicit memory--that is, perceptual-verbal skill learning and lexical-semantic priming effects--as well as resting cerebral blood flow (CBF) and oxygen metabolism (CMRO2) during the acute phase of transient global amnesia. In a 59 year old woman, whose amnestic episode fulfilled all current criteria for transient global amnesia, a neuropsychological protocol was administered, including word learning, story recall, categorical fluency, mirror reading, and word stem completion tasks. PET was performed using the (15)O steady state inhalation method, while the patient still exhibited severe anterograde amnesia and was interleaved with the cognitive tests. There was a clear cut dissociation between impaired long term episodic memory and preserved implicit memory for its two components. Categorical fluency was significantly altered, suggesting word retrieval strategy--rather than semantic memory--impairment. The PET study disclosed a reduced CMRO2 with relatively or fully preserved CBF in the left prefrontotemporal cortex and lentiform nucleus, and the reverse pattern over the left occipital cortex. The PET alterations with patchy CBF-CMRO2 uncoupling would be compatible with a migraine-like phenomenon and indicate that the isolated assessment of perfusion in transient global amnesia may be misleading. The pattern of metabolic depression, with sparing of the hippocampal area, is one among the distinct patterns of brain dysfunction that underlie the (apparently) uniform clinical presentation of transient global amnesia. The finding of a left prefrontal hypometabolism in the face of impaired episodic memory and altered verbal fluency would fit present day concepts from PET activation studies about the role of this area in episodic and semantic memory encoding/retrieval. Likewise, the changes affecting the lenticular nucleus but sparing the caudate would be consistent with the normal performance in perceptual-verbal skill learning. Finally, unaltered lexical-semantic priming effects, despite left temporal cortex hypometabolism, suggest that these processes are subserved by a more distributed neocortical network.

Flowing gas, non-nuclear experiments on the gas core reactor

NASA Technical Reports Server (NTRS)

Kunze, J. F.; Suckling, D. H.; Copper, C. G.

1972-01-01

Flow tests were conducted on models of the gas core (cavity) reactor. Variations in cavity wall and injection configurations were aimed at establishing flow patterns that give a maximum of the nuclear criticality eigenvalue. Correlation with the nuclear effect was made using multigroup diffusion theory normalized by previous benchmark critical experiments. Air was used to simulate the hydrogen propellant in the flow tests, and smoked air, argon, or freon to simulate the central nuclear fuel gas. All tests were run in the down-firing direction so that gravitational effects simulated the acceleration effect of a rocket. Results show that acceptable flow patterns with high volume fraction for the simulated nuclear fuel gas and high flow rate ratios of propellant to fuel can be obtained. Using a point injector for the fuel, good flow patterns are obtained by directing the outer gas at high velocity along the cavity wall, using louvered or oblique-angle-honeycomb injection schemes.

Complex Greenland outlet glacier flow captured

PubMed Central

Aschwanden, Andy; Fahnestock, Mark A.; Truffer, Martin

2016-01-01

The Greenland Ice Sheet is losing mass at an accelerating rate due to increased surface melt and flow acceleration in outlet glaciers. Quantifying future dynamic contributions to sea level requires accurate portrayal of outlet glaciers in ice sheet simulations, but to date poor knowledge of subglacial topography and limited model resolution have prevented reproduction of complex spatial patterns of outlet flow. Here we combine a high-resolution ice-sheet model coupled to uniformly applied models of subglacial hydrology and basal sliding, and a new subglacial topography data set to simulate the flow of the Greenland Ice Sheet. Flow patterns of many outlet glaciers are well captured, illustrating fundamental commonalities in outlet glacier flow and highlighting the importance of efforts to map subglacial topography. Success in reproducing present day flow patterns shows the potential for prognostic modelling of ice sheets without the need for spatially varying parameters with uncertain time evolution. PMID:26830316

Shear-Modulated Electroosmotic Flow on a Patterned Charged Surface

NASA Astrophysics Data System (ADS)

Wei, Hsien-Hung

2004-11-01

The effect of imposing shear flow on a charge-modulated electroosmotic flow is theoretically investigated. The flow pattern can contain saddle points or closed streamlines, depending on the relative strength of an imposed shear to the applied electrical field. The formation of closed streamlines could be advantageous for trapping non-diffusive particles in desired locations. Different time periodic alternating flows and their corresponding particle trajectories are also examined for assessing strategies for creating efficient mixing.

A qualitative and quantitative laser-based computer-aided flow visualization method. M.S. Thesis, 1992 Final Report

NASA Technical Reports Server (NTRS)

Canacci, Victor A.; Braun, M. Jack

1994-01-01

The experimental approach presented here offers a nonintrusive, qualitative and quantitative evaluation of full field flow patterns applicable in various geometries in a variety of fluids. This Full Flow Field Tracking (FFFT) Particle Image Velocimetry (PIV) technique, by means of particle tracers illuminated by a laser light sheet, offers an alternative to Laser Doppler Velocimetry (LDV), and intrusive systems such as Hot Wire/Film Anemometry. The method makes obtainable the flow patterns, and allows quantitative determination of the velocities, accelerations, and mass flows of an entire flow field. The method uses a computer based digitizing system attached through an imaging board to a low luminosity camera. A customized optical train allows the system to become a long distance microscope (LDM), allowing magnifications of areas of interest ranging up to 100 times. Presented in addition to the method itself, are studies in which the flow patterns and velocities were observed and evaluated in three distinct geometries, with three different working fluids. The first study involved pressure and flow analysis of a brush seal in oil. The next application involved studying the velocity and flow patterns in a cowl lip cooling passage of an air breathing aircraft engine using water as the working fluid. Finally, the method was extended to a study in air to examine the flows in a staggered pin arrangement located on one side of a branched duct.

40 CFR 230.23 - Current patterns and water circulation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... or fill material can modify current patterns and water circulation by obstructing flow, changing the direction or velocity of water flow, changing the direction or velocity of water flow and circulation, or otherwise changing the dimensions of a water body. As a result, adverse changes can occur in: Location...

40 CFR 230.23 - Current patterns and water circulation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... or fill material can modify current patterns and water circulation by obstructing flow, changing the direction or velocity of water flow, changing the direction or velocity of water flow and circulation, or otherwise changing the dimensions of a water body. As a result, adverse changes can occur in: Location...

40 CFR 230.23 - Current patterns and water circulation.

Code of Federal Regulations, 2014 CFR

2014-07-01

... or fill material can modify current patterns and water circulation by obstructing flow, changing the direction or velocity of water flow, changing the direction or velocity of water flow and circulation, or otherwise changing the dimensions of a water body. As a result, adverse changes can occur in: Location...

Flow-separation patterns on symmetric forebodies

NASA Technical Reports Server (NTRS)

Keener, Earl R.

1986-01-01

Flow-visualization studies of ogival, parabolic, and conical forebodies were made in a comprehensive investigation of the various types of flow patterns. Schlieren, vapor-screen, oil-flow, and sublimation flow-visualization tests were conducted over an angle-of-attack range from 0 deg. to 88 deg., over a Reynolds-number range from 0.3X10(6) to 2.0X10(6) (based on base diameter), and over a Mach number range from 0.1 to 2. The principal effects of angle of attack, Reynolds number, and Mach number on the occurrence of vortices, the position of vortex shedding, the principal surface-flow-separation patterns, the magnitude of surface-flow angles, and the extent of laminar and turbulent flow for symmetric, asymmetric, and wake-like flow-separation regimes are presented. It was found that the two-dimensional cylinder analogy was helpful in a qualitative sense in analyzing both the surface-flow patterns and the external flow field. The oil-flow studies showed three types of primary separation patterns at the higher Reynolds numbers owing to the influence of boundary-layer transition. The effect of angle of attack and Reynolds number is to change the axial location of the onset and extent of the primary transitional and turbulent separation regions. Crossflow inflectional-instability vortices were observed on the windward surface at angles of attack from 5 deg. to 55 deg. Their effect is to promote early transition. At low angles of attack, near 10 deg., an unexpected laminar-separation bubble occurs over the forward half of the forebody. At high angles of attack, at which vortex asymmetry occurs, the results support the proposition that the principal cause of vortex asymmetry is the hydrodynamic instability of the inviscid flow field. On the other hand, boundary-layer asymmetries also occur, especially at transitional Reynolds numbers. The position of asymmetric vortex shedding moves forward with increasing angle of attack and with increasing Reynolds number, and moves rearward with increasing Mach number.

Training the Brain or Tending a Garden? Students' Metaphors of Learning Predict Self-Reported Learning Patterns

ERIC Educational Resources Information Center

Wegner, Elisabeth; Nückles, Matthias

2015-01-01

Conceptions of learning are seen as an important factor in shaping students' patterns of learning. However, conceptions are often implicit and difficult to assess. Metaphors have been proposed as a method to assess conceptions, because metaphors are closely linked to the conceptual system. Therefore, in our study we assessed which conceptions of…

Collaborative mining of graph patterns from multiple sources

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romanoa, John

2016-05-01

Intelligence analysts require automated tools to mine multi-source data, including answering queries, learning patterns of life, and discovering malicious or anomalous activities. Graph mining algorithms have recently attracted significant attention in intelligence community, because the text-derived knowledge can be efficiently represented as graphs of entities and relationships. However, graph mining models are limited to use-cases involving collocated data, and often make restrictive assumptions about the types of patterns that need to be discovered, the relationships between individual sources, and availability of accurate data segmentation. In this paper we present a model to learn the graph patterns from multiple relational data sources, when each source might have only a fragment (or subgraph) of the knowledge that needs to be discovered, and segmentation of data into training or testing instances is not available. Our model is based on distributed collaborative graph learning, and is effective in situations when the data is kept locally and cannot be moved to a centralized location. Our experiments show that proposed collaborative learning achieves learning quality better than aggregated centralized graph learning, and has learning time comparable to traditional distributed learning in which a knowledge of data segmentation is needed.

Syntax-induced pattern deafness

PubMed Central

Endress, Ansgar D.; Hauser, Marc D.

2009-01-01

Perceptual systems often force systematically biased interpretations upon sensory input. These interpretations are obligatory, inaccessible to conscious control, and prevent observers from perceiving alternative percepts. Here we report a similarly impenetrable phenomenon in the domain of language, where the syntactic system prevents listeners from detecting a simple perceptual pattern. Healthy human adults listened to three-word sequences conforming to patterns readily learned even by honeybees, rats, and sleeping human neonates. Specifically, sequences either started or ended with two words from the same syntactic category (e.g., noun–noun–verb or verb–verb–noun). Although participants readily processed the categories and learned repetition patterns over nonsyntactic categories (e.g., animal–animal–clothes), they failed to learn the repetition pattern over syntactic categories, even when explicitly instructed to look for it. Further experiments revealed that participants successfully learned the repetition patterns only when they were consistent with syntactically possible structures, irrespective of whether these structures were attested in English or in other languages unknown to the participants. When the repetition patterns did not match such syntactically possible structures, participants failed to learn them. Our results suggest that when human adults hear a string of nouns and verbs, their syntactic system obligatorily attempts an interpretation (e.g., in terms of subjects, objects, and predicates). As a result, subjects fail to perceive the simpler pattern of repetitions—a form of syntax-induced pattern deafness that is reminiscent of how other perceptual systems force specific interpretations upon sensory input. PMID:19920182

Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences

ERIC Educational Resources Information Center

Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

2015-01-01

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

Associative-memory representations emerge as shared spatial patterns of theta activity spanning the primate temporal cortex

PubMed Central

Nakahara, Kiyoshi; Adachi, Ken; Kawasaki, Keisuke; Matsuo, Takeshi; Sawahata, Hirohito; Majima, Kei; Takeda, Masaki; Sugiyama, Sayaka; Nakata, Ryota; Iijima, Atsuhiko; Tanigawa, Hisashi; Suzuki, Takafumi; Kamitani, Yukiyasu; Hasegawa, Isao

2016-01-01

Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation. PMID:27282247

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Thermomagnetic convective flows in a vertical layer of ferrocolloid: perturbation energy analysis and experimental study.

PubMed

Suslov, Sergey A; Bozhko, Alexandra A; Sidorov, Alexander S; Putin, Gennady F

2012-07-01

Flow patterns arising in a vertical differentially heated layer of nonconducting ferromagnetic fluid placed in an external uniform transverse magnetic field are studied experimentally and discussed from the point of view of the perturbation energy balance. A quantitative criterion for detecting the parametric point where the dominant role in generating a flow instability is transferred between the thermogravitational and thermomagnetic mechanisms is suggested, based on the disturbance energy balance analysis. A comprehensive experimental study of various flow patterns is undertaken, and the existence is demonstrated of oblique thermomagnetic waves theoretically predicted by Suslov [Phys. Fluids 20, 084101 (2008)] and superposed onto the stationary magnetoconvective pattern known previously. It is found that the wave number of the detected convection patterns depends sensitively on the temperature difference across the layer and on the applied magnetic field. In unsteady regimes its value varies periodically by a factor of almost 2, indicating the appearance of two different competing wave modes. The wave numbers and spatial orientation of the observed dominant flow patterns are found to be in good agreement with theoretical predictions.

The Effects of Autonomy-Supportive and Controlling Teaching Behaviour in Biology Lessons with Primary and Secondary Experiences on Students' Intrinsic Motivation and Flow-Experience

ERIC Educational Resources Information Center

Hofferber, Natalia; Basten, Melanie; Großmann, Nadine; Wilde, Matthias

2016-01-01

Self-Determination Theory and Flow Theory propose that perceived autonomy fosters the positive qualities of motivation and flow-experience. Autonomy-support can help to maintain students' motivation in very interesting learning activities and may lead to an increase in the positive qualities of motivation in less interesting learning activities.…

Spiral Laminar Flow: a Survey of a Three-Dimensional Arterial Flow Pattern in a Group of Volunteers.

PubMed

Stonebridge, P A; Suttie, S A; Ross, R; Dick, J

2016-11-01

Spiral laminar flow was suggested as potentially the predominant arterial blood flow pattern many years ago. Computational fluid dynamics and flow rig testing have suggested there are advantages to spiral laminar flow. The aim of this study was to identify whether spiral laminar is the predominant flow pattern in a cohort of volunteers. This study included 42 volunteers (mean age 66.8 years). Eleven arterial sites were examined, comprising bilateral examination of the common carotid artery, internal carotid artery, external carotid artery, common femoral artery, superficial femoral artery, and the infra renal aorta. The presence or absence of spiral laminar flow, the peak systolic velocity, and the rotational velocity were assessed by colour Duplex scanning. The incidence of spiral laminar flow ranged from 81% in the internal carotid artery to 90% in the common carotid artery and the infra renal aorta. Overall, in 58% of all right-sided arteries the rotation was clockwise and 42% anticlockwise. In all left-sided arteries these numbers were reversed. Analysis on the basis of volunteer rather than examination site showed that 41/42 (97%) had more sites with spiral laminar flow than without. Only one volunteer had more sites exhibiting non-spiral laminar flow. Spiral laminar flow was the predominant flow pattern in the study population. This observation raises questions and suggests a need for further studies concerning the form and function of the left ventricle, the geometry of the arterial system, and the function of the arterial wall. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Altered Actin Centripetal Retrograde Flow in Physically Restricted Immunological Synapses

PubMed Central

Yu, Cheng-han; Wu, Hung-Jen; Kaizuka, Yoshihisa; Vale, Ronald D.; Groves, Jay T.

2010-01-01

Antigen recognition by T cells involves large scale spatial reorganization of numerous receptor, adhesion, and costimulatory proteins within the T cell-antigen presenting cell (APC) junction. The resulting patterns can be distinctive, and are collectively known as the immunological synapse. Dynamical assembly of cytoskeletal network is believed to play an important role in driving these assembly processes. In one experimental strategy, the APC is replaced with a synthetic supported membrane. An advantage of this configuration is that solid structures patterned onto the underlying substrate can guide immunological synapse assembly into altered patterns. Here, we use mobile anti-CD3ε on the spatial-partitioned supported bilayer to ligate and trigger T cell receptor (TCR) in live Jurkat T cells. Simultaneous tracking of both TCR clusters and GFP-actin speckles reveals their dynamic association and individual flow patterns. Actin retrograde flow directs the inward transport of TCR clusters. Flow-based particle tracking algorithms allow us to investigate the velocity distribution of actin flow field across the whole synapse, and centripetal velocity of actin flow decreases as it moves toward the center of synapse. Localized actin flow analysis reveals that, while there is no influence on actin motion from substrate patterns directly, velocity differences of actin are observed over physically trapped TCR clusters. Actin flow regains its velocity immediately after passing through confined TCR clusters. These observations are consistent with a dynamic and dissipative coupling between TCR clusters and viscoelastic actin network. PMID:20686692

Phonological Concept Learning

ERIC Educational Resources Information Center

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by…

CHARACTERISTICS OF SOLAR MERIDIONAL FLOWS DURING SOLAR CYCLE 23

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basu, Sarbani; Antia, H. M., E-mail: sarbani.basu@yale.ed, E-mail: antia@tifr.res.i

2010-07-01

We have analyzed available full-disk data from the Michelson Doppler Imager on board SOHO using the 'ring diagram' technique to determine the behavior of solar meridional flows over solar cycle 23 in the outer 2% of the solar radius. We find that the dominant component of meridional flows during solar maximum was much lower than that during the minima at the beginning of cycles 23 and 24. There were differences in the flow velocities even between the two minima. The meridional flows show a migrating pattern with higher-velocity flows migrating toward the equator as activity increases. Additionally, we find thatmore » the migrating pattern of the meridional flow matches those of sunspot butterfly diagram and the zonal flows in the shallow layers. A high-latitude band in meridional flow appears around 2004, well before the current activity minimum. A Legendre polynomial decomposition of the meridional flows shows that the latitudinal pattern of the flow was also different during the maximum as compared to that during the two minima. The different components of the flow have different time dependences, and the dependence is different at different depths.« less

Cilia driven flow networks in the brain

NASA Astrophysics Data System (ADS)

Wang, Yong; Faubel, Regina; Westendorf, Chrsitian; Eichele, Gregor; Bodenschatz, Eberhard

Neurons exchange soluble substances via the cerebrospinal fluid (CSF) that fills the ventricular system. The walls of the ventricular cavities are covered with motile cilia that constantly beat and thereby induce a directional flow. We recently discovered that cilia in the third ventricle generate a complex flow pattern leading to partitioning of the ventricular volume and site-directed transport paths along the walls. Transient and daily recurrent alterations in the cilia beating direction lead to changes in the flow pattern. This has consequences for delivery of CSF components along the near wall flow. The contribution of this cilia-induced flow to overall CSF flow remains to be investigated. The state-of-art lattice Boltzmann method is adapted for studying the CFS flow. The 3D geometry of the third ventricle at high resolution was reconstructed. Simulation of CSF flow without cilia in this geometry confirmed that the previous idea about unidirectional flow does not explain how different components of CSF can be delivered to their various target sites. We study the contribution of the cilia-induced flow pattern to overall CSF flow and identify target areas for site-specific delivery of CSF-constituents with respect to the temporal changes.

Venturi flow meter and Electrical Capacitance Probe in a horizontal two-phase flow

NASA Astrophysics Data System (ADS)

Monni, G.; Caramello, M.; De Salve, M.; Panella, B.

2015-11-01

The paper presents the results obtained with a spool piece (SP) made of a Venturi flow meter (VMF) and an Electrical Capacitance Probe (ECP) in stratified two-phase flow. The objective is to determine the relationship between the test measurements and the physical characteristics of the flow such as superficial velocities, density and void fraction. The outputs of the ECP are electrical signals proportional to the void fraction between the electrodes; the parameters measured by the VFM are the total and the irreversible pressure losses of the two- phase mixture. The fluids are air and demineralized water at ambient conditions. The flow rates are in the range of 0,065-0,099 kg/s for air and 0- 0,039 kg/s (0-140 l/h) for water. The flow patterns recognized during the experiments are stratified, dispersed and annular flow. The presence of the VFM plays an important role on the alteration of the flow pattern due to wall flow detachment phenomena. The signals of differential pressure of the VFM in horizontal configuration are strongly dependent on the superficial velocities and on the flow pattern because of a lower symmetry of the flow with respect to the vertical configuration.

Temporal evolution of age data under transient pumping conditions

NASA Astrophysics Data System (ADS)

Leray, S.; De Dreuzy, J.; Aquilina, L.; Vergnaud, V.; Labasque, T.; Bour, O.; Le Borgne, T.

2013-12-01

While most age data derived from tracers have been analyzed in steady-state flow conditions, we determine their temporal evolution under transient pumping conditions. Starting pumping in a well modifies the natural flow patterns induced by the topographical gradient to a mainly convergent flow to the well. Our study is based on a set of models made up of a shallowly dipping aquifer overlain by a less permeable aquitard. These settings are characteristic of the crystalline aquifer of Plœmeur (Brittany, France) located in a highly fractured zone at the contact between a granite and micaschists. Under a pseudo steady-state flow assumption (instantaneous shift between two steady-state flow fields), we solve the transport equation with a backward particle-tracking method and determine the temporal evolution of the concentrations at the pumping well of the four atmospheric tracers CFC 11, CFC 12, CFC 113 and SF6. We show that apparent ages deduced from these concentrations evolve both because of the flow patterns modifications and because of the non-linear evolution of the atmospheric tracer concentrations. Flow patterns modifications only intervene just after the start of pumping, when the initially piston-like residence time distribution is transformed to a broader distribution mixing residence times from a wide variety of flow lines. Later, while flow patterns and the supplying volume of the pumping well still evolve, the residence time distributions are hardly modified and apparent ages are solely altered by the non-linear atmospheric tracer concentrations that progressively modifies the weighting of the residence time distribution. These results are confirmed by the observations at the site of Plœmeur in the pumping area. First, long term chloride observations confirm the quick evolution of the flow patterns after the start of pumping. Second, posterior and more recent evolutions of apparent ages derived from CFCs are consistent with the modeling results revealing in turn the marginal effect of the 20-year pumping on the first 70 years of the residence time distribution. We conclude that the temporal evolution of apparent ages should be used with great care for identifying the temporal evolution of the flow patterns as the apparent age evolution can have two sources - the transient flow patterns and transient tracer atmospheric concentrations. We argue that both evolutions either controlled by transient flow patterns or by transient tracer atmospheric concentrations provide key information that can be further used for the characterization of the hydrogeological system. This study illustrates that the temporal evolution of apparent ages could be used for models segregation and slightly compensate for the small number of tracers.

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

NASA Astrophysics Data System (ADS)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

PubMed Central

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

PubMed

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

Hands-On! Living in the Biosphere: Production, Pattern, Population, and Diversity. Developing Active Learning Module on the Human Dimensions of Global Change.

ERIC Educational Resources Information Center

Brown, Dwight

Biogeography examines questions of organism inventory and pattern, organisms' interactions with the environment, and the processes that create and change inventory, pattern, and interactions. This learning module uses time series maps and simple simulation models to illustrate how human actions alter biological productivity patterns at local and…

Multi-frequency complex network from time series for uncovering oil-water flow structure.

PubMed

Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

2015-02-04

Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

Regimes of Flow over Complex Structures of Endothelial Glycocalyx: A Molecular Dynamics Simulation Study.

PubMed

Jiang, Xi Zhuo; Feng, Muye; Ventikos, Yiannis; Luo, Kai H

2018-04-10

Flow patterns on surfaces grafted with complex structures play a pivotal role in many engineering and biomedical applications. In this research, large-scale molecular dynamics (MD) simulations are conducted to study the flow over complex surface structures of an endothelial glycocalyx layer. A detailed structure of glycocalyx has been adopted and the flow/glycocalyx system comprises about 5,800,000 atoms. Four cases involving varying external forces and modified glycocalyx configurations are constructed to reveal intricate fluid behaviour. Flow profiles including temporal evolutions and spatial distributions of velocity are illustrated. Moreover, streamline length and vorticity distributions under the four scenarios are compared and discussed to elucidate the effects of external forces and glycocalyx configurations on flow patterns. Results show that sugar chain configurations affect streamline length distributions but their impact on vorticity distributions is statistically insignificant, whilst the influence of the external forces on both streamline length and vorticity distributions are trivial. Finally, a regime diagram for flow over complex surface structures is proposed to categorise flow patterns.

Competing Processes of Sibling Influence: Observational Learning and Sibling Deidentification

ERIC Educational Resources Information Center

Whiteman, Shawn D.; McHale, Susan M.; Crouter, Ann C.

2007-01-01

Although commonly cited as explanations for patterns of sibling similarity and difference, observational learning and sibling deidentification processes have rarely been examined directly. Using a person-oriented approach, we identified patterns in adolescents' perceptions of sibling influences and connected these patterns to sibling similarities…

On aerobic exercise and behavioral and neural plasticity.

PubMed

Swain, Rodney A; Berggren, Kiersten L; Kerr, Abigail L; Patel, Ami; Peplinski, Caitlin; Sikorski, Angela M

2012-11-29

Aerobic exercise promotes rapid and profound alterations in the brain. Depending upon the pattern and duration of exercise, these changes in the brain may extend beyond traditional motor areas to regions and structures normally linked to learning, cognition, and emotion. Exercise-induced alterations may include changes in blood flow, hormone and growth factor release, receptor expression, angiogenesis, apoptosis, neurogenesis, and synaptogenesis. Together, we believe that these changes underlie elevations of mood and prompt the heightened behavioral plasticity commonly observed following adoption of a chronic exercise regimen. In the following paper, we will explore both the psychological and psychobiological literatures relating to exercise effects on brain in both human and non-human animals and will attempt to link plastic changes in these neural structures to modifications in learned behavior and emotional expression. In addition, we will explore the therapeutic potential of exercise given recent reports that aerobic exercise may serve as a neuroprotectant and can also slow cognitive decline during normal and pathological aging.

On Aerobic Exercise and Behavioral and Neural Plasticity

PubMed Central

Swain, Rodney A.; Berggren, Kiersten L.; Kerr, Abigail L.; Patel, Ami; Peplinski, Caitlin; Sikorski, Angela M.

2012-01-01

Aerobic exercise promotes rapid and profound alterations in the brain. Depending upon the pattern and duration of exercise, these changes in the brain may extend beyond traditional motor areas to regions and structures normally linked to learning, cognition, and emotion. Exercise-induced alterations may include changes in blood flow, hormone and growth factor release, receptor expression, angiogenesis, apoptosis, neurogenesis, and synaptogenesis. Together, we believe that these changes underlie elevations of mood and prompt the heightened behavioral plasticity commonly observed following adoption of a chronic exercise regimen. In the following paper, we will explore both the psychological and psychobiological literatures relating to exercise effects on brain in both human and non-human animals and will attempt to link plastic changes in these neural structures to modifications in learned behavior and emotional expression. In addition, we will explore the therapeutic potential of exercise given recent reports that aerobic exercise may serve as a neuroprotectant and can also slow cognitive decline during normal and pathological aging. PMID:24961267

Two phase flow bifurcation due to turbulence: transition from slugs to bubbles

NASA Astrophysics Data System (ADS)

Górski, Grzegorz; Litak, Grzegorz; Mosdorf, Romuald; Rysak, Andrzej

2015-09-01

The bifurcation of slugs to bubbles within two-phase flow patterns in a minichannel is analyzed. The two-phase flow (water-air) occurring in a circular horizontal minichannel with a diameter of 1 mm is examined. The sequences of light transmission time series recorded by laser-phototransistor sensor is analyzed using recurrence plots and recurrence quantification analysis. Recurrence parameters allow the two-phase flow patterns to be found. On changing the water flow rate we identified partitioning of slugs or aggregation of bubbles.

The epidemic spreading model and the direction of information flow in brain networks.

PubMed

Meier, J; Zhou, X; Hillebrand, A; Tewarie, P; Stam, C J; Van Mieghem, P

2017-05-15

The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple Susceptible-Infected-Susceptible (SIS) epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns and posterior hubs in the structural network seem to play a dominant role in the network dynamics. For small time scales, when these hubs acted as strong receivers of information, the global pattern of information flow was in the posterior-to-anterior direction and in the opposite direction when they were strong senders. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions and their directions seem to be linked to different time scales of the spreading process. Copyright © 2017 Elsevier Inc. All rights reserved.

A high-capacity model for one shot association learning in the brain

PubMed Central

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs. PMID:25426060

A high-capacity model for one shot association learning in the brain.

PubMed

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs.

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes

ERIC Educational Resources Information Center

Bufford, Carolyn A.; Mettler, Everett; Geller, Emma H.; Kellman, Philip J.

2014-01-01

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM)…

Social Skills Deficits in Learning Disabilities: The Psychiatric Comorbidity Hypothesis.

ERIC Educational Resources Information Center

San Miguel, Stephanie K.; And Others

1996-01-01

This article explores the hypothesis that social skill deficits among children with learning disabilities are associated with high rates of undetected psychiatric diagnoses. The maladaptive social skills patterns of children with specific subtypes of learning disabilities appear to mimic the symptom patterns of children with attention deficit…

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach

ERIC Educational Resources Information Center

Man, Thomas Wing Yan

2006-01-01

Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which…

Teaching Tectonics to Undergraduates with Web GIS

NASA Astrophysics Data System (ADS)

Anastasio, D. J.; Bodzin, A.; Sahagian, D. L.; Rutzmoser, S.

2013-12-01

Geospatial reasoning skills provide a means for manipulating, interpreting, and explaining structured information and are involved in higher-order cognitive processes that include problem solving and decision-making. Appropriately designed tools, technologies, and curriculum can support spatial learning. We present Web-based visualization and analysis tools developed with Javascript APIs to enhance tectonic curricula while promoting geospatial thinking and scientific inquiry. The Web GIS interface integrates graphics, multimedia, and animations that allow users to explore and discover geospatial patterns that are not easily recognized. Features include a swipe tool that enables users to see underneath layers, query tools useful in exploration of earthquake and volcano data sets, a subduction and elevation profile tool which facilitates visualization between map and cross-sectional views, drafting tools, a location function, and interactive image dragging functionality on the Web GIS. The Web GIS platform is independent and can be implemented on tablets or computers. The GIS tool set enables learners to view, manipulate, and analyze rich data sets from local to global scales, including such data as geology, population, heat flow, land cover, seismic hazards, fault zones, continental boundaries, and elevation using two- and three- dimensional visualization and analytical software. Coverages which allow users to explore plate boundaries and global heat flow processes aided learning in a Lehigh University Earth and environmental science Structural Geology and Tectonics class and are freely available on the Web.

Scaling analysis of gas-liquid two-phase flow pattern in microgravity

NASA Technical Reports Server (NTRS)

Lee, Jinho

1993-01-01

A scaling analysis of gas-liquid two-phase flow pattern in microgravity, based on the dominant physical mechanism, was carried out with the goal of predicting the gas-liquid two-phase flow regime in a pipe under conditions of microgravity. The results demonstrated the effect of inlet geometry on the flow regime transition. A comparison of the predictions with existing experimental data showed good agreement.

Analysis of serial coronary artery flow patterns early after primary angioplasty: new insights into the dynamics of the microcirculation.

PubMed

Sharif, Dawod; Rofe, Guy; Sharif-Rasslan, Amal; Goldhammer, Ehud; Makhoul, Nabeel; Shefer, Arie; Hassan, Amin; Rauchfleisch, Shmuel; Rosenschein, Uri

2008-06-01

The temporal behavior of the coronary microcirculation in acute myocardial infarction may affect outcome. Diastolic deceleration time and early systolic flow reversal derived from coronary artery blood flow velocity patterns reflect microcirculatory function. To assess left anterior descending coronary artery flow velocity patterns using Doppler transthoracic echocardiography after primary percutaneous coronary intervention, in patients with anterior AMI. Patterns of flow velocity patterns of the LAD were obtained using transthoracic echocardiography-Doppler in 31 consecutive patients who presented with anterior AMI. Measurements were done at 6 hours, 36-48 hours, and 5 days after successful PPCI. Measurements of DDT and pressure half times (Pt%), as well as observation for ESFR were performed. In the first 2 days following PPCI, the average DDT (600 +/- 340 msec) was shorter than on day 5 (807 +/- 332 msec) (P < 0.012), FVP in the first 2 days were dynamic and bidirectional: from short DDT (< 600 msec) to long DDT (> 600 msec) and vice versa. On day 5 most DDTs became longer. Pt1/2 at 6 hours was not different than at day 2 (174 +/- 96 vs. 193 +/- 99 msec, P = NS) and became longer on day 5 (235 +/- 98 msec, P = 0.012). Bidirectional patterns were also observed in the ESFR in 6 patients (19%) at baseline, in 4 (13%) at 36 hours, and in 2 (6.5%) on day 5 after PPCI. Flow velocity patterns of the LAD after PPCI in AMI are dynamic and reflect unpredictable changes in microcirculation.

Exploiting multiple sources of information in learning an artificial language: human data and modeling.

PubMed

Perruchet, Pierre; Tillmann, Barbara

2010-03-01

This study investigates the joint influences of three factors on the discovery of new word-like units in a continuous artificial speech stream: the statistical structure of the ongoing input, the initial word-likeness of parts of the speech flow, and the contextual information provided by the earlier emergence of other word-like units. Results of an experiment conducted with adult participants show that these sources of information have strong and interactive influences on word discovery. The authors then examine the ability of different models of word segmentation to account for these results. PARSER (Perruchet & Vinter, 1998) is compared to the view that word segmentation relies on the exploitation of transitional probabilities between successive syllables, and with the models based on the Minimum Description Length principle, such as INCDROP. The authors submit arguments suggesting that PARSER has the advantage of accounting for the whole pattern of data without ad-hoc modifications, while relying exclusively on general-purpose learning principles. This study strengthens the growing notion that nonspecific cognitive processes, mainly based on associative learning and memory principles, are able to account for a larger part of early language acquisition than previously assumed. Copyright © 2009 Cognitive Science Society, Inc.

PeakVizor: Visual Analytics of Peaks in Video Clickstreams from Massive Open Online Courses.

PubMed

Chen, Qing; Chen, Yuanzhe; Liu, Dongyu; Shi, Conglei; Wu, Yingcai; Qu, Huamin

2016-10-01

Massive open online courses (MOOCs) aim to facilitate open-access and massive-participation education. These courses have attracted millions of learners recently. At present, most MOOC platforms record the web log data of learner interactions with course videos. Such large amounts of multivariate data pose a new challenge in terms of analyzing online learning behaviors. Previous studies have mainly focused on the aggregate behaviors of learners from a summative view; however, few attempts have been made to conduct a detailed analysis of such behaviors. To determine complex learning patterns in MOOC video interactions, this paper introduces a comprehensive visualization system called PeakVizor. This system enables course instructors and education experts to analyze the "peaks" or the video segments that generate numerous clickstreams. The system features three views at different levels: the overview with glyphs to display valuable statistics regarding the peaks detected; the flow view to present spatio-temporal information regarding the peaks; and the correlation view to show the correlation between different learner groups and the peaks. Case studies and interviews conducted with domain experts have demonstrated the usefulness and effectiveness of PeakVizor, and new findings about learning behaviors in MOOC platforms have been reported.

Selection of Two-Phase Flow Patterns at a Simple Junction in Microfluidic Devices

NASA Astrophysics Data System (ADS)

Engl, W.; Ohata, K.; Guillot, P.; Colin, A.; Panizza, P.

2006-04-01

We study the behavior of a confined stream made of two immiscible fluids when it reaches a T junction. Two flow patterns are witnessed: the stream is either directed in only one sidearm, yielding a preferential flow pathway for the dispersed phase, or splits between both. We show that the selection of these patterns is not triggered by the shape of the junction nor by capillary effects, but results from confinement. It can be anticipated in terms of the hydrodynamic properties of the flow. A simple model yielding universal behavior in terms of the relevant adimensional parameters of the problem is presented and discussed.

Instability patterns in a miscible core annular flow

NASA Astrophysics Data System (ADS)

D'Olce, Marguerite; Martin, Jerome; Rakotomalala, Nicole; Salin, Dominique; Talon, Laurent

2006-11-01

Laboratoire FAST, batiment 502, campus universitaire, 91405 Orsay Cedex (France). Experiments are performed with two miscible fluids of equal density but different viscosities. The fluids are injected co-currently and concentrically into a cylindrical pipe. The so-obtained base state is an axisymmetric parallel flow, for which the ratio of the flow rates of the two fluids monitors the relative amount (and so the radius) of the fluids. Depending on this relative amount and on the total flow rate of the fluids, unstable axisymmetric patterns such as mushrooms and pearls are observed. We delineate the diagram of occurrence of the two patterns and characterize the instabilities.

Flow-driven pattern formation in the calcium-oxalate system.

PubMed

Bohner, Bíborka; Endrődi, Balázs; Horváth, Dezső; Tóth, Ágota

2016-04-28

The precipitation reaction of calcium oxalate is studied experimentally in the presence of spatial gradients by controlled flow of calcium into oxalate solution. The density difference between the reactants leads to strong convection in the form of a gravity current that drives the spatiotemporal pattern formation. The phase diagram of the system is constructed, the evolving precipitate patterns are analyzed and quantitatively characterized by their diameters and the average height of the gravity flow. The compact structures of calcium oxalate monohydrate produced at low flow rates are replaced by the thermodynamically unstable calcium oxalate dihydrate favored in the presence of a strong gravity current.

Quantitative analysis of skin flap blood flow in the rat using laser Doppler velocimetry.

PubMed Central

Marks, N J

1985-01-01

Two experiments carried out on rat skin flaps are described, where microvascular flow has been measured noninvasively by a laser Doppler velocimeter. Using this technique it is possible to define the limits of an axial pattern flap in terms of microvascular flow; this was found to increase when the flap is elevated. 'Random-pattern' perfusion is defined by a fall in flow. This recovers sequentially along the flap, and at a constant rate at all sites. A differential in microvascular perfusion is thus maintained along a random-pattern flap for at least the first postoperative week. In a second experiment it is shown that there appears to be a linear relationship between the reduction in skin blood flow in a random-pattern flap and the distance from the base at which the measurements are made. It is suggested that these data support the view that the blood flow in a skin flap recovers primarily from its base rather than via peripheral neovascularization, and that this is due to vascular collaterals opening within the flap rather than to a relaxation of sympathetic tone. PMID:3156992

Probing the Gaps: A Synthesis of Well-known and Lesser-known Hydrological Feedbacks Influencing Vegetation Patterning and Long-term Geomorphic Change in Low-gradient Fluvial Landscapes

NASA Astrophysics Data System (ADS)

Larsen, L.; Christensen, A.; Harvey, J. W.; Ma, H.; Newman, S.; Saunders, C.; Twilley, R.

2017-12-01

Emergence of vegetation patterning in fluvial landscapes is a classic example of how autogenic processes can drive long term fluvial and geomorphic adjustments in aquatic ecosystems. Studies elucidating the physics of flow through vegetation patches have produced understanding of how patterning in topography and vegetation commonly emerges and what effect it has on long term geomorphic change. However, with regard to mechanisms underlying pattern existence and resilience, several knowledge gaps remain, including the role of landscape-scale flow-vegetation feedbacks, feedbacks that invoke additional biogeochemical or biological agents, and determination of the relative importance of autogenic processes relative to external drivers. Here we provide a synthesis of the processes over a range of scales known to drive vegetation patterning and sedimentation in low gradient fluvial landscapes, emphasizing recent field and modeling studies in the Everglades, FL and Wax Lake Delta, LA that address these gaps. In the Everglades, while flow routing and sediment redistribution at the patch scale is known to be a primary driver of vegetation pattern emergence, landscape-scale routing of flow, as driven by the landscape's connectivity, can set up positive feedbacks that influence the rate of pattern degradation. Recent flow release experiments reveal that an additional feedback, involving phosphorus concentrations, flow, and floating vegetation communities that are abundant under low phosphorus, low flow conditions further stabilizes the alternative landscape states established through local scale sediment redistribution. Biogeochemistry-vegetation-sediment feedbacks may also be important for geomorphic development of newly emerging landscapes such as the Wax Lake Delta. There, fine sediment deposition shapes hydrogeomorphic zones with vegetation patterns that stimulate the growth of biofilm, while biofilm characteristics override the physical characteristics of vegetation canopies in determining fine sediment deposition rates and influence nitrogen and carbon biogeochemistry. Emerging tools and data streams, such as information flow analysis of lidar-derived vegetation biovolume and topography, can help identify the relative roles of autogenic vs. external forcing in these landscapes.

Diagnostic Utility of the Bannatyne WISC-III Pattern. Learning Disabilities Practice

ERIC Educational Resources Information Center

Smith, Courtney B.; Watkins, Marley W.

2004-01-01

Regrouping Wechsler Intelligence Scale for Children-Third Edition (WISC-III) subtests into Bannatyne's spatial, conceptual, and sequential patterns has been thought by many to identify children with learning disabilities (LD). This study investigated the prevalence and diagnostic utility of WISC-III Bannatyne patterns by comparing 1,302 children…

Possible effects of two-phase flow pattern on the mechanical behavior of mudstones

NASA Astrophysics Data System (ADS)

Goto, H.; Tokunaga, T.; Aichi, M.

2016-12-01

To investigate the influence of two-phase flow pattern on the mechanical behavior of mudstones, laboratory experiments were conducted. In the experiment, air was injected from the bottom of the water-saturated Quaternary Umegase mudstone sample under hydrostatic external stress condition. Both axial and circumferential strains at half the height of the sample and volumetric discharge of water at the outlet were monitored during the experiment. Numerical simulation of the experiment was tried by using a simulator which can solve coupled two-phase flow and poroelastic deformation assuming the extended-Darcian flow with relative permeability and capillary pressure as functions of the wetting-phase fluid saturation. In the numerical simulation, the volumetric discharge of water was reproduced well while both strains were not. Three dimensionless numbers, i.e., the viscosity ratio, the Capillary number, and the Bond number, which characterize the two-phase flow pattern (Lenormand et al., 1988; Ewing and Berkowitz, 1998) were calculated to be 2×10-2, 2×10-11, and 7×10-11, respectively, in the experiment. Because the Bond number was quite small, it was possible to apply Lenormand et al. (1988)'s diagram to evaluate the flow regime, and the flow regime was considered to be capillary fingering. While, in the numerical simulation, air moved uniformly upward with quite low non-wetting phase saturation conditions because the fluid flow obeyed the two-phase Darcy's law. These different displacement patterns developed in the experiment and assumed in the numerical simulation were considered to be the reason why the deformation behavior observed in the experiment could not be reproduced by numerical simulation, suggesting that the two-phase flow pattern could affect the changes of internal fluid pressure patterns during displacement processes. For further studies, quantitative analysis of the experimental results by using a numerical simulator which can solve the coupled processes of two-phase flow through preferential flow paths and deformation of porous media is needed. References: Ewing R. P., and B. Berkowitz (1998), Water Resour. Res., 34, 611-622. Lenormand, R., E. Touboul, and C. Zarcone (1988), J. Fluid Mech., 189, 165-187.

Complexity of spatiotemporal traffic phenomena in flow of identical drivers: Explanation based on fundamental hypothesis of three-phase theory

NASA Astrophysics Data System (ADS)

Kerner, Boris S.

2012-03-01

Based on numerical simulations of a stochastic three-phase traffic flow model, we reveal the physics of the fundamental hypothesis of three-phase theory that, in contrast with a fundamental diagram of classical traffic flow theories, postulates the existence of a two-dimensional (2D) region of steady states of synchronized flow where a driver makes an arbitrary choice of a space gap (time headway) to the preceding vehicle. We find that macroscopic and microscopic spatiotemporal effects of the entire complexity of traffic congestion observed up to now in real measured traffic data can be explained by simulations of traffic flow consisting of identical drivers and vehicles, if a microscopic model used in these simulations incorporates the fundamental hypothesis of three-phase theory. It is shown that the driver's choice of space gaps within the 2D region of synchronized flow associated with the fundamental hypothesis of three-phase theory can qualitatively change types of congested patterns that can emerge at a highway bottleneck. In particular, if drivers choose long enough spaces gaps associated with the fundamental hypothesis, then general patterns, which consist of synchronized flow and wide moving jams, do not emerge independent of the flow rates and bottleneck characteristics: Even at a heavy bottleneck leading to a very low speed within congested patterns, only synchronized flow patterns occur in which no wide moving jams emerge spontaneously.

Complexity of spatiotemporal traffic phenomena in flow of identical drivers: explanation based on fundamental hypothesis of three-phase theory.

PubMed

Kerner, Boris S

2012-03-01

Based on numerical simulations of a stochastic three-phase traffic flow model, we reveal the physics of the fundamental hypothesis of three-phase theory that, in contrast with a fundamental diagram of classical traffic flow theories, postulates the existence of a two-dimensional (2D) region of steady states of synchronized flow where a driver makes an arbitrary choice of a space gap (time headway) to the preceding vehicle. We find that macroscopic and microscopic spatiotemporal effects of the entire complexity of traffic congestion observed up to now in real measured traffic data can be explained by simulations of traffic flow consisting of identical drivers and vehicles, if a microscopic model used in these simulations incorporates the fundamental hypothesis of three-phase theory. It is shown that the driver's choice of space gaps within the 2D region of synchronized flow associated with the fundamental hypothesis of three-phase theory can qualitatively change types of congested patterns that can emerge at a highway bottleneck. In particular, if drivers choose long enough spaces gaps associated with the fundamental hypothesis, then general patterns, which consist of synchronized flow and wide moving jams, do not emerge independent of the flow rates and bottleneck characteristics: Even at a heavy bottleneck leading to a very low speed within congested patterns, only synchronized flow patterns occur in which no wide moving jams emerge spontaneously.

Diagnostic value of high-resolution B-mode and power-mode sonography in the follow-up of thyroid cancer.

PubMed

Görges, Rainer; Eising, E G; Fotescu, D; Renzing-Köhler, K; Frilling, A; Schmid, K W; Bockisch, A; Dirsch, O

2003-02-01

Ultrasonography is an established diagnostic modality in the follow-up of thyroid cancer. Color flow Doppler has been proposed by some authors as an additional tool for differentiating benign from malignant cervical lesions in various types of head and neck cancer. Over the last few years, a new generation of high-resolution ultrasound platforms with the "power-mode" feature has become available, that also enables the imaging of small vessel blood flow. The objective of our study was to find ways of optimizing the differentiation of benign and malignant cervical tumors in thyroid cancer follow-up by means of sonography. Hundred and twelve cervical lesions in 90 patients with thyroid cancer were evaluated by high-end ultrasonography (Sonoline Elegra, Siemens) using a small-part transducer (7.5 L 40, Siemens). B-mode sonography was performed at a frequency of 8 MHz. The Solbiati index (SI= ratio of largest to smallest diameter), configuration, echogenicity, intranodular structures, and margins were assessed. Perinodular and intranodular blood flow was evaluated by color flow Doppler (PRF 1250 Hz for conventional color flow Doppler, 868 Hz for power-mode Doppler). Possible malignancy was validated by histology, cytology, scintigraphy, and follow-up. Thirty five lesions were benign (diameter 0.4-3.0 cm) and 77 were malignant (0.4-5.4 cm). The patients were randomized into a test group and a learning group to determine the diagnostic value of various ultrasound criteria by means of statistical analysis. In the learning group, decision rules based on the dichotomized criteria were developed using a logistic regression model. Sensitivity and specificity of these decision rules were then evaluated in the test group. The presence of an echocomplex pattern or irregular hyperechoic small intranodular structures (criterion A) and the presence of an irregular diffuse intranodular blood flow (criterion B) are the best indicators of malignancy, whereas an SI >2 is highly indicative of benign changes. Color flow Doppler is a useful addition to B-mode scanning for distinguishing benign and malignant neoplasms in the follow-up of thyroid cancer. Power-mode Doppler sonography significantly improves imaging of perinodular and intranodular blood flow when compared with conventional color flow Doppler. We propose the following decision rules based on a combination of the criteria above: (A) and (B) fulfilled: malignant, if SI< or =4; (B) but not (A) fulfilled: malignant, if SI< or =3; (A) but not (B) fulfilled: malignant, if SI< or =2; neither (A) nor (B) fulfilled: malignant, if SI approximately equal to 1 (sensitivity: 90%; specificity: 82%; accuracy 88%).

Using pattern enumeration to accelerate process development and ramp yield

NASA Astrophysics Data System (ADS)

Zhuang, Linda; Pang, Jenny; Xu, Jessy; Tsai, Mengfeng; Wang, Amy; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh; Ding, Hua

2016-03-01

During a new technology node process setup phase, foundries do not initially have enough product chip designs to conduct exhaustive process development. Different operational teams use manually designed simple test keys to set up their process flows and recipes. When the very first version of the design rule manual (DRM) is ready, foundries enter the process development phase where new experiment design data is manually created based on these design rules. However, these IP/test keys contain very uniform or simple design structures. This kind of design normally does not contain critical design structures or process unfriendly design patterns that pass design rule checks but are found to be less manufacturable. It is desired to have a method to generate exhaustive test patterns allowed by design rules at development stage to verify the gap of design rule and process. This paper presents a novel method of how to generate test key patterns which contain known problematic patterns as well as any constructs which designers could possibly draw based on current design rules. The enumerated test key patterns will contain the most critical design structures which are allowed by any particular design rule. A layout profiling method is used to do design chip analysis in order to find potential weak points on new incoming products so fab can take preemptive action to avoid yield loss. It can be achieved by comparing different products and leveraging the knowledge learned from previous manufactured chips to find possible yield detractors.

Active learning strategies for the deduplication of electronic patient data using classification trees.

PubMed

Sariyar, M; Borg, A; Pommerening, K

2012-10-01

Supervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether a simple active learning strategy using binary comparison patterns is sufficient or if string metrics together with a more sophisticated algorithm are necessary to achieve high accuracies with a small training set. Based on medical registry data with different numbers of attributes, we used active learning to acquire training sets for classification trees, which were then used to classify the remaining data. Active learning for binary patterns means that every distinct comparison pattern represents a stratum from which one item is sampled. Active learning for patterns consisting of the Levenshtein string metric values uses an iterative process where the most informative and representative examples are added to the training set. In this context, we extended the active learning strategy by Sarawagi and Bhamidipaty (2002). On the original data set, active learning based on binary comparison patterns leads to the best results. When dropping four or six attributes, using string metrics leads to better results. In both cases, not more than 200 manually reviewed training examples are necessary. In record linkage applications where only forename, name and birthday are available as attributes, we suggest the sophisticated active learning strategy based on string metrics in order to achieve highly accurate results. We recommend the simple strategy if more attributes are available, as in our study. In both cases, active learning significantly reduces the amount of manual involvement in training data selection compared to usual record linkage settings. Copyright © 2012 Elsevier Inc. All rights reserved.

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

PubMed

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

Influence of fast advective flows on pattern formation of Dictyostelium discoideum

PubMed Central

Bae, Albert; Zykov, Vladimir; Bodenschatz, Eberhard

2018-01-01

We report experimental and numerical results on pattern formation of self-organizing Dictyostelium discoideum cells in a microfluidic setup under a constant buffer flow. The external flow advects the signaling molecule cyclic adenosine monophosphate (cAMP) downstream, while the chemotactic cells attached to the solid substrate are not transported with the flow. At high flow velocities, elongated cAMP waves are formed that cover the whole length of the channel and propagate both parallel and perpendicular to the flow direction. While the wave period and transverse propagation velocity are constant, parallel wave velocity and the wave width increase linearly with the imposed flow. We also observe that the acquired wave shape is highly dependent on the wave generation site and the strength of the imposed flow. We compared the wave shape and velocity with numerical simulations performed using a reaction-diffusion model and found excellent agreement. These results are expected to play an important role in understanding the process of pattern formation and aggregation of D. discoideum that may experience fluid flows in its natural habitat. PMID:29590179

Experimental investigation of heat transfer and flow pattern from heated horizontal rectangular fin array under natural convection

NASA Astrophysics Data System (ADS)

Taji, S. G.; Parishwad, G. V.; Sane, N. K.

2014-07-01

This paper presents results of the experimental study conducted on heated horizontal rectangular fin array under natural convection. The temperature mapping and the prediction of the flow patterns over the fin array with variable fin spacing is carried out. Dimensionless fin spacing to height (S/H) ratio is varied from 0.05 to 0.3 and length to height ratio (L/H) = 5 is kept constant. The heater input to the fin array assembly is varied from 25 to 100 W. The single chimney flow pattern is observed from 8 to 12 mm fin spacing. The end flow is choked below 6 mm fin spacing. The single chimney flow pattern changes to sliding or end flow choking at 6 mm fin spacing. The average heat transfer coefficient (ha) is very small (2.52-5.78 W/m2 K) at 100 W for S = 5-12 mm. The ha is very small (1.12-1.8 W/m2 K) at 100 W for 2-4 mm fin spacing due to choked fin array end condition. The end flow is not sufficient to reach up to central portion of fin array and in the middle portion there is an unsteady down and up flow pattern resulting in sliding chimney. The central bottom portion of fin array channel does not contribute much in heat dissipation for S = 2-4 mm. The ha has significantly improved at higher spacing as compared to lower spacing region. The single chimney flow pattern is preferred from heat transfer point of view. The optimum spacing is confirmed in the range of 8-10 mm. The average heat transfer results are compared with previous literature and showed similar trend and satisfactory agreement. An empirical equation has been proposed to correlate the average Nusselt number as a function of Grashof number and fin spacing to height ratio. The average error for this equation is -0.32 %.

Testing the limits of long-distance learning: learning beyond a three-segment window.

PubMed

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones because long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant-harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ("sh") and triggered a suffix that was either [-su] or [-∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. Copyright © 2012 Cognitive Science Society, Inc.

Unifying cost and information in information-theoretic competitive learning.

PubMed

Kamimura, Ryotaro

2005-01-01

In this paper, we introduce costs into the framework of information maximization and try to maximize the ratio of information to its associated cost. We have shown that competitive learning is realized by maximizing mutual information between input patterns and competitive units. One shortcoming of the method is that maximizing information does not necessarily produce representations faithful to input patterns. Information maximizing primarily focuses on some parts of input patterns that are used to distinguish between patterns. Therefore, we introduce the cost, which represents average distance between input patterns and connection weights. By minimizing the cost, final connection weights reflect input patterns well. We applied the method to a political data analysis, a voting attitude problem and a Wisconsin cancer problem. Experimental results confirmed that, when the cost was introduced, representations faithful to input patterns were obtained. In addition, improved generalization performance was obtained within a relatively short learning time.

Accumulation, metabolism and toxicity of parathion in tadpoles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hall, R.J.

1990-04-01

Earlier work exposing tadpoles to organophosphorus pesticides indicated the great resistance of tadpoles of the bullfrog (Rana catesbeiana) to these chemicals and their surprising ability to accumulate parathion and fenthion from water. These qualities seemed to make them an ideal model with which to test a hypothesis advanced by Burke and Ferguson, who noted that parathion is more toxic to resistant mosquitofish in static water than in flowing water--a reversal of the pattern normally seen. They believed that highly toxic metabolite paraoxon was produced by the fish and that its buildup in static systems resulted in the unexpected mortality. Amphibiansmore » have been shown to produce paraoxon and to accumulate the parent compound parathion to levels that are potentially hazardous to other organisms. In the course of examining paraoxon production by tadpoles, it would also be possible to learn more about their patterns of parathion uptake and elimination. Retention of residues is also a matter of concern given the high levels observed in the earlier studies.« less

Atypical performance patterns on Delis-Kaplan Executive Functioning System Color-Word Interference Test: Cognitive switching and learning ability in older adults.

PubMed

Berg, Jody-Lynn; Swan, Natasha M; Banks, Sarah J; Miller, Justin B

2016-09-01

Cognitive set shifting requires flexible application of lower level processes. The Delis-Kaplan Executive Functioning System (DKEFS) Color-Word Interference Test (CWIT) is commonly used to clinically assess cognitive set shifting. An atypical pattern of performance has been observed on the CWIT; a subset of individuals perform faster, with equal or fewer errors, on the more difficult inhibition/switching than the inhibition trial. This study seeks to explore the cognitive underpinnings of this atypical pattern. It is hypothesized that atypical patterns on CWIT will be associated with better performance on underlying cognitive measures of attention, working memory, and learning when compared to typical CWIT patterns. Records from 239 clinical referrals (age: M = 68.09 years, SD = 10.62; education: M = 14.87 years, SD = 2.73) seen for a neuropsychological evaluation as part of diagnostic work up in an outpatient dementia and movement disorders clinic were sampled. The standard battery of tests included measures of attention, learning, fluency, executive functioning, and working memory. Analyses of variance (ANOVAs) were conducted to compare the cognitive performance of those with typical versus atypical CWIT patterns. An atypical pattern of performance was confirmed in 23% of our sample. Analyses revealed a significant group difference in acquisition of information on both nonverbal (Brief Visuospatial Memory Test-Revised, BVMT-R total recall), F(1, 213) = 16.61, p < .001, and verbal (Hopkins Verbal Learning Test-Revised, HVLT-R total recall) learning tasks, F(1, 181) = 6.43, p < .01, and semantic fluency (Animal Naming), F(1, 232) = 7.57, p = .006, with the atypical group performing better on each task. Effect sizes were larger for nonverbal (Cohen's d = 0.66) than verbal learning (Cohen's d = 0.47) and semantic fluency (Cohen's d = 0.43). Individuals demonstrating an atypical pattern of performance on the CWIT inhibition/switching trial also demonstrated relative strengths in semantic fluency and learning.

Numerical modelling of strain in lava tubes

NASA Astrophysics Data System (ADS)

Merle, Olivier

The strain within lava tubes is described in terms of pipe flow. Strain is partitioned into three components: (a) two simple shear components acting from top to bottom and from side to side of a rectangular tube in transverse section; and (b) a pure shear component corresponding to vertical shortening in a deflating flow and horizontal compression in an inflating flow. The sense of shear of the two simple shear components is reversed on either side of a central zone of no shear. Results of numerical simulations of strain within lava tubes reveal a concentric pattern of flattening planes in section normal to the flow direction. The central node is a zone of low strain, which increases toward the lateral borders. Sections parallel to the flow show obliquity of the flattening plane to the flow axis, constituting an imbrication. The strain ellipsoid is generally of plane strain type, but can be of constriction or flattening type if thinning (i.e. deflating flow) or thickening (i.e. inflating flow) is superimposed on the simple shear regime. The strain pattern obtained from numerical simulation is then compared with several patterns recently described in natural lava flows. It is shown that the strain pattern revealed by AMS studies or crystal preferred orientations is remarkably similar to the numerical simulation. However, some departure from the model is found in AMS measurements. This may indicate inherited strain recorded during early stages of the flow or some limitation of the AMS technique.

Transthoracic Ultrafast Doppler Imaging of Human Left Ventricular Hemodynamic Function

PubMed Central

Osmanski, Bruno-Félix; Maresca, David; Messas, Emmanuel; Tanter, Mickael; Pernot, Mathieu

2016-01-01

Heart diseases can affect intraventricular blood flow patterns. Real-time imaging of blood flow patterns is challenging because it requires both a high frame rate and a large field of view. To date, standard Doppler techniques can only perform blood flow estimation with high temporal resolution within small regions of interest. In this work, we used ultrafast imaging to map in 2D human left ventricular blood flow patterns during the whole cardiac cycle. Cylindrical waves were transmitted at 4800 Hz with a transthoracic phased array probe to achieve ultrafast Doppler imaging of the left ventricle. The high spatio-temporal sampling of ultrafast imaging permits to rely on a much more effective wall filtering and to increase sensitivity when mapping blood flow patterns during the pre-ejection, ejection, early diastole, diastasis and late diastole phases of the heart cycle. The superior sensitivity and temporal resolution of ultrafast Doppler imaging makes it a promising tool for the noninvasive study of intraventricular hemodynamic function. PMID:25073134

Multiple Near Wake Patterns Behind Annular Rings

NASA Astrophysics Data System (ADS)

Zhang, Jinzhong; Higuchi, Hiroshi; Muzas, Brian K.; Furuya, Shojiro

1996-11-01

Wake interactions behind concentric annular rings at different spacing ratios were experimentally investigated. The flow visualization, laser Doppler velocimetry data and results from the particle tracking velocimetry are presented and discussed. Jets through individual slots merged in multiply-stable, axisymmetric manners. Most flow patterns were persistent unless the flow was strongly disturbed. The vortex interactions from individual annular elements were also axisymmetric in the near wake. This is in contrast to the asymmetric flows observed earlier behind two-dimensional slotted plates (Higuchi et al. J. Aircraft 26 1989, Phys. Fluids 6(1), 1994). The intermediate wake, however, was dominated by large scale, three-dimensional wake motions even at moderate porosity. Onset of the specific flow patterns was associated with the interactions among start-up vortices. Given model geometry, different turbulent structures and mean velocity profiles were observed in the intermediate wake depending on the near wake pattern. *BKM was a NSF-REU Program undergrad. from Princeton U. and SF was from Mitsubishi Heavy Industries. This work was suppoted in part by the Naval Air Warfare Center.

Subtidal circulation patterns in a shallow, highly stratified estuary: Mobile Bay, Alabama

USGS Publications Warehouse

Noble, M.A.; Schroeder, W.W.; Wiseman, W.J.; Ryan, H.F.; Gelfenbaum, G.

1996-01-01

Mobile Bay is a wide (25-50 km), shallow (3 m), highly stratified estuary on the Gulf coast of the United States. In May 1991 a series of instruments that measure near-surface and near-bed current, temperature, salinity, and middepth pressure were deployed for a year-long study of the bay. A full set of measurements were obtained at one site in the lower bay; all but current measurements were obtained at a midbay site. These observations show that the subtidal currents in the lower bay are highly sheared, despite the shallow depth of the estuary. The sheared flow patterns are partly caused by differential forcing from wind stress and river discharge. Two wind-driven flow patterns actually exist in lower Mobile Bay. A barotropic response develops when the difference between near-surface and near-bottom salinity is less than 5 parts per thousand. For stronger salinity gradients the wind-driven currents are larger and the response resembles a baroclinic flow pattern. Currents driven by river flows are sheared and also have a nonlinear response pattern. Only near-surface currents are driven seaward by discharges below 3000 m3/s. At higher discharge rates, surface current variability uncouples from the river flow and the increased discharge rates drive near-bed current seaward. This change in the river-forced flow pattern may be associated with a hydraulic jump in the mouth of the estuary. Copyright 1996 by the American Geophysical Union.

Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

PubMed

Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

2018-04-01

Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

Vortex shedding in bileaflet heart valve prostheses.

PubMed

Gross, J M; Shermer, C D; Hwang, N H

1988-01-01

A dynamic study of two geometrically similar bileaflet heart valve prostheses (HVP) was performed using a physiologic mock circulatory flow loop. The HVPs studied were the 25 mm St. Jude Medical (SJM) and the 25 mm Carbomedics (CMI) in the aortic position and the 27 mm SJM and 27 mm CMI in the mitral position. All data were collected at a heart rate of 70 beats/min and a cardiac output of 5.0 L/min. Flow visualization was conducted in the transparent flow chambers of the pulsatile mock circulatory flow loop using a 15 mW He-Ne laser light source. A cylindrical lens and optics system converted the incident laser beam into a thin parallel light plane, and 420 microns tracer particles were suspended in the testing fluid to illuminate the flow field at selected planes. Frame-by-frame analysis of the 16 mm high-speed cine provides detailed phasic flow patterns in the vicinity of the HVP. A series of still photographs of flow patterns, taken at approximately 22.5 degrees phase intervals, are sequentially presented for each HVP. In the aortic position, a Karman-like vortex pattern appears downstream of the SJM at the end of the ejection phase. The CMI exhibits a rather symmetrical ejection flow pattern that turns into random motion immediately after the onset of ejection. In the mitral position, the SJM again exhibits a strong core flow during ventricular filling, whereas the CMI produces a more diffuse pattern during the same period. A pair of vortices shed from both the SJM and CMI are clearly visible toward the end of the ventricular filling phase. The vortex mechanisms are discussed in light of leaflet boundary layer formation.

Experimental study on hydraulic characteristic around trash rack of a pumping station

NASA Astrophysics Data System (ADS)

Zhou, MinZhe; Li, TongChun; Lin, XiangYang; Liu, XiaoQing; Ding, Yuan; Liu, GuangYuan

2017-11-01

This paper focuses on flow pattern around trash rack of intake of a pumping station project. This pumping station undertake the task of supplying up to 3,500,000 m3 water per day for a megacity. Considering the large flow rate, high lift, multi-pipe supply and long-time operation in this water conveyance pumping station, we built a physical model test to measure the flow velocity and observe the flow pattern to verify the reasonability of preliminary design. In this test, we set 3 layers of current meters around each trash rack of intake in reservoir to collect the flow velocity. Furthermore, we design 2 operating conditions of 9 pumps to observe the change of flow pattern. Finally, we found the velocity data were in a normal range under 2 different operating conditions of the 9 pump units.

Retention time and flow patterns in Lake Marion, South Carolina, 1984

USGS Publications Warehouse

Patterson, G.G.; Harvey, R.M.

1995-01-01

In 1984, six dye tracer tests were made on Lake Marion to determine flow patterns and retention times under conditions of high and low flow. During the high-flow tests, with an average inflow of about 29,000 cubic feet per second, the approximate travel time through the lake for the peak tracer concentration was 14 days. The retention time was about 20 days. During the low-flow tests, with an average inflow of about 9,000 cubic feet per second, the approximate travel time was 41 days, and the retention time was about 60 days. The primary factors controlling movement of water in the lake are lake inflow and outflow. The tracer cloud moved consistently downstream, slowing as the lake widened. Flow patterns in most of the coves, and in some areas along the northeastern shore, are influenced more by tributary inflow than by factors attributable to water from the main body of the lake.

Children's Discourse in Cooperative and Didactic Interaction: Developmental Patterns in Effective Learning.

ERIC Educational Resources Information Center

Cooper, Catherine R.; And Others

Experimental and supplementary observational studies of how children help one another learn are reported. In the experiment, developmental patterns in children's discourse in two common peer-learning situations were investigated. Sixty-four pairs of children, drawn equally from kindergarten and second grade, participated in the study. Dyads,…

Using Learning Styles and Viewing Styles in Streaming Video

ERIC Educational Resources Information Center

de Boer, Jelle; Kommers, Piet A. M.; de Brock, Bert

2011-01-01

Improving the effectiveness of learning when students observe video lectures becomes urgent with the rising advent of (web-based) video materials. Vital questions are how students differ in their learning preferences and what patterns in viewing video can be detected in log files. Our experiments inventory students' viewing patterns while watching…

Patterns of Indigenous Learning: An Ethnographic Study on How Kindergartners Learn in Mana, Fiji

ERIC Educational Resources Information Center

Lee, Chih-Yih; Sparks, Paul

2015-01-01

Technology has greatly impacted educational systems around the world, even in the most geographically isolated places. This study utilizes an ethnographic approach to examine the patterns of learning in a kindergarten in Mana, Fiji. Data comprised of interviews, observations and examination of related artifacts. The results provide baseline data…

Identifying Learning Patterns of Children at Risk for Specific Reading Disability

ERIC Educational Resources Information Center

Barbot, Baptiste; Krivulskaya, Suzanna; Hein, Sascha; Reich, Jodi; Thuma, Philip E.; Grigorenko, Elena L.

2016-01-01

Differences in learning patterns of vocabulary acquisition in children at risk (+SRD) and not at risk (-SRD) for Specific Reading Disability (SRD) were examined using a microdevelopmental paradigm applied to the multi-trial Foreign Language Learning Task (FLLT; Baddeley et al., 1995). The FLLT was administered to 905 children from rural…

Fashion Students Choose How to Learn by Constructing Videos of Pattern Making

ERIC Educational Resources Information Center

Cavanagh, Michaella; Peté, Marí

2017-01-01

This paper analyses new learning experiences of first year pattern technology students at a university of technology, in the context of selected characteristics of authentic learning theories. The paper contributes to existing knowledge by proposing a method that could be followed for design-based subjects in a vocational education setting.…

WISC-R Subtest Pattern Stability and Learning Disabilities: A Profile Analysis.

ERIC Educational Resources Information Center

Mealor, David J.; Abrams, Pamela F.

Profile analysis was performed on Wechsler Intelligence Scale for Children-Revised (WISC-R) scores of 29 learning disabled students (6-10 years old) in a Specific Learning Disabilities (SLD) program, to determine whether subtest patterns for initial and re-evaluation WISC-R administrations would differ significantly. Profile analysis was applied…

PUPIL-TEACHER ADJUSTEMENT AND MUTUAL ADAPTATION IN CREATING CLASSROOM LEARNING ENVIRONMENTS.

ERIC Educational Resources Information Center

FOX, ROBERT S.; AND OTHERS

AN ANALYSIS OF THE DYNAMICS OF THE LEARNING SITUATIONS IN A VARIETY OF PUBLIC SCHOOL CLASSROOMS WAS UNDERTAKEN. THE PROJECT MADE A COMPARATIVE ANALYSIS OF THE PATTERNS OF COOPERATION OR ALIENATION AMONG PARENTS, TEACHERS, PEERS, AND INDIVIDUAL PUPILS. THE PATTERNS CREATE LEARNING CULTURES OF DIFFERENT PRODUCTIVITY IN VARIOUS CLASSROOMS. THE DATA…

Elementary School Students' Strategic Learning: Does Task-Type Matter?

ERIC Educational Resources Information Center

Malmberg, Jonna; Järvelä, Sanna; Kirschner, Paul A.

2014-01-01

This study investigated what types of learning patterns and strategies elementary school students use to carry out ill- and well-structured tasks. Specifically, it was investigated which and when learning patterns actually emerge with respect to students' task solutions. The present study uses computer log file traces to investigate how…

The Development of Group Interaction Patterns: How Groups become Adaptive, Generative, and Transformative Learners

ERIC Educational Resources Information Center

London, Manuel; Sessa, Valerie I.

2007-01-01

This article integrates the literature on group interaction process analysis and group learning, providing a framework for understanding how patterns of interaction develop. The model proposes how adaptive, generative, and transformative learning processes evolve and vary in their functionality. Environmental triggers for learning, the group's…

Waveform classification and statistical analysis of seismic precursors to the July 2008 Vulcanian Eruption of Soufrière Hills Volcano, Montserrat

NASA Astrophysics Data System (ADS)

Rodgers, Mel; Smith, Patrick; Pyle, David; Mather, Tamsin

2016-04-01

Understanding the transition between quiescence and eruption at dome-forming volcanoes, such as Soufrière Hills Volcano (SHV), Montserrat, is important for monitoring volcanic activity during long-lived eruptions. Statistical analysis of seismic events (e.g. spectral analysis and identification of multiplets via cross-correlation) can be useful for characterising seismicity patterns and can be a powerful tool for analysing temporal changes in behaviour. Waveform classification is crucial for volcano monitoring, but consistent classification, both during real-time analysis and for retrospective analysis of previous volcanic activity, remains a challenge. Automated classification allows consistent re-classification of events. We present a machine learning (random forest) approach to rapidly classify waveforms that requires minimal training data. We analyse the seismic precursors to the July 2008 Vulcanian explosion at SHV and show systematic changes in frequency content and multiplet behaviour that had not previously been recognised. These precursory patterns of seismicity may be interpreted as changes in pressure conditions within the conduit during magma ascent and could be linked to magma flow rates. Frequency analysis of the different waveform classes supports the growing consensus that LP and Hybrid events should be considered end members of a continuum of low-frequency source processes. By using both supervised and unsupervised machine-learning methods we investigate the nature of waveform classification and assess current classification schemes.

Structural Analysis of Silicic Lavas Reveals the Importance of Endogenous Flow During Emplacement

NASA Astrophysics Data System (ADS)

Andrews, G. D.; Martens, A.; Isom, S.; Maxwell, A.; Brown, S. R.

2017-12-01

Recent observations of silicic lava flows in Chile strongly suggest sustained, endogeneous flow beneath an insulating carapace, where the flow advances through breakouts at the flow margin. New mapping of vertical exposures around the margin of Obsidian Dome, California, has identified discreet lobe structures in cross-section, suggesting that flow-front breakouts occured there during emplacement. The flow lobes are identified through structural measurements of flow-banding orientation and the stretching directions of vesicles. Newly acquired lidar of the Inyo Domes, including Obsidian Dome, is being analyzed to better understand the patterns of folding on the upper surface of the lavas, and to test for fold vergence patterns that may distinguish between endogenous and exogenous flow.

Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend

USGS Publications Warehouse

Engel, Frank; Rhoads, Bruce L.

2016-01-01

Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.

Simulation of tidal flow and circulation patterns in the Loxahatchee River Estuary, southeastern Florida

USGS Publications Warehouse

Russell, G.M.; Goodwin, C.R.

1987-01-01

Results of a two-dimensional, vertically averaged, computer simulation model of the Loxahatchee River estuary show that under typical low freshwater inflow and vertically well mixed conditions, water circulation is dominated by freshwater inflow rather than by tidal influence. The model can simulate tidal flow and circulation in the Loxahatchee River estuary under typical low freshwater inflow and vertically well mixed conditions, but is limited, however, to low-flow and well mixed conditions. Computed patterns of residual water transport show a consistent seaward flow from the northwest fork through the central embayment and out Jupiter Inlet to the Atlantic Ocean. A large residual seaward flow was computed from the North Intracoastal Waterway to the inlet channel. Although the tide produces large flood and ebb flows in the estuary, tide-induced residual transport rates are low in comparison with freshwater-induced residual transport. Model investigations of partly mixed or stratified conditions in the estuary need to await development of systems capable of simulating three-dimensional flow patterns. (Author 's abstract)

Flow of two immiscible fluids in a periodically constricted tube: Transitions to stratified, segmented, churn, spray or segregated flow

NASA Astrophysics Data System (ADS)

Tsamopoulos, John; Fraggedakis, Dimitris; Dimakopoulos, Yiannis

2015-11-01

We study the flow of two immiscible, Newtonian fluids in a periodically constricted tube driven by a constant pressure gradient. Our Volume-of-Fluid algorithm is used to solve the governing equations. First the code is validated by comparing its predictions to previously reported results for stratified and pulsing flow. Then it is used to capture accurately all the significant topological changes that take place. Initially, the fluids have a core-annular arrangement, which is found to either remain the same or change to a different arrangement depending on the fluid properties, the pressure driving the flow or the flow geometry. The flow-patterns that appear are the core-annular, segmented, churn, spray and segregated flow. The predicted scalings near pinching of the core fluid concur with similarity predictions and earlier numerical results (Cohen et al. (1999)). Flow-pattern maps are constructed in terms of the Reynolds and Weber numbers. Our results provide deeper insights in the mechanism of the pattern transitions and are in agreement with previous studies on core-annular flow (Kouris & Tsamopoulos (2001 & 2002)), segmented flow (Lac & Sherwood (2009)) and churn flow (Bai et al. (1992)). GSRT of Greece through the program ``Excellence'' (Grant No. 1918, entitled ``FilCoMicrA'').

On the pulse boiling frequency in thermosyphons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, J.F.; Wang, J.C.Y.

1992-02-01

The unsteady periodic boiling phenomenon, pulse boiling, appearing in the evaporator of thermosyphons has been mentioned and investigated by many researchers. The heat transfer coefficient in evaporators was predicted according to different considerations of flow patterns. For instance, Shiraishi et al. proposed a method based on a combination flow pattern: the nucleate boiling in a liquid pool and the evaporation from a falling condensate film. Liu et al. only considered a pure pulse boiling flow pattern, and Xin et al. focused on the flow pattern of the continuous boiling process without pulse phenomenon. Besides, the forming conditions of pulse boilingmore » were also described differently. Xin et al. also reported that pulse boiling cannot occur in a carbon-steel/water heat pipe; Ma et al., however, observed this phenomenon in a carbon-steel/water thermosyphon. Nearly all researchers mentioned that this phenomenon indeed exists in glass/water thermosyphons. Although the influential factors have been discussed qualitatively, the quantitative analysis has yet to be conducted. This study focuses on the pulse boiling frequency as a criterion for the determination of flow patterns, and attempts are made to predict the frequency both experimentally and theoretically.« less

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Characterization of Sheet Fracture Patterns in Polygonal-Jointed Lavas at Kokostick Butte, OR, and Mazama Ridge, WA: Investigation and Interpretation of Their Formation and Significance

NASA Astrophysics Data System (ADS)

Lodge, R. W.; Lescinsky, D. T.

2006-12-01

Polygonal joints in lava flows ("columns") are commonly equant leading to a model of formation associated with cooling in an isotropic stress field. This model, however, does not explain rectangular columns, sheet-like fractures, fractures with crosscutting relationships, and fractures with orientations other than perpendicular to the cooling surface. These fracture patterns are often observed at glaciated volcanoes. The presence of preferential fracture orientations suggests an applied stress component likely due to environmental conditions such as the presence of glaciers or flow dynamics such as down-slope settling or flow margin inflation. During this study we investigated the formation and significance of these non-equant fracture patterns to propose a model for their formation. These `abnormal' fracture patterns have not been discussed in the literature and may be important to better understanding the cooling conditions of such lava flows. To test these possibilities we studied Kokostick Butte dacite flow, OR (near South Sister), and Mazama Ridge andesite flow at Mount Rainier, WA. Both of these flows have well developed sheet-like fractures and display evidence of ice-contact during eruption and emplacement. Sheet fractures are long and continuous fractures that have perpendicular connecting fractures forming rectangular columns. The sheet-like fractures are largely parallel to each other on the exposure surface and the connecting fractures vary locally from primary fractures (associated with cooling toward flow interior) to secondary fractures (associated with cooling by water infiltration). Detailed measurements of fracture orientations and spacing were collected at Kokostick Butte and Mazama Ridge to examine the relationship between the sheet fractures and flow geometry. Preliminary results support this relationship and suggest these patterns likely form due to shear associated with small amounts of flow advance by the rapidly cooling lava. Laboratory studies have been undertaken to complement the field observations and measurements. Starch- water experiments have been proven a useful analogue for lava column formation. Various experimental setups involving different mixture thicknesses and compression of the mixture were utilized to simulate the stresses acting during ponding of lava against glacial ice and to produce different fracture morphologies and patterns. Initial results show that compression of the starch slurry results in non-equant fracture patterns with some sheet-like fracturing present.

Investigation of Contingency Patterns of Teachers' Scaffolding in Teaching and Learning Mathematics

ERIC Educational Resources Information Center

Anwar; Yuwono, Ipung; Irawan, Edy Bambang; As'ari, Abdur Rahman

2017-01-01

The purpose of this study is to investigate the patterns of scaffolding contingency in teaching and learning mathematics carried out by three teachers. Contingency patterns are obtained by examining the transcription from video recording of conversation fragments between teachers and students during the provision of scaffolding. The contingency…

Learning and recall of form discriminations during reversible cooling deactivation of ventral-posterior suprasylvian cortex in the cat.

PubMed Central

Lomber, S G; Payne, B R; Cornwell, P

1996-01-01

Extrastriate visual cortex of the ventral-posterior suprasylvian gyrus (vPS cortex) of freely behaving cats was reversibly deactivated with cooling to determine its role in performance on a battery of simple or masked two-dimensional pattern discriminations, and three-dimensional object discriminations. Deactivation of vPS cortex by cooling profoundly impaired the ability of the cats to recall the difference between all previously learned pattern and object discriminations. However, the cats' ability to learn or relearn pattern and object discriminations while vPS was deactivated depended upon the nature of the pattern or object and the cats' prior level of exposure to them. During cooling of vPS cortex, the cats could neither learn the novel object discriminations nor relearn a highly familiar masked or partially occluded pattern discrimination, although they could relearn both the highly familiar object and simple pattern discriminations. These cooling-induced deficits resemble those induced by cooling of the topologically equivalent inferotemporal cortex of monkeys and provides evidence that the equivalent regions contribute to visual processing in similar ways. Images Fig. 1 Fig. 3 PMID:8643686

The cerebellum and visual perceptual learning: evidence from a motion extrapolation task.

PubMed

Deluca, Cristina; Golzar, Ashkan; Santandrea, Elisa; Lo Gerfo, Emanuele; Eštočinová, Jana; Moretto, Giuseppe; Fiaschi, Antonio; Panzeri, Marta; Mariotti, Caterina; Tinazzi, Michele; Chelazzi, Leonardo

2014-09-01

Visual perceptual learning is widely assumed to reflect plastic changes occurring along the cerebro-cortical visual pathways, including at the earliest stages of processing, though increasing evidence indicates that higher-level brain areas are also involved. Here we addressed the possibility that the cerebellum plays an important role in visual perceptual learning. Within the realm of motor control, the cerebellum supports learning of new skills and recalibration of motor commands when movement execution is consistently perturbed (adaptation). Growing evidence indicates that the cerebellum is also involved in cognition and mediates forms of cognitive learning. Therefore, the obvious question arises whether the cerebellum might play a similar role in learning and adaptation within the perceptual domain. We explored a possible deficit in visual perceptual learning (and adaptation) in patients with cerebellar damage using variants of a novel motion extrapolation, psychophysical paradigm. Compared to their age- and gender-matched controls, patients with focal damage to the posterior (but not the anterior) cerebellum showed strongly diminished learning, in terms of both rate and amount of improvement over time. Consistent with a double-dissociation pattern, patients with focal damage to the anterior cerebellum instead showed more severe clinical motor deficits, indicative of a distinct role of the anterior cerebellum in the motor domain. The collected evidence demonstrates that a pure form of slow-incremental visual perceptual learning is crucially dependent on the intact cerebellum, bearing the notion that the human cerebellum acts as a learning device for motor, cognitive and perceptual functions. We interpret the deficit in terms of an inability to fine-tune predictive models of the incoming flow of visual perceptual input over time. Moreover, our results suggest a strong dissociation between the role of different portions of the cerebellum in motor versus non-motor functions, with only the posterior lobe being responsible for learning in the perceptual domain. Copyright © 2014. Published by Elsevier Ltd.

Relation of coronary flow pattern to myocardial blush grade in patients with first acute myocardial infarction

PubMed Central

Hoffmann, R; Haager, P; Lepper, W; Franke, A; Hanrath, P

2003-01-01

Background: Analysis of myocardial blush grade (MBG) and coronary flow velocity pattern has been used to obtain direct or indirect information about microvascular damage and reperfusion injury after percutaneous transluminal coronary angiography for acute myocardial infarction. Objective: To evaluate the relation between coronary blood flow velocity pattern and MBG immediately after angioplasty plus stenting for acute myocardial infarction. Design: The coronary blood flow velocity pattern in the infarct related artery was determined immediately after angioplasty in 35 patients with their first acute myocardial infarct using a Doppler guide wire. Measurements were related to MBG as a direct index of microvascular function in the infarct zone. Results: Coronary flow velocity patterns were different between patients with absent myocardial blush (n = 14), reduced blush (n = 7), or normal blush (n = 14). The following variables (mean (SD)) differed significantly between the three groups: systolic peak flow velocity (cm/s): absent blush 10.9 (4.2), reduced blush 14.2 (6.4), normal blush 19.2 (11.2); p = 0.036; diastolic deceleration rate (ms): absent blush 103 (58), reduced blush 80 (65), normal blush 50 (19); p = 0.025; and diastolic–systolic velocity ratio: absent blush 4.06 (2.18), reduced blush 2.02 (0.55), normal blush 1.88 (1.03); p = 0.002. In a multivariate analysis MBG was the only variable with a significant impact on the diastolic deceleration rate (p = 0.034,) while age, infarct location, time to revascularisation, infarct vessel diameter, and maximum creatine kinase had no significant impact. Conclusions: The coronary flow velocity pattern in the infarct related epicardial artery is primarily determined by the microvascular function of the dependent myocardium, as reflected by MBG. PMID:12975402

In vivo visualization method by absolute blood flow velocity based on speckle and fringe pattern using two-beam multipoint laser Doppler velocimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kyoden, Tomoaki, E-mail: kyouden@nc-toyama.ac.jp; Naruki, Shoji; Akiguchi, Shunsuke

Two-beam multipoint laser Doppler velocimetry (two-beam MLDV) is a non-invasive imaging technique able to provide an image of two-dimensional blood flow and has potential for observing cancer as previously demonstrated in a mouse model. In two-beam MLDV, the blood flow velocity can be estimated from red blood cells passing through a fringe pattern generated in the skin. The fringe pattern is created at the intersection of two beams in conventional LDV and two-beam MLDV. Being able to choose the depth position is an advantage of two-beam MLDV, and the position of a blood vessel can be identified in a three-dimensionalmore » space using this technique. Initially, we observed the fringe pattern in the skin, and the undeveloped or developed speckle pattern generated in a deeper position of the skin. The validity of the absolute velocity value detected by two-beam MLDV was verified while changing the number of layers of skin around a transparent flow channel. The absolute velocity value independent of direction was detected using the developed speckle pattern, which is created by the skin construct and two beams in the flow channel. Finally, we showed the relationship between the signal intensity and the fringe pattern, undeveloped speckle, or developed speckle pattern based on the skin depth. The Doppler signals were not detected at deeper positions in the skin, which qualitatively indicates the depth limit for two-beam MLDV.« less

Simulating pattern-process relationships to validate landscape genetic models

Treesearch

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

Study of dynamics of two-phase flow through a minichannel by means of recurrences

NASA Astrophysics Data System (ADS)

Litak, Grzegorz; Górski, Grzegorz; Mosdorf, Romuald; Rysak, Andrzej

2017-05-01

By changing air and water flow rates in the two-phase (air-water) flow through a minichannel, we observed the evolution of air bubbles and slugs patterns. This spatiotemporal behaviour was identified qualitatively by using a digital camera. Simultaneously, we provided a detailed analysis of these phenomena by using the corresponding sequences of light transmission time series recorded with a laser-phototransistor sensor. To distinguish particular patterns, we used recurrence plots and recurrence quantification analysis. Finally, we showed that the maxima of various recurrence quantificators obtained from the laser time series could follow the bubble and slugs patterns in studied ranges of air and water flows.

The role of varying flow on channel morphology: a flume experiment

NASA Astrophysics Data System (ADS)

Hempel, L. A.; Grant, G.; Eaton, B. C.; Hassan, M. A.; Lewis, S.

2017-12-01

Numerous studies have explored how alluvial channels develop under different sediment and flow conditions, yet we still know very little about how channels adjust and respond to changing flow conditions. One reason for this oversight is the long-held idea that channels with complex flow regimes are adjusted to a single, channel-forming discharge. But growing evidence shows that channel form reflects time-dependent processes occuring over multiple flows. To better understand how stream channels adjust to a range of flows, and identify the timescales associated with those adjustments, we conducted a series of hydrograph experiments in a freely-adjustable flume that developed a self-formed, meander pattern with pool-riffle morphology. Hydrographs had different shapes, magnitudes, and durations, but the total sediment volume fed under equilibrium conditions was kept constant among experiments. We found that hydrograph shape controlled channel morphology, the rate of channel development, and degree of regularity in the pool-riffle pattern. Hydrographs with slowly rising rates of rise and fall produced channels that were equivalent in size to channels generated from constant flow experiments, and had regularly spaced pool-riffle and meander patterns, while hydrographs with fast rates of rise and fall produced undersized channels with a chaotic bed structure and pool-riffle pattern. The latter suggests that during quickly rising hydrographs, the flow rate increases faster than the channel capacity and planform pattern adjusts. We confirmed these observations by comparing the timescales associated with pool-riffle and planform curvature development, which were identified under simple, constant flow conditions, to the total duration of the hydrograph. Hydrographs with step durations equal to or longer than the channel adjustment time produced channels with a more regular pool-riffle patterns compared to channels with step durations shorter than the adjustment time. This work points to the importance of the hydrograph as a fundamental control on channel adjustment and offers the prospect of better understanding of how changes in the flow regime, either through climate, land use, or dams, translate into morphodynamic changes.

A Comparative Study of Relational Learning Capacity in Honeybees (Apis mellifera) and Stingless Bees (Melipona rufiventris)

PubMed Central

Moreno, Antonio Mauricio; de Souza, Deisy das Graças; Reinhard, Judith

2012-01-01

Background Learning of arbitrary relations is the capacity to acquire knowledge about associations between events or stimuli that do not share any similarities, and use this knowledge to make behavioural choices. This capacity is well documented in humans and vertebrates, and there is some evidence it exists in the honeybee (Apis mellifera). However, little is known about whether the ability for relational learning extends to other invertebrates, although many insects have been shown to possess excellent learning capacities in spite of their small brains. Methodology/Principal Findings Using a symbolic matching-to-sample procedure, we show that the honeybee Apis mellifera rapidly learns arbitrary relations between colours and patterns, reaching 68.2% correct choice for pattern-colour relations and 73.3% for colour-pattern relations. However, Apis mellifera does not transfer this knowledge to the symmetrical relations when the stimulus order is reversed. A second bee species, the stingless bee Melipona rufiventris from Brazil, seems unable to learn the same arbitrary relations between colours and patterns, although it exhibits excellent discrimination learning. Conclusions/Significance Our results confirm that the capacity for learning arbitrary relations is not limited to vertebrates, but even insects with small brains can perform this learning task. Interestingly, it seems to be a species-specific ability. The disparity in relational learning performance between the two bee species we tested may be linked to their specific foraging and recruitment strategies, which evolved in adaptation to different environments. PMID:23251542

A comparative study of relational learning capacity in honeybees (Apis mellifera) and stingless bees (Melipona rufiventris).

PubMed

Moreno, Antonio Mauricio; de Souza, Deisy das Graças; Reinhard, Judith

2012-01-01

Learning of arbitrary relations is the capacity to acquire knowledge about associations between events or stimuli that do not share any similarities, and use this knowledge to make behavioural choices. This capacity is well documented in humans and vertebrates, and there is some evidence it exists in the honeybee (Apis mellifera). However, little is known about whether the ability for relational learning extends to other invertebrates, although many insects have been shown to possess excellent learning capacities in spite of their small brains. Using a symbolic matching-to-sample procedure, we show that the honeybee Apis mellifera rapidly learns arbitrary relations between colours and patterns, reaching 68.2% correct choice for pattern-colour relations and 73.3% for colour-pattern relations. However, Apis mellifera does not transfer this knowledge to the symmetrical relations when the stimulus order is reversed. A second bee species, the stingless bee Melipona rufiventris from Brazil, seems unable to learn the same arbitrary relations between colours and patterns, although it exhibits excellent discrimination learning. Our results confirm that the capacity for learning arbitrary relations is not limited to vertebrates, but even insects with small brains can perform this learning task. Interestingly, it seems to be a species-specific ability. The disparity in relational learning performance between the two bee species we tested may be linked to their specific foraging and recruitment strategies, which evolved in adaptation to different environments.

Automatic OPC repair flow: optimized implementation of the repair recipe

NASA Astrophysics Data System (ADS)

Bahnas, Mohamed; Al-Imam, Mohamed; Word, James

2007-10-01

Virtual manufacturing that is enabled by rapid, accurate, full-chip simulation is a main pillar in achieving successful mask tape-out in the cutting-edge low-k1 lithography. It facilitates detecting printing failures before a costly and time-consuming mask tape-out and wafer print occur. The OPC verification step role is critical at the early production phases of a new process development, since various layout patterns will be suspected that they might to fail or cause performance degradation, and in turn need to be accurately flagged to be fed back to the OPC Engineer for further learning and enhancing in the OPC recipe. At the advanced phases of the process development, there is much less probability of detecting failures but still the OPC Verification step act as the last-line-of-defense for the whole RET implemented work. In recent publication the optimum approach of responding to these detected failures was addressed, and a solution was proposed to repair these defects in an automated methodology and fully integrated and compatible with the main RET/OPC flow. In this paper the authors will present further work and optimizations of this Repair flow. An automated analysis methodology for root causes of the defects and classification of them to cover all possible causes will be discussed. This automated analysis approach will include all the learning experience of the previously highlighted causes and include any new discoveries. Next, according to the automated pre-classification of the defects, application of the appropriate approach of OPC repair (i.e. OPC knob) on each classified defect location can be easily selected, instead of applying all approaches on all locations. This will help in cutting down the runtime of the OPC repair processing and reduce the needed number of iterations to reach the status of zero defects. An output report for existing causes of defects and how the tool handled them will be generated. The report will with help further learning and facilitate the enhancement of the main OPC recipe. Accordingly, the main OPC recipe can be more robust, converging faster and probably in a fewer number of iterations. This knowledge feedback loop is one of the fruitful benefits of the Automatic OPC Repair flow.

Fooling Around with Water

ERIC Educational Resources Information Center

Rice, Michael

1969-01-01

Describes four different styles of working exhibited by four different children as they worked with water flow. Each of the four children's approaches varied substantially, but each learned in his own way about water flow. The author believes that each child should be encouraged to follow his own style of learning. (BR)

The Effects of Flow on Learning Outcomes in an Online Information Management Course

ERIC Educational Resources Information Center

Rossin, Don; Ro, Young K.; Klein, Barbara D.; Guo, Yi Maggie

2009-01-01

As online courses and programs expand in business schools, it becomes increasingly important to understand the link between students' experiences in these courses and learning outcomes. The study reported here investigates the relationship between students' experiences of flow, a psychological state generally associated with improved task…

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

Effects of Mobile Phone-Based App Learning Compared to Computer-Based Web Learning on Nursing Students: Pilot Randomized Controlled Trial

PubMed Central

2015-01-01

Objectives This study aimed to determine the effect of mobile-based discussion versus computer-based discussion on self-directed learning readiness, academic motivation, learner-interface interaction, and flow state. Methods This randomized controlled trial was conducted at one university. Eighty-six nursing students who were able to use a computer, had home Internet access, and used a mobile phone were recruited. Participants were randomly assigned to either the mobile phone app-based discussion group (n = 45) or a computer web-based discussion group (n = 41). The effect was measured at before and after an online discussion via self-reported surveys that addressed academic motivation, self-directed learning readiness, time distortion, learner-learner interaction, learner-interface interaction, and flow state. Results The change in extrinsic motivation on identified regulation in the academic motivation (p = 0.011) as well as independence and ability to use basic study (p = 0.047) and positive orientation to the future in self-directed learning readiness (p = 0.021) from pre-intervention to post-intervention was significantly more positive in the mobile phone app-based group compared to the computer web-based discussion group. Interaction between learner and interface (p = 0.002), having clear goals (p = 0.012), and giving and receiving unambiguous feedback (p = 0.049) in flow state was significantly higher in the mobile phone app-based discussion group than it was in the computer web-based discussion group at post-test. Conclusions The mobile phone might offer more valuable learning opportunities for discussion teaching and learning methods in terms of self-directed learning readiness, academic motivation, learner-interface interaction, and the flow state of the learning process compared to the computer. PMID:25995965

Gas-liquid two-phase flow pattern identification by ultrasonic echoes reflected from the inner wall of a pipe

NASA Astrophysics Data System (ADS)

Liang, Fachun; Zheng, Hongfeng; Yu, Hao; Sun, Yuan

2016-03-01

A novel ultrasonic pulse echo method is proposed for flow pattern identification in a horizontal pipe with gas-liquid two-phase flow. A trace of echoes reflected from the pipe’s internal wall rather than the gas-liquid interface is used for flow pattern identification. Experiments were conducted in a horizontal air-water two-phase flow loop. Two ultrasonic transducers with central frequency of 5 MHz were mounted at the top and bottom of the pipe respectively. The experimental results show that the ultrasonic reflection coefficient of the wall-gas interface is much larger than that of the wall-liquid interface due to the large difference in the acoustic impedance of gas and liquid. The stratified flow, annular flow and slug flow can be successfully recognized using the attenuation ratio of the echoes. Compared with the conventional ultrasonic echo measurement method, echoes reflected from the inner surface of a pipe wall are independent of gas-liquid interface fluctuation, sound speed, and gas and liquid superficial velocities, which makes the method presented a promising technique in field practice.

Use of a Scale Model in the Design of Modifications to the NASA Glenn Icing Research Tunnel

NASA Technical Reports Server (NTRS)

Canacci, Victor A.; Gonsalez, Jose C.; Spera, David A.; Burke, Thomas (Technical Monitor)

2001-01-01

Major modifications were made in 1999 to the 6- by 9-Foot (1.8- by 2.7-m) Icing Research tunnel (IRT) at the NASA Glenn Research Center, including replacement of its heat exchanger and associated ducts and turning vanes, and the addition of fan outlet guide vanes (OGV's). A one-tenth scale model of the IRT (designated as the SMIRT) was constructed with and without these modifications and tested to increase confidence in obtaining expected improvements in flow quality around the tunnel loop. The SMIRT is itself an aerodynamic test facility whose flow patterns without modifications have been shown to be accurate, scaled representations of those measured in the IRT prior to the 1999 upgrade program. In addition, tests in the SMIRT equipped with simulated OGV's indicated that these devices in the IRT might reduce flow distortions immediately downstream of the fan by two thirds. Flow quality parameters measured in the SMIRT were projected to the full-size modified IRT, and quantitative estimates of improvements in flow quality were given prior to construction. In this paper, the results of extensive flow quality studies conducted in the SMIRT are documented. Samples of these are then compared with equivalent measurements made in the full-scale IRT, both before and after its configuration was upgraded. Airspeed, turbulence intensity, and flow angularity distributions are presented for cross sections downstream of the drive fan, both upstream and downstream of the replacement flat heat exchanger, in the stilling chamber, in the test section, and in the wakes of the new comer turning vanes with their unique expanding and contracting designs. Lessons learned from these scale-model studies are discussed.

Current challenges in quantifying preferential flow through the vadose zone

NASA Astrophysics Data System (ADS)

Koestel, John; Larsbo, Mats; Jarvis, Nick

2017-04-01

In this presentation, we give an overview of current challenges in quantifying preferential flow through the vadose zone. A review of the literature suggests that current generation models do not fully reflect the present state of process understanding and empirical knowledge of preferential flow. We believe that the development of improved models will be stimulated by the increasingly widespread application of novel imaging technologies as well as future advances in computational power and numerical techniques. One of the main challenges in this respect is to bridge the large gap between the scales at which preferential flow occurs (pore to Darcy scales) and the scale of interest for management (fields, catchments, regions). Studies at the pore scale are being supported by the development of 3-D non-invasive imaging and numerical simulation techniques. These studies are leading to a better understanding of how macropore network topology and initial/boundary conditions control key state variables like matric potential and thus the strength of preferential flow. Extrapolation of this knowledge to larger scales would require support from theoretical frameworks such as key concepts from percolation and network theory, since we lack measurement technologies to quantify macropore networks at these large scales. Linked hydro-geophysical measurement techniques that produce highly spatially and temporally resolved data enable investigation of the larger-scale heterogeneities that can generate preferential flow patterns at pedon, hillslope and field scales. At larger regional and global scales, improved methods of data-mining and analyses of large datasets (machine learning) may help in parameterizing models as well as lead to new insights into the relationships between soil susceptibility to preferential flow and site attributes (climate, land uses, soil types).

Laser imaging in liquid-liquid flows

NASA Astrophysics Data System (ADS)

Abidin, M. I. I. Zainal; Park, Kyeong H.; Voulgaropoulos, Victor; Chinaud, Maxime; Angeli, Panagiota

2016-11-01

In this work, the flow patterns formed during the horizontal flow of two immiscible liquids are studied. The pipe is made from acrylic, has an ID of 26 mm and a length of 4 m. A silicone oil (5cSt) and a water/glycerol mixture are used as test fluids. This set of liquids is chosen to match the refractive indices of the phases and enable laser based flow pattern identification. A double pulsed Nd:Yag laser was employed (532mm) with the appropriate optics to generate a laser sheet at the middle of the pipe. The aqueous phase was dyed with Rhodamine 6G, to distinguish between the two phases. Experiments were carried out for mixture velocities ranging from 0.15 to 2 m/s. Different inlet designs were used to actuate flow patterns in a controlled way and observe their development downstream the test section. A static mixer produced dispersed flow at the inlet which separated downstream due to enhanced coalescence. On the other hand, the use of a cylindrical bluff body at the inlet created non-linear interfacial waves in initially stratified flows from which drops detached leading to the transition to dispersed patterns. From the detailed images important flow parameters were measured such as wave characteristics and drop size. Project funded under the UK Engineering and Physical Sciences Research Council (EPSRC) Programme Grant MEMPHIS.

Visualization investigation on flowing condensation in horizontal small channels with liquid separator

NASA Astrophysics Data System (ADS)

Zhang, Xuan; Jia, Li; Dang, Chao; Peng, Qi

2018-02-01

A simultaneous visualization and measurement experiment was carried out to investigate condensation flow patterns and condensing heat transfer characteristics of refrigerant R141b in parallel horizontal multi-channels with liquid-vapor separator. The hydraulic diameter of each channel was 1.5 mm and the channel length was 100 mm. The refrigerant vapor flowing in the small channels was cooled by cooling water. The parallel horizontal multi- channels were covered with a transparent silica glass for visualization of flow patterns. Experiments were performed at different inlet superheat temperatures (ranging from 3°C to 7°C). Mass velocity was in the range of 82.37 kg m-2s-1 to 35.56 kg m-2s-1. It was found that there were three different flow patterns through the multi- channels with the increase of mass velocity. The flow patterns in each channel pass almost tended to be same and all of them were annular flows. The efficiency of the liquid-vapor separator with U-type was related to vapor mass velocity and the pressure in the small channels. It was also found that the heat transfer coefficient increased with the increase of the mass velocity while the cooling water mass flow rate increased. It increased to a top point and then decreased. It increased with the increase of superheat in the low superheat temperature region.

Bayesian learning of visual chunks by human observers

PubMed Central

Orbán, Gergő; Fiser, József; Aslin, Richard N.; Lengyel, Máté

2008-01-01

Efficient and versatile processing of any hierarchically structured information requires a learning mechanism that combines lower-level features into higher-level chunks. We investigated this chunking mechanism in humans with a visual pattern-learning paradigm. We developed an ideal learner based on Bayesian model comparison that extracts and stores only those chunks of information that are minimally sufficient to encode a set of visual scenes. Our ideal Bayesian chunk learner not only reproduced the results of a large set of previous empirical findings in the domain of human pattern learning but also made a key prediction that we confirmed experimentally. In accordance with Bayesian learning but contrary to associative learning, human performance was well above chance when pair-wise statistics in the exemplars contained no relevant information. Thus, humans extract chunks from complex visual patterns by generating accurate yet economical representations and not by encoding the full correlational structure of the input. PMID:18268353

Quantum machine learning.

PubMed

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Quantum machine learning

NASA Astrophysics Data System (ADS)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-01

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Revealing Adaptive Management of Environmental Flows

NASA Astrophysics Data System (ADS)

Allan, Catherine; Watts, Robyn J.

2018-03-01

Managers of land, water, and biodiversity are working with increasingly complex social ecological systems with high uncertainty. Adaptive management (learning from doing) is an ideal approach for working with this complexity. The competing social and environmental demands for water have prompted interest in freshwater adaptive management, but its success and uptake appear to be slow. Some of the perceived "failure" of adaptive management may reflect the way success is conceived and measured; learning, rarely used as an indicator of success, is narrowly defined when it is. In this paper, we document the process of adaptive flow management in the Edward-Wakool system in the southern Murray-Darling Basin, Australia. Data are from interviews with environmental water managers, document review, and the authors' structured reflection on their experiences of adaptive management and environmental flows. Substantial learning occurred in relation to the management of environmental flows in the Edward-Wakool system, with evidence found in planning documents, water-use reports, technical reports, stakeholder committee minutes, and refereed papers, while other evidence was anecdotal. Based on this case, we suggest it may be difficult for external observers to perceive the success of large adaptive management projects because evidence of learning is dispersed across multiple documents, and learning is not necessarily considered a measure of success. We suggest that documentation and sharing of new insights, and of the processes of learning, should be resourced to facilitate social learning within the water management sector, and to help demonstrate the successes of adaptive management.

Revealing Adaptive Management of Environmental Flows.

PubMed

Allan, Catherine; Watts, Robyn J

2018-03-01

Managers of land, water, and biodiversity are working with increasingly complex social ecological systems with high uncertainty. Adaptive management (learning from doing) is an ideal approach for working with this complexity. The competing social and environmental demands for water have prompted interest in freshwater adaptive management, but its success and uptake appear to be slow. Some of the perceived "failure" of adaptive management may reflect the way success is conceived and measured; learning, rarely used as an indicator of success, is narrowly defined when it is. In this paper, we document the process of adaptive flow management in the Edward-Wakool system in the southern Murray-Darling Basin, Australia. Data are from interviews with environmental water managers, document review, and the authors' structured reflection on their experiences of adaptive management and environmental flows. Substantial learning occurred in relation to the management of environmental flows in the Edward-Wakool system, with evidence found in planning documents, water-use reports, technical reports, stakeholder committee minutes, and refereed papers, while other evidence was anecdotal. Based on this case, we suggest it may be difficult for external observers to perceive the success of large adaptive management projects because evidence of learning is dispersed across multiple documents, and learning is not necessarily considered a measure of success. We suggest that documentation and sharing of new insights, and of the processes of learning, should be resourced to facilitate social learning within the water management sector, and to help demonstrate the successes of adaptive management.

Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

PubMed

Young, Sean D; Yu, Wenchao; Wang, Wei

2017-02-01

"Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trends and transmission, the review process is time consuming and resource intensive. Machine learning methods derived from computer science might be used to assist HIV domain experts by learning how to rapidly and accurately identify patterns associated with HIV from a large set of social data. Using an existing social media data set that was associated with HIV and coded by an HIV domain expert, we tested whether 4 commonly used machine learning methods could learn the patterns associated with HIV risk behavior. We used the 10-fold cross-validation method to examine the speed and accuracy of these models in applying that knowledge to detect HIV content in social media data. Logistic regression and random forest resulted in the highest accuracy in detecting HIV-related social data (85.3%), whereas the Ridge Regression Classifier resulted in the lowest accuracy. Logistic regression yielded the fastest processing time (16.98 seconds). Machine learning can enable social big data to become a new and important tool in HIV research, helping to create a new field of "digital HIV epidemiology." If a domain expert can identify patterns in social data associated with HIV risk or HIV transmission, machine learning models could quickly and accurately learn those associations and identify potential HIV patterns in large social data sets.

Studies of Two-Phase Gas-Liquid Flow in Microgravity. Ph.D. Thesis, Dec. 1994

NASA Technical Reports Server (NTRS)

Bousman, William Scott

1995-01-01

Two-phase gas-liquid flows are expected to occur in many future space operations. Due to a lack of buoyancy in the microgravity environment, two-phase flows are known to behave differently than those in earth gravity. Despite these concerns, little research has been conducted on microgravity two-phase flow and the current understanding is poor. This dissertation describes an experimental and modeling study of the characteristics of two-phase flows in microgravity. An experiment was operated onboard NASA aircraft capable of producing short periods of microgravity. In addition to high speed photographs of the flows, electronic measurements of void fraction, liquid film thickness, bubble and wave velocity, pressure drop and wall shear stress were made for a wide range of liquid and gas flow rates. The effects of liquid viscosity, surface tension and tube diameter on the behavior of these flows were also assessed. From the data collected, maps showing the occurrence of various flow patterns as a function of gas and liquid flow rates were constructed. Earth gravity two-phase flow models were compared to the results of the microgravity experiments and in some cases modified. Models were developed to predict the transitions on the flow pattern maps. Three flow patterns, bubble, slug and annular flow, were observed in microgravity. These patterns were found to occur in distinct regions of the gas-liquid flow rate parameter space. The effect of liquid viscosity, surface tension and tube diameter on the location of the boundaries of these regions was small. Void fraction and Weber number transition criteria both produced reasonable transition models. Void fraction and bubble velocity for bubble and slug flows were found to be well described by the Drift-Flux model used to describe such flows in earth gravity. Pressure drop modeling by the homogeneous flow model was inconclusive for bubble and slug flows. Annular flows were found to be complex systems of ring-like waves and a substrate film. Pressure drop was best fitted with the Lockhart- Martinelli model. Force balances suggest that droplet entrainment may be a large component of the total pressure drop.

Wind Effects on Flow Patterns and Net Fluxes in Density-Driven High-Latitude Channel Flow

NASA Astrophysics Data System (ADS)

Huntley, Helga S.; Ryan, Patricia

2018-01-01

A semianalytic two-dimensional model is used to analyze the interplay between the different forces acting on density-driven flow in high-latitude channels. In particular, the balance between wind stress, viscous forces, baroclinicity, and sea surface slope adjustments under specified flux conditions is examined. Weak winds are found not to change flow patterns appreciably, with minimal (<7%) adjustments to horizontal velocity maxima. In low-viscosity regimes, strong winds change the flow significantly, especially at the surface, by either strengthening the dual-jet pattern, established without wind, by a factor of 2-3 or initiating return flow at the surface. A nonzero flux does not result in the addition of a uniform velocity throughout the channel cross section, but modifies both along-channel and cross-channel velocities to become more symmetric, dominated by a down-channel jet centered in the domain and counter-clockwise lateral flow. We also consider formulations of the model that allow adjustments of the net flux in response to the wind. Flow patterns change, beyond uniform intensification or weakening, only for strong winds and high Ekman number. Comparisons of the model results to observational data collected in Nares Strait in the Canadian Archipelago in the summer of 2007 show rough agreement, but the model misses the upstream surface jet on the east side of the strait and propagates bathymetric effects too strongly in the vertical for this moderately high eddy viscosity. Nonetheless, the broad strokes of the observed high-latitude flow are reproduced.

A Cross-Cultural Comparison of Student Learning Patterns in Higher Education

ERIC Educational Resources Information Center

Marambe, Kosala N.; Vermunt, Jan D.; Boshuizen, Henny P. A.

2012-01-01

The aim of this study was to compare student learning patterns in higher education across different cultures. A meta-analysis was performed on three large-scale studies that had used the same research instrument: the Inventory of learning Styles (ILS). The studies were conducted in the two Asian countries Sri Lanka and Indonesia and the European…

Allowing Learners to Choose: Self-Controlled Practice Schedules for Learning Multiple Movement Patterns

ERIC Educational Resources Information Center

Wu, Will F. W.; Magill, Richard A.

2011-01-01

For this study, we investigated the effects of self-controlled practice on learning multiple motor skills. Thirty participants were randomly assigned to self-control or yoked conditions. Participants learned a three-keystroke pattern with three different relative time structures. Those in the self-control group chose one of three relative time…

Developing a Learning Progression for Three-Dimensional Learning of the Patterns of Evolution

ERIC Educational Resources Information Center

Wyner, Yael; Doherty, Jennifer H.

2017-01-01

This paper examines how students make progress toward three-dimensional (3D) understanding of the patterns of evolution. Specifically, it proposes a learning progression that explains how scientific practices, crosscutting concepts, and disciplinary core ideas come together in naming and grouping, length of change over time, and the role of common…

The Effects of Selective Attention on the Decoding Skills of Children with Learning Disabilities.

ERIC Educational Resources Information Center

Schworm, Ronald W.

1979-01-01

To test the effects of selective attention on decoding skills, 23 children (grades 2 through 6) with learning disabilities were studied. Results showed that treatment directly improved the ability of the experimental groups to transfer spelling patterns learned in isolation to unknown words containing those patterns and improved the ability of Ss…

Learners' Goal Profiles and Their Learning Patterns over an Academic Year

ERIC Educational Resources Information Center

Ng, Clarence

2015-01-01

The present study aimed to examine distance learners' goal profiles and their contrasting patterns of learning and achievements at three different points during an academic year, i.e. in the beginning of the course in relation to learners' general orientations to learning, at the middle of the course in relation to learners' completion of an…

[Assessment of blood flow in the middle cerebral artery and the umbilical artery in fetuses with umbilical venous pulsations].

PubMed

Borowski, Dariusz; Czuba, Bartosz; Kaczmarek, Piotr; Włoch, Agata; Pawłowicz, Paweł; Wyrwas, Dorota; Wielgos, Mirosław; Sodowski, Krzysztof; Szaflik, Krzysztof

2006-03-01

Umbilical venous pulsation is an important sign of hemodynamic compromise, especially during fetal heart failure and asphyxia. The aim of this study was to determine of the blow flow in the middle cerebral artery and the umbilical artery in fetuses with umbilical venous pulsations. The investigation included 18 fetuses with signs of the intrauterine growth restriction and umbilical venous pulsations after 28th weeks of gestation. We evaluated cerebral-placental ratio (CPR) and pulsation index (PI) in the middle cerebral artery (MCA) and the umbilical artery (UA). We observed brain sparring effect in all cases of analyzing fetuses. There were 77,8% of abnormal flow pattern in umbilical artery. 13 fetuses had a single pulsation pattern in umbilical vein and another 5 had double pulsation pattern. The coexistence of umbilical vein pulsation and abnormal flow pattern in umbilical artery is closely related to increased perinatal mortality.

A synchronized particle image velocimetry and infrared thermography technique applied to convective mass transfer in champagne glasses

NASA Astrophysics Data System (ADS)

Beaumont, Fabien; Liger-Belair, Gérard; Bailly, Yannick; Polidori, Guillaume

2016-05-01

In champagne glasses, it was recently suggested that ascending bubble-driven flow patterns should be involved in the release of gaseous carbon dioxide (CO2) and volatile organic compounds. A key assumption was that the higher the velocity of the upward bubble-driven flow patterns in the liquid phase, the higher the volume fluxes of gaseous CO2 desorbing from the supersaturated liquid phase. In the present work, simultaneous monitoring of bubble-driven flow patterns within champagne glasses and gaseous CO2 escaping above the champagne surface was performed, through particle image velocimetry and infrared thermography techniques. Two quite emblematic types of champagne drinking vessels were investigated, namely a long-stemmed flute and a wide coupe. The synchronized use of both techniques proved that the cloud of gaseous CO2 escaping above champagne glasses strongly depends on the mixing flow patterns found in the liquid phase below.

The value of assessing pulmonary venous flow velocity for predicting severity of mitral regurgitation: A quantitative assessment integrating left ventricular function

NASA Technical Reports Server (NTRS)

Pu, M.; Griffin, B. P.; Vandervoort, P. M.; Stewart, W. J.; Fan, X.; Cosgrove, D. M.; Thomas, J. D.

1999-01-01

Although alteration in pulmonary venous flow has been reported to relate to mitral regurgitant severity, it is also known to vary with left ventricular (LV) systolic and diastolic dysfunction. There are few data relating pulmonary venous flow to quantitative indexes of mitral regurgitation (MR). The object of this study was to assess quantitatively the accuracy of pulmonary venous flow for predicting MR severity by using transesophageal echocardiographic measurement in patients with variable LV dysfunction. This study consisted of 73 patients undergoing heart surgery with mild to severe MR. Regurgitant orifice area (ROA), regurgitant stroke volume (RSV), and regurgitant fraction (RF) were obtained by quantitative transesophageal echocardiography and proximal isovelocity surface area. Both left and right upper pulmonary venous flow velocities were recorded and their patterns classified by the ratio of systolic to diastolic velocity: normal (>/=1), blunted (<1), and systolic reversal (<0). Twenty-three percent of patients had discordant patterns between the left and right veins. When the most abnormal patterns either in the left or right vein were used for analysis, the ratio of peak systolic to diastolic flow velocity was negatively correlated with ROA (r = -0.74, P <.001), RSV (r = -0.70, P <.001), and RF (r = -0.66, P <.001) calculated by the Doppler thermodilution method; values were r = -0.70, r = -0.67, and r = -0.57, respectively (all P <.001), for indexes calculated by the proximal isovelocity surface area method. The sensitivity, specificity, and predictive values of the reversed pulmonary venous flow pattern for detecting a large ROA (>0.3 cm(2)) were 69%, 98%, and 97%, respectively. The sensitivity, specificity, and predictive values of the normal pulmonary venous flow pattern for detecting a small ROA (<0.3 cm(2)) were 60%, 96%, and 94%, respectively. However, the blunted pattern had low sensitivity (22%), specificity (61%), and predictive values (30%) for detecting ROA of greater than 0.3 cm(2) with significant overlap with the reversed and normal patterns. Among patients with the blunted pattern, the correlation between the systolic to diastolic velocity ratio was worse in those with LV dysfunction (ejection fraction <50%, r = 0.23, P >.05) than in those with normal LV function (r = -0.57, P <.05). Stepwise linear regression analysis showed that the peak systolic to diastolic velocity ratio was independently correlated with RF (P <.001) and effective stroke volume (P <.01), with a multiple correlation coefficient of 0.71 (P <.001). In conclusion, reversed pulmonary venous flow in systole is a highly specific and reliable marker of moderately severe or severe MR with an ROA greater than 0.3 cm(2), whereas the normal pattern accurately predicts mild to moderate MR. Blunted pulmonary venous flow can be seen in all grades of MR with low predictive value for severity of MR, especially in the presence of LV dysfunction. The blunted pulmonary venous flow pattern must therefore be interpreted cautiously in clinical practice as a marker for severity of MR.

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task

PubMed Central

2017-01-01

Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making. PMID:28961245

Discharge characteristics and hydrodynamics behaviors of atmospheric plasma jets produced in various gas flow patterns

NASA Astrophysics Data System (ADS)

Setsuhara, Yuichi; Uchida, Giichiro; Nakajima, Atsushi; Takenaka, Kosuke; Koga, Kazunori; Shiratani, Masaharu

2015-09-01

Atmospheric nonequilibrium plasma jets have been widely employed in biomedical applications. For biomedical applications, it is an important issue to understand the complicated mechanism of interaction of the plasma jet with liquid. In this study, we present analysis of the discharge characteristics of a plasma jet impinging onto the liquid surface under various gas flow patterns such as laminar and turbulence flows. For this purpose, we analyzed gas flow patters by using a Schlieren gas-flow imaging system in detail The plasma jet impinging into the liquid surface expands along the liquid surface. The diameter of the expanded plasma increases with gas flow rate, which is well explained by an increase in the diameter of the laminar gas-flow channel. When the gas flow rate is further increased, the gas flow mode transits from laminar to turbulence in the gas flow channel, which leads to the shortening of the plasm-jet length. Our experiment demonstrated that the gas flow patterns strongly affect the discharge characteristics in the plasma-jet system. This study was partly supported by a Grant-in-Aid for Scientific Research on Innovative Areas ``Plasma Medical Innovation'' (24108003) from the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT).

Influence of pulsatile flow on LDL transport in the arterial wall.

PubMed

Sun, Nanfeng; Wood, Nigel B; Hughes, Alun D; Thom, Simon A M; Xu, X Yun

2007-10-01

The accumulation of low-density lipoprotein (LDL) is one of the important factors in atherogenesis. Two different time scales may influence LDL transport in vivo: (1) LDL transport is coupled to blood flow with a pulse cycle of around 1 s in humans; (2) LDL transport within the arterial wall is mediated by transmural flow in the order of 10(-8) m/s. Most existing models have assumed steady flow conditions and overlooked the interactions between physical phenomena with different time scales. The objective of this study was to investigate the influence of pulsatile flow on LDL transport and examine the validity of steady flow assumption. The effect of pulsatile flow on transmural transport was incorporated by using a lumen-free cyclic (LFC) and a lumen-free time-averaged (LFTA) procedures. It is found that the steady flow simulation predicted a focal distribution in the post-stenotic region, differing from the diffuse distribution pattern produced by the pulsatile flow simulation. The LFTA procedure, in which time-averaged shear-dependent transport properties calculated from instantaneous wall shear stress (WSS) were used, predicted a similar distribution pattern to the LFC simulations. We conclude that the steady flow assumption is inadequate and instantaneous hemodynamic conditions have important influence on LDL transmural transport in arterial geometries with disturbed and complicated flow patterns.

Spanwise structure of the flow past a fixed or freely vibrating cylinder in the early turbulent regime

NASA Astrophysics Data System (ADS)

Bourguet, Remi; Gsell, Simon; Braza, Marianna

2017-11-01

The flow patterns developing downstream of slender bodies with bluff cross-section have been the object of intense research in the past decades. Particular attention was paid to the vortex patterns emerging in the plane perpendicular to the body axis. In the present study, focus is placed on the spanwise structure of the flow, in the early turbulent regime. The existence of dominant spanwise wavelengths had already been reported. However, many aspects remained to be explored, among others, the streamwise evolution of the spanwise patterns and their possible alteration when the body oscillates. These aspects are examined here on the basis of direct numerical simulations of the flow past a circular cylinder at Reynolds number 3900. The body is either fixed or subjected to vortex-induced vibrations. A systematic analysis of the spanwise patterns reveals persistent trends of their amplitude and wavelength in the different compartments of the flow, i.e. the separating shear layer and wake regions. Physical mechanisms are proposed to explain these trends. It is also found that the spanwise structure of the flow is differently altered in these two regions once the cylinder vibrates, the alteration being concentrated in the separating shear layers.

Patterns in the sky: Natural visualization of aircraft flow fields

NASA Technical Reports Server (NTRS)

Campbell, James F.; Chambers, Joseph R.

1994-01-01

The objective of the current publication is to present the collection of flight photographs to illustrate the types of flow patterns that were visualized and to present qualitative correlations with computational and wind tunnel results. Initially in section 2, the condensation process is discussed, including a review of relative humidity, vapor pressure, and factors which determine the presence of visible condensate. Next, outputs from computer code calculations are postprocessed by using water-vapor relationships to determine if computed values of relative humidity in the local flow field correlate with the qualitative features of the in-flight condensation patterns. The photographs are then presented in section 3 by flow type and subsequently in section 4 by aircraft type to demonstrate the variety of condensed flow fields that was visualized for a wide range of aircraft and flight maneuvers.

A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

PubMed

Dovgopoly, Alexander; Mercado, Eduardo

2013-06-01

Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

PATTERNS OF FLOWS IN AN INTERMEDIATE PROMINENCE OBSERVED BY HINODE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahn, Kwangsu; Chae, Jongchul; Cao Wenda

2010-09-20

The investigation of plasma flows in filaments/prominences gives us clues to understanding their magnetic structures. We studied the patterns of flows in an intermediate prominence observed by Hinode/SOT. By examining a time series of H{alpha} images and Ca II H images, we have found horizontal flows in the spine and vertical flows in the barb. Both of these flows have a characteristic speed of 10-20 km s{sup -1}. The horizontal flows displayed counterstreaming. Our detailed investigation revealed that most of the moving fragments in fact reversed direction at the end point of the spine near a footpoint close to themore » associated active region. These returning flows may be one possible explanation of the well-known counterstreaming flows in prominences. In contrast, we have found vertical flows-downward and upward-in the barb. Most of the horizontal flows in the spine seem to switch into vertical flows when they approach the barb, and vice versa. We propose that the net force resulting from a small deviation from magnetohydrostatic equilibrium, where magnetic fields are predominantly horizontal, may drive these patterns of flow. In the prominence studied here, the supposed magnetohydrostatic configuration is characterized by magnetic field lines sagging with angles of 13{sup 0} and 39{sup 0} in the spine and the barb, respectively.« less

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Overland flow dynamics through visual observation using time-lapse photographs

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2016-04-01

Overland flow process on agricultural land is important to be investigated as it affects the stream discharge and water quality assessment. During rainfall events the formation of overland flow may happen through different processes (i.e. Hortonian or saturation excess overland flow) based on the governing soil hydraulic parameters (i.e. soil infiltration rate, soil water capacity). The dynamics of the soil water state and the processes will affect the surface runoff response which can be analyzed visually by observing the saturation patterns with a camera. Although visual observation was proven useful in laboratory experiments, the technique is not yet assessed for natural rainfall events. The aim of this work is to explore the use of time-lapse photographs of naturally occurring-saturation patterns in understanding the threshold processes of overland flow generation. The image processing produces orthographic projection of the saturation patterns which will be used to assess the dynamics of overland flow formation in relation with soil moisture state and rainfall magnitude. The camera observation was performed at Hydrological Open Air Laboratory (HOAL) catchment at Petzenkirchen, Lower Austria. The catchment covers an area of 66 ha dominated with agricultural land (87%). The mean annual precipitation and mean annual flow at catchment outlet are 750 mm and 4 l/s, respectively. The camera was set to observe the overland flow along a thalweg on an arable field which was drained in 1950s and has advantages of: (1) representing agricultural land as the dominant part of the catchment, (2) adjacent to the stream with clear visibility (no obstructing objects, such as trees), (3) drained area provides extra cases in understanding the response of tile drain outflow to overland flow formation and vice versa, and (4) in the vicinity of TDT soil moisture stations. The camera takes a picture with 1280 x 720 pixels resolution every minute and sends it directly in a PC via fiber-optic network. Exterior orientation is required to project the observed saturation patterns in the photographs onto orthographic map. This was done by georeferencing the on-field GPS points taken throughout the camera field of view to the orthographic map obtained from an airborne laser scanning (ALS) campaign. Based on the projected saturation patterns, the patterns dynamics were analyzed in relation to soil moisture state and rainfall magnitude for events in autumn and winter 2014. From the observed events during saturated soil condition, tile drain flow reacted within one hour after the rain started, while no sign of saturation pattern evolving into overland flow was observed. Within two hours after the rain started, overland flow was fully formed along the thalweg which flowed to the erosion gully and created signal at the discharge station almost immediately. From the surface roughness aspect, field management is an important factor of overland flow development as surface runoff was formed faster along the tractor tracks. In overall, time-lapse photographs have potentials to qualitatively assess the saturation patterns dynamics during rainfall events with high time resolution and wide area coverage.

Supporting Teachers in Designing CSCL Activities: A Case Study of Principle-Based Pedagogical Patterns in Networked Second Language Classrooms

ERIC Educational Resources Information Center

Wen, Yun; Looi, Chee-Kit; Chen, Wenli

2012-01-01

This paper proposes the identification and use of principle-based pedagogical patterns to help teachers to translate design principles into actionable teaching activities, and to scaffold student learning with sufficient flexibility and creativity. A set of pedagogical patterns for networked Second language (L2) learning, categorized and…

The L-Shaped Classroom: A Pattern for Promoting Learning

ERIC Educational Resources Information Center

Lippman, Peter C.

2004-01-01

There has been little analysis of how the "L" Shape design pattern might influence learning as well as be incorporated into the design of new school facilities. This article: (1) re-examines the "Fat L" (Dyck, 1994) Classroom as a design pattern which supports a range of activity settings; (2) defines activity settings; (3)…

Bannatyne-Recategorized WISC-R Patterns of Mentally Retarded, Learning Disabled, Normal, and Intellectually Superior Children: A Meta-Analysis.

ERIC Educational Resources Information Center

Mueller, Horst H.; And Others

1983-01-01

Metaanalytical procedures examined the Wechsler Intelligence Scale-Revised subtest performance patterns of 36 samples of below average, normal average, learning disabled average, and above average IQ children from research. Relative patterning of WISC-R subtests as reflected in children's Bannatyne-recategorized performance profiles appeared to be…

Frequency and Pattern of Learner-Instructor Interaction in an Online English Language Learning Environment in Vietnam

ERIC Educational Resources Information Center

Pham, Thach; Thalathoti, Vijay; Dakich, Eva

2014-01-01

This study examines the frequency and pattern of interpersonal interactions between the learners and instructors of an online English language learning course offered at a Vietnamese university. The paper begins with a review of literature on interaction type, pattern and model of interaction followed by a brief description of the online…

Vapor Flow Patterns During a Start-Up Transient in Heat Pipes

NASA Technical Reports Server (NTRS)

Issacci, F.; Ghoniem, N, M.; Catton, I.

1996-01-01

The vapor flow patterns in heat pipes are examined during the start-up transient phase. The vapor core is modelled as a channel flow using a two dimensional compressible flow model. A nonlinear filtering technique is used as a post process to eliminate the non-physical oscillations of the flow variables. For high-input heat flux, multiple shock reflections are observed in the evaporation region. The reflections cause a reverse flow in the evaporation and circulations in the adiabatic region. Furthermore, each shock reflection causes a significant increase in the local pressure and a large pressure drop along the heat pipe.

Some simple guides to finding useful information in exploration geochemical data

USGS Publications Warehouse

Singer, D.A.; Kouda, R.

2001-01-01

Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data-unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups. To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values. In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only. Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations. ?? 2001 International Association for Mathematical Geology.

Exploring Conceptions about Writing and Learning: Undergraduates' Patterns of Beliefs and the Quality of Academic Writing (Acercamiento a las concepciones sobre la escritura y el aprendizaje: patrones de creencias de los universitarios y la calidad de su redacción académica)

ERIC Educational Resources Information Center

Martínez-Fernández, J. R.; Corcelles, M.; Bañales, G.; Castelló, M.; Gutiérrez-Braojos, C.

2016-01-01

Introduction: In this study, the conceptions of learning and writing of a group of undergraduates enrolled in a teacher education programme were identified. The relationship between them were analysed, and a set of patterns of beliefs about learning and writing were defined. Finally, the relation between these patterns and the quality of a text…

Landslides and Mudslides

MedlinePlus

... from landslides and debris flows In the United States, landslides and debris flows result in 25 to 50 deaths each year. ... and debris flows. Learn whether landslides or debris flows have ... department, state geological surveys or departments of natural resources, or ...

Biomorphodynamics: Physical-biological feedbacks that shape landscapes

USGS Publications Warehouse

Murray, A.B.; Knaapen, M.A.F.; Tal, M.; Kirwan, M.L.

2008-01-01

Plants and animals affect morphological evolution in many environments. The term "ecogeomorphology" describes studies that address such effects. In this opinion article we use the term "biomorphodynamics" to characterize a subset of ecogeomorphologic studies: those that investigate not only the effects of organisms on physical processes and morphology but also how the biological processes depend on morphology and physical forcing. The two-way coupling precipitates feedbacks, leading to interesting modes of behavior, much like the coupling between flow/sediment transport and morphology leads to rich morphodynamic behaviors. Select examples illustrate how even the basic aspects of some systems cannot be understood without considering biomorphodynamic coupling. Prominent examples include the dynamic interactions between vegetation and flow/sediment transport that can determine river channel patterns and the multifaceted biomorphodynamic feedbacks shaping tidal marshes and channel networks. These examples suggest that the effects of morphology and physical processes on biology tend to operate over the timescale of the evolution of the morphological pattern. Thus, in field studies, which represent a snapshot in the pattern evolution, these effects are often not as obvious as the effects of biology on physical processes. However, numerical modeling indicates that the influences on biology from physical processes can play a key role in shaping landscapes and that even local and temporary vegetation disturbances can steer large-scale, long-term landscape evolution. The prevalence of biomorphodynamic research is burgeoning in recent years, driven by societal need and a confluence of complex systems-inspired modeling approaches in ecology and geomorphology. To make fundamental progress in understanding the dynamics of many landscapes, our community needs to increasingly learn to look for two-way, biomorphodynamic feedbacks and to collect new types of data to support the modeling of such emergent interactions. Copyright 2008 by the American Geophysical Union.

Injection flow during steam condensation in silicon microchannels

NASA Astrophysics Data System (ADS)

Wu, Huiying; Yu, Mengmeng; Cheng, Ping; Wu, Xinyu

2007-08-01

An experimental investigation with the combined use of visualization and measurement techniques was performed on flow pattern transitions and wall temperature distributions in the condensation of steam in silicon microchannels. Three sets of trapezoidal silicon microchannels, having hydraulic diameters of 53.0 µm, 77.5 µm and 128.5 µm, respectively, were tested under different flow and cooling conditions. It was found that during the transitions from the annular flow to the slug/bubbly flow, a peculiar flow pattern injection flow appeared in silicon microchannels. The location at which the injection flow occurred was dependent on the Reynolds number, condensation number and hydraulic diameter. With increase in the Reynolds number, or decrease in the condensation number and hydraulic diameter, the injection flow moved towards the channel outlet. Based on the experimental results, a dimensionless correlation for the location of injection flow in functions of the Reynolds number, condensation number and hydraulic diameter was proposed for the first time. This correlation can be used to determine the annular flow zone and the slug/bubbly flow zone, and further to determine the dominating condensation flow pattern in silicon microchannels. Wall temperature distributions were also explored in this paper. It was found that near the injection flow, wall temperatures have a rapid decrease in the flow direction, while upstream and downstream far away from the injection flow, wall temperatures decreased mildly. Thus, the location of injection flow can also be determined based on the wall temperature distributions. The results presented in this paper help us to better understand the condensation flow and heat transfer in silicon microchannels.

Continuous flow chemistry: a discovery tool for new chemical reactivity patterns.

PubMed

Hartwig, Jan; Metternich, Jan B; Nikbin, Nikzad; Kirschning, Andreas; Ley, Steven V

2014-06-14

Continuous flow chemistry as a process intensification tool is well known. However, its ability to enable chemists to perform reactions which are not possible in batch is less well studied or understood. Here we present an example, where a new reactivity pattern and extended reaction scope has been achieved by transferring a reaction from batch mode to flow. This new reactivity can be explained by suppressing back mixing and precise control of temperature in a flow reactor set up.

A simulation of streaming flows associated with acoustic levitators

NASA Astrophysics Data System (ADS)

Rednikov, A.; Riley, N.

2002-04-01

Steady-state acoustic streaming flow patterns have been observed by Trinh and Robey [Phys. Fluids 6, 3567 (1994)], during the operation of a variety of single axis ultrasonic levitators in a gaseous environment. Microstreaming around levitated samples is superimposed on the streaming flow which is observed in the levitator even in the absence of any particle therein. In this paper, by physical arguments, numerical and analytical simulations we provide entirely satisfactory interpretations of the observed flow patterns in both isothermal and nonisothermal situations.

Preserved complex emotion-based learning in amnesia.

PubMed

Turnbull, Oliver H; Evans, Cathryn E Y

2006-01-01

An important role for emotion in decision-making has recently been highlighted by disruptions in problem solving abilities after lesion to the frontal lobes. Such complex decision-making skills appear to be based on a class of memory ability (emotion-based learning) that may be anatomically independent of hippocampally mediated episodic memory systems. There have long been reports of intact emotion-based learning in amnesia, arguably dating back to the classic report of Claparede. However, all such accounts relate to relatively simple patterns of emotional valence learning, rather than the more complex contingency patterns of emotional experience, which characterise everyday life. A patient, SL, who had a profound anterograde amnesia following posterior cerebral artery infarction, performed a measure of complex emotion-based learning (the Iowa Gambling Task) on three separate occasions. Despite his severe episodic memory impairment, he showed normal levels of performance on the Gambling Task, at levels comparable or better than controls-including learning that persisted across substantial periods of time (weeks). Thus, emotion-based learning systems appear able to encode, and sustain, more sophisticated patterns of valence learning than have previously been reported.

Interactions of double patterning technology with wafer processing, OPC and design flows

NASA Astrophysics Data System (ADS)

Lucas, Kevin; Cork, Chris; Miloslavsky, Alex; Luk-Pat, Gerry; Barnes, Levi; Hapli, John; Lewellen, John; Rollins, Greg; Wiaux, Vincent; Verhaegen, Staf

2008-03-01

Double patterning technology (DPT) is one of the main options for printing logic devices with half-pitch less than 45nm; and flash and DRAM memory devices with half-pitch less than 40nm. DPT methods decompose the original design intent into two individual masking layers which are each patterned using single exposures and existing 193nm lithography tools. The results of the individual patterning layers combine to re-create the design intent pattern on the wafer. In this paper we study interactions of DPT with lithography, masks synthesis and physical design flows. Double exposure and etch patterning steps create complexity for both process and design flows. DPT decomposition is a critical software step which will be performed in physical design and also in mask synthesis. Decomposition includes cutting (splitting) of original design intent polygons into multiple polygons where required; and coloring of the resulting polygons. We evaluate the ability to meet key physical design goals such as: reduce circuit area; minimize rework; ensure DPT compliance; guarantee patterning robustness on individual layer targets; ensure symmetric wafer results; and create uniform wafer density for the individual patterning layers.

2010 Presidential Address: Learning Religion and Religiously Learning amid Global Cultural Flows

ERIC Educational Resources Information Center

Hess, Mary E.

2011-01-01

Emerging social media that build on digital technologies are reshaping how we interact with each other. Religious education and identity formation within these new cultural flows demands recognition of the shifts in authority, authenticity, and agency that are taking place, as well as the challenges posed by "context collapse." Digital…

Structural Relationships among E-Learners' Sense of Presence, Usage, Flow, Satisfaction, and Persistence

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyoung; Kim, Eun Kyung

2013-01-01

This study aimed to investigate the structural relationships among teaching presence, cognitive presence, usage, learning flow, satisfaction, and learning persistence in corporate e-learners. The research participants were 462 e-learners registered for cyber-lectures through an electronics company in South Korea. The extrinsic variables were sense…

A Generalized Mechanism for Perception of Pitch Patterns

PubMed Central

Loui, Psyche; Wu, Elaine H.; Wessel, David L.; Knight, Robert T.

2009-01-01

Surviving in a complex and changeable environment relies upon the ability to extract probable recurring patterns. Here we report a neurophysiological mechanism for rapid probabilistic learning of a new system of music. Participants listened to different combinations of tones from a previously-unheard system of pitches based on the Bohlen-Pierce scale, with chord progressions that form 3:1 ratios in frequency, notably different from 2:1 frequency ratios in existing musical systems. Event-related brain potentials elicited by improbable sounds in the new music system showed emergence over a one-hour period of physiological signatures known to index sound expectation in standard Western music. These indices of expectation learning were eliminated when sound patterns were played equiprobably, and co-varied with individual behavioral differences in learning. These results demonstrate that humans utilize a generalized probability-based perceptual learning mechanism to process novel sound patterns in music. PMID:19144845

Hydrodynamics of freely swimming flagellates

NASA Astrophysics Data System (ADS)

Dolger, Julia; Nielsen, Lasse Tor; Kiorboe, Thomas; Bohr, Tomas; Andersen, Anders

2016-11-01

Flagellates are a diverse group of unicellular organisms forming an important part of the marine ecosystem. The arrangement of flagella around the cell serves as a key trait optimizing and compromising essential functions. With micro-particle image velocimetry we observed time-resolved near-cell flows around freely swimming flagellates, and we developed an analytical model based on the Stokes flow around a solid sphere propelled by a variable number of differently placed, temporally varying point forces, each representing one flagellum. The model allows us to reproduce the observed flow patterns and swimming dynamics, and to extract quantities such as swimming velocities and prey clearance rates as well as flow disturbances revealing the organism to flow-sensing predators. Our results point to optimal flagellar arrangements and beat patterns, and essential trade-offs. For biflagellates with two symmetrically arranged flagella we contrasted two species using undulatory and ciliary beat patterns, respectively, and found breast-stroke type beat patterns with equatorial power strokes to be favorable for fast as well as quiet swimming. The Centre for Ocean Life is a VKR Centre of Excellence supported by the Villum Foundation.

Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

NASA Astrophysics Data System (ADS)

Daya Sagar, B. S.

2005-01-01

Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

Formation of Nanoparticle Stripe Patterns via Flexible-Blade Flow Coating

NASA Astrophysics Data System (ADS)

Lee, Dong Yun; Kim, Hyun Suk; Parkos, Cassandra; Lee, Cheol Hee; Emrick, Todd; Crosby, Alfred

2011-03-01

We present the controlled formation of nanostripe patterns of nanoparticles on underlying substrates by flexible-blade flow coating. This technique exploits the combination of convective flow of confined nanoparticle solutions and programmed translation of a substrate to fabricate nanoparticle-polymer line assemblies with width below 300 nm, thickness of a single nanoparticle, and lengths exceeding 10 cm. We demonstrate how the incorporation of a flexible blade into this technique allows capillary forces to self-regulate the uniformity of convective flow processes across large lateral lengths. Furthermore, we exploit solvent mixture dynamics to enhance intra-assembly particle packing and dimensional range. This facile technique opens up a new paradigm for integration of nanoscale patterns over large areas for various applications.

Using Social Networking Environments to Support Collaborative Learning in a Chinese University Class: Interaction Pattern and Influencing Factors

ERIC Educational Resources Information Center

Lu, Jie; Churchill, Daniel

2014-01-01

This paper reports a study that investigated the social interaction pattern of collaborative learning and the factors affecting the effectiveness of collaborative learning in a social networking environment (SNE). A class of 55 undergraduate students enrolled in an elective course at a Chinese university was recruited for the study. The…

A Cross-Cultural Analysis of the Patterns of Learning and Academic Performance of Spanish and Latin-American Undergraduates

ERIC Educational Resources Information Center

Martínez-Fernández, J. Reinaldo; Vermunt, Jan D.

2015-01-01

The aim of this study was to analyse and compare the learning patterns of higher education students from Spain and three Latin-American countries (Colombia, Mexico and Venezuela). For this purpose Vermunt's Inventory of Learning Styles (ILS) was translated into Spanish and tested. The participants were 456 undergraduates enrolled in a teacher…

Extracting Phonological Patterns for L2 Word Learning: The Effect of Poor Phonological Awareness

ERIC Educational Resources Information Center

Hu, Chieh-Fang

2014-01-01

An implicit word learning paradigm was designed to test the hypothesis that children who came to the task of L2 vocabulary acquisition with poorer L1 phonological awareness (PA) are less capable of extracting phonological patterns from L2 and thus have difficulties capitalizing on this knowledge to support L2 vocabulary learning. A group of…

Levels and Patterns of Participation and Social Interaction in an Online Learning Community for Learning to Teach

ERIC Educational Resources Information Center

Tsai, I-Chun

2011-01-01

This study investigates how pre-service and in-service teachers participate in an online community for learning to teach. Members' levels and patterns of participation and social interaction were examined via social network analysis of activity logs and content analysis of interviews. The results of the analyses show that (a) members' levels and…

Educational Design and Networked Learning: Patterns, Pattern Languages and Design Practice

ERIC Educational Resources Information Center

Goodyear, Peter

2005-01-01

There is a growing demand for advice about effective, time efficient ways of using ICT to support student learning in higher education. This paper uses one such area of activity--networked learning--as a context in which to outline a novel approach to educational design. The paper makes two main contributions. It provides a high level view of the…

Influence of the tilt angle of Percutaneous Aortic Prosthesis on Velocity and Shear Stress Fields

PubMed Central

Gomes, Bruno Alvares de Azevedo; Camargo, Gabriel Cordeiro; dos Santos, Jorge Roberto Lopes; Azevedo, Luis Fernando Alzuguir; Nieckele, Ângela Ourivio; Siqueira-Filho, Aristarco Gonçalves; de Oliveira, Glaucia Maria Moraes

2017-01-01

Background Due to the nature of the percutaneous prosthesis deployment process, a variation in its final position is expected. Prosthetic valve placement will define the spatial location of its effective orifice in relation to the aortic annulus. The blood flow pattern in the ascending aorta is related to the aortic remodeling process, and depends on the spatial location of the effective orifice. The hemodynamic effect of small variations in the angle of inclination of the effective orifice has not been studied in detail. Objective To implement an in vitro simulation to characterize the hydrodynamic blood flow pattern associated with small variations in the effective orifice inclination. Methods A three-dimensional aortic phantom was constructed, reproducing the anatomy of one patient submitted to percutaneous aortic valve implantation. Flow analysis was performed by use of the Particle Image Velocimetry technique. The flow pattern in the ascending aorta was characterized for six flow rate levels. In addition, six angles of inclination of the effective orifice were assessed. Results The effective orifice at the -4º and -2º angles directed the main flow towards the anterior wall of the aortic model, inducing asymmetric and high shear stress in that region. However, the effective orifice at the +3º and +5º angles mimics the physiological pattern, centralizing the main flow and promoting a symmetric distribution of shear stress. Conclusion The measurements performed suggest that small changes in the angle of inclination of the percutaneous prosthesis aid in the generation of a physiological hemodynamic pattern, and can contribute to reduce aortic remodeling. PMID:28793046

Collaborative mining and transfer learning for relational data

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Eslami, Mohammed

2015-06-01

Many of the real-world problems, - including human knowledge, communication, biological, and cyber network analysis, - deal with data entities for which the essential information is contained in the relations among those entities. Such data must be modeled and analyzed as graphs, with attributes on both objects and relations encode and differentiate their semantics. Traditional data mining algorithms were originally designed for analyzing discrete objects for which a set of features can be defined, and thus cannot be easily adapted to deal with graph data. This gave rise to the relational data mining field of research, of which graph pattern learning is a key sub-domain [11]. In this paper, we describe a model for learning graph patterns in collaborative distributed manner. Distributed pattern learning is challenging due to dependencies between the nodes and relations in the graph, and variability across graph instances. We present three algorithms that trade-off benefits of parallelization and data aggregation, compare their performance to centralized graph learning, and discuss individual benefits and weaknesses of each model. Presented algorithms are designed for linear speedup in distributed computing environments, and learn graph patterns that are both closer to ground truth and provide higher detection rates than centralized mining algorithm.

Unidirectional pulmonary airflow patterns in the savannah monitor lizard.

PubMed

Schachner, Emma R; Cieri, Robert L; Butler, James P; Farmer, C G

2014-02-20

The unidirectional airflow patterns in the lungs of birds have long been considered a unique and specialized trait associated with the oxygen demands of flying, their endothermic metabolism and unusual pulmonary architecture. However, the discovery of similar flow patterns in the lungs of crocodilians indicates that this character is probably ancestral for all archosaurs--the group that includes extant birds and crocodilians as well as their extinct relatives, such as pterosaurs and dinosaurs. Unidirectional flow in birds results from aerodynamic valves, rather than from sphincters or other physical mechanisms, and similar aerodynamic valves seem to be present in crocodilians. The anatomical and developmental similarities in the primary and secondary bronchi of birds and crocodilians suggest that these structures and airflow patterns may be homologous. The origin of this pattern is at least as old as the split between crocodilians and birds, which occurred in the Triassic period. Alternatively, this pattern of flow may be even older; this hypothesis can be tested by investigating patterns of airflow in members of the outgroup to birds and crocodilians, the Lepidosauromorpha (tuatara, lizards and snakes). Here we demonstrate region-specific unidirectional airflow in the lungs of the savannah monitor lizard (Varanus exanthematicus). The presence of unidirectional flow in the lungs of V. exanthematicus thus gives rise to two possible evolutionary scenarios: either unidirectional airflow evolved independently in archosaurs and monitor lizards, or these flow patterns are homologous in archosaurs and V. exanthematicus, having evolved only once in ancestral diapsids (the clade encompassing snakes, lizards, crocodilians and birds). If unidirectional airflow is plesiomorphic for Diapsida, this respiratory character can be reconstructed for extinct diapsids, and evolved in a small ectothermic tetrapod during the Palaeozoic era at least a hundred million years before the origin of birds.

Ground Based Studies of Gas-Liquid Flows in Microgravity Using Learjet Trajectories

NASA Technical Reports Server (NTRS)

Bousman, W. S.; Dukler, A. E.

1994-01-01

A 1.27 cm diameter two phase gas-liquid flow experiment has been developed with the NASA Lewis Research Center to study two-phase flows in microgravity. The experiment allows for the measurement of void fraction, pressure drop, film thickness and bubble and wave velocities as well as for high speed photography. Three liquids were used to study the effects of liquid viscosity and surface tension, and flow pattern maps are presented for each. The experimental results are used to develop mechanistically based models to predict void fraction, bubble velocity, pressure drop and flow pattern transitions in microgravity.

Nitrate Removal Rates in Denitrifying Bioreactors During Storm Flows

NASA Astrophysics Data System (ADS)

Pluer, W.; Walter, T.

2017-12-01

Field denitrifying bioreactors are designed to reduce excess nitrate (NO3-) pollution in runoff from agricultural fields. Field bioreactors saturate organic matter to create conditions that facilitate microbial denitrification. Prior studies using steady flow in lab-scale bioreactors showed that a hydraulic retention time (HRT) between 4 and 10 hours was optimal for reducing NO3- loads. However, during storm-induced events, flow rate and actual HRT fluctuate. These fluctuations have the potential to disrupt the system in significant ways that are not captured by the idealized steady-flow HRT models. The goal of this study was to investigate removal rate during dynamic storm flows of variable rates and durations. Our results indicate that storm peak flow and duration were not significant controlling variables. Instead, we found high correlations (p=0.004) in average removal rates between bioreactors displaying a predominantly uniform flow pattern compared with bioreactors that exhibited preferential flow (24.4 and 21.4 g N m-3 d-1, respectively). This suggests that the internal flow patterns are a more significant driver of removal rate than external factors of the storm hydrograph. Designing for flow patterns in addition to theoretical HRT will facilitate complete mixing within the bioreactors. This will help maximize excess NO3- removal during large storm-induced runoff events.

Spontaneous generalization of abstract multimodal patterns in young domestic chicks.

PubMed

Versace, Elisabetta; Spierings, Michelle J; Caffini, Matteo; Ten Cate, Carel; Vallortigara, Giorgio

2017-05-01

From the early stages of life, learning the regularities associated with specific objects is crucial for making sense of experiences. Through filial imprinting, young precocial birds quickly learn the features of their social partners by mere exposure. It is not clear though to what extent chicks can extract abstract patterns of the visual and acoustic stimuli present in the imprinting object, and how they combine them. To investigate this issue, we exposed chicks (Gallus gallus) to three days of visual and acoustic imprinting, using either patterns with two identical items or patterns with two different items, presented visually, acoustically or in both modalities. Next, chicks were given a choice between the familiar and the unfamiliar pattern, present in either the multimodal, visual or acoustic modality. The responses to the novel stimuli were affected by their imprinting experience, and the effect was stronger for chicks imprinted with multimodal patterns than for the other groups. Interestingly, males and females adopted a different strategy, with males more attracted by unfamiliar patterns and females more attracted by familiar patterns. Our data show that chicks can generalize abstract patterns by mere exposure through filial imprinting and that multimodal stimulation is more effective than unimodal stimulation for pattern learning.

Ecosystem processes at the watershed scale: hydrologic vegetation gradient as an indicator for lateral hydrologic connectivity of headwater catchments

Treesearch

Taehee Hwang; James M. Vose; Christina Tague

2012-01-01

Lateral water flow in catchments can produce important patterns in water and nutrient fluxes and stores and also influences the long-term spatial development of forest ecosystems. Specifically, patterns of vegetation type and density along hydrologic flow paths can represent a signal of the redistribution of water and nitrogen mediated by lateral hydrologic flow. This...

Speech Synthesis Using Perceptually Motivated Features

DTIC Science & Technology

2012-01-23

with others a few years prior (with the concurrence of the project’s program manager. Willard Larkin). The Perceptual Flow of Phonetic Information and...34The Perceptual Flow of Phonetic Processing," consonant confusion matrices are analyzed for patterns of phonetic-feature decoding errors conditioned...decoding) is also observed. From these conditional probability patterns, it is proposed that they reflect a temporal flow of perceptual processing

Patterns of mating in an insect-pollinated tree species in the Missouri Ozark Forest Ecosystem Project

Treesearch

Victoria J. Apsit; Rodney J. Dyer; Victoria L. Sork

2002-01-01

Contemporary gene flow is a major mechanism for the maintenance of genetic diversity. One component of gene flow is the mating system, which is a composite measure of selfing, mating with relatives, and outcrossing. Although both gene flow and mating patterns contribute to the ecological sustainability of populations, a focus of many forest management plans, these...

Optimizing Micromixer Surfaces To Deter Biofouling.

PubMed

Waters, James T; Liu, Ya; Li, Like; Balazs, Anna C

2018-03-07

Using computational modeling, we show that the dynamic interplay between a flowing fluid and the appropriately designed surface relief pattern can inhibit the fouling of the substrate. We specifically focus on surfaces that are decorated with three-dimensional (3D) chevron or sawtooth "micromixer" patterns and model the fouling agents (e.g., cells) as spherical microcapsules. The interaction between the imposed shear flow and the chevrons on the surface generates 3D vortices in the system. We pinpoint a range of shear rates where the forces from these vortices can rupture the bonds between the two mobile microcapsules near the surface. Notably, the patterned surface offers fewer points of attachment than a flat substrate, and the shear flows readily transport the separated capsules away from the layer. We contrast the performance of surfaces that encompass rectangular posts, chevrons, and asymmetric sawtooth patterns and thereby identify the geometric factors that cause the sawtooth structure to be most effective at disrupting the bonding between the capsules. By breaking up nascent clusters of contaminant cells, these 3D relief patterns can play a vital role in disrupting the biofouling of surfaces immersed in flowing fluids.

Recurrent Neural Networks With Auxiliary Memory Units.

PubMed

Wang, Jianyong; Zhang, Lei; Guo, Quan; Yi, Zhang

2018-05-01

Memory is one of the most important mechanisms in recurrent neural networks (RNNs) learning. It plays a crucial role in practical applications, such as sequence learning. With a good memory mechanism, long term history can be fused with current information, and can thus improve RNNs learning. Developing a suitable memory mechanism is always desirable in the field of RNNs. This paper proposes a novel memory mechanism for RNNs. The main contributions of this paper are: 1) an auxiliary memory unit (AMU) is proposed, which results in a new special RNN model (AMU-RNN), separating the memory and output explicitly and 2) an efficient learning algorithm is developed by employing the technique of error flow truncation. The proposed AMU-RNN model, together with the developed learning algorithm, can learn and maintain stable memory over a long time range. This method overcomes both the learning conflict problem and gradient vanishing problem. Unlike the traditional method, which mixes the memory and output with a single neuron in a recurrent unit, the AMU provides an auxiliary memory neuron to maintain memory in particular. By separating the memory and output in a recurrent unit, the problem of learning conflicts can be eliminated easily. Moreover, by using the technique of error flow truncation, each auxiliary memory neuron ensures constant error flow during the learning process. The experiments demonstrate good performance of the proposed AMU-RNNs and the developed learning algorithm. The method exhibits quite efficient learning performance with stable convergence in the AMU-RNN learning and outperforms the state-of-the-art RNN models in sequence generation and sequence classification tasks.

Inhibition of the active lymph pump by flow in rat mesenteric lymphatics and thoracic duct

NASA Technical Reports Server (NTRS)

Gashev, Anatoliy A.; Davis, Michael J.; Zawieja, David C.; Delp, M. D. (Principal Investigator)

2002-01-01

There are only a few reports of the influence of imposed flow on an active lymph pump under conditions of controlled intraluminal pressure. Thus, the mechanisms are not clearly defined. Rat mesenteric lymphatics and thoracic ducts were isolated, cannulated and pressurized. Input and output pressures were adjusted to impose various flows. Lymphatic systolic and diastolic diameters were measured and used to determine contraction frequency and pump flow indices. Imposed flow inhibited the active lymph pump in both mesenteric lymphatics and in the thoracic duct. The active pump of the thoracic duct appeared more sensitive to flow than did the active pump of the mesenteric lymphatics. Imposed flow reduced the frequency and amplitude of the contractions and accordingly the active pump flow. Flow-induced inhibition of the active lymph pump followed two temporal patterns. The first pattern was a rapidly developing inhibition of contraction frequency. Upon imposition of flow, the contraction frequency immediately fell and then partially recovered over time during continued flow. This effect was dependent on the magnitude of imposed flow, but did not depend on the direction of flow. The effect also depended upon the rate of change in the direction of flow. The second pattern was a slowly developing reduction of the amplitude of the lymphatic contractions, which increased over time during continued flow. The inhibition of contraction amplitude was dependent on the direction of the imposed flow, but independent of the magnitude of flow. Nitric oxide was partly but not completely responsible for the influence of flow on the mesenteric lymph pump. Exposure to NO mimicked the effects of flow, and inhibition of the NO synthase by N (G)-monomethyl-L-arginine attenuated but did not completely abolish the effects of flow.

Capturing Flow in the Business Classroom

ERIC Educational Resources Information Center

Guo, Yi Maggie; Ro, Young K.

2008-01-01

This study focuses on the flow experience in business education. Flow experience, characterized by concentration, control, and enjoyment, can lead to better learning outcomes. Leading preconditions of flow include the balance of challenge and skill, feedback, and goal clarity. Other situational factors affect the flow experience through the…

The impact of traffic-flow patterns on air quality in urban street canyons.

PubMed

Thaker, Prashant; Gokhale, Sharad

2016-01-01

We investigated the effect of different urban traffic-flow patterns on pollutant dispersion in different winds in a real asymmetric street canyon. Free-flow traffic causes more turbulence in the canyon facilitating more dispersion and a reduction in pedestrian level concentration. The comparison of with and without a vehicle-induced-turbulence revealed that when winds were perpendicular, the free-flow traffic reduced the concentration by 73% on the windward side with a minor increase of 17% on the leeward side, whereas for parallel winds, it reduced the concentration by 51% and 29%. The congested-flow traffic increased the concentrations on the leeward side by 47% when winds were perpendicular posing a higher risk to health, whereas reduced it by 17-42% for parallel winds. The urban air quality and public health can, therefore, be improved by improving the traffic-flow patterns in street canyons as vehicle-induced turbulence has been shown to contribute significantly to dispersion. Copyright © 2015 Elsevier Ltd. All rights reserved.

Patterns of Control over the Teaching-Studying-Learning Process and Classrooms as Complex Dynamic Environments: A Theoretical Framework

ERIC Educational Resources Information Center

Harjunen, Elina

2012-01-01

In this theoretical paper the role of power in classroom interactions is examined in terms of a dominance continuum to advance a theoretical framework justifying the emergence of three ways of distributing power when it comes to dealing with the control over the teaching-studying-learning (TSL) "pattern of teacher domination," "pattern of…

Cognitive Patterns of Learning Disability Subtypes as Measured by the Woodcock-Johnson Psycho-Educational Battery.

ERIC Educational Resources Information Center

Breen, Michael J.

1986-01-01

The cognitive patterns of three learning disability subtypes were studied: (1) students with higher math than reading skills, (2) students with higher reading than math skills, and (3) students with equally low math and reading skills. Results indicated that although the three groups were characterized by a number of discrete or unique patterns,…

FAST TRACK COMMUNICATION: Effects of Penning ionization on the discharge patterns of atmospheric pressure plasma jets

NASA Astrophysics Data System (ADS)

Li, Qing; Zhu, Wen-Chao; Zhu, Xi-Ming; Pu, Yi-Kang

2010-09-01

Atmospheric pressure plasma jets, generated in a coaxial dielectric barrier discharge configuration, have been investigated with different flowing gases. Discharge patterns in different tube regions were compared in the flowing gases of helium, neon and krypton. To explain the difference of these discharge patterns, a theoretical analysis is presented to reveal the possible basic processes. A comparison of experimental and theoretical results identifies that Penning ionization is mainly responsible for the discharge patterns of helium and neon plasma jets.

Dynamics and stability of thin liquid films

NASA Astrophysics Data System (ADS)

Craster, R. V.; Matar, O. K.

2009-07-01

The dynamics and stability of thin liquid films have fascinated scientists over many decades: the observations of regular wave patterns in film flows down a windowpane or along guttering, the patterning of dewetting droplets, and the fingering of viscous flows down a slope are all examples that are familiar in daily life. Thin film flows occur over a wide range of length scales and are central to numerous areas of engineering, geophysics, and biophysics; these include nanofluidics and microfluidics, coating flows, intensive processing, lava flows, dynamics of continental ice sheets, tear-film rupture, and surfactant replacement therapy. These flows have attracted considerable attention in the literature, which have resulted in many significant developments in experimental, analytical, and numerical research in this area. These include advances in understanding dewetting, thermocapillary- and surfactant-driven films, falling films and films flowing over structured, compliant, and rapidly rotating substrates, and evaporating films as well as those manipulated via use of electric fields to produce nanoscale patterns. These developments are reviewed in this paper and open problems and exciting research avenues in this thriving area of fluid mechanics are also highlighted.

Anisotropic shear stress patterns predict the orientation of convergent tissue movements in the embryonic heart

PubMed Central

2017-01-01

Myocardial contractility and blood flow provide essential mechanical cues for the morphogenesis of the heart. In general, endothelial cells change their migratory behavior in response to shear stress patterns, according to flow directionality. Here, we assessed the impact of shear stress patterns and flow directionality on the behavior of endocardial cells, the specialized endothelial cells of the heart. At the early stages of zebrafish heart valve formation, we show that endocardial cells are converging to the valve-forming area and that this behavior depends upon mechanical forces. Quantitative live imaging and mathematical modeling allow us to correlate this tissue convergence with the underlying flow forces. We predict that tissue convergence is associated with the direction of the mean wall shear stress and of the gradient of harmonic phase-averaged shear stresses, which surprisingly do not match the overall direction of the flow. This contrasts with the usual role of flow directionality in vascular development and suggests that the full spatial and temporal complexity of the wall shear stress should be taken into account when studying endothelial cell responses to flow in vivo. PMID:29183943

Effects of lung disease on the three-dimensional structure and air flow pattern in the human airway tree

NASA Astrophysics Data System (ADS)

van de Moortele, Tristan; Nemes, Andras; Wendt, Christine; Coletti, Filippo

2016-11-01

The morphological features of the airway tree directly affect the air flow features during breathing, which determines the gas exchange and inhaled particle transport. Lung disease, Chronic Obstructive Pulmonary Disease (COPD) in this study, affects the structural features of the lungs, which in turn negatively affects the air flow through the airways. Here bronchial tree air volume geometries are segmented from Computed Tomography (CT) scans of healthy and diseased subjects. Geometrical analysis of the airway centerlines and corresponding cross-sectional areas provide insight into the specific effects of COPD on the airway structure. These geometries are also used to 3D print anatomically accurate, patient specific flow models. Three-component, three-dimensional velocity fields within these models are acquired using Magnetic Resonance Imaging (MRI). The three-dimensional flow fields provide insight into the change in flow patterns and features. Additionally, particle trajectories are determined using the velocity fields, to identify the fate of therapeutic and harmful inhaled aerosols. Correlation between disease-specific and patient-specific anatomical features with dysfunctional airflow patterns can be achieved by combining geometrical and flow analysis.

Making long-term memories in minutes: a spaced learning pattern from memory research in education

PubMed Central

Kelley, Paul; Whatson, Terry

2013-01-01

Memory systems select from environmental stimuli those to encode permanently. Repeated stimuli separated by timed spaces without stimuli can initiate Long-Term Potentiation (LTP) and long-term memory (LTM) encoding. These processes occur in time scales of minutes, and have been demonstrated in many species. This study reports on using a specific timed pattern of three repeated stimuli separated by 10 min spaces drawn from both behavioral and laboratory studies of LTP and LTM encoding. A technique was developed based on this pattern to test whether encoding complex information into LTM in students was possible using the pattern within a very short time scale. In an educational context, stimuli were periods of highly compressed instruction, and spaces were created through 10 min distractor activities. Spaced Learning in this form was used as the only means of instruction for a national curriculum Biology course, and led to very rapid LTM encoding as measured by the high-stakes test for the course. Remarkably, learning at a greatly increased speed and in a pattern that included deliberate distraction produced significantly higher scores than random answers (p < 0.00001) and scores were not significantly different for experimental groups (one hour spaced learning) and control groups (four months teaching). Thus learning per hour of instruction, as measured by the test, was significantly higher for the spaced learning groups (p < 0.00001). In a third condition, spaced learning was used to replace the end of course review for one of two examinations. Results showed significantly higher outcomes for the course using spaced learning (p < 0.0005). The implications of these findings and further areas for research are briefly considered. PMID:24093012

Animating streamlines with repeated asymmetric patterns for steady flow visualization

NASA Astrophysics Data System (ADS)

Yeh, Chih-Kuo; Liu, Zhanping; Lee, Tong-Yee

2012-01-01

Animation provides intuitive cueing for revealing essential spatial-temporal features of data in scientific visualization. This paper explores the design of Repeated Asymmetric Patterns (RAPs) in animating evenly-spaced color-mapped streamlines for dense accurate visualization of complex steady flows. We present a smooth cyclic variable-speed RAP animation model that performs velocity (magnitude) integral luminance transition on streamlines. This model is extended with inter-streamline synchronization in luminance varying along the tangential direction to emulate orthogonal advancing waves from a geometry-based flow representation, and then with evenly-spaced hue differing in the orthogonal direction to construct tangential flow streaks. To weave these two mutually dual sets of patterns, we propose an energy-decreasing strategy that adopts an iterative yet efficient procedure for determining the luminance phase and hue of each streamline in HSL color space. We also employ adaptive luminance interleaving in the direction perpendicular to the flow to increase the contrast between streamlines.

Systematic study of source mask optimization and verification flows

NASA Astrophysics Data System (ADS)

Ben, Yu; Latypov, Azat; Chua, Gek Soon; Zou, Yi

2012-06-01

Source mask optimization (SMO) emerged as powerful resolution enhancement technique (RET) for advanced technology nodes. However, there is a plethora of flow and verification metrics in the field, confounding the end user of the technique. Systemic study of different flows and the possible unification thereof is missing. This contribution is intended to reveal the pros and cons of different SMO approaches and verification metrics, understand the commonality and difference, and provide a generic guideline for RET selection via SMO. The paper discusses 3 different type of variations commonly arise in SMO, namely pattern preparation & selection, availability of relevant OPC recipe for freeform source and finally the metrics used in source verification. Several pattern selection algorithms are compared and advantages of systematic pattern selection algorithms are discussed. In the absence of a full resist model for SMO, alternative SMO flow without full resist model is reviewed. Preferred verification flow with quality metrics of DOF and MEEF is examined.

Velocity bias induced by flow patterns around ADCPs and associated deployment platforms

USGS Publications Warehouse

Mueller, David S.

2015-01-01

Velocity measurements near the Acoustic Doppler Current Profiler (ADCP) are important for mapping surface currents, measuring velocity and discharge in shallow streams, and providing accurate estimates of discharge in the top unmeasured portion of the water column. Improvements to ADCP performance permit measurement of velocities much closer (5 cm) to the transducer than has been possible in the past (25 cm). Velocity profiles collected by the U.S. Geological Survey (USGS) with a 1200 kHz Rio Grande Zedhead ADCP in 2002 showed a negative bias in measured velocities near the transducers. On the basis of these results, the USGS initiated a study combining field, laboratory, and numerical modeling data to assess the effect of flow patterns caused by flow around the ADCP and deployment platforms on velocities measured near the transducers. This ongoing study has shown that the negative bias observed in the field is due to the flow pattern around the ADCP. The flow pattern around an ADCP violates the basic assumption of flow homogeneity required for an accurate three-dimensional velocity solution. Results, to date (2014), have indicated velocity biases within the measurable profile, due to flow disturbance, for the TRDI 1200 kHz Rio Grande Zedhead and the SonTek RiverSurveyor M9 ADCPs. The flow speed past the ADCP, the mount and the deployment platform have also been shown to play an important role in the magnitude and extent of the velocity bias.

Influence of anatomical dominance and hypertension on coronary conduit arterial and microcirculatory flow patterns: a multiscale modeling study.

PubMed

Mynard, Jonathan P; Smolich, Joseph J

2016-07-01

Coronary hemodynamics are known to be affected by intravascular and extravascular factors that vary regionally and transmurally between the perfusion territories of left and right coronary arteries. However, despite clinical evidence that left coronary arterial dominance portends greater cardiovascular risk, relatively little is known about the effects of left or right dominance on regional conduit arterial and microcirculatory blood flow patterns, particularly in the presence of systemic or pulmonary hypertension. We addressed this issue using a multiscale numerical model of the human coronary circulation situated in a closed-loop cardiovascular model. The coronary model represented left or right dominant anatomies and accounted for transmural and regional differences in vascular properties and extravascular compression. Regional coronary flow dynamics of the two anatomical variants were compared under normotensive conditions, raised systemic or pulmonary pressures with maintained flow demand, and after accounting for adaptations known to occur in acute and chronic hypertensive states. Key findings were that 1) right coronary arterial flow patterns were strongly influenced by dominance and systemic/pulmonary hypertension; 2) dominance had minor effects on left coronary arterial and all microvascular flow patterns (aside from mean circumflex flow); 3) although systemic hypertension favorably increased perfusion pressure, this benefit varied regionally and transmurally and was offset by increased left ventricular and septal flow demands; and 4) pulmonary hypertension had a substantial negative effect on right ventricular and septal flows, which was exacerbated by greater metabolic demands. These findings highlight the importance of interactions between coronary arterial dominance and hypertension in modulating coronary hemodynamics. Copyright © 2016 the American Physiological Society.

Rigorous assessment of patterning solution of metal layer in 7 nm technology node

NASA Astrophysics Data System (ADS)

Gao, Weimin; Ciofi, Ivan; Saad, Yves; Matagne, Philippe; Bachmann, Michael; Gillijns, Werner; Lucas, Kevin; Demmerle, Wolfgang; Schmoeller, Thomas

2016-01-01

In a 7 nm node (N7), the logic design requires a critical poly pitch of 42 to 45 nm and a metal 1 (M1) pitch of 28 to 32 nm. Such high-pattern density pushes the 193 immersion lithography solution toward its limit and also brings extremely complex patterning scenarios. The N7 M1 layer may require a self-aligned quadruple patterning (SAQP) with a triple litho-etch (LE3) block process. Therefore, the whole patterning process flow requires multiple exposure+etch+deposition processes and each step introduces a particular impact on the pattern profiles and the topography. In this study, we have successfully integrated a simulation tool that enables emulation of the whole patterning flow with realistic process-dependent three-dimensional (3-D) profile and topology. We use this tool to study the patterning process variations of the N7 M1 layer including the overlay control, the critical dimension uniformity budget, and the lithographic process window (PW). The resulting 3-D pattern structure can be used to optimize the process flow, verify design rules, extract parasitics, and most importantly, simulate the electric field, and identify hot spots for dielectric reliability. As an example application, the maximum electric field at M1 tip-to-tip, which is one of the most critical patterning locations, has been simulated and extracted. The approach helps to investigate the impact of process variations on dielectric reliability. We have also assessed the alternative M1 patterning flow with a single exposure block using extreme ultraviolet lithography (EUVL) and analyzed its advantages compared to the LE3 block approach.

Micro-PIV/LIF measurements on electrokinetically-driven flow in surface modified microchannels

NASA Astrophysics Data System (ADS)

Ichiyanagi, Mitsuhisa; Sasaki, Seiichi; Sato, Yohei; Hishida, Koichi

2009-04-01

Effects of surface modification patterning on flow characteristics were investigated experimentally by measuring electroosmotic flow velocities, which were obtained by micron-resolution particle image velocimetry using a confocal microscope. The depth-wise velocity was evaluated by using the continuity equation and the velocity data. The microchannel was composed of a poly(dimethylsiloxane) chip and a borosilicate cover-glass plate. Surface modification patterns were fabricated by modifying octadecyltrichlorosilane (OTS) on the glass surface. OTS can decrease the electroosmotic flow velocity compared to the velocity in the glass microchannel. For the surface charge varying parallel to the electric field, the depth-wise velocity was generated at the boundary area between OTS and the glass surfaces. For the surface charge varying perpendicular to the electric field, the depth-wise velocity did not form because the surface charge did not vary in the stream-wise direction. The surface charge pattern with the oblique stripes yielded a three-dimensional flow in a microchannel. Furthermore, the oblique patterning was applied to a mixing flow field in a T-shaped microchannel, and mixing efficiencies were evaluated from heterogeneity degree of fluorescent dye intensity, which was obtained by laser-induced fluorescence. It was found that the angle of the oblique stripes is an important factor to promote the span-wise and depth-wise momentum transport and contributes to the mixing flow in a microchannel.

Geologic mapping on the deep seafloor: Reconstructing lava flow emplacement and eruptive history at the Galápagos Spreading Center

NASA Astrophysics Data System (ADS)

McClinton, J. T.; White, S.; Colman, A.; Sinton, J. M.; Bowles, J. A.

2012-12-01

The deep seafloor imposes significant difficulties on data collection that require the integration of multiple data sets and the implementation of unconventional geologic mapping techniques. We combine visual mapping of geological contacts by submersible with lava flow morphology maps and relative and absolute age constraints to create a spatiotemporal framework for examining submarine lava flow emplacement at the intermediate-spreading, hotspot-affected Galápagos Spreading Center (GSC). We mapped 18 lava flow fields, interpreted to be separate eruptive episodes, within two study areas at the GSC using visual observations of superposition, surface preservation and sediment cover from submersible and towed camera surveys, augmented by high-resolution sonar surveys and sample petrology [Colman et al., Effects of variable magma supply on mid-ocean ridge eruptions: Constraints from mapped lava flow fields along the Galápagos Spreading Center; 2012 G3]. We also mapped the lava flow morphology within the majority of these eruptive units using an automated, machine-learning classification method [McClinton et al., Neuro-fuzzy classification of submarine lava flow morphology; 2012 PE&RS]. The method combines detailed geometric, acoustic, and textural attributes derived from high-resolution sonar data with visual observations and a machine-learning algorithm to classify submarine lava flow morphology as pillows, lobates, or sheets. The resulting lava morphology maps are a valuable tool for interpreting patterns in the emplacement of submarine lava flows at a mid-ocean ridge (MOR). Within our study area at 92°W, where the GSC has a relatively high magma supply, high effusion rate sheet and lobate lavas are more abundant in the oldest mapped eruptive units, while the most recent eruptions mostly consist of low effusion rate pillow lavas. The older eruptions (roughly 400yrs BP by paleomagnetic intensity) extend up to 1km off axis via prominent channels and tubes, while the most recent eruptions (<100yrs BP by paleomagnetic intensity) are mainly on-axis pillow ridges and domes. These spatial and temporal trends suggest a gradual transition from low-relief, "paving" eruptions to relief-building, "constructional" eruptions. In our second study area at 95°W, where magma supply is lower, eruptions mostly consist of axial seamounts and irregularly shaped clusters of pillow mounds. Many have summit plateaus with inflated, partially collapsed lobate lavas suggesting variable effusion rates and topographic influence on lava flows. In addition, a relatively extensive (~9.5km2) flow field of inflated lobate and sheet lavas erupted from vents ~1km north of the ridge axis and flowed ~1km into the inner axial graben through channels and tubes, ponding against older structures and leaving prominent "bathtub rings" and collapse features. This eruption provides direct evidence that large, high effusion rate eruptions can occur in low magma supply settings at MORs.

Perceptual learning in a non-human primate model of artificial vision

PubMed Central

Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.

2016-01-01

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058

Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning.

PubMed

Solouki, Saeed; Pooyan, Mohammad

2016-06-01

Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular structure of the cerebellum has been in the core of attention in theoretical and computational modeling. However, most of these models reflect some special features of the cerebellum without regarding the whole motor command computational process. In this paper, we try to make a logical relation between the most significant models of the cerebellum and introduce a new learning strategy to arrange the movement patterns: cerebellar modular arrangement and applying of movement patterns based on semi-supervised learning (CMAPS). We assume here the cerebellum like a big archive of patterns that has an efficient organization to classify and recall them. The main idea is to achieve an optimal use of memory locations by more than just a supervised learning and classification algorithm. Surely, more experimental and physiological researches are needed to confirm our hypothesis.

Simulation of interior ballistics flows in a shock tube

NASA Astrophysics Data System (ADS)

Seiler, F.

1983-07-01

The flow in front of and behind a projectile was investigated in a interior ballistics shock tube simulator. Flow patterns and heat flow were examined for flows with and without gas leakage. The boundary layers behind the piston can clearly be shown by differential interferograms. The dependence of the heat flow into the measuring tube wall on the base form is smaller than the signal perturbations. Flow patterns show no appreciable effect of gas leakage on the flow behind the piston; strong flow effects arise in front of the piston. The same effects are shown by heat flow measurements. In case of gas leakage heat flows into the tube wall before the piston reaches the wall. In the slit between piston and wall a maximum heat flow is found. High temperature gradients, due to the fact that hot gases come closer to the tube wall than in the boundary layer flow behind the piston, lead to high thermal loading of the wall materials which can cause cracks.

Effects of Gravity on Cocurrent Two-Phase Gas-Liquid Flows Through Packed Columns

NASA Technical Reports Server (NTRS)

Motil, Brian J.; Balakotaiah, Vemuri; Kamotani, Yasuhiro

2001-01-01

This work presents the experimental results of research on the influence of gravity on flow pattern transitions, pressure drop and flow characteristics for cocurrent gas-liquid two-phase flow through packed columns. The flow pattern transition data indicates that the pulse flow regime exists over a wider range of gas and liquid flow rates under reduced gravity conditions compared to normal gravity cocurrent down-flow. This is illustrated by comparing the flow regime transitions found in reduced gravity with the transitions predicted by Talmor. Next, the effect of gravity on the total pressure drop in a packed column is shown to depend on the flow regime. The difference is roughly equivalent to the liquid static head for bubbly flow but begins to decrease at the onset of pulse flow. As the spray flow regime is approached by increasing the gas to liquid ratio, the effect of gravity on pressure drop becomes negligible. Finally, gravity tends to suppress the amplitude of each pressure pulse. An example of this phenomenon is presented.

A novel anisotropic fast marching method and its application to blood flow computation in phase-contrast MRI.

PubMed

Schwenke, M; Hennemuth, A; Fischer, B; Friman, O

2012-01-01

Phase-contrast MRI (PC MRI) can be used to assess blood flow dynamics noninvasively inside the human body. The acquired images can be reconstructed into flow vector fields. Traditionally, streamlines can be computed based on the vector fields to visualize flow patterns and particle trajectories. The traditional methods may give a false impression of precision, as they do not consider the measurement uncertainty in the PC MRI images. In our prior work, we incorporated the uncertainty of the measurement into the computation of particle trajectories. As a major part of the contribution, a novel numerical scheme for solving the anisotropic Fast Marching problem is presented. A computing time comparison to state-of-the-art methods is conducted on artificial tensor fields. A visual comparison of healthy to pathological blood flow patterns is given. The comparison shows that the novel anisotropic Fast Marching solver outperforms previous schemes in terms of computing time. The visual comparison of flow patterns directly visualizes large deviations of pathological flow from healthy flow. The novel anisotropic Fast Marching solver efficiently resolves even strongly anisotropic path costs. The visualization method enables the user to assess the uncertainty of particle trajectories derived from PC MRI images.

Impact of wall hydrophobicity on condensation flow and heat transfer in silicon microchannels

NASA Astrophysics Data System (ADS)

Fang, Chen; Steinbrenner, Julie E.; Wang, Fu-Min; Goodson, Kenneth E.

2010-04-01

While microchannel condensation has been the subject of several recent studies, the critical impact of wall hydrophobicity on the microchannel condensation flow has received very little attention. The paper experimentally studies steam condensation in a silicon microchannel 286 µm in hydraulic diameter with three different wall hydrophobicities. It is found that the channel surface wettability has a significant impact on the flow pattern, pressure drop and heat transfer characteristic. Spatial flow pattern transition is observed in both hydrophobic and hydrophilic channels. In the hydrophobic channel, the transition from dropwise/slugwise flow to plug flow is induced by the slug instability. In the hydrophilic channel, the flow transition is characterized by the periodic bubble detachment, a process in which pressure evolution is found important. Local temperature measurement is conducted and heat flux distribution in the microchannel is reconstructed. For the same inlet vapor flux and temperature, the hydrophobic microchannel yields higher heat transfer rate and pressure drop compared to the hydrophilic channel. The difference is attributed to the distinction in flow pattern and heat transfer mechanism dictated by the channel hydrophobicity. This study highlights the importance of the channel hydrophobicity control for the optimization of the microchannel condenser.

Thermophoretic motion behavior of submicron particles in boundary-layer-separation flow around a droplet.

PubMed

Wang, Ao; Song, Qiang; Ji, Bingqiang; Yao, Qiang

2015-12-01

As a key mechanism of submicron particle capture in wet deposition and wet scrubbing processes, thermophoresis is influenced by the flow and temperature fields. Three-dimensional direct numerical simulations were conducted to quantify the characteristics of the flow and temperature fields around a droplet at three droplet Reynolds numbers (Re) that correspond to three typical boundary-layer-separation flows (steady axisymmetric, steady plane-symmetric, and unsteady plane-symmetric flows). The thermophoretic motion of submicron particles was simulated in these cases. Numerical results show that the motion of submicron particles around the droplet and the deposition distribution exhibit different characteristics under three typical flow forms. The motion patterns of particles are dependent on their initial positions in the upstream and flow forms. The patterns of particle motion and deposition are diversified as Re increases. The particle motion pattern, initial position of captured particles, and capture efficiency change periodically, especially during periodic vortex shedding. The key effects of flow forms on particle motion are the shape and stability of the wake behind the droplet. The drag force of fluid and the thermophoretic force in the wake contribute jointly to the deposition of submicron particles after the boundary-layer separation around a droplet.

Turbulent flow in a vessel agitated by side entering inclined blade turbine with different diameter using CFD simulation

NASA Astrophysics Data System (ADS)

Fathonah, N. N.; Nurtono, T.; Kusdianto; Winardi, S.

2018-03-01

Single phase turbulent flow in a vessel agitated by side entering inclined blade turbine has simulated using CFD. The aim of this work is to identify the hydrodynamic characteristics of a model vessel, which geometrical configuration is adopted at industrial scale. The laboratory scale model vessel is a flat bottomed cylindrical tank agitated by side entering 4-blade inclined blade turbine with impeller rotational speed N=100-400 rpm. The effect of the impeller diameter on fluid flow pattern has been investigated. The fluid flow patterns in a vessel is essentially characterized by the phenomena of macro-instabilities, i.e. the flow patterns change with large scale in space and low frequency. The intensity of fluid flow in the tank increase with the increase of impeller rotational speed from 100, 200, 300, and 400 rpm. It was accompanied by shifting the position of the core of circulation flow away from impeller discharge stream and approached the front of the tank wall. The intensity of fluid flow in the vessel increase with the increase of the impeller diameter from d=3 cm to d=4 cm.

Effect of the mitral valve on diastolic flow patterns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seo, Jung Hee; Vedula, Vijay; Mittal, Rajat, E-mail: mittal@jhu.edu

2014-12-15

The leaflets of the mitral valve interact with the mitral jet and significantly impact diastolic flow patterns, but the effect of mitral valve morphology and kinematics on diastolic flow and its implications for left ventricular function have not been clearly delineated. In the present study, we employ computational hemodynamic simulations to understand the effect of mitral valve leaflets on diastolic flow. A computational model of the left ventricle is constructed based on a high-resolution contrast computed-tomography scan, and a physiological inspired model of the mitral valve leaflets is synthesized from morphological and echocardiographic data. Simulations are performed with a diodemore » type valve model as well as the physiological mitral valve model in order to delineate the effect of mitral-valve leaflets on the intraventricular flow. The study suggests that a normal physiological mitral valve promotes the formation of a circulatory (or “looped”) flow pattern in the ventricle. The mitral valve leaflets also increase the strength of the apical flow, thereby enhancing apical washout and mixing of ventricular blood. The implications of these findings on ventricular function as well as ventricular flow models are discussed.« less

Flow pattern in the ventricle of brain with cilia beating and CSF circulation

NASA Astrophysics Data System (ADS)

Wang, Yong; Westendorf, Christian; Faubel, Regina; Eichele, Gregor; Bodenschatz, Eberhard

We recently discovered that cilia of the ventral third ventricle (v3V) of mammalian brain generate a complex flow network close to the wall. However, the flow pattern in the overall three dimensional v3V, especially under physiological condition, remains to be investigated. Computational fluid dynamics is arguably the best approach for such investigations. Several v3V geometries are reconstructed from different data for comparison study. The lattice Boltzmann method and immersed boundary method are used to reproduce the experimental set-up for an opened v3V firstly. The experimentally recorded cilia induced flow network is projected on the curved v3V wall. The flow maps obtained numerically at different heights from the v3V wall agree with the experimental data qualitatively. We then consider the entire v3V with ciliary flow network along the wall for boundary condition. Moreover, we add a time dependent flow rate to represent the CSF circulation, and study flow pattern in the ventricle. We thank the Max Planck Society (MPG) for financial support. This work is conducted within the Physics and Medicine Initiative at Goettingen Campus between MPG and University Medical Center.

Flow Patterns of Lobate Debris Aprons and Lineated Valley Fill North of Ismeniae Fossae, Mars

NASA Astrophysics Data System (ADS)

Baker, D. M.; Head, J. W.; Marchant, D. R.

2009-03-01

Flow patterns are mapped within lobate debris aprons and lineated valley fill north of Ismeniae Fossae, Mars. Flowlines are sourced in plateau alcoves and form large, well-integrated systems, consistent with a debris-covered glacier interpretation.

Use of soil moisture dynamics and patterns for the investigation of runoff generation processes with emphasis on preferential flow

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2007-08-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

A Factor Affecting Transonic Leading-edge Flow Separation

NASA Technical Reports Server (NTRS)

Wood, George P; Gooderum, Paul B

1956-01-01

A change in flow pattern that was observed as the free-stream Mach number was increased in the vicinity of 0.8 was described in NACA Technical Note 1211 by Lindsey, Daley, and Humphreys. The flow on the upper surface behind the leading edge of an airfoil at an angle of attack changed abruptly from detached flow with an extensive region of separation to attached supersonic flow terminated by a shock wave. In the present paper, the consequences of shock-wave - boundary layer interaction are proposed as a factor that may be important in determining the conditions under which the change in flow pattern occurs. Some experimental evidence in support of the importance of this factor is presented.