fast learning rates: Topics by Science.gov

Sample records for fast learning rates

Cognitive learning: a machine learning approach for automatic process characterization from design

NASA Astrophysics Data System (ADS)

Foucher, J.; Baderot, J.; Martinez, S.; Dervilllé, A.; Bernard, G.

2018-03-01

Cutting edge innovation requires accurate and fast process-control to obtain fast learning rate and industry adoption. Current tools available for such task are mainly manual and user dependent. We present in this paper cognitive learning, which is a new machine learning based technique to facilitate and to speed up complex characterization by using the design as input, providing fast training and detection time. We will focus on the machine learning framework that allows object detection, defect traceability and automatic measurement tools.
Quality Rating and Improvement System (QRIS) Validation Study Designs. CEELO FastFacts

ERIC Educational Resources Information Center

Schilder, D.

2013-01-01

In this "Fast Facts," a state has received Race to the Top Early Learning Challenge funds and is seeking information to inform the design of the Quality Rating and Improvement System (QRIS) validation study. The Center on Enhancing Early Learning Outcomes (CEELO) responds that according to Resnick (2012), validation of a QRIS is an…
Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069
Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.
The effect of presentation rate on implicit sequence learning in aging.

PubMed

Foster, Chris M; Giovanello, Kelly S

2017-02-01

Implicit sequence learning is thought to be preserved in aging when the to-be learned associations are first-order; however, when associations are second-order, older adults (OAs) tend to experience deficits as compared to young adults (YAs). Two experiments were conducted using a first (Experiment 1) and second-order (Experiment 2) serial-reaction time task. Stimuli were presented at a constant rate of either 800 milliseconds (fast) or 1200 milliseconds (slow). Results indicate that both age groups learned first-order dependencies equally in both conditions. OAs and YAs also learned second-order dependencies, but the learning of lag-2 information was significantly impacted by the rate of presentation for both groups. OAs showed significant lag-2 learning in slow condition while YAs showed significant lag-2 learning in the fast condition. The sensitivity of implicit sequence learning to the rate of presentation supports the idea that OAs and YAs different processing speeds impact the ability to build complex associations across time and intervening events.
One-trial overshadowing: Evidence for fast specific fear learning in humans.

PubMed

Haesen, Kim; Beckers, Tom; Baeyens, Frank; Vervliet, Bram

2017-03-01

Adaptive defensive actions necessitate a fear learning system that is both fast and specific. Fast learning serves to minimize the number of threat confrontations, while specific learning ensures that the acquired fears are tied to threat-relevant cues only. In Pavlovian fear conditioning, fear acquisition is typically studied via repetitive pairings of a single cue with an aversive experience, which is not optimal for the examination of fast specific fear learning. In this study, we adopted the one-trial overshadowing procedure from basic learning research, in which a combination of two visual cues is presented once and paired with an aversive electrical stimulation. Using on-line shock expectancy ratings, skin conductance reactivity and startle reflex modulation as indices of fear learning, we found evidence of strong fear after a single conditioning trial (fast learning) as well as attenuated fear responding when only half of the trained stimulus combination was presented (specific learning). Moreover, specificity of fear responding tended to correlate with levels of state and trait anxiety. These results suggest that one-trial overshadowing can be used as a model to study fast specific fear learning in humans and individual differences therein. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Neurocomputational Account of Taxonomic Responding and Fast Mapping in Early Word Learning

ERIC Educational Resources Information Center

Mayor, Julien; Plunkett, Kim

2010-01-01

We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to…
Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

PubMed

Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.
Dynamic functional connectivity shapes individual differences in associative learning.

PubMed

Fatima, Zainab; Kovacevic, Natasha; Misic, Bratislav; McIntosh, Anthony Randal

2016-11-01

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Reading Fluency and Students with Reading Disabilities: How Fast Is Fast Enough to Promote Reading Comprehension?

ERIC Educational Resources Information Center

O'Connor, Rollanda E.

2018-01-01

The goal of improving reading rate and fluency is to positively impact reading comprehension; however, it is unclear how fast students with learning disabilities (LD) need to read to reap this benefit. The purpose of this research was to identify the point of diminishing return for students who were dysfluent readers. Participants included 337…
Fast Mapping Across Time: Memory Processes Support Children's Retention of Learned Words.

PubMed

Vlach, Haley A; Sandhofer, Catherine M

2012-01-01

Children's remarkable ability to map linguistic labels to referents in the world is commonly called fast mapping. The current study examined children's (N = 216) and adults' (N = 54) retention of fast-mapped words over time (immediately, after a 1-week delay, and after a 1-month delay). The fast mapping literature often characterizes children's retention of words as consistently high across timescales. However, the current study demonstrates that learners forget word mappings at a rapid rate. Moreover, these patterns of forgetting parallel forgetting functions of domain-general memory processes. Memory processes are critical to children's word learning and the role of one such process, forgetting, is discussed in detail - forgetting supports extended mapping by promoting the memory and generalization of words and categories.
An Integrated Learning Management System for Islamic Studies: An Innovation from Jordan

ERIC Educational Resources Information Center

Rumzan, Ismael; Chowdhury, Imran; Mirza, Saudah; Idil, Raidah Shah

2010-01-01

The use of ICT in the Middle East is expanding at a fast rate; hence managers and decision makers must decide on the best learning solution for their organizations. This article describes how a small team of individuals in Jordan developed an effective learning solution to a social problem. This may provide some useful lessons for other…
Adaptive Learning and Pruning Using Periodic Packet for Fast Invariance Extraction and Recognition

NASA Astrophysics Data System (ADS)

Chang, Sheng-Jiang; Zhang, Bian-Li; Lin, Lie; Xiong, Tao; Shen, Jin-Yuan

2005-02-01

A new learning scheme using a periodic packet as the neuronal activation function is proposed for invariance extraction and recognition of handwritten digits. Simulation results show that the proposed network can extract the invariant feature effectively and improve both the convergence and the recognition rate.
Velocity-based motion categorization by pigeons.

PubMed

Cook, Robert G; Beale, Kevin; Koban, Angie

2011-04-01

To examine if animals could learn action-like categorizations in a manner similar to noun-based categories, eight pigeons were trained to categorize rates of object motion. Testing 40 different objects in a go/no-go discrimination, pigeons were first trained to discriminate between fast and slow rates of object rotation around their central y-axis. They easily learned this velocity discrimination and transferred it to novel objects and rates. This discrimination also transferred to novel types of motions including the other two axes of rotation and two new translations around the display. Comparable tests with rapid and slow changes in the objects' size, color, and shape failed to support comparable transfer. This difference in discrimination transfer between motion-based and property-based changes suggests the pigeons had learned motion concept rather than one based on change per se. The results provide evidence that pigeons can acquire an understanding of motion-based actions, at least with regard to the property of object velocity. This may be similar to our use of verbs and adverbs to categorize different classes of behavior or motion (e.g., walking, jogging, or running slow vs. fast).
STDP allows fast rate-modulated coding with Poisson-like spike trains.

PubMed

Gilson, Matthieu; Masquelier, Timothée; Hugues, Etienne

2011-10-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (~10-20 ms) for sufficiently many inputs (~100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks.
STDP Allows Fast Rate-Modulated Coding with Poisson-Like Spike Trains

PubMed Central

Hugues, Etienne

2011-01-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks. PMID:22046113
Nuclear Engineering Computer Modules, Thermal-Hydraulics, TH-2: Liquid Metal Fast Breeder Reactors.

ERIC Educational Resources Information Center

Reihman, Thomas C.

This learning module is concerned with the temperature field, the heat transfer rates, and the coolant pressure drop in typical liquid metal fast breeder reactor (LMFBR) fuel assemblies. As in all of the modules of this series, emphasis is placed on developing the theory and demonstrating the use with a simplified model. The heart of the module is…
Tracking the Speech Signal--Time-Locked MEG Signals during Perception of Ultra-Fast and Moderately Fast Speech in Blind and in Sighted Listeners

ERIC Educational Resources Information Center

Hertrich, Ingo; Dietrich, Susanne; Ackermann, Hermann

2013-01-01

Blind people can learn to understand speech at ultra-high syllable rates (ca. 20 syllables/s), a capability associated with hemodynamic activation of the central-visual system. To further elucidate the neural mechanisms underlying this skill, magnetoencephalographic (MEG) measurements during listening to sentence utterances were cross-correlated…
Fast mapping rapidly integrates information into existing memory networks.

PubMed

Coutanche, Marc N; Thompson-Schill, Sharon L

2014-12-01

Successful learning involves integrating new material into existing memory networks. A learning procedure known as fast mapping (FM), thought to simulate the word-learning environment of children, has recently been linked to distinct neuroanatomical substrates in adults. This idea has suggested the (never-before tested) hypothesis that FM may promote rapid incorporation into cortical memory networks. We test this hypothesis here in 2 experiments. In our 1st experiment, we introduced 50 participants to 16 unfamiliar animals and names through FM or explicit encoding (EE) and tested participants on the training day, and again after sleep. Learning through EE produced strong declarative memories, without immediate lexical competition, as expected from slow-consolidation models. Learning through FM, however, led to almost immediate lexical competition, which continued to the next day. Additionally, the learned words began to prime related concepts on the day following FM (but not EE) training. In a 2nd experiment, we replicated the lexical integration results and determined that presenting an already-known item during learning was crucial for rapid integration through FM. The findings presented here indicate that learned items can be integrated into cortical memory networks at an accelerated rate through fast mapping. The retrieval of a related known concept, in order to infer the target of the FM question, is critical for this effect. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Facilitation of learning induced by both random and gradual visuomotor task variation

PubMed Central

Braun, Daniel A.; Wolpert, Daniel M.

2012-01-01

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between −60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→−30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes. PMID:22131385

Improving Responsiveness to Intervention for English-Language Learners: A Comparison of Instructional Pace on Letter Naming Rates

ERIC Educational Resources Information Center

Gilbertson, Donna; Bluck, John

2006-01-01

An alternating treatments design was used to compare the effects of a 1-s and a 5-s paced intervention on rates of letter naming by English Language Learners (ELL). Participants were four kindergarten students performing below the average letter naming level and learning rate than other ELL classmates. The fast paced intervention consisted of a…
Investigating Speech Motor Practice and Learning in People Who Stutter

ERIC Educational Resources Information Center

Namasivayam, Aravind Kumar; van Lieshout, Pascal

2008-01-01

In this exploratory study, we investigated whether or not people who stutter (PWS) show motor practice and learning changes similar to those of people who do not stutter (PNS). To this end, five PWS and five PNS repeated a set of non-words at two different rates (normal and fast) across three test sessions (T1, T2 on the same day and T3 on a…
Statistical word learning in children with autism spectrum disorder and specific language impairment.

PubMed

Haebig, Eileen; Saffran, Jenny R; Ellis Weismer, Susan

2017-11-01

Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined underlying mechanisms of word learning, specifically, statistical learning and fast-mapping, in school-aged children with typical and atypical development. Statistical learning was assessed through a word segmentation task and fast-mapping was examined in an object-label association task. We also examined children's ability to map meaning onto newly segmented words in a third task that combined exposure to an artificial language and a fast-mapping task. Children with SLI had poorer performance on the word segmentation and fast-mapping tasks relative to the typically developing and ASD groups, who did not differ from one another. However, when children with SLI were exposed to an artificial language with phonemes used in the subsequent fast-mapping task, they successfully learned more words than in the isolated fast-mapping task. There was some evidence that word segmentation abilities are associated with word learning in school-aged children with typical development and ASD, but not SLI. Follow-up analyses also examined performance in children with ASD who did and did not have a language impairment. Children with ASD with language impairment evidenced intact statistical learning abilities, but subtle weaknesses in fast-mapping abilities. As the Procedural Deficit Hypothesis (PDH) predicts, children with SLI have impairments in statistical learning. However, children with SLI also have impairments in fast-mapping. Nonetheless, they are able to take advantage of additional phonological exposure to boost subsequent word-learning performance. In contrast to the PDH, children with ASD appear to have intact statistical learning, regardless of language status; however, fast-mapping abilities differ according to broader language skills. © 2017 Association for Child and Adolescent Mental Health.
Adaptive filter design using recurrent cerebellar model articulation controller.

PubMed

Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S

2010-07-01

A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.
Rapid consolidation of new knowledge in adulthood via fast mapping.

PubMed

Coutanche, Marc N; Thompson-Schill, Sharon L

2015-09-01

Rapid word learning, where words are 'fast mapped' onto new concepts, may help build vocabulary during childhood. Recent evidence has suggested that fast mapping might help to rapidly integrate information into memory networks of the adult neocortex. The neural basis for this learning by fast mapping determines key properties of the learned information. Copyright © 2015 Elsevier Ltd. All rights reserved.
The Adverse Effects and Treatment Results of Smoking Cessation Pharmacotherapy During Fasting/Non-Fasting State.

PubMed

Iliaz, Sinem; Tural Onur, Seda; Uysal, Mehmet Atilla; Chousein, Efsun Gonca Uğur; Tanriverdi, Elif; Bagci, Belma Akbaba; Bahadir, Ayse; Hattatoglu, Didem Gorgun; Ortakoylu, Mediha Gonenc; Yurt, Sibel

2017-07-03

Cigarette smoking is one of the most common addictions worldwide. Muslim smokers reduce the number of cigarettes they smoke during Ramadan due to the long fasting hours. We aimed to share our experience in a smoking cessation clinic during Ramadan by analyzing the efficacy and adverse effects of once-daily dosing of bupropion or varenicline in a fasting group compared with conventional dosing in a non-fasting group. We analyzed 57 patients who attended our smoking cessation clinic during Ramadan of 2014 and 2015, and at least one follow-up visit. For the fasting patients, we prescribed bupropion or varenicline after dinner (once daily) as the maintenance therapy. We recorded demographic characteristics of the patients, fasting state, drugs taken for smoking cessation, and the dosage of the medication. At the first follow-up visit, adverse effects seen with the treatment were recorded. We conducted telephone interviews 6 months after the first visits of the patients to learn the current smoking status of the groups. Of the total 57 patients, 20 (35.1%) were fasting and 37 (64.9%) were not fasting. Fasting and non-fasting patients were similar for sex, age, smoking pack-years, marital status, educational status, and mean Fagerström scores (p >.05). Adverse effects and quit rates after 6 months of follow-up were similar between the fasting and non-fasting groups (p >.05). Although our sample size was small, we found no difference in the rates of adverse effects or smoking cessation using a single daily oral dose of bupropion or varenicline between a fasting group and a non-fasting group that received conventional dosing.
Rats socially-reared and full fed learned an autoshaping task, showing less levels of fear-like behaviour than fasted or singly-reared rats.

PubMed

Molina-Hernández, Miguel; Téllez-Alcántara, N Patricia

2004-07-01

During the learning of instrumental tasks, rats are usually fasted to increase reinforced learning. However, fasting produces several undesirable side effects. The aim of this study was to test the hypothesis that control rats, i.e. full-fed and group-reared rats, will learn an autoshaping task to the same level as fasted or singly-reared rats. The interaction between fasting and single-rearing of rats was also tested. Results showed that control rats and fasted rats acquired the autoshaping task similarly, independently of rearing condition or gender. However, fasted or singly-reared rats produced fear-like behaviour, since male rats group-reared and fasted (85% body/wt, P <0.05), male rats singly-reared (full fed, P <0.05; 12 h fasted, P <0.05; 85% body/wt, P <0.05), female rats group-reared (12 h fasted, P <0.05; 85% body/wt, P <0.05) and female rats singly reared (full fed, P <0.05; 12 h fasted, P <0.05; 85% body/wt, P <0.05) displayed reduced amounts of time exploring the open arms of the elevated plus-maze. In conclusion, control rats learned the autoshaping task to the same level as fasted or singly-reared rats. However, fasting or single-rearing produced fear-like behaviour. Thus, the training of control rats in autoshaping tasks may be an option that improves animal welfare.
Distributed reinforcement learning for adaptive and robust network intrusion response

NASA Astrophysics Data System (ADS)

Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

2015-07-01

Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.
Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
New Software for the Fast Estimation of Population Recombination Rates (FastEPRR) in the Genomic Era.

PubMed

Gao, Feng; Ming, Chen; Hu, Wangjie; Li, Haipeng

2016-06-01

Genetic recombination is a very important evolutionary mechanism that mixes parental haplotypes and produces new raw material for organismal evolution. As a result, information on recombination rates is critical for biological research. In this paper, we introduce a new extremely fast open-source software package (FastEPRR) that uses machine learning to estimate recombination rate [Formula: see text] (=[Formula: see text]) from intraspecific DNA polymorphism data. When [Formula: see text] and the number of sampled diploid individuals is large enough ([Formula: see text]), the variance of [Formula: see text] remains slightly smaller than that of [Formula: see text] The new estimate [Formula: see text] (calculated by averaging [Formula: see text] and [Formula: see text]) has the smallest variance of all cases. When estimating [Formula: see text], the finite-site model was employed to analyze cases with a high rate of recurrent mutations, and an additional method is proposed to consider the effect of variable recombination rates within windows. Simulations encompassing a wide range of parameters demonstrate that different evolutionary factors, such as demography and selection, may not increase the false positive rate of recombination hotspots. Overall, accuracy of FastEPRR is similar to the well-known method, LDhat, but requires far less computation time. Genetic maps for each human population (YRI, CEU, and CHB) extracted from the 1000 Genomes OMNI data set were obtained in less than 3 d using just a single CPU core. The Pearson Pairwise correlation coefficient between the [Formula: see text] and [Formula: see text] maps is very high, ranging between 0.929 and 0.987 at a 5-Mb scale. Considering that sample sizes for these kinds of data are increasing dramatically with advances in next-generation sequencing technologies, FastEPRR (freely available at http://www.picb.ac.cn/evolgen/) is expected to become a widely used tool for establishing genetic maps and studying recombination hotspots in the population genomic era. Copyright © 2016 Gao et al.
Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping.

PubMed

Atir-Sharon, Tali; Gilboa, Asaf; Hazan, Hananel; Koilis, Ester; Manevitz, Larry M

2015-01-01

Neocortical structures typically only support slow acquisition of declarative memory; however, learning through fast mapping may facilitate rapid learning-induced cortical plasticity and hippocampal-independent integration of novel associations into existing semantic networks. During fast mapping the meaning of new words and concepts is inferred, and durable novel associations are incidentally formed, a process thought to support early childhood's exuberant learning. The anterior temporal lobe, a cortical semantic memory hub, may critically support such learning. We investigated encoding of semantic associations through fast mapping using fMRI and multivoxel pattern analysis. Subsequent memory performance following fast mapping was more efficiently predicted using anterior temporal lobe than hippocampal voxels, while standard explicit encoding was best predicted by hippocampal activity. Searchlight algorithms revealed additional activity patterns that predicted successful fast mapping semantic learning located in lateral occipitotemporal and parietotemporal neocortex and ventrolateral prefrontal cortex. By contrast, successful explicit encoding could be classified by activity in medial and dorsolateral prefrontal and parahippocampal cortices. We propose that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge. In healthy adults, this is better captured by unique anterior and lateral temporal lobe activity patterns, while hippocampal involvement is less predictive of this kind of learning.
Andragogical and Pedagogical Methods for Curriculum and Program Development

ERIC Educational Resources Information Center

Wang, Victor C. X., Ed.; Bryan, Valerie C., Ed.

2014-01-01

Today's ever-changing learning environment is characterized by the fast pace of technology that drives our society to move forward, and causes our knowledge to increase at an exponential rate. The need for in-depth research that is bound to generate new knowledge about curriculum and program development is becoming ever more relevant.…
Investigating Word Learning in Fragile X Syndrome: A Fast-Mapping Study

ERIC Educational Resources Information Center

McDuffie, Andrea; Kover, Sara T.; Hagerman, Randi; Abbeduto, Leonard

2013-01-01

Fast-mapping paradigms have not been used previously to examine the process of word learning in boys with fragile X syndrome (FXS), who are likely to have intellectual impairment, language delays, and symptoms of autism. In this study, a fast-mapping task was used to investigate associative word learning in 4- to 10-year-old boys with FXS relative…
Research on a pulmonary nodule segmentation method combining fast self-adaptive FCM and classification.

PubMed

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms.
Effects of Fasting During Ramadan Month on Cognitive Function in Muslim Athletes

PubMed Central

Tian, Ho-Heng; Aziz, Abdul-Rashid; Png, Weileen; Wahid, Mohamed Faizul; Yeo, Donald; Constance Png, Ai-Li

2011-01-01

Purpose Our study aimed to profile the effect of fasting during the Ramadan month on cognitive function in a group of healthy Muslim athletes. Methods Eighteen male athletes underwent computerized neuropsychological testing during (fasting) and after (non-fasting) Ramadan. Diet was standardized, and tests were performed at 0900h and 1600h to characterize potential time-of-day (TOD) interactions. Psychomotor function (processing speed), vigilance (visual attention), visual learning and memory, working memory (executive function), verbal learning and memory were examined. Capillary glucose, body temperature, urine specific gravity, and sleep volume were also recorded. Results Fasting effects were observed for psychomotor function (Cohen's d=1.3, P=0.01) and vigilance (d=0.6, P=0.004), with improved performance at 0900h during fasting; verbal learning and memory was poorer at 1600h (d=-0.8, P=0.03). A TOD effect was present for psychomotor function (d=-0.4, P<0.001), visual learning (d=-0.5, P=0.04), verbal learning and memory (d=-1.3, P=0.001), with poorer performances at 1600h. There was no significant fasting effect on visual learning and working memory. Conclusions Our results show that the effect of fasting on cognition is heterogeneous and domain-specific. Performance in functions requiring sustained rapid responses was better in the morning, declining in the late afternoon, whereas performance in non-speed dependent accuracy measures was more resilient. PMID:22375233
An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

PubMed

Saha, Monjoy; Chakraborty, Chandan; Arun, Indu; Ahmed, Rosina; Chatterjee, Sanjoy

2017-06-12

Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due to random morphological, color and intensity variations of cell nuclei (immunopositive and immunonegative), manual/subjective assessment of Ki-67 scoring is error-prone and time-consuming. Hence, several machine learning approaches have been reported; nevertheless, none of them had worked on deep learning based hotspots detection and proliferation scoring. In this article, we suggest an advanced deep learning model for computerized recognition of candidate hotspots and subsequent proliferation rate scoring by quantifying Ki-67 appearance in breast cancer immunohistochemical images. Unlike existing Ki-67 scoring techniques, our methodology uses Gamma mixture model (GMM) with Expectation-Maximization for seed point detection and patch selection and deep learning, comprises with decision layer, for hotspots detection and proliferation scoring. Experimental results provide 93% precision, 0.88% recall and 0.91% F-score value. The model performance has also been compared with the pathologists' manual annotations and recently published articles. In future, the proposed deep learning framework will be highly reliable and beneficial to the junior and senior pathologists for fast and efficient Ki-67 scoring.
Tobacco 101 | Smokefree 60+

Cancer.gov

Learn about the chemicals in your cigarette, and the harms caused by other forms of tobacco. What is nicotine? Nicotine is an addictive, fast-acting drug found in cigarettes. It affects your heart rate, blood pressure, brain chemistry, and mood. When you stop smoking, you experience cravings because your body is used to having a certain amount of nicotine each day.
QRIS and Inclusion: Do State QRIS Standards Support the Learning Needs of All Children? CEELO FastFact

ERIC Educational Resources Information Center

Horowitz, Michelle; Squires, Jim

2014-01-01

As the country quickly builds its efforts to enhance quality in early education and care classrooms, states are implementing Quality Rating and Improvement Systems (QRIS) to recognize and improve the quality of programs. QRIS also provides technical support and increased financial benefits for participating programs to attain higher levels of…
A new learning strategy for the two-time-scale neural controller with its application to the tracking control of rigid arms

NASA Technical Reports Server (NTRS)

Cheng, W.; Wen, J. T.

1992-01-01

A novel fast learning rule with fast weight identification is proposed for the two-time-scale neural controller, and a two-stage learning strategy is developed for the proposed neural controller. The results of the stability analysis show that both the tracking error and the fast weight error will be uniformly bounded and converge to a bounded region which depends only on the accuracy of the slow learning if the system is sufficiently excited. The efficiency of the two-stage learning is also demonstrated by a simulation of a two-link arm.
Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

PubMed Central

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120

Young Children's Fast Mapping and Generalization of Words, Facts, and Pictograms

ERIC Educational Resources Information Center

Deak, Gedeon O.; Toney, Alexis J.

2013-01-01

To test general and specific processes of symbol learning, 4- and 5-year-old children learned three kinds of abstract associates for novel objects: words, facts, and pictograms. To test fast mapping (i.e., one-trial learning) and subsequent learning, comprehension was tested after each of four exposures. Production was also tested, as was…
Variation across individuals and items determine learning outcomes from fast mapping.

PubMed

Coutanche, Marc N; Koch, Griffin E

2017-11-01

An approach to learning words known as "fast mapping" has been linked to unique neurobiological and behavioral markers in adult humans, including rapid lexical integration. However, the mechanisms supporting fast mapping are still not known. In this study, we sought to help change this by examining factors that modulate learning outcomes. In 90 subjects, we systematically manipulated the typicality of the items used to support fast mapping (foils), and quantified learners' inclination to employ semantic, episodic, and spatial memory through the Survey of Autobiographical Memory (SAM). We asked how these factors affect lexical competition and recognition performance, and then asked how foil typicality and lexical competition are related in an independent dataset. We find that both the typicality of fast mapping foils, and individual differences in how different memory systems are employed, influence lexical competition effects after fast mapping, but not after other learning approaches. Specifically, learning a word through fast mapping with an atypical foil led to lexical competition, while a typical foil led to lexical facilitation. This effect was particularly evident in individuals with a strong tendency to employ semantic memory. We further replicated the relationship between continuous foil atypicality and lexical competition in an independent dataset. These findings suggest that semantic properties of the foils that support fast mapping can influence the degree and nature of subsequent lexical integration. Further, the effects of foils differ based on an individual's tendency to draw-on the semantic memory system. Copyright © 2017 Elsevier Ltd. All rights reserved.
Procedural learning, consolidation, and transfer of a new skill in Developmental Coordination Disorder.

PubMed

Lejeune, Caroline; Wansard, Murielle; Geurten, Marie; Meulemans, Thierry

2016-01-01

The aim of this study was to explore the differences in procedural learning abilities between children with DCD and typically developing children by investigating the steps that lead to skill automatization (i.e., the stages of fast learning, consolidation, and slow learning). Transfer of the skill to a new situation was also assessed. We tested 34 children aged 6-12 years with and without DCD on a perceptuomotor adaptation task, a form of procedural learning that is thought to involve the cerebellum and the basal ganglia (regions whose impairment has been associated with DCD) but also other brain areas including frontal regions. The results showed similar rates of learning, consolidation, and transfer in DCD and control children. However, the DCD children's performance remained slower than that of controls throughout the procedural task and they reached a lower asymptotic performance level; the difficulties observed at the outset did not diminish with practice.
A new learning algorithm for a fully connected neuro-fuzzy inference system.

PubMed

Chen, C L Philip; Wang, Jing; Wang, Chi-Hsu; Chen, Long

2014-10-01

A traditional neuro-fuzzy system is transformed into an equivalent fully connected three layer neural network (NN), namely, the fully connected neuro-fuzzy inference systems (F-CONFIS). The F-CONFIS differs from traditional NNs by its dependent and repeated weights between input and hidden layers and can be considered as the variation of a kind of multilayer NN. Therefore, an efficient learning algorithm for the F-CONFIS to cope these repeated weights is derived. Furthermore, a dynamic learning rate is proposed for neuro-fuzzy systems via F-CONFIS where both premise (hidden) and consequent portions are considered. Several simulation results indicate that the proposed approach achieves much better accuracy and fast convergence.
Sleep-mediated memory consolidation depends on the level of integration at encoding.

PubMed

Himmer, Lea; Müller, Elias; Gais, Steffen; Schönauer, Monika

2017-01-01

There is robust evidence that sleep facilitates declarative memory consolidation. Integration of newly acquired memories into existing neocortical knowledge networks has been proposed to underlie this effect. Here, we test whether sleep affects memory retention for word-picture associations differently when it was learned explicitly or using a fast mapping strategy. Fast mapping is an incidental form of learning that references new information to existing knowledge and possibly allows neocortical integration already during encoding. If the integration of information into neocortical networks is a main function of sleep-dependent memory consolidation, material learned via fast mapping should therefore benefit less from sleep. Supporting this idea, we find that sleep has a protective effect on explicitly learned associations. In contrast, memory for associations learned by fast mapping does not benefit from sleep and remains stable regardless of whether sleep or wakefulness follows learning. Our results thus indicate that the need for sleep-mediated consolidation depends on the strategy used for learning and might thus be related to the level of integration of newly acquired memory achieved during encoding. Copyright © 2016 Elsevier Inc. All rights reserved.
A Randomized Field Trial of the Fast ForWord Language Computer-Based Training Program

ERIC Educational Resources Information Center

Borman, Geoffrey D.; Benson, James G.; Overman, Laura

2009-01-01

This article describes an independent assessment of the Fast ForWord Language computer-based training program developed by Scientific Learning Corporation. Previous laboratory research involving children with language-based learning impairments showed strong effects on their abilities to recognize brief and fast sequences of nonspeech and speech…
The relationship between phonological short-term memory, receptive vocabulary, and fast mapping in children with specific language impairment.

PubMed

Jackson, Emily; Leitao, Suze; Claessen, Mary

2016-01-01

Children with specific language impairment (SLI) often experience word-learning difficulties, which are suggested to originate in the early stage of word learning: fast mapping. Some previous research indicates significantly poorer fast mapping capabilities in children with SLI compared with typically developing (TD) counterparts, with a range of methodological factors impacting on the consistency of this finding. Research has explored key issues that might underlie fast mapping difficulties in children with SLI, with strong theoretical support but little empirical evidence for the role of phonological short-term memory (STM). Additionally, further research is required to explore the influence of receptive vocabulary on fast mapping capabilities. Understanding the factors associated with fast mapping difficulties that are experienced by children with SLI may lead to greater theoretically driven word-learning intervention. To investigate whether children with SLI demonstrate significant difficulties with fast mapping, and to explore the related factors. It was hypothesized that children with SLI would score significantly lower on a fast mapping production task compared with TD children, and that phonological STM and receptive vocabulary would significantly predict fast mapping production scores in both groups of children. Twenty-three children with SLI (mean = 64.39 months, SD = 4.10 months) and 26 TD children (mean = 65.92 months, SD = 2.98) were recruited from specialist language and mainstream schools. All participants took part in a unique, interactive fast-mapping task whereby nine novel objects with non-word labels were presented and production accuracy was assessed. A non-word repetition test and the Peabody Picture Vocabulary Test-Fourth Edition (PPVT-IV) were also administered as measures of phonological STM capacity and receptive vocabulary, respectively. Results of the fast-mapping task indicated that children with SLI had significantly poorer fast mapping production scores than TD children. Scores from the non-word repetition task were also significantly lower for the SLI group, revealing reduced phonological STM capacity. Phonological STM capacity and receptive vocabulary emerged as significant predictors of fast mapping performance when the group data were combined in a multiple regression analysis. These results suggest that the word-learning difficulties experienced by children with SLI may originate at the fast mapping stage, and that phonological STM and receptive vocabulary significantly predict fast mapping ability. These findings contribute to the theoretical understanding of word-learning difficulties in children with SLI and may inform lexical learning intervention. © 2015 Royal College of Speech and Language Therapists.
Personality matters: individual variation in reactions of naive bird predators to aposematic prey.

PubMed

Exnerová, Alice; Svádová, Katerina Hotová; Fucíková, Eva; Drent, Pieter; Stys, Pavel

2010-03-07

Variation in reactions to aposematic prey is common among conspecific individuals of bird predators. It may result from different individual experience but it also exists among naive birds. This variation may possibly be explained by the effect of personality--a complex of correlated, heritable behavioural traits consistent across contexts. In the great tit (Parus major), two extreme personality types have been defined. 'Fast' explorers are bold, aggressive and routine-forming; 'slow' explorers are shy, non-aggressive and innovative. Influence of personality type on unlearned reaction to aposematic prey, rate of avoidance learning and memory were tested in naive, hand-reared great tits from two opposite lines selected for exploration (slow against fast). The birds were subjected to a sequence of trials in which they were offered aposematic adult firebugs (Pyrrhocoris apterus). Slow birds showed a greater degree of unlearned wariness and learned to avoid the firebugs faster than fast birds. Although birds of both personality types remembered their experience, slow birds were more cautious in the memory test. We conclude that not only different species but also populations of predators that differ in proportions of personality types may have different impacts on survival of aposematic insects under natural conditions.
Crop-emptying rate and the design of pesticide risk assessment schemes in the honey bee and wild bees (Hymenoptera: Apidae).

PubMed

Fournier, Alice; Rollin, Orianne; Le Féon, Violette; Decourtye, Axel; Henry, Mickaël

2014-02-01

Recent scientific literature and reports from official sanitary agencies have pointed out the deficiency of current pesticide risk assessment processes regarding sublethal effects on pollinators. Sublethal effects include troubles in learning performance, orientation skills, or mobility, with possible contribution to substantial dysfunction at population scale. However, the study of sublethal effects is currently limited by considerable knowledge gaps, particularly for the numerous pollinators other than the honey bee Apis mellifera L.--the traditional model for pesticide risk assessment in pollinators. Here, we propose to use the crop-emptying time as a rule of thumb to guide the design of oral exposure experiments in the honey bee and wild bees. The administration of contaminated sucrose solutions is typically followed by a fasting time lapse to allow complete assimilation before the behavioral tests. The fasting duration should at least encompass the crop-emptying time, because no absorption takes place in the crop. We assessed crop-emptying rate in fasted bees and how it relates 1) with sucrose solution concentration in the honey bee and 2) with body mass in wild bees. Fasting duration required for complete crop emptying in honey bees fed 20 microl of a 50% sucrose solution was nearly 2 h. Actual fasting durations are usually shorter in toxicological studies, suggesting incomplete crop emptying, and therefore partial assimilation of experimental solutions that could imply underestimation of sublethal effects. We also found faster crop-emptying rates in large wild bees compared with smaller wild bees, and suggest operative rules to adapt sublethal assessment schemes accordingly.
The Relationship between Phonological Short-Term Memory, Receptive Vocabulary, and Fast Mapping in Children with Specific Language Impairment

ERIC Educational Resources Information Center

Jackson, Emily; Leitao, Suze; Claessen, Mary

2016-01-01

Background: Children with specific language impairment (SLI) often experience word-learning difficulties, which are suggested to originate in the early stage of word learning: fast mapping. Some previous research indicates significantly poorer fast mapping capabilities in children with SLI compared with typically developing (TD) counterparts, with…
Extreme learning machine: a new alternative for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters.

PubMed

Liu, Zhijian; Li, Hao; Tang, Xindong; Zhang, Xinyu; Lin, Fan; Cheng, Kewei

2016-01-01

Heat collection rate and heat loss coefficient are crucial indicators for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, wasting too much time and manpower. To address this problem, we previously used artificial neural networks and support vector machine to develop precise knowledge-based models for predicting the heat collection rates and heat loss coefficients of water-in-glass evacuated tube solar water heaters, setting the properties measured by "portable test instruments" as the independent variables. A robust software for determination was also developed. However, in previous results, the prediction accuracy of heat loss coefficients can still be improved compared to those of heat collection rates. Also, in practical applications, even a small reduction in root mean square errors (RMSEs) can sometimes significantly improve the evaluation and business processes. As a further study, in this short report, we show that using a novel and fast machine learning algorithm-extreme learning machine can generate better predicted results for heat loss coefficient, which reduces the average RMSEs to 0.67 in testing.
Educational Multimedia Profiling Recommendations for Device-Aware Adaptive Mobile Learning

ERIC Educational Resources Information Center

Moldovan, Arghir-Nicolae; Ghergulescu, Ioana; Muntean, Cristina Hava

2014-01-01

Mobile learning is seeing a fast adoption with the increasing availability and affordability of mobile devices such as smartphones and tablets. As the creation and consumption of educational multimedia content on mobile devices is also increasing fast, educators and mobile learning providers are faced with the challenge to adapt multimedia type…
Resources on Social and Emotional Development and Early Learning Standards. CEELO FastFacts

ERIC Educational Resources Information Center

Connors-Tadros, L.

2013-01-01

In this "FastFacts," a state's Department of Education requests information from the Center on Enhancing Early Learning Outcomes (CEELO) on how the research defines skills in social-emotional development, approaches to learning, and executive function, to inform planned revisions to the early childhood indicators of progress for children…
Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

PubMed

Li, Xuejian; Wang, Youqing

2016-12-01

Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.
Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

PubMed

McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

2015-07-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.
Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning

PubMed Central

Bond, Krista M.; Taylor, Jordan A.

2015-01-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. PMID:26134640
Sea ice classification using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Fung, A. K.; Manry, M. T.

1992-01-01

A first learning neural network approach to the classification of sea ice is presented. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) were tested on simulated data sets based on the known dominant scattering characteristics of the target class. Four classes were used in the data simulation: open water, thick lossy saline ice, thin saline ice, and multiyear ice. The BP network was unable to consistently converge to less than 25 percent error while the FL method yielded an average error of approximately 1 percent on the first iteration of training. The fast learning method presented can significantly reduce the CPU time necessary to train a neural network as well as consistently yield higher classification accuracy than BP networks.
Role of Plasticity at Different Sites across the Time Course of Cerebellar Motor Learning

PubMed Central

Lisberger, Stephen G.

2014-01-01

Learning comprises multiple components that probably involve cellular and synaptic plasticity at multiple sites. Different neural sites may play their largest roles at different times during behavioral learning. We have used motor learning in smooth pursuit eye movements of monkeys to determine how and when different components of learning occur in a known cerebellar circuit. The earliest learning occurs when one climbing-fiber response to a learning instruction causes simple-spike firing rate of Purkinje cells in the floccular complex of the cerebellum to be depressed transiently at the time of the instruction on the next trial. Trial-over-trial depression and the associated learning in eye movement are forgotten in <6 s, but facilitate long-term behavioral learning over a time scale of ∼5 min. During 100 repetitions of a learning instruction, simple-spike firing rate becomes progressively depressed in Purkinje cells that receive climbing-fiber inputs from the instruction. In Purkinje cells that prefer the opposite direction of pursuit and therefore do not receive climbing-fiber inputs related to the instruction, simple-spike responses undergo potentiation, but more weakly and more slowly. Analysis of the relationship between the learned changes in simple-spike firing and learning in eye velocity suggests an orderly progression of plasticity: first on Purkinje cells with complex-spike (CS) responses to the instruction, later on Purkinje cells with CS responses to the opposite direction of instruction, and last in sites outside the cerebellar cortex. Climbing-fiber inputs appear to play a fast and primary, but nonexclusive, role in pursuit learning. PMID:24849344
Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

PubMed

Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.
Cardiac e-learning: Development of a web-based implantable cardioverter defibrillator educational system.

PubMed

Hickey, Kathleen T; Johnson, Mary P; Biviano, Angelo; Aboelela, Sally; Thomas, Tami; Bakken, Suzanne; Garan, Hasan; Zimmerman, John L; Whang, William

2011-04-01

The objective of this study was to design a Web-based implantable cardioverter defibrillator (ICD) module that would allow greater access to learning which could occur at an individual's convenience outside the fast-paced clinical environment. A Web-based ICD software educational program was developed to provide general knowledge of the function of the ICD and the interpretation of the stored electrocardiograms. This learning tool could be accessed at any time via the Columbia University Internet server, using a unique, password protected login. A series of basic and advanced ICD terms were presented using actual ICD screenshots and videos that simulated scenarios the practitioner would most commonly encounter in the fast-paced clinical setting. To determine the usefulness of the site and improve the module, practitioners were asked to complete a brief (less than 5 min) online survey at the end of the module. Twenty-six practitioners have logged into our Web site: 20 nurses/nurse practitioners, four cardiac fellows, and two other practitioners. The majority of respondents rated the program as easy to use and useful. The success of this module has led to it becoming part of the training for student nurse practitioners before a clinical electrophysiology rotation, and the module is accessed by our cardiac entry level fellows before a rotation in the intensive care unit or electrophysiology service. Remote electronic arrhythmia learning is a successful example of the melding of technology and education to enhance clinical learning.

Ultra-fast speech comprehension in blind subjects engages primary visual cortex, fusiform gyrus, and pulvinar – a functional magnetic resonance imaging (fMRI) study

PubMed Central

2013-01-01

Background Individuals suffering from vision loss of a peripheral origin may learn to understand spoken language at a rate of up to about 22 syllables (syl) per second - exceeding by far the maximum performance level of normal-sighted listeners (ca. 8 syl/s). To further elucidate the brain mechanisms underlying this extraordinary skill, functional magnetic resonance imaging (fMRI) was performed in blind subjects of varying ultra-fast speech comprehension capabilities and sighted individuals while listening to sentence utterances of a moderately fast (8 syl/s) or ultra-fast (16 syl/s) syllabic rate. Results Besides left inferior frontal gyrus (IFG), bilateral posterior superior temporal sulcus (pSTS) and left supplementary motor area (SMA), blind people highly proficient in ultra-fast speech perception showed significant hemodynamic activation of right-hemispheric primary visual cortex (V1), contralateral fusiform gyrus (FG), and bilateral pulvinar (Pv). Conclusions Presumably, FG supports the left-hemispheric perisylvian “language network”, i.e., IFG and superior temporal lobe, during the (segmental) sequencing of verbal utterances whereas the collaboration of bilateral pulvinar, right auditory cortex, and ipsilateral V1 implements a signal-driven timing mechanism related to syllabic (suprasegmental) modulation of the speech signal. These data structures, conveyed via left SMA to the perisylvian “language zones”, might facilitate – under time-critical conditions – the consolidation of linguistic information at the level of verbal working memory. PMID:23879896
Basic Burns Management E-Learning: A New Teaching Tool.

PubMed

Egro, Francesco M

Burns teaching is organized only in a few medical schools in the United Kingdom. An e-learning tutorial was developed with the objective of incorporating burns teaching within the medical school curriculum. A 33-webpage e-learning was created, covering topics such as local and general response to burns, assessment of burns, first aid, primary and secondary survey, and referral guidelines. Medical student satisfaction was then evaluated using a 12-question feedback survey rated based on a Likert scale from 1 (very poor) to 5 (very good). The 12-question survey was completed by a total of 18 medical students ranging from second to fourth years (second = 17%, third = 22%, fourth = 61%). While only a couple of students had received prior burns teaching, 50% of the cohort had an interest to pursue surgery as a career. The majority of students (72%) would be interested to have an e-learning module on basic burns management in their medical curriculum. The means of all domains specific to the e-learning were rated as "good" or "very good." Students' rating for ease of use was 87%, usefulness was 88%, relevance to the medical curriculum was 90%, clarity and quality of content were 78% and 83%, respectively, design was 79%, and the overall satisfaction with this e-learning was 87%. The "Basic Burns Management" e-learning tutorial can provide an efficient and effective means of information delivery to medical students and junior doctors, allowing easy and fast incorporation of burns teaching within the medical curriculum and in other medical teaching settings.
The Relationship of Fast ForWord Scientific Learning to North Carolina End of Grade Reading Scores at a Middle School in Anson County, North Carolina

ERIC Educational Resources Information Center

Benfield, Jamie Ledsinger

2012-01-01

Anson County School District wished to determine the relationship between Fast ForWord Scientific Learning data and North Carolina End of Grade reading scores at Anson Middle School in Anson County, North Carolina. The specific research questions that guided this study include: 1. How does the literacy intervention, Fast ForWord, affect EOG growth…
A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.
Fast and Slow Spindles during the Sleep Slow Oscillation: Disparate Coalescence and Engagement in Memory Processing

PubMed Central

Mölle, Matthias; Bergmann, Til O.; Marshall, Lisa; Born, Jan

2011-01-01

Study Objectives: Thalamo-cortical spindles driven by the up-state of neocortical slow (< 1 Hz) oscillations (SOs) represent a candidate mechanism of memory consolidation during sleep. We examined interactions between SOs and spindles in human slow wave sleep, focusing on the presumed existence of 2 kinds of spindles, i.e., slow frontocortical and fast centro-parietal spindles. Design: Two experiments were performed in healthy humans (24.5 ± 0.9 y) investigating undisturbed sleep (Experiment I) and the effects of prior learning (word paired associates) vs. non-learning (Experiment II) on multichannel EEG recordings during sleep. Measurements and Results: Only fast spindles (12-15 Hz) were synchronized to the depolarizing SO up-state. Slow spindles (9-12 Hz) occurred preferentially at the transition into the SO down-state, i.e., during waning depolarization. Slow spindles also revealed a higher probability to follow rather than precede fast spindles. For sequences of individual SOs, fast spindle activity was largest for “initial” SOs, whereas SO amplitude and slow spindle activity were largest for succeeding SOs. Prior learning enhanced this pattern. Conclusions: The finding that fast and slow spindles occur at different times of the SO cycle points to disparate generating mechanisms for the 2 kinds of spindles. The reported temporal relationships during SO sequences suggest that fast spindles, driven by the SO up-state feed back to enhance the likelihood of succeeding SOs together with slow spindles. By enforcing such SO-spindle cycles, particularly after prior learning, fast spindles possibly play a key role in sleep-dependent memory processing. Citation: Mölle M; Bergmann TO; Marshall L; Born J. Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing. SLEEP 2011;34(10):1411–1421. PMID:21966073
Hyper-homeostatic learning of anticipatory hunger in rats.

PubMed

Jarvandi, Soghra; Booth, David A; Thibault, Louise

2007-11-23

Anticipatory hunger is a learnt increase in intake of food having a flavour or texture that predicts a long fast. This learning was studied in rats trained on a single food or a choice between protein-rich and carbohydrate-rich foods, presented for 1.5 h after 3 h without maintenance food at the start of the dark phase. Eight training cycles provided a pseudo-random sequence of 3 h and 10 h post-prandial fasts with a day on maintenance food between each training fast. The measure of anticipatory hunger is the difference over one 4-day cycle between the intake of test food having an odour predictive of the longer fast (TL) and intake of food with an odour cuing to the shorter fast (TS). Previous experiments showed that conditioning of preference for the odour before the shorter fast competes with learning to avoid hunger during the longer fast (anticipatory hunger), generating a cubic or quartic contrast. TL minus TS showed a strong cubic trend over 8 training cycles with both single and choice meals. There was a switch from preference for the short-fast odour at cycle 2 (TL-TS=-0.86 g) to a peak of anticipatory hunger at cycle 6 (TL-TS=1.57 g). We conclude that anticipatory hunger is learnt when a choice is given between protein-rich and carbohydrate-rich foods as well as on a single food. In addition, since anticipatory hunger extinguishes itself, such learning improves on negative-feedback homeostasis with a feed-forward "hyper-homeostatic" mechanism.
Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing.

PubMed

Mölle, Matthias; Bergmann, Til O; Marshall, Lisa; Born, Jan

2011-10-01

Thalamo-cortical spindles driven by the up-state of neocortical slow (< 1 Hz) oscillations (SOs) represent a candidate mechanism of memory consolidation during sleep. We examined interactions between SOs and spindles in human slow wave sleep, focusing on the presumed existence of 2 kinds of spindles, i.e., slow frontocortical and fast centro-parietal spindles. Two experiments were performed in healthy humans (24.5 ± 0.9 y) investigating undisturbed sleep (Experiment I) and the effects of prior learning (word paired associates) vs. non-learning (Experiment II) on multichannel EEG recordings during sleep. Only fast spindles (12-15 Hz) were synchronized to the depolarizing SO up-state. Slow spindles (9-12 Hz) occurred preferentially at the transition into the SO down-state, i.e., during waning depolarization. Slow spindles also revealed a higher probability to follow rather than precede fast spindles. For sequences of individual SOs, fast spindle activity was largest for "initial" SOs, whereas SO amplitude and slow spindle activity were largest for succeeding SOs. Prior learning enhanced this pattern. The finding that fast and slow spindles occur at different times of the SO cycle points to disparate generating mechanisms for the 2 kinds of spindles. The reported temporal relationships during SO sequences suggest that fast spindles, driven by the SO up-state feed back to enhance the likelihood of succeeding SOs together with slow spindles. By enforcing such SO-spindle cycles, particularly after prior learning, fast spindles possibly play a key role in sleep-dependent memory processing.
Statistical Mechanical Analysis of Online Learning with Weight Normalization in Single Layer Perceptron

NASA Astrophysics Data System (ADS)

Yoshida, Yuki; Karakida, Ryo; Okada, Masato; Amari, Shun-ichi

2017-04-01

Weight normalization, a newly proposed optimization method for neural networks by Salimans and Kingma (2016), decomposes the weight vector of a neural network into a radial length and a direction vector, and the decomposed parameters follow their steepest descent update. They reported that learning with the weight normalization achieves better converging speed in several tasks including image recognition and reinforcement learning than learning with the conventional parameterization. However, it remains theoretically uncovered how the weight normalization improves the converging speed. In this study, we applied a statistical mechanical technique to analyze on-line learning in single layer linear and nonlinear perceptrons with weight normalization. By deriving order parameters of the learning dynamics, we confirmed quantitatively that weight normalization realizes fast converging speed by automatically tuning the effective learning rate, regardless of the nonlinearity of the neural network. This property is realized when the initial value of the radial length is near the global minimum; therefore, our theory suggests that it is important to choose the initial value of the radial length appropriately when using weight normalization.
Geologic Carbon Sequestration Leakage Detection: A Physics-Guided Machine Learning Approach

NASA Astrophysics Data System (ADS)

Lin, Y.; Harp, D. R.; Chen, B.; Pawar, R.

2017-12-01

One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including pressure. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning technique based on support vector regression to effectively and efficiently predict the leakage locations and leakage rates based on limited number of pressure observations. Compared to the conventional data-driven approaches, which can be usually seem as a "black box" procedure, we develop a physics-guided machine learning method to incorporate the governing physics into the learning procedure. To validate the performance of our proposed leakage detection method, we employ our method to both 2D and 3D synthetic subsurface models. Our novel CO2 leakage detection method has shown high detection accuracy in the example problems.
FSMRank: feature selection algorithm for learning to rank.

PubMed

Lai, Han-Jiang; Pan, Yan; Tang, Yong; Yu, Rong

2013-06-01

In recent years, there has been growing interest in learning to rank. The introduction of feature selection into different learning problems has been proven effective. These facts motivate us to investigate the problem of feature selection for learning to rank. We propose a joint convex optimization formulation which minimizes ranking errors while simultaneously conducting feature selection. This optimization formulation provides a flexible framework in which we can easily incorporate various importance measures and similarity measures of the features. To solve this optimization problem, we use the Nesterov's approach to derive an accelerated gradient algorithm with a fast convergence rate O(1/T(2)). We further develop a generalization bound for the proposed optimization problem using the Rademacher complexities. Extensive experimental evaluations are conducted on the public LETOR benchmark datasets. The results demonstrate that the proposed method shows: 1) significant ranking performance gain compared to several feature selection baselines for ranking, and 2) very competitive performance compared to several state-of-the-art learning-to-rank algorithms.
Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

NASA Technical Reports Server (NTRS)

Farhat, Nabil H.

1987-01-01

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.
Ramadan Fasting and the Propensity for Learning: Is There a Cause for Concern?

ERIC Educational Resources Information Center

Masismadi, Nur Adilah; Lee, Marcus J. C.; Che Muhamed, Ahmad Munir; Chia, Michael Y. H.; Aziz, Abdul Rashid

2017-01-01

The literature indicates that glucose deprivation, dehydration, decreased sleep quality and quantity, and mood changes, independently and adversely can influence cognitive functions and therefore learning. The Ramadan fast is an annual religious act undertaken by Muslims where individuals refrain from consuming food and fluid during daylight…
The impact of odor–reward memory on chemotaxis in larval Drosophila

PubMed Central

Schleyer, Michael; Reid, Samuel F.; Pamir, Evren; Saumweber, Timo; Paisios, Emmanouil; Davies, Alexander

2015-01-01

How do animals adaptively integrate innate with learned behavioral tendencies? We tackle this question using chemotaxis as a paradigm. Chemotaxis in the Drosophila larva largely results from a sequence of runs and oriented turns. Thus, the larvae minimally need to determine (i) how fast to run, (ii) when to initiate a turn, and (iii) where to direct a turn. We first report how odor-source intensities modulate these decisions to bring about higher levels of chemotactic performance for higher odor-source intensities during innate chemotaxis. We then examine whether the same modulations are responsible for alterations of chemotactic performance by learned odor “valence” (understood throughout as level of attractiveness). We find that run speed (i) is neither modulated by the innate nor by the learned valence of an odor. Turn rate (ii), however, is modulated by both: the higher the innate or learned valence of the odor, the less often larvae turn whenever heading toward the odor source, and the more often they turn when heading away. Likewise, turning direction (iii) is modulated concordantly by innate and learned valence: turning is biased more strongly toward the odor source when either innate or learned valence is high. Using numerical simulations, we show that a modulation of both turn rate and of turning direction is sufficient to account for the empirically found differences in preference scores across experimental conditions. Our results suggest that innate and learned valence organize adaptive olfactory search behavior by their summed effects on turn rate and turning direction, but not on run speed. This work should aid studies into the neural mechanisms by which memory impacts specific aspects of behavior. PMID:25887280
The effect of time on word learning: An examination of decay of the memory trace and vocal rehearsal in children with and without specific language impairment

PubMed Central

Alt, Mary; Spaulding, Tammie

2011-01-01

Purpose The purpose of this study was to measure the effect of time to response in a fast-mapping word learning task for children with Specific Language Impairment (SLI) and children with typically-developing language skills (TD). Manipulating time to response allows us to examine decay of the memory trace, the use of vocal rehearsal, and their effects on word learning. Method Participants included 40 school-age children: half with SLI and half with TD. The children were asked to expressively and receptively fast-map 24 novel labels for 24 novel animated dinosaurs. They were asked to demonstrate learning either immediately after presentation of the novel word or after a 10-second delay. Data were collected on the use of vocal rehearsal and for recognition and production accuracy. Results Although the SLI group was less accurate overall, there was no evidence of decay of the memory trace. Both groups used vocal rehearsal at comparable rates, which did not vary when learning was tested immediately or after a delay. Use of vocal rehearsal resulted in better accuracy on the recognition task, but only for the TD group. Conclusions A delay in time to response without interference was not an undue burden for either group. Despite the fact that children with SLI used a vocal rehearsal strategy as often as unimpaired peers, they did not benefit from the strategy in the same way as their peers. Possible explanations for these findings and clinical implications will be discussed. PMID:21885056
A neurocomputational account of taxonomic responding and fast mapping in early word learning.

PubMed

Mayor, Julien; Plunkett, Kim

2010-01-01

We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to the quality of prelexical, categorical representations in the model. We show how synaptogenesis supports coherent generalization of word-object associations and show that later synaptic pruning minimizes metabolic costs without being detrimental to word learning. The role played by joint-attentional activities is identified in the model, both at the level of selecting efficient cross-modal synapses and at the behavioral level, by accelerating and refining overall vocabulary acquisition. The model can account for the qualitative shift in the way infants use words, from an associative to a referential-like use, for the pattern of overextension errors in production and comprehension observed during early childhood and typicality effects observed in lexical development. Interesting by-products of the model include a potential explanation of the shift from prototype to exemplar-based effects reported for adult category formation, an account of mispronunciation effects in early lexical development, and extendability to include accounts of individual differences in lexical development and specific disorders such as Williams syndrome. The model demonstrates how an established constraint on lexical learning, which has often been regarded as domain-specific, can emerge from domain-general learning principles that are simultaneously biologically, psychologically, and socially plausible.
An ERP study on initial second language vocabulary learning.

PubMed

Yum, Yen Na; Midgley, Katherine J; Holcomb, Phillip J; Grainger, Jonathan

2014-04-01

This study examined the very initial phases of orthographic and semantic acquisition in monolingual native English speakers learning Chinese words under controlled laboratory conditions. Participants engaged in 10 sessions of vocabulary learning, four of which were used to obtain ERPs. Performance in behavioral tests improved over sessions, and these data were used to define fast and slow learners. Most important is that ERPs in the two groups of learners revealed qualitatively distinct learning patterns. Only fast learners showed a left-lateralized increase in N170 amplitude with training. Furthermore, only fast learners showed an increased N400 amplitude with training, with a distinct anterior distribution. Slow learners, on the other hand, showed a posterior positive effect, with increasingly positive-going waveforms in occipital sites as training progressed. Possible mechanisms underlying these qualitative differences are discussed. Copyright © 2014 Society for Psychophysiological Research.
Sex differences in left/right confusion.

PubMed

Jordan, Kirsten; Wüstenberg, Torsten; Jaspers-Feyer, Fern; Fellbrich, Anja; Peters, Michael

2006-01-01

In agreement with the literature, females (n=269) gave themselves significantly poorer ratings than males (n=164) in evaluating their ability to make fast and accurate left/right judgments. In order to evaluate the ecological validity of the self-ratings, subjects were tested on a task that required fast and accurate left/right judgments, on a mental rotation task, and on a task that required navigation of a virtual maze. The correlations between the performances and self-ratings were computed. Both males and females who gave themselves very poor LRC (left/right confusion) ratings had significantly lower accuracy scores on the left/right judgement task than males and females with average ratings, but there was no sex-specific relation between LRC ratings and left/right judgements that would explain why females give themselves lower LRC ratings. For females only, a weak correlation between LRC scores and the learning of the virtual maze was observed, but no significant correlations were observed between LRC scores and mental rotation performance. We conclude that self-ratings on left/right confusion questions, although they yield reliable sex differences, are poor predictors of actual performance on spatial tasks that involve left/right judgements. Thus, and in support of earlier speculations (Sholl and Egeth, 1981; Teng and Lee, 1982; Williams et al., 1993), the principal cause of the marked sex differences in LRC self-ratings likely lies in a greater willingness of females to rate themselves more poorly on questions of this type than is the case for men.
Fast Break to Learning School Breakfast Program: A Report of the First Year Results, 1999-2000.

ERIC Educational Resources Information Center

Peterson, Kristin; Davison, Mark; Wahlstrom, Kyla; Himes, John; Hjelseth, Leah; Ross, Jesse; Tucker, Michelle

This study compared two types of school breakfast programs in Minnesota: Fast Break to Learning, a universal free breakfast program ("Fastbreak" schools), and programs with a sliding fee scale ("control" schools). Fastbreak and control schools were compared on several variables: (1) survey responses from principals and food…
The Effects of a Multiyear Universal Social-Emotional Learning Program: The Role of Student and School Characteristics

ERIC Educational Resources Information Center

Bierman, Karen L.; Coie, John D.; Dodge, Kenneth A.; Greenberg, Mark T.; Lochman, John E.; McMahon, Robert J.; Pinderhughes, Ellen

2010-01-01

Objective: This article examines the impact of a universal social-emotional learning program, the Fast Track PATHS (Promoting Alternative Thinking Strategies) curriculum and teacher consultation, embedded within the Fast Track selective prevention model. Method: The longitudinal analysis involved 2,937 children of multiple ethnicities who remained…
Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification

PubMed Central

Yang, Xinyi

2016-01-01

In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods. PMID:27610128

Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

PubMed

Pang, Shan; Yang, Xinyi

2016-01-01

In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods.
The effect of time on word learning: an examination of decay of the memory trace and vocal rehearsal in children with and without specific language impairment.

PubMed

Alt, Mary; Spaulding, Tammie

2011-01-01

The purpose of this study was to measure the effect of time to response in a fast-mapping word learning task for children with specific language impairment (SLI) and children with typically developing language skills (TD). Manipulating time to response allows us to examine decay of the memory trace, the use of vocal rehearsal, and their effects on word learning. Participants included 40 school-age children: half with SLI and half with TD. The children were asked to expressively and receptively fast-map 24 novel labels for 24 novel animated dinosaurs. They were asked to demonstrate learning either immediately after presentation of the novel word or after a 10-second delay. Data were collected on the use of vocal rehearsal and for recognition and production accuracy. Although the SLI group was less accurate overall, there was no evidence of decay of the memory trace. Both groups used vocal rehearsal at comparable rates, which did not vary when learning was tested immediately or after a delay. Use of vocal rehearsal resulted in better accuracy on the recognition task, but only for the TD group. A delay in time to response without interference was not an undue burden for either group. Despite the fact that children with SLI used a vocal rehearsal strategy as often as unimpaired peers, they did not benefit from the strategy in the same way as their peers. Possible explanations for these findings and clinical implications will be discussed. Readers will learn about how time to response affects word learning in children with specific language impairment and unimpaired peers. They will see how this issue fits into a framework of phonological working memory. They will also become acquainted with the effect of vocal rehearsal on word learning. Copyright © 2011 Elsevier Inc. All rights reserved.
Fast and Epsilon-Optimal Discretized Pursuit Learning Automata.

PubMed

Zhang, JunQi; Wang, Cheng; Zhou, MengChu

2015-10-01

Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit LA is the most popular one among them. During an iteration its operation consists of three basic phases: 1) selecting the next action; 2) finding the optimal estimated action; and 3) updating the state probability. However, when the number of actions is large, the learning becomes extremely slow because there are too many updates to be made at each iteration. The increased updates are mostly from phases 1 and 3. A new fast discretized pursuit LA with assured ε -optimality is proposed to perform both phases 1 and 3 with the computational complexity independent of the number of actions. Apart from its low computational complexity, it achieves faster convergence speed than the classical one when operating in stationary environments. This paper can promote the applications of LA toward the large-scale-action oriented area that requires efficient reinforcement learning tools with assured ε -optimality, fast convergence speed, and low computational complexity for each iteration.
A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.
Multiple effects of circadian dysfunction induced by photoperiod shifts: alterations in context memory and food metabolism in the same subjects.

PubMed

McDonald, Robert J; Zelinski, Erin L; Keeley, Robin J; Sutherland, Dylan; Fehr, Leah; Hong, Nancy S

2013-06-13

Humans exposed to shiftwork conditions have been reported to have increased susceptibility to various health problems including various forms of dementia, cancer, heart disease, and metabolic disorders related to obesity. The present experiments assessed the effects of circadian disruption on learning and memory function and various food related processes including diet consumption rates, food metabolism, and changes in body weight. These experiments utilized a novel variant of the conditioned place preference task (CPP) that is normally used to assess Pavlovian associative learning and memory processes produced via repeated context-reward pairings. For the present experiments, the standard CPP paradigm was modified in that both contexts were paired with food, but the dietary constituents of the food were different. In particular, we were interested in whether rats could differentiate between two types of carbohydrates, simple (dextrose) and complex (starch). Consumption rates for each type of carbohydrate were measured throughout training. A test of context preference without the food present was also conducted. At the end of behavioral testing, a fasting glucose test and a glucose challenge test were administered. Chronic photoperiod shifting resulted in impaired context learning and memory processes thought to be mediated by a neural circuit centered on the hippocampus. The results also showed that preferences for the different carbohydrate diets were altered in rats experiencing photoperiod shifting in that they maintained an initial preference for the simple carbohydrate throughout training. Lastly, photoperiod shifting resulted in changes in fasting blood glucose levels and elicited weight gain. These results show that chronic photoperiod shifting, which likely resulted in circadian dysfunction, impairs multiple functions of the brain and/or body in the same individual. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.
Bedside ultrasound curriculum for medical students: report of a blended learning curriculum implementation and validation.

PubMed

Blackstock, Uché; Munson, Jaclyn; Szyld, Demian

2015-03-01

Medical students on clinical rotations rarely receive formal bedside ultrasound (BUS) training. We designed, implemented, and evaluated a standardized BUS curriculum for medical students on their Emergency Medicine (EM) rotation. Teaching was aimed toward influencing four cognitive and psychomotor learning domains: BUS instrumentation knowledge, image interpretation, image acquisition, and procedural guidance. Participants viewed three instructional Web-based tutorials on BUS instrumentation, the Focused Assessment for Sonography in Trauma (FAST) examination and ultrasound-guided central venous catheter (CVC) placement. Subsequently, participants attended a 3-hour hands-on training session to discuss the same content area and practice with faculty coaches. A Web-based, multiple-choice questionnaire was administered before and after the session. During the final week of the rotation, students returned for skills assessments on FAST image acquisition and CVC placement. Forty-five medical students on an EM rotation were enrolled. Sonographic knowledge overall mean score improved significantly from 66.6% (SD ±11.2) to 85.7% (SD ±10.0), corresponding to a mean difference of 19.1% (95% CI 15.5-22.7; p < 0.001). There were high pass rates for FAST (89.0%, 40/45) and CVC (96.0%, 43/45) skills assessments. There was no significant difference between medical student posttest and EM resident test scores 85.7% (SD ±10.0) and 88.1% (SD ± 7.6) (p = 0.40), respectively. A formal BUS curriculum for medical students on EM rotation positively influenced performance in several key learning domains. As BUS competency is required for residency in EM and other specialties, medical schools could consider routinely incorporating BUS teaching into their clinical rotation curricula. © 2014 Wiley Periodicals, Inc.
Feedback control by online learning an inverse model.

PubMed

Waegeman, Tim; Wyffels, Francis; Schrauwen, Francis

2012-10-01

A model, predictor, or error estimator is often used by a feedback controller to control a plant. Creating such a model is difficult when the plant exhibits nonlinear behavior. In this paper, a novel online learning control framework is proposed that does not require explicit knowledge about the plant. This framework uses two learning modules, one for creating an inverse model, and the other for actually controlling the plant. Except for their inputs, they are identical. The inverse model learns by the exploration performed by the not yet fully trained controller, while the actual controller is based on the currently learned model. The proposed framework allows fast online learning of an accurate controller. The controller can be applied on a broad range of tasks with different dynamic characteristics. We validate this claim by applying our control framework on several control tasks: 1) the heating tank problem (slow nonlinear dynamics); 2) flight pitch control (slow linear dynamics); and 3) the balancing problem of a double inverted pendulum (fast linear and nonlinear dynamics). The results of these experiments show that fast learning and accurate control can be achieved. Furthermore, a comparison is made with some classical control approaches, and observations concerning convergence and stability are made.
Fast converging minimum probability of error neural network receivers for DS-CDMA communications.

PubMed

Matyjas, John D; Psaromiligkos, Ioannis N; Batalama, Stella N; Medley, Michael J

2004-03-01

We consider a multilayer perceptron neural network (NN) receiver architecture for the recovery of the information bits of a direct-sequence code-division-multiple-access (DS-CDMA) user. We develop a fast converging adaptive training algorithm that minimizes the bit-error rate (BER) at the output of the receiver. The adaptive algorithm has three key features: i) it incorporates the BER, i.e., the ultimate performance evaluation measure, directly into the learning process, ii) it utilizes constraints that are derived from the properties of the optimum single-user decision boundary for additive white Gaussian noise (AWGN) multiple-access channels, and iii) it embeds importance sampling (IS) principles directly into the receiver optimization process. Simulation studies illustrate the BER performance of the proposed scheme.
Word learning emerges from the interaction of online referent selection and slow associative learning

PubMed Central

McMurray, Bob; Horst, Jessica S.; Samuelson, Larissa K.

2013-01-01

Classic approaches to word learning emphasize the problem of referential ambiguity: in any naming situation the referent of a novel word must be selected from many possible objects, properties, actions, etc. To solve this problem, researchers have posited numerous constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative model in which referent selection is an online process that is independent of long-term learning. This two timescale approach creates significant power in the developing system. We illustrate this with a dynamic associative model in which referent selection is simulated as dynamic competition between competing referents, and learning is simulated using associative (Hebbian) learning. This model can account for a range of findings including the delay in expressive vocabulary relative to receptive vocabulary, learning under high degrees of referential ambiguity using cross-situational statistics, accelerating (vocabulary explosion) and decelerating (power-law) learning rates, fast-mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between individual differences in speed of processing and learning. Five theoretical points are illustrated. 1) Word learning does not require specialized processes – general association learning buttressed by dynamic competition can account for much of the literature. 2) The processes of recognizing familiar words are not different than those that support novel words (e.g., fast-mapping). 3) Online competition may allow the network (or child) to leverage information available in the task to augment performance or behavior despite what might be relatively slow learning or poor representations. 4) Even associative learning is more complex than previously thought – a major contributor to performance is the pruning of incorrect associations between words and referents. 5) Finally, the model illustrates that learning and referent selection/word recognition, though logically distinct, can be deeply and subtly related as phenomena like speed of processing and mutual exclusivity may derive in part from the way learning shapes the system. As a whole, this suggests more sophisticated ways of describing the interaction between situation- and developmental-time processes and points to the need for considering such interactions as a primary determinant of development and processing in children. PMID:23088341
Hybrid learning in signalling games

NASA Astrophysics Data System (ADS)

Barrett, Jeffrey A.; Cochran, Calvin T.; Huttegger, Simon; Fujiwara, Naoki

2017-09-01

Lewis-Skyrms signalling games have been studied under a variety of low-rationality learning dynamics. Reinforcement dynamics are stable but slow and prone to evolving suboptimal signalling conventions. A low-inertia trial-and-error dynamical like win-stay/lose-randomise is fast and reliable at finding perfect signalling conventions but unstable in the context of noise or agent error. Here we consider a low-rationality hybrid of reinforcement and win-stay/lose-randomise learning that exhibits the virtues of both. This hybrid dynamics is reliable, stable and exceptionally fast.
Expandable Grids: A User Interface Visualization Technique and a Policy Semantics to Support Fast, Accurate Security and Privacy Policy Authoring

DTIC Science & Technology

2008-07-01

dropout rate amongst Grid participants suggests participants found the Grid more frustrating to use, and subjective satisfaction scores show... learned more than N years of graduate school could ever teach me, and my sister, who was always there for me when my Black Friday letters came. Abstract...greatly affect whether policies match their authors’ intentions ; a bad user interface can lead to policies with many errors, while a good user interface
Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.
Fast Learning with Weak Synaptic Plasticity.

PubMed

Yger, Pierre; Stimberg, Marcel; Brette, Romain

2015-09-30

New sensory stimuli can be learned with a single or a few presentations. Similarly, the responses of cortical neurons to a stimulus have been shown to increase reliably after just a few repetitions. Long-term memory is thought to be mediated by synaptic plasticity, but in vitro experiments in cortical cells typically show very small changes in synaptic strength after a pair of presynaptic and postsynaptic spikes. Thus, it is traditionally thought that fast learning requires stronger synaptic changes, possibly because of neuromodulation. Here we show theoretically that weak synaptic plasticity can, in fact, support fast learning, because of the large number of synapses N onto a cortical neuron. In the fluctuation-driven regime characteristic of cortical neurons in vivo, the size of membrane potential fluctuations grows only as √N, whereas a single output spike leads to potentiation of a number of synapses proportional to N. Therefore, the relative effect of a single spike on synaptic potentiation grows as √N. This leverage effect requires precise spike timing. Thus, the large number of synapses onto cortical neurons allows fast learning with very small synaptic changes. Significance statement: Long-term memory is thought to rely on the strengthening of coactive synapses. This physiological mechanism is generally considered to be very gradual, and yet new sensory stimuli can be learned with just a few presentations. Here we show theoretically that this apparent paradox can be solved when there is a tight balance between excitatory and inhibitory input. In this case, small synaptic modifications applied to the many synapses onto a given neuron disrupt that balance and produce a large effect even for modifications induced by a single stimulus. This effect makes fast learning possible with small synaptic changes and reconciles physiological and behavioral observations. Copyright © 2015 the authors 0270-6474/15/3513351-12$15.00/0.
Inter-individual differences in the initial 80 minutes of motor learning of handrim wheelchair propulsion.

PubMed

Vegter, Riemer J K; Lamoth, Claudine J; de Groot, Sonja; Veeger, Dirkjan H E J; van der Woude, Lucas H V

2014-01-01

Handrim wheelchair propulsion is a cyclic skill that needs to be learned during rehabilitation. Yet it is unclear how inter-individual differences in motor learning impact wheelchair propulsion practice. Therefore we studied how early-identified motor learning styles in novice able-bodied participants impact the outcome of a low-intensity wheelchair-practice intervention. Over a 12-minute pre-test, 39 participants were split in two groups based on a relative 10% increase in mechanical efficiency. Following the pretest the participants continued one of four different low-intensity wheelchair practice interventions, yet all performed in the same trial-setup with a total 80-minute dose at 1.11 m/s at 0.20 W/kg. Instead of focusing on the effect of the different interventions, we focused on differences in motor learning between participants over the intervention. Twenty-six participants started the pretest with a lower mechanical efficiency and a less optimal propulsion technique, but showed a fast improvement during the first 12 minutes and this effect continued over the 80 minutes of practice. Eventually these initially fast improvers benefitted more from the given practice indicated by a better propulsion technique (like reduced frequency and increased stroke angle) and a higher mechanical efficiency. The initially fast improvers also had a higher intra-individual variability in the pre and posttest, which possibly relates to the increased motor learning of the initially fast improvers. Further exploration of the common characteristics of different types of learners will help to better tailor rehabilitation to the needs of wheelchair-dependent persons and improve our understanding of cyclic motor learning processes.
Lessons learned from and the future for NASA's Small Explorer Program

NASA Technical Reports Server (NTRS)

Newton, George P.

1991-01-01

NASA started the Small Explorer Program to provide space scientists with an opportunity to conduct space science research in the Explorer Program using scientific payloads launched on small-class expendable launch vehicles. A series of small payload, scientific missions was envisioned that could be launched at the rate of one to two missions per year. Three missions were selected in April 1989: Solar Anomalous and Magnetospheric Particle Explorer, Fast Auroral Snapshot Explorer, and Sub-millimeter Wave Astronomy. These missions are planned for launch in June 1992, September 1994 and June 1995, respectively. At a program level, this paper presents the history, objectives, status, and lessons learned which may be applicable to similar programs, and discusses future program plans.
Implicit associative learning in synesthetes and nonsynesthetes

PubMed Central

Bankieris, Kaitlyn R.; Aslin, Richard N.

2016-01-01

Although cross-modal neural connections and genetic underpinnings are prominent in most current theories regarding the development of synesthesia, the potential role of associative learning in the formation of synesthetic associations has recently been revitalized. In this study, we investigated implicit associative learning in synesthetes and nonsynesthetes by recording reaction times to a target whose color was probabilistically correlated with its shape. A continuous measure of target detection at multiple time points during learning revealed that synesthetes and nonsynesthetes learn associations differently. Specifically, our results demonstrate a ‘fast facilitation’ learning effect for nonsynesthetes and ‘fast interference, slow facilitation’ learning effect for synesthetes. Additionally, synesthetes exhibited superior long-term memory for learned associations in a surprise-delayed retest. After this retest, participants implicitly learned new (shuffled) shape-color associations. We found that synesthetes experienced greater interference while learning these new shape-color associations. These results detail ways in which implicit associative learning and memory differ between synesthetes and nonsynesthetes. PMID:27612860
Experience-Related Structural Changes of Degenerated Occipital White Matter in Late-Blind Humans – A Diffusion Tensor Imaging Study

PubMed Central

Dietrich, Susanne; Hertrich, Ingo; Kumar, Vinod; Ackermann, Hermann

2015-01-01

Late-blind humans can learn to understand speech at ultra-fast syllable rates (ca. 20 syllables/s), a capability associated with hemodynamic activation of the central-visual system. Thus, the observed functional cross-modal recruitment of occipital cortex might facilitate ultra-fast speech processing in these individuals. To further elucidate the structural prerequisites of this skill, diffusion tensor imaging (DTI) was conducted in late-blind subjects differing in their capability of understanding ultra-fast speech. Fractional anisotropy (FA) was determined as a quantitative measure of the directionality of water diffusion, indicating fiber tract characteristics that might be influenced by blindness as well as the acquired perceptual skills. Analysis of the diffusion images revealed reduced FA in late-blind individuals relative to sighted controls at the level of the optic radiations at either side and the right-hemisphere dorsal thalamus (pulvinar). Moreover, late-blind subjects showed significant positive correlations between FA and the capacity of ultra-fast speech comprehension within right-hemisphere optic radiation and thalamus. Thus, experience-related structural alterations occurred in late-blind individuals within visual pathways that, presumably, are linked to higher order frontal language areas. PMID:25830371
Brief Report: Fast Mapping Predicts Differences in Concurrent and Later Language Abilities among Children with ASD

ERIC Educational Resources Information Center

Venker, Courtney E.; Kover, Sara T.; Weismer, Susan Ellis

2016-01-01

This study investigated whether the ability to learn word-object associations following minimal exposure (i.e., fast mapping) was associated with concurrent and later language abilities in children with ASD. Children who were poor learners at age 3½ had significantly lower receptive language abilities than children who successfully learned the new…
Fast Break to Learning School Breakfast Program: A Report of the Second Year Results, 2000-2001.

ERIC Educational Resources Information Center

Peterson, Kristin; Davison, Mark; Wahlstrom, Kyla; Himes, John; Irish, Margaret L.

This report provides Year 2 data comparing two types of school breakfast programs in Minnesota to schools that did not serve breakfast at all (No Breakfast schools): Fast Break to Learning, a universal free breakfast program (Fastbreak schools), and programs with a sliding fee scale (control schools). Data were collected from 30 Fastbreak, 195…
Good, Fast, Cheap: How Centers of Teaching and Learning Can Capitalize in Today's Resource-Constrained Context

ERIC Educational Resources Information Center

Truong, Michael H.; Juillerat, Stephanie; Gin, Deborah H. C.

2016-01-01

This article provides leaders and educational developers of Centers for Teaching and Learning (CTL) with innovative and practical strategies on how to increase their centers' capacity and impact by focusing on quality, efficiency, and cost. This "good, fast, cheap" model represents a promising way that CTL can continue to grow, scale,…

Incremental Learning With Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy

PubMed Central

Gao, Yaozong; Zhan, Yiqiang

2015-01-01

Image-guided radiotherapy (IGRT) requires fast and accurate localization of the prostate in 3-D treatment-guided radiotherapy, which is challenging due to low tissue contrast and large anatomical variation across patients. On the other hand, the IGRT workflow involves collecting a series of computed tomography (CT) images from the same patient under treatment. These images contain valuable patient-specific information yet are often neglected by previous works. In this paper, we propose a novel learning framework, namely incremental learning with selective memory (ILSM), to effectively learn the patient-specific appearance characteristics from these patient-specific images. Specifically, starting with a population-based discriminative appearance model, ILSM aims to “personalize” the model to fit patient-specific appearance characteristics. The model is personalized with two steps: backward pruning that discards obsolete population-based knowledge and forward learning that incorporates patient-specific characteristics. By effectively combining the patient-specific characteristics with the general population statistics, the incrementally learned appearance model can localize the prostate of a specific patient much more accurately. This work has three contributions: 1) the proposed incremental learning framework can capture patient-specific characteristics more effectively, compared to traditional learning schemes, such as pure patient-specific learning, population-based learning, and mixture learning with patient-specific and population data; 2) this learning framework does not have any parametric model assumption, hence, allowing the adoption of any discriminative classifier; and 3) using ILSM, we can localize the prostate in treatment CTs accurately (DSC ∼0.89) and fast (∼4 s), which satisfies the real-world clinical requirements of IGRT. PMID:24495983
Fast repetition rate (FRR) fluorometer and method for measuring fluorescence and photosynthetic parameters

DOEpatents

Kolber, Zbigniew; Falkowski, Paul

1995-06-20

A fast repetition rate fluorometer device and method for measuring in vivo fluorescence of phytoplankton or higher plants chlorophyll and photosynthetic parameters of phytoplankton or higher plants by illuminating the phytoplankton or higher plants with a series of fast repetition rate excitation flashes effective to bring about and measure resultant changes in fluorescence yield of their Photosystem II. The series of fast repetition rate excitation flashes has a predetermined energy per flash and a rate greater than 10,000 Hz. Also, disclosed is a flasher circuit for producing the series of fast repetition rate flashes.
A shared resource between declarative memory and motor memory.

PubMed

Keisler, Aysha; Shadmehr, Reza

2010-11-03

The neural systems that support motor adaptation in humans are thought to be distinct from those that support the declarative system. Yet, during motor adaptation changes in motor commands are supported by a fast adaptive process that has important properties (rapid learning, fast decay) that are usually associated with the declarative system. The fast process can be contrasted to a slow adaptive process that also supports motor memory, but learns gradually and shows resistance to forgetting. Here we show that after people stop performing a motor task, the fast motor memory can be disrupted by a task that engages declarative memory, but the slow motor memory is immune from this interference. Furthermore, we find that the fast/declarative component plays a major role in the consolidation of the slow motor memory. Because of the competitive nature of declarative and nondeclarative memory during consolidation, impairment of the fast/declarative component leads to improvements in the slow/nondeclarative component. Therefore, the fast process that supports formation of motor memory is not only neurally distinct from the slow process, but it shares critical resources with the declarative memory system.
A shared resource between declarative memory and motor memory

PubMed Central

Keisler, Aysha; Shadmehr, Reza

2010-01-01

The neural systems that support motor adaptation in humans are thought to be distinct from those that support the declarative system. Yet, during motor adaptation changes in motor commands are supported by a fast adaptive process that has important properties (rapid learning, fast decay) that are usually associated with the declarative system. The fast process can be contrasted to a slow adaptive process that also supports motor memory, but learns gradually and shows resistance to forgetting. Here we show that after people stop performing a motor task, the fast motor memory can be disrupted by a task that engages declarative memory, but the slow motor memory is immune from this interference. Furthermore, we find that the fast/declarative component plays a major role in the consolidation of the slow motor memory. Because of the competitive nature of declarative and non-declarative memory during consolidation, impairment of the fast/declarative component leads to improvements in the slow/non-declarative component. Therefore, the fast process that supports formation of motor memory is not only neurally distinct from the slow process, but it shares critical resources with the declarative memory system. PMID:21048140
Investigating speech motor practice and learning in people who stutter.

PubMed

Namasivayam, Aravind Kumar; van Lieshout, Pascal

2008-03-01

In this exploratory study, we investigated whether or not people who stutter (PWS) show motor practice and learning changes similar to those of people who do not stutter (PNS). To this end, five PWS and five PNS repeated a set of non-words at two different rates (normal and fast) across three test sessions (T1, T2 on the same day and T3 on a separate day, at least 1 week apart). The results indicated that PWS and PNS may resemble each other on a number of performance variables (such as movement amplitude and duration), but they differ in terms of practice and learning on variables that relate to movement stability and strength of coordination patterns. These findings are interpreted in support of recent claims about speech motor skill limitations in PWS. The reader will be able to: (1) define oral articulatory changes associated with motor practice and learning and their measurement; (2) summarize findings from previous studies examining motor practice and learning in PWS; and (3) discuss hypotheses that could account for the present findings that suggest PWS and PNS differ in their speech motor learning abilities.
Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler.

PubMed

Li, Guoqiang; Niu, Peifeng; Wang, Huaibao; Liu, Yongchao

2014-03-01

This paper presents a novel artificial neural network with a very fast learning speed, all of whose weights and biases are determined by the twice Least Square method, so it is called Least Square Fast Learning Network (LSFLN). In addition, there is another difference from conventional neural networks, which is that the output neurons of LSFLN not only receive the information from the hidden layer neurons, but also receive the external information itself directly from the input neurons. In order to test the validity of LSFLN, it is applied to 6 classical regression applications, and also employed to build the functional relation between the combustion efficiency and operating parameters of a 300WM coal-fired boiler. Experimental results show that, compared with other methods, LSFLN with very less hidden neurons could achieve much better regression precision and generalization ability at a much faster learning speed. Copyright © 2013 Elsevier Ltd. All rights reserved.
Inter-Individual Differences in the Initial 80 Minutes of Motor Learning of Handrim Wheelchair Propulsion

PubMed Central

Vegter, Riemer J. K.; Lamoth, Claudine J.; de Groot, Sonja; Veeger, Dirkjan H. E. J.; van der Woude, Lucas H. V.

2014-01-01

Handrim wheelchair propulsion is a cyclic skill that needs to be learned during rehabilitation. Yet it is unclear how inter-individual differences in motor learning impact wheelchair propulsion practice. Therefore we studied how early-identified motor learning styles in novice able-bodied participants impact the outcome of a low-intensity wheelchair-practice intervention. Over a 12-minute pre-test, 39 participants were split in two groups based on a relative 10% increase in mechanical efficiency. Following the pretest the participants continued one of four different low-intensity wheelchair practice interventions, yet all performed in the same trial-setup with a total 80-minute dose at 1.11 m/s at 0.20 W/kg. Instead of focusing on the effect of the different interventions, we focused on differences in motor learning between participants over the intervention. Twenty-six participants started the pretest with a lower mechanical efficiency and a less optimal propulsion technique, but showed a fast improvement during the first 12 minutes and this effect continued over the 80 minutes of practice. Eventually these initially fast improvers benefitted more from the given practice indicated by a better propulsion technique (like reduced frequency and increased stroke angle) and a higher mechanical efficiency. The initially fast improvers also had a higher intra-individual variability in the pre and posttest, which possibly relates to the increased motor learning of the initially fast improvers. Further exploration of the common characteristics of different types of learners will help to better tailor rehabilitation to the needs of wheelchair-dependent persons and improve our understanding of cyclic motor learning processes. PMID:24586992
12 CFR 261.13 - Processing requests.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Information Office and that have already been cleared for public release may qualify for fast-track processing... will make the determination whether a request qualifies for fast-track processing. A requester may contact the Freedom of Information Office to learn whether a particular request has been assigned to fast...
12 CFR 261.13 - Processing requests.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Information Office and that have already been cleared for public release may qualify for fast-track processing... will make the determination whether a request qualifies for fast-track processing. A requester may contact the Freedom of Information Office to learn whether a particular request has been assigned to fast...
12 CFR 261.13 - Processing requests.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Information Office and that have already been cleared for public release may qualify for fast-track processing... will make the determination whether a request qualifies for fast-track processing. A requester may contact the Freedom of Information Office to learn whether a particular request has been assigned to fast...
12 CFR 261.13 - Processing requests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Information Office and that have already been cleared for public release may qualify for fast-track processing... will make the determination whether a request qualifies for fast-track processing. A requester may contact the Freedom of Information Office to learn whether a particular request has been assigned to fast...
12 CFR 261.13 - Processing requests.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Information Office and that have already been cleared for public release may qualify for fast-track processing... will make the determination whether a request qualifies for fast-track processing. A requester may contact the Freedom of Information Office to learn whether a particular request has been assigned to fast...
Fast repetition rate (FRR) fluorometer and method for measuring fluorescence and photosynthetic parameters

DOEpatents

Kolber, Z.; Falkowski, P.

1995-06-20

A fast repetition rate fluorometer device and method for measuring in vivo fluorescence of phytoplankton or higher plants chlorophyll and photosynthetic parameters of phytoplankton or higher plants is revealed. The phytoplankton or higher plants are illuminated with a series of fast repetition rate excitation flashes effective to bring about and measure resultant changes in fluorescence yield of their Photosystem II. The series of fast repetition rate excitation flashes has a predetermined energy per flash and a rate greater than 10,000 Hz. Also, disclosed is a flasher circuit for producing the series of fast repetition rate flashes. 14 figs.
No Trade-Off between Learning Speed and Associative Flexibility in Bumblebees: A Reversal Learning Test with Multiple Colonies

PubMed Central

Raine, Nigel E.; Chittka, Lars

2012-01-01

Potential trade-offs between learning speed and memory-related performance could be important factors in the evolution of learning. Here, we test whether rapid learning interferes with the acquisition of new information using a reversal learning paradigm. Bumblebees (Bombus terrestris) were trained to associate yellow with a floral reward. Subsequently the association between colour and reward was reversed, meaning bees then had to learn to visit blue flowers. We demonstrate that individuals that were fast to learn yellow as a predictor of reward were also quick to reverse this association. Furthermore, overnight memory retention tests suggest that faster learning individuals are also better at retaining previously learned information. There is also an effect of relatedness: colonies whose workers were fast to learn the association between yellow and reward also reversed this association rapidly. These results are inconsistent with a trade-off between learning speed and the reversal of a previously made association. On the contrary, they suggest that differences in learning performance and cognitive (behavioural) flexibility could reflect more general differences in colony learning ability. Hence, this study provides additional evidence to support the idea that rapid learning and behavioural flexibility have adaptive value. PMID:23028779
Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling.

PubMed

Raghuram, Jayaram; Miller, David J; Kesidis, George

2014-07-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates.
Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling

PubMed Central

Raghuram, Jayaram; Miller, David J.; Kesidis, George

2014-01-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates. PMID:25685511
An Object Oriented Approach to Improve the Precision of Learning Object Retrieval in a Self Learning Environment

ERIC Educational Resources Information Center

Raghuveer, V. R.; Tripathy, B. K.

2012-01-01

With the advancements in the WWW and ICT, the e-learning domain has developed very fast. Even many educational institutions these days have shifted their focus towards the e-learning and mobile learning environments. However, from the quality of learning point of view, which is measured in terms of "active learning" taking place, the…
Heart failure - discharge

MedlinePlus

... Avoid fatty foods. Stay away from fast-food restaurants. Avoid some prepared and frozen foods. Learn fast ... A.D.A.M. follows rigorous standards of quality and accountability. A.D.A.M. is among ...
Orthographic learning, fast and slow: Lexical competition effects reveal the time course of word learning in developing readers.

PubMed

Tamura, Niina; Castles, Anne; Nation, Kate

2017-06-01

Children learn new words via their everyday reading experience but little is known about how this learning happens. We addressed this by focusing on the conditions needed for new words to become familiar to children, drawing a distinction between lexical configuration (the acquisition of word knowledge) and lexical engagement (the emergence of interactive processes between newly learned words and existing words). In Experiment 1, 9-11-year-olds saw unfamiliar words in one of two storybook conditions, differing in degree of focus on the new words but matched for frequency of exposure. Children showed good learning of the novel words in terms of both configuration (form and meaning) and engagement (lexical competition). A frequency manipulation under incidental learning conditions in Experiment 2 revealed different time-courses of learning: a fast lexical configuration process, indexed by explicit knowledge, and a slower lexicalization process, indexed by lexical competition. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
A fast elitism Gaussian estimation of distribution algorithm and application for PID optimization.

PubMed

Xu, Qingyang; Zhang, Chengjin; Zhang, Li

2014-01-01

Estimation of distribution algorithm (EDA) is an intelligent optimization algorithm based on the probability statistics theory. A fast elitism Gaussian estimation of distribution algorithm (FEGEDA) is proposed in this paper. The Gaussian probability model is used to model the solution distribution. The parameters of Gaussian come from the statistical information of the best individuals by fast learning rule. A fast learning rule is used to enhance the efficiency of the algorithm, and an elitism strategy is used to maintain the convergent performance. The performances of the algorithm are examined based upon several benchmarks. In the simulations, a one-dimensional benchmark is used to visualize the optimization process and probability model learning process during the evolution, and several two-dimensional and higher dimensional benchmarks are used to testify the performance of FEGEDA. The experimental results indicate the capability of FEGEDA, especially in the higher dimensional problems, and the FEGEDA exhibits a better performance than some other algorithms and EDAs. Finally, FEGEDA is used in PID controller optimization of PMSM and compared with the classical-PID and GA.

A Fast Elitism Gaussian Estimation of Distribution Algorithm and Application for PID Optimization

PubMed Central

Xu, Qingyang; Zhang, Chengjin; Zhang, Li

2014-01-01

Estimation of distribution algorithm (EDA) is an intelligent optimization algorithm based on the probability statistics theory. A fast elitism Gaussian estimation of distribution algorithm (FEGEDA) is proposed in this paper. The Gaussian probability model is used to model the solution distribution. The parameters of Gaussian come from the statistical information of the best individuals by fast learning rule. A fast learning rule is used to enhance the efficiency of the algorithm, and an elitism strategy is used to maintain the convergent performance. The performances of the algorithm are examined based upon several benchmarks. In the simulations, a one-dimensional benchmark is used to visualize the optimization process and probability model learning process during the evolution, and several two-dimensional and higher dimensional benchmarks are used to testify the performance of FEGEDA. The experimental results indicate the capability of FEGEDA, especially in the higher dimensional problems, and the FEGEDA exhibits a better performance than some other algorithms and EDAs. Finally, FEGEDA is used in PID controller optimization of PMSM and compared with the classical-PID and GA. PMID:24892059
Learning accurate very fast decision trees from uncertain data streams

NASA Astrophysics Data System (ADS)

Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

2015-12-01

Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.
Online Learning: E-Learning Fast, Cheap, and Good

ERIC Educational Resources Information Center

Piskurich, George M.

2006-01-01

There is a variation of e-learning, used mainly in academic settings, that can be a valuable intervention tool for the performance technologist. It is often referred to as online learning. In the performance improvement field, this term is often used interchangeably with synchronous e-learning, but there are some major differences between these…
Relationships of Attention and Executive Functions to Oral Language, Reading, and Writing Skills and Systems in Middle Childhood and Early Adolescence.

PubMed

Berninger, Virginia; Abbott, Robert; Cook, Clayton R; Nagy, William

Relationships between attention/executive functions and language learning were investigated in students in Grades 4 to 9 ( N = 88) with and without specific learning disabilities (SLDs) in multiword syntax in oral and written language (OWL LD), word reading and spelling (dyslexia), and subword letter writing (dysgraphia). Prior attention-deficit/hyperactivity disorder (ADHD) diagnosis was correlated only with impaired handwriting. Parental ratings of inattention, but not hyperactivity, correlated with measures of written language but not oral language. Sustaining switching attention correlated with writing the alphabet from memory in manuscript or by keyboard and fast copying of a sentence with all the letters of the alphabet. Multiple regressions based on a principal component for composites of multiple levels of language (subword, word, and syntax/text) showed that measures of attention and executive function involving language processing rather than ratings of attention and executive function not specifically related to language accounted for more variance and identified more unique predictors in the composite outcomes for oral language, reading, and writing systems. Inhibition related to focused attention uniquely predicted outcomes for the oral language system. Findings are discussed in reference to implications for assessing and teaching students who are still learning to pay attention to heard and written language and self-regulate their language learning during middle childhood and adolescence.
Demarcating Advanced Learning Approaches from Methodological and Technological Perspectives

ERIC Educational Resources Information Center

Horvath, Imre; Peck, David; Verlinden, Jouke

2009-01-01

In the field of design and engineering education, the fast and expansive evolution of information and communication technologies is steadily converting traditional learning approaches into more advanced ones. Facilitated by Broadband (high bandwidth) personal computers, distance learning has developed into web-hosted electronic learning. The…
Fast Mapping by Bilingual Children: Storybooks and Cartoons

ERIC Educational Resources Information Center

Van Horn, Danielle; Kan, Pui Fong

2016-01-01

The purpose of this study was to examine the fast mapping skills in Spanish-English bilingual preschool children in two learning contexts: storybook reading and cartoon viewing. Eighteen typically developing Spanish-English bilingual preschool children completed a fast mapping task in Spanish (L1) and in English (L2). In 4 different sessions, each…
Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence

PubMed Central

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E.

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task. PMID:26973502
Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence.

PubMed

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task.
An Empirical Study of Factors Driving the Adoption of Mobile Learning in Omani Higher Education

ERIC Educational Resources Information Center

Sarrab, Mohamed; Al Shibli, Ibtisam; Badursha, Nabeela

2016-01-01

Mobile learning (M-learning) provides a new learning channel in which learners can access content and just in time information as required irrespective of the time and location. Even though M-learning is fast evolving in many regions of the world, research addressing the driving factors of M-learning adoption is in short supply. This article…
Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

PubMed

Sartori, Juliana M; Reckziegel, Ramiro; Passos, Ives Cavalcante; Czepielewski, Leticia S; Fijtman, Adam; Sodré, Leonardo A; Massuda, Raffael; Goi, Pedro D; Vianna-Sulzbach, Miréia; Cardoso, Taiane de Azevedo; Kapczinski, Flávio; Mwangi, Benson; Gama, Clarissa S

2018-08-01

Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well established, daily-life functioning impairments bulge among the consequences of the proposed progression. The objective of this study was to analyze MRI volumetric modifications in BD and healthy controls (HC) as possible predictors of daily-life functioning through a machine learning approach. Ninety-four participants (35 DSM-IV BD type I and 59 HC) underwent clinical and functioning assessments, and structural MRI. Functioning was assessed using the Functioning Assessment Short Test (FAST). The machine learning analysis was used to identify possible candidates of regional brain volumes that could predict functioning status, through a support vector regression algorithm. Patients with BD and HC did not differ in age, education and marital status. There were significant differences between groups in gender, BMI, FAST score, and employment status. There was significant correlation between observed and predicted FAST score for patients with BD, but not for controls. According to the model, the brain structures volumes that could predict FAST scores were: left superior frontal cortex, left rostral medial frontal cortex, right white matter total volume and right lateral ventricle volume. The machine learning approach demonstrated that brain volume changes in MRI were predictors of FAST score in patients with BD and could identify specific brain areas related to functioning impairment. Copyright © 2018 Elsevier Ltd. All rights reserved.
Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.
Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651
Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.
Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Safety of a no-fast protocol for tracheotomy in critical care

PubMed Central

Hartl, Trevor; Anderson, Donald; Levi, Jasna

2015-01-01

Summary With modern anesthesia, aspiration is an exceedingly rare complication, and we have learned that a prolonged fast can result in serious adverse effects in critically ill patients. We discuss the no-fast protocol implemented at Vancouver General Hospital in 2007 for intubated, tube-fed adult patients who underwent elective open tracheotomy. PMID:25621914
Fast ForWord[R]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2013

2013-01-01

"Fast ForWord"[R] is a computer-based reading program intended to help students develop and strengthen the cognitive skills necessary for successful reading and learning. The program, which is designed to be used 30-100 minutes a day, 5 days a week, for 4-16 weeks, includes three series. The "Fast ForWord[R] Language" series…
The Highly Adaptive Lasso Estimator

PubMed Central

Benkeser, David; van der Laan, Mark

2017-01-01

Estimation of a regression functions is a common goal of statistical learning. We propose a novel nonparametric regression estimator that, in contrast to many existing methods, does not rely on local smoothness assumptions nor is it constructed using local smoothing techniques. Instead, our estimator respects global smoothness constraints by virtue of falling in a class of right-hand continuous functions with left-hand limits that have variation norm bounded by a constant. Using empirical process theory, we establish a fast minimal rate of convergence of our proposed estimator and illustrate how such an estimator can be constructed using standard software. In simulations, we show that the finite-sample performance of our estimator is competitive with other popular machine learning techniques across a variety of data generating mechanisms. We also illustrate competitive performance in real data examples using several publicly available data sets. PMID:29094111
Peer Learning Community Guide. CEELO FastFact

ERIC Educational Resources Information Center

Schilder, Diane; Brown, Kirsty Clarke; Gillaspy, Kathi

2014-01-01

States and technical assistance centers have asked the Center on Enhancing Early Learning Outcomes (CEELO) for guidance on establishing and maintaining a peer learning community (PLC). This document is designed to delineate the steps to establish and sustain a Peer Learning Community (PLC). It begins with a definition of a PLC and then presents…
Exploring Teachers' Blended Learning Experiences in a Rural Alabama High School

ERIC Educational Resources Information Center

Jones, Aslean Madison

2017-01-01

The use of blended learning is fast becoming a practice used in public schools to address 21st century learning challenges. However, despite the growing use of instructional delivery models that blend online learning platforms with traditional instruction in brick and mortar classrooms, little is known about teachers' experiences with the…
Young children's fast mapping and generalization of words, facts, and pictograms.

PubMed

Deák, Gedeon O; Toney, Alexis J

2013-06-01

To test general and specific processes of symbol learning, 4- and 5-year-old children learned three kinds of abstract associates for novel objects: words, facts, and pictograms. To test fast mapping (i.e., one-trial learning) and subsequent learning, comprehension was tested after each of four exposures. Production was also tested, as was children's tendency to generalize learned items to new objects in the same taxon. To test for a bias toward mutually exclusive associations, children learned either one-to-one or many-to-many mappings. In Experiment 1, children learned words, facts (with or without incidental novel words), or pictograms. In Experiment 2, children learned words or pictograms. In both of these experiments, children learned words slower than facts and pictograms. Pictograms and facts were generalized more systematically than words, but only in Experiment 1. Children learned one-to-one mappings faster only in Experiment 2, when cognitive load was increased. In Experiment 3, 3- and 4-year-olds were taught facts (with novel words), words, and pictograms. Children learned facts faster than words; however, they remembered all items equally well a week later. The results suggest that word learning follows non-specialized memory and associative learning processes. Copyright © 2013 Elsevier Inc. All rights reserved.

The key to success in elite athletes? Explicit and implicit motor learning in youth elite and non-elite soccer players.

PubMed

Verburgh, L; Scherder, E J A; van Lange, P A M; Oosterlaan, J

2016-09-01

In sports, fast and accurate execution of movements is required. It has been shown that implicitly learned movements might be less vulnerable than explicitly learned movements to stressful and fast changing circumstances that exist at the elite sports level. The present study provides insight in explicit and implicit motor learning in youth soccer players with different expertise levels. Twenty-seven youth elite soccer players and 25 non-elite soccer players (aged 10-12) performed a serial reaction time task (SRTT). In the SRTT, one of the sequences must be learned explicitly, the other was implicitly learned. No main effect of group was found for implicit and explicit learning on mean reaction time (MRT) and accuracy. However, for MRT, an interaction was found between learning condition, learning phase and group. Analyses showed no group effects for the explicit learning condition, but youth elite soccer players showed better learning in the implicit learning condition. In particular, during implicit motor learning youth elite soccer showed faster MRTs in the early learning phase and earlier reached asymptote performance in terms of MRT. Present findings may be important for sports because children with superior implicit learning abilities in early learning phases may be able to learn more (durable) motor skills in a shorter time period as compared to other children.
Employing Wikibook Project in a Linguistics Course to Promote Peer Teaching and Learning

ERIC Educational Resources Information Center

Wang, Lixun

2016-01-01

Peer teaching and learning are learner-centred approaches with great potential for promoting effective learning, and the fast development of Web 2.0 technology has opened new doors for promoting peer teaching and learning. In this study, we aim to establish peer teaching and learning among students by employing a Wikibook project in the course…
Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

PubMed

Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

2018-03-23

Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.
Estimation of the prevalence of adverse drug reactions from social media.

PubMed

Nguyen, Thin; Larsen, Mark E; O'Dea, Bridianne; Phung, Dinh; Venkatesh, Svetha; Christensen, Helen

2017-06-01

This work aims to estimate the degree of adverse drug reactions (ADR) for psychiatric medications from social media, including Twitter, Reddit, and LiveJournal. Advances in lightning-fast cluster computing was employed to process large scale data, consisting of 6.4 terabytes of data containing 3.8 billion records from all the media. Rates of ADR were quantified using the SIDER database of drugs and side-effects, and an estimated ADR rate was based on the prevalence of discussion in the social media corpora. Agreement between these measures for a sample of ten popular psychiatric drugs was evaluated using the Pearson correlation coefficient, r, with values between 0.08 and 0.50. Word2vec, a novel neural learning framework, was utilized to improve the coverage of variants of ADR terms in the unstructured text by identifying syntactically or semantically similar terms. Improved correlation coefficients, between 0.29 and 0.59, demonstrates the capability of advanced techniques in machine learning to aid in the discovery of meaningful patterns from medical data, and social media data, at scale. Copyright © 2017 Elsevier B.V. All rights reserved.
Laparoscopic colorectal surgery in learning curve: Role of implementation of a standardized technique and recovery protocol. A cohort study

PubMed Central

Luglio, Gaetano; De Palma, Giovanni Domenico; Tarquini, Rachele; Giglio, Mariano Cesare; Sollazzo, Viviana; Esposito, Emanuela; Spadarella, Emanuela; Peltrini, Roberto; Liccardo, Filomena; Bucci, Luigi

2015-01-01

Background Despite the proven benefits, laparoscopic colorectal surgery is still under utilized among surgeons. A steep learning is one of the causes of its limited adoption. Aim of the study is to determine the feasibility and morbidity rate after laparoscopic colorectal surgery in a single institution, “learning curve” experience, implementing a well standardized operative technique and recovery protocol. Methods The first 50 patients treated laparoscopically were included. All the procedures were performed by a trainee surgeon, supervised by a consultant surgeon, according to the principle of complete mesocolic excision with central vascular ligation or TME. Patients underwent a fast track recovery programme. Recovery parameters, short-term outcomes, morbidity and mortality have been assessed. Results Type of resections: 20 left side resections, 8 right side resections, 14 low anterior resection/TME, 5 total colectomy and IRA, 3 total panproctocolectomy and pouch. Mean operative time: 227 min; mean number of lymph-nodes: 18.7. Conversion rate: 8%. Mean time to flatus: 1.3 days; Mean time to solid stool: 2.3 days. Mean length of hospital stay: 7.2 days. Overall morbidity: 24%; major morbidity (Dindo–Clavien III): 4%. No anastomotic leak, no mortality, no 30-days readmission. Conclusion Proper laparoscopic colorectal surgery is safe and leads to excellent results in terms of recovery and short term outcomes, even in a learning curve setting. Key factors for better outcomes and shortening the learning curve seem to be the adoption of a standardized technique and training model along with the strict supervision of an expert colorectal surgeon. PMID:25859386
Fast ForWord[R]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2007

2007-01-01

"Fast ForWord"[R] is a family of computer-based products. According to the developer's web site, the programs help students develop and strengthen the cognitive skills necessary for successful reading and learning. Participants spend 30 to 100 minutes a day, five days a week, for four to 16 weeks with these adaptive exercises. "Fast ForWord[R]…
Chronic intermittent fasting improves cognitive functions and brain structures in mice.

PubMed

Li, Liaoliao; Wang, Zhi; Zuo, Zhiyi

2013-01-01

Obesity is a major health issue. Obesity started from teenagers has become a major health concern in recent years. Intermittent fasting increases the life span. However, it is not known whether obesity and intermittent fasting affect brain functions and structures before brain aging. Here, we subjected 7-week old CD-1 wild type male mice to intermittent (alternate-day) fasting or high fat diet (45% caloric supplied by fat) for 11 months. Mice on intermittent fasting had better learning and memory assessed by the Barnes maze and fear conditioning, thicker CA1 pyramidal cell layer, higher expression of drebrin, a dendritic protein, and lower oxidative stress than mice that had free access to regular diet (control mice). Mice fed with high fat diet was obese and with hyperlipidemia. They also had poorer exercise tolerance. However, these obese mice did not present significant learning and memory impairment or changes in brain structures or oxidative stress compared with control mice. These results suggest that intermittent fasting improves brain functions and structures and that high fat diet feeding started early in life does not cause significant changes in brain functions and structures in obese middle-aged animals.
Chronic Intermittent Fasting Improves Cognitive Functions and Brain Structures in Mice

PubMed Central

Li, Liaoliao; Wang, Zhi; Zuo, Zhiyi

2013-01-01

Obesity is a major health issue. Obesity started from teenagers has become a major health concern in recent years. Intermittent fasting increases the life span. However, it is not known whether obesity and intermittent fasting affect brain functions and structures before brain aging. Here, we subjected 7-week old CD-1 wild type male mice to intermittent (alternate-day) fasting or high fat diet (45% caloric supplied by fat) for 11 months. Mice on intermittent fasting had better learning and memory assessed by the Barnes maze and fear conditioning, thicker CA1 pyramidal cell layer, higher expression of drebrin, a dendritic protein, and lower oxidative stress than mice that had free access to regular diet (control mice). Mice fed with high fat diet was obese and with hyperlipidemia. They also had poorer exercise tolerance. However, these obese mice did not present significant learning and memory impairment or changes in brain structures or oxidative stress compared with control mice. These results suggest that intermittent fasting improves brain functions and structures and that high fat diet feeding started early in life does not cause significant changes in brain functions and structures in obese middle-aged animals. PMID:23755298
Didactical design based on sharing and jumping tasks for senior high school chemistry learning

NASA Astrophysics Data System (ADS)

Fatimah, I.; Hendayana, S.; Supriatna, A.

2018-05-01

The purpose of this research is to develop the didactical design of senior high school chemistry learning based on sharing and jumping tasks in shift equilibrium chemistry. Sharing tasks used to facilitate students slow learners with help by other students of fast learners so they engage in learning. While jumping tasks used to challenge fast learners students so they didn’t feel bored in learning. In developing the didactic design, teacher activity is not only to focus on students and learning materials but also on the relationship between students and learning materials. The results of the analysis teaching plan of shift equilibrium chemistry in attached Senior High School to Indonesia University of Education showed that the learning activities more focus on how the teacher teaches instead of how the process of students’ learning. The use of research method is didactical design research (DDR). Didactical design consisted of three steps i.e. (a) analysing didactical condition before learning, (b) analyzing metapedadidactical, and (c) analyzing retrospective. Data were collected by test, observations, interviews, documentation and recordings (audio and video).The result showed that the didactical design on shift equilibrium chemistry was valid.
Moving Forwards with the Aim of Going Backwards Fast: High-Performance Rowing as a Learning Environment

ERIC Educational Resources Information Center

Rossi, Tony; Rynne, Steven B.; Rabjohns, Martin

2016-01-01

Background and purpose: This paper focuses on the learning culture within the high-performance levels of rowing. In doing so, we explore the case of an individual's learning as he moves across athletic, coaching and administrative functions. This exploration draws on a cultural learning framework and complementary theorisings related to…
An Empirical Study of Instructor Adoption of Web-Based Learning Systems

ERIC Educational Resources Information Center

Wang, Wei-Tsong; Wang, Chun-Chieh

2009-01-01

For years, web-based learning systems have been widely employed in both educational and non-educational institutions. Although web-based learning systems are emerging as a useful tool for facilitating teaching and learning activities, the number of users is not increasing as fast as expected. This study develops an integrated model of instructor…
Designing Collaborative E-Learning Environments Based upon Semantic Wiki: From Design Models to Application Scenarios

ERIC Educational Resources Information Center

Li, Yanyan; Dong, Mingkai; Huang, Ronghuai

2011-01-01

The knowledge society requires life-long learning and flexible learning environment that enables fast, just-in-time and relevant learning, aiding the development of communities of knowledge, linking learners and practitioners with experts. Based upon semantic wiki, a combination of wiki and Semantic Web technology, this paper designs and develops…
Report on the National Learning Roundtable (Edmonton, Alberta, Canada, March 19-20, 2001).

ERIC Educational Resources Information Center

Lowe, Graham S.

Forty-five individuals from a wide range of organizations and backgrounds participated in a national roundtable on learning in Canada. Working in small groups and plenaries, participants proposed a vision for learning as a way to address the widely expressed concern that Canada is not moving fast enough to increase learning opportunities and to…
Classification of large-sized hyperspectral imagery using fast machine learning algorithms

NASA Astrophysics Data System (ADS)

Xia, Junshi; Yokoya, Naoto; Iwasaki, Akira

2017-07-01

We present a framework of fast machine learning algorithms in the context of large-sized hyperspectral images classification from the theoretical to a practical viewpoint. In particular, we assess the performance of random forest (RF), rotation forest (RoF), and extreme learning machine (ELM) and the ensembles of RF and ELM. These classifiers are applied to two large-sized hyperspectral images and compared to the support vector machines. To give the quantitative analysis, we pay attention to comparing these methods when working with high input dimensions and a limited/sufficient training set. Moreover, other important issues such as the computational cost and robustness against the noise are also discussed.
Relationship between gestational fasting plasma glucose and neonatal birth weight, prenatal blood pressure and dystocia in pregnant Chinese women.

PubMed

Zhu, Min; Cai, Jing; Liu, Shujuan; Huang, Mingwei; Chen, Yao; Lai, Xiaolan; Chen, Yuyu; Zhao, Zhongwen; Wu, Fangzhen; Wu, Dongmei; Miu, Haiyan; Lai, Shenghan; Chen, Gang

2014-09-01

Little is known about the optimal cut-off point of fasting plasma glucose for the diagnosis of gestational diabetes mellitus for pregnant Chinese women. This study investigates the relationship between gestational fasting plasma glucose and several variables: neonatal birth weight, prenatal blood pressure and dystocia rate of pregnant women. In this study, we hoped to provide a useful tool to screen gestational diabetes mellitus in pregnant Chinese women. For 1058 pregnant women enrolled in our hospital at pregnancy weeks 22-30, fasting plasma glucose, neonatal birth weight and prenatal blood pressure, as well as dystocia conditions, were examined. We analysed the correlations between the following: gestational fasting plasma glucose and neonatal birth weight; prenatal blood pressure and gestational fasting plasma glucose as well as dystocia rate and gestational fasting plasma glucose group. A modest correlation was observed between gestational fasting plasma glucose and neonatal birth weight (r = 0.093, p = 0.003). The macrosomia rate was smallest when the gestational fasting plasma glucose was in the range 3.51-5.5 mmol/L. Prenatal blood pressure increased linearly with increasing gestational fasting plasma glucose (p = 0.000). There was a significant difference between the dystocia rates in different fasting plasma glucose groups (chi-squared = 13.015, p = 0.043). The results showed that the dystocia rate significantly increased when gestational fasting plasma glucose was >4.9 mmol/L; p = 0.03, OR = 2.156 (95% CI, 1.077-4.318). We suggest that the optimal range of gestational fasting plasma glucose for pregnant Chinese women is in the range 3.5-4.9 mmol/L. Copyright © 2014 John Wiley & Sons, Ltd.
Service Learning and Social Action: Feeding Preservice Teachers' Souls

ERIC Educational Resources Information Center

Eidson, Karla W.; Nickson, Lautrice; Hughes, Teresa

2014-01-01

Preservice teacher education candidates identified personal and professional benefits of participating in a service-learning project helping a food pantry, culminating in a 48-hour fast. At the end of the project, student reflections revealed that the service-learning component influenced participants' preconceptions about hunger.
Robust Fault Diagnosis in Electric Drives Using Machine Learning

DTIC Science & Technology

2004-09-08

detection of fault conditions of the inverter. A machine learning framework is developed to systematically select torque-speed domain operation points...were used to generate various fault condition data for machine learning . The technique is viable for accurate, reliable and fast fault detection in electric drives.
Facilitating Long-Term Changes in Student Approaches to Learning Science

ERIC Educational Resources Information Center

Buchwitz, Brian J.; Beyer, Catharine H.; Peterson, Jon E.; Pitre, Emile; Lalic, Nevena; Sampson, Paul D.; Wakimoto, Barbara T.

2012-01-01

Undergraduates entering science curricula differ greatly in individual starting points and learning needs. The fast pace, high enrollment, and high stakes of introductory science courses, however, limit students' opportunities to self-assess and modify learning strategies. The University of Washington's Biology Fellows Program (BFP) intervenes…
Fast Facts about Online Learning

ERIC Educational Resources Information Center

International Association for K-12 Online Learning, 2013

2013-01-01

This report explores the latest data concerning online and blended learning, enrollment, access, courses, and key policies indicators. It also reviews online learning statistics, trends, policy issues, and iNACOL strategic priorities. This report provides a snapshot view of state funding models for both full-time and supplemental online learning…
Can rational models be good accounts of developmental change? The case of language development at two time scales.

PubMed

Dawson, Colin R; Gerken, LouAnn

2012-01-01

Rational models of human perception and cognition have allowed researchers new ways to look at learning and the ability to make inferences from data. But how good are such models at accounting for developmental change? In this chapter, we address this question in the domain of language development, focusing on the speed with which developmental change takes place, and classifying different types of language development as either fast or slow. From the pattern of fast and slow development observed, we hypothesize that rational learning processes are generally well suited for handling fast processes over small amounts of input data. In contrast, we suggest that associative learning processes are generally better suited to slow development, in which learners accumulate information about what is typical of their language over time. Finally, although one system may be dominant for a particular component of language learning, we speculate that both systems frequently interact, with the associative system providing a source of emergent hypotheses to be evaluated by the rational system and the rational system serving to highlight which aspects of the learner's input need to be processed in greater depth by the associative system.

Propose but verify: Fast mapping meets cross-situational word learning

PubMed Central

Trueswell, John C.; Medina, Tamara Nicol; Hafri, Alon; Gleitman, Lila R.

2012-01-01

We report three eyetracking experiments that examine the learning procedure used by adults as they pair novel words and visually presented referents over a sequence of referentially ambiguous trials. Successful learning under such conditions has been argued to be the product of a learning procedure in which participants provisionally pair each novel word with several possible referents and use a statistical-associative learning mechanism to gradually converge on a single mapping across learning instances. We argue here that successful learning in this setting is instead the product of a one-trial procedure in which a single hypothesized word-referent pairing is retained across learning instances, abandoned only if the subsequent instance fails to confirm the pairing – more a ‘fast mapping’ procedure than a gradual statistical one. We provide experimental evidence for this Propose-but-Verify learning procedure via three experiments in which adult participants attempted to learn the meanings of nonce words cross-situationally under varying degrees of referential uncertainty. The findings, using both explicit (referent selection) and implicit (eye movement) measures, show that even in these artificial learning contexts, which are far simpler than those encountered by a language learner in a natural environment, participants do not retain multiple meaning hypotheses across learning instances. As we discuss, these findings challenge ‘gradualist’ accounts of word learning and are consistent with the known rapid course of vocabulary learning in a first language. PMID:23142693
The effects of a multiyear universal social-emotional learning program: The role of student and school characteristics.

PubMed

2010-04-01

This article examines the impact of a universal social-emotional learning program, the Fast Track PATHS (Promoting Alternative Thinking Strategies) curriculum and teacher consultation, embedded within the Fast Track selective prevention model. The longitudinal analysis involved 2,937 children of multiple ethnicities who remained in the same intervention or control schools for Grades 1, 2, and 3. The study involved a clustered randomized controlled trial involving sets of schools randomized within 3 U.S. locations. Measures assessed teacher and peer reports of aggression, hyperactive-disruptive behaviors, and social competence. Beginning in first grade and through 3 successive years, teachers received training and support and implemented the PATHS curriculum in their classrooms. The study examined the main effects of intervention as well as how outcomes were affected by characteristics of the child (baseline level of problem behavior, gender) and by the school environment (student poverty). Modest positive effects of sustained program exposure included reduced aggression and increased prosocial behavior (according to both teacher and peer report) and improved academic engagement (according to teacher report). Peer report effects were moderated by gender, with significant effects only for boys. Most intervention effects were moderated by school environment, with effects stronger in less disadvantaged schools, and effects on aggression were larger in students who showed higher baseline levels of aggression. A major implication of the findings is that well-implemented multiyear social-emotional learning programs can have significant and meaningful preventive effects on the population-level rates of aggression, social competence, and academic engagement in the elementary school years. (c) 2010 APA, all rights reserved.
Neural responses in songbird forebrain reflect learning rates, acquired salience, and stimulus novelty after auditory discrimination training.

PubMed

Bell, Brittany A; Phan, Mimi L; Vicario, David S

2015-03-01

How do social interactions form and modulate the neural representations of specific complex signals? This question can be addressed in the songbird auditory system. Like humans, songbirds learn to vocalize by imitating tutors heard during development. These learned vocalizations are important in reproductive and social interactions and in individual recognition. As a model for the social reinforcement of particular songs, male zebra finches were trained to peck for a food reward in response to one song stimulus (GO) and to withhold responding for another (NoGO). After performance reached criterion, single and multiunit neural responses to both trained and novel stimuli were obtained from multiple electrodes inserted bilaterally into two songbird auditory processing areas [caudomedial mesopallium (CMM) and caudomedial nidopallium (NCM)] of awake, restrained birds. Neurons in these areas undergo stimulus-specific adaptation to repeated song stimuli, and responses to familiar stimuli adapt more slowly than to novel stimuli. The results show that auditory responses differed in NCM and CMM for trained (GO and NoGO) stimuli vs. novel song stimuli. When subjects were grouped by the number of training days required to reach criterion, fast learners showed larger neural responses and faster stimulus-specific adaptation to all stimuli than slow learners in both areas. Furthermore, responses in NCM of fast learners were more strongly left-lateralized than in slow learners. Thus auditory responses in these sensory areas not only encode stimulus familiarity, but also reflect behavioral reinforcement in our paradigm, and can potentially be modulated by social interactions. Copyright © 2015 the American Physiological Society.
Flight Research into Simple Adaptive Control on the NASA FAST Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curtis E.

2011-01-01

A series of simple adaptive controllers with varying levels of complexity were designed, implemented and flight tested on the NASA Full-Scale Advanced Systems Testbed (FAST) aircraft. Lessons learned from the development and flight testing are presented.
Let's Celebrate Personalization: But Not Too Fast

ERIC Educational Resources Information Center

Tomlinson, Carol Ann

2017-01-01

The concept of personalization in learning appeals to many K-12 teachers and students weary of regimented, one-size-fits-all instruction. The in-vogue term personalization is used to refer to many different learning strategies and structures--from personal learning plans to greater student voice. Differentiation expert Carol Ann Tomlinson is…
Juggling with Language Learning Theories. [Videotape

ERIC Educational Resources Information Center

Murphey, Tim

2005-01-01

Learning to juggle has become popular among corporate training programs because it shows participants how to appreciate mistakes and use "Intelligent Fast Failure" (learning quickly by daring to make a lot of simple mistakes at the beginning of a process). Big business also likes the way juggling can get executives "out of the…
Assessing the Learning Culture and Performance of Educational Institutions

ERIC Educational Resources Information Center

Kumar, Naresh

2005-01-01

In today's fast-paced economy, Higher Learning Institutions (HLIs) are encountering tremendous challenges from the rapid advancement and expansion of new areas of knowledge. Advancement in information, communication, and technologies fundamentally alter the way teaching and learning occurs in colleges and universities. Thus, it is imperative for…
Visual Perceptual Echo Reflects Learning of Regularities in Rapid Luminance Sequences.

PubMed

Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K

2017-08-30

A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a long-lasting reverberation between a rapidly changing visual input and evoked neural activity, apparent in cross-correlations between occipital EEG and stimulus sequences, peaking in the alpha (∼10 Hz) range. We indeed found that perceptual echo is enhanced by repeatedly presenting the same visual sequence, indicating that the human visual system can rapidly and automatically learn regularities embedded within fast-changing dynamic sequences. These results point to a previously undiscovered regularity learning mechanism, operating at a rate defined by the alpha frequency. Copyright © 2017 the authors 0270-6474/17/378486-12$15.00/0.
Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

PubMed Central

Zhang, Jiangshe; Ding, Weifu

2017-01-01

With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R2 increased and root mean square error values decreased respectively. PMID:28125034
Hippocampal theta activity is selectively associated with contingency detection but not discrimination in rabbit discrimination-reversal eyeblink conditioning.

PubMed

Nokia, Miriam S; Wikgren, Jan

2010-04-01

The relative power of the hippocampal theta-band ( approximately 6 Hz) activity (theta ratio) is thought to reflect a distinct neural state and has been shown to affect learning rate in classical eyeblink conditioning in rabbits. We sought to determine if the theta ratio is mostly related to the detection of the contingency between the stimuli used in conditioning or also to the learning of more complex inhibitory associations when a highly demanding delay discrimination-reversal eyeblink conditioning paradigm is used. A high hippocampal theta ratio was not only associated with a fast increase in conditioned responding in general but also correlated with slow emergence of discriminative responding due to sustained responding to the conditioned stimulus not paired with an unconditioned stimulus. The results indicate that the neural state reflected by the hippocampal theta ratio is specifically linked to forming associations between stimuli rather than to the learning of inhibitory associations needed for successful discrimination. This is in line with the view that the hippocampus is responsible for contingency detection in the early phase of learning in eyeblink conditioning. (c) 2009 Wiley-Liss, Inc.
Exploring the Relationship between Dimensions of Organizational Learning and Firms' Financial and Knowledge Performance in the Korean Business Context

ERIC Educational Resources Information Center

Cho, Insik

2009-01-01

Many scholars and practitioners have emphasized the importance of learning within and by organizations to respond to the fast changing world. As a result, organizational learning has become a necessity to remain competitive. Though the importance of organizational learning has been growing in response to the rapidly changing business context,…
I'm Deleting as Fast as I Can: Negotiating Learning Practices in Cyberspace

ERIC Educational Resources Information Center

Thompson, Terrie Lynn

2012-01-01

Learning in and through work is one of the many spaces in which pedagogy may unfold. Web technologies amplify this fluidity and online learning now encompasses a plethora of practices. In this paper I focus on the delete button and deleting practices of self-employed workers engaged in informal work-related learning in online communities. How the…
Getting Comfortable with Failure and Vulnerability to Facilitate Learning and Innovation in the Game of School

ERIC Educational Resources Information Center

Machajewski, Szymon

2017-01-01

Schools are to prepare students for success. However, they often villainize failure. Instead, schools should teach students how to fail fast and safely in order to learn and to allow innovation through vulnerability. The lessons that the gaming culture has for learning will define future strategies of teaching and learning. Games are sometimes…
An Intelligent E-Learning Software for Learning to Write Correct Chinese Characters on Mobile Devices

ERIC Educational Resources Information Center

Tam, Vincent

2012-01-01

Purpose: Learning Chinese is unquestionably very important and popular worldwide with the fast economic growth of China. To most foreigners and also local students, one of the major challenges in learning Chinese is to write Chinese characters in correct stroke sequences that are considered as significant in the Chinese culture. However, due to…
User Acceptance of Mobile Technology: A Campus-Wide Implementation of Blackboard's Mobile™ Learn Application

ERIC Educational Resources Information Center

Chen, Baiyun; Sivo, Stephen; Seilhamer, Ryan; Sugar, Amy; Mao, Jin

2013-01-01

Mobile learning is a fast growing trend in higher education. This study examined how an extended technology acceptance model (TAM) could evaluate and predict the use of a mobile application in learning. A path analysis design was used to measure the mediating effects on the use of Blackboard's Mobile™ Learn application in coursework (N = 77). The…
DOE Office of Scientific and Technical Information (OSTI.GOV)

Samarel, A.M.; Parmacek, M.S.; Magid, N.M.

To determine the relative importance of protein degradation in the development of starvation-induced cardiac atrophy, in vivo fractional synthetic rates of total cardiac protein, myosin heavy chain, actin, light chain 1, and light chain 2 were measured in fed and fasted rabbits by continuous infusion of (/sup 3/H) leucine. In addition, the rate of left ventricular protein accumulation and loss were assessed in weight-matched control and fasted rabbits. Rates of total cardiac protein degradation were then estimated as the difference between rates of synthesis and growth. Fasting produced left ventricular atrophy by decreasing the rate of left ventricular protein synthesismore » (34.8 +/- 1.4, 27.3 +/- 3.0, and 19.3 +/- 1.2 mg/day of left ventricular protein synthesized for 0-, 3-, and 7-day fasted rabbits, respectively). Inhibition of contractile protein synthesis was evident by significant reductions in the fractional synthetic rates of all myofibrillar protein subunits. Although fractional rates of protein degradation increased significantly within 7 days of fasting, actual amounts of left ventricular protein degraded per day were unaffected. Thus, prolonged fasting profoundly inhibits the synthesis of new cardiac protein, including the major protein constituents of the myofibril. Both this inhibition in new protein synthesis as well as a smaller but significant reduction in the average half-lives of cardiac proteins are responsible for atrophy of the heart in response to fasting.« less
Fasting induces an anti-inflammatory effect on the neuroimmune system which a high-fat diet prevents

PubMed Central

Lavin, Desiree N.; Joesting, Jennifer J.; Chiu, Gabriel S.; Moon, Morgan L.; Meng, Jia; Dilger, Ryan N.; Freund, Gregory G.

2013-01-01

The neuroimmunological and behavioral consequences of a high-fat diet (HFD) are not well delineated. This is especially true when short term (24 h) fasting is used as a physiologic stressor. In this study, we examined the impact of a HFD on learning and memory and depressive-like behaviors to understand how fasting impacts neuroimmunity and if obesity modulates the response. Mice were fed diets containing either 10% (LFD mice) or 60% (HFD mice) calories from fat for 10-12 wks. Gene transcripts for 26 pro-/anti-inflammatory cytokines and markers of macrophage activation were examined in adipose tissue and whole brain. Mouse learning and memory (spontaneous alternation, novel object) and depressive like behaviors (saccharin preference, burrowing, forced swim) were studied in the fed and fasted state as were gene transcripts for F4/80, CD11b, IL-1alpha, IL-1beta, IL-1R1, IL-1R2, IL-1RA, IL-6 and TNF-alpha in cortex, hippocampus and hypothalamus. In the fed state, HFD mice compared to LFD mice had reduced locomotor activity, were adverse to saccharin and burrowed less. After fasting, LFD mice verse HFD mice lost 18% vs 5% of their body weight, respectively. In addition, HFD mice failed to down-regulate gene transcripts for the myeloid-cell associated proteins F4/80, CD11b and IL-1alpha in the brain, failed to appropriately explore a novel object, failed to reduce locomotor activity and had increased saccharin consumption and burrowing. These data indicate that fasting induces an anti-inflammatory effect on the neuroimmune system which a HFD prevents. This breakdown appears linked to the IL-1 system because of the association of this cytokine with memory and learning. PMID:21527899
Learning fast accurate movements requires intact frontostriatal circuits

PubMed Central

Shabbott, Britne; Ravindran, Roshni; Schumacher, Joseph W.; Wasserman, Paula B.; Marder, Karen S.; Mazzoni, Pietro

2013-01-01

The basal ganglia are known to play a crucial role in movement execution, but their importance for motor skill learning remains unclear. Obstacles to our understanding include the lack of a universally accepted definition of motor skill learning (definition confound), and difficulties in distinguishing learning deficits from execution impairments (performance confound). We studied how healthy subjects and subjects with a basal ganglia disorder learn fast accurate reaching movements. We addressed the definition and performance confounds by: (1) focusing on an operationally defined core element of motor skill learning (speed-accuracy learning), and (2) using normal variation in initial performance to separate movement execution impairment from motor learning abnormalities. We measured motor skill learning as performance improvement in a reaching task with a speed-accuracy trade-off. We compared the performance of subjects with Huntington's disease (HD), a neurodegenerative basal ganglia disorder, to that of premanifest carriers of the HD mutation and of control subjects. The initial movements of HD subjects were less skilled (slower and/or less accurate) than those of control subjects. To factor out these differences in initial execution, we modeled the relationship between learning and baseline performance in control subjects. Subjects with HD exhibited a clear learning impairment that was not explained by differences in initial performance. These results support a role for the basal ganglia in both movement execution and motor skill learning. PMID:24312037
Coding rate and duration of vocalizations of the frog, Xenopus laevis.

PubMed

Zornik, Erik; Yamaguchi, Ayako

2012-08-29

Vocalizations involve complex rhythmic motor patterns, but the underlying temporal coding mechanisms in the nervous system are poorly understood. Using a recently developed whole-brain preparation from which "fictive" vocalizations are readily elicited in vitro, we investigated the cellular basis of temporal complexity of African clawed frogs (Xenopus laevis). Male advertisement calls contain two alternating components--fast trills (∼300 ms) and slow trills (∼700 ms) that contain clicks repeated at ∼60 and ∼30 Hz, respectively. We found that males can alter the duration of fast trills without changing click rates. This finding led us to hypothesize that call rate and duration are regulated by independent mechanisms. We tested this by obtaining whole-cell patch-clamp recordings in the "fictively" calling isolated brain. We discovered a single type of premotor neuron with activity patterns correlated with both the rate and duration of fast trills. These "fast-trill neurons" (FTNs) exhibited long-lasting depolarizations (LLDs) correlated with each fast trill and action potentials that were phase-locked with motor output-neural correlates of call duration and rate, respectively. When depolarized without central pattern generator activation, FTNs produced subthreshold oscillations and action potentials at fast-trill rates, indicating FTN resonance properties are tuned to, and may dictate, the fast-trill rhythm. NMDA receptor (NMDAR) blockade eliminated LLDs in FTNs, and NMDAR activation in synaptically isolated FTNs induced repetitive LLDs. These results suggest FTNs contain an NMDAR-dependent mechanism that may regulate fast-trill duration. We conclude that a single premotor neuron population employs distinct mechanisms to regulate call rate and duration.
EFFECT OF DELAYED AUDITORY FEEDBACK, SPEECH RATE, AND SEX ON SPEECH PRODUCTION.

PubMed

Stuart, Andrew; Kalinowski, Joseph

2015-06-01

Perturbations in Delayed Auditory Feedback (DAF) and speech rate were examined as sources of disruptions in speech between men and women. Fluent adult men (n = 16) and women (n = 16) spoke at a normal and an imposed fast rate of speech with 0, 25, 50, 100, and 200 msec. DAF. The syllable rate significantly increased when participants were instructed to speak at a fast rate, and the syllable rate decreased with increasing DAF delays. Men's speech rate was significantly faster during the fast speech rate condition with a 200 msec. DAF. Disfluencies increased with increasing DAF delay. Significantly more disfluency occurred at delays of 25 and 50 msec. at the fast rate condition, while more disfluency occurred at 100 and 200 msec. in normal rate conditions. Men and women did not display differences in the number of disfluencies. These findings demonstrate sex differences in susceptibility to perturbations in DAF and speech rate suggesting feedforward/feedback subsystems that monitor vocalizations may be different between sexes.

Adaptive Filtering to Enhance Noise Immunity of Impedance and Admittance Spectroscopy: Comparison with Fourier Transformation

NASA Astrophysics Data System (ADS)

Stupin, Daniil D.; Koniakhin, Sergei V.; Verlov, Nikolay A.; Dubina, Michael V.

2017-05-01

The time-domain technique for impedance spectroscopy consists of computing the excitation voltage and current response Fourier images by fast or discrete Fourier transformation and calculating their relation. Here we propose an alternative method for excitation voltage and current response processing for deriving a system impedance spectrum based on a fast and flexible adaptive filtering method. We show the equivalence between the problem of adaptive filter learning and deriving the system impedance spectrum. To be specific, we express the impedance via the adaptive filter weight coefficients. The noise-canceling property of adaptive filtering is also justified. Using the RLC circuit as a model system, we experimentally show that adaptive filtering yields correct admittance spectra and elements ratings in the high-noise conditions when the Fourier-transform technique fails. Providing the additional sensitivity of impedance spectroscopy, adaptive filtering can be applied to otherwise impossible-to-interpret time-domain impedance data. The advantages of adaptive filtering are justified with practical living-cell impedance measurements.
Factors Determining e-Learning Service Quality

ERIC Educational Resources Information Center

Uppal, Muhammad Amaad; Ali, Samnan; Gulliver, Stephen R.

2018-01-01

e-Learning courses are fast becoming common-place, yet the success of these online courses varies considerably. Since limited research addresses the issue of e-learning quality (ELQ) of service in higher education environments, there is an increasing need to effectively assess ELQ. In this paper, we argue that to obtain a satisfactory e-learning…
Hybrid Learning in Higher Education: The Potential of Teaching and Learning with Robot-Mediated Communication

ERIC Educational Resources Information Center

Gleason, Benjamin; Greenhow, Christine

2017-01-01

Blended learning, which combines online and face-to-face pedagogy, is a fast-growing mode of instruction as universities strive for equitable and alternative pathways to course enrollment, retention, and educational attainment. However, challenges to successfully implementing blended instruction are that "social presence," or students'…
Functional connectivity in the resting-state motor networks influences the kinematic processes during motor sequence learning

PubMed Central

Bonzano, Laura; Palmaro, Eleonora; Teodorescu, Roxana; Fleysher, Lazar; Inglese, Matilde; Bove, Marco

2014-01-01

Neuroimaging studies support the involvement of the cerebello-cortical and striato-cortical motor loops in motor sequence learning. Here, we investigated whether the gain of motor sequence learning could depend on a priori resting-state functional connectivity (rsFC) between motor areas and structures belonging to these circuits. Fourteen healthy subjects underwent a resting-state fMRI session. Afterward, they were asked to reproduce a verbally-learned sequence of finger opposition movements as fast and accurate as possible. All subjects increased their movement rate with practice, by reducing touch duration and/or inter tapping interval. The rsFC analysis showed that at rest left and right M1 and left and right supplementary motor cortex (SMA) were mainly connected with other motor areas. The covariate analysis taking into account the different kinematic parameters indicated that the subjects achieving greater movement rate increase were those showing stronger rsFC of the left M1 and SMA with the right lobule VIII of the cerebellum. Notably, the subjects with greater inter tapping interval reduction showed stronger rsFC of the left M1 and SMA with the association nuclei of the thalamus. Conversely, the regression analysis with the right M1 and SMA seeds showed only few significant clusters for the different covariates not located in the cerebellum and thalamus. No common clusters were found between right M1 and SMA. All these findings indicate important functional connections at rest of those neural circuits responsible of motor learning improvement, involving the motor areas related to the hemisphere directly controlling the finger movements, the thalamus and the cerebellum. PMID:25328043
Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy.

PubMed

Miall, R Chris; Kitchen, Nick M; Nam, Se-Ho; Lefumat, Hannah; Renault, Alix G; Ørstavik, Kristin; Cole, Jonathan D; Sarlegna, Fabrice R

2018-05-19

It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participants' perception of applied forces. With visual feedback, the PL participants could report the perturbation's direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies.
Automated volumetric lung segmentation of thoracic CT images using fully convolutional neural network

NASA Astrophysics Data System (ADS)

Negahdar, Mohammadreza; Beymer, David; Syeda-Mahmood, Tanveer

2018-02-01

Deep Learning models such as Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in 2D medical image analysis. In clinical practice; however, most analyzed and acquired medical data are formed of 3D volumes. In this paper, we present a fast and efficient 3D lung segmentation method based on V-net: a purely volumetric fully CNN. Our model is trained on chest CT images through volume to volume learning, which palliates overfitting problem on limited number of annotated training data. Adopting a pre-processing step and training an objective function based on Dice coefficient addresses the imbalance between the number of lung voxels against that of background. We have leveraged Vnet model by using batch normalization for training which enables us to use higher learning rate and accelerates the training of the model. To address the inadequacy of training data and obtain better robustness, we augment the data applying random linear and non-linear transformations. Experimental results on two challenging medical image data show that our proposed method achieved competitive result with a much faster speed.
Learning speed is affected by personality and reproductive investment in a songbird.

PubMed

Rivera-Gutierrez, Hector Fabio; Martens, Tine; Pinxten, Rianne; Eens, Marcel

2017-01-01

Individuals from different taxa, including songbirds, differ consistently in behaviour and personality when facing different situations. Although our understanding of animal behaviour has increased, knowledge about between-individual differences in cognitive abilities is still limited. By using an experimental approach and a free-living songbird (Parus major) as a model, we attempted to understand between-individual differences in habituation to playbacks (as a proxy of learning speed), by investigating the role of personality, age and reproductive investment (clutch size). Pre-breeding males were tested for exploration (a proxy of personality) in standardized conditions. In addition, the same individuals were exposed to three playbacks in the field during incubation. Birds significantly moved less, stayed further away and overlapped less the playback with successive playback stimulation. While a decrease in the locomotor behaviour can be explained by personality, differences in habituation of overlapping were predicted by both reproductive investment and personality. Fast explorers habituated less. Moreover, males paired to females with larger clutches did not vary the intensity of overlapping. Since habituation requires information for recognition of non-threatening signals, personality may bias information gathering. While fast explorers may collect less information from the environment, slow explorers (reactive birds) seem to pay attention to environmental clues and collect detailed information. We provided evidence that the rate of habituation of behavioural responses, a proxy of cognitive abilities, may be affected by different factors and in a complex way.
Accelerated Leadership Development: Fast Tracking School Leaders

ERIC Educational Resources Information Center

Earley, Peter; Jones, Jeff

2010-01-01

"Accelerated Leadership Development" captures and communicates the lessons learned from successful fast-track leadership programmes in the private and public sector, and provides a model which schools can follow and customize as they plan their own leadership development strategies. As large numbers of headteachers and other senior staff…
Project FAST: [Functional Analysis Systems Training]: Adopter/Facilitator Information.

ERIC Educational Resources Information Center

Essexville-Hampton Public Schools, MI.

Presented is adopter/facilitator information of Project FAST (Functional Analysis Systems Training) to provide educational and support services to learning disordered children and their regular elementary teachers. Briefly described are the three schools in the Essexville-Hampton (Michigan) school district; objectives of the program; program…
A fast and precise indoor localization algorithm based on an online sequential extreme learning machine.

PubMed

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-15

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.
Carnivora Population Dynamics Are as Slow and as Fast as Those of Other Mammals: Implications for Their Conservation

PubMed Central

van de Kerk, Madelon; de Kroon, Hans; Conde, Dalia A.; Jongejans, Eelke

2013-01-01

Of the 285 species of Carnivora 71 are threatened, while many of these species fulfill important ecological roles in their ecosystems as top or meso-predators. Population transition matrices make it possible to study how age-specific survival and fecundity affect population growth, extinction risks, and responses to management strategies. Here we review 38 matrix models from 35 studies on 27 Carnivora taxa, covering 11% of the threatened Carnivora species. We show that the elasticity patterns (i.e. distribution over fecundity, juvenile survival and adult survival) in Carnivora cover the same range in triangular elasticity plots as those of other mammal species, despite the specific place of Carnivora in the food chain. Furthermore, reproductive loop elasticity analysis shows that the studied species spread out evenly over a slow-fast continuum, but also quantifies the large variation in the duration of important life cycles and their contributions to population growth rate. These general elasticity patterns among species, and their correlation with simple life history characteristics like body mass, age of first reproduction and life span, enables the extrapolation of population dynamical properties to unstudied species. With several examples we discuss how this slow-fast continuum, and related patterns of variation in reproductive loop elasticity, can be used in the formulation of tentative management plans for threatened species that cannot wait for the results of thorough demographic studies. We argue, however, that such management programs should explicitly include a plan for learning about the key demographic rates and how these are affected by environmental drivers and threats. PMID:23950922
Railway obstacle detection algorithm using neural network

NASA Astrophysics Data System (ADS)

Yu, Mingyang; Yang, Peng; Wei, Sen

2018-05-01

Aiming at the difficulty of detection of obstacle in outdoor railway scene, a data-oriented method based on neural network to obtain image objects is proposed. First, we mark objects of images(such as people, trains, animals) acquired on the Internet. and then use the residual learning units to build Fast R-CNN framework. Then, the neural network is trained to get the target image characteristics by using stochastic gradient descent algorithm. Finally, a well-trained model is used to identify an outdoor railway image. if it includes trains and other objects, it will issue an alert. Experiments show that the correct rate of warning reached 94.85%.
The new ATLAS Fast Calorimeter Simulation

NASA Astrophysics Data System (ADS)

Schaarschmidt, J.; ATLAS Collaboration

2017-10-01

Current and future need for large scale simulated samples motivate the development of reliable fast simulation techniques. The new Fast Calorimeter Simulation is an improved parameterized response of single particles in the ATLAS calorimeter that aims to accurately emulate the key features of the detailed calorimeter response as simulated with Geant4, yet approximately ten times faster. Principal component analysis and machine learning techniques are used to improve the performance and decrease the memory need compared to the current version of the ATLAS Fast Calorimeter Simulation. A prototype of this new Fast Calorimeter Simulation is in development and its integration into the ATLAS simulation infrastructure is ongoing.
Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning.

PubMed

Kuroda, S; Yamamoto, K; Miyamoto, H; Doya, K; Kawat, M

2001-03-01

Mean firing rates (MFRs), with analogue values, have thus far been used as information carriers of neurons in most brain theories of learning. However, the neurons transmit the signal by spikes, which are discrete events. The climbing fibers (CFs), which are known to be essential for cerebellar motor learning, fire at the ultra-low firing rates (around 1 Hz), and it is not yet understood theoretically how high-frequency information can be conveyed and how learning of smooth and fast movements can be achieved. Here we address whether cerebellar learning can be achieved by CF spikes instead of conventional MFR in an eye movement task, such as the ocular following response (OFR), and an arm movement task. There are two major afferents into cerebellar Purkinje cells: parallel fiber (PF) and CF, and the synaptic weights between PFs and Purkinje cells have been shown to be modulated by the stimulation of both types of fiber. The modulation of the synaptic weights is regulated by the cerebellar synaptic plasticity. In this study we simulated cerebellar learning using CF signals as spikes instead of conventional MFR. To generate the spikes we used the following four spike generation models: (1) a Poisson model in which the spike interval probability follows a Poisson distribution, (2) a gamma model in which the spike interval probability follows the gamma distribution, (3) a max model in which a spike is generated when a synaptic input reaches maximum, and (4) a threshold model in which a spike is generated when the input crosses a certain small threshold. We found that, in an OFR task with a constant visual velocity, learning was successful with stochastic models, such as Poisson and gamma models, but not in the deterministic models, such as max and threshold models. In an OFR with a stepwise velocity change and an arm movement task, learning could be achieved only in the Poisson model. In addition, for efficient cerebellar learning, the distribution of CF spike-occurrence time after stimulus onset must capture at least the first, second and third moments of the temporal distribution of error signals.
A Machine Learning Approach to Investigating the Effects of Mathematics Dispositions on Mathematical Literacy

ERIC Educational Resources Information Center

Gabriel, Florence; Signolet, Jason; Westwell, Martin

2018-01-01

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
A Distinctive Theory of Teaching and Learning for Older Learners: Why and Why Not?

ERIC Educational Resources Information Center

Tam, Maureen

2014-01-01

In the wake of the world's fast-growing ageing populations and the increasing recognition of the benefits of later life learning towards successful ageing, opportunities for elders and senior persons to engage in learning have proliferated, resulting in an array of programmes and activities being planned and organized by governments,…
English Learners (ELs) and Early Learning. Fast Facts

ERIC Educational Resources Information Center

Office of English Language Acquisition, US Department of Education, 2015

2015-01-01

The Office of English Language Acquisition (OELA) and Office of Early Learning (OEL) has synthesized key data on English learners (ELs) and early learning into two-page PDF sheets, by topic, with graphics, plus key contacts. The topics for this report include: (1) State-funded preschool programs with highest percentage of ELs: Fall 2013; (2)…
Changes in Sensory Evoked Responses Coincide with Rapid Improvement in Speech Identification Performance

ERIC Educational Resources Information Center

Alain, Claude; Campeanu, Sandra; Tremblay, Kelly

2010-01-01

Perceptual learning is sometimes characterized by rapid improvements in performance within the first hour of training (fast perceptual learning), which may be accompanied by changes in sensory and/or response pathways. Here, we report rapid physiological changes in the human auditory system that coincide with learning during a 1-hour test session…
Word Learning in 6-Month-Olds: Fast Encoding-Weak Retention

ERIC Educational Resources Information Center

Friedrich, Manuela; Friederici, Angela D.

2011-01-01

There has been general consensus that initial word learning during early infancy is a slow and time-consuming process that requires very frequent exposure, whereas later in development, infants are able to quickly learn a novel word for a novel meaning. From the perspective of memory maturation, this shift in behavioral development might represent…
A framework for porting the NeuroBayes machine learning algorithm to FPGAs

NASA Astrophysics Data System (ADS)

Baehr, S.; Sander, O.; Heck, M.; Feindt, M.; Becker, J.

2016-01-01

The NeuroBayes machine learning algorithm is deployed for online data reduction at the pixel detector of Belle II. In order to test, characterize and easily adapt its implementation on FPGAs, a framework was developed. Within the framework an HDL model, written in python using MyHDL, is used for fast exploration of possible configurations. Under usage of input data from physics simulations figures of merit like throughput, accuracy and resource demand of the implementation are evaluated in a fast and flexible way. Functional validation is supported by usage of unit tests and HDL simulation for chosen configurations.

Fast Low-Rank Shared Dictionary Learning for Image Classification.

PubMed

Tiep Huu Vu; Monga, Vishal

2017-11-01

Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recently proposed dictionary learning framework by separating the particularity and the commonality (COPAR). Inspired by this, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification with more intuitive constraints. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low-rank constraint, i.e., claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Furthermore, we develop new fast and accurate algorithms to solve the subproblems in the learning step, accelerating its convergence. The said algorithms could also be applied to FDDL and its extensions. The efficiencies of these algorithms are theoretically and experimentally verified by comparing their complexities and running time with those of other well-known dictionary learning methods. Experimental results on widely used image data sets establish the advantages of our method over the state-of-the-art dictionary learning methods.
Fast Low-Rank Shared Dictionary Learning for Image Classification

NASA Astrophysics Data System (ADS)

Vu, Tiep Huu; Monga, Vishal

2017-11-01

Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recently proposed dictionary learning framework by separating the particularity and the commonality (COPAR). Inspired by this, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification with more intuitive constraints. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low-rank constraint, i.e. claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Further, we develop new fast and accurate algorithms to solve the subproblems in the learning step, accelerating its convergence. The said algorithms could also be applied to FDDL and its extensions. The efficiencies of these algorithms are theoretically and experimentally verified by comparing their complexities and running time with those of other well-known dictionary learning methods. Experimental results on widely used image datasets establish the advantages of our method over state-of-the-art dictionary learning methods.
Fast detection of the fuzzy communities based on leader-driven algorithm

NASA Astrophysics Data System (ADS)

Fang, Changjian; Mu, Dejun; Deng, Zhenghong; Hu, Jun; Yi, Chen-He

2018-03-01

In this paper, we present the leader-driven algorithm (LDA) for learning community structure in networks. The algorithm allows one to find overlapping clusters in a network, an important aspect of real networks, especially social networks. The algorithm requires no input parameters and learns the number of clusters naturally from the network. It accomplishes this using leadership centrality in a clever manner. It identifies local minima of leadership centrality as followers which belong only to one cluster, and the remaining nodes are leaders which connect clusters. In this way, the number of clusters can be learned using only the network structure. The LDA is also an extremely fast algorithm, having runtime linear in the network size. Thus, this algorithm can be used to efficiently cluster extremely large networks.
Gluconeogenesis is associated with high rates of tricarboxylic acid and pyruvate cycling in fasting northern elephant seals.

PubMed

Champagne, Cory D; Houser, Dorian S; Fowler, Melinda A; Costa, Daniel P; Crocker, Daniel E

2012-08-01

Animals that endure prolonged periods of food deprivation preserve vital organ function by sparing protein from catabolism. Much of this protein sparing is achieved by reducing metabolic rate and suppressing gluconeogenesis while fasting. Northern elephant seals (Mirounga angustirostris) endure prolonged fasts of up to 3 mo at multiple life stages. During these fasts, elephant seals maintain high levels of activity and energy expenditure associated with breeding, reproduction, lactation, and development while maintaining rates of glucose production typical of a postabsorptive mammal. Therefore, we investigated how fasting elephant seals meet the requirements of glucose-dependent tissues while suppressing protein catabolism by measuring the contribution of glycogenolysis, glycerol, and phosphoenolpyruvate (PEP) to endogenous glucose production (EGP) during their natural 2-mo postweaning fast. Additionally, pathway flux rates associated with the tricarboxylic acid (TCA) cycle were measured specifically, flux through phosphoenolpyruvate carboxykinase (PEPCK) and pyruvate cycling. The rate of glucose production decreased during the fast (F(1,13) = 5.7, P = 0.04) but remained similar to that of postabsorptive mammals. The fractional contributions of glycogen, glycerol, and PEP did not change with fasting; PEP was the primary gluconeogenic precursor and accounted for ∼95% of EGP. This large contribution of PEP to glucose production occurred without substantial protein loss. Fluxes through the TCA cycle, PEPCK, and pyruvate cycling were higher than reported in other species and were the most energetically costly component of hepatic carbohydrate metabolism. The active pyruvate recycling fluxes detected in elephant seals may serve to rectify gluconeogeneic PEP production during restricted anaplerotic inflow in these fasting-adapted animals.
Fuzzy self-learning control for magnetic servo system

NASA Technical Reports Server (NTRS)

Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

1994-01-01

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.
Reconstruction of shifting elbow joint compliant characteristics during fast and slow movements.

PubMed

Latash, M L; Gottlieb, G L

1991-01-01

The purpose of this study was to experimentally investigate the applicability of the equilibrium-point hypothesis to the dynamics of single-joint movements. Subjects were trained to perform relatively slow (movement time 600-1000 ms) or fast (movement time 200-300 ms) single-joint elbow flexion movements against a constant extending torque bias. They were instructed to reproduce the same time pattern of central motor command for a series of movements when the external torque could slowly and unpredictably increase, decrease, or remain constant. For fast movements, the total muscle torque was calculated as a sum of external and inertial components. Analysis of the data allowed reconstruction of the elbow joint compliant characteristics at different times during execution of the learned motor command. "Virtual" trajectories of the movements, representing time-varying changes in a central control parameter, were reconstructed and compared with the "actual" trajectories. For slow movements, the actual trajectories lagged behind the virtual ones. There were no consistent changes in the joint stiffness during slow movements. Similar analysis of experiments without voluntary movements demonstrated a lack of changes in the central parameters, supporting the assumption that the subjects were able to keep the same central motor command in spite of externally imposed unexpected torque perturbations. For the fast movements, the virtual trajectories were N-shaped, and the joint stiffness demonstrated a considerable increase near the middle of the movement. These findings contradict an hypothesis of monotonic joint compliant characteristic translation at a nearly constant rate during such movements.
Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs.

PubMed

Berke, J D

2009-09-01

Oscillations may organize communication between components of large-scale brain networks. Although gamma-band oscillations have been repeatedly observed in cortical-basal ganglia circuits, their functional roles are not yet clear. Here I show that, in behaving rats, distinct frequencies of ventral striatal local field potential oscillations show coherence with different cortical inputs. The approximately 50 Hz gamma oscillations that normally predominate in awake ventral striatum are coherent with piriform cortex, whereas approximately 80-100 Hz high-gamma oscillations are coherent with frontal cortex. Within striatum, entrainment to gamma rhythms is selective to fast-spiking interneurons, with distinct fast-spiking interneuron populations entrained to different gamma frequencies. Administration of the psychomotor stimulant amphetamine or the dopamine agonist apomorphine causes a prolonged decrease in approximately 50 Hz power and increase in approximately 80-100 Hz power. The same frequency switch is observed for shorter epochs spontaneously in awake, undrugged animals and is consistently provoked for < 1 s following reward receipt. Individual striatal neurons can participate in these brief high-gamma bursts with, or without, substantial changes in firing rate. Switching between discrete oscillatory states may allow different modes of information processing during decision-making and reinforcement-based learning, and may also be an important systems-level process by which stimulant drugs affect cognition and behavior.
Summer anesthesiology externship: Demonstrating the ability of early clinical involvement to educate and increase specialty interest.

PubMed

Baker, Kevin S; Cormican, Daniel; Seidman, Peggy A

2012-01-01

We describe the influence of a 6-week "Summer Anesthesiology Externship" featuring didactic, procedure, and simulation education on formation of medical students' specialty choice. Eighteen months after externship completion, externs were sent a questionnaire with Likert scale agreement ratings of subspecialties/simulations and yes/no questions about student career interests before/after the program, stipend importance, and procedural skill performance during/after the program. General anesthesiology had the highest subspecialty approval rating (9.0). Externs strongly agreed that simulations successfully progressed at first year student understanding levels (9.2 mean agreement rating), increased confidence in being part of a care team (9.4 mean agreement rating), and provided personal/interpersonal development. Externs unanimously agreed that the program introduced them to the breadth of anesthesiology, and that practicing clinical/procedural skills improved confidence when performing the procedures later in medical school. Four of 14 students applied for the externship with some focus on anesthesiology as a career choice. After the externship, a significantly higher number of students (12 of 14) were strongly considering applying to the field (p<0.0001). Eleven of 14 ultimately entered anesthesiology residencies, a significantly higher rate than our general medical student classes (p<0.0001). Both CA1 and CA3 resident post-test scores improved at the end of the ultrasound guided regional workshop. Our study showed a 68% improvement in test scores, which is larger than the 50% improvement previously reported. These results show that fast learning can occur in this type of setting. Furthermore, knowledge acquired during the workshop was retained when CA1 residents were re-tested one year after the workshop. The ultrasound-guided regional anesthesia workshop will become part of the didactic series for our CA1 residents and will be a required learning activity. Additional work still needs to be done to find out the best way to test knowledge and skill outcomes in residents learning new technology and techniques.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolfe, R.R.; Peters, E.J.; Klein, S.

In this study the rate of lipolysis (fatty acid and glycerol release into blood) has been quantified in both normal weight and obese volunteers after both 15 and 87 h of fasting. In each study, the basal rate and subsequent response to epinephrine infusion were determined. The rate of appearance (R/sub a/) of free fatty acids (FFA) and glycerol were quantified by infusion of (1- TC)palmitate and D-5-glycerol, respectively. Substrate flux rates per unit of body fat mass and lean body mass were calculated from total body water measurements using H2 YO dilution. In normal volunteers, the basal R/sub a/more » FFA and R/sub a/ glycerol rose markedly with 87 h of fasting, whereas the increases were more modest in the obese subjects. However, the rate of mobilization of fat, in relation to the lean body mass, was higher in the obese subjects than in the normal subjects after 15 h of fasting, and the values were similar in both groups after 87 h of fasting. There was an increased lipolytic response to epinephrine after fasting in both groups. This increased sensitivity may have resulted from the enhancement of fatty acid-triglyceride substrate cycling that occurred after fasting.« less
Uncovering and Managing the Impact of Methodological Choices for the Computational Construction of Socio-Technical Networks from Texts

DTIC Science & Technology

2012-01-01

networks has become fast , cheap, and easy (Shapiro, 1971; Trigg & Weiser, 1986). Modern information and communication technologies, such as the internet...However, once the model is learned, inference time is not subject to this constraint. Therefore, applying the model in end-user applications is fast ...products that facilitate the fast collection and assessment of these networks. For the purpose of analyzing socio-technical networks of geopolitical
Measured Thermal and Fast Neutron Fluence Rates for ATF-1 Holders During ATR Cycle 157D

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

Smith, Larry Don; Miller, David Torbet

This report contains the thermal (2200 m/s) and fast (E>1MeV) neutron fluence rate data for the ATF-1 holders located in core for ATR Cycle 157D which were measured by the Radiation Measurements Laboratory (RML) as requested by the Power Reactor Programs (ATR Experiments) Radiation Measurements Work Order. This report contains measurements of the fluence rates corresponding to the particular elevations relative to the 80-ft. core elevation. The data in this report consist of (1) a table of the ATR power history and distribution, (2) a hard copy listing of all thermal and fast neutron fluence rates, and (3) plots ofmore » both the thermal and fast neutron fluence rates. The fluence rates reported are for the average power levels given in the table of power history and distribution.« less
The relationship between phonological memory, receptive vocabulary, and fast mapping in young children with specific language impairment.

PubMed

Gray, Shelley

2006-10-01

This study assessed the fast mapping performance of children with specific language impairment (SLI) across the preschool to kindergarten age span in relation to their phonological memory and vocabulary development. Fifty-three children diagnosed with SLI and 53 children with normal language (NL) matched for age and gender (30 three-year-olds, 18 four-year-olds, 28 five-year-olds, and 30 six-year-olds) participated. Children's phonological memory was assessed using nonword repetition and digit span tasks. Receptive vocabulary was assessed using the Peabody Picture Vocabulary Test-III. Children learned the names for 8 objects during 2 fast mapping tasks. Overall, the NL group demonstrated significantly better performance on phonological memory and vocabulary measures across the age span; however, performance on the fast mapping task differed significantly only at age 5. Phonological memory and existing receptive vocabulary did not predict fast mapping ability. The phonological memory skills of preschoolers with NL and SLI followed a similar developmental pattern, but the SLI group consistently scored significantly lower than the NL group. Overall, the NL group showed significantly better receptive vocabulary, with evidence that between-group differences increased at age 6. Neither short-term phonological memory nor receptive vocabulary predicted fast mapping comprehension or production performance, even though both have been shown to correlate with later stages of word learning.
Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

PubMed

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.
On Pedagogy

ERIC Educational Resources Information Center

Gergely, Gyorgy; Egyed, Katalin; Kiraly, Ildiko

2007-01-01

Humans are adapted to spontaneously transfer relevant cultural knowledge to conspecifics and to fast-learn the contents of such teaching through a human-specific social learning system called "pedagogy" ( Csibra & Gergely, 2006). Pedagogical knowledge transfer is triggered by specific communicative cues (such as eye-contact, contingent reactivity,…
Vocabulary Learning in a Yorkshire Terrier: Slow Mapping of Spoken Words

PubMed Central

Griebel, Ulrike; Oller, D. Kimbrough

2012-01-01

Rapid vocabulary learning in children has been attributed to “fast mapping”, with new words often claimed to be learned through a single presentation. As reported in 2004 in Science a border collie (Rico) not only learned to identify more than 200 words, but fast mapped the new words, remembering meanings after just one presentation. Our research tests the fast mapping interpretation of the Science paper based on Rico's results, while extending the demonstration of large vocabulary recognition to a lap dog. We tested a Yorkshire terrier (Bailey) with the same procedures as Rico, illustrating that Bailey accurately retrieved randomly selected toys from a set of 117 on voice command of the owner. Second we tested her retrieval based on two additional voices, one male, one female, with different accents that had never been involved in her training, again showing she was capable of recognition by voice command. Third, we did both exclusion-based training of new items (toys she had never seen before with names she had never heard before) embedded in a set of known items, with subsequent retention tests designed as in the Rico experiment. After Bailey succeeded on exclusion and retention tests, a crucial evaluation of true mapping tested items previously successfully retrieved in exclusion and retention, but now pitted against each other in a two-choice task. Bailey failed on the true mapping task repeatedly, illustrating that the claim of fast mapping in Rico had not been proven, because no true mapping task had ever been conducted with him. It appears that the task called retention in the Rico study only demonstrated success in retrieval by a process of extended exclusion. PMID:22363421
Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4. TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been
Teaching Power Electronics with a Design-Oriented, Project-Based Learning Method at the Technical University of Denmark

ERIC Educational Resources Information Center

Zhang, Zhe; Hansen, Claus Thorp; Andersen, Michael A. E.

2016-01-01

Power electronics is a fast-developing technology within the electrical engineering field. This paper presents the results and experiences gained from applying design-oriented project-based learning to switch-mode power supply design in a power electronics course at the Technical University of Denmark (DTU). Project-based learning (PBL) is known…
Lifelong Literacy: Some Trends and Issues in Conceptualising and Operationalising Literacy from a Lifelong Learning Perspective

ERIC Educational Resources Information Center

Hanemann, Ulrike

2015-01-01

In a fast-changing and highly inequitable world, lifelong learning is becoming increasingly important, not only as a key organising principle for all forms of education and learning but also as an absolute necessity for everyone. It is particularly important for disadvantaged individuals and groups who have been excluded from or failed to acquire…
Fast Back-Propagation Learning Using Steep Activation Functions and Automatic Weight

Treesearch

Tai-Hoon Cho; Richard W. Conners; Philip A. Araman

1992-01-01

In this paper, several back-propagation (BP) learning speed-up algorithms that employ the Ã£gainÃ¤ parameter, i.e., steepness of the activation function, are examined. Simulations will show that increasing the gain seemingly increases the speed of convergence and that these algorithms can converge faster than the standard BP learning algorithm on some problems. However,...
Learning in the Second Half of the Career: Stimulating and Prohibiting Reasons for Participation in Formal Learning Activities

ERIC Educational Resources Information Center

Kyndt, Eva; Michielsen, Maya; Van Nooten, Leen; Nijs, Sanne; Baert, Herman

2011-01-01

Past research has shown that, as workers age, their participation in education and training declines, which is a problem in our fast changing society and economy. This study focuses on the stimulating and prohibiting reasons for participation in formal learning activities. It investigates whether employees in the second half of their career differ…

There Is More to Digital Learning than Counting on Your Fingers: Transforming Learning and Teaching with Digital Pedagogy

ERIC Educational Resources Information Center

Smirnova, Lyudmila; Lazarevic , Bojan; Malloy, Veronica

2018-01-01

This paper explores how pedagogy is being influenced by fast developing digital technologies. Results are presented from exploratory research conducted in 2016. The findings are addressed in terms of the transformation of learning and education, including the move from the measured to the engaged classroom. Emerging technology creates a natural…
The Influence of Phonotactic Probability on Nonword Repetition and Fast Mapping in 3-Year-Olds With a History of Expressive Language Delay.

PubMed

MacRoy-Higgins, Michelle; Dalton, Kevin Patrick

2015-12-01

The purpose of this study was to examine the influence of phonotactic probability on sublexical (phonological) and lexical representations in 3-year-olds who had a history of being late talkers in comparison with their peers with typical language development. Ten 3-year-olds who were late talkers and 10 age-matched typically developing controls completed nonword repetition and fast mapping tasks; stimuli for both experimental procedures differed in phonotactic probability. Both participant groups repeated nonwords containing high phonotactic probability sequences more accurately than nonwords containing low phonotactic probability sequences. Participants with typical language showed an early advantage for fast mapping high phonotactic probability words; children who were late talkers required more exposures to the novel words to show the same advantage for fast mapping high phonotactic probability words. Children who were late talkers showed similar sensitivities to phonotactic probability in nonword repetition and word learning when compared with their peers with no history of language delay. However, word learning in children who were late talkers appeared to be slower when compared with their peers.
Amygdala kindling-resistant (SLOW) or -prone (FAST) rat strains show differential fear responses.

PubMed

Mohapel, P; McIntyre, D C

1998-12-01

The authors compared two rat strains, selectively bred for their susceptibility to amygdala kindling, with respect to their performance on various behavioral and learning tasks that are associated with fear and anxiety. The two rat strains differed significantly in measurements of exploration of novel and familiar environments, as well as in reactivity to footshock and fear-based learning. The kindling-resistant (SLOW) strain exhibited a lower ratio of open- to closed-arm entries in the elevated plus-maze, less activity over days in the open field, greater behavioral suppression in the open-field if previously footshocked, greater freezing in the inhibitory avoidance task, and slower acquisition and poorer retention in the one-way avoidance task than did the kindling-prone (FAST) strain. These experiments suggest that the SLOW rats are more expressively fearful than the FAST rats, particularly with respect to environmentally triggered freezing or immobility. Further, these observations imply that the relatively constrained excitability of the amygdala network in the SLOW rats might mediate their relatively greater expression of fear and anxiety compared with the FAST rats.
Effects of hand gestures on auditory learning of second-language vowel length contrasts.

PubMed

Hirata, Yukari; Kelly, Spencer D; Huang, Jessica; Manansala, Michael

2014-12-01

Research has shown that hand gestures affect comprehension and production of speech at semantic, syntactic, and pragmatic levels for both native language and second language (L2). This study investigated a relatively less explored question: Do hand gestures influence auditory learning of an L2 at the segmental phonology level? To examine auditory learning of phonemic vowel length contrasts in Japanese, 88 native English-speaking participants took an auditory test before and after one of the following 4 types of training in which they (a) observed an instructor in a video speaking Japanese words while she made syllabic-rhythm hand gesture, (b) produced this gesture with the instructor, (c) observed the instructor speaking those words and her moraic-rhythm hand gesture, or (d) produced the moraic-rhythm gesture with the instructor. All of the training types yielded similar auditory improvement in identifying vowel length contrast. However, observing the syllabic-rhythm hand gesture yielded the most balanced improvement between word-initial and word-final vowels and between slow and fast speaking rates. The overall effect of hand gesture on learning of segmental phonology is limited. Implications for theories of hand gesture are discussed in terms of the role it plays at different linguistic levels.
An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

PubMed Central

Potjans, Wiebke; Diesmann, Markus; Morrison, Abigail

2011-01-01

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards. PMID:21589888
A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine †

PubMed Central

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-01

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics. PMID:25599427
Fast learning of simple perceptual discriminations reduces brain activation in working memory and in high-level auditory regions.

PubMed

Daikhin, Luba; Ahissar, Merav

2015-07-01

Introducing simple stimulus regularities facilitates learning of both simple and complex tasks. This facilitation may reflect an implicit change in the strategies used to solve the task when successful predictions regarding incoming stimuli can be formed. We studied the modifications in brain activity associated with fast perceptual learning based on regularity detection. We administered a two-tone frequency discrimination task and measured brain activation (fMRI) under two conditions: with and without a repeated reference tone. Although participants could not explicitly tell the difference between these two conditions, the introduced regularity affected both performance and the pattern of brain activation. The "No-Reference" condition induced a larger activation in frontoparietal areas known to be part of the working memory network. However, only the condition with a reference showed fast learning, which was accompanied by a reduction of activity in two regions: the left intraparietal area, involved in stimulus retention, and the posterior superior-temporal area, involved in representing auditory regularities. We propose that this joint reduction reflects a reduction in the need for online storage of the compared tones. We further suggest that this change reflects an implicit strategic shift "backwards" from reliance mainly on working memory networks in the "No-Reference" condition to increased reliance on detected regularities stored in high-level auditory networks.
Fasting induces an anti-inflammatory effect on the neuroimmune system which a high-fat diet prevents.

PubMed

Lavin, Desiree N; Joesting, Jennifer J; Chiu, Gabriel S; Moon, Morgan L; Meng, Jia; Dilger, Ryan N; Freund, Gregory G

2011-08-01

The neuroimmunological and behavioral consequences of a high-fat diet (HFD) are not well delineated. This is especially true when short term (24 h) fasting is used as a physiologic stressor. In this study, we examined the impact of a HFD on learning and memory and depressive-like behaviors to understand how fasting impacts neuroimmunity and whether obesity modulates the response. Mice were fed diets containing either 10% (low-fat diet (LFD) mice) or 60% (HFD mice) calories from fat for 10-12 weeks. Gene transcripts for 26 pro-/anti-inflammatory cytokines and markers of macrophage activation were examined in adipose tissue and whole brain. Mouse learning and memory (spontaneous alternation, novel object) and depressive-like behaviors (saccharin preference, burrowing, forced swim) were studied in the fed and fasted state as were gene transcripts for F4/80, CD11b, interleukin-1α (IL-1α), IL-1β, IL-1R1, IL-1R2, IL-1RA, IL-6 and tumor necrosis factor-α in cortex, hippocampus and hypothalamus. In the fed state, HFD mice compared to LFD mice had reduced locomotor activity, and were adverse to saccharin and burrowed less. After fasting, LFD mice vs. HFD mice lost 18 vs. 5% of their body weight, respectively. In addition, HFD mice failed to downregulate gene transcripts for the myeloid-cell associated proteins F4/80, CD11b and IL-1α in the brain, failed to appropriately explore a novel object, failed to reduce locomotor activity and had increased saccharin consumption and burrowing. These data indicate that fasting induces an anti-inflammatory effect on the neuroimmune system which a HFD prevents. This breakdown appears linked to the IL-1 system because of the association of this cytokine with memory and learning.
Novel word retention in bilingual and monolingual speakers

PubMed Central

Kan, Pui Fong; Sadagopan, Neeraja

2014-01-01

The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan et al., 2014), the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals' fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals' fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals' retention scores. However, no such correlations were found among monolinguals' retention scores. The overall findings suggest that bilinguals' language experience and language knowledge most likely contribute to how they learn and retain new words. PMID:25324789
Novel word retention in bilingual and monolingual speakers.

PubMed

Kan, Pui Fong; Sadagopan, Neeraja

2014-01-01

The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan et al., 2014), the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals' fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals' fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals' retention scores. However, no such correlations were found among monolinguals' retention scores. The overall findings suggest that bilinguals' language experience and language knowledge most likely contribute to how they learn and retain new words.
Learning to assign binary weights to binary descriptor

NASA Astrophysics Data System (ADS)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.
Fast, Affordable, Science and Technology Satellite (FASTSAT) Huntsville-01 (HSV-01) Spacecraft Lessons Learned Report

NASA Technical Reports Server (NTRS)

Smith, Timothy A.

2012-01-01

The Fast Affordable Science and Technology Satellite (FASTSAT) project is a path finding effort to produce reliable satellite busses for different applications at an unprecedented speed and low cost. The project is designed to be a generational project and the first satellite produced is the Huntsville -01 (HSV-01) spacecraft. The subject of this report is the lessons learned gained during the development, testing, and up to the delivery of the FASTSAT HSV -01 spacecraft. The purpose of this report is to capture the major findings that will greatly benefit the future FASTSAT satellites and perhaps other projects interested in pushing the boundaries for cost and schedule. The FASTSAT HSV -01 primary objectives, success criteria, and team partners are summarized to give a frame of reference to the lessons learned.
Effect of donor fasting on survival of pancreas and heart grafts after warm ischemia.

PubMed

Nishihara, M; Sumimoto, R; Asahara, T; Fukuda, Y; Southard, J H; Dohi, K

1996-09-01

Livers from fasted animals are believed to be more vulnerable to ischemic injury than those from fed donors. However, we have recently shown the opposite: livers from fasted rats were more tolerant to ischemic injury. Indeed, the survival rate of 60 min warm ischemic damaged livers increased from 0 to 90% if donor rats were fasted for three days. In this study, we examined how donor fasting affects the outcome of pancreas and heart preservation. BN rats were used as both donors and recipients, and recipients of pancreatic grafts were rendered diabetic prior to transplantation. Pancreatic or heart grafts were subjected to 90 min or 25 min of warm ischemia and were transplanted into the right side of the necks of recipients rats. The viability rate of hearts transplanted from fed donors into fed recipients was only about 11% (1/9) after transplantation. However, the viability rate with fasted donors was 75% (6/8). The rate of successful pancreatic grafting from fed donors into fed recipients was 28.6% (2/7), and that from fasted donors to fed recipients was 41.7% (5/12). These results confirm that the nutritional status of the donor is an important factor in the outcome of not only liver, but also pancreas and heart preservation during transplantation, although the effect of fasting on pancreatic graft is marginal.
Satellite Ground Operations Automation: Lessons Learned and Future Approaches

NASA Technical Reports Server (NTRS)

Catena, John; Frank, Lou; Saylor, Rick; Weikel, Craig; Obenschain, Arthur F. (Technical Monitor)

2001-01-01

Reducing spacecraft ground system operations costs is a major goal in all missions. The Fast Auroral Snapshot (FAST) flight operations team at the NASA/Goddard Spacecraft Flight Center developed in-house scripts and procedures to automate monitoring of critical spacecraft functions. The initial staffing profile of 16x7 was reduced first to 8x5 and then to 'lights out'. Operations functions became an offline review of system performance and the generation of future science plans for subsequent upload to the spacecraft. Lessons learned will be applied to the challenging Triana mission, where 24x7 contact with the spacecraft will be necessary at all times.
Filopodia: A Rapid Structural Plasticity Substrate for Fast Learning

PubMed Central

Ozcan, Ahmet S.

2017-01-01

Formation of new synapses between neurons is an essential mechanism for learning and encoding memories. The vast majority of excitatory synapses occur on dendritic spines, therefore, the growth dynamics of spines is strongly related to the plasticity timescales. Especially in the early stages of the developing brain, there is an abundant number of long, thin and motile protrusions (i.e., filopodia), which develop in timescales of seconds and minutes. Because of their unique morphology and motility, it has been suggested that filopodia can have a dual role in both spinogenesis and environmental sampling of potential axonal partners. I propose that filopodia can lower the threshold and reduce the time to form new dendritic spines and synapses, providing a substrate for fast learning. Based on this proposition, the functional role of filopodia during brain development is discussed in relation to learning and memory. Specifically, it is hypothesized that the postnatal brain starts with a single-stage memory system with filopodia playing a significant role in rapid structural plasticity along with the stability provided by the mushroom-shaped spines. Following the maturation of the hippocampus, this highly-plastic unitary system transitions to a two-stage memory system, which consists of a plastic temporary store and a long-term stable store. In alignment with these architectural changes, it is posited that after brain maturation, filopodia-based structural plasticity will be preserved in specific areas, which are involved in fast learning (e.g., hippocampus in relation to episodic memory). These propositions aim to introduce a unifying framework for a diversity of phenomena in the brain such as synaptogenesis, pruning and memory consolidation. PMID:28676753
Sleep Spindles in the Right Hemisphere Support Awareness of Regularities and Reflect Pre-Sleep Activations.

PubMed

Yordanova, Juliana; Kolev, Vasil; Bruns, Eike; Kirov, Roumen; Verleger, Rolf

2017-11-01

The present study explored the sleep mechanisms which may support awareness of hidden regularities. Before sleep, 53 participants learned implicitly a lateralized variant of the serial response-time task in order to localize sensorimotor encoding either in the left or right hemisphere and induce implicit regularity representations. Electroencephalographic (EEG) activity was recorded at multiple electrodes during both task performance and sleep, searching for lateralized traces of the preceding activity during learning. Sleep EEG analysis focused on region-specific slow (9-12 Hz) and fast (13-16 Hz) sleep spindles during nonrapid eye movement sleep. Fast spindle activity at those motor regions that were activated during learning increased with the amount of postsleep awareness. Independently of side of learning, spindle activity at right frontal and fronto-central regions was involved: there, fast spindles increased with the transformation of sequence knowledge from implicit before sleep to explicit after sleep, and slow spindles correlated with individual abilities of gaining awareness. These local modulations of sleep spindles corresponded to regions with greater presleep activation in participants with postsleep explicit knowledge. Sleep spindle mechanisms are related to explicit awareness (1) by tracing the activation of motor cortical and right-hemisphere regions which had stronger involvement already during learning and (2) by recruitment of individually consolidated processing modules in the right hemisphere. The integration of different sleep spindle mechanisms with functional states during wake collectively supports the gain of awareness of previously experienced regularities, with a special role for the right hemisphere. © Sleep Research Society 2017. Published by Oxford University Press [on behalf of the Sleep Research Society].
Recovery Systems Design Guide

DTIC Science & Technology

1978-12-01

analysis. retrieval parachute concepts are being investigated. The development of recovery systems for fast flying, possible out-of-control missiles proved...system. 21 •, . , r, _ . .. , . " , , . : . .. . " . , ,- Reference 32 suggests certain applications (speed/ Fast Opening. An emergency escape...operation, physiological aspect of flying and escape. fast parachute opening., Low Rate of Descent. A sea level rate of descent low parachute opening
Not Only Size Matters: Early-Talker and Late-Talker Vocabularies Support Different Word-Learning Biases in Babies and Networks

ERIC Educational Resources Information Center

Colunga, Eliana; Sims, Clare E.

2017-01-01

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named--they have word-learning biases. This is not the case for children with relatively small vocabularies ("late…
Learning speed is affected by personality and reproductive investment in a songbird

PubMed Central

Martens, Tine; Pinxten, Rianne; Eens, Marcel

2017-01-01

Individuals from different taxa, including songbirds, differ consistently in behaviour and personality when facing different situations. Although our understanding of animal behaviour has increased, knowledge about between-individual differences in cognitive abilities is still limited. By using an experimental approach and a free-living songbird (Parus major) as a model, we attempted to understand between-individual differences in habituation to playbacks (as a proxy of learning speed), by investigating the role of personality, age and reproductive investment (clutch size). Pre-breeding males were tested for exploration (a proxy of personality) in standardized conditions. In addition, the same individuals were exposed to three playbacks in the field during incubation. Birds significantly moved less, stayed further away and overlapped less the playback with successive playback stimulation. While a decrease in the locomotor behaviour can be explained by personality, differences in habituation of overlapping were predicted by both reproductive investment and personality. Fast explorers habituated less. Moreover, males paired to females with larger clutches did not vary the intensity of overlapping. Since habituation requires information for recognition of non-threatening signals, personality may bias information gathering. While fast explorers may collect less information from the environment, slow explorers (reactive birds) seem to pay attention to environmental clues and collect detailed information. We provided evidence that the rate of habituation of behavioural responses, a proxy of cognitive abilities, may be affected by different factors and in a complex way. PMID:29020028
Fast Mapping in Healthy Young Adults: The Influence of Metamemory

ERIC Educational Resources Information Center

Ramachandra, Vijayachandra; Rickenbach, Bryna; Ruda, Marissa; LeCureux, Bethanie; Pope, Moira

2010-01-01

Several research studies suggest the significant role played by metamemory in lexical abilities of both adults and children. To our knowledge, there have been no studies to date that have explored the role of metamemory (Judgments of Learning) in fast mapping of novel words by adults. One hundred and twelve undergraduate students were given tasks…

Fast Track Initiative: Building a Global Compact for Education. Education Notes

ERIC Educational Resources Information Center

Human Development Network Education, 2005

2005-01-01

This note series is intended to summarize lessons learned and key policy findings on the World Bank's work in education. "Fast Track Initiative" ("FTI") was launched in 2002 as a partnership between donor and developing countries to accelerate progress towards the Millennium Development Goal (MDG) of universal primary education. "FTI" is built on…
Fast ForWord[R]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2010

2010-01-01

"Fast ForWord"[R] is a computer-based reading program intended to help students develop and strengthen the cognitive skills necessary for successful reading and learning. The program, which is designed to be used 30 to 100 minutes a day, five days a week, for 4 to 16 weeks, includes two components. The first component aims to build…
Fast-Mapping and Deliberate Word-Learning by EFL Children

ERIC Educational Resources Information Center

Hu, Chieh-Fang

2012-01-01

This study examined the abilities of young English as a foreign language (EFL) learners to identify quickly new words from a nonostensive, indirect teaching context (known as fast- mapping) and their ability to commit the words to memory. Seventy-five fourth-grade EFL learners heard novel words embedded in sentences. They were then tested for…
Constructing a "Fast Protocol" for Middle School Beginner Violin Classes in Japan

ERIC Educational Resources Information Center

Akutsu, Taichi

2018-01-01

This study aimed to investigate the process of constructing a "fast-protocol" for violin instruction. Since learning string instruments has not been common, and because there are limited hours for music in Japanese schools, the author, a violinist, collaborated with the general music teacher at a middle school in the Tokyo metropolitan…
Physical characterization of fast rotator NEOs

NASA Astrophysics Data System (ADS)

Kikwaya Eluo, Jean-Baptiste; Hergenrother, Carl W.

2015-08-01

Understanding the physical characteristics of fast rotator NEOs (sub-km sizes with H > 22) is important for two reasons: to establish properties that can constraint models of their potential hazard, and to learn about the origin and the evolution of the solar system. Technically it is difficult to cover different ranges of wavelengths using one telescope with one instrument. Setting up a network of telescopes with different instruments observing simultaneously the same object will efficiently contribute to the characterization of NEOs.ART (Arizona Robotic Telescope) is a University of Arizona initiative whose goal is to use local 2-m size telescopes to provide near real-time observations of Target of Opportunity objects covering the visible and the near- infrared wavelengths. We plan to use three telescopes of the ART project to observe fast rotator NEOs: 1) VATT (Vatican Advanced Technology Telescope) at Mount Graham (longitude: -109.8719, latitude: 32.7016, elevation: 10469 feet) with VATT-4K optical imager for photometry to estimate colors, lightcurves to get the rotation rate, and estimate the phase angle function of NEOs, 2) Bok 2.3 m at Kitt Peak (longitude: -111.6004, latitude: 31.9629, elevation: 6795 feet) with BCSpec (Boller & Chivens Spectrograph) for visible spectroscopy, and 3) Kuiper 1.5-m at Mount Bigelow (longitude: -110.7345, latitude: 32.4165, elevation: 8235 feet) with a near-infrared instrument.We report here the preliminary results of several NEOs whose rotation rate, color, and type have been estimated using photometry with images recorded with VATT-4K. 2009 SQ104 has a rotation rate of 6.85+/- 0.03 h, 2014 AY28 has a rotation rate of 0.91 +/- 0.02 h, 2014 EC of 0.54 +/-0.04 h, 2014 FA44 of 3.45 +/- 0.05 h, 2014 KS40 of 1.11 +/- 0.06 h, 2011 PT of 0.17 +/- 0.05 h, 2014 SC324 of 0.36 +/- 0.43 h, 2014 WF201 of 1.00 +/- 0.03 h. Of these objects, 2014 HM2, 2014 FA, 2014 SB145, 2011 PT fall among X-type asteroids; 2014 KS, 2014 WF are likely to be C-type; and 2014 SC 324 is a D-type.
Health beliefs and practices of Muslim women during Ramadan.

PubMed

Kridli, Suha Al-Oballi

2011-01-01

There are clear exemptions in Islam from fasting in Ramadan during sickness, pregnancy, and breastfeeding. Yet, some Muslim women still elect to fast while sick, pregnant, or breastfeeding because of a confluence of social, religious, and cultural factors. Little is known about the physiological effects of fasting during Ramadan on the mother or her unborn baby, and thus nurses and other healthcare providers are faced with the difficult task of providing appropriate medical advice to Muslim women regarding the safety and impact of their fasting. This article describes what is known about this topic and suggests that healthcare professionals learn as much as possible about the multicultural best practices and research-driven information about fasting in order to help Muslim women make informed decisions.
Fast machine-learning online optimization of ultra-cold-atom experiments.

PubMed

Wigley, P B; Everitt, P J; van den Hengel, A; Bastian, J W; Sooriyabandara, M A; McDonald, G D; Hardman, K S; Quinlivan, C D; Manju, P; Kuhn, C C N; Petersen, I R; Luiten, A N; Hope, J J; Robins, N P; Hush, M R

2016-05-16

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our 'learner' discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system.
Fast machine-learning online optimization of ultra-cold-atom experiments

PubMed Central

Wigley, P. B.; Everitt, P. J.; van den Hengel, A.; Bastian, J. W.; Sooriyabandara, M. A.; McDonald, G. D.; Hardman, K. S.; Quinlivan, C. D.; Manju, P.; Kuhn, C. C. N.; Petersen, I. R.; Luiten, A. N.; Hope, J. J.; Robins, N. P.; Hush, M. R.

2016-01-01

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ‘learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. PMID:27180805
The effect of fast-food restaurants on childhood obesity: a school level analysis.

PubMed

Alviola, Pedro A; Nayga, Rodolfo M; Thomsen, Michael R; Danforth, Diana; Smartt, James

2014-01-01

We analyze, using an instrumental variable approach, the effect of the number of fast-food restaurants on school level obesity rates in Arkansas. Using distance to the nearest major highway as an instrument, our results suggest that exposure to fast-food restaurants can impact weight outcomes. Specifically, we find that the number of fast-food restaurants within a mile from the school can significantly affect school level obesity rates. Copyright © 2013 Elsevier B.V. All rights reserved.
Predictive Chemical and Statistical Modeling of Particulate Matter Formation in Turbulent Combustion with Application to Aircraft Engines

DTIC Science & Technology

2012-03-01

the reactant. faster than phenanthrene II, whereas the latter decomposes about as fast as phenanthrene III. The correlation of these rates with the...the spreading rate of the jet at the first station near the nozzle is slightly too fast . Second, at the two downstream stations, the centerline...In previous RANS studies [93–96], the same two discrepancies are observed, that is, an initial jet spreading rate that is too fast and an
The effect of a 48 h fast on the thermoregulatory responses to graded cooling in man.

PubMed

Macdonald, I A; Bennett, T; Sainsbury, R

1984-10-01

The thermoregulatory responses to graded cooling were measured in 11 healthy male subjects after a 12 h fast and after a 48 h fast. The cooling stimulus was produced by changing the temperature of the skin of the trunk and legs with a water-perfused suit. Five levels of skin temperature from 35.5 to 24 degrees C were applied on each occasion. After a 12 h fast, core temperature was maintained during cooling. This maintenance of core temperature was associated with an increase in metabolic rate and a reduction in blood flow to the hand and to the forearm. After 48 h of fasting, the subjects could not maintain core temperature during cooling, and a decrease of 0.36 +/- 0.05 degrees C occurred as the suit temperature was reduced from 35.9 to 24 degrees C. Metabolic rate was slightly higher after the 48 h fast than after the 12 h fast, but similar increases in metabolic rate were observed during cooling. Vasoconstriction in the hand was initially less after a 48 h fast than after a 12 h fast, but at the lowest suit temperature, hand blood flow was similar, and low, on both occasions. After 48 h of fasting, forearm blood flow was elevated at all suit temperatures, being approximately twice the level recorded after the 12 h fast. Venous plasma noradrenaline levels did not change during cooling after the 12 h fast, whilst after 48 h of fasting a significant increase in noradrenaline level was observed at the lowest suit temperature. The results of this study provide further evidence that fasting induces an impairment of autonomic reflex mechanisms, but it is not clear whether this is due to a suppression of sympathetic nervous activity.
Skill (or lack thereof) of data-model fusion techniques to provide an early warning signal for an approaching tipping point.

PubMed

Singh, Riddhi; Quinn, Julianne D; Reed, Patrick M; Keller, Klaus

2018-01-01

Many coupled human-natural systems have the potential to exhibit a highly nonlinear threshold response to external forcings resulting in fast transitions to undesirable states (such as eutrophication in a lake). Often, there are considerable uncertainties that make identifying the threshold challenging. Thus, rapid learning is critical for guiding management actions to avoid abrupt transitions. Here, we adopt the shallow lake problem as a test case to compare the performance of four common data assimilation schemes to predict an approaching transition. In order to demonstrate the complex interactions between management strategies and the ability of the data assimilation schemes to predict eutrophication, we also analyze our results across two different management strategies governing phosphorus emissions into the shallow lake. The compared data assimilation schemes are: ensemble Kalman filtering (EnKF), particle filtering (PF), pre-calibration (PC), and Markov Chain Monte Carlo (MCMC) estimation. While differing in their core assumptions, each data assimilation scheme is based on Bayes' theorem and updates prior beliefs about a system based on new information. For large computational investments, EnKF, PF and MCMC show similar skill in capturing the observed phosphorus in the lake (measured as expected root mean squared prediction error). EnKF, followed by PF, displays the highest learning rates at low computational cost, thus providing a more reliable signal of an impending transition. MCMC approaches the true probability of eutrophication only after a strong signal of an impending transition emerges from the observations. Overall, we find that learning rates are greatest near regions of abrupt transitions, posing a challenge to early learning and preemptive management of systems with such abrupt transitions.
Skill (or lack thereof) of data-model fusion techniques to provide an early warning signal for an approaching tipping point

PubMed Central

Quinn, Julianne D.; Reed, Patrick M.; Keller, Klaus

2018-01-01

Many coupled human-natural systems have the potential to exhibit a highly nonlinear threshold response to external forcings resulting in fast transitions to undesirable states (such as eutrophication in a lake). Often, there are considerable uncertainties that make identifying the threshold challenging. Thus, rapid learning is critical for guiding management actions to avoid abrupt transitions. Here, we adopt the shallow lake problem as a test case to compare the performance of four common data assimilation schemes to predict an approaching transition. In order to demonstrate the complex interactions between management strategies and the ability of the data assimilation schemes to predict eutrophication, we also analyze our results across two different management strategies governing phosphorus emissions into the shallow lake. The compared data assimilation schemes are: ensemble Kalman filtering (EnKF), particle filtering (PF), pre-calibration (PC), and Markov Chain Monte Carlo (MCMC) estimation. While differing in their core assumptions, each data assimilation scheme is based on Bayes’ theorem and updates prior beliefs about a system based on new information. For large computational investments, EnKF, PF and MCMC show similar skill in capturing the observed phosphorus in the lake (measured as expected root mean squared prediction error). EnKF, followed by PF, displays the highest learning rates at low computational cost, thus providing a more reliable signal of an impending transition. MCMC approaches the true probability of eutrophication only after a strong signal of an impending transition emerges from the observations. Overall, we find that learning rates are greatest near regions of abrupt transitions, posing a challenge to early learning and preemptive management of systems with such abrupt transitions. PMID:29389938
Age Differences in Memory Retrieval Shift: Governed by Feeling-of-Knowing?

PubMed Central

Hertzog, Christopher; Touron, Dayna R.

2010-01-01

The noun-pair lookup (NP) task was used to evaluate strategic shift from visual scanning to retrieval. We investigated whether age differences in feeling-of-knowing (FOK) account for older adults' delayed retrieval shift. Participants were randomly assigned to one of three conditions: (1) standard NP learning, (2) fast binary FOK judgments, or (3) Choice, where participants had to choose in advance whether to see the look-up table or respond from memory. We found small age differences in FOK magnitudes, but major age differences in memory retrieval choices that mirrored retrieval use in the standard NP task. Older adults showed lower resolution in their confidence judgments (CJs) for recognition memory tests on the NP items, and this difference appeared to influence rates of retrieval shift, given that retrieval use was correlated with CJ magnitudes in both age groups. Older adults had particular difficulty with accuracy and confidence for rearranged pairs, relative to intact pairs. Older adults' slowed retrieval shift appears to be due to (a) impaired associative learning early in practice, not just a lower FOK; but also (b) retrieval reluctance later in practice after the degree of associative learning would afford memory-based responding. PMID:21401263
Computer-based auditory training (CBAT): benefits for children with language- and reading-related learning difficulties.

PubMed

Loo, Jenny Hooi Yin; Bamiou, Doris-Eva; Campbell, Nicci; Luxon, Linda M

2010-08-01

This article reviews the evidence for computer-based auditory training (CBAT) in children with language, reading, and related learning difficulties, and evaluates the extent it can benefit children with auditory processing disorder (APD). Searches were confined to studies published between 2000 and 2008, and they are rated according to the level of evidence hierarchy proposed by the American Speech-Language Hearing Association (ASHA) in 2004. We identified 16 studies of two commercially available CBAT programs (13 studies of Fast ForWord (FFW) and three studies of Earobics) and five further outcome studies of other non-speech and simple speech sounds training, available for children with language, learning, and reading difficulties. The results suggest that, apart from the phonological awareness skills, the FFW and Earobics programs seem to have little effect on the language, spelling, and reading skills of children. Non-speech and simple speech sounds training may be effective in improving children's reading skills, but only if it is delivered by an audio-visual method. There is some initial evidence to suggest that CBAT may be of benefit for children with APD. Further research is necessary, however, to substantiate these preliminary findings.
Motor Variability Arises from a Slow Random Walk in Neural State

PubMed Central

Chaisanguanthum, Kris S.; Shen, Helen H.

2014-01-01

Even well practiced movements cannot be repeated without variability. This variability is thought to reflect “noise” in movement preparation or execution. However, we show that, for both professional baseball pitchers and macaque monkeys making reaching movements, motor variability can be decomposed into two statistical components, a slowly drifting mean and fast trial-by-trial fluctuations about the mean. The preparatory activity of dorsal premotor cortex/primary motor cortex neurons in monkey exhibits similar statistics. Although the neural and behavioral drifts appear to be correlated, neural activity does not account for trial-by-trial fluctuations in movement, which must arise elsewhere, likely downstream. The statistics of this drift are well modeled by a double-exponential autocorrelation function, with time constants similar across the neural and behavioral drifts in two monkeys, as well as the drifts observed in baseball pitching. These time constants can be explained by an error-corrective learning processes and agree with learning rates measured directly in previous experiments. Together, these results suggest that the central contributions to movement variability are not simply trial-by-trial fluctuations but are rather the result of longer-timescale processes that may arise from motor learning. PMID:25186752
The effect of learning on feedback-related potentials in adolescents with dyslexia: an EEG-ERP study.

PubMed

Kraus, Dror; Horowitz-Kraus, Tzipi

2014-01-01

Individuals with dyslexia exhibit associated learning deficits and impaired executive functions. The Wisconsin Card Sorting Test (WCST) is a learning-based task that relies heavily on executive functioning, in particular, attention shift and working memory. Performance during early and late phases of a series within the task represents learning and implementation of a newly learned rule. Here, we aimed to examine two event-related potentials associated with learning, feedback-related negativity (FRN)-P300 complex, in individuals with dyslexia performing the WCST. Adolescents with dyslexia and age-matched typical readers performed the Madrid card sorting test (MCST), a computerized version of the WCST. Task performance, reading measures, and cognitive measures were collected. FRN and the P300 complex were acquired using the event-related potentials methodology and were compared in early vs late errors within a series. While performing the MCST, both groups showed a significant reduction in average reaction times and a trend toward decreased error rates. Typical readers performed consistently better than individuals with dyslexia. FRN amplitudes in early phases were significantly smaller in dyslexic readers, but were essentially equivalent to typical readers in the late phase. P300 amplitudes were initially smaller among readers with dyslexia and tended to decrease further in late phases. Differences in FRN amplitudes for early vs late phases were positively correlated with those of P300 amplitudes in the entire sample. Individuals with dyslexia demonstrate a behavioral and electrophysiological change within single series of the MCST. However, learning patterns seem to differ between individuals with dyslexia and typical readers. We attribute these differences to the lower baseline performance of individuals with dyslexia. We suggest that these changes represent a fast compensatory mechanism, demonstrating the importance of learning strategies on reading among individuals with dyslexia.
Word learning emerges from the interaction of online referent selection and slow associative learning.

PubMed

McMurray, Bob; Horst, Jessica S; Samuelson, Larissa K

2012-10-01

Classic approaches to word learning emphasize referential ambiguity: In naming situations, a novel word could refer to many possible objects, properties, actions, and so forth. To solve this, researchers have posited constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative in which referent selection is an online process and independent of long-term learning. We illustrate this theoretical approach with a dynamic associative model in which referent selection emerges from real-time competition between referents and learning is associative (Hebbian). This model accounts for a range of findings including the differences in expressive and receptive vocabulary, cross-situational learning under high degrees of ambiguity, accelerating (vocabulary explosion) and decelerating (power law) learning, fast mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between speed of processing and learning. Together it suggests that (a) association learning buttressed by dynamic competition can account for much of the literature; (b) familiar word recognition is subserved by the same processes that identify the referents of novel words (fast mapping); (c) online competition may allow the children to leverage information available in the task to augment performance despite slow learning; (d) in complex systems, associative learning is highly multifaceted; and (e) learning and referent selection, though logically distinct, can be subtly related. It suggests more sophisticated ways of describing the interaction between situation- and developmental-time processes and points to the need for considering such interactions as a primary determinant of development. PsycINFO Database Record (c) 2012 APA, all rights reserved.
A Review of the Growth of the Fast Food Industry in China and Its Potential Impact on Obesity.

PubMed

Wang, Youfa; Wang, Liang; Xue, Hong; Qu, Weidong

2016-11-09

The fast-food (FF) industry and obesity rates have rapidly increased in China. This study examined the FF industry growth in China, key factors contributing to the growth, and the association between FF consumption (FFC) and obesity. We collected related data from multiple sources and conducted analysis including linear regression analysis on the increase in FF revenue. It was found that FF industry in China is large, with over two million FF facilities. Its total revenue (in million US$) increased from 10,464 in 1999 to 94,218 in 2013, and by 13% annually since 2008. Increased income, urbanization, busier lifestyle, speedy FF service, assurance of food safety, new brands and foods have stimulated demand for FF. Studies have linked FFC with obesity risk, including a few reporting a positive association between FFC and obesity in China. Rapid expansion of Western-style FF restaurants has also stimulated local FF industry growth. Government regulation and public health education need to address the health consequences of rapidly increasing FFC. Lessons learned in China will help other countries.
A Review of the Growth of the Fast Food Industry in China and Its Potential Impact on Obesity

PubMed Central

Wang, Youfa; Wang, Liang; Xue, Hong; Qu, Weidong

2016-01-01

The fast-food (FF) industry and obesity rates have rapidly increased in China. This study examined the FF industry growth in China, key factors contributing to the growth, and the association between FF consumption (FFC) and obesity. We collected related data from multiple sources and conducted analysis including linear regression analysis on the increase in FF revenue. It was found that FF industry in China is large, with over two million FF facilities. Its total revenue (in million US$) increased from 10,464 in 1999 to 94,218 in 2013, and by 13% annually since 2008. Increased income, urbanization, busier lifestyle, speedy FF service, assurance of food safety, new brands and foods have stimulated demand for FF. Studies have linked FFC with obesity risk, including a few reporting a positive association between FFC and obesity in China. Rapid expansion of Western-style FF restaurants has also stimulated local FF industry growth. Government regulation and public health education need to address the health consequences of rapidly increasing FFC. Lessons learned in China will help other countries. PMID:27834887

The Development of the E-Learning Course "Sociology"

ERIC Educational Resources Information Center

Aleksic-Maslac, Karmela; Magzan, Masa; Maslac, Ilena

2008-01-01

The fast development of information and communication technologies (ICT) improves greatly education quality. E-learning is an important education component at Zagreb School of Economics and Management (ZSEM) and, in addition, it is obligatory for all our teachers and students. In this paper, the development process of course "Sociology"…
Learning Objects Metadata and Tools in the Area of Operations Research.

ERIC Educational Resources Information Center

Kassanke, Stephan; El-Saddik, Abdulmotaleb; Steinacker, Achim

Information technology and the Internet are making inroads into almost all areas of society. The requirements of students and professionals are fast changing, and the information society requires lifelong learning in practically all areas, especially those related to information technologies. The educational sector can profit in particular from…
Conceptualizing an M-Learning System for Seniors

ERIC Educational Resources Information Center

Teine, Matthias; Beutner, Marc

2016-01-01

In accelerating fast changing knowledge-based and information societies such like the European Union technology dominates most facets of our everyday lives, and learning activities as well. Unfortunately, particularly seniors and elderly people suffer the risk to be left behind, and that the digital divide becomes bigger. This is problematic…
Characteristics of Context for Instructional Design

ERIC Educational Resources Information Center

Hansen, Brett E.

2010-01-01

The fast-paced and continual change experienced in the workplace requires graduates to possess knowledge that can immediately transfer to their chosen profession so that they can quickly become productive and successful. Learning in context is known to have positive effects on learning and facilitate the transfer of knowledge from learning…
Leadership in Multiplayer Online Gaming Environments

ERIC Educational Resources Information Center

Lisk, Timothy C.; Kaplancali, Ugur T.; Riggio, Ronald E.

2012-01-01

With their increased popularity, games open up possibilities for simultaneous learning on multiple levels; players may learn from contextual information embedded in the narrative of the game and through the risks, benefits, costs, outcomes, and rewards of the alternative strategies that result from fast-paced decision making. Such dynamics also…
Orthographic Learning in Dyslexic Spanish Children

ERIC Educational Resources Information Center

Suárez-Coalla, Paz; Ramos, Sara; Álvarez-Cañizo, Marta; Cuetos, Fernando

2014-01-01

Reading fluency is one of the basic processes of learning to read. Children begin to develop fluency when they are able to form orthographic representations of words, which provide direct, smooth, and fast reading. Dyslexic children of transparent orthographic systems are mainly characterized by poor reading fluency (Cuetos & Suárez-Coalla…
Comparison between extreme learning machine and wavelet neural networks in data classification

NASA Astrophysics Data System (ADS)

Yahia, Siwar; Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

2017-03-01

Extreme learning Machine is a well known learning algorithm in the field of machine learning. It's about a feed forward neural network with a single-hidden layer. It is an extremely fast learning algorithm with good generalization performance. In this paper, we aim to compare the Extreme learning Machine with wavelet neural networks, which is a very used algorithm. We have used six benchmark data sets to evaluate each technique. These datasets Including Wisconsin Breast Cancer, Glass Identification, Ionosphere, Pima Indians Diabetes, Wine Recognition and Iris Plant. Experimental results have shown that both extreme learning machine and wavelet neural networks have reached good results.
Fast reversible learning based on neurons functioning as anisotropic multiplex hubs

NASA Astrophysics Data System (ADS)

Vardi, Roni; Goldental, Amir; Sheinin, Anton; Sardi, Shira; Kanter, Ido

2017-05-01

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like independent anisotropic multiplex hubs, which relay and mute incoming signals following their input directions. Theoretically, the observed information routing enriches the computational capabilities of neurons by allowing, for instance, equalization among different information routes in the network, as well as high-frequency transmission of complex time-dependent signals constructed via several parallel routes. In addition, this kind of hubs adaptively eliminate very noisy neurons from the dynamics of the network, preventing masking of information transmission. The timescales for these features are several seconds at most, as opposed to the imprint of information by the synaptic plasticity, a process which exceeds minutes. Results open the horizon to the understanding of fast and adaptive learning realities in higher cognitive brain's functionalities.
Motivated Strategies for Learning in Accelerated Second-Degree Nursing Students.

PubMed

El-Banna, Majeda M; Tebbenhoff, Billinda; Whitlow, Malinda; Wyche, Karen Fraser

Students in a second-degree accelerated BSN program experience a rigorous curriculum and fast-paced introduction to the nursing profession. This study examined the relationships among self-esteem, motivation, learning strategies, demographic characteristics, and academic achievement. The results indicated that all of the students had good self-esteem; some demographic characteristics influenced the type of motivation and learning strategies they endorsed but did not influence their current academic performance.
The Complete Guide to Service Learning: Proven, Practical Ways to Engage Students in Civic Responsibility, Academic Curriculum, & Social Action. Revised & Updated Second Edition

ERIC Educational Resources Information Center

Kaye, Cathryn Berger

2010-01-01

"The Complete Guide to Service Learning" is the go-to resource in the fast-growing field of service learning. It is an award-winning treasury of service activities, community service project ideas, quotes, reflections, and resources that can help teachers and youth workers engage young hearts and minds in reaching out and giving back. Author, and…
ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any
Multiple systems for motor skill learning.

PubMed

Clark, Dav; Ivry, Richard B

2010-07-01

Motor learning is a ubiquitous feature of human competence. This review focuses on two particular classes of model tasks for studying skill acquisition. The serial reaction time (SRT) task is used to probe how people learn sequences of actions, while adaptation in the context of visuomotor or force field perturbations serves to illustrate how preexisting movements are recalibrated in novel environments. These tasks highlight important issues regarding the representational changes that occur during the course of motor learning. One important theme is that distinct mechanisms vary in their information processing costs during learning and performance. Fast learning processes may require few trials to produce large changes in performance but impose demands on cognitive resources. Slower processes are limited in their ability to integrate complex information but minimally demanding in terms of attention or processing resources. The representations derived from fast systems may be accessible to conscious processing and provide a relatively greater measure of flexibility, while the representations derived from slower systems are more inflexible and automatic in their behavior. In exploring these issues, we focus on how multiple neural systems may interact and compete during the acquisition and consolidation of new behaviors. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Motor Skill and Performance. Copyright © 2010 John Wiley & Sons, Ltd.
Selected regulation of gastrointestinal acid-base secretion and tissue metabolism for the diamondback water snake and Burmese python.

PubMed

Secor, Stephen M; Taylor, Josi R; Grosell, Martin

2012-01-01

Snakes exhibit an apparent dichotomy in the regulation of gastrointestinal (GI) performance with feeding and fasting; frequently feeding species modestly regulate intestinal function whereas infrequently feeding species rapidly upregulate and downregulate intestinal function with the start and completion of each meal, respectively. The downregulatory response with fasting for infrequently feeding snakes is hypothesized to be a selective attribute that reduces energy expenditure between meals. To ascertain the links between feeding habit, whole-animal metabolism, and GI function and metabolism, we measured preprandial and postprandial metabolic rates and gastric and intestinal acid-base secretion, epithelial conductance and oxygen consumption for the frequently feeding diamondback water snake (Nerodia rhombifer) and the infrequently feeding Burmese python (Python molurus). Independent of body mass, Burmese pythons possess a significantly lower standard metabolic rate and respond to feeding with a much larger metabolic response compared with water snakes. While fasting, pythons cease gastric acid and intestinal base secretion, both of which are stimulated with feeding. In contrast, fasted water snakes secreted gastric acid and intestinal base at rates similar to those of digesting snakes. We observed no difference between fasted and fed individuals for either species in gastric or intestinal transepithelial potential and conductance, with the exception of a significantly greater gastric transepithelial potential for fed pythons at the start of titration. Water snakes experienced no significant change in gastric or intestinal metabolism with feeding. Fed pythons, in contrast, experienced a near-doubling of gastric metabolism and a tripling of intestinal metabolic rate. For fasted individuals, the metabolic rate of the stomach and small intestine was significantly lower for pythons than for water snakes. The fasting downregulation of digestive function for pythons is manifested in a depressed gastric and intestinal metabolism, which selectively serves to reduce basal metabolism and hence promote survival between infrequent meals. By maintaining elevated GI performance between meals, fasted water snakes incur the additional cost of tissue activity, which is expressed in a higher standard metabolic rate.
Fast and Frugal Heuristics Are Plausible Models of Cognition: Reply to Dougherty, Franco-Watkins, and Thomas (2008)

ERIC Educational Resources Information Center

Gigerenzer, Gerd; Hoffrage, Ulrich; Goldstein, Daniel G.

2008-01-01

M. R. Dougherty, A. M. Franco-Watkins, and R. Thomas (2008) conjectured that fast and frugal heuristics need an automatic frequency counter for ordering cues. In fact, only a few heuristics order cues, and these orderings can arise from evolutionary, social, or individual learning, none of which requires automatic frequency counting. The idea that…
An Active Learning Mammalian Skeletal Muscle Lab Demonstrating Contractile and Kinetic Properties of Fast- and Slow-Twitch Muscle

ERIC Educational Resources Information Center

Head, S. I.; Arber, M. B.

2013-01-01

The fact that humans possess fast and slow-twitch muscle in the ratio of approximately 50% has profound implications for designing exercise training strategies for power and endurance activities. With the growth of exercise and sport science courses, we have seen the need to develop an undergraduate student laboratory that demonstrates the basic…
Getting a College Degree Fast: Testing Out & Other Accredited Short Cuts.

ERIC Educational Resources Information Center

Aber, Joanne

This book, directed especially to individuals over age 30, takes a how-to approach to earning a college degree in the least amount of time for the least amount of money. The book explains how to use fast-track methods such as "testing out," which takes advantage of prior learning, and accredited shortcuts to earn an accelerated degree. The first…
Use of Speaker Intent and Grammatical Cues in Fast-Mapping by Adolescents with Down Syndrome

ERIC Educational Resources Information Center

McDuffie, Andrea S.; Sindberg, Heidi A.; Hesketh, Linda J.; Chapman, Robin S.

2007-01-01

Purpose: The authors asked whether adolescents with Down syndrome (DS) could fast-map novel nouns and verbs when word learning depended on using the speaker's pragmatic or syntactic cues. Compared with typically developing (TD) comparison children, the authors predicted that syntactic cues would prove harder for the group with DS to use and that…
Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

PubMed

Carpenter, Gail A.

1997-11-01

A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network.
Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453
Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

Rotation invariant deep binary hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Dai, Lai; Liu, Jianming; Jiang, Aiwen

2017-07-01

In this paper, we study how to compactly represent image's characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn't have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.
Intermittent fasting in Type 2 diabetes mellitus and the risk of hypoglycaemia: a randomized controlled trial.

PubMed

Corley, B T; Carroll, R W; Hall, R M; Weatherall, M; Parry-Strong, A; Krebs, J D

2018-05-01

To establish whether the risk of hypoglycaemia is greater with 2 consecutive days of very-low-calorie diet compared with 2 non-consecutive days of very-low-calorie diet in people with Type 2 diabetes. This was a non-blinded randomized parallel group interventional trial of intermittent fasting in adults. The participants had a BMI of 30-45 kg/m 2 , Type 2 diabetes treated with metformin and/or hypoglycaemic medications and an HbA 1c concentration of 50-86 mmol/mol (6.7-10%). The participants followed a 2092-2510-kJ diet on 2 days per week for 12 weeks. A total of 41 participants were randomized 1:1 to consecutive (n=19) or non-consecutive (n=22) day fasts, of whom 37 (n=18 and n=19, respectively) were included in the final analysis. The primary outcome was difference in the rate of hypoglycaemia between the two study arms. Secondary outcomes included change in diet, quality of life, weight, lipid, glucose and HbA 1c levels, and liver function. The mean hypoglycaemia rate was 1.4 events over 12 weeks. Fasting increased the rate of hypoglycaemia despite medication reduction (RR 2.05, 95% CI 1.17 to 3.52). There was no difference between fasting on consecutive days and fasting on non-consecutive days (RR 1.54, 95% CI 0.35 to 6.11). Improvements in weight, HbA 1c , fasting glucose and quality of life were experienced by participants in both arms. In individuals with Type 2 diabetes on hypoglycaemic medications, fasting of any type increased the rate of hypoglycaemia. With education and medication reduction, fewer than expected hypoglycaemic events occurred. Although it was not possible to determine whether fasting on consecutive days increased the risk of hypoglycaemia, an acceptable rate was observed in both arms. © 2018 Diabetes UK.
A rate-constrained fast full-search algorithm based on block sum pyramid.

PubMed

Song, Byung Cheol; Chun, Kang-Wook; Ra, Jong Beom

2005-03-01

This paper presents a fast full-search algorithm (FSA) for rate-constrained motion estimation. The proposed algorithm, which is based on the block sum pyramid frame structure, successively eliminates unnecessary search positions according to rate-constrained criterion. This algorithm provides the identical estimation performance to a conventional FSA having rate constraint, while achieving considerable reduction in computation.
Extension of Viscoplasticity Based on Overstress to Capture the Effects of Prior Aging on the Time Dependent Deformation Behavior of a High-Temperature Polymer: Experiments and Modeling

DTIC Science & Technology

2008-10-01

the standard model characterization procedure is based on creep and recovery tests, where loading and unloading occurs at a fast rate of 1.0 MPa/s...σ − g[ǫ] and on d̊g[ǫ] dǫ = E, where g̊ is defined as the equilibrium stress g[ ] for extremely fast loading. For this case, the stress-strain curves...Strain S tr es s Strain Rate Slow Strain Rate Medium Strain Rate Fast Plastic Flow Fully Established Figure 2.10: Stress Strain Curve Schematic
A study of video frame rate on the perception of moving imagery detail

NASA Technical Reports Server (NTRS)

Haines, Richard F.; Chuang, Sherry L.

1993-01-01

The rate at which each frame of color moving video imagery is displayed was varied in small steps to determine what is the minimal acceptable frame rate for life scientists viewing white rats within a small enclosure. Two, twenty five second-long scenes (slow and fast animal motions) were evaluated by nine NASA principal investigators and animal care technicians. The mean minimum acceptable frame rate across these subjects was 3.9 fps both for the slow and fast moving animal scenes. The highest single trial frame rate averaged across all subjects for the slow and the fast scene was 6.2 and 4.8, respectively. Further research is called for in which frame rate, image size, and color/gray scale depth are covaried during the same observation period.
Recall of short word lists presented visually at fast rates: effects of phonological similarity and word length.

PubMed

Coltheart, V; Langdon, R

1998-03-01

Phonological similarity of visually presented list items impairs short-term serial recall. Lists of long words are also recalled less accurately than are lists of short words. These results have been attributed to phonological recoding and rehearsal. If subjects articulate irrelevant words during list presentation, both phonological similarity and word length effects are abolished. Experiments 1 and 2 examined effects of phonological similarity and recall instructions on recall of lists shown at fast rates (from one item per 0.114-0.50 sec), which might not permit phonological encoding and rehearsal. In Experiment 3, recall instructions and word length were manipulated using fast presentation rates. Both phonological similarity and word length effects were observed, and they were not dependent on recall instructions. Experiments 4 and 5 investigated the effects of irrelevant concurrent articulation on lists shown at fast rates. Both phonological similarity and word length effects were removed by concurrent articulation, as they were with slow presentation rates.
The Role of Competition in Word Learning via Referent Selection

ERIC Educational Resources Information Center

Horst, Jessica S.; Scott, Emilly J.; Pollard, Jessica A.

2010-01-01

Previous research suggests that competition among the objects present during referent selection influences young children's ability to learn words in fast mapping tasks. The present study systematically explored this issue with 30-month-old children. Children first received referent selection trials with a target object and either two, three or…
Teaching Chemistry at Indira Gandhi National Open University

ERIC Educational Resources Information Center

Fozdar, Bharat I.; Kumar, Lalita S.

2006-01-01

The Open Distance Learning (ODL) concept is fast becoming popular all over the world and it has a lot of relevance for a highly populated country like India. However, the most important aspect of this type of teaching-learning process is establishment of the credibility especially when the laboratory based science programmes are delivered from…
A Practice of Mobile Learning Based on Cloud Computing

ERIC Educational Resources Information Center

Heng, Wu; Zhong, Dong

2016-01-01

Information and communication technology are well known rapid growing industry in this decade. That is nearly the same as fast as growth in costs in education. Therefore, many people have been forced to find alternative ways to meet their education needs. Innovations of distance education create a new way to provide learning content, unlimited…
Use of Distance Education by Christian Religion to Train, Edify and Educate Adherents

ERIC Educational Resources Information Center

Satyanarayana, P.; DK Meduri, Emmanuel

2013-01-01

Distance Education has been growing fast, in a marvelously diverse fashion. The efficiency, effectiveness, validity and utility of distance teaching-learning are on increase. All communities and religious groups are making use of distance learning methodology to upgrade their knowledge, skills and attitudes. Christian educational institutions in…
Learning from Our Students

ERIC Educational Resources Information Center

Noddings, Nel

2004-01-01

Most teachers have been good students. Some students are fast learners and attain the required knowledge and skills easily; others are obedient, hard workers. In either case, teachers are likely to believe that if students really try, they will do well. Listening to students over many years, the author has learned that this is probably not true.…
Word Learning Processes in Children with Cochlear Implants

ERIC Educational Resources Information Center

Walker, Elizabeth A.; McGregor, Karla K.

2013-01-01

Purpose: To determine whether 3 aspects of the word learning process--fast mapping, retention, and extension--are problematic for children with cochlear implants (CIs). Method: The authors compared responses of 24 children with CIs, 24 age-matched hearing children, and 23 vocabulary-matched hearing children to a novel object noun training episode.…
Optimize Knowledge Sharing, Team Effectiveness, and Individual Learning within the Flipped Team-Based Classroom

ERIC Educational Resources Information Center

Huang, Chung-Kai; Lin, Chun-Yu; Lin, Zih-Cin; Wang, Cui; Lin, Chia-Jung

2017-01-01

Due to the competitive and fast-changing nature of external business environments, university students should acquire knowledge of how to cooperate, share knowledge, and enhance team effectiveness and individual learning in the future workplace. Consequently, the redesign of business courses in higher education merits more discussion. Based on the…
Memory Consolidation within the Central Amygdala Is Not Necessary for Modulation of Cerebellar Learning

ERIC Educational Resources Information Center

Steinmetz, Adam B.; Ng, Ka H.; Freeman, John H.

2017-01-01

Amygdala lesions impair, but do not prevent, acquisition of cerebellum-dependent eyeblink conditioning suggesting that the amygdala modulates cerebellar learning. Two-factor theories of eyeblink conditioning posit that a fast-developing memory within the amygdala facilitates slower-developing memory within the cerebellum. The current study tested…
Reading in the Social Studies.

ERIC Educational Resources Information Center

Ediger, Marlow

Reading social studies content presents situations in which selected pupils have not been as successful in learning as they might have been. Fast learners may find the content exceptionally easy to read, thus learning does not become the challenge it should be. Slow learners may find the content too difficult to comprehend. There are a variety of…
Counting-loss correction for X-ray spectroscopy using unit impulse pulse shaping.

PubMed

Hong, Xu; Zhou, Jianbin; Ni, Shijun; Ma, Yingjie; Yao, Jianfeng; Zhou, Wei; Liu, Yi; Wang, Min

2018-03-01

High-precision measurement of X-ray spectra is affected by the statistical fluctuation of the X-ray beam under low-counting-rate conditions. It is also limited by counting loss resulting from the dead-time of the system and pile-up pulse effects, especially in a high-counting-rate environment. In this paper a detection system based on a FAST-SDD detector and a new kind of unit impulse pulse-shaping method is presented, for counting-loss correction in X-ray spectroscopy. The unit impulse pulse-shaping method is evolved by inverse deviation of the pulse from a reset-type preamplifier and a C-R shaper. It is applied to obtain the true incoming rate of the system based on a general fast-slow channel processing model. The pulses in the fast channel are shaped to unit impulse pulse shape which possesses small width and no undershoot. The counting rate in the fast channel is corrected by evaluating the dead-time of the fast channel before it is used to correct the counting loss in the slow channel.
Whole-body fat oxidation increases more by prior exercise than overnight fasting in elite endurance athletes.

PubMed

Andersson Hall, Ulrika; Edin, Fredrik; Pedersen, Anders; Madsen, Klavs

2016-04-01

The purpose of this study was to compare whole-body fat oxidation kinetics after prior exercise with overnight fasting in elite endurance athletes. Thirteen highly trained athletes (9 men and 4 women; maximal oxygen uptake: 66 ± 1 mL·min(-1)·kg(-1)) performed 3 identical submaximal incremental tests on a cycle ergometer using a cross-over design. A control test (CON) was performed 3 h after a standardized breakfast, a fasting test (FAST) 12 h after a standardized evening meal, and a postexercise test (EXER) after standardized breakfast, endurance exercise, and 2 h fasting recovery. The test consisted of 3 min each at 30%, 40%, 50%, 60%, 70%, and 80% of maximal oxygen uptake and fat oxidation rates were measured through indirect calorimetry. During CON, maximal fat oxidation rate was 0.51 ± 0.04 g·min(-1) compared with 0.69 ± 0.04 g·min(-1) in FAST (P < 0.01), and 0.89 ± 0.05 g·min(-1) in EXER (P < 0.01). Across all intensities, EXER was significantly higher than FAST and FAST was higher than CON (P < 0.01). Blood insulin levels were lower and free fatty acid and cortisol levels were higher at the start of EXER compared with CON and FAST (P < 0.05). Plasma nuclear magnetic resonance-metabolomics showed similar changes in both EXER and FAST, including increased levels of fatty acids and succinate. In conclusion, prior exercise significantly increases whole-body fat oxidation during submaximal exercise compared with overnight fasting. Already high rates of maximal fat oxidation in elite endurance athletes were increased by approximately 75% after prior exercise and fasting recovery.
Optimal duration of fasting period after endoscopic submucosal dissection for gastric epithelial neoplasia: A prospective evaluation.

PubMed

Oh, Kwang Hoon; Lee, Sang Jin; Park, Jong Kyu

2017-08-01

There are currently no standardized guidelines for adequately determining the fasting period following gastric endoscopic submucosal dissection (ESD). The aim of this study was to determine the appropriate fasting period. The enrolled patients were randomized into a short and a long-fasting group. In the short-fasting group, patients had fasted until the day after the ESD. In the long-fasting group, patients had fasted until 2 days after the ESD. A second-look endoscopy was performed immediately prior to starting to eat meals. The primary end-point was the measurement of discomfort-related ESD after starting meals such as epigastric pain, heartburn, regurgitation, nausea and vomiting. Secondary end-points included the bleeding rate after starting meals, hospital stay, patient satisfaction and hemostasis upon second-look endoscopy. We analyzed data from 101 of 110 randomized patients. Both groups demonstrated similar baseline characteristics. There were no significant differences in reports of epigastric pain, heartburn, regurgitation, nausea and vomiting after starting meals. Both groups demonstrated similar hemostasis rates upon second-look endoscopy (26% vs 31.4%, P = 0.551) and bleeding rate (4% vs 0%, P = 0.149). The duration of hospital stay was significantly shorter in the short-fasting group (4.3 days vs 5.1 days, P < 0.001), and patient satisfaction was greater (P = 0.003) than in the long-fasting group. A short fasting protocol does not cause discomfort related to ESD or influence post-ESD bleeding. Moreover, the short fasting protocol results in shorter hospital stays and greater patient satisfaction. © 2017 Chinese Medical Association Shanghai Branch, Chinese Society of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.
Neural learning of constrained nonlinear transformations

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Gulati, Sandeep; Zak, Michail

1989-01-01

Two issues that are fundamental to developing autonomous intelligent robots, namely, rudimentary learning capability and dexterous manipulation, are examined. A powerful neural learning formalism is introduced for addressing a large class of nonlinear mapping problems, including redundant manipulator inverse kinematics, commonly encountered during the design of real-time adaptive control mechanisms. Artificial neural networks with terminal attractor dynamics are used. The rapid network convergence resulting from the infinite local stability of these attractors allows the development of fast neural learning algorithms. Approaches to manipulator inverse kinematics are reviewed, the neurodynamics model is discussed, and the neural learning algorithm is presented.
Active and Interactive Discovery of Goal Selection Knowledge

DTIC Science & Technology

2011-01-01

Generator retrieves the goal ct.g of the most similar case ct and outputs it to the Goal Manager. 5.3 Retention and Maintenance: Active Learning Figure...pp. 202-206). Seattle, WA: AAAI Press. Hu, R., Delaney, S.J., & Mac Namee, B. (2010). EGAL: Exploration guided active learning for TCBR. Proceedings...Sculley, D. (2007). Online active learning methods for fast label- efficient spam filtering. In Proceedings of the Fourth Conference on Email and Anti

Muslim patients in Ramadan: A review for primary care physicians

PubMed Central

Abolaban, Heba; Al-Moujahed, Ahmad

2017-01-01

Fasting Ramadan, in which Muslims abstain from specific habits and behaviors from dawn to sunset, is one of the five Pillars of Islam. While there are several exemptions from fasting, many Muslim patients with acute or chronic medical conditions still choose to fast, which may adversely affect their health if not addressed properly. Some patients may not be well educated about the effects of some medical treatments and procedures on the validity of their fast, which can unnecessarily lead to suboptimal management of their conditions or treatment nonadherence. Since spirituality, religiosity, and personal beliefs affect patients' health behaviors and adherence to treatments, health-care providers need to learn how fasting Ramadan can affect the health of their Muslim patients, especially those with chronic medical conditions, and how to help them achieve safe fasting. This article aims to provide an overview of the main topics that primary care physicians may need to know in order to improve their cultural competence when caring for their fasting Muslim patients. PMID:28791239
Dendritic Learning as a Paradigm Shift in Brain Learning.

PubMed

Sardi, Shira; Vardi, Roni; Goldental, Amir; Tugendhaft, Yael; Uzan, Herut; Kanter, Ido

2018-06-20

Experimental and theoretical results reveal a new underlying mechanism for fast brain learning process, dendritic learning, as opposed to the misdirected research in neuroscience over decades, which is based solely on slow synaptic plasticity. The presented paradigm indicates that learning occurs in closer proximity to the neuron, the computational unit, dendritic strengths are self-oscillating, and weak synapses, which comprise the majority of our brain and previously were assumed to be insignificant, play a key role in plasticity. The new learning sites of the brain call for a reevaluation of current treatments for disordered brain functionality and for a better understanding of proper chemical drugs and biological mechanisms to maintain, control and enhance learning.
Hunger Promotes Fear Extinction by Activation of an Amygdala Microcircuit

PubMed Central

Verma, Dilip; Wood, James; Lach, Gilliard; Herzog, Herbert; Sperk, Guenther; Tasan, Ramon

2016-01-01

Emotions control evolutionarily-conserved behavior that is central to survival in a natural environment. Imbalance within emotional circuitries, however, may result in malfunction and manifestation of anxiety disorders. Thus, a better understanding of emotional processes and, in particular, the interaction of the networks involved is of considerable clinical relevance. Although neurobiological substrates of emotionally controlled circuitries are increasingly evident, their mutual influences are not. To investigate interactions between hunger and fear, we performed Pavlovian fear conditioning in fasted wild-type mice and in mice with genetic modification of a feeding-related gene. Furthermore, we analyzed in these mice the electrophysiological microcircuits underlying fear extinction. Short-term fasting before fear acquisition specifically impaired long-term fear memory, whereas fasting before fear extinction facilitated extinction learning. Furthermore, genetic deletion of the Y4 receptor reduced appetite and completely impaired fear extinction, a phenomenon that was rescued by fasting. A marked increase in feed-forward inhibition between the basolateral and central amygdala has been proposed as a synaptic correlate of fear extinction and involves activation of the medial intercalated cells. This form of plasticity was lost in Y4KO mice. Fasting before extinction learning, however, resulted in specific activation of the medial intercalated neurons and re-established the enhancement of feed-forward inhibition in this amygdala microcircuit of Y4KO mice. Hence, consolidation of fear and extinction memories is differentially regulated by hunger, suggesting that fasting and modification of feeding-related genes could augment the effectiveness of exposure therapy and provide novel drug targets for treatment of anxiety disorders. PMID:26062787
Hunger Promotes Fear Extinction by Activation of an Amygdala Microcircuit.

PubMed

Verma, Dilip; Wood, James; Lach, Gilliard; Herzog, Herbert; Sperk, Guenther; Tasan, Ramon

2016-01-01

Emotions control evolutionarily-conserved behavior that is central to survival in a natural environment. Imbalance within emotional circuitries, however, may result in malfunction and manifestation of anxiety disorders. Thus, a better understanding of emotional processes and, in particular, the interaction of the networks involved is of considerable clinical relevance. Although neurobiological substrates of emotionally controlled circuitries are increasingly evident, their mutual influences are not. To investigate interactions between hunger and fear, we performed Pavlovian fear conditioning in fasted wild-type mice and in mice with genetic modification of a feeding-related gene. Furthermore, we analyzed in these mice the electrophysiological microcircuits underlying fear extinction. Short-term fasting before fear acquisition specifically impaired long-term fear memory, whereas fasting before fear extinction facilitated extinction learning. Furthermore, genetic deletion of the Y4 receptor reduced appetite and completely impaired fear extinction, a phenomenon that was rescued by fasting. A marked increase in feed-forward inhibition between the basolateral and central amygdala has been proposed as a synaptic correlate of fear extinction and involves activation of the medial intercalated cells. This form of plasticity was lost in Y4KO mice. Fasting before extinction learning, however, resulted in specific activation of the medial intercalated neurons and re-established the enhancement of feed-forward inhibition in this amygdala microcircuit of Y4KO mice. Hence, consolidation of fear and extinction memories is differentially regulated by hunger, suggesting that fasting and modification of feeding-related genes could augment the effectiveness of exposure therapy and provide novel drug targets for treatment of anxiety disorders.
An audit of preoperative fasting compliance at a major tertiary referral hospital in Singapore

PubMed Central

Lim, Hsien Jer; Lee, Hanjing; Ti, Lian Kah

2014-01-01

INTRODUCTION To avoid the risk of pulmonary aspiration, fasting before anaesthesia is important. We postulated that the rate of noncompliance with fasting would be high in patients who were admitted on the day of surgery. Therefore, we surveyed patients in our institution to determine the rate of fasting compliance. We also examined patients’ knowledge on preoperative fasting, as well as their perception of and attitudes toward preoperative fasting. METHODS Patients scheduled for ‘day surgery’ or ‘same day admission surgery’ under general or regional anaesthesia were surveyed over a four-week period. The patients were asked to answer an eighteen-point questionnaire on demographics, preoperative fasting and attitudes toward fasting. RESULTS A total of 130 patients were surveyed. 128 patients fasted before surgery, 111 patients knew that they needed to fast for at least six hours before surgery, and 121 patients believed that preoperative fasting was important, with 103 believing that preoperative fasting was necessary to avoid perioperative complications. However, patient understanding was poor, with only 44.6% of patients knowing the reason for fasting, and 10.8% of patients thinking that preoperative fasting did not include abstinence from beverages and sweets. When patients who did and did not know the reason for fasting were compared, we did not find any significant differences in age, gender or educational status. CONCLUSION Despite the patients’ poor understanding of the reason for fasting, they were highly compliant with preoperative fasting. This is likely a result of their perception that fasting was important. However, poor understanding of the reason for fasting may lead to unintentional noncompliance. PMID:24452973
Issues in NASA Program and Project Management. Special Report: 1997 Conference. Project Management Now and in the New Millennium

NASA Technical Reports Server (NTRS)

Hoffman, Edward J. (Editor); Lawbaugh, William M. (Editor)

1997-01-01

Topics Considered Include: NASA's Shared Experiences Program; Core Issues for the Future of the Agency; National Space Policy Strategic Management; ISO 9000 and NASA; New Acquisition Initiatives; Full Cost Initiative; PM Career Development; PM Project Database; NASA Fast Track Studies; Fast Track Projects; Earned Value Concept; Value-Added Metrics; Saturn Corporation Lessons Learned; Project Manager Credibility.
Selective Attention in Fast and Slow Learners During Discrimination Learning in the Haptic Modality. Information and Research Report.

ERIC Educational Resources Information Center

Hunt, Dennis; And Others

Sixty-four 8-year-old children were divided into fast and slow learner groups and trained on a tactile simultaneous discrimination task. Selective attention was measured in terms of percentage contact time per trial to the relevant dimension. Inter- and intracouplings per trial were also recorded. A multivariate analysis was carried out to examine…
Combating information overload: a six-month pilot evaluation of a knowledge management system in general practice.

PubMed Central

O'Brien, C; Cambouropoulos, P

2000-01-01

A six-month prospective study was conducted on the usefulness and usability of a representative electronic knowledge management tool, the WAX Active Library, for 19 general practitioners (GPs) evaluated using questionnaires and audit trail data. The number of pages accessed was highest in the final two months, when over half of the access trails were completed within 40 seconds. Most GPs rated the system as easy to learn, fast to use, and preferable to paper for providing information during consultations. Such tools could provide a medium for the activities of knowledge officers, help demand management, and promote sharing of information within primary care groups and across NHSnet or the Internet. PMID:10962792
Public Information Use in Chimpanzees (Pan troglodytes) and Children (Homo sapiens)

PubMed Central

Vale, Gill L.; Flynn, Emma G.; Lambeth, Susan P.; Schapiro, Steven J.; Kendal, Rachel L.

2014-01-01

The discernment of resource quality is pertinent to many daily decisions faced by animals. Public information is a critical information source that promotes quality assessments, attained by monitoring others’ performance. Here we provide the first evidence, to our knowledge, that chimpanzees (Pan troglodytes) use public information to guide resource selection. Thirty-two chimpanzees were presented with two simultaneous video demonstrations depicting a conspecific acquiring resources at a fast (resource-rich) or slow (resource-poor) rate. Subsequently, subjects selected the resource-rich site above chance expectation. As a comparison, we report evidence of public information use in young children. Investigation of public information use in primates is pertinent, as it can enhance foraging success and potentially facilitate payoff-biased social learning. PMID:24060244
Metabolic profiles and bile acid extraction rate in the liver of cows with fasting-induced hepatic lipidosis.

PubMed

Mohamed, T; Oikawa, S; Iwasaki, Y; Mizunuma, Y; Takehana, K; Endoh, D; Kurosawa, T; Sato, H

2004-04-01

This study was designed to monitor lipid profile in the portal and hepatic blood of cows with fasting-induced hepatic lipidosis, and to compare the results with those in the jugular blood. The work was also carried out to investigate bile acid (BA) in these vessels, and further to investigate BA extraction rate in the liver. Five cows were equipped with catheters in the portal, hepatic and jugular veins (day 0), fasted for 4 days (day 1-day 4) and then refed (day 5-day 11). Before morning feeding, blood was sampled before, during and after fasting from the catheterized vessels. In the portal blood, the concentration of non-esterified fatty acids (NEFA) showed a progressive increase and at day 5 there was an approximate twofold rise. Increased NEFA concentrations were also found similarly in the other two veins. At day 5, beta-hydroxybutyrate (BHBA) in the portal, hepatic and jugular blood rose to 197, 190 and 186% of the pre-fasting value, respectively. However, the concentrations of NEFA and BHBA in the three veins gradually returned to pre-fasting concentration during the refeeding period. Compared with the pre-fasting value at day 0, the content of liver triglyceride (TG) increased significantly at day 5 (P < 0.01). In the liver, the hepatic extraction rate of BA dropped from 3.1 times pre-fasting to 2.2 times during fasting. There were no significant differences in the concentrations of glucose, TG, total cholesterol, cholesterol esters, free cholesterol and phospholipids. The results of the current study show that metabolic alterations occur in the portal, hepatic and jugular veins during induction of hepatic lipidosis in cows, and mostly metabolites, with exception of BA concentration, run parallel. The decreased BA extraction rate in the liver of fasted cows was considered to reflect hepatic cell impairment caused by TG accumulation. Hopefully, the findings, at least in part, contribute to the explanation of the pathophysiology of hepatic lipidosis in dairy cows.
Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography.

PubMed

Venhuizen, Freerk G; van Ginneken, Bram; Liefers, Bart; van Asten, Freekje; Schreur, Vivian; Fauser, Sascha; Hoyng, Carel; Theelen, Thomas; Sánchez, Clara I

2018-04-01

We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition. A cascade of neural networks was introduced to include prior information on the retinal anatomy, boosting performance significantly. The proposed algorithm approached human performance reaching an overall Dice coefficient of 0.754 ± 0.136 and an intraclass correlation coefficient of 0.936, for the task of IRC segmentation and quantification, respectively. The proposed method allows for fast quantitative IRC volume measurements that can be used to improve patient care, reduce costs, and allow fast and reliable analysis in large population studies.
Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography

PubMed Central

Venhuizen, Freerk G.; van Ginneken, Bram; Liefers, Bart; van Asten, Freekje; Schreur, Vivian; Fauser, Sascha; Hoyng, Carel; Theelen, Thomas; Sánchez, Clara I.

2018-01-01

We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition. A cascade of neural networks was introduced to include prior information on the retinal anatomy, boosting performance significantly. The proposed algorithm approached human performance reaching an overall Dice coefficient of 0.754 ± 0.136 and an intraclass correlation coefficient of 0.936, for the task of IRC segmentation and quantification, respectively. The proposed method allows for fast quantitative IRC volume measurements that can be used to improve patient care, reduce costs, and allow fast and reliable analysis in large population studies. PMID:29675301
AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.
Automatic estimation of heart boundaries and cardiothoracic ratio from chest x-ray images

NASA Astrophysics Data System (ADS)

Dallal, Ahmed H.; Agarwal, Chirag; Arbabshirani, Mohammad R.; Patel, Aalpen; Moore, Gregory

2017-03-01

Cardiothoracic ratio (CTR) is a widely used radiographic index to assess heart size on chest X-rays (CXRs). Recent studies have suggested that also two-dimensional CTR might contain clinical information about the heart function. However, manual measurement of such indices is both subjective and time consuming. This study proposes a fast algorithm to automatically estimate CTR indices based on CXRs. The algorithm has three main steps: 1) model based lung segmentation, 2) estimation of heart boundaries from lung contours, and 3) computation of cardiothoracic indices from the estimated boundaries. We extended a previously employed lung detection algorithm to automatically estimate heart boundaries without using ground truth heart markings. We used two datasets: a publicly available dataset with 247 images as well as clinical dataset with 167 studies from Geisinger Health System. The models of lung fields are learned from both datasets. The lung regions in a given test image are estimated by registering the learned models to patient CXRs. Then, heart region is estimated by applying Harris operator on segmented lung fields to detect the corner points corresponding to the heart boundaries. The algorithm calculates three indices, CTR1D, CTR2D, and cardiothoracic area ratio (CTAR). The method was tested on 103 clinical CXRs and average error rates of 7.9%, 25.5%, and 26.4% (for CTR1D, CTR2D, and CTAR respectively) were achieved. The proposed method outperforms previous CTR estimation methods without using any heart templates. This method can have important clinical implications as it can provide fast and accurate estimate of cardiothoracic indices.
Learning in the Workplace for Garage Mechanics and Technicians

ERIC Educational Resources Information Center

Jans, Ruben, Bollen, Ria,

2008-01-01

Employees in technical firms, like garages, need more and more formations. Due to the very fast innovation in technology, lifelong learning is a real need for these labour forces. On the other hand, there are the needed formations very specialized and expensive. Another problem employers faced in these economical sectors in Western Europe is the…
OAEditor--A Framework for Editing Adaptive Learning Objects

ERIC Educational Resources Information Center

Pereira, Joao Carlos Rodrigues; Cabral, Lucidio dos Anjos Formiga; Oiveira, Ronei dos Santos; Bezerra, Lucimar Leandro; de Melo, Nisston Moraes Tavares

2012-01-01

Distance Learning supported by the WEB is a reality which is growing fast and, like any technological or empirical innovation, it reveals positive and negative aspects. An important aspect is in relation to the monitoring of the activities done by the students since an accurate online assessment of the knowledge acquired is an open and, therefore,…
Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2014-01-01

Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…
Dave Moore: Taking Roundabout Path to Perovskite Fast Track | News | NREL

Science.gov Websites

energy of academia is awesome and contagious. It keeps you young to hang around young people and keep learning." Although he'd had a checkered high school academic career prior to stepping on the college ," Moore said. "That's where I first learned about the energy crisis." And that's when he
Using Word Clouds for Fast, Formative Assessment of Students' Short Written Responses

ERIC Educational Resources Information Center

Brooks, Bill J.; Gilbuena, Debra M.; Krause, Stephen J.; Koretsky, Milo D.

2014-01-01

Active learning in class helps students develop deeper understanding of chemical engineering principles. While the use of multiple-choice ConcepTests is clearly effective, we advocate for including student writing in learning activities as well. In this article, we demonstrate that word clouds can provide a quick analytical technique to assess…
Addressing Challenges in Web Accessibility for the Blind and Visually Impaired

ERIC Educational Resources Information Center

Guercio, Angela; Stirbens, Kathleen A.; Williams, Joseph; Haiber, Charles

2011-01-01

Searching for relevant information on the web is an important aspect of distance learning. This activity is a challenge for visually impaired distance learners. While sighted people have the ability to filter information in a fast and non sequential way, blind persons rely on tools that process the information in a sequential way. Learning is…

Designing a Syntax-Based Retrieval System for Supporting Language Learning

ERIC Educational Resources Information Center

Tsao, Nai-Lung; Kuo, Chin-Hwa; Wible, David; Hung, Tsung-Fu

2009-01-01

In this paper, we propose a syntax-based text retrieval system for on-line language learning and use a fast regular expression search engine as its main component. Regular expression searches provide more scalable querying and search results than keyword-based searches. However, without a well-designed index scheme, the execution time of regular…
From Chalk and Talk to Walking the Walk: Facilitating Dynamic Learning Contexts for Entrepreneurship Students in Fast-Tracking Innovations

ERIC Educational Resources Information Center

Gilbert, David H.

2012-01-01

Purpose: The purpose of this paper is to examine the notion of designing and developing applied, industry-engaged learning environments that embrace ambiguity and uncertainty in overcoming pedagogical inertia in educating young entrepreneurs and innovators. The research reported on proposes a solution to the dual expectations of producing…
Enhancing Learning and Teaching with Technology: What the Research Says

ERIC Educational Resources Information Center

Luckin, Rosemary, Ed.

2018-01-01

The educational technology sector is growing fast, with schools, colleges and universities more than ever looking for the best ways to use technology in the classroom. At the same time, there is an increasing appetite for learning and teaching practices to be backed up by evidence. However, there are few resources that bring these two things…
A fast and accurate online sequential learning algorithm for feedforward networks.

PubMed

Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

2006-11-01

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.
Three timescales in prism adaptation.

PubMed

Inoue, Masato; Uchimura, Motoaki; Karibe, Ayaka; O'Shea, Jacinta; Rossetti, Yves; Kitazawa, Shigeru

2015-01-01

It has been proposed that motor adaptation depends on at least two learning systems, one that learns fast but with poor retention and another that learns slowly but with better retention (Smith MA, Ghazizadeh A, Shadmehr R. PLoS Biol 4: e179, 2006). This two-state model has been shown to account for a range of behavior in the force field adaptation task. In the present study, we examined whether such a two-state model could also account for behavior arising from adaptation to a prismatic displacement of the visual field. We first confirmed that an "adaptation rebound," a critical prediction of the two-state model, occurred when visual feedback was deprived after an adaptation-extinction episode. We then examined the speed of decay of the prism aftereffect (without any visual feedback) after repetitions of 30, 150, and 500 trials of prism exposure. The speed of decay decreased with the number of exposure trials, a phenomenon that was best explained by assuming an "ultraslow" system, in addition to the fast and slow systems. Finally, we compared retention of aftereffects 24 h after 150 or 500 trials of exposure: retention was significantly greater after 500 than 150 trials. This difference in retention could not be explained by the two-state model but was well explained by the three-state model as arising from the difference in the amount of adaptation of the "ultraslow process." These results suggest that there are not only fast and slow systems but also an ultraslow learning system in prism adaptation that is activated by prolonged prism exposure of 150-500 trials. Copyright © 2015 the American Physiological Society.
DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.
Effect of eating rate on binge size in Bulimia Nervosa

PubMed Central

Kissileff, Harry R; Zimmerli, Ellen J; Torres, Migdalia I; Devlin, Michael J; Walsh, B Timothy

2008-01-01

Effect of eating rate on binge size in bulimia nervosa. Bulimia Nervosa (BN) is an eating disorder characterized by recurrent episodes of binge eating. During binge eating episodes, patients often describe the rapid consumption of food, and laboratory studies have shown that during binges patients with BN eat faster than normal controls (NC), but the hypothesis that a rapid rate of eating contributes to the excessive intake of binge meals has not yet been experimentally tested. The aim of this study was to assess the effect of eating rate on binge size in BN, in order to determine whether binge size is mediated, in part, by rate of eating. Thirteen BN and 14 NC subjects were asked to binge eat a yogurt shake that was served at a fast rate (140g/min) on one occasion and at a slow rate (70g/min) on another. NC subjects consumed 169 g more when eating at the fast rate than when eating at the slow rate. In contrast, consumption rates failed to influence binge size in patients with BN (fast: 1205 g; slow: 1195 g). Consequently, there was a significant group by rate interaction. As expected, patients with BN consumed more overall than NC subjects (1200 g vs. 740 g). When instructed to binge in the eating laboratory, patients with BN ate equally large amounts of food at a slow rate as at a fast rate. NC subjects ate less at a slow rate. These findings indicate that in a structured laboratory meal paradigm binge size is not affected by rate of eating. PMID:17996257
Human tracking in thermal images using adaptive particle filters with online random forest learning

NASA Astrophysics Data System (ADS)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.
Why "The Best Way of Learning to Coach the Game Is Playing the Game": Conceptualising "Fast-Tracked" High-Performance Coaching Pathways

ERIC Educational Resources Information Center

Blackett, Alexander David; Evans, Adam; Piggott, David

2017-01-01

At the beginning of the 2013/2014 season in England and Wales, 90 head coaches of the 92 men's national professional football league clubs and 20 of the 22 men's professional rugby union clubs had tenure as a professional elite player in their respective sports. Moreover, Rynne [(2014). "'Fast track' and 'traditional path' coaches:…
Restructuring for the 90s and Beyond: Solution Based Learning in the Era of Smart Homes, Wired Communities, Fast Systems, Global Networks, and Fast Forward Learners in a Borderless World.

ERIC Educational Resources Information Center

Groff, Warren H.

An ultimate purpose of education is human resource development to provide society with a critical mass of intellectual capital and competent workforces. To accomplish this end, leaders implement planning processes to guide policy-making, develop institutions, and allocate resources. Although new information technologies are becoming commonplace in…
Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words.

PubMed

Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero

2012-01-01

Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning to optimize therapeutic strategies.
Inversion of surface parameters using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Olvera, J.; Fung, A. K.; Manry, M. T.

1992-01-01

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.
Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning.

PubMed

Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C

2018-02-08

Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.
Effects of nutritional status on metabolic rate, exercise and recovery in a freshwater fish.

PubMed

Gingerich, Andrew James; Philipp, David P; Suski, Cory D

2010-03-01

The influence of feeding on swimming performance and exercise recovery in fish is poorly understood. Examining swimming behavior and physiological status following periods of feeding and fasting is important because wild fish often face periods of starvation. In the current study, researchers force fed and fasted groups of largemouth bass (Micropterus salmoides) of similar sizes for a period of 16 days. Following this feeding and fasting period, fish were exercised for 60 s and monitored for swimming performance and physiological recovery. Resting metabolic rates were also determined. Fasted fish lost an average of 16 g (nearly 12%) of body mass, while force fed fish maintained body mass. Force fed fish swam 28% further and required nearly 14 s longer to tire during exercise. However, only some physiological conditions differed between feeding groups. Resting muscle glycogen concentrations was twofold greater in force fed fish, at rest and throughout recovery, although it decreased in both feeding treatments following exercise. Liver mass was nearly three times greater in force fed fish, and fasted fish had an average of 65% more cortisol throughout recovery. Similar recovery rates of most physiological responses were observed despite force fed fish having a metabolic rate 75% greater than fasted fish. Results are discussed as they relate to largemouth bass starvation in wild systems and how these physiological differences might be important in an evolutionary context.
Explosion Monitoring with Machine Learning: A LSTM Approach to Seismic Event Discrimination

NASA Astrophysics Data System (ADS)

Magana-Zook, S. A.; Ruppert, S. D.

2017-12-01

The streams of seismic data that analysts look at to discriminate natural from man- made events will soon grow from gigabytes of data per day to exponentially larger rates. This is an interesting problem as the requirement for real-time answers to questions of non-proliferation will remain the same, and the analyst pool cannot grow as fast as the data volume and velocity will. Machine learning is a tool that can solve the problem of seismic explosion monitoring at scale. Using machine learning, and Long Short-term Memory (LSTM) models in particular, analysts can become more efficient by focusing their attention on signals of interest. From a global dataset of earthquake and explosion events, a model was trained to recognize the different classes of events, given their spectrograms. Optimal recurrent node count and training iterations were found, and cross validation was performed to evaluate model performance. A 10-fold mean accuracy of 96.92% was achieved on a balanced dataset of 30,002 instances. Given that the model is 446.52 MB it can be used to simultaneously characterize all incoming signals by researchers looking at events in isolation on desktop machines, as well as at scale on all of the nodes of a real-time streaming platform. LLNL-ABS-735911
The fast food and obesity link: consumption patterns and severity of obesity.

PubMed

Garcia, Ginny; Sunil, Thankam S; Hinojosa, Pedro

2012-05-01

Rates of extreme forms of obesity are rapidly rising, as is the use of bariatric surgery for its treatment. The aim of the present study was to examine selected behavioral factors associated with severity of obesity among preoperative bariatric surgery patients in the San Antonio area, focusing specifically on the effects of fast food consumption. We used ordered logistic regression to model behavioral and attitudinal effects on obesity outcomes among 270 patients. These outcomes were based on the severity of obesity and were measured on the basis of body mass index. Our results indicated that, among the behavioral factors, fast food consumption exerted the largest influence on higher levels of obesity. These remained after controlling for several social and demographic characteristics. Our findings suggest that higher rates of fast food consumption are connected to the increasing rates of severe obesity. Given that morbid and super morbid obesity rates are growing at a more advanced pace than moderate obesity, it is necessary to explore the behavioral characteristics associated with these trends.
46 CFR 12.10-9 - Endorsement for proficiency in fast rescue boats.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Endorsement for proficiency in fast rescue boats. 12.10... SEAMEN REQUIREMENTS FOR RATING ENDORSEMENTS Lifeboatman § 12.10-9 Endorsement for proficiency in fast rescue boats. (a) Each person engaged or employed as a lifeboatman proficient in fast rescue boats must...
46 CFR 12.10-9 - Endorsement for proficiency in fast rescue boats.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 1 2013-10-01 2013-10-01 false Endorsement for proficiency in fast rescue boats. 12.10... SEAMEN REQUIREMENTS FOR RATING ENDORSEMENTS Lifeboatman § 12.10-9 Endorsement for proficiency in fast rescue boats. (a) Each person engaged or employed as a lifeboatman proficient in fast rescue boats must...
46 CFR 12.10-9 - Endorsement for proficiency in fast rescue boats.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Endorsement for proficiency in fast rescue boats. 12.10... SEAMEN REQUIREMENTS FOR RATING ENDORSEMENTS Lifeboatman § 12.10-9 Endorsement for proficiency in fast rescue boats. (a) Each person engaged or employed as a lifeboatman proficient in fast rescue boats must...
46 CFR 12.10-9 - Endorsement for proficiency in fast rescue boats.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Endorsement for proficiency in fast rescue boats. 12.10... SEAMEN REQUIREMENTS FOR RATING ENDORSEMENTS Lifeboatman § 12.10-9 Endorsement for proficiency in fast rescue boats. (a) Each person engaged or employed as a lifeboatman proficient in fast rescue boats must...

Direct hospital costs of total laparoscopic hysterectomy compared with fast-track open hysterectomy at a tertiary hospital: a retrospective case-controlled study.

PubMed

Rhou, Yoon J J; Pather, Selvan; Loadsman, John A; Campbell, Neil; Philp, Shannon; Carter, Jonathan

2015-12-01

To assess the direct intraoperative and postoperative costs in women undergoing total laparoscopic hysterectomy and fast-track open hysterectomy. A retrospective review of the direct hospital-related costs in a matched cohort of women undergoing total laparoscopic hysterectomy (TLH) and fast-track open hysterectomy (FTOH) at a tertiary hospital. All costs were calculated, including the cost of advanced high-energy laparoscopic devices. The effect of the learning curve on cost in laparoscopic hysterectomy was also assessed, as was the hospital case-weighted cost, which was compared with the actual cost. Fifty women were included in each arm of the study. TLH had a higher intraoperative cost, but a lower postoperative cost than FTOH (AUD$3877 vs AUD$2776 P < 0.001, AUD$3965 vs AUD$6233 P < 0.001). The total cost of TLH was not different from FTOH (AUD$7842 vs AUD$9009 P = 0.068) and after a learning curve; TLH cost less than FTOH (AUD$6797 vs AUD$8647, P < 0.001). The use of high-energy devices did not impact on the cost benefit of TLH, and hospital case-weight-based funding correlated poorly with actual cost. Despite the use of fast-track recovery protocols, the cost of TLH is no different to FTOH and after a learning curve is cheaper than open hysterectomy. Judicious use of advanced energy devices does not impact on the cost, and hospital case-weight-based funding model in our hospital is inaccurate when compared to directly calculated hospital costs. © 2013 The Authors ANZJOG © 2013 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.
MRI of gallstones with different compositions.

PubMed

Tsai, Hong-Ming; Lin, Xi-Zhang; Chen, Chiung-Yu; Lin, Pin-Wen; Lin, Jui-Che

2004-06-01

Gallstones are usually recognized on MRI as filling defects of hypointensity. However, they sometimes may appear as hyperintensities on T1-weighted imaging. This study investigated how gallstones appear on MRI and how their appearance influences the detection of gallstones. Gallstones from 24 patients who had MRI performed before the removal of the gallstones were collected for study. The gallstones were classified either as cholesterol gallstone (n = 4) or as pigment gallstone (n = 20) according to their gross appearance and based on analysis by Fourier transform infrared spectroscopy. MRI included three sequences: single-shot fast spin-echo T2-weighted imaging, 3D fast spoiled gradient-echo T1-weighted imaging, and in-phase fast spoiled gradient-echo T1-weighted imaging. The signal intensity and the detection rate of gallstones on MRI were further correlated with the character of the gallstones. On T1-weighted 3D fast spoiled gradient-echo images, most of the pigment gallstones (18/20) were hyperintense and all the cholesterol gallstones (4/4) were hypointense. The mean ratio of the signal intensity of gallstone to bile was (+/- standard deviation) 3.36 +/- 1.88 for pigment gallstone and 0.24 +/- 0.10 for cholesterol gallstone on the 3D fast spoiled gradient-echo sequence (p < 0.001). Combining the 3D fast spoiled gradient-echo and single-shot fast spin-echo sequences achieved the highest gallstone detection rate (96.4%). Based on the differences of signal intensity of gallstones, the 3D fast spoiled gradient-echo T1-weighted imaging was able to diagnose the composition of gallstones. Adding the 3D fast spoiled gradient-echo imaging to the single-shot fast spin-echo T2-weighted sequence can further improve the detection rate of gallstones.
Induction of hepatic ABC transporter expression is part of the PPARalpha-mediated fasting response in the mouse.

PubMed

Kok, Tineke; Wolters, Henk; Bloks, Vincent W; Havinga, Rick; Jansen, Peter L M; Staels, Bart; Kuipers, Folkert

2003-01-01

Fatty acids are natural ligands of the peroxisome proliferator-activated receptor alpha (PPARalpha). Synthetic ligands of this nuclear receptor, i.e., fibrates, induce the hepatic expression of the multidrug resistance 2 gene (Mdr2), encoding the canalicular phospholipid translocator, and affect hepatobiliary lipid transport. We tested whether fasting-associated fatty acid release from adipose tissues alters hepatic transporter expression and bile formation in a PPARalpha-dependent manner. A 24-hour fasting/48-hour refeeding schedule was used in wild-type and Pparalpha((-/-)) mice. Expression of genes involved in the control of bile formation was determined and related to secretion rates of biliary components. Expression of Pparalpha, farnesoid X receptor, and liver X receptor alpha genes encoding nuclear receptors that control hepatic bile salt and sterol metabolism was induced on fasting in wild-type mice only. The expression of Mdr2 was 5-fold increased in fasted wild-type mice and increased only marginally in Pparalpha((-/-)) mice, and it normalized on refeeding. Mdr2 protein levels and maximal biliary phospholipid secretion rates were clearly increased in fasted wild-type mice. Hepatic expression of the liver X receptor target genes ATP binding cassette transporter a1 (Abca1), Abcg5, and Abcg8, implicated in hepatobiliary cholesterol transport, was induced in fasted wild-type mice only. However, the maximal biliary cholesterol secretion rate was reduced by approximately 50%. Induction of Mdr2 expression and function is part of the PPARalpha-mediated fasting response in mice. Fasting also induces expression of the putative hepatobiliary cholesterol transport genes Abca1, Abcg5, and Abcg8, but, nonetheless, maximal biliary cholesterol excretion is decreased after fasting.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Spier, C.E.; Little, D.E.; Trim, S.C.

We investigated activity patterns of 17 elementary school students aged 10-12, and 19 high school students aged 13-17, in suburban Los Angeles during the oxidant pollution season. Individuals' relationships between ventilation rate (VR) and heart rate (HR) were calibrated' in supervised outdoor walking/jogging. Log VR was consistently proportional to HR; although calibrations' were limited by a restricted range of exercise, and possibly by artifact due to mouthpiece breathing, which may cause overestimation of VR at rest. Each subject then recorded activities in diaries, and recorded HR once per minute by wearing Heart Watches, over 3 days (Saturday-Monday). For each activitymore » the subject estimated a breathing rate--slow (slow walking), medium (fast walking), or fast (running). VR ranges for each breathing rate and activity type were estimated from HR recordings. High-school students' diaries showed their aggregate distribution of waking hours as 68% slow inside, 8% slow outside, 10% medium inside, 9% medium outside, 1.5% fast inside, 1.5% fast outside. Elementary students' distribution was 47% slow inside, 15% slow outside, 20% medium inside, 12% medium outside, 2.5% fast inside, 3.5% fast outside. Sleep occupied 38% of high-school students' and 40% of elementary students' time; HR were generally lower in sleep than in slow waking activity. High school students' mean VR estimates were 13 L/min for slow breathing, 18 for medium, and 23 for fast; elementary students' were 14 slow, 18 medium, and 19 fast. VR distributions were approximately lognormal. Maximum estimated VR were approximately 70 L/min in elementary and approximately 100 L/min in high school students. Compared to adults studied similarly, students reported more medium or fast breathing, and had equal or higher VR estimates during slow and medium breathing despite their smaller size. These results suggest that, relative to body size, young people inhale larger doses of outdoor air pollutants than adults.« less
SDSS-IV MaNGA: the different quenching histories of fast and slow rotators

NASA Astrophysics Data System (ADS)

Smethurst, R. J.; Masters, K. L.; Lintott, C. J.; Weijmans, A.; Merrifield, M.; Penny, S. J.; Aragón-Salamanca, A.; Brownstein, J.; Bundy, K.; Drory, N.; Law, D. R.; Nichol, R. C.

2018-01-01

Do the theorized different formation mechanisms of fast and slow rotators produce an observable difference in their star formation histories? To study this, we identify quenching slow rotators in the MaNGA sample by selecting those that lie below the star-forming sequence and identify a sample of quenching fast rotators that were matched in stellar mass. This results in a total sample of 194 kinematically classified galaxies, which is agnostic to visual morphology. We use u - r and NUV - u colours from the Sloan Digital Sky Survey and GALEX and an existing inference package, STARPY, to conduct a first look at the onset time and exponentially declining rate of quenching of these galaxies. An Anderson-Darling test on the distribution of the inferred quenching rates across the two kinematic populations reveals they are statistically distinguishable (3.2σ). We find that fast rotators quench at a much wider range of rates than slow rotators, consistent with a wide variety of physical processes such as secular evolution, minor mergers, gas accretion and environmentally driven mechanisms. Quenching is more likely to occur at rapid rates (τ ≲ 1 Gyr) for slow rotators, in agreement with theories suggesting slow rotators are formed in dynamically fast processes, such as major mergers. Interestingly, we also find that a subset of the fast rotators quench at these same rapid rates as the bulk of the slow rotator sample. We therefore discuss how the total gas mass of a merger, rather than the merger mass ratio, may decide a galaxy's ultimate kinematic fate.
Comparative Studies of Prediction Strategies for Solar X-ray Time Series

NASA Astrophysics Data System (ADS)

Muranushi, T.; Hattori, T.; Jin, Q.; Hishinuma, T.; Tominaga, M.; Nakagawa, K.; Fujiwara, Y.; Nakamura, T.; Sakaue, T.; Takahashi, T.; Seki, D.; Namekata, K.; Tei, A.; Ban, M.; Kawamura, A. D.; Hada-Muranushi, Y.; Asai, A.; Nemoto, S.; Shibata, K.

2016-12-01

Crucial virtues for operational space weather forecast are real-timeforecast ability, forecast precision and customizability to userneeds. The recent development of deep-learning makes it veryattractive to space weather, because (1) it learns gradually incomingdata, (2) it exhibits superior accuracy over conventional algorithmsin many fields, and (3) it makes the customization of the forecasteasier because it accepts raw images.However, the best deep-learning applications are only attainable bycareful human designers that understands both the mechanism of deeplearning and the application field. Therefore, we need to foster youngresearchers to enter the field of machine-learning aided forecast. So,we have held a seminar every Monday with undergraduate and graduatestudents from May to August 2016.We will review the current status of space weather science and theautomated real-time space weather forecast engine UFCORIN. Then, weintroduce the deep-learning space weather forecast environments wehave set up using Python and Chainer on students' laptop computers.We have started from simple image classification neural network, thenimplemented space-weather neural network that predicts future X-rayflux of the Sun based on the past X-ray lightcurve and magnetic fieldline-of-sight images.In order to perform each forecast faster, we have focused on simplelightcurve-to-lightcurve forecast, and performed comparative surveysby changing following parameters: The size and topology of the neural network Batchsize Neural network hyperparameters such as learning rates to optimize the preduction accuracy, and time for prediction.We have found how to design compact, fast but accurate neural networkto perform forecast. Our forecasters can perform predictionexperiment for four-year timespan in a few minutes, and achieveslog-scale errors of the order of 1. Our studies is ongoing, and inour talk we will review our progress till December.
The Changing Face of the of Former Soviet Cities: Elucidated by Remote Sensing and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Poghosyan, Armen

2017-04-01

Despite remote sensing of urbanization emerged as a powerful tool to acquire critical knowledge about urban growth and its effects on global environmental change, human-environment interface as well as environmentally sustainable urban development, there is lack of studies utilizing remote sensing techniques to investigate urbanization trends in the Post-Soviet states. The unique challenges accompanying the urbanization in the Post-Soviet republics combined with the expected robust urban growth in developing countries over the next several decades highlight the critical need for a quantitative assessment of the urban dynamics in the former Soviet states as they navigate towards a free market democracy. This study uses total of 32 Level-1 precision terrain corrected (L1T) Landsat scenes with 30-m resolution as well as further auxiliary population and economic data for ten cities distributed in nine former Soviet republics to quantify the urbanization patterns in the Post-Soviet region. Land cover in each urban center of this study was classified by using Support Vector Machine (SVM) learning algorithm with overall accuracies ranging from 87 % to 97 % for 29 classification maps over three time steps during the past twenty-five years in order to estimate quantities, trends and drivers of urban growth in the study area. The results demonstrated several spatial and temporal urbanization patterns observed across the Post-Soviet states and based on urban expansion rates the cities can be divided into two groups, fast growing and slow growing urban centers. The relatively fast-growing urban centers have an average urban expansion rate of about 2.8 % per year, whereas the slow growing cities have an average urban expansion rate of about 1.0 % per year. The total area of new land converted to urban environment ranged from as low as 26 km2 to as high as 780 km2 for the ten cities over the 1990 - 2015 period, while the overall urban land increase ranged from 11.3 % to 96.6 % over the study period. Thus, after some initial developments following the breakup of the Soviet Union the growth rate in the urban core decreased gradually constrained by the availability of suitable land, while the urban expansion rates in the outer peripheral region were characterized with a robust urban growth rates across the study area. The rapid urban expansion observed in the former Soviet cities impairs environmentally sustainable characteristics such as compactness, better integrated land uses with abundant parks and greenbelts, low social polarization, as well as reliable public transit systems in some urban centers after the disintegration of the Soviet Union. The urban expansion rates considerably outpaced the urban population growth rates in all ten cities during the last quarter of a century, thus indicating that the urban growth is becoming more expansive with all cities experiencing significant decreases in overall urban population densities.
Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning

NASA Astrophysics Data System (ADS)

Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H.

2017-05-01

We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling with disposable sensing chips and automated data acquisition has been developed. The prototype allows for fast, user-friendly sampling, which has made it possible to produce large datasets of colorimetric data for different target analytes in laboratory and simulated real-world application scenarios. To make use of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions. The robustness of the colorimetric sensor has been evaluated in a series of experiments focusing on the amphetamine pre-cursor phenylacetone as well as the improvised explosives pre-cursor hydrogen peroxide. The analysis demonstrates that the system is able to detect analytes in clean air and mixed with substances that occur naturally in real-world sampling scenarios. The technology under development in CRIM-TRACK has the potential as an effective tool to control trafficking of illegal drugs, explosive detection, or in other law enforcement applications.
NASA Tech Briefs, March 2005

NASA Technical Reports Server (NTRS)

2005-01-01

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.
C-FSCV: Compressive Fast-Scan Cyclic Voltammetry for Brain Dopamine Recording.

PubMed

Zamani, Hossein; Bahrami, Hamid Reza; Chalwadi, Preeti; Garris, Paul A; Mohseni, Pedram

2018-01-01

This paper presents a novel compressive sensing framework for recording brain dopamine levels with fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode. Termed compressive FSCV (C-FSCV), this approach compressively samples the measured total current in each FSCV scan and performs basic FSCV processing steps, e.g., background current averaging and subtraction, directly with compressed measurements. The resulting background-subtracted faradaic currents, which are shown to have a block-sparse representation in the discrete cosine transform domain, are next reconstructed from their compressively sampled counterparts with the block sparse Bayesian learning algorithm. Using a previously recorded dopamine dataset, consisting of electrically evoked signals recorded in the dorsal striatum of an anesthetized rat, the C-FSCV framework is shown to be efficacious in compressing and reconstructing brain dopamine dynamics and associated voltammograms with high fidelity (correlation coefficient, ), while achieving compression ratio, CR, values as high as ~ 5. Moreover, using another set of dopamine data recorded 5 minutes after administration of amphetamine (AMPH) to an ambulatory rat, C-FSCV once again compresses (CR = 5) and reconstructs the temporal pattern of dopamine release with high fidelity ( ), leading to a true-positive rate of 96.4% in detecting AMPH-induced dopamine transients.
Efficient Learning for the Poor: New Insights into Literacy Acquisition for Children

ERIC Educational Resources Information Center

Abadzi, Helen

2008-01-01

Reading depends on the speed of visual recognition and capacity of short-term memory. To understand a sentence, the mind must read it fast enough to capture it within the limits of the short-term memory. This means that children must attain a minimum speed of fairly accurate reading to understand a passage. Learning to read involves "tricking" the…
A Closer Look at Split Visual Attention in System- and Self-Paced Instruction in Multimedia Learning

ERIC Educational Resources Information Center

Schmidt-Weigand, Florian; Kohnert, Alfred; Glowalla, Ulrich

2010-01-01

Two experiments examined visual attention distribution in learning from text and pictures. Participants watched a 16-step multimedia instruction on the formation of lightning. In Experiment 1 (N=90) the instruction was system-paced (fast, medium, slow pace), while it was self-paced in Experiment 2 (N=31). In both experiments the text modality was…
Human Computer Interaction (HCI) and Internet Residency: Implications for Both Personal Life and Teaching/Learning

ERIC Educational Resources Information Center

Crearie, Linda

2016-01-01

Technological advances over the last decade have had a significant impact on the teaching and learning experiences students encounter today. We now take technologies such as Web 2.0, mobile devices, cloud computing, podcasts, social networking, super-fast broadband, and connectedness for granted. So what about the student use of these types of…
Mindgames: Altering Simulations Use at the Brigade Level

DTIC Science & Technology

2014-05-22

Kahneman, Daniel. Thinking, Fast and Slow. New York: Farrar, Strous, and Giroux, 2011. Kolb , David A. Experiential Learning : Experience as the...guidelines utilized in procuring these systems. Contemporary learning theories are discussed to provide a frame of reference to support the idea...and training theory involving both individuals and organizations offers reasons to either emphasize or change some training requirements in order to
Failure to Learn from Feedback underlies Word Learning Difficulties in Toddlers at Risk for Autism

ERIC Educational Resources Information Center

Bedford, R.; Gliga, T.; Frame, K.; Hudry, K.; Chandler, S.; Johnson, M. H.; Charman, T.

2013-01-01

Children's assignment of novel words to nameless objects, over objects whose names they know (mutual exclusivity; ME) has been described as a driving force for vocabulary acquisition. Despite their ability to use ME to fast-map words (Preissler & Carey, 2005), children with autism show impaired language acquisition. We aimed to address…
Functional Reorganization in the Developing Lexicon: Separable and Changing Influences of Lexical and Phonological Variables on Children's Fast-Mapping

ERIC Educational Resources Information Center

McKean, Cristina; Letts, Carolyn; Howard, David

2013-01-01

Neighbourhood Density (ND) and Phonotactic Probability (PP) influence word learning in children. This influence appears to change over development but the separate developmental trajectories of influence of PP and ND on word learning have not previously been mapped. This study examined the cross-sectional developmental trajectories of influence of…
Using Mobile-Assisted Exercises to Support Students' Vocabulary Skill Development

ERIC Educational Resources Information Center

Suwantarathip, Ornprapat; Orawiwatnakul, Wiwat

2015-01-01

The use of mobile phones for learning has become well-known and is widely adopted in many language classes. The use of SMS for transmitting short messages is a fast way of helping students to learn vocabulary. To address this issue, this study was conducted to examine the effects of mobile-assisted vocabulary exercises on vocabulary acquisition of…
Cognitive and Motivational Impacts of Learning Game Design on Middle School Children

ERIC Educational Resources Information Center

Akcaoglu, Mete

2013-01-01

In today`s complex and fast-evolving world, problem solving is an important skill to possess. For young children to be successful at their future careers, they need to have the "skill" and the "will" to solve complex problems that are beyond the well-defined problems that they learn to solve at schools. One promising approach…
More than Words: Fast Acquisition and Generalization of Orthographic Regularities during Novel Word Learning in Adults

ERIC Educational Resources Information Center

Laine, Matti; Polonyi, Tünde; Abari, Kálmán

2014-01-01

In literates, reading is a fundamental channel for acquiring new vocabulary both in the mother tongue and in foreign languages. By using an artificial language learning task, we examined the acquisition of novel written words and their embedded regularities (an orthographic surface feature and a syllabic feature) in three groups of university…
No evidence that 'fast-mapping' benefits novel learning in healthy Older adults.

PubMed

Greve, Andrea; Cooper, Elisa; Henson, Richard N

2014-07-01

Much evidence suggests that the Hippocampus is necessary for learning novel associations. Contrary to this, Sharon, Moscovitch, and Gilboa (2011) reported four amnesic patients with Hippocampal damage who maintained the capacity to learn novel object-name associations when trained with a 'fast-mapping' (FM) technique. This technique therefore potentially offers an alternative route for learning novel information in populations experiencing memory problems. We examined this potential in healthy ageing, by comparing 24 Older and 24 Young participants who completed a FM procedure very similar to Sharon et al. (2011). As expected, the Older group showed worse memory than the Young group under standard explicit encoding (EE) instructions. However, the Older group continued to show worse performance under the FM procedure, with no evidence that FM alleviated their memory deficit. Indeed, performance was worse for the FM than EE condition in both groups. Structural MRI scans confirmed reduced Hippocampal grey-matter volume in the Older group, which correlated with memory performance across both groups and both EE/FM conditions. We conclude FM does not help memory problems that occur with normal ageing, and discuss theoretical implications for memory theories. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Elevated fasting insulin levels increase the risk of abdominal obesity in Korean men.

PubMed

Park, Sung Keun; Oh, Chang-Mo; Jung, Taegi; Choi, Young-Jun; Chung, Ju Youn; Ryoo, Jae-Hong

2017-04-01

This study was designed to investigate whether an elevated fasting insulin level predicts abdominal obesity. A cohort study was conducted with 13,707 non-obese Korean men. They were categorized into 4 groups according to the quartile of fasting insulin level, and followed up from 2005 to 2010. Incidence rates of obesity were compared among the 4 groups during follow-up, and a Cox proportional hazards model was used to calculate hazard ratios (HRs) for abdominal obesity according to fasting insulin level. The overall incidence rate of obesity was 16.2%, but the rate increased in proportion to the fasting insulin level (quartiles 1-4: 9.8%, 12.4%, 16.9%, 25.5%, P<0.001). When HR of the 1st quartile was regarded as the reference, HRs for abdominal obesity increased proportionally to baseline fasting insulin level in an unadjusted model. However, after adjustment for covariates, including baseline waist circumference (WC), only in the quartile 4 group was the statistical significance of the association maintained [quartile 2-4; abdominal obesity: 0.89 (0.76-1.02), 1.00 (0.86-1.14) and 1.24 (1.08-1.43), P for trend <0.001]. Although the risk of incident abdominal obesity was highest in the group with the highest fasting insulin levels, an overall proportional relationship between fasting insulin level and incident abdominal obesity was not found. Additionally, this association was largely accounted for by baseline WC. Copyright © 2017 Elsevier B.V. All rights reserved.
Comparative Study on Prediction Effects of Short Fatigue Crack Propagation Rate by Two Different Calculation Methods

NASA Astrophysics Data System (ADS)

Yang, Bing; Liao, Zhen; Qin, Yahang; Wu, Yayun; Liang, Sai; Xiao, Shoune; Yang, Guangwu; Zhu, Tao

2017-05-01

To describe the complicated nonlinear process of the fatigue short crack evolution behavior, especially the change of the crack propagation rate, two different calculation methods are applied. The dominant effective short fatigue crack propagation rates are calculated based on the replica fatigue short crack test with nine smooth funnel-shaped specimens and the observation of the replica films according to the effective short fatigue cracks principle. Due to the fast decay and the nonlinear approximation ability of wavelet analysis, the self-learning ability of neural network, and the macroscopic searching and global optimization of genetic algorithm, the genetic wavelet neural network can reflect the implicit complex nonlinear relationship when considering multi-influencing factors synthetically. The effective short fatigue cracks and the dominant effective short fatigue crack are simulated and compared by the Genetic Wavelet Neural Network. The simulation results show that Genetic Wavelet Neural Network is a rational and available method for studying the evolution behavior of fatigue short crack propagation rate. Meanwhile, a traditional data fitting method for a short crack growth model is also utilized for fitting the test data. It is reasonable and applicable for predicting the growth rate. Finally, the reason for the difference between the prediction effects by these two methods is interpreted.
Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex.

PubMed

Kendrick, Keith M; Zhan, Yang; Fischer, Hanno; Nicol, Alister U; Zhang, Xuejuan; Feng, Jianfeng

2011-06-09

How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.
Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex

PubMed Central

2011-01-01

Background How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Results Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Conclusions Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs. PMID:21658251
Interaction between fed gastric media (Ensure Plus®) and different hypromellose based caffeine controlled release tablets: comparison and mechanistic study of caffeine release in fed and fasted media versus water using the USP dissolution apparatus 3.

PubMed

Franek, Frans; Holm, Per; Larsen, Frank; Steffansen, Bente

2014-01-30

The aim of the study was to investigate caffeine release in fed and fasted state media from three controlled release matrix tablets containing different HPMC viscosity grades. The biorelevant in vitro dissolution methods utilize the USP 3 dissolution apparatus and biorelevant media to simulate fed and fasted gastro-intestinal dissolution conditions. The effect of tablet reciprocation rate (dip speed) in dissolution media (10 and 15 dips per minute) and media (water, fed and fasted) on caffeine release rate from - and erosion rate of - 100, 4000 and 15,000 mPa s HPMC viscosity tablets was investigated using factorial designed experiments. Furthermore, the mechanism of release in Ensure Plus(®), a nutrition drink similar in composition to the FDA standard meal, was investigated by studying tablet swelling using texture analysis. Altering dip speed has negligible effect on release and erosion rates. Using fasted media instead of water slightly decreases caffeine release from 100 and 4000 mPa s HPMC viscosity tablets as well as erosion rates, while 15,000 mPa s tablets remain unaffected. Fed compared to fasted media decreases caffeine release rate, and the food effect is greater for the 100 mPa s viscosity tablets compared to the 4000 and 15,000 mPa s viscosity tablets. The investigation using texture analysis indicates that Ensure Plus(®) becomes rate-limiting for caffeine release from HPMC tablets by forming a hydrophobic barrier around the tablets. The barrier decreases tablet water permeation, which decreases erosion rate in 100 mPa s viscosity tablets, swelling in 15,000 mPa s viscosity tablets and caffeine release from both tablets. This observed interaction between Ensure Plus(®) and the HPMC tablets may translate into decreased drug release rate in the fed stomach, which may decrease the amount of drug available for absorption in the small intestine and thus reduce systemic drug exposure and maximum plasma concentration. Copyright © 2013 Elsevier B.V. All rights reserved.
A Machine Learning Classifier for Fast Radio Burst Detection at the VLBA

NASA Astrophysics Data System (ADS)

Wagstaff, Kiri L.; Tang, Benyang; Thompson, David R.; Khudikyan, Shakeh; Wyngaard, Jane; Deller, Adam T.; Palaniswamy, Divya; Tingay, Steven J.; Wayth, Randall B.

2016-08-01

Time domain radio astronomy observing campaigns frequently generate large volumes of data. Our goal is to develop automated methods that can identify events of interest buried within the larger data stream. The V-FASTR fast transient system was designed to detect rare fast radio bursts within data collected by the Very Long Baseline Array. The resulting event candidates constitute a significant burden in terms of subsequent human reviewing time. We have trained and deployed a machine learning classifier that marks each candidate detection as a pulse from a known pulsar, an artifact due to radio frequency interference, or a potential new discovery. The classifier maintains high reliability by restricting its predictions to those with at least 90% confidence. We have also implemented several efficiency and usability improvements to the V-FASTR web-based candidate review system. Overall, we found that time spent reviewing decreased and the fraction of interesting candidates increased. The classifier now classifies (and therefore filters) 80%-90% of the candidates, with an accuracy greater than 98%, leaving only the 10%-20% most promising candidates to be reviewed by humans.
eLearning courses.

PubMed

2006-02-01

FAST Healthcare, at www.fasthealthcare.com , provides work based interactive elearning courses that address national service framework standards, such as those for people with diabetes, older people and those with coronary heart disease.
Digestive state influences the heart rate hysteresis and rates of heat exchange in the varanid lizard Varanus rosenbergi.

PubMed

Clark, T D; Butler, P J; Frappell, P B

2005-06-01

To maximize the period where body temperature (Tb) exceeds ambient temperature (Ta), many reptiles have been reported to regulate heart rate (fH) and peripheral blood flow so that the rate of heat gain in a warming environment occurs more rapidly than the rate of heat loss in a cooling environment. It may be hypothesized that the rate of cooling, particularly at relatively cool Tbs, would be further reduced during postprandial periods when specific dynamic action (SDA) increases endogenous heat production (i.e. the heat increment of feeding). Furthermore, it may also be hypothesized that the increased perfusion of the gastrointestinal organs that occurs during digestion may limit peripheral blood flow and thus compromise the rate of heating. Finally, if the changes in fh are solely for the purpose of thermoregulation, there should be no associated changes in energy demand and, consequently, no hysteresis in the rate of oxygen consumption (V(O2)). To test these hypotheses, seven individual Varanus rosenbergi were heated and cooled between 19 degrees C and 35 degrees C following at least 8 days fasting and then approximately 25 h after consumption of a meal (mean 10% of fasted body mass). For a given Tb between the range of 19-35 degrees C, fh of fasting lizards was higher during heating than during cooling. Postprandial lizards also displayed a hysteresis in fh, although the magnitude was reduced in comparison with that of fasting lizards as a result of a higher fh during cooling in postprandial animals. Both for fasting and postprandial lizards, there was no hysteresis in V(O2) at any Tb throughout the range although, as a result of SDA, postprandial animals displayed a significantly higher V(O2) than fasting animals both during heating and during cooling at Tbs above 24 degrees C. The values of fh during heating at a given Tb were the same for fasting and postprandial animals, which, in combination with a slower rate of heating in postprandial animals, suggests that a prioritization of blood flow to the gastrointestinal organs during digestion is occurring at the expense of higher rates of heating. Additionally, postprandial lizards took longer to cool at Tbs below 23 degrees C, suggesting that the endogenous heat produced during digestion temporarily enhances thermoregulatory ability at lower temperatures, which would presumably assist V. rosenbergi during cooler periods in the natural environment by augmenting temperature-dependent physiological processes.
Measured thermal and fast neutron fluence rates for ATF-1 holders during ATR cycle 160A

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

Walker, B. J.; Miller, D. T.

This report contains the thermal (2200 m/s) and fast (E>1MeV) neutron fluence rate data for the ATF-1 holders located in core for ATR Cycle 160A which were measured by the Radiation Measurements Laboratory (RML).
David Bowie and the Art of Slow Innovation: A Fast-Second Winner Strategy for Biotechnology and Precision Medicine Global Development.

PubMed

Özdemir, Vural; Patrinos, George P

2017-11-01

Original ideas and innovation cannot always be ordered like a courier service and delivered fresh to our desk at 9 am. Yet, most creativity-based organizations, careers, and professions, science and biotechnology innovation included, emphasize the speed as the prevailing ideology. But a narrow focus on speed has several and overlooked shortcomings. For example, it does not offer the opportunity to draw from, and stitch together disparate concepts and practices for truly disruptive innovation. Preventing false starts, learning from others' or our own mistakes, and customizing innovations for local community needs are difficult in a speed-hungry innovation ecosystem. We introduce a new strategy, the Fast-Second Winner, specifically in relation to global development of biotechnologies and precision medicine. This à la carte global development strategy envisions a midstream entry into the innovation ecosystem. Moreover, we draw from the works of the late David Bowie who defied rigid classifications as an artist and prolific innovator, and introduce the concept and practice of slow innovation that bodes well with the Fast-Second Winner strategy. A type of slow innovation, the Fast-Second Winner is actually fast and sustainable in the long term, and efficient by reducing false starts in new precision medicine application contexts and geographies, learning from other innovators' failures, and shaping innovations for the local community needs. The establishment of Centers for Fast-Second Innovation (CFSIs), and their funding, for example, by crowdfunding and other innovative mechanisms, could be timely for omics and precision medicine global development. If precision medicine is about tailoring drug treatments and various health interventions to individuals, we suggest to start from tailoring new ideas, and focus not only on how much we innovate but also what and how we innovate. In principle, the Fast-Second Winner can be applied to omics and other biotechnology responsible development in medical practice or any field of applied innovation.
Two-day fasting evokes stress, but does not affect mood, brain activity, cognitive, psychomotor, and motor performance in overweight women.

PubMed

Solianik, Rima; Sujeta, Artūras

2018-02-15

The physiological, cognitive state, and motor behavior changes that occur during acute fasting are not completely understood. Thus, the aim of this study was to estimate the effect of 2-day total fasting on evoked stress, mood, brain activity, and cognitive, psychomotor, and motor function in overweight women. Eleven overweight women (body mass index above 25kg/m 2 ) aged 20-30 years were tested under two conditions allocated randomly: 2-day zero-calorie diet with water provided ad libitum and 2-day usual diet. One week before the experiment, aerobic fitness was evaluated. Subjective stress ratings in relation to the diet, autonomic function, prefrontal cortex activity, cognitive performance, psychomotor coordination, and grip strength were evaluated before and after each diet. The study demonstrated that fasting decreased log-transformed high-frequency (HF) power, without affecting heart rate. The relative maximum oxygen uptake was negatively correlated with subjective stress rating and changes in log-transformed HF. Fasting did not affect mood, brain activity, and cognitive, motor, and psychomotor performance. Thus, 2-day total fasting evoked moderate stress with a shift of the autonomic nervous system balance toward sympathetic activity in overweight women. Better aerobic endurance is likely to facilitate the capacity for dealing with acute fasting. Regardless of the evoked stress, cognitive state and motor behavior remained intact. Copyright © 2017 Elsevier B.V. All rights reserved.
A novel setup for wafer curvature measurement at very high heating rates.

PubMed

Islam, T; Zechner, J; Bernardoni, M; Nelhiebel, M; Pippan, R

2017-02-01

The curvature evolution of a thin film layer stack containing a top Al layer is measured during temperature cycles with very high heating rates. The temperature cycles are generated by means of programmable electrical power pulses applied to miniaturized polysilicon heater systems embedded inside a semiconductor chip and the curvature is measured by a fast wafer curvature measurement setup. Fast temperature cycles with heating duration of 100 ms are created to heat the specimen up to 270 °C providing an average heating rate of 2500 K/s. As a second approach, curvature measurement utilizing laser scanning Doppler vibrometry is also demonstrated which verifies the results obtained from the fast wafer curvature measurement setup. Film stresses calculated from the measured curvature values compare well to literature results, indicating that the new method can be used to measure curvature during fast temperature cycling.
A Reinforcement Learning Model Equipped with Sensors for Generating Perception Patterns: Implementation of a Simulated Air Navigation System Using ADS-B (Automatic Dependent Surveillance-Broadcast) Technology.

PubMed

Álvarez de Toledo, Santiago; Anguera, Aurea; Barreiro, José M; Lara, Juan A; Lizcano, David

2017-01-19

Over the last few decades, a number of reinforcement learning techniques have emerged, and different reinforcement learning-based applications have proliferated. However, such techniques tend to specialize in a particular field. This is an obstacle to their generalization and extrapolation to other areas. Besides, neither the reward-punishment (r-p) learning process nor the convergence of results is fast and efficient enough. To address these obstacles, this research proposes a general reinforcement learning model. This model is independent of input and output types and based on general bioinspired principles that help to speed up the learning process. The model is composed of a perception module based on sensors whose specific perceptions are mapped as perception patterns. In this manner, similar perceptions (even if perceived at different positions in the environment) are accounted for by the same perception pattern. Additionally, the model includes a procedure that statistically associates perception-action pattern pairs depending on the positive or negative results output by executing the respective action in response to a particular perception during the learning process. To do this, the model is fitted with a mechanism that reacts positively or negatively to particular sensory stimuli in order to rate results. The model is supplemented by an action module that can be configured depending on the maneuverability of each specific agent. The model has been applied in the air navigation domain, a field with strong safety restrictions, which led us to implement a simulated system equipped with the proposed model. Accordingly, the perception sensors were based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology, which is described in this paper. The results were quite satisfactory, and it outperformed traditional methods existing in the literature with respect to learning reliability and efficiency.
A Reinforcement Learning Model Equipped with Sensors for Generating Perception Patterns: Implementation of a Simulated Air Navigation System Using ADS-B (Automatic Dependent Surveillance-Broadcast) Technology

PubMed Central

Álvarez de Toledo, Santiago; Anguera, Aurea; Barreiro, José M.; Lara, Juan A.; Lizcano, David

2017-01-01

Over the last few decades, a number of reinforcement learning techniques have emerged, and different reinforcement learning-based applications have proliferated. However, such techniques tend to specialize in a particular field. This is an obstacle to their generalization and extrapolation to other areas. Besides, neither the reward-punishment (r-p) learning process nor the convergence of results is fast and efficient enough. To address these obstacles, this research proposes a general reinforcement learning model. This model is independent of input and output types and based on general bioinspired principles that help to speed up the learning process. The model is composed of a perception module based on sensors whose specific perceptions are mapped as perception patterns. In this manner, similar perceptions (even if perceived at different positions in the environment) are accounted for by the same perception pattern. Additionally, the model includes a procedure that statistically associates perception-action pattern pairs depending on the positive or negative results output by executing the respective action in response to a particular perception during the learning process. To do this, the model is fitted with a mechanism that reacts positively or negatively to particular sensory stimuli in order to rate results. The model is supplemented by an action module that can be configured depending on the maneuverability of each specific agent. The model has been applied in the air navigation domain, a field with strong safety restrictions, which led us to implement a simulated system equipped with the proposed model. Accordingly, the perception sensors were based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology, which is described in this paper. The results were quite satisfactory, and it outperformed traditional methods existing in the literature with respect to learning reliability and efficiency. PMID:28106849
A machine learning approach for viral genome classification.

PubMed

Remita, Mohamed Amine; Halioui, Ahmed; Malick Diouara, Abou Abdallah; Daigle, Bruno; Kiani, Golrokh; Diallo, Abdoulaye Baniré

2017-04-11

Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for specific well-studied family of viruses. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families. Here, we introduce a virus classification platform, CASTOR, based on machine learning methods. CASTOR is inspired by a well-known technique in molecular biology: restriction fragment length polymorphism (RFLP). It simulates, in silico, the restriction digestion of genomic material by different enzymes into fragments. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of human papillomaviruses (HPV), hepatitis B viruses (HBV) and human immunodeficiency viruses type 1 (HIV-1). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV-1 M subtyping, respectively. Furthermore, CASTOR shows a competitive performance compared to well-known HIV-1 specific classifiers (REGA and COMET) on whole genomes and pol fragments. The performance of CASTOR, its genericity and robustness could permit to perform novel and accurate large scale virus studies. The CASTOR web platform provides an open access, collaborative and reproducible machine learning classifiers. CASTOR can be accessed at http://castor.bioinfo.uqam.ca .
Fast adaptation of the internal model of gravity for manual interceptions: evidence for event-dependent learning.

PubMed

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2005-02-01

We studied how subjects learn to deal with two conflicting sensory environments as a function of the probability of each environment and the temporal distance between repeated events. Subjects were asked to intercept a visual target moving downward on a screen with randomized laws of motion. We compared five protocols that differed in the probability of constant speed (0g) targets and accelerated (1g) targets. Probability ranged from 9 to 100%, and the time interval between consecutive repetitions of the same target ranged from about 1 to 20 min. We found that subjects systematically timed their responses consistent with the assumption of gravity effects, for both 1 and 0g trials. With training, subjects rapidly adapted to 0g targets by shifting the time of motor activation. Surprisingly, the adaptation rate was independent of both the probability of 0g targets and their temporal distance. Very few 0g trials sporadically interspersed as catch trials during immersive practice with 1g trials were sufficient for learning and consolidation in long-term memory, as verified by retesting after 24 h. We argue that the memory store for adapted states of the internal gravity model is triggered by individual events and can be sustained for prolonged periods of time separating sporadic repetitions. This form of event-related learning could depend on multiple-stage memory, with exponential rise and decay in the initial stages followed by a sample-and-hold module.
Explaining postnatal growth plasticity in a generalist brood parasite

NASA Astrophysics Data System (ADS)

Remeš, Vladimír

2010-03-01

Selection of a particular host has clear consequences for the performance of avian brood parasites. Experimental studies showed that growth rate and fledging mass of brood parasites varied between host species independently of the original host species. Finding correlates of this phenotypic plasticity in growth is important for assessing adaptiveness and potential fitness consequences of host choice. Here, I analyzed the effects of several host characteristics on growth rate and fledging mass of the young of brown-headed cowbird ( Molothrus ater), a generalist, non-evicting brood parasite. Cowbird chicks grew better in fast-developing host species and reached higher fledging mass in large hosts with fast postnatal development. A potential proximate mechanism linking fast growth and high fledging mass of cowbird with fast host development is superior food supply in fast-developing foster species. So far, we know very little about the consequences of the great plasticity in cowbird growth for later performance of the adult parasite. Thus, cowbird species could become interesting model systems for investigating the role of plasticity and optimization in the evolution of growth rate in birds.
Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence.

PubMed

Sandino, Juan; Pegg, Geoff; Gonzalez, Felipe; Smith, Grant

2018-03-22

The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust ( Austropuccinia psidii ) on paperbark tea trees ( Melaleuca quinquenervia ) in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral image sensors, and data processing algorithms using machine learning. Imagery is acquired using a Headwall Nano-Hyperspec ® camera, orthorectified in Headwall SpectralView ® , and processed in Python programming language using eXtreme Gradient Boosting (XGBoost), Geospatial Data Abstraction Library (GDAL), and Scikit-learn third-party libraries. In total, 11,385 samples were extracted and labelled into five classes: two classes for deterioration status and three classes for background objects. Insights reveal individual detection rates of 95% for healthy trees, 97% for deteriorated trees, and a global multiclass detection rate of 97%. The methodology is versatile to be applied to additional datasets taken with different image sensors, and the processing of large datasets with freeware tools.
Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence

PubMed Central

2018-01-01

The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust (Austropuccinia psidii) on paperbark tea trees (Melaleuca quinquenervia) in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral image sensors, and data processing algorithms using machine learning. Imagery is acquired using a Headwall Nano-Hyperspec® camera, orthorectified in Headwall SpectralView®, and processed in Python programming language using eXtreme Gradient Boosting (XGBoost), Geospatial Data Abstraction Library (GDAL), and Scikit-learn third-party libraries. In total, 11,385 samples were extracted and labelled into five classes: two classes for deterioration status and three classes for background objects. Insights reveal individual detection rates of 95% for healthy trees, 97% for deteriorated trees, and a global multiclass detection rate of 97%. The methodology is versatile to be applied to additional datasets taken with different image sensors, and the processing of large datasets with freeware tools. PMID:29565822
A Fast Optimization Method for General Binary Code Learning.

PubMed

Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng

2016-09-22

Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

A study of adaptation mechanisms based on ABR recorded at high stimulation rate.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Alvarez, Isaac; Segura, Jose Carlos; Thornton, A Roger D; Sainz, Manuel; Vargas, Jose Luis

2014-04-01

This paper analyzes the fast and slow mechanisms of adaptation through a study of latencies and amplitudes on ABR recorded at high stimulation rates using the randomized stimulation and averaging (RSA) technique. The RSA technique allows a separate processing of auditory responses, and is used, in this study, to categorize responses according to the interstimulus interval (ISI) of their preceding stimulus. The fast and slow mechanisms of adaptation are analyzed by the separated responses methodology, whose underlying principles and mathematical basis are described in detail. The morphology of the ABR is influenced by both fast and slow mechanisms of adaptation. These results are consistent with previous animal studies based on spike rate. Both fast and slow mechanisms of adaptation are present in all subjects. In addition, the distribution of the jitter and the sequencing of the stimuli may be critical parameters when obtaining reliable ABRs. The separated responses methodology enables for the first time the analysis of the fast and slow mechanisms of adaptation in ABR obtained at stimulation rates greater than 100 Hz. The non-invasive nature of this methodology is appropriate for its use in humans. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Effect of Kampo medicine "Dai-kenchu-to" on microbiome in the intestine of the rats with fast stress.

PubMed

Yoshikawa, Kozo; Shimada, Mitsuo; Kuwahara, Tomomi; Hirakawa, Hideki; Kurita, Nobuhiro; Sato, Hirohiko; Utsunomiya, Tohru; Iwata, Takashi; Miyatani, Tomohiko; Higashijima, Jun; Kashihara, Hideya; Takasu, Chie; Matsumoto, Noriko; Nakayama-Imaohji, Haruyuki

2013-01-01

Diversity of gut microbiome has been recently reported to be lost in inflammatory bowel disease. We have previously reported that the Dai-kenchu-to (DKT) prevented the bacterial translocation through suppression of cytokine and apoptosis in rat's fast stress model. The aim of this study was to evaluate the effect of DKT on maintenance of microbial diversity in rat's intestine with inflammation. Wister rats were received the fast stress for 5 days. In DKT group, rats were administered with DKT (300 mg/kg/day) during the fast stress (DKT-group). The gut microbiomes were analyzed at before- and after- fast stress, and the effect of DKT for on microbial diversities of the gut were evaluated by the PCR-clone library method targeting the 16 S ribosomal RNA gene. In Control-group, Erysipelotrichaceae increased to 86% in after fast stress, OTU of before-fast stress was 111 and after fast stress was only 9 (changing rate: 58%). The diversity of microbiome was severely decreased. On the other hand, in DKT-group, diversity of microbiome was kept after fast stress (Lachnospiraceae: Ruminococcaceae: Coriobacteriales 54%, 22%, 5%), Operational taxonomic units of before fast stress was 52 and after fast stress was 55 (changing rate: 6%). Family Lachnospiraceae which includes butyrate-producing Clostridia (Clostridium IV and XIVa). DKT prevented the reduction of diversity of microbiome in rat's fast stress model. Our data suggested the new anti-inflammatory mechanism of DKT through gut microbiome.
FAST: FAST Analysis of Sequences Toolbox

PubMed Central

Lawrence, Travis J.; Kauffman, Kyle T.; Amrine, Katherine C. H.; Carper, Dana L.; Lee, Raymond S.; Becich, Peter J.; Canales, Claudia J.; Ardell, David H.

2015-01-01

FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought. PMID:26042145
Sharp rates of decay of solutions to the nonlinear fast diffusion equation via functional inequalities

PubMed Central

Vázquez, J. L.

2010-01-01

The goal of this paper is to state the optimal decay rate for solutions of the nonlinear fast diffusion equation and, in self-similar variables, the optimal convergence rates to Barenblatt self-similar profiles and their generalizations. It relies on the identification of the optimal constants in some related Hardy–Poincaré inequalities and concludes a long series of papers devoted to generalized entropies, functional inequalities, and rates for nonlinear diffusion equations. PMID:20823259
Scalloping minimization in deep Si etching on Unaxis DSE tools

NASA Astrophysics Data System (ADS)

Lai, Shouliang; Johnson, Dave J.; Westerman, Russ J.; Nolan, John J.; Purser, David; Devre, Mike

2003-01-01

Sidewall smoothness is often a critical requirement for many MEMS devices, such as microfludic devices, chemical, biological and optical transducers, while fast silicon etch rate is another. For such applications, the time division multiplex (TDM) etch processes, so-called "Bosch" processes are widely employed. However, in the conventional TDM processes, rough sidewalls result due to scallop formation. To date, the amplitude of the scalloping has been directly linked to the silicon etch rate. At Unaxis USA Inc., we have developed a proprietary fast gas switching technique that is effective for scalloping minimization in deep silicon etching processes. In this technique, process cycle times can be reduced from several seconds to as little as a fraction of second. Scallop amplitudes can be reduced with shorter process cycles. More importantly, as the scallop amplitude is progressively reduced, the silicon etch rate can be maintained relatively constant at high values. An optimized experiment has shown that at etch rate in excess of 7 μm/min, scallops with length of 116 nm and depth of 35 nm were obtained. The fast gas switching approach offers an ideal manufacturing solution for MEMS applications where extremely smooth sidewall and fast etch rate are crucial.
Mirror reversal and visual rotation are learned and consolidated via separate mechanisms: recalibrating or learning de novo?

PubMed

Telgen, Sebastian; Parvin, Darius; Diedrichsen, Jörn

2014-10-08

Motor learning tasks are often classified into adaptation tasks, which involve the recalibration of an existing control policy (the mapping that determines both feedforward and feedback commands), and skill-learning tasks, requiring the acquisition of new control policies. We show here that this distinction also applies to two different visuomotor transformations during reaching in humans: Mirror-reversal (left-right reversal over a mid-sagittal axis) of visual feedback versus rotation of visual feedback around the movement origin. During mirror-reversal learning, correct movement initiation (feedforward commands) and online corrections (feedback responses) were only generated at longer latencies. The earliest responses were directed into a nonmirrored direction, even after two training sessions. In contrast, for visual rotation learning, no dependency of directional error on reaction time emerged, and fast feedback responses to visual displacements of the cursor were immediately adapted. These results suggest that the motor system acquires a new control policy for mirror reversal, which initially requires extra processing time, while it recalibrates an existing control policy for visual rotations, exploiting established fast computational processes. Importantly, memory for visual rotation decayed between sessions, whereas memory for mirror reversals showed offline gains, leading to better performance at the beginning of the second session than in the end of the first. With shifts in time-accuracy tradeoff and offline gains, mirror-reversal learning shares common features with other skill-learning tasks. We suggest that different neuronal mechanisms underlie the recalibration of an existing versus acquisition of a new control policy and that offline gains between sessions are a characteristic of latter. Copyright © 2014 the authors 0270-6474/14/3413768-12$15.00/0.
A real-time phoneme counting algorithm and application for speech rate monitoring.

PubMed

Aharonson, Vered; Aharonson, Eran; Raichlin-Levi, Katia; Sotzianu, Aviv; Amir, Ofer; Ovadia-Blechman, Zehava

2017-03-01

Adults who stutter can learn to control and improve their speech fluency by modifying their speaking rate. Existing speech therapy technologies can assist this practice by monitoring speaking rate and providing feedback to the patient, but cannot provide an accurate, quantitative measurement of speaking rate. Moreover, most technologies are too complex and costly to be used for home practice. We developed an algorithm and a smartphone application that monitor a patient's speaking rate in real time and provide user-friendly feedback to both patient and therapist. Our speaking rate computation is performed by a phoneme counting algorithm which implements spectral transition measure extraction to estimate phoneme boundaries. The algorithm is implemented in real time in a mobile application that presents its results in a user-friendly interface. The application incorporates two modes: one provides the patient with visual feedback of his/her speech rate for self-practice and another provides the speech therapist with recordings, speech rate analysis and tools to manage the patient's practice. The algorithm's phoneme counting accuracy was validated on ten healthy subjects who read a paragraph at slow, normal and fast paces, and was compared to manual counting of speech experts. Test-retest and intra-counter reliability were assessed. Preliminary results indicate differences of -4% to 11% between automatic and human phoneme counting. Differences were largest for slow speech. The application can thus provide reliable, user-friendly, real-time feedback for speaking rate control practice. Copyright Â© 2017 Elsevier Inc. All rights reserved.
Modification Of Learning Rate With Lvq Model Improvement In Learning Backpropagation

NASA Astrophysics Data System (ADS)

Tata Hardinata, Jaya; Zarlis, Muhammad; Budhiarti Nababan, Erna; Hartama, Dedy; Sembiring, Rahmat W.

2017-12-01

One type of artificial neural network is a backpropagation, This algorithm trained with the network architecture used during the training as well as providing the correct output to insert a similar but not the same with the architecture in use at training.The selection of appropriate parameters also affects the outcome, value of learning rate is one of the parameters which influence the process of training, Learning rate affects the speed of learning process on the network architecture.If the learning rate is set too large, then the algorithm will become unstable and otherwise the algorithm will converge in a very long period of time.So this study was made to determine the value of learning rate on the backpropagation algorithm. LVQ models of learning rate is one of the models used in the determination of the value of the learning rate of the algorithm LVQ.By modifying this LVQ model to be applied to the backpropagation algorithm. From the experimental results known to modify the learning rate LVQ models were applied to the backpropagation algorithm learning process becomes faster (epoch less).
Genetic susceptibility to Gilbert's syndrome in a valencian population; efficacy of the fasting test.

PubMed

Torres, A K; Escartín, N; Monzó, C; Guzmán, C; Ferrer, I; González-Muñoz, C; Peña, P; Monzó, V; Marcaida, G; Rodríguez-López, R

To describe the populational distribution of the UGT1A1*28 variant (genetic variant code rs8175347) located in the promotor of the UGT gene and correlate its genotypes with the results of the fasting test, as well as its relationship with the biochemical disorder of Gilbert's syndrome (GS) in a Valencian population. We studied the prevalence of the genotypes (TA) 6/6 (TA) 6/7 and (TA) 7/7 of the deleterious variant rs8175347 in 144 patients with hyperbilirubinemia, 38 of whom had previously undergone the fasting test to diagnose GS, and in 150 control patients. By analysing the genomic region of the TATA box of the UGT1A1 gene promotor using Sanger sequencing, we established the correlation between the rs8175347 genotypes and the fasting test results and with the patients' biochemical disorders. The rate of heterozygosity of allele (TA) 7 in the control population was 32% and increased to 87.59% among the patients with suspected GS. The rate of genotype TA 7/7 was 81.94% among the patients with hyperbilirubinemia, compared with 11.33% in the control patients. The fasting test showed a 15.79% rate of false negatives and a 5.26% rate of false positives. The high frequency of allele (TA) 7 among the Valencian control population, almost double the 5% reported for European control patients, confirms the high rate of GS reported in the Spanish population, without observing significant differences between the geographical ends of the country. The efficacy and reliability of the fasting test for the diagnosis of GS is questionable. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Medicina Interna (SEMI). All rights reserved.
Assessing the Role of Place and Timing Cues in Coding Frequency and Amplitude Modulation as a Function of Age.

PubMed

Whiteford, Kelly L; Kreft, Heather A; Oxenham, Andrew J

2017-08-01

Natural sounds can be characterized by their fluctuations in amplitude and frequency. Ageing may affect sensitivity to some forms of fluctuations more than others. The present study used individual differences across a wide age range (20-79 years) to test the hypothesis that slow-rate, low-carrier frequency modulation (FM) is coded by phase-locked auditory-nerve responses to temporal fine structure (TFS), whereas fast-rate FM is coded via rate-place (tonotopic) cues, based on amplitude modulation (AM) of the temporal envelope after cochlear filtering. Using a low (500 Hz) carrier frequency, diotic FM and AM detection thresholds were measured at slow (1 Hz) and fast (20 Hz) rates in 85 listeners. Frequency selectivity and TFS coding were assessed using forward masking patterns and interaural phase disparity tasks (slow dichotic FM), respectively. Comparable interaural level disparity tasks (slow and fast dichotic AM and fast dichotic FM) were measured to control for effects of binaural processing not specifically related to TFS coding. Thresholds in FM and AM tasks were correlated, even across tasks thought to use separate peripheral codes. Age was correlated with slow and fast FM thresholds in both diotic and dichotic conditions. The relationship between age and AM thresholds was generally not significant. Once accounting for AM sensitivity, only diotic slow-rate FM thresholds remained significantly correlated with age. Overall, results indicate stronger effects of age on FM than AM. However, because of similar effects for both slow and fast FM when not accounting for AM sensitivity, the effects cannot be unambiguously ascribed to TFS coding.
Rate of renal function decline, race and referral to nephrology in a large cohort of primary care patients.

PubMed

Koraishy, Farrukh M; Hooks-Anderson, Denise; Salas, Joanne; Scherrer, Jeffrey F

2017-08-01

Late nephrology referral is associated with adverse outcomes especially among minorities. Research on the association of the rate of chronic kidney disease (CKD) progression with nephrology referral in white versus black patients is lacking. Compute the odds of nephrology referral in primary care and their associations with race and the rate of CKD progression. Electronic health record data were obtained from 2170 patients in primary care clinics in the Saint Louis metropolitan area with at least two estimated glomerular filtration rate (eGFR) values over a 7-year observation period. Fast CKD progression was defined as a decline in eGFR of ≥5 ml/min/1.73 m2/year. Logistic regression models were computed to measure the associations between eGFR progression, race and nephrology referral before and after adjusting for potential confounding factors. Nephrology referrals were significantly more prevalent among those with fast compared to slow progression (5.6 versus 2.0%, P < 0.0001), however, a majority of fast progressors were not referred. Fast CKD progression and black race were associated with increased odds of nephrology referral (OR = 2.74; 95% CI: 1.60-4.72 and OR = 2.42; 95% CI: 1.28-4.56, respectively). The interaction of race and eGFR progression in nephrology referral was found to be non-significant. Nephrology referrals are more common in fast CKD progression, but referrals are underutilized. Nephrology referral is more common among blacks but its' association with rate of decline does not differ by race. Further studies are required to investigate the benefit of early referral of patients at risk of fast CKD progression. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Impact of Ramadan fasting on glucose levels in women with gestational diabetes mellitus treated with diet alone or diet plus metformin: a continuous glucose monitoring study.

PubMed

Afandi, Bachar O; Hassanein, Mohamed M; Majd, Lina M; Nagelkerke, Nico J D

2017-01-01

Women with gestational diabetes mellitus (GDM) are categorized as at high risk for adverse events during Ramadan fasting. However, this is largely based on clinical opinion. In this study, we shed some light on what happens to glucose levels during Ramadan fasting. This is a prospective observational study. A total of 32 patients with GDM were recruited; 10 patients, treated with diet only (group 1), to observe their glucose levels before fasting and 22 patients who insisted on fasting the month of Ramadan, 13 treated with diet only (group 2) and nine treated with diet plus metformin 500 mg twice daily (group 3), to evaluate their glucose levels during fasting. Interstitial glucose was monitored in all by using the iPro2 Professional continuous glucose monitoring (CGM) system. Mean glucose level was 116±21 mg/dL (6.16±1.16 mmol/L), 106±9 mg/dL (5.88±0.49 mmol/L) and 99±7 mg/dL (5.49±0.34 mmol/L) in groups 1, 2 and 3, respectively. Patients in group 1 had the lowest rate of hypoglycemia (50%), followed by patients in group 2 (60%), whereas patients in group 3 had the highest rate of hypoglycemia (78%). CGM data indicates that Ramadan fasting in women with GDM treated with diet alone or with diet plus metformin was associated with lower mean glucose levels and higher rates of hypoglycemia when compared with non-fasting glucose levels. Women with GDM should be advised against fasting during Ramadan until further data is available.
Distinct Effect of Impact Rise Times on Immediate and Early Neuropathology After Brain Injury in Juvenile Rats

PubMed Central

Jayakumar, Archana; Pfister, Bryan J.; Santhakumar, Vijayalakshmi

2015-01-01

Traumatic brain injury (TBI) can occur from physical trauma from a wide spectrum of insults ranging from explosions to falls. The biomechanics of the trauma can vary in key features, including the rate and magnitude of the insult. Although the effect of peak injury pressure on neurological outcome has been examined in the fluid percussion injury (FPI) model, it is unknown whether differences in rate of rise of the injury waveform modify cellular and physiological changes after TBI. Using a programmable FPI device, we examined juvenile rats subjected to a constant peak pressure at two rates of injury: a standard FPI rate of rise and a faster rate of rise to the same peak pressure. Immediate postinjury assessment identified fewer seizures and relatively brief loss of consciousness after fast-rise injuries than after standard-rise injuries at similar peak pressures. Compared with rats injured at standard rise, fewer silver-stained injured neuronal profiles and degenerating hilar neurons were observed 4-6 hr after fast-rise FPI. However, 1 week postinjury, both fast- and standard-rise FPI resulted in hilar cell loss and enhanced perforant path-evoked granule cell field excitability compared with sham controls. Notably, the extent of neuronal loss and increase in dentate excitability were not different between rats injured at fast and standard rates of rise to peak pressure. Our data indicate that reduced cellular damage and improved immediate neurological outcome after fast rising primary concussive injuries mask the severity of the subsequent cellular and neurophysiological pathology and may be unreliable as a predictor of prognosis. PMID:24799156
Accelerating Decoding-Related Skills in Poor Readers Learning a Foreign Language: A Computer-Based Intervention

ERIC Educational Resources Information Center

Björn, Piia Maria; Leppänen, Paavo H. T.

2013-01-01

The results of Fast ForWord® training on English decoding-related skills were examined. Finnish fifth-grade students were identified as having reading fluency problems and poor skills in English as a foreign language learned at school and were randomly assigned to either a training group (TRG) or a control group. The TRG ("n"?=?13)…
Effect of Speaker Gaze on Word Learning in Fragile X Syndrome: A Comparison with Nonsyndromic Autism Spectrum Disorder

ERIC Educational Resources Information Center

Benjamin, David P.; McDuffie, Andrea S.; Thurman, Angela J.; Kover, Sara T.; Mastergeorge, Ann M.; Hagerman, Randi J.; Abbeduto, Leonard

2015-01-01

Purpose: This study examined use of a speaker's direction of gaze during word learning by boys with fragile X syndrome (FXS), boys with nonsyndromic autism spectrum disorder (ASD), and typically developing (TD) boys. Method: A fast-mapping task with follow-in and discrepant labeling conditions was administered. We expected that the use of speaker…
Exploring Technology-Enhanced Learning Using Google Glass to Offer Students a Unique Instructor's Point of View Live Laboratory Demonstration

ERIC Educational Resources Information Center

Man, Fung Fun

2016-01-01

Technology-enhanced learning (TEL) is fast gaining momentum among educational institutions all over the world. The usual way in which laboratory instructional videos are filmed takes the third-person view. However, such videos are not as realistic and sensorial. With the advent of Google Glass and GoPro cameras, a more personal and effective way…
World History and Global Consciousness: A Case Study in the Scholarship of Teaching and Learning

ERIC Educational Resources Information Center

Quirin, James A.

2009-01-01

World history has become part of the "revolution in historical studies" since the 1960s, and a fast-growing area of college teaching in recent years. This article reports the author's research on his own world history-based course at Fisk University under the rubric of the Scholarship of Teaching and Learning (SoTL). This SoTL research suggests…
Fast ForWord®: the birth of the neurocognitive training revolution.

PubMed

Tallal, Paula

2013-01-01

In 1996, I cofounded Scientific Learning Corporation (SLC) with Drs Michael Merzenich, William Jenkins, and Steve Miller. I coined the term "Cogniceutical" to describe the new type of company we envisioned. SLC was the first company cofounded by academic scientists with the mission of building neurocognitive interventions. Fast ForWord® is the registered trade name of the platform SLC built to translate basic neuroplasticity-based training research into clinical and educational products. Fast ForWord® was the first cognitive neurotherapeutic intervention, the first to be individually adaptive in real time, the first "brain fitness" program that collected data over the Internet, and the first to use computer gaming technologies to change brains and enhance human potential. We included lofty goals in our first business plan for SLC. These included: using neuroplasticity-based training to improve language, literacy, and other academic skills; helping seniors maintain and recover function; helping people learn English as a second language; helping patient populations with neurological or mental disorders. SLC's first focus became improving language and literacy. Mike, Bill, Steve, and I began this journey together in 1994 with a laboratory-based research study that included seven children. To date, over two million children in 46 countries have used Fast ForWord® products. On any given school day, approximately 60,000 children log in to train on 1 of 10 Fast ForWord Language, Literacy, or Reading programs. We did not know at the time that we were creating what became a "disruptive innovation." This chapter chronicles this transformational journey. © 2013 Elsevier B.V. All rights reserved.
Don’t speak too fast! Processing of fast rate speech in children with specific language impairment

PubMed Central

Bedoin, Nathalie; Krifi-Papoz, Sonia; Herbillon, Vania; Caillot-Bascoul, Aurélia; Gonzalez-Monge, Sibylle; Boulenger, Véronique

2018-01-01

Background Perception of speech rhythm requires the auditory system to track temporal envelope fluctuations, which carry syllabic and stress information. Reduced sensitivity to rhythmic acoustic cues has been evidenced in children with Specific Language Impairment (SLI), impeding syllabic parsing and speech decoding. Our study investigated whether these children experience specific difficulties processing fast rate speech as compared with typically developing (TD) children. Method Sixteen French children with SLI (8–13 years old) with mainly expressive phonological disorders and with preserved comprehension and 16 age-matched TD children performed a judgment task on sentences produced 1) at normal rate, 2) at fast rate or 3) time-compressed. Sensitivity index (d′) to semantically incongruent sentence-final words was measured. Results Overall children with SLI perform significantly worse than TD children. Importantly, as revealed by the significant Group × Speech Rate interaction, children with SLI find it more challenging than TD children to process both naturally or artificially accelerated speech. The two groups do not significantly differ in normal rate speech processing. Conclusion In agreement with rhythm-processing deficits in atypical language development, our results suggest that children with SLI face difficulties adjusting to rapid speech rate. These findings are interpreted in light of temporal sampling and prosodic phrasing frameworks and of oscillatory mechanisms underlying speech perception. PMID:29373610
Effects of chewing rate and reactive hyperemia on blood flow in denture-supporting mucosa during simulated chewing.

PubMed

Ogino, Takamichi; Ueda, Takayuki; Ogami, Koichiro; Koike, Takashi; Sakurai, Kaoru

2017-01-01

We examined how chewing rate and the extent of reactive hyperemia affect the blood flow in denture-supporting mucosa during chewing. The left palatal mucosa was loaded under conditions of simulated chewing or simulated clenching for 30s, and the blood flow during loading was recorded. We compared the relative blood flow during loading under conditions that recreated different chewing rates by combining duration of chewing cycle (DCC) and occlusal time (OT): fast chewing group, typical chewing group, slow chewing group and clenching group. The relationship between relative blood flow during simulated chewing and the extent of reactive hyperemia was also analyzed. When comparing the different chewing rate, the relative blood flow was highest in fast chewing rate, followed by typical chewing rate and slow chewing rate. Accordingly, we suggest that fast chewing increases the blood flow more than typical chewing or slow chewing. There was a significant correlation between the amount of blood flow during simulated chewing and the extent of reactive hyperemia. Within the limitations of this study, we concluded that slow chewing induced less blood flow than typical or fast chewing in denture-supporting mucosa and that people with less reactive hyperemia had less blood flow in denture-supporting mucosa during chewing. Copyright © 2016 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

A framework for plasticity implementation on the SpiNNaker neural architecture.

PubMed

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A; Furber, Steve B; Benosman, Ryad B

2014-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system.
Statistical interpretation of machine learning-based feature importance scores for biomarker discovery.

PubMed

Huynh-Thu, Vân Anh; Saeys, Yvan; Wehenkel, Louis; Geurts, Pierre

2012-07-01

Univariate statistical tests are widely used for biomarker discovery in bioinformatics. These procedures are simple, fast and their output is easily interpretable by biologists but they can only identify variables that provide a significant amount of information in isolation from the other variables. As biological processes are expected to involve complex interactions between variables, univariate methods thus potentially miss some informative biomarkers. Variable relevance scores provided by machine learning techniques, however, are potentially able to highlight multivariate interacting effects, but unlike the p-values returned by univariate tests, these relevance scores are usually not statistically interpretable. This lack of interpretability hampers the determination of a relevance threshold for extracting a feature subset from the rankings and also prevents the wide adoption of these methods by practicians. We evaluated several, existing and novel, procedures that extract relevant features from rankings derived from machine learning approaches. These procedures replace the relevance scores with measures that can be interpreted in a statistical way, such as p-values, false discovery rates, or family wise error rates, for which it is easier to determine a significance level. Experiments were performed on several artificial problems as well as on real microarray datasets. Although the methods differ in terms of computing times and the tradeoff, they achieve in terms of false positives and false negatives, some of them greatly help in the extraction of truly relevant biomarkers and should thus be of great practical interest for biologists and physicians. As a side conclusion, our experiments also clearly highlight that using model performance as a criterion for feature selection is often counter-productive. Python source codes of all tested methods, as well as the MATLAB scripts used for data simulation, can be found in the Supplementary Material.
A framework for plasticity implementation on the SpiNNaker neural architecture

PubMed Central

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A.; Furber, Steve B.; Benosman, Ryad B.

2015-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system. PMID:25653580
Mitochondrial oxidative phosphorylation efficiency is upregulated during fasting in two major oxidative tissues of ducklings.

PubMed

Monternier, Pierre-Axel; Teulier, Loïc; Drai, Jocelyne; Bourguignon, Aurore; Collin-Chavagnac, Delphine; Hervant, Frédéric; Rouanet, Jean-Louis; Roussel, Damien

2017-10-01

Fasted endothermic vertebrates must develop physiological responses to maximize energy conservation and survival. The aim of this study was to determine the effect of 1-wk. fasting in 5-wk. old ducklings (Cairina moschata) from whole-body resting metabolic rate and body temperature to metabolic phenotype of tissues and mitochondrial coupling efficiency. At the level of whole organism, the mass-specific metabolic rate of ducklings was decreased by 40% after 1-wk. of fasting, which was associated with nocturnal Tb declines and shallow diurnal hypothermia during fasting. At the cellular level, fasting induced a large reduction in liver, gastrocnemius (oxidative) and pectoralis (glycolytic) muscle masses together with a fuel selection towards lipid oxidation and ketone body production in liver and a lower glycolytic phenotype in skeletal muscles. At the level of mitochondria, fasting induced a reduction of oxidative phosphorylation activities and an up-regulation of coupling efficiency (+30% on average) in liver and skeletal muscles. The present integrative study shows that energy conservation in fasted ducklings is mainly achieved by an overall reduction in mitochondrial activity and an increase in mitochondrial coupling efficiency, which would, in association with shallow hypothermia, increase the conservation of endogenous fuel stores during fasting. Copyright © 2017 Elsevier Inc. All rights reserved.
Two fast and accurate heuristic RBF learning rules for data classification.

PubMed

Rouhani, Modjtaba; Javan, Dawood S

2016-03-01

This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. Copyright © 2015 Elsevier Ltd. All rights reserved.
Measured thermal and fast neutron fluence rates for ATF-1 holders during ATR cycle 158B/159A

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

Smith, Larry Don; Miller, David Torbet; Walker, Billy Justin

2016-11-01

This report contains the thermal (2200 m/s) and fast (E>1MeV) neutron fluence rate data for the ATF-1 holders located in core for ATR Cycle 158B/159A which were measured by the Radiation Measurements Laboratory (RML).
Semantic Maps Capturing Organization Knowledge in e-Learning

NASA Astrophysics Data System (ADS)

Mavridis, Androklis; Koumpis, Adamantios; Demetriadis, Stavros N.

e-learning, shows much promise in accessibility and opportunity to learn, due to its asynchronous nature and its ability to transmit knowledge fast and effectively. However without a universal standard for online learning and teaching, many systems are proclaimed as “e-learning-compliant”, offering nothing more than automated services for delivering courses online, providing no additional enhancement to reusability and learner personalization. Hence, the focus is not on providing reusable and learner-centered content, but on developing the technology aspects of e-learning. This current trend has made it crucial to find a more refined definition of what constitutes knowledge in the e-learning context. We propose an e-learning system architecture that makes use of a knowledge model to facilitate continuous dialogue and inquiry-based knowledge learning, by exploiting the full benefits of the semantic web as a medium capable for supplying the web with formalized knowledge.
Adaptation to Low Temperature Exposure Increases Metabolic Rates Independently of Growth Rates

PubMed Central

Williams, Caroline M.; Szejner-Sigal, Andre; Morgan, Theodore J.; Edison, Arthur S.; Allison, David B.; Hahn, Daniel A.

2016-01-01

Metabolic cold adaptation is a pattern where ectotherms from cold, high-latitude, or -altitude habitats have higher metabolic rates than ectotherms from warmer habitats. When found, metabolic cold adaptation is often attributed to countergradient selection, wherein short, cool growing seasons select for a compensatory increase in growth rates and development times of ectotherms. Yet, ectotherms in high-latitude and -altitude environments face many challenges in addition to thermal and time constraints on lifecycles. In addition to short, cool growing seasons, high-latitude and - altitude environments are characterized by regular exposure to extreme low temperatures, which cause ectotherms to enter a transient state of immobility termed chill coma. The ability to resume activity quickly after chill coma increases with latitude and altitude in patterns consistent with local adaptation to cold conditions. We show that artificial selection for fast and slow chill coma recovery among lines of the fly Drosophila melanogaster also affects rates of respiratory metabolism. Cold-hardy fly lines, with fast recovery from chill coma, had higher respiratory metabolic rates than control lines, with cold-susceptible slow-recovering lines having the lowest metabolic rates. Fast chill coma recovery was also associated with higher respiratory metabolism in a set of lines derived from a natural population. Although their metabolic rates were higher than control lines, fast-recovering cold-hardy lines did not have faster growth rates or development times than control lines. This suggests that raised metabolic rates in high-latitude and -altitude species may be driven by adaptation to extreme low temperatures, illustrating the importance of moving “Beyond the Mean”. PMID:27103615
Fermentation of Ammonia Fiber Expansion Treated and Untreated Barley Straw in a Rumen Simulation Technique Using Rumen Inoculum from Cattle with Slow versus Fast Rate of Fiber Disappearance.

PubMed

Griffith, Candace L; Ribeiro, Gabriel O; Oba, Masahito; McAllister, Tim A; Beauchemin, Karen A

2016-01-01

The purpose of this study was to determine the effect of rumen inoculum from heifers with fast vs. slow rate of in situ fiber digestion on the fermentation of complex versus easily digested fiber sources in the forms of untreated and Ammonia Fiber Expansion (AFEX) treated barley straw, respectively, using an artificial rumen simulation technique (Rusitec). In situ fiber digestion was measured in a previous study by incubating untreated barley straw in the rumen of 16 heifers fed a diet consisting of 700 g/kg barley straw and 300 g/kg concentrate. The two heifers with fastest rate of digestion (Fast ≥ 4.18% h -1 ) and the two heifers with the slowest rate of digestion (Slow ≤ 3.17% h -1 ) were chosen as inoculum donors for this study. Two Rusitec apparatuses each equipped with eight fermenters were used in a completely randomized block design with two blocks (apparatus) and four treatments in a 2 × 2 factorial arrangement of treatments (Fast or Slow rumen inoculum and untreated or AFEX treated straw). Fast rumen inoculum and AFEX straw both increased ( P < 0.05) disappearance of dry matter (DMD), organic matter, true DMD, neutral detergent fiber, acid detergent fiber, and nitrogen (N) with an interactive effect between the two ( P < 0.05). Fast rumen inoculum increased ( P > 0.05) methane production per gram of digested material for both untreated and AFEX straw, and reduced (interaction, P < 0.05) acetate: propionate ratio for untreated straw. Greater relative populations of Ruminococcus albus ( P < 0.05) and increased microbial N production ( P = 0.045) were observed in Fast rumen inoculum. AFEX straw in Fast inoculum had greater total bacterial populations than Slow, but for untreated straw this result was reversed (interaction, P = 0.013). These findings indicate that differences in microbial populations in rumen fluid contribute to differences in the capacity of rumen inoculum to digest fiber.
Tips to Make Fast Food Friendlier for Kids

MedlinePlus

... Hey Kids, Learn About Blood Sugar and Diabetes Teaching Gardens Teaching Gardens Recognition Teaching Gardens-See Our Gardens How to Get a Teaching Garden Teaching Gardens-Donate Teaching Gardens Photos and ...
Fast Forward: An Upskilling Programme for Ford Motor Company Foundry Workers.

ERIC Educational Resources Information Center

Cousin, Glynis; Pound, Gill

1991-01-01

The purpose of an upgrading program for British Ford Motor Company employees was getting trainees back into learning environments and improving communication, listening, calculation, reading, and cooperation. (SK)
Decodability of Reward Learning Signals Predicts Mood Fluctuations.

PubMed

Eldar, Eran; Roth, Charlotte; Dayan, Peter; Dolan, Raymond J

2018-05-07

Our mood often fluctuates without warning. Recent accounts propose that these fluctuations might be preceded by changes in how we process reward. According to this view, the degree to which reward improves our mood reflects not only characteristics of the reward itself (e.g., its magnitude) but also how receptive to reward we happen to be. Differences in receptivity to reward have been suggested to play an important role in the emergence of mood episodes in psychiatric disorders [1-16]. However, despite substantial theory, the relationship between reward processing and daily fluctuations of mood has yet to be tested directly. In particular, it is unclear whether the extent to which people respond to reward changes from day to day and whether such changes are followed by corresponding shifts in mood. Here, we use a novel mobile-phone platform with dense data sampling and wearable heart-rate and electroencephalographic sensors to examine mood and reward processing over an extended period of one week. Subjects regularly performed a trial-and-error choice task in which different choices were probabilistically rewarded. Subjects' choices revealed two complementary learning processes, one fast and one slow. Reward prediction errors [17, 18] indicative of these two processes were decodable from subjects' physiological responses. Strikingly, more accurate decodability of prediction-error signals reflective of the fast process predicted improvement in subjects' mood several hours later, whereas more accurate decodability of the slow process' signals predicted better mood a whole day later. We conclude that real-life mood fluctuations follow changes in responsivity to reward at multiple timescales. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.
The oxidative debt of fasting: evidence for short- to medium-term costs of advanced fasting in adult king penguins.

PubMed

Schull, Quentin; Viblanc, Vincent A; Stier, Antoine; Saadaoui, Hédi; Lefol, Emilie; Criscuolo, François; Bize, Pierre; Robin, Jean-Patrice

2016-10-15

In response to prolonged periods of fasting, animals have evolved metabolic adaptations helping to mobilize body reserves and/or reduce metabolic rate to ensure a longer usage of reserves. However, those metabolic changes can be associated with higher exposure to oxidative stress, raising the question of how species that naturally fast during their life cycle avoid an accumulation of oxidative damage over time. King penguins repeatedly cope with fasting periods of up to several weeks. Here, we investigated how adult male penguins deal with oxidative stress after an experimentally induced moderate fasting period (PII) or an advanced fasting period (PIII). After fasting in captivity, birds were released to forage at sea. We measured plasmatic oxidative stress on the same individuals at the start and end of the fasting period and when they returned from foraging at sea. We found an increase in activity of the antioxidant enzyme superoxide dismutase along with fasting. However, PIII individuals showed higher oxidative damage at the end of the fast compared with PII individuals. When they returned from re-feeding at sea, all birds had recovered their initial body mass and exhibited low levels of oxidative damage. Notably, levels of oxidative damage after the foraging trip were correlated to the rate of mass gain at sea in PIII individuals but not in PII individuals. Altogether, our results suggest that fasting induces a transitory exposure to oxidative stress and that effort to recover in body mass after an advanced fasting period may be a neglected carryover cost of fasting. © 2016. Published by The Company of Biologists Ltd.
Relationships between extraction and metabolism of glucose, blood flow, and tissue blood volume in regions of rat brain.

PubMed

Cremer, J E; Cunningham, V J; Seville, M P

1983-09-01

Studies were made on the relationships between the rate of glucose metabolism, the transport of glucose between plasma and brain, cerebral blood flow, and blood content. Conscious control rats were compared with rats with intense tremors induced with cismethrin. The influence of plasma glucose concentration was studied by fasting some animals overnight prior to the induction of tremors. Mean plasma glucose was 8.83 mM in controls, 12.57 mM in fed rats with tremors, and 4.94 mM in rats fasted overnight prior to induction of tremors. Of 12 brain regions studied, nine showed an increased rate of glucose utilization in both fed and fasted trembling rats. Cerebellum had the highest percentage increase (200%). Rates of unidirectional glucose influx in fed trembling rats were significantly greater than those in controls in eight regions. In fasted animals, rates were the same as in controls, except in cerebellum, where it was 1.6 times higher. These high rates of glucose influx at low plasma glucose concentrations were indicative of a change in kinetic parameters of glucose transport. Unidirectional glucose influx rates were transformed to estimates of maximal transport rates (Tmax), based on the Michaelis-Menten equation. Average plasma glucose concentrations in regional capillaries (c) were calculated and shown to be maintained at values close to arterial plasma glucose concentrations (Ca), in all brain regions of each group. In trembling rats, Tmax for each brain region was higher than that in controls. In fasted rats with tremors, Tmax was higher in several brain regions than in fed rats. Tmax in cerebellum was 3.37, 4.71, and 7.89 mumol g-1 min-1 in control, fed trembling, and fasted trembling rats, respectively. Blood flow increased significantly in all regions in rats with tremors and was higher in fasted than in fed animals. There was only a weak correlation between blood flow and Tmax. Blood content of several regions increased in rats with tremors, and there was a strong correlation between Tmax and tissue blood volume. Results are consistent with localized regulatory links between blood flow, capillary surface area, and glucose transport in response to metabolic demand and hypoglycaemia. These involve changes in the linear velocity of blood through capillaries and in the extent of capillary recruitment.
Transfer of piano practice in fast performance of skilled finger movements.

PubMed

Furuya, Shinichi; Nakamura, Ayumi; Nagata, Noriko

2013-11-01

Transfer of learning facilitates the efficient mastery of various skills without practicing all possible sensory-motor repertoires. The present study assessed whether motor practice at a submaximal speed, which is typical in sports and music performance, results in an increase in a maximum speed of finger movements of trained and untrained skills. Piano practice of sequential finger movements at a submaximal speed over days progressively increased the maximum speed of trained movements. This increased maximum speed of finger movements was maintained two months after the practice. The learning transferred within the hand to some extent, but not across the hands. The present study confirmed facilitation of fast finger movements following a piano practice at a submaximal speed. In addition, the findings indicated the intra-manual transfer effects of piano practice on the maximum speed of skilled finger movements.
Relationship of /sup 65/Zn absorption kinetics to intestinal metallothionein in rats: effects of zinc depletion and fasting

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

Hoadley, J.E.; Leinart, A.S.; Cousins, R.J.

1988-04-01

Intestinal 65Zn transport and metallothionein levels were examined in rats fed zinc-adequate and zinc-deficient diets and in rats subjected to an overnight fast. 65Zn uptake by intestines perfused with 1.5 microM 65Zn was greater in both zinc-deficient and fasted groups than in the control group. Mucosal retention of 65Zn was also greater in the zinc-deficient group but not in the fasted group. The greater 65Zn uptake in the fasted group was associated with a compartment that readily released 65Zn back into the lumen. Kinetic analysis of the rate of 65Zn transfer to the vascular space (absorption) showed that 65Zn absorptionmore » involved approximately 3% of mucosal 65Zn in a 40-min perfusion period. The half-life (t1/2) of this mucosal 65Zn rapid transport pool corresponded directly to changes in intestinal metallothionein levels. Both metallothionein and t1/2 were higher in the fasted group and lower in the zinc-deficient group than in controls. While the rate of 65Zn transport from this rapid transport pool decreased with increasing metallothionein level, the predicted pool size increased when the metallothionein level was elevated by fasting. These results indicate that the rate of zinc absorption is inversely related to intestinal metallothionein levels, but the portion of mucosal 65Zn available for absorption is directly related to intestinal metallothionein.« less
Long-term fasting decreases mitochondrial avian UCP-mediated oxygen consumption in hypometabolic king penguins.

PubMed

Rey, Benjamin; Halsey, Lewis G; Dolmazon, Virginie; Rouanet, Jean-Louis; Roussel, Damien; Handrich, Yves; Butler, Patrick J; Duchamp, Claude

2008-07-01

In endotherms, regulation of the degree of mitochondrial coupling affects cell metabolic efficiency. Thus it may be a key contributor to minimizing metabolic rate during long periods of fasting. The aim of the present study was to investigate whether variation in mitochondrial avian uncoupling proteins (avUCP), as putative regulators of mitochondrial oxidative phosphorylation, may contribute to the ability of king penguins (Aptenodytes patagonicus) to withstand fasting for several weeks. After 20 days of fasting, king penguins showed a reduced rate of whole animal oxygen consumption (Vo2; -33%) at rest, together with a reduced abundance of avUCP and peroxisome proliferator-activated receptor-gamma coactivator-1alpha (PGC1-alpha) mRNA in pectoralis muscle (-54%, -36%, respectively). These parameters were restored after the birds had been refed for 3 days. Furthermore, in recently fed, but not in fasted penguins, isolated muscle mitochondria showed a guanosine diphosphate-inhibited, fatty acid plus superoxide-activated respiration, indicating the presence of a functional UCP. It was calculated that variation in mitochondrial UCP-dependent respiration in vitro may contribute to nearly 20% of the difference in resting Vo2 between fed or refed penguins and fasted penguins measured in vivo. These results suggest that the lowering of avUCP activity during periods of long-term energetic restriction may contribute to the reduction in metabolic rate and hence the ability of king penguins to face prolonged periods of fasting.
Long-term fasting decreases mitochondrial avian UCP-mediated oxygen consumption in hypometabolic king penguins

PubMed Central

Rey, Benjamin; Halsey, Lewis G.; Dolmazon, Virginie; Rouanet, Jean-Louis; Roussel, Damien; Handrich, Yves; Butler, Patrick J.; Duchamp, Claude

2008-01-01

In endotherms, regulation of the degree of mitochondrial coupling affects cell metabolic efficiency. Thus it may be a key contributor to minimizing metabolic rate during long periods of fasting. The aim of the present study was to investigate whether variation in mitochondrial avian uncoupling proteins (avUCP), as putative regulators of mitochondrial oxidative phosphorylation, may contribute to the ability of king penguins (Aptenodytes patagonicus) to withstand fasting for several weeks. After 20 days of fasting, king penguins showed a reduced rate of whole animal oxygen consumption (V̇o2; −33%) at rest, together with a reduced abundance of avUCP and peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1-α) mRNA in pectoralis muscle (−54%, −36%, respectively). These parameters were restored after the birds had been refed for 3 days. Furthermore, in recently fed, but not in fasted penguins, isolated muscle mitochondria showed a guanosine diphosphate-inhibited, fatty acid plus superoxide-activated respiration, indicating the presence of a functional UCP. It was calculated that variation in mitochondrial UCP-dependent respiration in vitro may contribute to nearly 20% of the difference in resting V̇o2 between fed or refed penguins and fasted penguins measured in vivo. These results suggest that the lowering of avUCP activity during periods of long-term energetic restriction may contribute to the reduction in metabolic rate and hence the ability of king penguins to face prolonged periods of fasting. PMID:18495832
The orexin component of fasting triggers memory processes underlying conditioned food selection in the rat.

PubMed

Ferry, Barbara; Duchamp-Viret, Patricia

2014-03-14

To test the selectivity of the orexin A (OXA) system in olfactory sensitivity, the present study compared the effects of fasting and of central infusion of OXA on the memory processes underlying odor-malaise association during the conditioned odor aversion (COA) paradigm. Animals implanted with a cannula in the left ventricle received ICV infusion of OXA or artificial cerebrospinal fluid (ACSF) 1 h before COA acquisition. An additional group of intact rats were food-deprived for 24 h before acquisition. Results showed that the increased olfactory sensitivity induced by fasting and by OXA infusion was accompanied by enhanced COA performance. The present results suggest that fasting-induced central OXA release influenced COA learning by increasing not only olfactory sensitivity, but also the memory processes underlying the odor-malaise association.
Fast neutron irradiation deteriorates hippocampus-related memory ability in adult mice.

PubMed

Yang, Miyoung; Kim, Hwanseong; Kim, Juhwan; Kim, Sung-Ho; Kim, Jong-Choon; Bae, Chun-Sik; Kim, Joong-Sun; Shin, Taekyun; Moon, Changjong

2012-03-01

Object recognition memory and contextual fear conditioning task performance in adult C57BL/6 mice exposed to cranial fast neutron irradiation (0.8 Gy) were examined to evaluate hippocampus-related behavioral dysfunction following acute exposure to relatively low doses of fast neutrons. In addition, hippocampal neurogenesis changes in adult murine brain after cranial irradiation were analyzed using the neurogenesis immunohistochemical markers Ki-67 and doublecortin (DCX). In the object recognition memory test and contextual fear conditioning, mice trained 1 and 7 days after irradiation displayed significant memory deficits compared to the sham-irradiated controls. The number of Ki-67- and DCX-positive cells decreased significantly 24 h post-irradiation. These results indicate that acute exposure of the adult mouse brain to a relatively low dose of fast neutrons interrupts hippocampal functions, including learning and memory, possibly by inhibiting neurogenesis.

The orexin component of fasting triggers memory processes underlying conditioned food selection in the rat

PubMed Central

Ferry, Barbara; Duchamp-Viret, Patricia

2014-01-01

To test the selectivity of the orexin A (OXA) system in olfactory sensitivity, the present study compared the effects of fasting and of central infusion of OXA on the memory processes underlying odor–malaise association during the conditioned odor aversion (COA) paradigm. Animals implanted with a cannula in the left ventricle received ICV infusion of OXA or artificial cerebrospinal fluid (ACSF) 1 h before COA acquisition. An additional group of intact rats were food-deprived for 24 h before acquisition. Results showed that the increased olfactory sensitivity induced by fasting and by OXA infusion was accompanied by enhanced COA performance. The present results suggest that fasting-induced central OXA release influenced COA learning by increasing not only olfactory sensitivity, but also the memory processes underlying the odor–malaise association. PMID:24634353
Vanishing points detection using combination of fast Hough transform and deep learning

NASA Astrophysics Data System (ADS)

Sheshkus, Alexander; Ingacheva, Anastasia; Nikolaev, Dmitry

2018-04-01

In this paper we propose a novel method for vanishing points detection based on convolutional neural network (CNN) approach and fast Hough transform algorithm. We show how to determine fast Hough transform neural network layer and how to use it in order to increase usability of the neural network approach to the vanishing point detection task. Our algorithm includes CNN with consequence of convolutional and fast Hough transform layers. We are building estimator for distribution of possible vanishing points in the image. This distribution can be used to find candidates of vanishing point. We provide experimental results from tests of suggested method using images collected from videos of road trips. Our approach shows stable result on test images with different projective distortions and noise. Described approach can be effectively implemented for mobile GPU and CPU.
Sleep and satisfaction in 8- and 12-h forward-rotating shift systems: Industrial employees prefer 12-h shifts.

PubMed

Karhula, Kati; Härmä, Mikko; Ropponen, Annina; Hakola, Tarja; Sallinen, Mikael; Puttonen, Sampsa

2016-01-01

Twelve-hour shift systems have become more popular in industry. Survey data of shift length, shift rotation speed, self-rated sleep, satisfaction and perceived health were investigated for the associations among 599 predominantly male Finnish industrial employees. The studied forward-rotating shift systems were 12-h fast (12fast, DDNN------, n = 268), 8-h fast (8fast, MMEENN----, n = 161) and 8-h slow (8slow, MMMM-EEEE-NNNN, n = 170). Satisfaction with shift system differed between the groups (p < 0.01) after controlling for age, gender, shift work experience and self-rated stress. In the 12fast, 98% of employees were satisfied with their shift system (75% 8fast, 54% 8slow). Negative effects on sleep and alertness were rare (8%) in the 12fast group (53% 8fast, 66% 8 slow, p < 0.01) and self-reported sleep difficulties were less frequent than in the 8fast and 8slow groups (8%, 27%, 41%, respectively, p < 0.01). The self-reported average sleep duration (12fast 7:50, 8fast 7:24, 8slow 7:15, p < 0.01), and shift-specific sleep before and between morning shifts and after first night shift were longer in the 12fast group. Perceived negative effects of the current shift system on general health (12fast 4%, 8fast 30%, 8slow 41%, p < 0.001) and work-life balance (12fast 8%, 8fast 52%, 8slow 63%, p < 0.001) differed strongly between the groups. In conclusion, the perceived effects of shift work were dependent on both shift length and shift rotation speed: employees in the 12-h rapidly forward-rotating shift system were most satisfied, perceived better work-life balance and slept better than the employees in the 8fast or especially the employees in the 8-h slowly rotating systems.
A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis.

PubMed

Liang, Liang; Liu, Minliang; Martin, Caitlin; Sun, Wei

2018-01-01

Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis. © 2018 The Author(s).
Fast Learning for Immersive Engagement in Energy Simulations

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

Bush, Brian W; Bugbee, Bruce; Gruchalla, Kenny M

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximationmore » methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.« less
A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.
Ultra High Strain Rate Nanoindentation Testing.

PubMed

Sudharshan Phani, Pardhasaradhi; Oliver, Warren Carl

2017-06-17

Strain rate dependence of indentation hardness has been widely used to study time-dependent plasticity. However, the currently available techniques limit the range of strain rates that can be achieved during indentation testing. Recent advances in electronics have enabled nanomechanical measurements with very low noise levels (sub nanometer) at fast time constants (20 µs) and high data acquisition rates (100 KHz). These capabilities open the doors for a wide range of ultra-fast nanomechanical testing, for instance, indentation testing at very high strain rates. With an accurate dynamic model and an instrument with fast time constants, step load tests can be performed which enable access to indentation strain rates approaching ballistic levels (i.e., 4000 1/s). A novel indentation based testing technique involving a combination of step load and constant load and hold tests that enables measurement of strain rate dependence of hardness spanning over seven orders of magnitude in strain rate is presented. A simple analysis is used to calculate the equivalent uniaxial response from indentation data and compared to the conventional uniaxial data for commercial purity aluminum. Excellent agreement is found between the indentation and uniaxial data over several orders of magnitude of strain rate.
Heart Rate Effects of Intraosseous Injections Using Slow and Fast Rates of Anesthetic Solution Deposition

PubMed Central

Susi, Louis; Reader, Al; Nusstein, John; Beck, Mike; Weaver, Joel; Drum, Melissa

2008-01-01

The authors, using a crossover design, randomly administered, in a single-blind manner, 3 primary intraosseous injections to 61 subjects using: the Wand local anesthetic system at a deposition rate of 45 seconds (fast injection); the Wand local anesthetic system at a deposition rate of 4 minutes and 45 seconds (slow injection); a conventional syringe injection at a deposition rate of 4 minutes and 45 seconds (slow injection), in 3 separate appointments spaced at least 3 weeks apart. A pulse oximeter measured heart rate (pulse). The results demonstrated the mean maximum heart rate was statistically higher with the fast intraosseous injection (average 21 to 28 beats/min increase) than either of the 2 slow intraosseous injections (average 10 to 12 beats/min increase). There was no statistically significant difference between the 2 slow injections. We concluded that an intraosseous injection of 1.4 mL of 2% lidocaine with 1 : 100,000 epinephrine with the Wand at a 45-second rate of anesthetic deposition resulted in a significantly higher heart rate when compared with a 4-minute and 45-second anesthetic solution deposition using either the Wand or traditional syringe. PMID:18327970
Heart rate effects of intraosseous injections using slow and fast rates of anesthetic solution deposition.

PubMed

Susi, Louis; Reader, Al; Nusstein, John; Beck, Mike; Weaver, Joel; Drum, Melissa

2008-01-01

The authors, using a crossover design, randomly administered, in a single-blind manner, 3 primary intraosseous injections to 61 subjects using: the Wand local anesthetic system at a deposition rate of 45 seconds (fast injection); the Wand local anesthetic system at a deposition rate of 4 minutes and 45 seconds (slow injection); a conventional syringe injection at a deposition rate of 4 minutes and 45 seconds (slow injection), in 3 separate appointments spaced at least 3 weeks apart. A pulse oximeter measured heart rate (pulse). The results demonstrated the mean maximum heart rate was statistically higher with the fast intraosseous injection (average 21 to 28 beats/min increase) than either of the 2 slow intraosseous injections (average 10 to 12 beats/min increase). There was no statistically significant difference between the 2 slow injections. We concluded that an intraosseous injection of 1.4 mL of 2% lidocaine with 1 : 100,000 epinephrine with the Wand at a 45-second rate of anesthetic deposition resulted in a significantly higher heart rate when compared with a 4-minute and 45-second anesthetic solution deposition using either the Wand or traditional syringe.
Fast magnetic reconnection with large guide fields

DOE PAGES

Stanier, A.; Simakov, Andrei N.; Chacón, L.; ...

2015-01-09

We domonstrate, using two-fluid simulations, that low-βmagnetic reconnection remains fast, regardless of the presence of fast dispersive waves, which have been previously suggested to play a critical role. In order to understand these results, a discrete model is constructed that offers scaling relationships for the reconnection rate and dissipation region (DR) thickness in terms of the upstream magnetic field and DR length. Moreover, we verify these scalings numerically and show how the DR self-adjusts to process magnetic flux at the same rate that it is supplied to a larger region where two-fluid effects become important. The rate is therefore independentmore » of the DR physics and is in good agreement with kinetic results.« less
Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.

PubMed

Jepma, Marieke; Murphy, Peter R; Nassar, Matthew R; Rangel-Gomez, Mauricio; Meeter, Martijn; Nieuwenhuis, Sander

2016-10-01

Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.
Bilingualism with and without CLIL, a Double-Edged Sword: Comparing Bilingual and Non Bilingual Young Learners' Beliefs about EFL and Science Learning

ERIC Educational Resources Information Center

Sandoval Brotons, Alfonso Victor

2015-01-01

Bilingualism and its reference methodology: CLIL are spreading at a very fast pace all through educative systems from some years on. The young status of bilingual programmes leads to little research about how bilingualism is influencing real learning contexts and which factors play important roles in that influence. In this way, this study aims to…
Fast Transients: Closing the Loop on Air Force Professional Military Education

DTIC Science & Technology

2013-02-19

esprit de corps, and offer experiential leadership opportunities unique to the military.5 Since Colonel Ritchey’s inception, technological advances have...the technology that delivers it, and while PME students and instructors will be geographically separated, it is important to note that the... technology of distance learning should not replace the instructor. Hence, any PME distance learning courseware must be more than a fire-and-forget system. As
Supporting self and others: from staff nurse to nurse consultant. Part 2: learning from experience.

PubMed

Fowler, John

This series of articles explores various ways of supporting staff who work in the fast-moving and ever-changing health service. In the first article, John Fowler, an experienced nursing lecturer, author and consultant examined the importance of developing a supportive working culture. Here in the second part of the series, he looks at the supportive effects of learning from experience.
Binary Multidimensional Scaling for Hashing.

PubMed

Huang, Yameng; Lin, Zhouchen

2017-10-04

Hashing is a useful technique for fast nearest neighbor search due to its low storage cost and fast query speed. Unsupervised hashing aims at learning binary hash codes for the original features so that the pairwise distances can be best preserved. While several works have targeted on this task, the results are not satisfactory mainly due to the oversimplified model. In this paper, we propose a unified and concise unsupervised hashing framework, called Binary Multidimensional Scaling (BMDS), which is able to learn the hash code for distance preservation in both batch and online mode. In the batch mode, unlike most existing hashing methods, we do not need to simplify the model by predefining the form of hash map. Instead, we learn the binary codes directly based on the pairwise distances among the normalized original features by Alternating Minimization. This enables a stronger expressive power of the hash map. In the online mode, we consider the holistic distance relationship between current query example and those we have already learned, rather than only focusing on current data chunk. It is useful when the data come in a streaming fashion. Empirical results show that while being efficient for training, our algorithm outperforms state-of-the-art methods by a large margin in terms of distance preservation, which is practical for real-world applications.
Short-term desensitization of fast escape behavior associated with suppression of Mauthner cell activity in larval zebrafish.

PubMed

Takahashi, Megumi; Inoue, Maya; Tanimoto, Masashi; Kohashi, Tsunehiko; Oda, Yoichi

2017-08-01

Escape is among the simplest animal behaviors employed to study the neural mechanisms underlying learning. Teleost fishes exhibit behavioral learning of fast escape initiated with a C-shaped body bend (C-start). C-starts are subdivided into short-latency (SLC) and long-latency (LLC) types in larval zebrafish. Whether these two can be separately modified, and the neural correlates of this modification, however, remains undetermined. We thus performed Ca 2+ imaging of Mauthner (M-) cells, a pair of giant hindbrain neurons constituting a core element of SLC circuit, during behavioral learning in larval zebrafish. The Ca 2+ response corresponding to a single spiking of the M-cells was coupled with SLCs but not LLCs. Conditioning with a repeated weak sound at subthreshold intensity to elicit C-starts selectively suppressed SLC occurrence for 10min without affecting LLC responsiveness. The short-term desensitization of SLC was associated with the suppression of M-cell activity, suggesting that changes in single neuron responsiveness mediate behavioral learning. The conditioning did not affect the acoustically evoked mechanotransduction of inner ear hair cells, further suggesting plastic change in transmission efficacy within the auditory input circuit between the hair cells and the M-cell. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.
Longitudinal Evaluation of Myocardial Fatty Acid and Glucose Metabolism in Fasted and Nonfasted Spontaneously Hypertensive Rats Using MicroPET/CT

DOE PAGES

Huber, Jennifer S.; Hernandez, Andrew M.; Janabi, Mustafa; ...

2017-09-06

Using longitudinal micro positron emission tomography (microPET)/computed tomography (CT) studies, we quantified changes in myocardial metabolism and perfusion in spontaneously hypertensive rats (SHRs), a model of left ventricular hypertrophy (LVH). Fatty acid and glucose metabolism were quantified in the hearts of SHRs and Wistar-Kyoto (WKY) normotensive rats using long-chain fatty acid analog 18F-fluoro-6-thia heptadecanoic acid ( 18F-FTHA) and glucose analog 18F-fluorodeoxyglucose ( 18F-FDG) under normal or fasting conditions. We also used 18F-fluorodihydrorotenol ( 18F-FDHROL) to investigate perfusion in their hearts without fasting. Rats were imaged at 4 or 5 times over their life cycle. Compartment modeling was used to estimatemore » the rate constants for the radiotracers. Blood samples were obtained and analyzed for glucose and free fatty acid concentrations. SHRs demonstrated no significant difference in 18F-FDHROL wash-in rate constant (P = .1) and distribution volume (P = .1), significantly higher 18F-FDG myocardial influx rate constant (P = 4×10 –8), and significantly lower 18F-FTHA myocardial influx rate constant (P = .007) than WKYs during the 2009-2010 study without fasting. SHRs demonstrated a significantly higher 18F-FDHROL wash-in rate constant (P = 5×10 –6) and distribution volume (P = 3×10 –8), significantly higher 18F-FDG myocardial influx rate constant (P = 3×10 –8), and a higher trend of 18F-FTHA myocardial influx rate constant (not significant, P = .1) than WKYs during the 2011–2012 study with fasting. Changes in glucose plasma concentrations were generally negatively correlated with corresponding radiotracer influx rate constant changes. The study indicates a switch from preferred fatty acid metabolism to increased glucose metabolism with hypertrophy. Increased perfusion during the 2011-2012 study may be indicative of increased aerobic metabolism in the SHR model of LVH.« less
Longitudinal Evaluation of Myocardial Fatty Acid and Glucose Metabolism in Fasted and Nonfasted Spontaneously Hypertensive Rats Using MicroPET/CT

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

Huber, Jennifer S.; Hernandez, Andrew M.; Janabi, Mustafa

Using longitudinal micro positron emission tomography (microPET)/computed tomography (CT) studies, we quantified changes in myocardial metabolism and perfusion in spontaneously hypertensive rats (SHRs), a model of left ventricular hypertrophy (LVH). Fatty acid and glucose metabolism were quantified in the hearts of SHRs and Wistar-Kyoto (WKY) normotensive rats using long-chain fatty acid analog 18F-fluoro-6-thia heptadecanoic acid ( 18F-FTHA) and glucose analog 18F-fluorodeoxyglucose ( 18F-FDG) under normal or fasting conditions. We also used 18F-fluorodihydrorotenol ( 18F-FDHROL) to investigate perfusion in their hearts without fasting. Rats were imaged at 4 or 5 times over their life cycle. Compartment modeling was used to estimatemore » the rate constants for the radiotracers. Blood samples were obtained and analyzed for glucose and free fatty acid concentrations. SHRs demonstrated no significant difference in 18F-FDHROL wash-in rate constant (P = .1) and distribution volume (P = .1), significantly higher 18F-FDG myocardial influx rate constant (P = 4×10 –8), and significantly lower 18F-FTHA myocardial influx rate constant (P = .007) than WKYs during the 2009-2010 study without fasting. SHRs demonstrated a significantly higher 18F-FDHROL wash-in rate constant (P = 5×10 –6) and distribution volume (P = 3×10 –8), significantly higher 18F-FDG myocardial influx rate constant (P = 3×10 –8), and a higher trend of 18F-FTHA myocardial influx rate constant (not significant, P = .1) than WKYs during the 2011–2012 study with fasting. Changes in glucose plasma concentrations were generally negatively correlated with corresponding radiotracer influx rate constant changes. The study indicates a switch from preferred fatty acid metabolism to increased glucose metabolism with hypertrophy. Increased perfusion during the 2011-2012 study may be indicative of increased aerobic metabolism in the SHR model of LVH.« less
Small-size pedestrian detection in large scene based on fast R-CNN

NASA Astrophysics Data System (ADS)

Wang, Shengke; Yang, Na; Duan, Lianghua; Liu, Lu; Dong, Junyu

2018-04-01

Pedestrian detection is a canonical sub-problem of object detection with high demand during recent years. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited success for small size pedestrian detection in large-view scene. We study that the insufficient resolution of feature maps lead to the unsatisfactory accuracy when handling small instances. In this paper, we investigate issues involving Fast R-CNN for pedestrian detection. Driven by the observations, we propose a very simple but effective baseline for pedestrian detection based on Fast R-CNN, employing the DPM detector to generate proposals for accuracy, and training a fast R-CNN style network to jointly optimize small size pedestrian detection with skip connection concatenating feature from different layers to solving coarseness of feature maps. And the accuracy is improved in our research for small size pedestrian detection in the real large scene.
Mass Loss Rates of Fasting Polar Bears.

PubMed

Pilfold, Nicholas W; Hedman, Daryll; Stirling, Ian; Derocher, Andrew E; Lunn, Nicholas J; Richardson, Evan

2016-01-01

Polar bears (Ursus maritimus) have adapted to an annual cyclic regime of feeding and fasting, which is extreme in seasonal sea ice regions of the Arctic. As a consequence of climate change, sea ice breakup has become earlier and the duration of the open-water period through which polar bears must rely on fat reserves has increased. To date, there is limited empirical data with which to evaluate the potential energetic capacity of polar bears to withstand longer fasts. We measured the incoming and outgoing mass of inactive polar bears (n = 142) that were temporarily detained by Manitoba Conservation and Water Stewardship during the open-water period near the town of Churchill, Manitoba, Canada, in 2009-2014. Polar bears were given access to water but not food and held for a median length of 17 d. Median mass loss rates were 1.0 kg/d, while median mass-specific loss rates were 0.5%/d, similar to other species with high adiposity and prolonged fasting capacities. Mass loss by unfed captive adult males was identical to that lost by free-ranging individuals, suggesting that terrestrial feeding contributes little to offset mass loss. The inferred metabolic rate was comparable to a basal mammalian rate, suggesting that while on land, polar bears can maintain a depressed metabolic rate to conserve energy. Finally, we estimated time to starvation for subadults and adult males for the on-land period. Results suggest that at 180 d of fasting, 56%-63% of subadults and 18%-24% of adult males in this study would die of starvation. Results corroborate previous assessments on the limits of polar bear capacity to withstand lengthening ice-free seasons and emphasize the greater sensitivity of subadults to changes in sea ice phenology.

RG-inspired machine learning for lattice field theory

NASA Astrophysics Data System (ADS)

Foreman, Sam; Giedt, Joel; Meurice, Yannick; Unmuth-Yockey, Judah

2018-03-01

Machine learning has been a fast growing field of research in several areas dealing with large datasets. We report recent attempts to use renormalization group (RG) ideas in the context of machine learning. We examine coarse graining procedures for perceptron models designed to identify the digits of the MNIST data. We discuss the correspondence between principal components analysis (PCA) and RG flows across the transition for worm configurations of the 2D Ising model. Preliminary results regarding the logarithmic divergence of the leading PCA eigenvalue were presented at the conference. More generally, we discuss the relationship between PCA and observables in Monte Carlo simulations and the possibility of reducing the number of learning parameters in supervised learning based on RG inspired hierarchical ansatzes.
Fast phonetic learning occurs already in 2-to-3-month old infants: an ERP study

PubMed Central

Wanrooij, Karin; Boersma, Paul; van Zuijen, Titia L.

2014-01-01

An important mechanism for learning speech sounds in the first year of life is “distributional learning,” i.e., learning by simply listening to the frequency distributions of the speech sounds in the environment. In the lab, fast distributional learning has been reported for infants in the second half of the first year; the present study examined whether it can also be demonstrated at a much younger age, long before the onset of language-specific speech perception (which roughly emerges between 6 and 12 months). To investigate this, Dutch infants aged 2 to 3 months were presented with either a unimodal or a bimodal vowel distribution based on the English /æ/~/ε/ contrast, for only 12 minutes. Subsequently, mismatch responses (MMRs) were measured in an oddball paradigm, where one half of the infants in each group heard a representative [æ] as the standard and a representative [ε] as the deviant, and the other half heard the same reversed. The results (from the combined MMRs during wakefulness and active sleep) disclosed a larger MMR, implying better discrimination of [æ] and [ε], for bimodally than unimodally trained infants, thus extending an effect of distributional training found in previous behavioral research to a much younger age when speech perception is still universal rather than language-specific, and to a new method (using event-related potentials). Moreover, the analysis revealed a robust interaction between the distribution (unimodal vs. bimodal) and the identity of the standard stimulus ([æ] vs. [ε]), which provides evidence for an interplay between a perceptual asymmetry and distributional learning. The outcomes show that distributional learning can affect vowel perception already in the first months of life. PMID:24701203
Fast neutron background characterization with the Radiological Multi-sensor Analysis Platform (RadMAP)

DOE PAGES

Davis, John R.; Brubaker, Erik; Vetter, Kai

2017-03-29

In an effort to characterize the fast neutron radiation background, 16 EJ-309 liquid scintillator cells were installed in the Radiological Multi-sensor Analysis Platform (RadMAP) to collect data in the San Francisco Bay Area. Each fast neutron event was associated with specific weather metrics (pressure, temperature, absolute humidity) and GPS coordinates. Furthermore, the expected exponential dependence of the fast neutron count rate on atmospheric pressure was demonstrated and event rates were subsequently adjusted given the measured pressure at the time of detection. Pressure adjusted data was also used to investigate the influence of other environmental conditions on the neutron background rate.more » Using National Oceanic and Atmospheric Administration (NOAA) coastal area lidar data, an algorithm was implemented to approximate sky-view factors (the total fraction of visible sky) for points along RadMAPs route. In the three areas we analyzed, San Francisco, Downtown Oakland, and Berkeley, all demonstrated a suppression in the background rate of over 50% for the range of sky-view factors measured. This effect, which is due to the shielding of cosmic-ray produced neutrons by surrounding buildings, was comparable to the pressure influence which yielded a 32% suppression in the count rate over the range of pressures measured.« less
Development of an Efficient Identifier for Nuclear Power Plant Transients Based on Latest Advances of Error Back-Propagation Learning Algorithm

NASA Astrophysics Data System (ADS)

Moshkbar-Bakhshayesh, Khalil; Ghofrani, Mohammad B.

2014-02-01

This study aims to improve the performance of nuclear power plants (NPPs) transients training and identification using the latest advances of error back-propagation (EBP) learning algorithm. To this end, elements of EBP, including input data, initial weights, learning rate, cost function, activation function, and weights updating procedure are investigated and an efficient neural network is developed. Usefulness of modular networks is also examined and appropriate identifiers, one for each transient, are employed. Furthermore, the effect of transient type on transient identifier performance is illustrated. Subsequently, the developed transient identifier is applied to Bushehr nuclear power plant (BNPP). Seven types of the plant events are probed to analyze the ability of the proposed identifier. The results reveal that identification occurs very early with only five plant variables, whilst in the previous studies a larger number of variables (typically 15 to 20) were required. Modular networks facilitated identification due to its sole dependency on the sign of each network output signal. Fast training of input patterns, extendibility for identification of more transients and reduction of false identification are other advantageous of the proposed identifier. Finally, the balance between the correct answer to the trained transients (memorization) and reasonable response to the test transients (generalization) is improved, meeting one of the primary design criteria of identifiers.
Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

PubMed

Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

2016-03-01

Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.
MAP: an iterative experimental design methodology for the optimization of catalytic search space structure modeling.

PubMed

Baumes, Laurent A

2006-01-01

One of the main problems in high-throughput research for materials is still the design of experiments. At early stages of discovery programs, purely exploratory methodologies coupled with fast screening tools should be employed. This should lead to opportunities to find unexpected catalytic results and identify the "groups" of catalyst outputs, providing well-defined boundaries for future optimizations. However, very few new papers deal with strategies that guide exploratory studies. Mostly, traditional designs, homogeneous covering, or simple random samplings are exploited. Typical catalytic output distributions exhibit unbalanced datasets for which an efficient learning is hardly carried out, and interesting but rare classes are usually unrecognized. Here is suggested a new iterative algorithm for the characterization of the search space structure, working independently of learning processes. It enhances recognition rates by transferring catalysts to be screened from "performance-stable" space zones to "unsteady" ones which necessitate more experiments to be well-modeled. The evaluation of new algorithm attempts through benchmarks is compulsory due to the lack of past proofs about their efficiency. The method is detailed and thoroughly tested with mathematical functions exhibiting different levels of complexity. The strategy is not only empirically evaluated, the effect or efficiency of sampling on future Machine Learning performances is also quantified. The minimum sample size required by the algorithm for being statistically discriminated from simple random sampling is investigated.
Domain IV voltage-sensor movement is both sufficient and rate limiting for fast inactivation in sodium channels.

PubMed

Capes, Deborah L; Goldschen-Ohm, Marcel P; Arcisio-Miranda, Manoel; Bezanilla, Francisco; Chanda, Baron

2013-08-01

Voltage-gated sodium channels are critical for the generation and propagation of electrical signals in most excitable cells. Activation of Na(+) channels initiates an action potential, and fast inactivation facilitates repolarization of the membrane by the outward K(+) current. Fast inactivation is also the main determinant of the refractory period between successive electrical impulses. Although the voltage sensor of domain IV (DIV) has been implicated in fast inactivation, it remains unclear whether the activation of DIV alone is sufficient for fast inactivation to occur. Here, we functionally neutralize each specific voltage sensor by mutating several critical arginines in the S4 segment to glutamines. We assess the individual role of each voltage-sensing domain in the voltage dependence and kinetics of fast inactivation upon its specific inhibition. We show that movement of the DIV voltage sensor is the rate-limiting step for both development and recovery from fast inactivation. Our data suggest that activation of the DIV voltage sensor alone is sufficient for fast inactivation to occur, and that activation of DIV before channel opening is the molecular mechanism for closed-state inactivation. We propose a kinetic model of sodium channel gating that can account for our major findings over a wide voltage range by postulating that DIV movement is both necessary and sufficient for fast inactivation.
Fast detection of peroxidase (POD) activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Kong, Wenwen; Liu, Fei; Zhang, Chu; Bao, Yidan; Yu, Jiajia; He, Yong

2014-01-01

Tomatoes are cultivated around the world and gray mold is one of its most prominent and destructive diseases. An early disease detection method can decrease losses caused by plant diseases and prevent the spread of diseases. The activity of peroxidase (POD) is very important indicator of disease stress for plants. The objective of this study is to examine the possibility of fast detection of POD activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging data. Five pre-treatment methods were investigated. Genetic algorithm-partial least squares (GA-PLS) was applied to select optimal wavelengths. A new fast learning neural algorithm named extreme learning machine (ELM) was employed as multivariate analytical tool in this study. 21 optimal wavelengths were selected by GA-PLS and used as inputs of three calibration models. The optimal prediction result was achieved by ELM model with selected wavelengths, and the r and RMSEP in validation were 0.8647 and 465.9880 respectively. The results indicated that hyperspectral imaging could be considered as a valuable tool for POD activity prediction. The selected wavelengths could be potential resources for instrument development.
Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2016-01-01

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.
A real-time phenotyping framework using machine learning for plant stress severity rating in soybean.

PubMed

Naik, Hsiang Sing; Zhang, Jiaoping; Lofquist, Alec; Assefa, Teshale; Sarkar, Soumik; Ackerman, David; Singh, Arti; Singh, Asheesh K; Ganapathysubramanian, Baskar

2017-01-01

Phenotyping is a critical component of plant research. Accurate and precise trait collection, when integrated with genetic tools, can greatly accelerate the rate of genetic gain in crop improvement. However, efficient and automatic phenotyping of traits across large populations is a challenge; which is further exacerbated by the necessity of sampling multiple environments and growing replicated trials. A promising approach is to leverage current advances in imaging technology, data analytics and machine learning to enable automated and fast phenotyping and subsequent decision support. In this context, the workflow for phenotyping (image capture → data storage and curation → trait extraction → machine learning/classification → models/apps for decision support) has to be carefully designed and efficiently executed to minimize resource usage and maximize utility. We illustrate such an end-to-end phenotyping workflow for the case of plant stress severity phenotyping in soybean, with a specific focus on the rapid and automatic assessment of iron deficiency chlorosis (IDC) severity on thousands of field plots. We showcase this analytics framework by extracting IDC features from a set of ~4500 unique canopies representing a diverse germplasm base that have different levels of IDC, and subsequently training a variety of classification models to predict plant stress severity. The best classifier is then deployed as a smartphone app for rapid and real time severity rating in the field. We investigated 10 different classification approaches, with the best classifier being a hierarchical classifier with a mean per-class accuracy of ~96%. We construct a phenotypically meaningful 'population canopy graph', connecting the automatically extracted canopy trait features with plant stress severity rating. We incorporated this image capture → image processing → classification workflow into a smartphone app that enables automated real-time evaluation of IDC scores using digital images of the canopy. We expect this high-throughput framework to help increase the rate of genetic gain by providing a robust extendable framework for other abiotic and biotic stresses. We further envision this workflow embedded onto a high throughput phenotyping ground vehicle and unmanned aerial system that will allow real-time, automated stress trait detection and quantification for plant research, breeding and stress scouting applications.
The effect of fast-food availability on fast-food consumption and obesity among rural residents: an analysis by race/ethnicity.

PubMed

Dunn, Richard A; Sharkey, Joseph R; Horel, Scott

2012-01-01

Rural areas of the United States tend to have higher obesity rates than urban areas, particularly in regions with high proportions of non-white residents. This paper analyzes the effect of fast-food availability on the level of fast-food consumption and obesity risk among both white and non-white residents of central Texas. Potential endogeneity of fast-food availability is addressed through instrumental variables regression using distance to the nearest major highway as an instrument. We find that non-whites tend to exhibit higher obesity rates, greater access to fast-food establishments and higher consumption of fast-food meals compared to their white counterparts. In addition, we found that whites and non-whites respond differently to the availability of fast-food in rural environments. Greater availability is not associated with either greater consumption of fast-food meals or a higher obesity risk among the sample of whites. In contrast, greater availability of fast-food is positively associated with both the number of meals consumed for non-white rural residents and their obesity. While our results are robust to specification, the effect of availability on weight outcomes is notably weaker when indirectly calculated from the implied relationship between consumption and caloric intake. This highlights the importance of directly examining the proposed mechanism through which an environmental factor influences weight outcomes. Copyright © 2011 Elsevier B.V. All rights reserved.
Investigation of Response Amplitude Operators for Floating Offshore Wind Turbines: Preprint

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

Ramachandran, G. K. V.; Robertson, A.; Jonkman, J. M.

This paper examines the consistency between response amplitude operators (RAOs) computed from WAMIT, a linear frequency-domain tool, to RAOs derived from time-domain computations based on white-noise wave excitation using FAST, a nonlinear aero-hydro-servo-elastic tool. The RAO comparison is first made for a rigid floating wind turbine without wind excitation. The investigation is further extended to examine how these RAOs change for a flexible and operational wind turbine. The RAOs are computed for below-rated, rated, and above-rated wind conditions. The method is applied to a floating wind system composed of the OC3-Hywind spar buoy and NREL 5-MW wind turbine. The responsesmore » are compared between FAST and WAMIT to verify the FAST model and to understand the influence of structural flexibility, aerodynamic damping, control actions, and waves on the system responses. The results show that based on the RAO computation procedure implemented, the WAMIT- and FAST-computed RAOs are similar (as expected) for a rigid turbine subjected to waves only. However, WAMIT is unable to model the excitation from a flexible turbine. Further, the presence of aerodynamic damping decreased the platform surge and pitch responses, as computed by both WAMIT and FAST when wind was included. Additionally, the influence of gyroscopic excitation increased the yaw response, which was captured by both WAMIT and FAST.« less
Short-term episodes of imposed fasting have a greater effect on young northern fur seals (Callorhinus ursinus) in summer than in winter

PubMed Central

Rosen, David A. S.; Volpov, Beth L.; Trites, Andrew W.

2014-01-01

An unexpected shortage of food may affect wildlife in a different way depending on the time of year when it occurs. We imposed 48 h fasts on six female northern fur seals (Callorhinus ursinus; ages 6–24 months) to identify times of year when they might be particularly sensitive to interruptions in food supply. We monitored changes in their resting metabolic rates and their metabolic response to thermal challenges, and also examined potential bioenergetic causes for seasonal differences in body mass loss. The pre-fast metabolism of the fur seals while in ambient air or submerged in water at 4°C was higher during summer (June to Sepember) than winter (November to March), and submergence did not significantly increase metabolism, indicating a lack of additional thermoregulatory costs. There was no evidence of metabolic depression following the fasting periods, nor did metabolism increase during the post-fast thermal challenge, suggesting that mass loss did not negatively impact thermoregulatory capacity. However, the fur seals lost mass at greater rates while fasting during the summer months, when metabolism is normally high to facilitate faster growth rates (which would ordinarily have been supported by higher food intake levels). Our findings suggest that summer is a more critical time of year than winter for young northern fur seals to obtain adequate nutrition. PMID:27293642
DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoadley, J.E.; Leinart, A.S.; Cousins, R.J.

Intestinal 65Zn transport and metallothionein levels were examined in rats fed zinc-adequate and zinc-deficient diets and in rats subjected to an overnight fast. 65Zn uptake by intestines perfused with 1.5 microM 65Zn was greater in both zinc-deficient and fasted groups than in the control group. Mucosal retention of 65Zn was also greater in the zinc-deficient group but not in the fasted group. The greater 65Zn uptake in the fasted group was associated with a compartment that readily released 65Zn back into the lumen. Kinetic analysis of the rate of 65Zn transfer to the vascular space (absorption) showed that 65Zn absorptionmore » involved approximately 3% of mucosal 65Zn in a 40-min perfusion period. The half-life (t1/2) of this mucosal 65Zn rapid transport pool corresponded directly to changes in intestinal metallothionein levels. Both metallothionein and t1/2 were higher in the fasted group and lower in the zinc-deficient group than in controls. While the rate of 65Zn transport from this rapid transport pool decreased with increasing metallothionein level, the predicted pool size increased when the metallothionein level was elevated by fasting. These results indicate that the rate of zinc absorption is inversely related to intestinal metallothionein levels, but the portion of mucosal 65Zn available for absorption is directly related to intestinal metallothionein.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Gingerich, Andrew J.; Philipp, D. P.; Suski, C. D.

The influence of feeding on swimming performance and exercise recovery in fish is poorly understood. Examining swimming behavior and physiological status following periods of feeding and fasting is important because wild fish often face periods of starvation. In the current study, researchers force fed and fasted groups of largemouth bass (Micropterus salmoides) of similar sizes for a period of 16 days. Following this feeding and fasting period, fish were exercised for 60 s and monitored for swimming performance and physiological recovery. Resting metabolic rates were also determined. Fasted fish lost an average of 16 g (nearly 12%) of body mass,more » while force fed fish maintained body mass. Force fed fish swam 28% further and required nearly 14 s longer to tire during exercise. However, only some physiological conditions differed between feeding groups. Resting muscle glycogen concentrations was twofold greater in force fed fish, at rest and throughout recovery, although it decreased in both feeding treatments following exercise. Liver mass was nearly three times greater in force fed fish, and fasted fish had an average of 65% more cortisol throughout recovery. Similar recovery rates of most physiological responses were observed despite force fed fish having a metabolic rate 75% greater than fasted fish. Results are discussed as they relate to largemouth bass starvation in wild systems and how these physiological differences might be important in an evolutionary context.« less
Catecholaminergic Regulation of Learning Rate in a Dynamic Environment

PubMed Central

Jepma, Marieke; Nassar, Matthew R.; Rangel-Gomez, Mauricio; Meeter, Martijn; Nieuwenhuis, Sander

2016-01-01

Adaptive behavior in a changing world requires flexibly adapting one’s rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the ‘learning rate’). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG—an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex—predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables—capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief—on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants’ baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change. PMID:27792728
e-Learning in nursing education--Challenges and opportunities.

PubMed

Kokol, Peter; Blazun, Helena; Micetić-Turk, Dusanka; Abbott, Patricia A

2006-01-01

Quick changes on the field of informational communication technologies forces educational and other institutions to think about different ways of teaching and learning in both formal and informal environments. It addition it is well known that due to fast advancement of science and technology the knowledge gained in schools is getting out-of-date rapidly, so life long learning is becoming an essential alternative. As a consequence we are facing a rapid development and use of new educational approaches such as e-learning, simulations, virtual reality, etc. They brought a revolution to learning and instruction. But in general the empirical results of e-learning studies are somewhat disappointing. They cannot prove the superiority of e-learning processes over traditional learning in general, neither in specific areas like nursing. In our international study we proved that e-Learning can have many benefits and that it can enhance learning experience in nursing education, but it has to be provided in correct manner.
Covariance-based synaptic plasticity in an attractor network model accounts for fast adaptation in free operant learning.

PubMed

Neiman, Tal; Loewenstein, Yonatan

2013-01-23

In free operant experiments, subjects alternate at will between targets that yield rewards stochastically. Behavior in these experiments is typically characterized by (1) an exponential distribution of stay durations, (2) matching of the relative time spent at a target to its relative share of the total number of rewards, and (3) adaptation after a change in the reward rates that can be very fast. The neural mechanism underlying these regularities is largely unknown. Moreover, current decision-making neural network models typically aim at explaining behavior in discrete-time experiments in which a single decision is made once in every trial, making these models hard to extend to the more natural case of free operant decisions. Here we show that a model based on attractor dynamics, in which transitions are induced by noise and preference is formed via covariance-based synaptic plasticity, can account for the characteristics of behavior in free operant experiments. We compare a specific instance of such a model, in which two recurrently excited populations of neurons compete for higher activity, to the behavior of rats responding on two levers for rewarding brain stimulation on a concurrent variable interval reward schedule (Gallistel et al., 2001). We show that the model is consistent with the rats' behavior, and in particular, with the observed fast adaptation to matching behavior. Further, we show that the neural model can be reduced to a behavioral model, and we use this model to deduce a novel "conservation law," which is consistent with the behavior of the rats.
Mechanisms of High-Temperature Fatigue Failure in Alloy 800H

NASA Technical Reports Server (NTRS)

BhanuSankaraRao, K.; Schuster, H.; Halford, G. R.

1996-01-01

The damage mechanisms influencing the axial strain-controlled Low-Cycle Fatigue (LCF) behavior of alloy 800H at 850 C have been evaluated under conditions of equal tension/compression ramp rates (Fast-Fast (F-F): 4 X 10(sup -3)/s and Slow-Slow (S-S): 4 X 10(sup -5)/s) and asymmetrical ramp rates (Fast-Slow (F-S): 4 x 10(sup -3)/s / 4 X 10(sup -5/s and Slow-Fast (S-F): 4 X 10(sup -5) / 4 X 10(sup -3)/s) in tension and compression. The fatigue life, cyclic stress response, and fracture modes were significantly influenced by the waveform shape. The fatigue lives displayed by different loading conditions were in the following order: F-F greater than S-S greater than F-S greater than S-F. The fracture mode was dictated by the ramp rate adopted in the tensile direction. The fast ramp rate in the tensile direction led to the occurrence of transgranular crack initiation and propagation, whereas the slow ramp rate caused intergranular initiation and propagation. The time-dependent processes and their synergistic interactions, which were at the basis of observed changes in cyclic stress response and fatigue life, were identified. Oxidation, creep damage, dynamic strain aging, massive carbide precipitation, time-dependent creep deformation, and deformation ratcheting were among the several factors influencing cyclic life. Irrespective of the loading condition, the largest effect on life was exerted by oxidation processes. Deformation ratcheting had its greatest influence on life under asymmetrical loading conditions. Creep damage accumulated the greatest amount during the slow tensile ramp under S-F conditions.
Degradation kinetics of ptaquiloside in soil and soil solution.

PubMed

Ovesen, Rikke Gleerup; Rasmussen, Lars Holm; Hansen, Hans Christian Bruun

2008-02-01

Ptaquiloside (PTA) is a carcinogenic norsesquiterpene glycoside produced in bracken (Pteridium aquilinum (L.) Kuhn), a widespread, aggressive weed. Transfer of PTA to soil and soil solution eventually may contaminate groundwater and surface water. Degradation rates of PTA were quantified in soil and soil solutions in sandy and clayey soils subjected to high natural PTA loads from bracken stands. Degradation kinetics in moist soil could be fitted with the sum of a fast and a slow first-order reaction; the fast reaction contributed 20 to 50% of the total degradation of PTA. The fast reaction was similar in all horizons, with the rate constant k(1F) ranging between 0.23 and 1.5/h. The slow degradation, with the rate constant k(1S) ranging between 0.00067 and 0.029/ h, was more than twice as fast in topsoils compared to subsoils, which is attributable to higher microbial activity in topsoils. Experiments with sterile controls confirmed that nonmicrobial degradation processes constituted more than 90% of the fast degradation and 50% of the slow degradation. The lower nonmicrobial degradation rate observed in the clayey compared with the sandy soil is attributed to a stabilizing effect of PTA by clay silicates. Ptaquiloside appeared to be stable in all soil solutions, in which no degradation was observed within a period of 28 d, in strong contrast to previous studies of hydrolysis rates in artificial aqueous electrolytes. The present study predicts that the risk of PTA leaching is controlled mainly by the residence time of pore water in soil, soil microbial activity, and content of organic matter and clay silicates.

How our own speech rate influences our perception of others.

PubMed

Bosker, Hans Rutger

2017-08-01

In conversation, our own speech and that of others follow each other in rapid succession. Effects of the surrounding context on speech perception are well documented but, despite the ubiquity of the sound of our own voice, it is unknown whether our own speech also influences our perception of other talkers. This study investigated context effects induced by our own speech through 6 experiments, specifically targeting rate normalization (i.e., perceiving phonetic segments relative to surrounding speech rate). Experiment 1 revealed that hearing prerecorded fast or slow context sentences altered the perception of ambiguous vowels, replicating earlier work. Experiment 2 demonstrated that talking at a fast or slow rate prior to target presentation also altered target perception, though the effect of preceding speech rate was reduced. Experiment 3 showed that silent talking (i.e., inner speech) at fast or slow rates did not modulate the perception of others, suggesting that the effect of self-produced speech rate in Experiment 2 arose through monitoring of the external speech signal. Experiment 4 demonstrated that, when participants were played back their own (fast/slow) speech, no reduction of the effect of preceding speech rate was observed, suggesting that the additional task of speech production may be responsible for the reduced effect in Experiment 2. Finally, Experiments 5 and 6 replicate Experiments 2 and 3 with new participant samples. Taken together, these results suggest that variation in speech production may induce variation in speech perception, thus carrying implications for our understanding of spoken communication in dialogue settings. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
[Minimally invasive interventional techniques involving the urogenital tract in dogs and cats].

PubMed

Heilmann, R M

2016-01-01

Minimally invasive interventional techniques are advancing fast in small animal medicine. These techniques utilize state-of-the-art diagnostic methods, including fluoroscopy, ultrasonography, endoscopy, and laparoscopy. Minimally invasive procedures are particularly attractive in the field of small animal urology because, in the past, treatment options for diseases of the urogenital tract were rather limited or associated with a high rate of complications. Most endourological interventions have a steep learning curve. With the appropriate equipment and practical training some of these procedures can be performed in most veterinary practices. However, most interventions require referral to a specialty clinic. This article summarizes the standard endourological equipment and materials as well as the different endourological interventions performed in dogs and cats with diseases of the kidneys/renal pelves, ureters, or lower urinary tract (urinary bladder and urethra).
A methodology for achieving high-speed rates for artificial conductance injection in electrically excitable biological cells.

PubMed

Butera, R J; Wilson, C G; Delnegro, C A; Smith, J C

2001-12-01

We present a novel approach to implementing the dynamic-clamp protocol (Sharp et al., 1993), commonly used in neurophysiology and cardiac electrophysiology experiments. Our approach is based on real-time extensions to the Linux operating system. Conventional PC-based approaches have typically utilized single-cycle computational rates of 10 kHz or slower. In thispaper, we demonstrate reliable cycle-to-cycle rates as fast as 50 kHz. Our system, which we call model reference current injection (MRCI); pronounced merci is also capable of episodic logging of internal state variables and interactive manipulation of model parameters. The limiting factor in achieving high speeds was not processor speed or model complexity, but cycle jitter inherent in the CPU/motherboard performance. We demonstrate these high speeds and flexibility with two examples: 1) adding action-potential ionic currents to a mammalian neuron under whole-cell patch-clamp and 2) altering a cell's intrinsic dynamics via MRCI while simultaneously coupling it via artificial synapses to an internal computational model cell. These higher rates greatly extend the applicability of this technique to the study of fast electrophysiological currents such fast a currents and fast excitatory/inhibitory synapses.
Fast Track Teaching: Beginning the Experiment in Accelerated Leadership Development

ERIC Educational Resources Information Center

Churches, Richard; Hutchinson, Geraldine; Jones, Jeff

2009-01-01

This article provides an overview of the development of the Fast Track teaching programme and personalised nature of the training and support that has been delivered. Fast Track teacher promotion rates are compared to national statistics demonstrating significant progression for certain groups, particularly women. (Contains 3 tables and 3 figures.)
46 CFR 12.601 - General requirements for STCW rating endorsements.

Code of Federal Regulations, 2014 CFR

2014-10-01

...,000 HP or more. (6) Proficiency in survival craft and rescue boats, other than fast rescue boats (PSC). (7) Proficiency in survival craft and rescue boats, other than lifeboats and fast rescue boats (PSC-limited). (8) Proficiency in fast rescue boats. (9) Medical first-aid provider. (10) Person in charge of...
Particle-in-cell studies of fast-ion slowing-down rates in cool tenuous magnetized plasma

NASA Astrophysics Data System (ADS)

Evans, Eugene S.; Cohen, Samuel A.; Welch, Dale R.

2018-04-01

We report on 3D-3V particle-in-cell simulations of fast-ion energy-loss rates in a cold, weakly-magnetized, weakly-coupled plasma where the electron gyroradius, ρe, is comparable to or less than the Debye length, λDe, and the fast-ion velocity exceeds the electron thermal velocity, a regime in which the electron response may be impeded. These simulations use explicit algorithms, spatially resolve ρe and λDe, and temporally resolve the electron cyclotron and plasma frequencies. For mono-energetic dilute fast ions with isotropic velocity distributions, these scaling studies of the slowing-down time, τs, versus fast-ion charge are in agreement with unmagnetized slowing-down theory; with an applied magnetic field, no consistent anisotropy between τs in the cross-field and field-parallel directions could be resolved. Scaling the fast-ion charge is confirmed as a viable way to reduce the required computational time for each simulation. The implications of these slowing down processes are described for one magnetic-confinement fusion concept, the small, advanced-fuel, field-reversed configuration device.
Rural New Zealand health professionals' perceived barriers to greater use of the internet for learning.

PubMed

Janes, Ron; Arroll, Bruce; Buetow, Stephen; Coster, Gregor; McCormick, Ross; Hague, Iain

2005-01-01

The purpose of this research was to investigate rural North Island (New Zealand) health professionals' attitudes and perceived barriers to using the internet for ongoing professional learning. A cross-sectional postal survey of all rural North Island GPs, practice nurses and pharmacists was conducted in mid-2003. The questionnaire contained both quantitative and qualitative questions. The transcripts from two open questions requiring written answers were analysed for emergent themes, which are reported here. The first open question asked: 'Do you have any comments on the questionnaire, learning, computers or the Internet?' The second open question asked those who had taken a distance-learning course using the internet to list positive and negative aspects of their course, and suggest improvements. Out of 735 rural North Island health professionals surveyed, 430 returned useable questionnaires (a response rate of 59%). Of these, 137 answered the question asking for comments on learning, computers and the internet. Twenty-eight individuals who had completed a distance-learning course using the internet, provided written responses to the second question. Multiple barriers to greater use of the internet were identified. They included lack of access to computers, poor availability of broadband (fast) internet access, lack of IT skills/knowledge, lack of time, concerns about IT costs and database security, difficulty finding quality information, lack of time, energy or motivation to learn new skills, competing priorities (eg family), and a preference for learning modalities which include more social interaction. Individuals also stated that rural health professionals needed to engage the technology, because it provided rapid, flexible access from home or work to a significant health information resource, and would save money and travelling time to urban-based education. In mid-2003, there were multiple barriers to rural North Island health professionals making greater use of the internet for learning. Now that access to broadband internet is available in all rural towns in New Zealand, there is a clear need to address the other identified barriers, especially the self-reported lack of IT skills, which are preventing many in the rural health workforce from gaining maximum advantage from both computers and the internet.
Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans

PubMed Central

Keramati, Mehdi

2017-01-01

Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter. Therefore, we developed a novel two-level contingency change task in which transition contingencies between states change every few trials; MB and MF control predict different responses following these contingency changes, allowing their relative influence to be inferred. Additionally, we manipulated the rate of contingency changes in order to determine whether contingency change volatility would play a role in shifting subjects between a MB and MF strategy. We found that human subjects employed a hybrid MB/MF strategy on the task, corroborating the parallel contribution of MB and MF systems in reinforcement learning. Further, subjects did not remain at one level of MB/MF behaviour but rather displayed a shift towards more MB behavior over the first two blocks that was not attributable to the rate of contingency changes but rather to the extent of training. We demonstrate that flexibility to contingency changes can distinguish MB and MF strategies, with human subjects utilizing a hybrid strategy that shifts towards more MB behavior over blocks, consequently corresponding to a higher payoff. PMID:28957319
Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans.

PubMed

Lee, Julie J; Keramati, Mehdi

2017-09-01

Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter. Therefore, we developed a novel two-level contingency change task in which transition contingencies between states change every few trials; MB and MF control predict different responses following these contingency changes, allowing their relative influence to be inferred. Additionally, we manipulated the rate of contingency changes in order to determine whether contingency change volatility would play a role in shifting subjects between a MB and MF strategy. We found that human subjects employed a hybrid MB/MF strategy on the task, corroborating the parallel contribution of MB and MF systems in reinforcement learning. Further, subjects did not remain at one level of MB/MF behaviour but rather displayed a shift towards more MB behavior over the first two blocks that was not attributable to the rate of contingency changes but rather to the extent of training. We demonstrate that flexibility to contingency changes can distinguish MB and MF strategies, with human subjects utilizing a hybrid strategy that shifts towards more MB behavior over blocks, consequently corresponding to a higher payoff.
A machine learning model with human cognitive biases capable of learning from small and biased datasets.

PubMed

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.
Assembling old tricks for new tasks: a neural model of instructional learning and control.

PubMed

Huang, Tsung-Ren; Hazy, Thomas E; Herd, Seth A; O'Reilly, Randall C

2013-06-01

We can learn from the wisdom of others to maximize success. However, it is unclear how humans take advice to flexibly adapt behavior. On the basis of data from neuroanatomy, neurophysiology, and neuroimaging, a biologically plausible model is developed to illustrate the neural mechanisms of learning from instructions. The model consists of two complementary learning pathways. The slow-learning parietal pathway carries out simple or habitual stimulus-response (S-R) mappings, whereas the fast-learning hippocampal pathway implements novel S-R rules. Specifically, the hippocampus can rapidly encode arbitrary S-R associations, and stimulus-cued responses are later recalled into the basal ganglia-gated pFC to bias response selection in the premotor and motor cortices. The interactions between the two model learning pathways explain how instructions can override habits and how automaticity can be achieved through motor consolidation.
Warning Signs of Heart Attack, Stroke and Cardiac Arrest

MedlinePlus

... a Heart Attack WARNING SIGNS OF HEART ATTACK, STROKE & CARDIAC ARREST HEART ATTACK WARNING SIGNS CHEST DISCOMFORT ... nausea or lightheadedness. Learn more about heart attack STROKE WARNING SIGNS Spot a stroke F.A.S.T.: - ...
Personality Dimensions of Gifted and Talented Junior High Students.

ERIC Educational Resources Information Center

Rosenblatt, Howard S.; And Others

1980-01-01

Compared to a peer group of average abilities, gifted and talented junior high school students appeared more outgoing, participating, insightful, fast-learning, intellectually adaptable, conscientious, persistent, and moralistic, thus indicating significant between-group differences. (SB)
A Fast Variational Approach for Learning Markov Random Field Language Models

DTIC Science & Technology

2015-01-01

the same distribution as n- gram models, but utilize a non-linear neural network pa- rameterization. NLMs have been shown to produce com- petitive...to either resort to local optimiza- tion methods, such as those used in neural lan- guage models, or work with heavily constrained distributions. In...embeddings learned through neural language models. Central to the language modelling problem is the challenge Proceedings of the 32nd International
The Effect of Time on Word Learning: An Examination of Decay of the Memory Trace and Vocal Rehearsal in Children with and without Specific Language Impairment

ERIC Educational Resources Information Center

Alt, Mary; Spaulding, Tammie

2011-01-01

Purpose: The purpose of this study was to measure the effect of time to response in a fast-mapping word learning task for children with specific language impairment (SLI) and children with typically developing language skills (TD). Manipulating time to response allows us to examine decay of the memory trace, the use of vocal rehearsal, and their…
CMU DeepLens: deep learning for automatic image-based galaxy-galaxy strong lens finding

NASA Astrophysics Data System (ADS)

Lanusse, François; Ma, Quanbin; Li, Nan; Collett, Thomas E.; Li, Chun-Liang; Ravanbakhsh, Siamak; Mandelbaum, Rachel; Póczos, Barnabás

2018-01-01

Galaxy-scale strong gravitational lensing can not only provide a valuable probe of the dark matter distribution of massive galaxies, but also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as Large Synoptic Survey Telescope, Euclid and Wide-Field Infrared Survey Telescope. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on deep learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20 000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99 per cent, a completeness of 90 per cent can be achieved for lenses with Einstein radii larger than 1.4 arcsec and S/N larger than 20 on individual g-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens.
Transfer of piano practice in fast performance of skilled finger movements

PubMed Central

2013-01-01

Background Transfer of learning facilitates the efficient mastery of various skills without practicing all possible sensory-motor repertoires. The present study assessed whether motor practice at a submaximal speed, which is typical in sports and music performance, results in an increase in a maximum speed of finger movements of trained and untrained skills. Results Piano practice of sequential finger movements at a submaximal speed over days progressively increased the maximum speed of trained movements. This increased maximum speed of finger movements was maintained two months after the practice. The learning transferred within the hand to some extent, but not across the hands. Conclusions The present study confirmed facilitation of fast finger movements following a piano practice at a submaximal speed. In addition, the findings indicated the intra-manual transfer effects of piano practice on the maximum speed of skilled finger movements. PMID:24175946
Coordinate changes of myosin light and heavy chain isoforms during forced fiber type transitions in rabbit muscle.

PubMed

Leeuw, T; Pette, D

1996-01-01

Skeletal muscle fibers are versatile entities, capable of changing their phenotype in response to altered functional demands. In the present study, fast-to-slow fiber type transitions were induced in rabbit tibialis anterior (fA) muscles by chronic low-frequency stimulation (CLFS). The time course of changes in relative protein concentrations of fast and slow myosin light chain (MLC) isoforms and changes in their relative synthesis rates by in vivo labeling with [35S]methionine were followed during stimulation periods of up to 60 days. Generally, relative synthesis rates and protein concentrations changed in parallel; i.e., fast isoforms decreased and slow isoforms increased. MLC3f, however, which turns over at a higher rate than the other light chains, exhibited a conspicuous discrepancy between a markedly reduced relative synthesis but only a moderate decrease in protein amount during the initial 2 weeks of CLFS. Apparently, MLC3f is regulated independent of MLC1f, with protein degradation playing an important role in its regulation. The exchange of fast MLC isoforms with their slow counterparts seemed to correspond to the ultimate fast-to-slow (MHCIIa-->MHCI) transition at the MHC level. However, due to an earlier onset of the fast-to-slow transition of the regulatory light chain and the delayed fast-to-slow exchange of the alkali light chains, a spectrum of hybrid isomyosins composed of fast and slow light and heavy chains must have existed transiently in transforming fibers. Such hybrid isomyosins appeared to be restricted to MHCIIa- and MHCI-based combinations. In conclusion, fiber type specific programs that normally coordinate the expression of myofibrillar protein isoforms seem to be maintained during fiber type transitions. Possible differences in post-transcriptional regulation may result in the transient accumulation of atypical combinations of fast and slow MLC and MHC isoforms, giving rise to the appearance of hybrid fibers under the conditions of forced fiber type conversion.
Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm

PubMed Central

McDonnell, Mark D.; Tissera, Migel D.; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

2015-01-01

Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the ‘Extreme Learning Machine’ (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random ‘receptive field’ sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems. PMID:26262687
An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

PubMed

Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

2018-04-01

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic, prosthetic, and industrial applications.

Memory Effects on Movement Behavior in Animal Foraging

PubMed Central

Bracis, Chloe; Gurarie, Eliezer; Van Moorter, Bram; Goodwin, R. Andrew

2015-01-01

An individual’s choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems. PMID:26288228
Memory Effects on Movement Behavior in Animal Foraging.

PubMed

Bracis, Chloe; Gurarie, Eliezer; Van Moorter, Bram; Goodwin, R Andrew

2015-01-01

An individual's choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems.
Health status monitoring for ICU patients based on locally weighted principal component analysis.

PubMed

Ding, Yangyang; Ma, Xin; Wang, Youqing

2018-03-01

Intelligent status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then make appropriate treatment strategy. However, general-type monitoring model now widely used is difficult to adapt the changes of intensive care unit (ICU) patients' status due to its fixed pattern, and a more robust, efficient and fast monitoring model should be developed to the individual. A data-driven learning approach combining locally weighted projection regression (LWPR) and principal component analysis (PCA) is firstly proposed and applied to monitor the nonlinear process of patients' health status in ICU. LWPR is used to approximate the complex nonlinear process with local linear models, in which PCA could be further applied to status monitoring, and finally a global weighted statistic will be acquired for detecting the possible abnormalities. Moreover, some improved versions are developed, such as LWPR-MPCA and LWPR-JPCA, which also have superior performance. Eighteen subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and two vital signs of each subject were chosen for online monitoring. The proposed method was compared with several existing methods including traditional PCA, Partial least squares (PLS), just in time learning combined with modified PCA (L-PCA), and Kernel PCA (KPCA). The experimental results demonstrated that the mean fault detection rate (FDR) of PCA can be improved by 41.7% after adding LWPR. The mean FDR of LWPR-MPCA was increased by 8.3%, compared with the latest reported method L-PCA. Meanwhile, LWPR spent less training time than others, especially KPCA. LWPR is first introduced into ICU patients monitoring and achieves the best monitoring performance including adaptability to changes in patient status, sensitivity for abnormality detection as well as its fast learning speed and low computational complexity. The algorithm is an excellent approach to establishing a personalized model for patients, which is the mainstream direction of modern medicine in the following development, as well as improving the global monitoring performance. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
The effects of presentation pace and modality on learning a multimedia science lesson

NASA Astrophysics Data System (ADS)

Chung, Wen-Hung

Working memory is a system that consists of multiple components. The visuospatial sketchpad is the main entrance for visual and spatial information, whereas acoustic and verbal information is processed in the phonological loop. The central executive works as a coordinator of information from these two subsystems. Numerous studies have shown that working memory has a very limited capacity. Based on these characteristics of working memory, theories such as cognitive load theory and the cognitive theory of multimedia learning provide multimedia design principles. One of these principles is that when verbal information accompanying pictures is presented in audio mode instead of visually, learning can be more effective than if both text and pictures are presented visually. This is called the modality effect. However, some studies have found that the modality effect does not occur in some situations. In most experiments examining the modality effect, the multimedia is presented as system-paced. If learners are able to repeat listening as many times as they need, the superiority of spoken text over visual text seems lessened. One aim of this study was to examine the modality effect in a learner-controlled condition. This study also used the one-word-at-a-time technique to investigate whether the modality effect would still occur if both reading and listening rates were equal. There were 182 college students recruited for this study. Participants were randomly assigned to seven groups: a self-paced listening group, a self-paced reading group, a self text-block reading group, a general-paced listening group, a general-paced reading group, a fast-paced listening group, and a fast-paced reading group. The experimental material was a cardiovascular multimedia module. A three-by-two between-subjects design was used to test the main effect. Results showed that modality effect was still present but not between the self-paced listening group and the self text-block reading group. A post-study survey showed participants' different responses to the two modalities and their preferences as well. Results and research limitations are discussed and applications and future directions are also addressed.
Impact of Prolonged Fasting on the Risk of Calcium Phosphate Precipitation in the Urine: Calcium Phosphate Lithogenesis during Prolonged Fasting in a Healthy Cohort.

PubMed

Shafiee, Mohammad A; Aarabi, Mehdi; Shaker, Pouyan; Ghafarian, Amir M; Chamanian, Pouyan; Halperin, Mitchell L

2018-03-02

Intermittent fasting and curtailing water intake for extended periods were likely common in Paleolithic times. Today it occurs for religious and dietary reasons. This restriction in intake should cause a decrease in the urine flow rate while raising the concentration of certain substances in urine to the point of precipitation. In this study we measured the risk of CaHPO 4 precipitation following 18 hours of food and water deprivation. Urine samples were periodically collected from 15 healthy subjects who fasted and abstained from drinking any liquid for 18 hours. The urine constituents Ca 2+ , HPO 4 2- and pH involved in CaHPO 4 formation were measured at various times throughout the fasting day. A comparison was made with control data, which consisted of diurnal urine collections taken throughout a separate nonfasting day prior to the fasting day. The mean ± SEM urine flow rate decreased significantly from 0.93 ± 0.1 ml per minute in the control group to 0.37 ± 0.05 ml per minute in the fasting group (p <0.05). Mean Na + and Ca 2+ excretion rates decreased significantly from 127 ± 12 to 54 ± 13 μmol per minute and from 3.2 ± 0.4 to 0.80 ± 0.21, respectively. Mean urinary Na + and Ca 2+ concentrations also decreased from 161 ± 11.6 to 122 ± 16.0 mmol/l and from 3.7 ± 0.5 to 2.0 ± 0.55, respectively. Urinary pH and the concentration of phosphate, citrate and magnesium were not significantly affected. Although the steady decrease in the urine flow rate was statistically significant during 18 hours of food and water deprivation, there was no evidence that the calculated risk of CaHPO 4 precipitation in the healthy subjects had increased. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Effect of sleep stage on interictal high-frequency oscillations recorded from depth macroelectrodes in patients with focal epilepsy

PubMed Central

Bagshaw, Andrew P.; Jacobs, Julia; LeVan, Pierre; Dubeau, François; Gotman, Jean

2013-01-01

Summary Purpose To investigate the effect of sleep stage on the properties of high-frequency oscillations (HFOs) recorded from depth macroelectrodes in patients with focal epilepsy. Methods Ten-minute epochs of wakefulness (W), stage 1–2 non-REM (N1-N2), stage 3 non-REM (N3) and REM sleep (R) were identified from stereo- electroencephalography (SEEG) data recorded at 2 kHz in nine patients. Rates of spikes, ripples (>80 Hz), and fast ripples (>250 Hz) were calculated, as were HFO durations, degree of spike–HFO overlap, HFO rates inside and outside of spikes, and inside and outside of the seizure-onset zone (SOZ). Results Ripples were observed in nine patients and fast ripples in eight. Spike rate was highest in N1-N2 in 5 of 9 patients, and in N3 in 4 of 9 patients, whereas ripple rate was highest in N1-N2 in 4 of 9 patients, in N3 in 4 of 9 patients, and in Win 1 of 9 patients. Fast ripple rate was highest in N1-N2 in 4 of 8 patients, and in N3 in 4 of 8 patients. HFO properties changed significantly with sleep stage, although the absolute effects were small. The difference in HFO rates inside and outside of the SOZ was highly significant (p < 0.000001) in all stages except for R and, for fast ripples, only marginally significant (p = 0.018) in W. Conclusions Rates of HFOs recorded from depth macroelectrodes are highest in non-REM sleep. HFO properties were similar in stages N1-N2 and N3, suggesting that accurate sleep staging is not necessary. The spatial specificity of HFO, particularly fast ripples, was affected by sleep stage, suggesting that recordings excluding REM sleep and wakefulness provide a more reliable indicator of the SOZ. PMID:18801037
Physiological response to extreme fasting in subantarctic fur seal (Arctocephalus tropicalis) pups: metabolic rates, energy reserve utilization, and water fluxes.

PubMed

Verrier, Delphine; Groscolas, René; Guinet, Christophe; Arnould, John P Y

2009-11-01

Surviving prolonged fasting requires various metabolic adaptations, such as energy and protein sparing, notably when animals are simultaneously engaged in energy-demanding processes such as growth. Due to the intermittent pattern of maternal attendance, subantarctic fur seal pups have to repeatedly endure exceptionally long fasting episodes throughout the 10-mo rearing period while preparing for nutritional independence. Their metabolic responses to natural prolonged fasting (33.4 +/- 3.3 days) were investigated at 7 mo of age. Within 4-6 fasting days, pups shifted into a stage of metabolic economy characterized by a minimal rate of body mass loss (0.7%/day) and decreased resting metabolic rate (5.9 +/- 0.1 ml O(2)xkg(-1)xday(-1)) that was only 10% above the level predicted for adult terrestrial mammals. Field metabolic rate (289 +/- 10 kJxkg(-1)xday(-1)) and water influx (7.9 +/- 0.9 mlxkg(-1)xday(-1)) were also among the lowest reported for any young otariid, suggesting minimized energy allocation to behavioral activity and thermoregulation. Furthermore, lean tissue degradation was dramatically reduced. High initial adiposity (>48%) and predominant reliance on lipid catabolism likely contributed to the exceptional degree of protein sparing attained. Blood chemistry supported these findings and suggested utilization of alternative fuels, such as beta-hydroxybutyrate and de novo synthesized glucose from fat-released glycerol. Regardless of sex and body condition, pups tended to adopt a convergent strategy of extreme energy and lean body mass conservation that appears highly adaptive for it allows some tissue growth during the repeated episodes of prolonged fasting they experience throughout their development.
Influence of chewing rate on salivary stress hormone levels.

PubMed

Tasaka, Akinori; Tahara, Yasuaki; Sugiyama, Tetsuya; Sakurai, Kaoru

2008-10-01

The purpose of this study was to clarify the effect of different chewing rates on salivary cortisol levels as a stress indicator. The subject group consisted of 16 healthy males. They were required to rest for 30 min, and then given arithmetic calculations to perform for 30 min as stress loading. Immediately after, the first set of saliva specimens (S1) was collected over a period of 1 min to measure cortisol levels. Next, they were asked to chew a tasteless gum base for 10 min, and the second set of saliva specimens (S2) was collected in the same manner. They were then required to rest for 10 min, after which the third set of saliva specimens (S3) was collected. Chewing rates were set to slow, habitual, and fast in time with a metronome. Salivary cortisol levels were analyzed by radioimmunoassay. Changes in salivary cortisol levels comparing S1 with S2, and S1 with S3 were determined. Changes in salivary cortisol levels between S1 and S2 showed a reduction of 4.7%, 14.6%, and 16.2% with slow, habitual, and fast chewing, respectively. A significant difference was observed between slow and fast chewing. Changes in salivary cortisol levels between S1 and S3 showed a reduction of 14.4%, 22.2%, and 25.8% with slow, habitual, and fast chewing, respectively. A significant difference was observed between slow and fast chewing. This study showed that differences in chewing rate affected salivary cortisol levels as a stress indicator, and suggested that the effect on stress release with fast chewing is greater than that with slow chewing.
Reinnervation of the lateral gastrocnemius and soleus muscles in the rat by their common nerve.

PubMed Central

Gillespie, M J; Gordon, T; Murphy, P R

1986-01-01

To determine whether there is any specificity of regenerating nerves for their original muscles, the common lateral gastrocnemius soleus nerve (l.g.s.) innervating the fast-twitch lateral gastrocnemius (l.g.) and slow-twitch soleus muscles was sectioned in the hind limb of twenty adult rats. The proximal nerve stump was sutured to the dorsal surface of the l.g. muscle and 4-14 months later, the contractile properties of the reinnervated l.g. and soleus muscles and their single motor units were studied by dissection and stimulation of the ventral root filaments. Contractile properties of normal contralateral muscles were examined for comparison and motor units were isolated in l.g. and soleus muscles for study in a group of untreated animals. Measurement of time and rate parameters of maximal twitch and tetanic contractions showed that the rate of development of force increased significantly in reinnervated soleus muscles and approached the speed of l.g. muscles but rate of relaxation did not change appreciably. In reinnervated l.g. muscles, contraction speed was similar to normal l.g. muscles but relaxation rate declined toward the rates of relaxation in control soleus muscles. After reinnervation by the common l.g.s. nerve, the proportion of slow motor units in l.g. increased from 10 to 31% and decreased in soleus from 80 to 31%. The relative proportions of fast and slow motor units in each muscle were the same as the proportions of fast and slow units in the normal l.g. and soleus muscles combined. It was concluded that fast and slow muscles do not show any preference for their former nerves and that the change in the force profile of the reinnervated muscles is indicative of the relative proportions of fast and slow motor units: fast units dominate the contraction phase and slow units the relaxation phase of twitch and tetanic contractions of the muscle. PMID:3723414
Perceptual learning in visual search: fast, enduring, but non-specific.

PubMed

Sireteanu, R; Rettenbach, R

1995-07-01

Visual search has been suggested as a tool for isolating visual primitives. Elementary "features" were proposed to involve parallel search, while serial search is necessary for items without a "feature" status, or, in some cases, for conjunctions of "features". In this study, we investigated the role of practice in visual search tasks. We found that, under some circumstances, initially serial tasks can become parallel after a few hundred trials. Learning in visual search is far less specific than learning of visual discriminations and hyperacuity, suggesting that it takes place at another level in the central visual pathway, involving different neural circuits.
Fermentation of Ammonia Fiber Expansion Treated and Untreated Barley Straw in a Rumen Simulation Technique Using Rumen Inoculum from Cattle with Slow versus Fast Rate of Fiber Disappearance

PubMed Central

Griffith, Candace L.; Ribeiro, Gabriel O.; Oba, Masahito; McAllister, Tim A.; Beauchemin, Karen A.

2016-01-01

The purpose of this study was to determine the effect of rumen inoculum from heifers with fast vs. slow rate of in situ fiber digestion on the fermentation of complex versus easily digested fiber sources in the forms of untreated and Ammonia Fiber Expansion (AFEX) treated barley straw, respectively, using an artificial rumen simulation technique (Rusitec). In situ fiber digestion was measured in a previous study by incubating untreated barley straw in the rumen of 16 heifers fed a diet consisting of 700 g/kg barley straw and 300 g/kg concentrate. The two heifers with fastest rate of digestion (Fast ≥ 4.18% h-1) and the two heifers with the slowest rate of digestion (Slow ≤ 3.17% h-1) were chosen as inoculum donors for this study. Two Rusitec apparatuses each equipped with eight fermenters were used in a completely randomized block design with two blocks (apparatus) and four treatments in a 2 × 2 factorial arrangement of treatments (Fast or Slow rumen inoculum and untreated or AFEX treated straw). Fast rumen inoculum and AFEX straw both increased (P < 0.05) disappearance of dry matter (DMD), organic matter, true DMD, neutral detergent fiber, acid detergent fiber, and nitrogen (N) with an interactive effect between the two (P < 0.05). Fast rumen inoculum increased (P > 0.05) methane production per gram of digested material for both untreated and AFEX straw, and reduced (interaction, P < 0.05) acetate: propionate ratio for untreated straw. Greater relative populations of Ruminococcus albus (P < 0.05) and increased microbial N production (P = 0.045) were observed in Fast rumen inoculum. AFEX straw in Fast inoculum had greater total bacterial populations than Slow, but for untreated straw this result was reversed (interaction, P = 0.013). These findings indicate that differences in microbial populations in rumen fluid contribute to differences in the capacity of rumen inoculum to digest fiber. PMID:27899919
Applied Comparative Effectiveness Researchers Must Measure Learning Rates: A Commentary on Efficiency Articles

ERIC Educational Resources Information Center

Skinner, Christopher H.

2010-01-01

Almost all academic skills deficits can be conceptualized as learning rate problems as students are not failing to learn, but not learning rapidly enough. Thus, when selecting among various possible remedial procedures, educators need an evidence base that indicates which procedure results in the greatest increases in learning rates. Previous…
Altered Risk-Based Decision Making following Adolescent Alcohol Use Results from an Imbalance in Reinforcement Learning in Rats

PubMed Central

Hart, Andrew S.; Collins, Anne L.; Bernstein, Ilene L.; Phillips, Paul E. M.

2012-01-01

Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life. PMID:22615989
Oxygen consumption, oxygen cost, heart rate, and perceived effort during split-belt treadmill walking in young healthy adults.

PubMed

Roper, Jaimie A; Stegemöller, Elizabeth L; Tillman, Mark D; Hass, Chris J

2013-03-01

During split-belt treadmill walking the speed of the treadmill under one limb is faster than the belt under the contralateral limb. This unique intervention has shown evidence of acutely improving gait impairments in individuals with neurologic impairment such as stroke and Parkinson's disease. However, oxygen use, heart rate and perceived effort associated with split-belt treadmill walking are unknown and may limit the utility of this locomotor intervention. To better understand the intensity of this new intervention, this study was undertaken to examine the oxygen consumption, oxygen cost, heart rate, and rating of perceived exertion associated with split-belt treadmill walking in young healthy adults. Fifteen participants completed three sessions of treadmill walking: slow speed with belts tied, fast speed with belts tied, and split-belt walking with one leg walking at the fast speed and one leg walking at the slow speed. Oxygen consumption, heart rate, and rating of perceived exertion were collected during each walking condition and oxygen cost was calculated. Results revealed that oxygen consumption, heart rate, and perceived effort associated with split-belt walking were higher than slow treadmill walking, but only oxygen consumption was significantly lower during both split-belt walking than fast treadmill walking. Oxygen cost associated with slow treadmill walking was significantly higher than fast treadmill walking. These findings have implications for using split-belt treadmill walking as a rehabilitation tool as the cost associated with split-belt treadmill walking may not be higher or potentially more detrimental than that associated with previously used treadmill training rehabilitation strategies.
Discovery of a New Photometric Sub-class of Faint and Fast Classical Novae

NASA Astrophysics Data System (ADS)

Kasliwal, M. M.; Cenko, S. B.; Kulkarni, S. R.; Ofek, E. O.; Quimby, R.; Rau, A.

2011-07-01

We present photometric and spectroscopic follow-up of a sample of extragalactic novae discovered by the Palomar 60 inch telescope during a search for "Fast Transients In Nearest Galaxies" (P60-FasTING). Designed as a fast cadence (1 day) and deep (g < 21 mag) survey, P60-FasTING was particularly sensitive to short-lived and faint optical transients. The P60-FasTING nova sample includes 10 novae in M 31, 6 in M 81, 3 in M 82, 1 in NGC 2403, and 1 in NGC 891. This significantly expands the known sample of extragalactic novae beyond the Local Group, including the first discoveries in a starburst environment. Surprisingly, our photometry shows that this sample is quite inconsistent with the canonical maximum-magnitude-rate-of-decline (MMRD) relation for classical novae. Furthermore, the spectra of the P60-FasTING sample are indistinguishable from classical novae. We suggest that we have uncovered a sub-class of faint and fast classical novae in a new phase space in luminosity-timescale of optical transients. Thus, novae span two orders of magnitude in both luminosity and time. Perhaps the MMRD, which is characterized only by the white dwarf mass, was an oversimplification. Nova physics appears to be characterized by a relatively rich four-dimensional parameter space in white dwarf mass, temperature, composition, and accretion rate.
LIMITS ON THE EVENT RATES OF FAST RADIO TRANSIENTS FROM THE V-FASTR EXPERIMENT

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

Wayth, Randall B.; Tingay, Steven J.; Deller, Adam T.

2012-07-10

We present the first results from the V-FASTR experiment, a commensal search for fast transient radio bursts using the Very Long Baseline Array (VLBA). V-FASTR is unique in that the widely spaced VLBA antennas provide a discriminant against non-astronomical signals and a mechanism for the localization and identification of events that is not possible with single dishes or short baseline interferometers. Thus, far V-FASTR has accumulated over 1300 hr of observation time with the VLBA, between 90 cm and 3 mm wavelength (327 MHz-86 GHz), providing the first limits on fast transient event rates at high radio frequencies (>1.4 GHz).more » V-FASTR has blindly detected bright individual pulses from seven known pulsars but has not detected any single-pulse events that would indicate high-redshift impulsive bursts of radio emission. At 1.4 GHz, V-FASTR puts limits on fast transient event rates comparable with the PALFA survey at the Arecibo telescope, but generally at lower sensitivities, and comparable to the 'fly's eye' survey at the Allen Telescope Array, but with less sky coverage. We also illustrate the likely performance of the Phase 1 SKA dish array for an incoherent fast transient search fashioned on V-FASTR.« less
Fast-sausage oscillations in coronal loops with smooth boundary

NASA Astrophysics Data System (ADS)

Lopin, I.; Nagorny, I.

2014-12-01

Aims: The effect of the transition layer (shell) in nonuniform coronal loops with a continuous radial density profile on the properties of fast-sausage modes are studied analytically and numerically. Methods: We modeled the coronal waveguide as a structured tube consisting of a cord and a transition region (shell) embedded within a magnetic uniform environment. The derived general dispersion relation was investigated analytically and numerically in the context of frequency, cut-off wave number, and the damping rate of fast-sausage oscillations for various values of loop parameters. Results: The frequency of the global fast-sausage mode in the loops with a diffuse (or smooth) boundary is determined mainly by the external Alfvén speed and longitudinal wave number. The damping rate of such a mode can be relatively low. The model of coronal loop with diffuse boundary can support a comparatively low-frequency, global fast-sausage mode of detectable quality without involving extremely low values of the density contrast. The effect of thin transition layer (corresponds to the loops with steep boundary) is negligible and produces small reductions of oscillation frequency and relative damping rate in comparison with the case of step-function density profile. Seismological application of obtained results gives the estimated Alfvén speed outside the flaring loop about 3.25 Mm/s.
Coast Community College: The Learning Society, California Style

ERIC Educational Resources Information Center

Real, James

1978-01-01

Community colleges in the California Coast Community College district have capitalized on a burgeoning adult education clientele and the public television boom to acquire one of the fasting growing and most venturesome education systems in the world. (Author/LBH)
Molecular adaptations of adipose tissue to 6 weeks of morning fasting vs. daily breakfast consumption in lean and obese adults

PubMed Central

Gonzalez, Javier T.; Richardson, Judith D.; Chowdhury, Enhad A.; Koumanov, Francoise; Holman, Geoffrey D.; Cooper, Scott; Thompson, Dylan

2017-01-01

Key points In lean individuals, 6 weeks of extended morning fasting increases the expression of genes involved in lipid turnover (ACADM) and insulin signalling (IRS2) in subcutaneous abdominal adipose tissue.In obese individuals, 6 weeks of extended morning fasting increases IRS2 expression in subcutaneous abdominal adipose tissue.The content and activation status of key proteins involved in insulin signalling and glucose transport (GLUT4, Akt1 and Akt2) were unaffected by extended morning fasting. Therefore, any observations of altered adipose tissue insulin sensitivity with extended morning fasting do not necessarily require changes in insulin signalling proximal to Akt.Insulin‐stimulated adipose tissue glucose uptake rates are lower in obese versus lean individuals, but this difference is abolished when values are normalised to whole‐body fat mass. This suggests a novel hypothesis which proposes that the reduced adipose glucose uptake in obesity is a physiological down‐regulation to prevent excessive de novo lipogenesis. Abstract This study assessed molecular responses of human subcutaneous abdominal adipose tissue (SCAT) to 6 weeks of morning fasting. Forty‐nine healthy lean (n = 29) and obese (n = 20) adults provided SCAT biopsies before and after 6 weeks of morning fasting (FAST; 0 kcal until 12.00 h) or daily breakfast consumption (BFAST; ≥700 kcal before 11.00 h). Biopsies were analysed for mRNA levels of selected genes, and GLUT4 and Akt protein content. Basal and insulin‐stimulated Akt activation and tissue glucose uptake rates were also determined. In lean individuals, lipid turnover and insulin signalling genes (ACADM and IRS2) were up‐regulated with FAST versus BFAST (ACADM: 1.14 (95% CI: 0.97–1.30) versus 0.80 (95% CI: 0.64–0.96), P = 0.007; IRS2: 1.75 (95% CI: 1.33–2.16) versus 1.09 (95% CI: 0.67–1.51), P = 0.03, respectively). In obese individuals, no differential (FAST versus BFAST) expression was observed in genes involved in lipid turnover (all P > 0.1). GLUT4, Akt protein content and insulin‐stimulated Akt phosphorylation were unaffected by FAST versus BFAST in both lean and obese cohorts (all P > 0.1). Lower insulin‐stimulated glucose uptake rates in obese versus lean individuals were eradicated when normalised to whole‐body fat mass (P = 0.416). We conclude that morning fasting up‐regulates lipid turnover genes in SCAT of lean individuals. Secondly, altered SCAT insulin sensitivity with morning fasting is unlikely to be explained by signalling proximal to Akt. Finally, lower insulin‐stimulated SCAT glucose uptake rates in obese individuals are proportional to whole‐body fat mass, suggesting a compensatory down‐regulation, presumably to prevent excessive de novo lipogenesis in adipose tissue. This trial was registered as ISRCTN31521726. PMID:29193093
Fast volumetric imaging with patterned illumination via digital micro-mirror device-based temporal focusing multiphoton microscopy.

PubMed

Chang, Chia-Yuan; Hu, Yvonne Yuling; Lin, Chun-Yu; Lin, Cheng-Han; Chang, Hsin-Yu; Tsai, Sheng-Feng; Lin, Tzu-Wei; Chen, Shean-Jen

2016-05-01

Temporal focusing multiphoton microscopy (TFMPM) has the advantage of area excitation in an axial confinement of only a few microns; hence, it can offer fast three-dimensional (3D) multiphoton imaging. Herein, fast volumetric imaging via a developed digital micromirror device (DMD)-based TFMPM has been realized through the synchronization of an electron multiplying charge-coupled device (EMCCD) with a dynamic piezoelectric stage for axial scanning. The volumetric imaging rate can achieve 30 volumes per second according to the EMCCD frame rate of more than 400 frames per second, which allows for the 3D Brownian motion of one-micron fluorescent beads to be spatially observed. Furthermore, it is demonstrated that the dynamic HiLo structural multiphoton microscope can reject background noise by way of the fast volumetric imaging with high-speed DMD patterned illumination.

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