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Sample records for selective reversal learning

  1. The chemotherapeutic agent paclitaxel selectively impairs reversal learning while sparing prior learning, new learning and episodic memory.

    Science.gov (United States)

    Panoz-Brown, Danielle; Carey, Lawrence M; Smith, Alexandra E; Gentry, Meredith; Sluka, Christina M; Corbin, Hannah E; Wu, Jie-En; Hohmann, Andrea G; Crystal, Jonathon D

    2017-10-01

    Chemotherapy is widely used to treat patients with systemic cancer. The efficacy of cancer therapies is frequently undermined by adverse side effects that have a negative impact on the quality of life of cancer survivors. Cancer patients who receive chemotherapy often experience chemotherapy-induced cognitive impairment across a variety of domains including memory, learning, and attention. In the current study, the impact of paclitaxel, a taxane derived chemotherapeutic agent, on episodic memory, prior learning, new learning, and reversal learning were evaluated in rats. Neurogenesis was quantified post-treatment in the dentate gyrus of the same rats using immunostaining for 5-Bromo-2'-deoxyuridine (BrdU) and Ki67. Paclitaxel treatment selectively impaired reversal learning while sparing episodic memory, prior learning, and new learning. Furthermore, paclitaxel-treated rats showed decreases in markers of hippocampal cell proliferation, as measured by markers of cell proliferation assessed using immunostaining for Ki67 and BrdU. This work highlights the importance of using multiple measures of learning and memory to identify the pattern of impaired and spared aspects of chemotherapy-induced cognitive impairment. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2011-01-01

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

  3. Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.

    Science.gov (United States)

    Izquierdo, Alicia; Murray, Elisabeth A

    2007-01-31

    Neuropsychological studies in nonhuman primates have led to the view that the amygdala plays an essential role in stimulus-reward association. The main evidence in support of this idea is that bilateral aspirative or radiofrequency lesions of the amygdala yield severe impairments on object reversal learning, a task that assesses the ability to shift choices of objects based on the presence or absence of food reward (i.e., reward contingency). The behavioral effects of different lesion techniques, however, can vary. The present study therefore evaluated the effects of selective, excitotoxic lesions of the amygdala in rhesus monkeys on object reversal learning. For comparison, we tested the same monkeys on a task known to be sensitive to amygdala damage, the reinforcer devaluation task. Contrary to previous results based on less selective lesion techniques, monkeys with complete excitotoxic amygdala lesions performed object reversal learning as quickly as controls. As predicted, however, the same operated monkeys were impaired in making object choices after devaluation of the associated food reinforcer. The results suggest two conclusions. First, the results demonstrate that the amygdala makes a selective contribution to stimulus-reward association; the amygdala is critical for guiding object choices after changes in reward value but not after changes in reward contingency. Second, the results implicate a critical contribution to object reversal learning of structures nearby the amygdala, perhaps the subjacent rhinal cortex.

  4. Selective activation of M4 muscarinic acetylcholine receptors reverses MK-801-induced behavioral impairments and enhances associative learning in rodents

    DEFF Research Database (Denmark)

    Bubser, Michael; Bridges, Thomas M; Dencker, Ditte

    2014-01-01

    PAMs, enabling a more extensive characterization of M4 actions in rodent models. We used VU0467154 to test the hypothesis that selective potentiation of M4 receptor signaling could ameliorate the behavioral, cognitive, and neurochemical impairments induced by the noncompetitive NMDAR antagonist MK-801....... VU0467154 produced a robust dose-dependent reversal of MK-801-induced hyperlocomotion and deficits in preclinical models of associative learning and memory functions, including the touchscreen pairwise visual discrimination task in wild-type mice, but failed to reverse these stimulant...

  5. Selective Activation of M4 Muscarinic Acetylcholine Receptors Reverses MK-801-Induced Behavioral Impairments and Enhances Associative Learning in Rodents

    Science.gov (United States)

    2015-01-01

    Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a novel approach for the treatment of psychotic symptoms associated with schizophrenia and other neuropsychiatric disorders. We recently reported that the selective M4 PAM VU0152100 produced an antipsychotic drug-like profile in rodents after amphetamine challenge. Previous studies suggest that enhanced cholinergic activity may also improve cognitive function and reverse deficits observed with reduced signaling through the N-methyl-d-aspartate subtype of the glutamate receptor (NMDAR) in the central nervous system. Prior to this study, the M1 mAChR subtype was viewed as the primary candidate for these actions relative to the other mAChR subtypes. Here we describe the discovery of a novel M4 PAM, VU0467154, with enhanced in vitro potency and improved pharmacokinetic properties relative to other M4 PAMs, enabling a more extensive characterization of M4 actions in rodent models. We used VU0467154 to test the hypothesis that selective potentiation of M4 receptor signaling could ameliorate the behavioral, cognitive, and neurochemical impairments induced by the noncompetitive NMDAR antagonist MK-801. VU0467154 produced a robust dose-dependent reversal of MK-801-induced hyperlocomotion and deficits in preclinical models of associative learning and memory functions, including the touchscreen pairwise visual discrimination task in wild-type mice, but failed to reverse these stimulant-induced deficits in M4 KO mice. VU0467154 also enhanced the acquisition of both contextual and cue-mediated fear conditioning when administered alone in wild-type mice. These novel findings suggest that M4 PAMs may provide a strategy for addressing the more complex affective and cognitive disruptions associated with schizophrenia and other neuropsychiatric disorders. PMID:25137629

  6. Multiple reversal olfactory learning in honeybees

    Directory of Open Access Journals (Sweden)

    Theo Mota

    2010-07-01

    Full Text Available In multiple reversal learning, animals trained to discriminate a reinforced from a non-reinforced stimulus are subjected to various, successive reversals of stimulus contingencies (e.g. A+ vs. B-, A- vs. B+, A+ vs. B-. This protocol is useful to determine whether or not animals learn to learn and solve successive discriminations faster (or with fewer errors with increasing reversal experience. Here we used the olfactory conditioning of proboscis extension reflex to study how honeybees Apis mellifera perform in a multiple reversal task. Our experiment contemplated four consecutive differential conditioning phases involving the same odors (A+ vs. B- to A- vs. B+ to A+ vs. B- to A- vs. B+. We show that bees in which the weight of reinforced or non-reinforced stimuli was similar mastered the multiple olfactory reversals. Bees which failed the task exhibited asymmetric responses to reinforced and non-reinforced stimuli, thus being unable to rapidly reverse stimulus contingencies. Efficient reversers did not improve their successive discriminations but rather tended to generalize their choice to both odors at the end of conditioning. As a consequence, both discrimination and reversal efficiency decreasedalong experimental phases. This result invalidates a learning-to-learn effect and indicates that bees do not only respond to the actual stimulus contingencies but rather combine these with an average of past experiences with the same stimuli.  

  7. Reverse hypothesis machine learning a practitioner's perspective

    CERN Document Server

    Kulkarni, Parag

    2017-01-01

    This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as ...

  8. SELECTED PROBLEMS OF REVERSE LOGISTICS IN POLAND

    OpenAIRE

    Agata Mesjasz-Lech

    2009-01-01

    This paper presents the essence of reverse logistics and directions of physical and information flows between logistic network partners. It also analyses effects of implementation of the principles of reverse logistics in Poland in the years 2004-2007

  9. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

    Science.gov (United States)

    Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

    2016-01-01

    Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

  10. Memory formation in reversal learning of the honeybee

    Directory of Open Access Journals (Sweden)

    Ravit Hadar

    2010-12-01

    Full Text Available In reversal learning animals are first trained with a differential learning protocol, where they learn to respond to a reinforced odor (CS+ and not to respond to a nonreinforced odor (CS-. Once they respond correctly to this rule, the contingencies of the conditioned stimuli are reversed, and animals learn to adjust their response to the new rule. This study investigated the effect of a protein synthesis inhibitor (emetine on the memory formed after reversal learning in the honeybee Apis mellifera. Two groups of bees were studied: summer bees and winter bees, each yielded different results. Blocking protein synthesis in summer bees inhibits consolidation of the excitatory learning following reversal learning whereas it blocked the consolidation of the inhibitory learning in winter bees. These findings suggest that excitatory and inhibitory learning may involve different molecular processes in bees, which are seasonally dependent.

  11. Vasectomy as a reversible form of contraception for select patients.

    Science.gov (United States)

    Samplaski, Mary K; Daniel, Ariande; Jarvi, Keith

    2014-04-01

    To provide an effective form of birth control, men may choose a reversible or permanent form of contraception. Vasectomy is presently offered as a permanent option for male contraception. We have had patients who were interested in vasectomy and reversal as a temporary birth control option. The purpose of this paper is to determine if vasectomy should be offered for selected couples as a temporary form of contraception and under which circumstances. A literature review was conducted to determine the available reversible contraceptive options, risks, failure rates and contraindications to each, and the risks and success rates of vasectomy and vasectomy reversal. Reversible contraceptives include hormonally based methods for women, non-hormonal anatomic barrier devices and spermatocidal agents. Hormone based therapies may be contraindicated in women with cardiovascular disease, hypertension, and some cancers. Non-hormonal contraceptives are generally less effective and may be unacceptable for some couples due to higher failure rates, difficulty of use and lack of acceptance. Both vasectomy and vasectomy reversal are low risk procedures. Reversal may be performed with a high degree of success, particularly with a short obstructive interval (97% patency if performed form of sterilization for most couples, there are select couples, unable or unwilling to use other forms of birth control, who would benefit from an informed discussion about using a vasectomy as a reversible form of contraception.

  12. Motivational Classroom Climate for Learning Mathematics: A Reversal Theory Perspective

    Science.gov (United States)

    Lewis, Gareth

    2015-01-01

    In this article, a case is made that affect is central in determining students' experience of learning or not learning mathematics. I show how reversal theory (Apter, 2001), and particularly its taxonomy of motivations and emotions, provides a basis for a thick description of students' experiences of learning in a mathematics classroom. Using data…

  13. Ultrapermeable, reverse-selective nanocomposite membranes.

    Science.gov (United States)

    Merkel, T C; Freeman, B D; Spontak, R J; He, Z; Pinnau, I; Meakin, P; Hill, A J

    2002-04-19

    Polymer nanocomposites continue to receive tremendous attention for application in areas such as microelectronics, organic batteries, optics, and catalysis. We have discovered that physical dispersion of nonporous, nanoscale, fumed silica particles in glassy amorphous poly(4-methyl-2-pentyne) simultaneously and surprisingly enhances both membrane permeability and selectivity for large organic molecules over small permanent gases. These highly unusual property enhancements, in contrast to results obtained in conventional filled polymer systems, reflect fumed silica-induced disruption of polymer chain packing and an accompanying subtle increase in the size of free volume elements through which molecular transport occurs, as discerned by positron annihilation lifetime spectroscopy. Such nanoscale hybridization represents an innovative means to tune the separation properties of glassy polymeric media through systematic manipulation of molecular packing.

  14. Spatial reversal learning in preclinical scrapie-inoculated mice.

    Science.gov (United States)

    Lysons, A M; Woollard, S J

    1996-04-10

    Acquisition and reversal of a two-choice spatial discrimination were tested in scrapie-inoculated mice. Both acquisition and reversal were normal in mice tested 138 and 103 days prior to the onset of clinical symptoms. At 65 days before onset of clinical symptoms, scrapie-inoculated mice required more trails to criterion in reversal learning, but this effect was not significant in a second experiment (68 days preclinical) and was transient: no effect was seen 33 days before symptoms. However, the course of reversal learning was abnormal in all three late preclinical groups (68, 65 and 33 days before symptoms). Reversal learning in these three groups was characterized by a rapid extinction of the original discrimination, followed by a period, absent in controls, during which performance showed no further improvement. This effect corresponds in time of onset to the appearance of characteristic neuropathological features.

  15. The neural basis of reversal learning: An updated perspective

    Science.gov (United States)

    Izquierdo, Alicia; Brigman, Jonathan L.; Radke, Anna K.; Rudebeck, Peter H.; Holmes, Andrew

    2016-01-01

    Reversal learning paradigms are among the most widely used tests of cognitive flexibility and have been used as assays, across species, for altered cognitive processes in a host of neuropsychiatric conditions. Based on recent studies in humans, non-human primates, and rodents, the notion that reversal learning tasks primarily measure response inhibition, has been revised. In this review, we describe how cognitive flexibility is measured by reversal learning and discuss new definitions of the construct validity of the task that are serving as an heuristic to guide future research in this field. We also provide an update on the available evidence implicating certain cortical and subcortical brain regions in the mediation of reversal learning, and an overview of the principle neurotransmitter systems involved. PMID:26979052

  16. Post-training depletions of basolateral amygdala serotonin fail to disrupt discrimination, retention, or reversal learning

    Directory of Open Access Journals (Sweden)

    G. Jesus eOchoa

    2015-05-01

    Full Text Available In goal-directed pursuits, the basolateral amygdala (BLA is critical in learning about changes in the value of rewards. BLA-lesioned rats show enhanced reversal learning, a task employed to measure the flexibility of response to changes in reward. Similarly, there is a trend for enhanced discrimination learning, suggesting that BLA may modulate formation of stimulus-reward associations. There is a parallel literature on the importance of serotonin (5HT in new stimulus-reward and reversal learning. Recent postulations implicate 5HT in learning from punishment. Whereas dopaminergic involvement is critical in behavioral activation and reinforcement, 5HT may be most critical for aversive processing and behavioral inhibition, complementary cognitive processes. Given these findings, a 5HT-mediated mechanism in BLA may mediate the facilitated learning observed previously. The present study investigated the effects of selective 5HT lesions in BLA using 5,7-dihydroxytryptamine (5,7-DHT versus infusions of saline (Sham on discrimination, retention, and deterministic reversal learning. Rats were required to reach an 85% correct pairwise discrimination and single reversal criterion prior to surgery. Postoperatively, rats were then tested on the 1 retention of the pretreatment discrimination pair 2 discrimination of a novel pair and 3 reversal learning performance. We found statistically comparable preoperative learning rates between groups, intact postoperative retention, and unaltered novel discrimination and reversal learning in 5,7-DHT rats. These findings suggest that 5HT in BLA is not required for formation and flexible adjustment of new stimulus-reward associations when the strategy to efficiently solve the task has already been learned. Given the complementary role of orbitofrontal cortex in reward learning and its interconnectivity with BLA, these findings add to the list of dissociable mechanisms for BLA and orbitofrontal cortex in reward learning.

  17. "At Sea": Reversibility in Teaching and Learning

    Science.gov (United States)

    Cavicchi, Elizabeth Mary

    2018-01-01

    An equal-armed balance at equilibrium--the bar is horizontal--tips into disequilibrium upon displacing a weight. Equilibrium is restored by reversing that move--putting the weight back where it was, or doing the same on the other side. Piaget adopted the idea of equilibration to describe how the intellect, in relating to the world, develops.…

  18. Genetic dissection of behavioral flexibility: reversal learning in mice.

    Science.gov (United States)

    Laughlin, Rick E; Grant, Tara L; Williams, Robert W; Jentsch, J David

    2011-06-01

    Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels. Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  19. Anti-amyloid beta protein antibody passage across the blood-brain barrier in the SAMP8 mouse model of Alzheimer's disease: an age-related selective uptake with reversal of learning impairment.

    Science.gov (United States)

    Banks, William A; Farr, Susan A; Morley, John E; Wolf, Kathy M; Geylis, Valeria; Steinitz, Michael

    2007-08-01

    Amyloid beta protein (Abeta) levels are elevated in the brain of Alzheimer's disease patients. Anti-Abeta antibodies can reverse the histologic and cognitive impairments in mice which overexpress Abeta. Passive immunization appears safer than vaccination and treatment of patients will likely require human rather than xenogenic antibodies. Effective treatment will likely require antibody to cross the blood-brain barrier (BBB). Unfortunately, antibodies typically cross the BBB very poorly and accumulate less well in brain than even albumin, a substance nearly totally excluded from the brain. We compared the ability of two anti-Abeta human monoclonal IgM antibodies, L11.3 and HyL5, to cross the BBB of young CD-1 mice to that of young and aged SAMP8 mice. The SAMP8 mouse has a spontaneous mutation that induces an age-related, Abeta-dependent cognitive deficit. There was preferential uptake of intravenously administered L11.3 in comparison to HyL5, albumin, and a control human monoclonal IgM (RF), especially by hippocampus and olfactory bulb in aged SAMP8 mice. Injection of L11.3 into the brains of aged SAMP8 mice reversed both learning and memory impairments in aged SAMP8 mice, whereas IgG and IgM controls were ineffective. Pharmacokinetic analysis predicted that an intravenous dose 1000 times higher than the brain injection dose would reverse cognitive impairments. This predicted intravenous dose reversed the impairment in learning, but not memory, in aged SAMP8 mice. In conclusion, an IgM antibody was produced that crosses the BBB to reverse cognitive impairment in a murine model of Alzheimer's disease.

  20. Greater mindful eating practice is associated with better reversal learning

    NARCIS (Netherlands)

    Janssen, Lieneke K.; Duif, Iris; Loon, Van Ilke; Vries, De Jeanne H.M.; Speckens, Anne E.M.; Cools, Roshan; Aarts, Esther

    2018-01-01

    Mindfulness-based interventions are thought to reduce compulsive behavior such as overeating by promoting behavioral flexibility. Here the main aim was to provide support for mindfulness-mediated improvements in reversal learning, a direct measure of behavioral flexibility. We investigated

  1. Learning course adjustments during arm movements with reversed sensitivity derivatives

    Directory of Open Access Journals (Sweden)

    Tweed Douglas B

    2010-11-01

    Full Text Available Abstract Background To learn, a motor system needs to know its sensitivity derivatives, which quantify how its neural commands affect motor error. But are these derivatives themselves learned, or are they known solely innately? Here we test a recent theory that the brain's estimates of sensitivity derivatives are revisable based on sensory feedback. In its simplest form, the theory says that each control system has a single, adjustable estimate of its sensitivity derivatives which affects all aspects of its task, e.g. if you learn to reach to mirror-reversed targets then your revised estimate should reverse not only your initial aiming but also your online course adjustments when the target jumps in mid-movement. Methods Human subjects bent a joystick to move a cursor to a target on a computer screen, but the cursor's motion was reversed relative to the joystick's. The target jumped once during each movement. Subjects had up to 4000 trials to practice aiming and responding to target jumps. Results All subjects learned to reverse both initial aiming and course adjustments. Conclusions Our study confirms that sensitivity derivatives can be relearned. It is consistent with the idea of a single, all-purpose estimate of those derivatives; and it suggests that the estimate is a function of context, as one would expect given that the true sensitivity derivatives may vary with the state of the controlled system, the target, and the motor commands.

  2. Selection of protective antigens in Lawsonia intracellularis by reverse vaccinology

    DEFF Research Database (Denmark)

    Vadekær, Dorte Fink; Lundegaard, Claus; Riber, Ulla

    protection against L. intracellularis. To this end, a reverse vaccinology approach was applied: the entire L. intracellularis genome encoding 1340 proteins was screened in silico using bioinformatics tools to identify potential protein antigens. Advanced software algorithms predicted 150 secreted and outer...... present in top 30 of both lists, and a combined rank was calculated. The two highest ranking proteins were initially selected for production. Synthetic genes have been designed, and the proteins are currently being produced in recombinant forms in bacterial expression systems. They will be analyzed...

  3. Reversal learning enhanced by lysergic acid diethylamide (LSD)

    Science.gov (United States)

    King, A.R.; Martin, I.L.; Arabella Melville, K.

    1974-01-01

    1 Small doses of lysergic acid diethylamide (LSD) (12.5-50 μg/kg) consistently facilitated learning of a brightness discrimination reversal. 2 2-Bromo-lysergic acid diethylamide (BOL-148), a structural analogue of LSD, with similar peripheral anti-5-hydroxytrypamine activity but no psychotomimetic properties, had no effect in this learning situation at a similar dose (25 μg/kg). 3 LSD, but not BOL-148, caused a small but significant increase in brain 5-hydroxytryptamine levels, but had no effect on the levels of catecholamines in the brain at 25 μg/kg. PMID:4458849

  4. Mutual learning and reverse innovation–where next?

    Science.gov (United States)

    2014-01-01

    There is a clear and evident need for mutual learning in global health systems. It is increasingly recognized that innovation needs to be sourced globally and that we need to think in terms of co-development as ideas are developed and spread from richer to poorer countries and vice versa. The Globalization and Health journal’s ongoing thematic series, “Reverse innovation in global health systems: learning from low-income countries” illustrates how mutual learning and ideas about so-called "reverse innovation" or "frugal innovation" are being developed and utilized by researchers and practitioners around the world. The knowledge emerging from the series is already catalyzing change and challenging the status quo in global health. The path to truly “global innovation flow”, although not fully established, is now well under way. Mobilization of knowledge and resources through continuous communication and awareness raising can help sustain this movement. Global health learning laboratories, where partners can support each other in generating and sharing lessons, have the potential to construct solutions for the world. At the heart of this dialogue is a focus on creating practical local solutions and, simultaneously, drawing out the lessons for the whole world. PMID:24673828

  5. Mutual learning and reverse innovation--where next?

    Science.gov (United States)

    Crisp, Nigel

    2014-03-28

    There is a clear and evident need for mutual learning in global health systems. It is increasingly recognized that innovation needs to be sourced globally and that we need to think in terms of co-development as ideas are developed and spread from richer to poorer countries and vice versa. The Globalization and Health journal's ongoing thematic series, "Reverse innovation in global health systems: learning from low-income countries" illustrates how mutual learning and ideas about so-called "reverse innovation" or "frugal innovation" are being developed and utilized by researchers and practitioners around the world. The knowledge emerging from the series is already catalyzing change and challenging the status quo in global health. The path to truly "global innovation flow", although not fully established, is now well under way. Mobilization of knowledge and resources through continuous communication and awareness raising can help sustain this movement. Global health learning laboratories, where partners can support each other in generating and sharing lessons, have the potential to construct solutions for the world. At the heart of this dialogue is a focus on creating practical local solutions and, simultaneously, drawing out the lessons for the whole world.

  6. Reward/Punishment reversal learning in older suicide attempters.

    Science.gov (United States)

    Dombrovski, Alexandre Y; Clark, Luke; Siegle, Greg J; Butters, Meryl A; Ichikawa, Naho; Sahakian, Barbara J; Szanto, Katalin

    2010-06-01

    Suicide rates are high in old age, and the contribution of cognitive risk factors remains poorly understood. Suicide may be viewed as an outcome of an altered decision process. The authors hypothesized that impairment in reward/punishment-based learning, a component of affective decision making, is associated with attempted suicide in late-life depression. They expected that suicide attempters would discount past reward/punishment history, focusing excessively on the most recent rewards and punishments. The authors further hypothesized that this impairment could be dissociated from executive abilities, such as forward planning. The authors assessed reward/punishment-based learning using the probabilistic reversal learning task in 65 individuals age 60 and older: suicide attempters, suicide ideators, nonsuicidal depressed elderly, and nondepressed comparison subjects. The authors used a reinforcement learning computational model to decompose reward/punishment processing over time. The Stockings of Cambridge test served as a control measure of executive function. Suicide attempters but not suicide ideators showed impaired probabilistic reversal learning compared to both nonsuicidal depressed elderly and nondepressed comparison subjects, after controlling for effects of education, global cognitive function, and substance use. Model-based analyses revealed that suicide attempters discounted previous history to a higher degree relative to comparison subjects, basing their choice largely on reward/punishment received on the last trial. Groups did not differ in their performance on the Stockings of Cambridge test. Older suicide attempters display impaired reward/punishment-based learning. The authors propose a hypothesis that older suicide attempters make overly present-focused decisions, ignoring past experiences. Modification of this "myopia for the past" may have therapeutic potential.

  7. Statistical learning and selective inference.

    Science.gov (United States)

    Taylor, Jonathan; Tibshirani, Robert J

    2015-06-23

    We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

  8. The GABAergic Anterior Paired Lateral Neurons Facilitate Olfactory Reversal Learning in "Drosophila"

    Science.gov (United States)

    Wu, Yanying; Ren, Qingzhong; Li, Hao; Guo, Aike

    2012-01-01

    Reversal learning has been widely used to probe the implementation of cognitive flexibility in the brain. Previous studies in monkeys identified an essential role of the orbitofrontal cortex (OFC) in reversal learning. However, the underlying circuits and molecular mechanisms are poorly understood. Here, we use the T-maze to investigate the neural…

  9. Multiplicative Genotype-Environment Interaction as a Cause of Reversed Response to Directional Selection

    OpenAIRE

    Gimelfarb, A.

    1986-01-01

    In experiments with directional selection on a quantitative character a "reversed response" to selection is occasionally observed, when selection of individuals for a higher (lower) value of the character results in a lower (higher) value of the character among their offspring. A sudden change in environments or random drift is often assumed to be responsible for this. It is demonstrated in this paper that these two causes cannot account for the reversed response at least in some of the exper...

  10. No trade-off between learning speed and associative flexibility in bumblebees: a reversal learning test with multiple colonies.

    Directory of Open Access Journals (Sweden)

    Nigel E Raine

    Full Text Available 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.

  11. Learning for Climate Change Adaptation among Selected ...

    African Journals Online (AJOL)

    Learning for Climate Change Adaptation among Selected Communities of Lusaka ... This research was aimed at surveying perceptions of climate change and ... This work is licensed under a Creative Commons Attribution 3.0 License.

  12. Embedded Incremental Feature Selection for Reinforcement Learning

    Science.gov (United States)

    2012-05-01

    Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

  13. Reversal learning as a measure of impulsive and compulsive behavior in addictions.

    Science.gov (United States)

    Izquierdo, Alicia; Jentsch, J David

    2012-01-01

    Our ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence. Though we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions. We restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction. The research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.

  14. Efficient abstraction selection in reinforcement learning

    NARCIS (Netherlands)

    Seijen, H. van; Whiteson, S.; Kester, L.

    2013-01-01

    This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of

  15. Bioinspired Architecture Selection for Multitask Learning

    Directory of Open Access Journals (Sweden)

    Andrés Bueno-Crespo

    2017-06-01

    Full Text Available Faced with a new concept to learn, our brain does not work in isolation. It uses all previously learned knowledge. In addition, the brain is able to isolate the knowledge that does not benefit us, and to use what is actually useful. In machine learning, we do not usually benefit from the knowledge of other learned tasks. However, there is a methodology called Multitask Learning (MTL, which is based on the idea that learning a task along with other related tasks produces a transfer of information between them, what can be advantageous for learning the first one. This paper presents a new method to completely design MTL architectures, by including the selection of the most helpful subtasks for the learning of the main task, and the optimal network connections. In this sense, the proposed method realizes a complete design of the MTL schemes. The method is simple and uses the advantages of the Extreme Learning Machine to automatically design a MTL machine, eliminating those factors that hinder, or do not benefit, the learning process of the main task. This architecture is unique and it is obtained without testing/error methodologies that increase the computational complexity. The results obtained over several real problems show the good performances of the designed networks with this method.

  16. Ageing and spatial reversal learning in humans: findings from a virtual water maze.

    Science.gov (United States)

    Schoenfeld, R; Foreman, N; Leplow, B

    2014-08-15

    Deterioration in spatial memory with normal ageing is well accepted. Animal research has shown spatial reversal learning to be most vulnerable to pathological changes in the brain, but this has never been tested in humans. We studied ninety participants (52% females, 20-80 yrs) in a virtual water maze with a reversal learning procedure. Neuropsychological functioning, mood and personality were assessed to control moderator effects. For data analysis, participants were subdivided post hoc into groups aged 20-24, 25-34, 35-44, 45-64 and 65-80 yrs. Initial spatial learning occurred in all age groups but 65-80-yrs-olds never reached the level of younger participants. When tested for delayed recall of spatial memory, younger people frequented the target area but those over 65 yrs did not. In spatial reversal learning, age groups over 45 yrs were deficient and the 65-80-yrs-olds showed no evidence of reversal. Spatial measures were associated with neuropsychological functioning. Extraversion and measures of depression moderated the age effect on the learning index with older introverted and non-depressed individuals showing better results. Measures of anxiety moderated the age effect on reversal learning with older people having higher anxiety scores showing a preserved reversal learning capability. Results confirmed age to be a major factor in spatial tasks but further showed neuropsychological functioning, psycho-affective determinants and personality traits to be significant predictors of individual differences. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Dynamics of the evolution of learning algorithms by selection

    International Nuclear Information System (INIS)

    Neirotti, Juan Pablo; Caticha, Nestor

    2003-01-01

    We study the evolution of artificial learning systems by means of selection. Genetic programming is used to generate populations of programs that implement algorithms used by neural network classifiers to learn a rule in a supervised learning scenario. In contrast to concentrating on final results, which would be the natural aim while designing good learning algorithms, we study the evolution process. Phenotypic and genotypic entropies, which describe the distribution of fitness and of symbols, respectively, are used to monitor the dynamics. We identify significant functional structures responsible for the improvements in the learning process. In particular, some combinations of variables and operators are useful in assessing performance in rule extraction and can thus implement annealing of the learning schedule. We also find combinations that can signal surprise, measured on a single example, by the difference between predicted and correct classification. When such favorable structures appear, they are disseminated on very short time scales throughout the population. Due to such abruptness they can be thought of as dynamical transitions. But foremost, we find a strict temporal order of such discoveries. Structures that measure performance are never useful before those for measuring surprise. Invasions of the population by such structures in the reverse order were never observed. Asymptotically, the generalization ability approaches Bayesian results

  18. Selective reversal of muscle relaxation in general anesthesia: focus on sugammadex

    Directory of Open Access Journals (Sweden)

    Sorin J Brull

    2009-04-01

    Full Text Available Sorin J Brull1, Mohamed Naguib21Department of Anesthesiology, Mayo Clinic College of Medicine, Mayo Clinic Hospital, Jacksonville, FL, USA; 2Department of Anesthesiology and Pain Medicine, The University of Texas M D Anderson Cancer Center,  Houston, TX, USAAbstract: Despite the significant improvements in the pharmacology of muscle relaxants in the past six decades, the search for the ideal muscle relaxant continues, mainly because of the incomplete efficacy and persistent side effects associated with their antagonism. Clinical concerns remain about the residual paralysis and hemodynamic side effects associated with the classic pharmacologic reversal agents, the acetylcholinesterase inhibitors. Although the development of the “ideal muscle relaxant” remains illusory, pharmacologic advancements hold promise for improved clinical care and patient safety. Recent clinical advances include the development of short-acting nondepolarizing muscle relaxant agents that have fast onset and a very rapid metabolism that allows reliable and complete recovery; and the development of selective, “designer” reversal agents that are specific for a single drug or class of drugs. This article reviews recent developments in the pharmacology of these selective reversal agents: plasma cholinesterases, cysteine, and sugammadex. Although each of the selective reversal agents is specific in its substrate, the clinical use of the combination of muscle relaxant with its specific reversal agent will allow much greater intraoperative titrating ability, decreased side effect profile, and may result in a decreased incidence of postoperative residual paralysis and improved patient safety.Keywords: selective reversal agents, cysteine, plasma cholinesterases, sugammadex

  19. Interactions between estradiol and haloperidol on perseveration and reversal learning in amphetamine-sensitized female rats.

    Science.gov (United States)

    Almey, Anne; Arena, Lauren; Oliel, Joshua; Shams, Waqqas M; Hafez, Nada; Mancinelli, Cynthia; Henning, Lukas; Tsanev, Aleks; Brake, Wayne G

    2017-03-01

    There are sex differences associated with schizophrenia, as women exhibit later onset of the disorder, less severe symptomatology, and better response to antipsychotic medications. Estrogens are thought to play a role in these sex differences; estrogens facilitate the effects of antipsychotic medications to reduce the positive symptoms of schizophrenia, but it remains unclear whether estrogens protect against the cognitive symptoms of this disorder. Amphetamine sensitization is used to model some symptoms of schizophrenia in rats, including cognitive deficits like excessive perseveration and slower reversal learning. In this experiment female rats were administered a sensitizing regimen of amphetamine to mimic these cognitive symptoms. They were ovariectomized and administered either low or high estradiol replacement as well as chronic administration of the antipsychotic haloperidol, and were assessed in tests of perseveration and reversal learning. Results of these experiments demonstrated that, in amphetamine-sensitized rats, estradiol alone does not affect perseveration or reversal learning. However, low estradiol facilitates a 0.25mg/day dose of haloperidol to reduce perseveration and improve reversal learning. Combined high estradiol and 0.25mg/day haloperidol has no effect on perseveration or reversal learning, but high estradiol facilitates the effects of 0.13mg/day haloperidol to reduce perseveration and improve reversal learning. Thus, in amphetamine-sensitized female rats, 0.25mg/day haloperidol only improved perseveration and reversal learning when estradiol was low, while 0.13mg/day haloperidol only improved these cognitive processes when estradiol was high. These findings suggest that estradiol facilitates the effects of haloperidol to improve perseveration and reversal learning in a dose-dependent manner. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Does learning or instinct shape habitat selection?

    Directory of Open Access Journals (Sweden)

    Scott E Nielsen

    Full Text Available Habitat selection is an important behavioural process widely studied for its population-level effects. Models of habitat selection are, however, often fit without a mechanistic consideration. Here, we investigated whether patterns in habitat selection result from instinct or learning for a population of grizzly bears (Ursus arctos in Alberta, Canada. We found that habitat selection and relatedness were positively correlated in female bears during the fall season, with a trend in the spring, but not during any season for males. This suggests that habitat selection is a learned behaviour because males do not participate in parental care: a genetically predetermined behaviour (instinct would have resulted in habitat selection and relatedness correlations for both sexes. Geographic distance and home range overlap among animals did not alter correlations indicating that dispersal and spatial autocorrelation had little effect on the observed trends. These results suggest that habitat selection in grizzly bears are partly learned from their mothers, which could have implications for the translocation of wildlife to novel environments.

  1. Calculation of separation selectivity of aqueous electrolytic solutions with reverse osmosis membranes

    International Nuclear Information System (INIS)

    Ognevskij, A.V.; Fomichev, S.V.; Khvostov, V.F.; Kochergin, N.V.; AN SSSR, Moscow

    1988-01-01

    Viscosity and dielectric permittivity of a bound water layer in micropores of cellulose acetate membranes used for electrolyte ion separation by reverse osmosis method are calculated using the water cluster model and the proposed structural temperature parameter. Based on the model representations presented an algorithmof reverse osmosis membrane selectivity calculation in diluted aqueous solutions ofelectrolytes containing Cs + , Sr 2+ , I - and other ions is constructed

  2. Reversible and regionally selective downregulation of brain cannabinoid CB1 receptors in chronic daily cannabis smokers

    OpenAIRE

    Hirvonen, J; Goodwin, RS; Li, C-T; Terry, GE; Zoghbi, SS; Morse, C; Pike, VW; Volkow, ND; Huestis, MA; Innis, RB

    2011-01-01

    Chronic cannabis (marijuana, hashish) smoking can result in dependence. Rodent studies show reversible downregulation of brain cannabinoid CB1 (cannabinoid receptor type 1) receptors after chronic exposure to cannabis. However, whether downregulation occurs in humans who chronically smoke cannabis is unknown. Here we show, using positron emission tomography imaging, reversible and regionally selective downregulation of brain cannabinoid CB1 receptors in human subjects who chronically smoke ca...

  3. Feature and Region Selection for Visual Learning.

    Science.gov (United States)

    Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

    2016-03-01

    Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

  4. Learning context conditions for BDI plan selection

    NARCIS (Netherlands)

    Singh, D.; Sardina, S.; Padgham, L.; Airiau, S.; van der Hoek, W.; Kaminka, G.A.; Lespérance, Y.; Luck, M.; Sen, S.

    2010-01-01

    An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-called context conditions of plans, on which the whole model relies for plan selection, are restricted to be boolean formulas

  5. Neural correlates of a reversal learning task with an affectively neutral baseline: an event-related fMRI study

    NARCIS (Netherlands)

    Remijnse, Peter L.; Nielen, Marjan M. A.; Uylings, Harry B. M.; Veltman, Dick J.

    2005-01-01

    Reversal learning may conceptually be dissected into acquiring stimulus-reinforcement associations and subsequently altering behavior by switching to new associations as stimulus-reinforcement contingencies reverse (i.e., affective switching). Previous imaging studies have found regions of the

  6. Reversal of diastereofacial selectivity in hydride reductions of N-tert-butanesulfinyl imines.

    Science.gov (United States)

    Colyer, John T; Andersen, Neil G; Tedrow, Jason S; Soukup, Troy S; Faul, Margaret M

    2006-09-01

    A variety of N-tert-butanesulfinyl imines were reduced with NaBH4 in THF containing 2% water to provide the corresponding secondary sulfinamides in high yield and diastereoselectivity. By using the same sulfinyl imine starting materials and changing the reductant to L-Selectride, the stereoselectivity could be efficiently reversed to afford the opposite product diastereomer in high yield and selectivity.

  7. Reverse Transcriptase Mechanism of Somatic Hypermutation: 60 Years of Clonal Selection Theory

    Directory of Open Access Journals (Sweden)

    Edward J. Steele

    2017-11-01

    Full Text Available The evidence for the reverse transcriptase mechanism of somatic hypermutation is substantial and multifactorial. In this 60th anniversary year of the publication of Sir MacFarlane Burnet’s Clonal Selection Theory, the evidence is briefly reviewed and updated.

  8. An integrated conceptual framework for selecting reverse logistics providers in the presence of vagueness

    Science.gov (United States)

    Fırdolaş, Tugba; Önüt, Semih; Kongar, Elif

    2005-11-01

    In recent years, relating organization's attitude towards sustainable development, environmental management is gaining an increasing interest among researchers in supply chain management. With regard to a long term requirement of a shift from a linear economy towards a cycle economy, businesses should be motivated to embrace change brought about by consumers, government, competition, and ethical responsibility. To achieve business goals and objectives, a company must reply to increasing consumer demand for "green" products and implement environmentally responsible plans. Reverse logistics is an activity within organizations delegated to the customer service function, where customers with warranted or defective products would return them to their supplier. Emergence of reverse logistics enables to provide a competitive advantage and significant return on investment with an indirect effect on profitability. Many organizations are hiring third-party providers to implement reverse logistics programs designed to retain value by getting products back. Reverse logistics vendors play an important role in helping organizations in closing the loop for products offered by the organizations. In this regard, the selection of third-party providers issue is increasingly becoming an area of reverse logistics concept and practice. This study aims to assist managers in determining which third-party logistics provider to collaborate in the reverse logistics process with an alternative approach based on an integrated model using neural networks and fuzzy logic. An illustrative case study is discussed and the best provider is identified through the solution of this model.

  9. Mirror reversal and visual rotation are learned and consolidated via separate mechanisms: recalibrating or learning de novo?

    Science.gov (United States)

    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.

  10. Selection as a learning experience: an exploratory study.

    Science.gov (United States)

    de Visser, Marieke; Laan, Roland F; Engbers, Rik; Cohen-Schotanus, Janke; Fluit, Cornelia

    2018-01-01

    Research on selection for medical school does not explore selection as a learning experience, despite growing attention for the learning effects of assessment in general. Insight in the learning effects allows us to take advantage of selection as an inclusive part of medical students' learning process to become competent professionals. The aims of this study at Radboud University Medical Center, the Netherlands, were 1) to determine whether students have learning experiences in the selection process, and, if so, what experiences; and 2) to understand what students need in order to utilize the learning effects of the selection process at the start of the formal curriculum. We used focus groups to interview 30 students admitted in 2016 about their learning experiences in the selection process. Thematic analysis was used to explore the outcomes of the interviews and to define relevant themes. In the selection process, students learned about the curriculum, themselves, their relation to others, and the profession they had been selected to enter, although this was not explicitly perceived as learning. Students needed a connection between selection and the curriculum as well as feedback to be able to really use their learning experiences for their further development. Medical school selection qualifies as a learning experience, and students as well as medical schools can take advantage of this. We recommend a careful design of the selection procedure, integrating relevant selection learning experiences into the formal curriculum, providing feedback and explicitly approaching the selection and the formal curriculum as interconnected contributors to students' development.

  11. Effect of haptic assistance on learning vehicle reverse parking skills.

    Science.gov (United States)

    Hirokawa, Masakazu; Uesugi, Naohisa; Furugori, Satoru; Kitagawa, Tomoko; Suzuki, Kenji

    2014-01-01

    Compared to conventional visual- and auditory-based assisted driving technologies, haptic modality promises to be more effective and less disturbing assistance to the driver. However, in most previous studies, haptic assistance systems were evaluated from safety and stability viewpoints. Moreover, the effect of haptic assistance on human driving behavior has not been sufficiently discussed. In this paper, we introduce an assisted driving method based on haptic assistance for driver training in reverse parking, which is considered as an uncertain factor in conventional assisted driving systems. The proposed system assists the driver by applying a torque on the steering wheel to guide proper and well-timed steering. To design the appropriate assistance method, we conducted a measurement experiment to determine the qualitative reverse parking driver characteristics. Based on the determined characteristics, we propose a haptic assistance calculation method that utilizes the receding horizon control algorithm. For a simulation environment to assess the proposed assistance method, we also developed a scaled car simulator comprising a 1/10 scaled robot car and an omnidirectional camera. We used the scaled car simulator to conduct comparative experiments on subjects, and observed that the driving skills of the assisted subjects were significantly better than those of the control subjects.

  12. Effects of MDMA on olfactory memory and reversal learning in rats.

    Science.gov (United States)

    Hawkey, Andrew; April, L Brooke; Galizio, Mark

    2014-10-01

    The effects of acute and sub-chronic MDMA were assessed using a procedure designed to test rodent working memory capacity: the odor span task (OST). Rats were trained to select an odor that they had not previously encountered within the current session, and the number of odors to remember was incremented up to 24 during the course of each session. In order to separate drug effects on the OST from more general performance impairment, a simple olfactory discrimination was also assessed in each session. In Experiment 1, acute doses of MDMA were administered prior to select sessions. MDMA impaired memory span in a dose-dependent fashion, but impairment was seen only at doses (1.8 and 3.0 mg/kg) that also increased response omissions on both the simple discrimination and the OST. In Experiment 2, a sub-chronic regimen of MDMA (10.0 mg/kg, twice daily over four days) was administered after OST training. There was no evidence of reduced memory span following sub-chronic MDMA, but a temporary increase in omission errors on the OST was observed. In addition, rats exposed to sub-chronic MDMA showed delayed learning when the simple discrimination was reversed. Overall, the disruptive effects of both acute and sub-chronic MDMA appeared to be due to non-mnemonic processes, rather than effects on specific memory functions. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Reversible and regionally selective downregulation of brain cannabinoid CB1 receptors in chronic daily cannabis smokers.

    Science.gov (United States)

    Hirvonen, J; Goodwin, R S; Li, C-T; Terry, G E; Zoghbi, S S; Morse, C; Pike, V W; Volkow, N D; Huestis, M A; Innis, R B

    2012-06-01

    Chronic cannabis (marijuana, hashish) smoking can result in dependence. Rodent studies show reversible downregulation of brain cannabinoid CB(1) (cannabinoid receptor type 1) receptors after chronic exposure to cannabis. However, whether downregulation occurs in humans who chronically smoke cannabis is unknown. Here we show, using positron emission tomography imaging, reversible and regionally selective downregulation of brain cannabinoid CB(1) receptors in human subjects who chronically smoke cannabis. Downregulation correlated with years of cannabis smoking and was selective to cortical brain regions. After ∼4 weeks of continuously monitored abstinence from cannabis on a secure research unit, CB(1) receptor density returned to normal levels. This is the first direct demonstration of cortical cannabinoid CB(1) receptor downregulation as a neuroadaptation that may promote cannabis dependence in human brain.

  14. Numerical study of power generation by reverse electrodialysis in ion-selective nanochannels

    International Nuclear Information System (INIS)

    Kim, Dong Kwon

    2011-01-01

    In this article, ion-selective nanochannels are numerically studied to investigate the power generation capability of a concentration gradient in conjunction with reverse electrodialysis. The generation of power from the nanochannel when it is placed between two reservoirs containing sodium chloride solutions with different concentrations is investigated. The current-potential characteristics of the nanochannel were calculated by solving the Poisson equation and the Nernst-Planck equation. The effects of engineering parameters on the power generation density are investigated

  15. Numerical study of power generation by reverse electrodialysis in ion-selective nanochannels

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Kwon [Ajou University, Suwon (Korea, Republic of)

    2011-01-15

    In this article, ion-selective nanochannels are numerically studied to investigate the power generation capability of a concentration gradient in conjunction with reverse electrodialysis. The generation of power from the nanochannel when it is placed between two reservoirs containing sodium chloride solutions with different concentrations is investigated. The current-potential characteristics of the nanochannel were calculated by solving the Poisson equation and the Nernst-Planck equation. The effects of engineering parameters on the power generation density are investigated.

  16. Measuring Discrimination- and Reversal Learning in Mouse Models within 4 Days and without Prior Food Deprivation

    Science.gov (United States)

    Remmelink, Esther; Smit, August B.; Verhage, Matthijs; Loos, Maarten

    2016-01-01

    Many neurological and psychiatric disorders are characterized by deficits in cognitive flexibility. Modeling cognitive flexibility in mice enables the investigation of mechanisms underlying these deficits. The majority of currently available behavioral tests targeting this cognitive domain are reversal learning tasks that require scheduled food…

  17. That's not how the learning works - the paradox of Reverse Innovation: a qualitative study.

    Science.gov (United States)

    Harris, Matthew; Weisberger, Emily; Silver, Diana; Dadwal, Viva; Macinko, James

    2016-07-05

    There are significant differences in the meaning and use of the term 'Reverse Innovation' between industry circles, where the term originated, and health policy circles where the term has gained traction. It is often conflated with other popularized terms such as Frugal Innovation, Co-development and Trickle-up Innovation. Compared to its use in the industrial sector, this conceptualization of Reverse Innovation describes a more complex, fragmented process, and one with no particular institution in charge. It follows that the way in which the term 'Reverse Innovation', specifically, is understood and used in the healthcare space is worthy of examination. Between September and December 2014, we conducted eleven in-depth face-to-face or telephone interviews with key informants from innovation, health and social policy circles, experts in international comparative policy research and leaders in the Reverse Innovation space in the United States. Interviews were open-ended with guiding probes into the barriers and enablers to Reverse Innovation in the US context, specifically also informants' experience and understanding of the term Reverse Innovation. Interviews were recorded, transcribed and analyzed thematically using the process of constant comparison. We describe three main themes derived from the interviews. First, 'Reverse Innovation,' the term, has marketing currency to convince policy-makers that may be wary of learning from or adopting innovations from unexpected sources, in this case Low-Income Countries. Second, the term can have the opposite effect - by connoting frugality, or innovation arising from necessity as opposed to good leadership, the proposed innovation may be associated with poor quality, undermining potential translation into other contexts. Finally, the term 'Reverse Innovation' is a paradox - it breaks down preconceptions of the directionality of knowledge and learning, whilst simultaneously reinforcing it. We conclude that this term means

  18. Acute effects of cocaine and cannabis on reversal learning as a function of COMT and DRD2 genotype

    NARCIS (Netherlands)

    Spronk, D.B.; Schaaf, M.E. van der; Cools, R.; Bruijn, E.R. De; Franke, B.; Wel, J.H. van; Ramaekers, J.G.; Verkes, R.J.

    2016-01-01

    RATIONALE: Long-term cannabis and cocaine use has been associated with impairments in reversal learning. However, how acute cannabis and cocaine administration affect reversal learning in humans is not known. OBJECTIVE: In this study, we aimed to establish the acute effects of administration of

  19. Observing others stay or switch - How social prediction errors are integrated into reward reversal learning.

    Science.gov (United States)

    Ihssen, Niklas; Mussweiler, Thomas; Linden, David E J

    2016-08-01

    Reward properties of stimuli can undergo sudden changes, and the detection of these 'reversals' is often made difficult by the probabilistic nature of rewards/punishments. Here we tested whether and how humans use social information (someone else's choices) to overcome uncertainty during reversal learning. We show a substantial social influence during reversal learning, which was modulated by the type of observed behavior. Participants frequently followed observed conservative choices (no switches after punishment) made by the (fictitious) other player but ignored impulsive choices (switches), even though the experiment was set up so that both types of response behavior would be similarly beneficial/detrimental (Study 1). Computational modeling showed that participants integrated the observed choices as a 'social prediction error' instead of ignoring or blindly following the other player. Modeling also confirmed higher learning rates for 'conservative' versus 'impulsive' social prediction errors. Importantly, this 'conservative bias' was boosted by interpersonal similarity, which in conjunction with the lack of effects observed in a non-social control experiment (Study 2) confirmed its social nature. A third study suggested that relative weighting of observed impulsive responses increased with increased volatility (frequency of reversals). Finally, simulations showed that in the present paradigm integrating social and reward information was not necessarily more adaptive to maximize earnings than learning from reward alone. Moreover, integrating social information increased accuracy only when conservative and impulsive choices were weighted similarly during learning. These findings suggest that to guide decisions in choice contexts that involve reward reversals humans utilize social cues conforming with their preconceptions more strongly than cues conflicting with them, especially when the other is similar. Copyright © 2016 The Authors. Published by Elsevier B

  20. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    Directory of Open Access Journals (Sweden)

    Ashley I. Heinson

    2017-02-01

    Full Text Available Reverse vaccinology (RV is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML techniques to distinguish bacterial protective antigens (BPAs from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM classifier that could discriminate BPAs (n = 200 from non-BPAs (n = 200 with an area under the curve (AUC of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  1. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley

    2017-02-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  2. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley; Gunawardana, Yawwani; Moesker, Bastiaan; Hume, Carmen; Vataga, Elena; Hall, Yper; Stylianou, Elena; McShane, Helen; Williams, Ann; Niranjan, Mahesan; Woelk, Christopher

    2017-01-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  3. Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence.

    Science.gov (United States)

    Aoun, Bachir

    2016-05-05

    A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.

  4. Reversal of long-term potentiation-like plasticity processes after motor learning disrupts skill retention.

    Science.gov (United States)

    Cantarero, Gabriela; Lloyd, Ashley; Celnik, Pablo

    2013-07-31

    Plasticity of synaptic connections in the primary motor cortex (M1) is thought to play an essential role in learning and memory. Human and animal studies have shown that motor learning results in long-term potentiation (LTP)-like plasticity processes, namely potentiation of M1 and a temporary occlusion of additional LTP-like plasticity. Moreover, biochemical processes essential for LTP are also crucial for certain types of motor learning and memory. Thus, it has been speculated that the occlusion of LTP-like plasticity after learning, indicative of how much LTP was used to learn, is essential for retention. Here we provide supporting evidence of it in humans. Induction of LTP-like plasticity can be abolished using a depotentiation protocol (DePo) consisting of brief continuous theta burst stimulation. We used transcranial magnetic stimulation to assess whether application of DePo over M1 after motor learning affected (1) occlusion of LTP-like plasticity and (2) retention of motor skill learning. We found that the magnitude of motor memory retention is proportional to the magnitude of occlusion of LTP-like plasticity. Moreover, DePo stimulation over M1, but not over a control site, reversed the occlusion of LTP-like plasticity induced by motor learning and disrupted skill retention relative to control subjects. Altogether, these results provide evidence of a link between occlusion of LTP-like plasticity and retention and that this measure could be used as a biomarker to predict retention. Importantly, attempts to reverse the occlusion of LTP-like plasticity after motor learning comes with the cost of reducing retention of motor learning.

  5. Age-related similarities and differences in brain activity underlying reversal learning

    Directory of Open Access Journals (Sweden)

    Kaoru eNashiro

    2013-05-01

    Full Text Available The ability to update associative memory is an important aspect of episodic memory and a critical skill for social adaptation. Previous research with younger adults suggests that emotional arousal alters brain mechanisms underlying memory updating; however, it is unclear whether this applies to older adults. Given that the ability to update associative information declines with age, it is important to understand how emotion modulates the brain processes underlying memory updating in older adults. The current study investigated this question using reversal learning tasks, where younger and older participants (age ranges 19-35 and 61-78 respectively learn a stimulus–outcome association and then update their response when contingencies change. We found that younger and older adults showed similar patterns of activation in the frontopolar OFC and the amygdala during emotional reversal learning. In contrast, when reversal learning did not involve emotion, older adults showed greater parietal cortex activity than did younger adults. Thus, younger and older adults show more similarities in brain activity during memory updating involving emotional stimuli than during memory updating not involving emotional stimuli.

  6. Effects of acute sleep deprivation on motor and reversal learning in mice.

    Science.gov (United States)

    Varga, Andrew W; Kang, Mihwa; Ramesh, Priyanka V; Klann, Eric

    2014-10-01

    Sleep supports the formation of a variety of declarative and non-declarative memories, and sleep deprivation often impairs these types of memories. In human subjects, natural sleep either during a nap or overnight leads to long-lasting improvements in visuomotor and fine motor tasks, but rodent models recapitulating these findings have been scarce. Here we present evidence that 5h of acute sleep deprivation impairs mouse skilled reach learning compared to a matched period of ad libitum sleep. In sleeping mice, the duration of total sleep time during the 5h of sleep opportunity or during the first bout of sleep did not correlate with ultimate gain in motor performance. In addition, we observed that reversal learning during the skilled reaching task was also affected by sleep deprivation. Consistent with this observation, 5h of sleep deprivation also impaired reversal learning in the water-based Y-maze. In conclusion, acute sleep deprivation negatively impacts subsequent motor and reversal learning and memory. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. A change in competitive context reverses sexual selection on male size.

    Science.gov (United States)

    Kasumovic, M M; Andrade, M C B

    2009-02-01

    In studies of sexual selection, larger size is often argued to increase male fitness, and relatively smaller males are explained by genetic and/or environmental variation. We demonstrate that a size-development life-history trade-off could underlie the maintenance of a broad, unimodal distribution of size in male redback spiders (Latrodectus hasselti). Larger males are superior in direct competition, but redback males mature rapidly at small size in the presence of females. In field enclosures, we simulated two competitive contexts favouring development of divergent male sizes. Relatively smaller males lost when competing directly, but had 10 times higher fitness than relatively larger males when given the temporal advantage of rapid development. Linear selection gradients confirmed the reversal of selection on size, showing that it is critical to consider life-history decisions underlying the development of traits related to fitness.

  8. Highly selective and reversible chemosensor for Pd(2+) detected by fluorescence, colorimetry, and test paper.

    Science.gov (United States)

    Wang, Mian; Liu, Xiaomei; Lu, Huizhe; Wang, Hongmei; Qin, Zhaohai

    2015-01-21

    A "turn-on" fluorescent and colorimetric chemosensor (RBS) for Pd(2+) has been designed and synthesized through introduction of sulfur as a ligand atom to Rhodamine B. RBS exhibits high selectivity (freedom from the interference of Hg(2+ )in particular) and sensitivity toward Pd(2+) with a detection limit as low as 2.4 nM. RBS is also a reversible sensor, and it can be made into test paper to detect Pd(2+) in pure water. Compared to the chemosensors that introduced phosphorus to Rhodamine to detect Pd(2+), RBS can be synthesized more simply and economically.

  9. Incoherent dictionary learning for reducing crosstalk noise in least-squares reverse time migration

    Science.gov (United States)

    Wu, Juan; Bai, Min

    2018-05-01

    We propose to apply a novel incoherent dictionary learning (IDL) algorithm for regularizing the least-squares inversion in seismic imaging. The IDL is proposed to overcome the drawback of traditional dictionary learning algorithm in losing partial texture information. Firstly, the noisy image is divided into overlapped image patches, and some random patches are extracted for dictionary learning. Then, we apply the IDL technology to minimize the coherency between atoms during dictionary learning. Finally, the sparse representation problem is solved by a sparse coding algorithm, and image is restored by those sparse coefficients. By reducing the correlation among atoms, it is possible to preserve most of the small-scale features in the image while removing much of the long-wavelength noise. The application of the IDL method to regularization of seismic images from least-squares reverse time migration shows successful performance.

  10. Reversal learning enhanced by lysergic acid diethylamide (LSD): concomitant rise in brain 5-hydroxytryptamine levels.

    Science.gov (United States)

    King, A R; Martin, I L; Melville, K A

    1974-11-01

    1 Small doses of lysergic acid diethylamide (LSD) (12.5-50 mug/kg) consistently facilitated learning of a brightness discrimination reversal.2 2-Bromo-lysergic acid diethylamide (BOL-148), a structural analogue of LSD, with similar peripheral anti-5-hydroxytrypamine activity but no psychotomimetic properties, had no effect in this learning situation at a similar dose (25 mug/kg).3 LSD, but not BOL-148, caused a small but significant increase in brain 5-hydroxytryptamine levels, but had no effect on the levels of catecholamines in the brain at 25 mug/kg.

  11. An improved clustering algorithm based on reverse learning in intelligent transportation

    Science.gov (United States)

    Qiu, Guoqing; Kou, Qianqian; Niu, Ting

    2017-05-01

    With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.

  12. Selective social learning in infancy: looking for mechanisms.

    Science.gov (United States)

    Crivello, Cristina; Phillips, Sara; Poulin-Dubois, Diane

    2018-05-01

    Although there is mounting evidence that selective social learning begins in infancy, the psychological mechanisms underlying this ability are currently a controversial issue. The purpose of this study is to investigate whether theory of mind abilities and statistical learning skills are related to infants' selective social learning. Seventy-seven 18-month-olds were first exposed to a reliable or an unreliable speaker and then completed a word learning task, two theory of mind tasks, and a statistical learning task. If domain-general abilities are linked to selective social learning, then infants who demonstrate superior performance on the statistical learning task should perform better on the selective learning task, that is, should be less likely to learn words from an unreliable speaker. Alternatively, if domain-specific abilities are involved, then superior performance on theory of mind tasks should be related to selective learning performance. Findings revealed that, as expected, infants were more likely to learn a novel word from a reliable speaker. Importantly, infants who passed a theory of mind task assessing knowledge attribution were significantly less likely to learn a novel word from an unreliable speaker compared to infants who failed this task. No such effect was observed for the other tasks. These results suggest that infants who possess superior social-cognitive abilities are more apt to reject an unreliable speaker as informant. A video abstract of this article can be viewed at: https://youtu.be/zuuCniHYzqo. © 2017 John Wiley & Sons Ltd.

  13. The performance of cleaner wrasse, Labroides dimidiatus, in a reversal learning task varies across experimental paradigms

    Directory of Open Access Journals (Sweden)

    Simon Gingins

    2018-05-01

    Full Text Available Testing performance in controlled laboratory experiments is a powerful tool for understanding the extent and evolution of cognitive abilities in non-human animals. However, cognitive testing is prone to a number of potential biases, which, if unnoticed or unaccounted for, may affect the conclusions drawn. We examined whether slight modifications to the experimental procedure and apparatus used in a spatial task and reversal learning task affected performance outcomes in the bluestreak cleaner wrasse, Labroides dimidiatus (hereafter “cleaners”. Using two-alternative forced-choice tests, fish had to learn to associate a food reward with a side (left or right in their holding aquarium. Individuals were tested in one of four experimental treatments that differed slightly in procedure and/or physical set-up. Cleaners from all four treatment groups were equally able to solve the initial spatial task. However, groups differed in their ability to solve the reversal learning task: no individuals solved the reversal task when tested in small tanks with a transparent partition separating the two options, whereas over 50% of individuals solved the task when performed in a larger tank, or with an opaque partition. These results clearly show that seemingly insignificant details to the experimental set-up matter when testing performance in a spatial task and might significantly influence the outcome of experiments. These results echo previous calls for researchers to exercise caution when designing methodologies for cognition tasks to avoid misinterpretations.

  14. A functional polymorphism in the prodynorphin gene affects cognitive flexibility and brain activation during reversal learning.

    Directory of Open Access Journals (Sweden)

    Mikhail eVotinov

    2015-07-01

    Full Text Available Whether the opioid system plays a role in the ability to flexibly adapt behavior is still unclear. We used fMRI to investigate the effect of a nucleotide tandem repeat (68-bp VNTR functional polymorphism of the prodynorphin gene on cerebral activation during a reversal learning task in which participants had to flexibly adapt stimulus-response associations. Past studies suggested that alleles with 3 or 4 repeats (HH genotype of this polymorphism are associated with higher levels of dynorphin peptides than alleles with 1 or 2 repeats (LL genotype. On the behavioral level, the HH group made more perseverative errors than the LL group. On the neural level, the HH group demonstrated less engagement of left orbitofrontal cortex (lOFC and cortico-striatal circuitry, and lower effective connectivity of lOFC with anterior midcingulate cortex and anterior insula/ventrolateral prefrontal cortex during reversal learning and processing negative feedback. This points to a lower ability of the HH genotype to monitor or adapt to changes in reward contingencies. These findings provide first evidence that dynorphins may contribute to individual differences in reversal learning, and that considering the opioid system may shed new light on the neurochemical correlates of decision-making and behavioral regulation.

  15. Reversal learning and resurgence of operant behavior in zebrafish (Danio rerio).

    Science.gov (United States)

    Kuroda, Toshikazu; Mizutani, Yuto; Cançado, Carlos R X; Podlesnik, Christopher A

    2017-09-01

    Zebrafish are used extensively as vertebrate animal models in biomedical research for having such features as a fully sequenced genome and transparent embryo. Yet, operant-conditioning studies with this species are scarce. The present study investigated reversal learning and resurgence of operant behavior in zebrafish. A target response (approaching a sensor) was reinforced in Phase 1. In Phase 2, the target response was extinguished while reinforcing an alternative response (approaching a different sensor). In Phase 3, extinction was in effect for the target and alternative responses. Reversal learning was demonstrated when responding tracked contingency changes between Phases 1 and 2. Moreover, resurgence occurred in 10 of 13 fish in Phase 3: Target response rates increased transiently and exceeded rates of an unreinforced control response. The present study provides the first evidence with zebrafish supporting reversal learning between discrete operant responses and a laboratory model of relapse. These findings open the possibility to assessing genetic influences of operant behavior generally and in models of relapse (e.g., resurgence, renewal, reinstatement). Copyright © 2017 Elsevier B.V. All rights reserved.

  16. The performance of cleaner wrasse, Labroides dimidiatus, in a reversal learning task varies across experimental paradigms.

    Science.gov (United States)

    Gingins, Simon; Marcadier, Fanny; Wismer, Sharon; Krattinger, Océane; Quattrini, Fausto; Bshary, Redouan; Binning, Sandra A

    2018-01-01

    Testing performance in controlled laboratory experiments is a powerful tool for understanding the extent and evolution of cognitive abilities in non-human animals. However, cognitive testing is prone to a number of potential biases, which, if unnoticed or unaccounted for, may affect the conclusions drawn. We examined whether slight modifications to the experimental procedure and apparatus used in a spatial task and reversal learning task affected performance outcomes in the bluestreak cleaner wrasse, Labroides dimidiatus (hereafter "cleaners"). Using two-alternative forced-choice tests, fish had to learn to associate a food reward with a side (left or right) in their holding aquarium. Individuals were tested in one of four experimental treatments that differed slightly in procedure and/or physical set-up. Cleaners from all four treatment groups were equally able to solve the initial spatial task. However, groups differed in their ability to solve the reversal learning task: no individuals solved the reversal task when tested in small tanks with a transparent partition separating the two options, whereas over 50% of individuals solved the task when performed in a larger tank, or with an opaque partition. These results clearly show that seemingly insignificant details to the experimental set-up matter when testing performance in a spatial task and might significantly influence the outcome of experiments. These results echo previous calls for researchers to exercise caution when designing methodologies for cognition tasks to avoid misinterpretations.

  17. Reversible Assembly of Graphitic Carbon Nitride 3D Network for Highly Selective Dyes Absorption and Regeneration.

    Science.gov (United States)

    Zhang, Yuye; Zhou, Zhixin; Shen, Yanfei; Zhou, Qing; Wang, Jianhai; Liu, Anran; Liu, Songqin; Zhang, Yuanjian

    2016-09-27

    Responsive assembly of 2D materials is of great interest for a range of applications. In this work, interfacial functionalized carbon nitride (CN) nanofibers were synthesized by hydrolyzing bulk CN in sodium hydroxide solution. The reversible assemble and disassemble behavior of the as-prepared CN nanofibers was investigated by using CO2 as a trigger to form a hydrogel network at first. Compared to the most widespread absorbent materials such as active carbon, graphene and previously reported supramolecular gel, the proposed CN hydrogel not only exhibited a competitive absorbing capacity (maximum absorbing capacity of methylene blue up to 402 mg/g) but also overcame the typical deficiencies such as poor selectivity and high energy-consuming regeneration. This work would provide a strategy to construct a 3D CN network and open an avenue for developing smart assembly for potential applications ranging from environment to selective extraction.

  18. Mechanism of molecular transport in novel reverse-selective nanocomposite membranes

    International Nuclear Information System (INIS)

    Merkel, T.C.; Freeman, B.D.; Spontak, R.J.; Meakin, P.; Hill, A.J.; Monash University, VIC

    2002-01-01

    Full text: Polymer nanocomposites continue to receive tremendous attention as organic-inorganic hybrid materials exhibiting a wide range of interesting, as well as technologically relevant, properties. This work reports a novel use of polymer nanocomposites as reverse-selective membranes. We have found that physical dispersion of nonporous fumed silica [FS] into glassy poly(4-methyl-2-pentyne) [PMP] simultaneously enhances membrane permeability (by as much as 240%) and selectivity for large organic molecules over small permanent gases. This surprising observation, in stark contrast to conventional filled polymer systems, reflects silica-induced disruption of local polymer chain packing and, as discerned by positron annihilation lifetime spectroscopy [PALS], a resulting subtle increase in the size of free volume elements through which molecular transport occurs. Such nanoscale hybridization represents an innovative means of tuning the transport properties of glassy polymeric media through control of molecular ordering

  19. Identification and characterization of the novel reversible and selective cathepsin X inhibitors.

    Science.gov (United States)

    Fonović, Urša Pečar; Mitrović, Ana; Knez, Damijan; Jakoš, Tanja; Pišlar, Anja; Brus, Boris; Doljak, Bojan; Stojan, Jure; Žakelj, Simon; Trontelj, Jurij; Gobec, Stanislav; Kos, Janko

    2017-09-13

    Cathepsin X is a cysteine peptidase involved in the progression of cancer and neurodegenerative diseases. Targeting this enzyme with selective inhibitors opens a new possibility for intervention in several therapeutic areas. In this study triazole-based reversible and selective inhibitors of cathepsin X have been identified. Their selectivity and binding is enhanced when the 2,3-dihydrobenzo[b][1,4]dioxine moiety is present as the R 1 substituent. Of a series of selected triazole-benzodioxine derivatives, compound 22 is the most potent inhibitor of cathepsin X carboxypeptidase activity (K i  = 2.45 ± 0.05 μM) with at least 100-fold greater selectivity in comparison to cathepsin B or other related cysteine peptidases. Compound 22 is not cytotoxic to prostate cancer cells PC-3 or pheochromocytoma PC-12 cells at concentrations up to 10 μM. It significantly inhibits the migration of tumor cells and increases the outgrowth of neurites, both processes being under the control of cathepsin X carboxypeptidase activity. Compound 22 and other characterized triazole-based inhibitors thus possess a great potential for further development resulting in several in vivo applications.

  20. Robot soccer action selection based on Q learning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

  1. Learning feedback and feedforward control in a mirror-reversed visual environment.

    Science.gov (United States)

    Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

    2015-10-01

    When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

  2. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

    2012-01-01

    Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

  3. Effect of molecular interactions on retention and selectivity in reversed-phase liquid chromatography.

    Science.gov (United States)

    Szepesy, László

    2002-06-25

    The linear solvation energy relationships (LSERs) have been applied in the last years for description and prediction of retention and selectivity in reversed-phase liquid chromatography with good results. Widely different stationary phases have been compared and characterized by LSERs. In recent publications the influence of the type of the organic moderator and the composition of the mobile phase have also been described. However, the influence of the molecular properties of the solutes to be separated has never been discussed. According to the LSER model variation in retention factors (log k) with solute structure can be related to their potential for various intermolecular interactions. The retention factor is given as the sum of the terms of the LSER equation representing various types of molecular interactions. For this reason the influence of the structure and molecular properties of the solutes to be separated can also be investigated using the LSER equation. In this study we shall demonstrate how the specific molecular interactions influence chromatographic retention and selectivity. We intend to show that retention and selectivity depend on all participants of the system. In addition to the structure and properties of the stationary phase and the type and composition of the mobile phase the molecular properties of the solutes, characterized by the solvation parameters, will also influence the type and extent of the various molecular interactions governing retention and selectivity.

  4. Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis.

    Science.gov (United States)

    Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

    2016-05-15

    Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Mechanisms of rapid sympatric speciation by sex reversal and sexual selection in cichlid fish.

    Science.gov (United States)

    Lande, R; Seehausen, O; van Alphen, J J

    2001-01-01

    Mechanisms of speciation in cichlid fish were investigated by analyzing population genetic models of sexual selection on sex-determining genes associated with color polymorphisms. The models are based on a combination of laboratory experiments and field observations on the ecology, male and female mating behavior, and inheritance of sex-determination and color polymorphisms. The models explain why sex-reversal genes that change males into females tend to be X-linked and associated with novel colors, using the hypothesis of restricted recombination on the sex chromosomes, as suggested by previous theory on the evolution of recombination. The models reveal multiple pathways for rapid sympatric speciation through the origin of novel color morphs with strong assortative mating that incorporate both sex-reversal and suppressor genes. Despite the lack of geographic isolation or ecological differentiation, the new species coexists with the ancestral species either temporarily or indefinitely. These results may help to explain different patterns and rates of speciation among groups of cichlids, in particular the explosive diversification of rock-dwelling haplochromine cichlids.

  6. Optimizing learning path selection through memetic algorithms

    NARCIS (Netherlands)

    Acampora, G.; Gaeta, M.; Loia, V.; Ritrovato, P.; Salerno, S.

    2008-01-01

    e-Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering

  7. Least-squares reverse time migration of marine data with frequency-selection encoding

    KAUST Repository

    Dai, Wei

    2013-08-20

    The phase-encoding technique can sometimes increase the efficiency of the least-squares reverse time migration (LSRTM) by more than one order of magnitude. However, traditional random encoding functions require all the encoded shots to share the same receiver locations, thus limiting the usage to seismic surveys with a fixed spread geometry. We implement a frequency-selection encoding strategy that accommodates data with a marine streamer geometry. The encoding functions are delta functions in the frequency domain, so that all the en- coded shots have unique non-overlapping frequency content, and the receivers can distinguish the wavefield from each shot with a unique frequency band. Since the encoding functions are orthogonal to each other, there will be no crosstalk between different shots during modeling and migration. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is compara- ble to conventional RTM for both the Marmousi2 model and a marine data set recorded in the Gulf of Mexico. With more iterations, the LSRTM image quality is further improved. We conclude that LSRTM with frequency-selection is an efficient migration method that can sometimes produce more focused images than conventional RTM.

  8. Least-squares reverse time migration of marine data with frequency-selection encoding

    KAUST Repository

    Dai, Wei

    2013-06-24

    The phase-encoding technique can sometimes increase the efficiency of the least-squares reverse time migration (LSRTM) by more than one order of magnitude. However, traditional random encoding functions require all the encoded shots to share the same receiver locations, thus limiting the usage to seismic surveys with a fixed spread geometry. We implement a frequency-selection encoding strategy that accommodates data with a marine streamer geometry. The encoding functions are delta functions in the frequency domain, so that all the encoded shots have unique nonoverlapping frequency content, and the receivers can distinguish the wavefield from each shot with a unique frequency band. Because the encoding functions are orthogonal to each other, there will be no crosstalk between different shots during modeling and migration. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is comparable to conventional RTM for the Marmousi2 model and a marine data set recorded in the Gulf of Mexico. With more iterations, the LSRTM image quality is further improved by suppressing migration artifacts, balancing reflector amplitudes, and enhancing the spatial resolution. We conclude that LSRTM with frequency-selection is an efficient migration method that can sometimes produce more focused images than conventional RTM. © 2013 Society of Exploration Geophysicists.

  9. Reversal of sibutramine-induced anorexia with a selective 5-HT(2C) receptor antagonist.

    Science.gov (United States)

    Higgs, Suzanne; Cooper, Alison J; Barnes, Nicholas M

    2011-04-01

    The monoamine reuptake inhibitor sibutramine reduces food intake but the receptor subtypes mediating the effects of sibutramine on feeding remain to be clearly identified. The involvement of the 5-HT(2C) receptor subtype in the satiety-enhancing effects of sibutramine was investigated by examining the effects of co-administration of sibutramine with the selective 5-HT(2C) receptor antagonist SB 242084 Microstructural analyses of licking for a glucose solution by non-deprived, male rats were performed over a range of doses of sibutramine to identify a selective satiety-enhancing dose (experiment 1). Similar analyses were performed after administration of a vehicle control, two doses of SB 242084 alone or two doses of SB 242084 in combination with sibutramine (experiment 2). Sibutramine at doses of 1-3 mg/kg selectively reduced glucose consumption via a reduction in the number of bouts of licking. Non-selective effects to increase latency to lick were only observed at the higher dose of 6 mg/kg. Co-administration of sibutramine (3 mg/kg) with SB 242084 (1 or 3 mg/kg) reversed the effect of sibutramine on bout number whereas either dose of SB 242084 alone had no significant effect. We confirm behaviourally selective effects of sibutramine on feeding and provide further support for the satiety-enhancing effects of sibutramine. Our data also provide evidence for the involvement of the 5-HT(2C) receptor in the satiety-enhancing effects of sibutramine although additional targets may have an impact, and further investigation of the molecular mechanisms underlying the efficacy of sibutramine as an anorectic is warranted.

  10. Effects of orbitofrontal cortex lesions on autoshaped lever pressing and reversal learning.

    Science.gov (United States)

    Chang, Stephen E

    2014-10-15

    A cue associated with a rewarding event can trigger behavior towards the cue itself due to the cue acquiring incentive value through its pairing with the rewarding outcome (i.e., sign-tracking). For example, rats will approach, press, and attempt to "consume" a retractable lever conditioned stimulus (CS) that signals delivery of a food unconditioned stimulus (US). Attending to food-predictive CSs is important when seeking out food, and it is just as important to be able to modify one's behavior when the relationships between CSs and USs are changed. Using a discriminative autoshaping procedure with lever CSs, the present study investigated the effects of orbitofrontal cortex (OFC) lesions on sign-tracking and reversal learning. Insertion of one lever was followed by sucrose delivery upon retraction, and insertion of another lever was followed by nothing. After the acquisition phase, the contingencies between the levers and outcomes were reversed. Bilateral OFC lesions had no effect on the acquisition of sign-tracking. However, OFC-lesioned rats showed substantial deficits in acquiring sign-tracking compared to sham-lesioned rats once the stimulus-outcome contingencies were reversed. Over the course of reversal learning, OFC-lesioned rats were able to reach comparable levels of sign-tracking as sham-lesioned rats. These findings suggest that OFC is not necessary for the ability of a CS to acquire incentive value and provide more evidence that OFC is critical for modifying behavior appropriately following a change in stimulus-outcome contingencies. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Effects of Mode of Target Task Selection on Learning about Plants in a Mobile Learning Environment: Effortful Manual Selection versus Effortless QR-Code Selection

    Science.gov (United States)

    Gao, Yuan; Liu, Tzu-Chien; Paas, Fred

    2016-01-01

    This study compared the effects of effortless selection of target plants using quick respond (QR) code technology to effortful manual search and selection of target plants on learning about plants in a mobile device supported learning environment. In addition, it was investigated whether the effectiveness of the 2 selection methods was…

  12. Independent effects of age and levodopa on reversal learning in healthy volunteers.

    Science.gov (United States)

    Vo, Andrew; Seergobin, Ken N; MacDonald, Penny A

    2018-05-18

    The dopamine overdose hypothesis has provided an important theoretical framework for understanding cognition in Parkinson's disease. It posits that effects of dopaminergic therapy on cognition in Parkinson's disease depend on baseline dopamine levels in brain regions that support different functions. Although functions performed by more severely dopamine-depleted brain regions improve with medication, those associated with less dopamine deficient areas are actually worsened. It is presumed that medication-related worsening of cognition owes to dopamine overdose. We investigated whether age-related changes in baseline dopamine levels would modulate effects of dopaminergic therapy on reward learning in healthy volunteers. In a double-blind, crossover design, healthy younger and older adults completed a probabilistic reversal learning task after treatment with 100/25 mg of levodopa/carbidopa versus placebo. Older adults learned more poorly than younger adults at baseline, being more likely to shift responses after misleading punishment. Levodopa worsened stimulus-reward learning relative to placebo to the same extent in both groups, irrespective of differences in baseline performance and expected dopamine levels. When order effects were eliminated, levodopa induced response shifts after reward more often than placebo. Our results reveal independent deleterious effects of age group and exogenous dopamine on reward learning, suggesting a more complex scenario than predicted by the dopamine overdose hypothesis. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Design and manufacture of customized dental implants by using reverse engineering and selective laser melting technology.

    Science.gov (United States)

    Chen, Jianyu; Zhang, Zhiguang; Chen, Xianshuai; Zhang, Chunyu; Zhang, Gong; Xu, Zhewu

    2014-11-01

    Recently a new therapeutic concept of patient-specific implant dentistry has been advanced based on computer-aided design/computer-aided manufacturing technology. However, a comprehensive study of the design and 3-dimensional (3D) printing of the customized implants, their mechanical properties, and their biomechanical behavior is lacking. The purpose of this study was to evaluate the mechanical and biomechanical performance of a novel custom-made dental implant fabricated by the selective laser melting technique with simulation and in vitro experimental studies. Two types of customized implants were designed by using reverse engineering: a root-analog implant and a root-analog threaded implant. The titanium implants were printed layer by layer with the selective laser melting technique. The relative density, surface roughness, tensile properties, bend strength, and dimensional accuracy of the specimens were evaluated. Nonlinear and linear finite element analysis and experimental studies were used to investigate the stress distribution, micromotion, and primary stability of the implants. Selective laser melting 3D printing technology was able to reproduce the customized implant designs and produce high density and strength and adequate dimensional accuracy. Better stress distribution and lower maximum micromotions were observed for the root-analog threaded implant model than for the root-analog implant model. In the experimental tests, the implant stability quotient and pull-out strength of the 2 types of implants indicated that better primary stability can be obtained with a root-analog threaded implant design. Selective laser melting proved to be an efficient means of printing fully dense customized implants with high strength and sufficient dimensional accuracy. Adding the threaded characteristic to the customized root-analog threaded implant design maintained the approximate geometry of the natural root and exhibited better stress distribution and

  14. System Quality Characteristics for Selecting Mobile Learning Applications

    Directory of Open Access Journals (Sweden)

    Mohamed SARRAB

    2015-10-01

    Full Text Available The majority of M-learning (Mobile learning applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.

  15. Performance evaluation of reverse osmosis technology for selected antibiotics removal from synthetic pharmaceutical wastewater

    Directory of Open Access Journals (Sweden)

    Gholami Mitra

    2012-12-01

    Full Text Available Abstract This study addresses the possibility for low pressure reverse osmosis membrane (RE 2521, CSM process to serve as an alternative to remove selected antibiotics (ampicillin and amoxicillin from synthetic wastewater by changing operating conditions such as pH = 3, 6.5 and 10; Pressure = 9, 11 and13 (bar; antibiotic concentration = 10, 255 and 500(mg/L, and temperature = 20, 30 and 40°C. The experiment was designed based on Box-benken, which is a Response Surface methodology design (RSM, using Design Expert software. The concentration of antibiotics was measured by applying a UV-spectrophotometer (Cecil, at the wavelength of 254 nm. Results showed a range of rejection percentage from 73.52% to 99.36% and 75.1% to 98.8%, for amoxicillin and ampicillin, respectively. Considering the solute rejections and the membrane porosity show that the prevailing rejection mechanism of the examined antibiotics by the membrane was the size exclusion effect. The permeate flux for both of the antibiotics was 12–18.73 L/m2.h. Although the permeate flux and antibiotic rejection are influenced by operating pressure, pH, and temperature individually, the interaction between operating parameters did not have noticeable effects. According to the results obtained in this study, the application of RO membrane is recommended for the selected antibiotics to be removed to a considerable degree (up to 95%.

  16. Effects of MK-801 on vicarious trial-and-error and reversal of olfactory discrimination learning in weanling rats.

    Science.gov (United States)

    Griesbach, G S; Hu, D; Amsel, A

    1998-12-01

    The effects of dizocilpine maleate (MK-801) on vicarious trial-and-error (VTE), and on simultaneous olfactory discrimination learning and its reversal, were observed in weanling rats. The term VTE was used by Tolman (The determiners of behavior at a choice point. Psychol. Rev. 1938;46:318-336), who described it as conflict-like behavior at a choice-point in simultaneous discrimination learning. It takes the form of head movements from one stimulus to the other, and has recently been proposed by Amsel (Hippocampal function in the rat: cognitive mapping or vicarious trial-and-error? Hippocampus, 1993;3:251-256) as related to hippocampal, nonspatial function during this learning. Weanling male rats received systemic MK-801 either 30 min before the onset of olfactory discrimination training and its reversal, or only before its reversal. The MK-801-treated animals needed significantly more sessions to acquire the discrimination and showed significantly fewer VTEs in the acquisition phase of learning. Impaired reversal learning was shown only when MK-801 was administered during the reversal-learning phase, itself, and not when it was administered throughout both phases.

  17. Glutamine/glutamate (Glx) concentration in prefrontal cortex predicts reversal learning performance in the marmoset.

    Science.gov (United States)

    Lacreuse, Agnès; Moore, Constance M; LaClair, Matthew; Payne, Laurellee; King, Jean A

    2018-07-02

    This study used Magnetic Resonance Spectroscopy (MRS) to identify potential neurometabolitic markers of cognitive performance in male (n = 7) and female (n = 8) middle-aged (∼5 years old) common marmosets (Callithrix jacchus). Anesthetized marmosets were scanned with a 4.7 T/40 cm horizontal magnet equipped with 450 mT/m magnetic field gradients and a 20 G/cm magnetic field gradient insert, within 3 months of completing the CANTAB serial Reversal Learning task. Neurometabolite concentrations of N-Acetyl Asparate, Myo-Inositol, Choline, Phosphocreatine + creatine, Glutamate and Glutamine were acquired from a 3 mm 3 voxel positioned in the Prefrontal Cortex (PFC). Males acquired the reversals (but not simple discriminations) faster than the females. Higher PFC Glx (glutamate + glutamine) concentration was associated with faster acquisition of the reversals. Interestingly, the correlation between cognitive performance and Glx was significant in males, but not in females. These results suggest that MRS is a useful tool to identify biochemical markers of cognitive performance in the healthy nonhuman primate brain and that biological sex modulates the relationship between neurochemical composition and cognition. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Contributions to reversed-phase column selectivity: III. Column hydrogen-bond basicity.

    Science.gov (United States)

    Carr, P W; Dolan, J W; Dorsey, J G; Snyder, L R; Kirkland, J J

    2015-05-22

    Column selectivity in reversed-phase chromatography (RPC) can be described in terms of the hydrophobic-subtraction model, which recognizes five solute-column interactions that together determine solute retention and column selectivity: hydrophobic, steric, hydrogen bonding of an acceptor solute (i.e., a hydrogen-bond base) by a stationary-phase donor group (i.e., a silanol), hydrogen bonding of a donor solute (e.g., a carboxylic acid) by a stationary-phase acceptor group, and ionic. Of these five interactions, hydrogen bonding between donor solutes (acids) and stationary-phase acceptor groups is the least well understood; the present study aims at resolving this uncertainty, so far as possible. Previous work suggests that there are three distinct stationary-phase sites for hydrogen-bond interaction with carboxylic acids, which we will refer to as column basicity I, II, and III. All RPC columns exhibit a selective retention of carboxylic acids (column basicity I) in varying degree. This now appears to involve an interaction of the solute with a pair of vicinal silanols in the stationary phase. For some type-A columns, an additional basic site (column basicity II) is similar to that for column basicity I in primarily affecting the retention of carboxylic acids. The latter site appears to be associated with metal contamination of the silica. Finally, for embedded-polar-group (EPG) columns, the polar group can serve as a proton acceptor (column basicity III) for acids, phenols, and other donor solutes. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Reversal learning in gonadectomized marmosets with and without hormone replacement: are males more sensitive to punishment?

    Science.gov (United States)

    LaClair, Matthew; Lacreuse, Agnès

    2016-05-01

    This study examined sex differences in executive function in middle-aged gonadectomized marmosets (Callithrix jacchus) with or without hormonal replacement. We tested ten castrated male (mean age 5.5 years) marmosets treated with testosterone cypionate (T, n = 5) or vehicle (n = 5) on Reversal Learning, which contributes to cognitive flexibility, and the Delayed Response task, measuring working memory. Their performance was compared to that of 11 ovariectomized females (mean age = 3.7 years) treated with Silastic capsules filled with 17-β estradiol (E2, n = 6) or empty capsules (n = 5), previously tested on the same tasks (Lacreuse et al. in J Neuroendocrinol 26:296-309, 2014. doi: 10.1111/jne.12147). Behavioral observations were conducted daily. Females exhibited more locomotor behaviors than males. Males and females did not differ in the number of trials taken to reach criterion on the reversals, but males had significantly longer response latencies, regardless of hormone replacement. They also had a greater number of refusals than females. Additionally, both control and T-treated males, but not females, had slower responses on incorrect trials, suggesting that males were making errors due to distraction, lack of motivation or uncertainty. Furthermore, although both males and females had slower responding following an incorrect compared to a correct trial, the sex difference in response latencies was disproportionally large following an incorrect trial. No sex difference was found in the Delayed Response task. Overall, slower response latencies in males than females during Reversal Learning, especially during and following an incorrect trial, may reflect greater sensitivity to punishment (omission of reward) and greater performance monitoring in males, compared to females. Because these differences occurred in gonadectomized animals and regardless of hormone replacement, they may be organized early in life.

  20. Fast algorithm selection using learning curves

    NARCIS (Netherlands)

    Rijn, van J.N.; Abdulrahman, S.M.; Brazdil, P.; Vanschoren, J.; Fromont, E.; De Bie, T.; Leeuwen, van M.

    2015-01-01

    One of the challenges in Machine Learning to find a classifier and parameter settings that work well on a given dataset. Evaluating all possible combinations typically takes too much time, hence many solutions have been proposed that attempt to predict which classifiers are most promising to try. As

  1. Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

    Science.gov (United States)

    Ku, David Tawei; Huang, Yung-Hsin

    2012-01-01

    This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

  2. Isotope and ion selectivity in reverse osmosis desalination: geochemical tracers for man-made freshwater.

    Science.gov (United States)

    Kloppmann, Wolfram; Vengosh, Avner; Guerrot, Catherine; Millot, Romain; Pankratov, Irena

    2008-07-01

    A systematic measurement of ions and 2H/1H, 7Li/6Li, 11B/10B, 18O/ 16O, and 87Sr/86Sr isotopes in feed-waters, permeates, and brines from commercial reverse osmosis (RO) desalination plants in Israel (Ashkelon, Eilat, and Nitzana) and Cyprus (Larnaca) reveals distinctive geochemical and isotopic fingerprints of fresh water generated from desalination of seawater (SWRO) and brackish water (BWRO). The degree of isotope fractionation during the passage of water and solutes through the RO membranes depends on the medium (solvent-water vs. solutes), chemical speciation of the solutes, their charge, and their mass difference. O, H, and Sr isotopes are not fractionated during the RO process. 7Li is preferentially rejected in low pH RO, and B isotope fractionation depends on the pH conditions. Under low pH conditions, B isotopes are not significantly fractionated, whereas at high pH, RO permeates are enriched by 20 per thousand in 11B due to selective rejection of borate ion and preferential permeation of 11B-enriched boric acid through the membrane. The specific geochemical and isotopic fingerprints of SWRO provide a unique tool for tracing "man-made" fresh water as an emerging recharge component of natural water resources.

  3. Selective removal of arsenic and monovalent ions from brackish water reverse osmosis concentrate.

    Science.gov (United States)

    Xu, Pei; Capito, Marissa; Cath, Tzahi Y

    2013-09-15

    Concentrate disposal and management is a considerable challenge for the implementation of desalination technologies, especially for inland applications where concentrate disposal options are limited. This study has focused on selective removal of arsenic and monovalent ions from brackish groundwater reverse osmosis (RO) concentrate for beneficial use and safe environmental disposal using in situ and pre-formed hydrous ferric oxides/hydroxides adsorption, and electrodialysis (ED) with monovalent permselective membranes. Coagulation with ferric salts is highly efficient at removing arsenic from RO concentrate to meet a drinking water standard of 10 μg/L. The chemical demand for ferric chloride however is much lower than ferric sulfate as coagulant. An alternative method using ferric sludge from surface water treatment plant is demonstrated as an efficient adsorbent to remove arsenic from RO concentrate, providing a promising low cost, "waste treat waste" approach. The monovalent permselective anion exchange membranes exhibit high selectivity in removing monovalent anions over di- and multi-valent anions. The transport of sulfate and phosphate through the anion exchange membranes was negligible over a broad range of electrical current density. However, the transport of divalent cations such as calcium and magnesium increases through monovalent permselective cation exchange membranes with increasing current density. Higher overall salt concentration reduction is achieved around limiting current density while higher normalized salt removal rate in terms of mass of salt per membrane area and applied energy is attained at lower current density because the energy unitization efficiency decreases at higher current density. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Selective Learning and Teaching among Japanese and German Children

    Science.gov (United States)

    Kim, Sunae; Paulus, Markus; Sodian, Beate; Itakura, Shoji; Ueno, Mika; Senju, Atsushi; Proust, Joëlle

    2018-01-01

    Despite an increasing number of studies demonstrating that young children selectively learn from others, and a few studies of children's selective teaching, the evidence almost exclusively comes from Western cultures, and cross-cultural comparison in this line of work is very rare. In the present research, we investigated Japanese and German…

  5. Over-Selectivity as a Learned Response

    Science.gov (United States)

    Reed, Phil; Petrina, Neysa; McHugh, Louise

    2011-01-01

    An experiment investigated the effects of different levels of task complexity in pre-training on over-selectivity in a subsequent match-to-sample (MTS) task. Twenty human participants were divided into two groups; exposed either to a 3-element, or a 9-element, compound stimulus as a sample during MTS training. After the completion of training,…

  6. Learning a New Selection Rule in Visual and Frontal Cortex.

    Science.gov (United States)

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

    2016-08-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

  7. Joint Feature Selection and Classification for Multilabel Learning.

    Science.gov (United States)

    Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

    2018-03-01

    Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

  8. Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Guangyong Gao

    2015-01-01

    Full Text Available Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE technique. Firstly, the extreme learning machine (ELM with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED predictor and gradient-adjusted predictor (GAP, the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches.

  9. Machine learning techniques to select variable stars

    Directory of Open Access Journals (Sweden)

    García-Varela Alejandro

    2017-01-01

    Full Text Available In order to perform a supervised classification of variable stars, we propose and evaluate a set of six features extracted from the magnitude density of the light curves. They are used to train automatic classification systems using state-of-the-art classifiers implemented in the R statistical computing environment. We find that random forests is the most successful method to select variables.

  10. Altered brain activation in a reversal learning task unmasks adaptive changes in cognitive control in writer's cramp.

    Science.gov (United States)

    Zeuner, Kirsten E; Knutzen, Arne; Granert, Oliver; Sablowsky, Simone; Götz, Julia; Wolff, Stephan; Jansen, Olav; Dressler, Dirk; Schneider, Susanne A; Klein, Christine; Deuschl, Günther; van Eimeren, Thilo; Witt, Karsten

    2016-01-01

    Previous receptor binding studies suggest dopamine function is altered in the basal ganglia circuitry in task-specific dystonia, a condition characterized by contraction of agonist and antagonist muscles while performing specific tasks. Dopamine plays a role in reward-based learning. Using fMRI, this study compared 31 right-handed writer's cramp patients to 35 controls in reward-based learning of a probabilistic reversal-learning task. All subjects chose between two stimuli and indicated their response with their left or right index finger. One stimulus response was rewarded 80%, the other 20%. After contingencies reversal, the second stimulus response was rewarded in 80%. We further linked the DRD2/ANKK1-TaqIa polymorphism, which is associated with 30% reduction of the striatal dopamine receptor density with reward-based learning and assumed impaired reversal learning in A + subjects. Feedback learning in patients was normal. Blood-oxygen level dependent (BOLD) signal in controls increased with negative feedback in the insula, rostral cingulate cortex, middle frontal gyrus and parietal cortex (pFWE based learning. The dACC is connected with the basal ganglia-thalamo-loop modulated by dopaminergic signaling. This finding suggests disturbed integration of reinforcement history in decision making and implicate that the reward system might contribute to the pathogenesis in writer's cramp.

  11. Cognitive aspects of congenital learned helplessness and its reversal by the monoamine oxidase (MAO)-B inhibitor deprenyl.

    Science.gov (United States)

    Schulz, Daniela; Mirrione, Martine M; Henn, Fritz A

    2010-02-01

    Cognitive processes are assumed to change with learned helplessness, an animal model of depression, but little is known about such deficits. Here we investigated the role of cognitive and related functions in selectively bred helpless (cLH, n=10), non-helpless (cNLH, n=12) and wild type (WT, n=8) Sprague Dawley rats. The animals were exposed to an open field for 10min on each of two test days. On the third day, an object exploration paradigm was carried out. The animals were later tested for helplessness. Both cLH and cNLH rats were more active than WTs on the first day in the open field. Over trials, cNLH and WT rats lowered their activity less than cLH rats. This resistance-to-habituation co-varied with a resistance to develop helplessness. In cLH rats, higher 'anxiety' or less time spent in the center of the open field co-varied with severe helplessness. In WTs, a greater reactivity to novel objects and to a spatially relocated object predicted lower levels of helplessness. In cLH rats (n=4-5 per group), chronic treatment with a high dose of the monoamine oxidase (MAO)-B inhibitor deprenyl (10mg/kg; i.p.), an anti-Parkinson, nootropic and antidepressant drug, attenuated helplessness. Remarkably, helplessness reversal required the experience of repeated test trials, reminiscent of a learning process. Chronic deprenyl (10mg/kg; i.p.) did not alter locomotion/exploration or 'anxiety' in the open field. In conclusion, helplessness may be related to altered mechanisms of reinforcement learning and working memory, and to abnormalities in MAO-A and/or MAO-B functioning. Copyright 2009 Elsevier Inc. All rights reserved.

  12. Spatial and reversal learning in the Morris water maze are largely resistant to six hours of REM sleep deprivation following training

    Science.gov (United States)

    Walsh, Christine M.; Booth, Victoria; Poe, Gina R.

    2011-01-01

    This first test of the role of REM (rapid eye movement) sleep in reversal spatial learning is also the first attempt to replicate a much cited pair of papers reporting that REM sleep deprivation impairs the consolidation of initial spatial learning in the Morris water maze. We hypothesized that REM sleep deprivation following training would impair both hippocampus-dependent spatial learning and learning a new target location within a familiar environment: reversal learning. A 6-d protocol was divided into the initial spatial learning phase (3.5 d) immediately followed by the reversal phase (2.5 d). During the 6 h following four or 12 training trials/day of initial or reversal learning phases, REM sleep was eliminated and non-REM sleep left intact using the multiple inverted flowerpot method. Contrary to our hypotheses, REM sleep deprivation during four or 12 trials/day of initial spatial or reversal learning did not affect training performance. However, some probe trial measures indicated REM sleep-deprivation–associated impairment in initial spatial learning with four trials/day and enhancement of subsequent reversal learning. In naive animals, REM sleep deprivation during normal initial spatial learning was followed by a lack of preference for the subsequent reversal platform location during the probe. Our findings contradict reports that REM sleep is essential for spatial learning in the Morris water maze and newly reveal that short periods of REM sleep deprivation do not impair concurrent reversal learning. Effects on subsequent reversal learning are consistent with the idea that REM sleep serves the consolidation of incompletely learned items. PMID:21677190

  13. Least-squares reverse time migration of marine data with frequency-selection encoding

    KAUST Repository

    Dai, Wei; Huang, Yunsong; Schuster, Gerard T.

    2013-01-01

    The phase-encoding technique can sometimes increase the efficiency of the least-squares reverse time migration (LSRTM) by more than one order of magnitude. However, traditional random encoding functions require all the encoded shots to share

  14. STRATEGY FOR EVALUATION AND SELECTION OF SYSTEMS FOR ELECTRONIC LEARNING

    Directory of Open Access Journals (Sweden)

    Dubravka Mandušić

    2012-12-01

    Full Text Available Today`s technology supported and accelerated learning time requires constant and continuous acquisition of new knowledge. On the other hand, it does not leave enough time for additional education. Increasing number of E-learning systems, withdraws a need for precise evaluation of functionality that those systems provide; so they could be reciprocally compared. While implementing new systems for electronic learning, it is very important to pre-evaluate existing systems in order to select the one that meets all defined parameters, with low costs/investment. Proper evaluation can save time and money.

  15. Comparison of the efficacy of two anticonvulsants, phenytoin and valproate to improve PCP and d-amphetamine induced deficits in a reversal learning task in the rat

    Directory of Open Access Journals (Sweden)

    Nagi F Idris

    2009-06-01

    Full Text Available Recent studies in our laboratory have shown that PCP (phencyclidine and d-amphetamine induce a cognitive deficit in rats, in a paradigm of potential relevance for the pathology of schizophrenia. Atypical, but not classical antipsychotics and the anticonvulsant, lamotrigine have been shown to prevent a selective reversal learning deficit induced by PCP. In contrast, only haloperidol reversed the d-amphetamine-induced deficit. The present study aimed to explore the ability of two anticonvulsants with differing mechanism of action, valproate and phenytoin to attenuate the cognitive deficits induced by PCP and d-amphetamine in the reversal learning paradigm. PCP at 1.5mg/kg and d-amphetamine at 0.5mg/kg both produced a selective and significant reduction in performance of the reversal phase with no effect on the initial phase of the task in female-hooded Lister rats. Valproate (25-200mg/kg and phenytoin (25-50mg/kg had no effect on performance when administered alone. Valproate (100-200mg/kg, whose principle action is thought to be the enhancement of GABA transmission, was unable to prevent the cognitive deficit induced by either PCP or d-amphetamine. Conversely, phenytoin (50mg/kg, a use-dependent sodium channel inhibitor, significantly prevented the deficit induced by PCP, but not d-amphetamine. These results add to our earlier work with lamotrigine, and suggest that sodium channel blockade may be a mechanism by which some anticonvulsant drugs can prevent the PCP-induced deficit. These data have implications for the use of anticonvulsant drugs in the treatment of cognitive or psychotic disorders.

  16. Feedback-related negativity codes outcome valence, but not outcome expectancy, during reversal learning.

    Science.gov (United States)

    von Borries, A K L; Verkes, R J; Bulten, B H; Cools, R; de Bruijn, E R A

    2013-12-01

    Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures--that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model predicts an FRN on negative prediction errors, as well as implying a role for the FRN in learning and the adaptation of behavior. However, these predictions have recently been challenged. Notably, studies so far have used tasks in which the outcomes have been contingent on the response. In these paradigms, the need to adapt behavioral responses is present only for negative, not for positive feedback. The goal of the present study was to investigate the effects of positive as well as negative violations of expectancy on FRN amplitudes, without the usual confound of behavioral adjustments. A reversal-learning task was employed in which outcome value and outcome expectancy were orthogonalized; that is, both positive and negative outcomes were equally unexpected. The results revealed a double dissociation, with effects of valence but not expectancy on the FRN and, conversely, effects of expectancy but not valence on the P300. While FRN amplitudes were largest for negative-outcome trials, irrespective of outcome expectancy, P300 amplitudes were largest for unexpected-outcome trials, irrespective of outcome valence. These FRN effects were interpreted to reflect an evaluation along a good-bad dimension, rather than reflecting a negative prediction error or a role in behavioral adaptation. By contrast, the P300 reflects the updating of information relevant for behavior in a changing context.

  17. Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-01-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory of mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children’s preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children’s developing social cognition and early learning. PMID:26211504

  18. Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-11-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory-of-mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children's preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children's developing social cognition and early learning. © 2015 The British Psychological Society.

  19. Sexual selection accounts for the geographic reversal of sexual size dimorphism in the dung fly, sepsis punctum (Diptera: Sepsidae).

    Science.gov (United States)

    Puniamoorthy, Nalini; Schäfer, Martin A; Blanckenhorn, Wolf U

    2012-07-01

    Sexual size dimorphism (SSD) varies widely across and within species. The differential equilibrium model of SSD explains dimorphism as the evolutionary outcome of consistent differences in natural and sexual selection between the sexes. Here, we comprehensively examine a unique cross-continental reversal in SSD in the dung fly, Sepsis punctum. Using common garden laboratory experiments, we establish that SSD is male-biased in Europe and female-biased in North America. When estimating sexual (pairing success) and fecundity selection (clutch size of female partner) on males under three operational sex ratios (OSRs), we find that the intensity of sexual selection is significantly stronger in European versus North American populations, increasing with male body size and OSR in the former only. Fecundity selection on female body size also increases strongly with egg number and weakly with egg volume, however, equally on both continents. Finally, viability selection on body size in terms of intrinsic (physiological) adult life span in the laboratory is overall nil and does not vary significantly across all seven populations. Although it is impossible to prove causality, our results confirm the differential equilibrium model of SSD in that differences in sexual selection intensity account for the reversal in SSD in European versus North American populations, presumably mediating the ongoing speciation process in S. punctum. © 2012 The Author(s).

  20. Selecting Learning Tasks: Effects of Adaptation and Shared Control on Learning Efficiency and Task Involvement

    Science.gov (United States)

    Corbalan, Gemma; Kester, Liesbeth; van Merrienboer, Jeroen J. G.

    2008-01-01

    Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity [Baddeley, A. D. (1992). Working memory. "Science, 255", 556-559]. To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner's competence level and perceived task…

  1. Project Selection in the Design Studio: Absence of Learning Environments

    Science.gov (United States)

    Basa, Inci

    2010-01-01

    Project selection is an essential matter of design teaching. Based on observations of a specific curriculum, the author claims that a wide repertoire of subjects including offices, restaurants, hotels, and other public places are used to prepare design students, but that schools and other "learning environments/ schools" are similarly…

  2. Biologically Predisposed Learning and Selective Associations in Amygdalar Neurons

    Science.gov (United States)

    Chung, Ain; Barot, Sabiha K.; Kim, Jeansok J.; Bernstein, Ilene L.

    2011-01-01

    Modern views on learning and memory accept the notion of biological constraints--that the formation of association is not uniform across all stimuli. Yet cellular evidence of the encoding of selective associations is lacking. Here, conditioned stimuli (CSs) and unconditioned stimuli (USs) commonly employed in two basic associative learning…

  3. Lack of Pannexin 1 Alters Synaptic GluN2 Subunit Composition and Spatial Reversal Learning in Mice.

    Science.gov (United States)

    Gajardo, Ivana; Salazar, Claudia S; Lopez-Espíndola, Daniela; Estay, Carolina; Flores-Muñoz, Carolina; Elgueta, Claudio; Gonzalez-Jamett, Arlek M; Martínez, Agustín D; Muñoz, Pablo; Ardiles, Álvaro O

    2018-01-01

    Long-term potentiation (LTP) and long-term depression (LTD) are two forms of synaptic plasticity that have been considered as the cellular substrate of memory formation. Although LTP has received considerable more attention, recent evidences indicate that LTD plays also important roles in the acquisition and storage of novel information in the brain. Pannexin 1 (Panx1) is a membrane protein that forms non-selective channels which have been shown to modulate the induction of hippocampal synaptic plasticity. Animals lacking Panx1 or blockade of Pannexin 1 channels precludes the induction of LTD and facilitates LTP. To evaluate if the absence of Panx1 also affects the acquisition of rapidly changing information we trained Panx1 knockout (KO) mice and wild type (WT) littermates in a visual and hidden version of the Morris water maze (MWM). We found that KO mice find the hidden platform similarly although slightly quicker than WT animals, nonetheless, when the hidden platform was located in the opposite quadrant (OQ) to the previous learned location, KO mice spent significantly more time in the previous quadrant than in the new location indicating that the absence of Panx1 affects the reversion of a previously acquired spatial memory. Consistently, we observed changes in the content of synaptic proteins critical to LTD, such as GluN2 subunits of N-methyl-D-aspartate receptors (NMDARs), which changed their contribution to synaptic plasticity in conditions of Panx1 ablation. Our findings give further support to the role of Panx1 channels on the modulation of synaptic plasticity induction, learning and memory processes.

  4. Lack of Pannexin 1 Alters Synaptic GluN2 Subunit Composition and Spatial Reversal Learning in Mice

    Science.gov (United States)

    Gajardo, Ivana; Salazar, Claudia S.; Lopez-Espíndola, Daniela; Estay, Carolina; Flores-Muñoz, Carolina; Elgueta, Claudio; Gonzalez-Jamett, Arlek M.; Martínez, Agustín D.; Muñoz, Pablo; Ardiles, Álvaro O.

    2018-01-01

    Long-term potentiation (LTP) and long-term depression (LTD) are two forms of synaptic plasticity that have been considered as the cellular substrate of memory formation. Although LTP has received considerable more attention, recent evidences indicate that LTD plays also important roles in the acquisition and storage of novel information in the brain. Pannexin 1 (Panx1) is a membrane protein that forms non-selective channels which have been shown to modulate the induction of hippocampal synaptic plasticity. Animals lacking Panx1 or blockade of Pannexin 1 channels precludes the induction of LTD and facilitates LTP. To evaluate if the absence of Panx1 also affects the acquisition of rapidly changing information we trained Panx1 knockout (KO) mice and wild type (WT) littermates in a visual and hidden version of the Morris water maze (MWM). We found that KO mice find the hidden platform similarly although slightly quicker than WT animals, nonetheless, when the hidden platform was located in the opposite quadrant (OQ) to the previous learned location, KO mice spent significantly more time in the previous quadrant than in the new location indicating that the absence of Panx1 affects the reversion of a previously acquired spatial memory. Consistently, we observed changes in the content of synaptic proteins critical to LTD, such as GluN2 subunits of N-methyl-D-aspartate receptors (NMDARs), which changed their contribution to synaptic plasticity in conditions of Panx1 ablation. Our findings give further support to the role of Panx1 channels on the modulation of synaptic plasticity induction, learning and memory processes. PMID:29692709

  5. Lack of Pannexin 1 Alters Synaptic GluN2 Subunit Composition and Spatial Reversal Learning in Mice

    Directory of Open Access Journals (Sweden)

    Ivana Gajardo

    2018-04-01

    Full Text Available Long-term potentiation (LTP and long-term depression (LTD are two forms of synaptic plasticity that have been considered as the cellular substrate of memory formation. Although LTP has received considerable more attention, recent evidences indicate that LTD plays also important roles in the acquisition and storage of novel information in the brain. Pannexin 1 (Panx1 is a membrane protein that forms non-selective channels which have been shown to modulate the induction of hippocampal synaptic plasticity. Animals lacking Panx1 or blockade of Pannexin 1 channels precludes the induction of LTD and facilitates LTP. To evaluate if the absence of Panx1 also affects the acquisition of rapidly changing information we trained Panx1 knockout (KO mice and wild type (WT littermates in a visual and hidden version of the Morris water maze (MWM. We found that KO mice find the hidden platform similarly although slightly quicker than WT animals, nonetheless, when the hidden platform was located in the opposite quadrant (OQ to the previous learned location, KO mice spent significantly more time in the previous quadrant than in the new location indicating that the absence of Panx1 affects the reversion of a previously acquired spatial memory. Consistently, we observed changes in the content of synaptic proteins critical to LTD, such as GluN2 subunits of N-methyl-D-aspartate receptors (NMDARs, which changed their contribution to synaptic plasticity in conditions of Panx1 ablation. Our findings give further support to the role of Panx1 channels on the modulation of synaptic plasticity induction, learning and memory processes.

  6. The effect of ethanol on reversal learning in honey bees (Apis mellifera anatolica): Response inhibition in a social insect model.

    Science.gov (United States)

    Abramson, Charles I; Craig, David Philip Arthur; Varnon, Christopher A; Wells, Harrington

    2015-05-01

    We investigated the effects of ethanol on reversal learning in honey bees (Apis mellifera anatolica). The rationale behind the present experiment was to determine the species generality of the effect of ethanol on response inhibition. Subjects were originally trained to associate either a cinnamon or lavender odor with a sucrose feeding before a reversal of the conditioned stimuli. We administered 15 μL of ethanol at varying doses (0%, 2.5%, 5%, 10%, or 20%) according to group assignment. Ethanol was either administered 5 min before original discrimination training or 5 min before the stimuli reversal. We analyzed the effects of these three manipulations via a recently developed individual analysis that eschews aggregate assessments in favor of a model that conceptualizes learning as occurring in individual organisms. We measured responding in the presence of conditioned stimuli associated with a sucrose feeding, responding in the presence of conditioned stimuli associated with distilled water, and responding in the presence of the unconditioned stimulus (sucrose). Our analyses revealed the ethanol dose manipulation lowered responding for all three measures at increasingly higher doses, which suggests ethanol served as a general behavioral suppressor. Consistent with previous ethanol reversal literature, we found administering ethanol before the original discrimination phase or before the reversal produced inconsistent patterns of responding at varying ethanol doses. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Serial Entrepreneurship, Learning by Doing and Self-selection

    DEFF Research Database (Denmark)

    Rocha, Vera; Carneiro, Anabela; Varum, Celeste

    2015-01-01

    of the person-specific effect, using information on individuals’ past histories in paid employment, confirm that serial entrepreneurs exhibit, on average, a larger person-specific effect than non-serial business owners. Moreover, ignoring serial entrepreneurs’ self-selection overestimates learning by doing......It remains a question whether serial entrepreneurs typically perform better than their novice counterparts owing to learning by doing effects or mostly because they are a selected sample of higher-than-average ability entrepreneurs. This paper tries to unravel these two effects by exploring a novel...... empirical strategy based on continuous time duration models with selection. We use a large longitudinal matched employer-employee dataset that allows us to identify about 220,000 individuals who have left their first entrepreneurial experience, out of which over 35,000 became serial entrepreneurs. We...

  8. Maternal obesity caused by overnutrition exposure leads to reversal learning deficits and striatal disturbance in rats.

    Directory of Open Access Journals (Sweden)

    Ting Wu

    Full Text Available Maternal obesity caused by overnutrition during pregnancy increases susceptibility to metabolic risks in adulthood, such as obesity, insulin resistance, and type 2 diabetes; however, whether and how it affects the cognitive system associated with the brain remains elusive. Here, we report that pregnant obesity induced by exposure to excessive high fatty or highly palatable food specifically impaired reversal learning, a kind of adaptive behavior, while leaving serum metabolic metrics intact in the offspring of rats, suggesting a much earlier functional and structural defects possibly occurred in the central nervous system than in the metabolic system in the offspring born in unfavorable intrauterine nutritional environment. Mechanically, we found that above mentioned cognitive inflexibility might be associated with significant striatal disturbance including impaired dopamine homeostasis and disrupted leptin signaling in the adult offspring. These collective data add a novel perspective of understanding the adverse postnatal sequelae in central nervous system induced by developmental programming and the related molecular mechanism through which priming of risk for developmental disorders may occur during early life.

  9. Automatic learning-based beam angle selection for thoracic IMRT

    International Nuclear Information System (INIS)

    Amit, Guy; Marshall, Andrea; Purdie, Thomas G.; Jaffray, David A.; Levinshtein, Alex; Hope, Andrew J.; Lindsay, Patricia; Pekar, Vladimir

    2015-01-01

    Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume

  10. Preparation and selected properties of ion-containing reverse osmosis membranes

    International Nuclear Information System (INIS)

    Hegazy, E.S.A.; Dessouki, A.M.

    1986-01-01

    Ion-containing reverse osmosis membranes were prepared by the post radiation grafting of 4-vinylpyridine onto low density polyethylene films, followed by quaternization of the pyridine rings in the graft chains to confer ionic character to the membranes. The effect of some preparation conditions on the grafting yield was investigated. Different quaternizing agents such as methyl iodide, allyl bromide, and hydrochloric acid were used for the quaternization of the graft chains. The effect of quaternizing agent and degree of grafting on the properties of the membranes such as swelling behaviour, specific electric resistance, water flux and salt rejection, was investigated. The properties of these ionic membranes did not deteriorate with the operation time and they show a great promise for the use in the field of reverse osmosis desalination of sea water. (author)

  11. A numeric comparison of variable selection algorithms for supervised learning

    International Nuclear Information System (INIS)

    Palombo, G.; Narsky, I.

    2009-01-01

    Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.

  12. Vascular Risk Factors and Diseases Modulate Deficits of Reward-Based Reversal Learning in Acute Basal Ganglia Stroke.

    Directory of Open Access Journals (Sweden)

    Ulla K Seidel

    Full Text Available Besides motor function, the basal ganglia have been implicated in feedback learning. In patients with chronic basal ganglia infarcts, deficits in reward-based reversal learning have previously been described.We re-examined the acquisition and reversal of stimulus-stimulus-reward associations and acquired equivalence in eleven patients with acute basal ganglia stroke (8 men, 3 women; 57.8±13.3 years, whose performance was compared eleven healthy subjects of comparable age, sex distribution and education, who were recruited outside the hospital. Eleven hospitalized patients with a similar vascular risk profile as the stroke patients but without stroke history served as clinical control group.In a neuropsychological assessment 7±3 days post-stroke, verbal and spatial short-term and working memory and inhibition control did not differ between groups. Compared with healthy subjects, control patients with vascular risk factors exhibited significantly reduced performance in the reversal phase (F[2,30] = 3.47; p = 0.044; post-hoc comparison between risk factor controls and healthy controls: p = 0.030, but not the acquisition phase (F[2,30] = 1.01; p = 0.376 and the acquired equivalence (F[2,30] = 1.04; p = 0.367 tasks. In all tasks, the performance of vascular risk factor patients closely resembled that of basal ganglia stroke patients. Correlation studies revealed a significant association of the number of vascular risk factors with reversal learning (r = -0.33, p = 0.012, but not acquisition learning (r = -0.20, p = 0.121 or acquired equivalence (r = -0.22, p = 0.096.The previously reported impairment of reward-based learning may be attributed to vascular risk factors and associated diseases, which are enriched in stroke patients. This study emphasizes the necessity of appropriate control subjects in cognition studies.

  13. Pairwise Constraint-Guided Sparse Learning for Feature Selection.

    Science.gov (United States)

    Liu, Mingxia; Zhang, Daoqiang

    2016-01-01

    Feature selection aims to identify the most informative features for a compact and accurate data representation. As typical supervised feature selection methods, Lasso and its variants using L1-norm-based regularization terms have received much attention in recent studies, most of which use class labels as supervised information. Besides class labels, there are other types of supervised information, e.g., pairwise constraints that specify whether a pair of data samples belong to the same class (must-link constraint) or different classes (cannot-link constraint). However, most of existing L1-norm-based sparse learning methods do not take advantage of the pairwise constraints that provide us weak and more general supervised information. For addressing that problem, we propose a pairwise constraint-guided sparse (CGS) learning method for feature selection, where the must-link and the cannot-link constraints are used as discriminative regularization terms that directly concentrate on the local discriminative structure of data. Furthermore, we develop two variants of CGS, including: 1) semi-supervised CGS that utilizes labeled data, pairwise constraints, and unlabeled data and 2) ensemble CGS that uses the ensemble of pairwise constraint sets. We conduct a series of experiments on a number of data sets from University of California-Irvine machine learning repository, a gene expression data set, two real-world neuroimaging-based classification tasks, and two large-scale attribute classification tasks. Experimental results demonstrate the efficacy of our proposed methods, compared with several established feature selection methods.

  14. Hippocampal theta activity is selectively associated with contingency detection but not discrimination in rabbit discrimination-reversal eyeblink conditioning.

    Science.gov (United States)

    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.

  15. Word learning emerges from the interaction of online referent selection and slow associative learning

    Science.gov (United States)

    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

  16. Learning to Select Supplier Portfolios for Service Supply Chain.

    Science.gov (United States)

    Zhang, Rui; Li, Jingfei; Wu, Shaoyu; Meng, Dabin

    2016-01-01

    The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.

  17. Sex-Dependent Effects of the Histone Deacetylase Inhibitor, Sodium Valproate, on Reversal Learning After Developmental Arsenic Exposure

    Directory of Open Access Journals (Sweden)

    Christina R. Steadman Tyler

    2018-06-01

    Full Text Available Several studies have demonstrated that exposure to arsenic in drinking water adversely affects brain development and cognitive function in adulthood. While the mechanism by which arsenic induces adverse neurological outcomes remains elusive, studies suggest a link between reduced levels of histone acetylation and impaired performance on a variety of behavioral tasks following arsenic exposure. Using our developmental arsenic exposure (DAE paradigm, we have previously reported reduced histone acetylation and associated histone acetyltransferase enzyme expression in the frontal cortex of C57BL/6J adult male mice, with no changes observed in the female frontal cortex. In the present study, we sought to determine if DAE produced sex-dependent deficits in frontal cortical executive function using the Y-maze acquisition and reversal learning tasks, which are specific for assessing cognitive flexibility. Further, we tested whether the administration of valproic acid, a class I–IIa histone deacetylase inhibitor, was able to mitigate behavioral and biochemical changes resulting from DAE. As anticipated, DAE inhibited acquisition and reversal learning performance in adult male, but not female, mice. Valproate treatment for 2 weeks restored reversal performance in the male arsenic-exposed offspring, while not affecting female performance. Protein levels of HDACs 1, 2, and 5 were elevated following behavioral assessment but only in DAE male mice; restoration of appropriate HDAC levels occurred after valproate treatment and was concurrent with improved behavioral performance, particularly during reversal learning. Female frontal cortical levels of HDAC enzymes were not impacted by DAE or valproate treatment. Finally, mRNA expression levels of brain-derived neurotrophic factor, Bdnf, which has been implicated in the control of frontal cortical flexibility and is regulated by HDAC5, were elevated in DAE male mice and restored to normal levels following HDACi

  18. Whole brain radiation-induced impairments in learning and memory are time-sensitive and reversible by systemic hypoxia.

    Directory of Open Access Journals (Sweden)

    Junie P Warrington

    Full Text Available Whole brain radiation therapy (WBRT is commonly used for treatment of primary and metastatic brain tumors; however, cognitive impairment occurs in 40-50% of brain tumor survivors. The etiology of the cognitive impairment following WBRT remains elusive. We recently reported that radiation-induced cerebrovascular rarefaction within hippocampal subregions could be completely reversed by systemic hypoxia. However, the effects of this intervention on learning and memory have not been reported. In this study, we assessed the time-course for WBRT-induced impairments in contextual and spatial learning and the capacity of systemic hypoxia to reverse WBRT-induced deficits in spatial memory. A clinical fractionated series of 4.5Gy WBRT was administered to mice twice weekly for 4 weeks, and after various periods of recovery, behavioral analyses were performed. To study the effects of systemic hypoxia, mice were subjected to 11% (hypoxia or 21% oxygen (normoxia for 28 days, initiated 1 month after the completion of WBRT. Our results indicate that WBRT induces a transient deficit in contextual learning, disruption of working memory, and progressive impairment of spatial learning. Additionally, systemic hypoxia completely reversed WBRT-induced impairments in learning and these behavioral effects as well as increased vessel density persisted for at least 2 months following hypoxia treatment. Our results provide critical support for the hypothesis that cerebrovascular rarefaction is a key component of cognitive impairment post-WBRT and indicate that processes of learning and memory, once thought to be permanently impaired after WBRT, can be restored.

  19. Learning from Fables: Moral Values in Three Selected English Stories

    Science.gov (United States)

    Abrar, Mukhlash

    2016-01-01

    Fable is not just a fun story, but it certainly has the moral lesson(s) inside of the storyline. This research tries to portray ethical value(s) in three selected English fable stories as well as to let the readers know that they can learn something from the fables. With this study, the researcher also correlated the value(s) to real life and…

  20. Instance Selection for Classifier Performance Estimation in Meta Learning

    OpenAIRE

    Marcin Blachnik

    2017-01-01

    Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be inform...

  1. A pillar-layered metal-organic framework as luminescent sensor for selective and reversible response of chloroform

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Kun; Li, Shuni; Jiang, Yucheng; Hu, Mancheng; Zhai, Quan-Guo, E-mail: zhaiqg@snnu.edu.cn

    2017-03-15

    A new 3D metal-organic framework, namely, (Zn{sub 4}(H{sub 2}BPTC){sub 2}(HCOO){sub 4}){sub n} (SNNU-1, H{sub 4}BPTC=biphenyl-3,3',5,5'-tetracarboxylic acid, SNNU=Shaanxi Normal University) has been solvothermal synthesized. Four independent tetrahedral Zn atoms are connected by organic ligands to form a 2D Zn-H{sub 2}BPTC layer, which is further bridged by in-situ generated HCOO{sup -} to give the 3D pillar-layered framework of SNNU-1. Unique Zn and H{sub 2}BPTC all act as 4-connected nodes leading to a new 4,4,4-connected topological net with point symbol of (4·5·6{sup 2}·8{sup 2})(4·5{sup 2}·6{sup 2}·8)(5{sup 2}·6{sup 3}·7). Notably, intense blue emission band is observed for SNNU-1, which exhibits solvent-dependent effect. Compared to other common organic solvents, chloroform can specially improve the photoluminescent intensity of SNNU-1. Further repeated response and release experiments clearly showed that SNNU-1 can act as luminescent sensor for selective and reversible detection of chloroform. - Graphical abstract: Zn{sup 2+} ions are bridged by aromatic tetracarboxylate ligands and inorganic formate anions to give a microporous pillar layered open-framework, which exhibits not only strong photoluminescence but also selective and reversible luminescent sensing for chloroform. - Highlights: • Novel Zn-tetracarboxylate-formate microporous pillar layered open-framework. • New 4,4,4-connected topology and rod-packing net. • Solvent-dependent photoluminescent intensity. • Selective and reversible response for chloroform.

  2. PD173074, a selective FGFR inhibitor, reverses MRP7 (ABCC10-mediated MDR

    Directory of Open Access Journals (Sweden)

    Nagaraju Anreddy

    2014-06-01

    Full Text Available Multidrug resistance protein 7 (MRP7, ABCC10 is a recently identified member of the ATP-binding cassette (ABC transporter family, which adequately confers resistance to a diverse group of antineoplastic agents, including taxanes, vinca alkaloids and nucleoside analogs among others. Clinical studies indicate an increased MRP7 expression in non-small cell lung carcinomas (NSCLC compared to a normal healthy lung tissue. Recent studies revealed increased paclitaxel sensitivity in the Mrp7−/− mouse model compared to their wild-type counterparts. This demonstrates that MRP7 is a key contributor in developing drug resistance. Recently our group reported that PD173074, a specific fibroblast growth factor receptor (FGFR inhibitor, could significantly reverse P-glycoprotein-mediated MDR. However, whether PD173074 can interact with and inhibit other MRP members is unknown. In the present study, we investigated the ability of PD173074 to reverse MRP7-mediated MDR. We found that PD173074, at non-toxic concentration, could significantly increase the cellular sensitivity to MRP7 substrates. Mechanistic studies indicated that PD173074 (1 μmol/L significantly increased the intracellular accumulation and in-turn decreased the efflux of paclitaxel by inhibiting the transport activity without altering expression levels of the MRP7 protein, thereby representing a promising therapeutic agent in the clinical treatment of chemoresistant cancer patients.

  3. Evolution of learning in fluctuating environments: when selection favors both social and exploratory individual learning.

    Science.gov (United States)

    Borenstein, Elhanan; Feldman, Marcus W; Aoki, Kenichi

    2008-03-01

    Cumulative cultural change requires organisms that are capable of both exploratory individual learning and faithful social learning. In our model, an organism's phenotype is initially determined innately (by its genotypic value) or by social learning (copying a phenotype from the parental generation), and then may or may not be modified by individual learning (exploration around the initial phenotype). The environment alternates periodically between two states, each defined as a certain range of phenotypes that can survive. These states may overlap, in which case the same phenotype can survive in both states, or they may not. We find that a joint social and exploratory individual learning strategy-the strategy that supports cumulative culture-is likely to spread when the environmental states do not overlap. In particular, when the environmental states are contiguous and mutation is allowed among the genotypic values, this strategy will spread in either moderately or highly stable environments, depending on the exact nature of the individual learning applied. On the other hand, natural selection often favors a social learning strategy without exploration when the environmental states overlap. We find only partial support for the "consensus" view, which holds that individual learning, social learning, and innate determination of behavior will evolve at short, intermediate, and long environmental periodicities, respectively.

  4. Jordan-3: measuring visual reversals in children as symptoms of learning disability and attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Jordan, Brian T; Martin, Nancy; Austin, J Sue

    2012-12-01

    The purpose of this research was to establish new norms for the Jordan-3 for children ages 5 to 18 years. The research also investigated the frequency of visual reversals in children previously identified as having reading disability, attention-deficit/hyperactivity disorder, and broader learning disabilities. Participants were regular education students, ages 5 through 18 years, and special education students previously diagnosed with attention-deficit/hyperactivity disorder, reading disability, or broader learning disability. Jordan-3 Accuracy and Error raw scores were compared to assess if there was a significant difference between the two groups. Mean Accuracy and Error scores were compared for males and females. Children with learning disability and attention-deficit/hyperactivity disorder had higher reversals when compared to regular education children, which lends continued support to the Jordan-3 as a valid and reliable measure of visual reversals in children and adolescents. This study illustrates the utility of the Jordan-3 when assessing children who may require remediation to reach their academic potential.

  5. An integrated decision making model for the selection of sustainable forward and reverse logistic providers

    DEFF Research Database (Denmark)

    Govindan, Kannan; Agarwal, Vernika; Darbari, Jyoti Dhingra

    2017-01-01

    Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC...... strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper...... improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image....

  6. Stronger sexual selection in warmer waters: the case of a sex role reversed pipefish.

    Directory of Open Access Journals (Sweden)

    Nuno M Monteiro

    Full Text Available In order to answer broader questions about sexual selection, one needs to measure selection on a wide array of phenotypic traits, simultaneously through space and time. Nevertheless, studies that simultaneously address temporal and spatial variation in reproduction are scarce. Here, we aimed to investigate the reproductive dynamics of a cold-water pipefish simultaneously through time (encompassing variation within each breeding cycle and as individuals grow and space (by contrasting populations experiencing distinct water temperature regimes in order to test hypothesized differences in sexual selection. Even though the sampled populations inhabited locations with very different water temperature regimes, they exhibited considerable similarities in reproductive parameters. The most striking was the existence of a well-defined substructure in reproductive activity, where larger individuals reproduce for longer periods, which seemed dependent on a high temperature threshold for breeding rather than on the low temperatures that vary heavily according to latitude. Furthermore, the perceived disparities among populations, such as size at first reproduction, female reproductive investment, or degree of sexual size dimorphism, seemed dependent on the interplay between seawater temperature and the operational sex ratio (OSR. Contrary to our expectations of an enhanced opportunity for sexual selection in the north, we found the opposite: higher female reproductive investment coupled with increased sexual size dimorphism in warmer waters, implying that a prolonged breeding season does not necessarily translate into reduced sexual selection pressure. In fact, if the limited sex has the ability to reproduce either continuously or recurrently during the entire breeding season, an increased opportunity for sexual selection might arise from the need to compete for available partners under strongly biased OSRs across protracted breeding seasons. A more general

  7. Meta-Analytic Evidence for a Reversal Learning Effect on the Iowa Gambling Task in Older Adults.

    Science.gov (United States)

    Pasion, Rita; Gonçalves, Ana R; Fernandes, Carina; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

    2017-01-01

    Iowa Gambling Task (IGT) is one of the most widely used tools to assess economic decision-making. However, the research tradition on aging and the Iowa Gambling Task (IGT) has been mainly focused on the overall performance of older adults in relation to younger or clinical groups, remaining unclear whether older adults are capable of learning along the task. We conducted a meta-analysis to examine older adults' decision-making on the IGT, to test the effects of aging on reversal learning (45 studies) and to provide normative data on total and block net scores (55 studies). From the accumulated empirical evidence, we found an average total net score of 7.55 (±25.9). We also observed a significant reversal learning effect along the blocks of the IGT, indicating that older adults inhibit the prepotent response toward immediately attractive options associated with high losses, in favor of initially less attractive options associated with long-run profit. During block 1, decisions of older adults led to a negative gambling net score, reflecting the expected initial pattern of risk-taking. However, the shift toward more safe options occurred between block 2 (small-to-medium effect size) and blocks 3, 4, 5 (medium-to-large effect size). These main findings highlight that older adults are able to move from the initial uncertainty, when the possible outcomes are unknown, to decisions based on risk, when the outcomes are learned and may be used to guide future adaptive decision-making.

  8. Selection based on the size of the black tie of the great tit may be reversed in urban habitats.

    Science.gov (United States)

    Senar, Juan Carlos; Conroy, Michael J; Quesada, Javier; Mateos-Gonzalez, Fernando

    2014-07-01

    A standard approach to model how selection shapes phenotypic traits is the analysis of capture-recapture data relating trait variation to survival. Divergent selection, however, has never been analyzed by the capture-recapture approach. Most reported examples of differences between urban and nonurban animals reflect behavioral plasticity rather than divergent selection. The aim of this paper was to use a capture-recapture approach to test the hypothesis that divergent selection can also drive local adaptation in urban habitats. We focused on the size of the black breast stripe (i.e., tie width) of the great tit (Parus major), a sexual ornament used in mate choice. Urban great tits display smaller tie sizes than forest birds. Because tie size is mostly genetically determined, it could potentially respond to selection. We analyzed capture/recapture data of male great tits in Barcelona city (N = 171) and in a nearby (7 km) forest (N = 324) from 1992 to 2008 using MARK. When modelling recapture rate, we found it to be strongly influenced by tie width, so that both for urban and forest habitats, birds with smaller ties were more trap-shy and more cautious than their larger tied counterparts. When modelling survival, we found that survival prospects in forest great tits increased the larger their tie width (i.e., directional positive selection), but the reverse was found for urban birds, with individuals displaying smaller ties showing higher survival (i.e., directional negative selection). As melanin-based tie size seems to be related to personality, and both are heritable, results may be explained by cautious personalities being favored in urban environments. More importantly, our results show that divergent selection can be an important mechanism in local adaptation to urban habitats and that capture-recapture is a powerful tool to test it.

  9. Reversible switch between the nanoporous and the nonporous state of amphiphilic block copolymer films regulated by selective swelling.

    Science.gov (United States)

    Yan, Nina; Wang, Yong

    2015-09-21

    Switchable nanoporous films, which can repeatedly alternate their porosities, are of great interest in a diversity of fields. Currently these intelligent materials are mostly based on polyelectrolytes and their porosities can change only in relatively narrow ranges, typically under wet conditions, severely limiting their applications. Here we develop a new system, which is capable of reversibly switching between a highly porous state and a nonporous state dozens of times regulated simply by exposure to selective solvents. In this system nanopores are created or reversibly eliminated in films of a block copolymer, polystyrene-block-poly(2-vinyl pyridine) (PS-b-P2VP), by exposing the films to P2VP-selective or PS-selective solvents, respectively. The mechanism of the switch is based on the selective swelling of the constituent blocks in corresponding solvents, which is a nondestructive and easily controllable process enabling the repeatable and ample switch between the open and the closed state. Systematic microscopic and ellipsometric characterization methods are performed to elucidate the pore-closing course induced by nonsolvents and the cycling between the pore-open and the pore-closed state up to 20 times. The affinity of the solvent for PS blocks is found to play a dominating role in determining the pore-closing process and the porosities of the pore-open films increase with the cycling numbers as a result of loose packing conditions of the polymer chains. We finally demonstrate the potential applications of these films as intelligent antireflection coatings and drug carriers.

  10. [Selectivity tuning in multi-binary eluents for reversed-phase liquid chromatography (RPLC)].

    Science.gov (United States)

    Lü, M; Zou, H; Liang, X; Lu, P

    1999-01-01

    In this article, the retention equation and the relationship between retention parameters and the parameters of molecular structure deduced from statistical thermodynamics in RPLC have been used to explain the difference of selectivity towards a particular species of compounds polycyclic aromatic hydrocarbons (PAHs). Methanol/water, acetonitrile/water and isopropanol/acetonitrile have been provided in advance, then the retention behaviors of sixteen PAHs under three binary solvent systems have been investigated. It is found that each pair of binary solvents of methanol/water, acetonitrile/water and isopropanol/acetonitrile has its own unique selectivity. The best selectivity obtained for acenaphthene and fluorene is methanol/water system for fluoranthene and pyrene is acetonitrile/water, and for benzo[g,h,i]perylene and dibenzo[a,h]anthracene is isopropanol/acetonitrile. So a three-stepwise gradient elution of multi-binary mobile phase can be chosen for separation of 16 PAHs.

  11. Instance Selection for Classifier Performance Estimation in Meta Learning

    Directory of Open Access Journals (Sweden)

    Marcin Blachnik

    2017-11-01

    Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.

  12. Chemogenetic locus coeruleus activation restores reversal learning in a rat model of Alzheimer's disease.

    Science.gov (United States)

    Rorabaugh, Jacki M; Chalermpalanupap, Termpanit; Botz-Zapp, Christian A; Fu, Vanessa M; Lembeck, Natalie A; Cohen, Robert M; Weinshenker, David

    2017-11-01

    See Grinberg and Heinsen (doi:10.1093/brain/awx261) for a scientific commentary on this article. Clinical evidence suggests that aberrant tau accumulation in the locus coeruleus and noradrenergic dysfunction may be a critical early step in Alzheimer’s disease progression. Yet, an accurate preclinical model of these phenotypes that includes early pretangle tau accrual in the locus coeruleus, loss of locus coeruleus innervation and deficits locus coeruleus/norepinephrine modulated behaviours, does not exist, hampering the identification of underlying mechanisms and the development of locus coeruleus-based therapies. Here, a transgenic rat (TgF344-AD) expressing disease-causing mutant amyloid precursor protein (APPsw) and presenilin-1 (PS1ΔE9) was characterized for histological and behavioural signs of locus coeruleus dysfunction reminiscent of mild cognitive impairment/early Alzheimer’s disease. In TgF344-AD rats, hyperphosphorylated tau was detected in the locus coeruleus prior to accrual in the medial entorhinal cortex or hippocampus, and tau pathology in the locus coeruleus was negatively correlated with noradrenergic innervation in the medial entorhinal cortex. Likewise, TgF344-AD rats displayed progressive loss of hippocampal norepinephrine levels and locus coeruleus fibres in the medial entorhinal cortex and dentate gyrus, with no frank noradrenergic cell body loss. Cultured mouse locus coeruleus neurons expressing hyperphosphorylation-prone mutant human tau had shorter neurites than control neurons, but similar cell viability, suggesting a causal link between pretangle tau accrual and altered locus coeruleus fibre morphology. TgF344-AD rats had impaired reversal learning in the Morris water maze compared to their wild-type littermates, which was rescued by chemogenetic locus coeruleus activation via designer receptors exclusively activated by designer drugs (DREADDs). Our results indicate that TgF344-AD rats uniquely meet several key criteria for a

  13. Selective cooling on land supports cloud formation by cosmic ray during geomagnetic reversals

    Science.gov (United States)

    Kitaba, I.; Hyodo, M.; Nakagawa, T.; Katoh, S.; Dettman, D. L.; Sato, H.

    2017-12-01

    On geological time scales, the galactic cosmic ray (GCR) flux at the Earth's surface has increased significantly during many short time intervals. There is a growing body of evidence that suggests that climatic cooling occurred during these episodes. Cloud formation by GCR has been claimed as the most likely cause of the linkage. However, the mechanism is not fully understood due to the difficulty of accurately estimating the amount of cloud cover in the geologic past. Our study focused on the geomagnetic field and climate in East Asia. The Earth's magnetic field provides a shield against GCR. The East Asian climate reflects the temperature balance between the Eurasian landmass and the Pacific Ocean that drives monsoon circulation.Two geomagnetic polarity reversals occurred at 780 ka and 1,070 ka. At these times the geomagnetic field decreased to about 10% of its present level causing a near doubling of the GCR flux. Temperature and rainfall amounts during these episodes were reconstructed using pollen in sediment cores from Osaka Bay, Japan. The results show a more significant temperature drop on the Eurasian continent than over the Pacific, and a decrease of summer rainfall in East Asia (i.e. a weakening of East Asian summer monsoon). These observed climate changes can be accounted for if the landmasses were more strongly cooled than the oceans. The simplest mechanism behind such asymmetric cooling is the so-called `umbrella effect' (increased cloud cover blocking solar radiation) that induces greater cooling of objects with smaller heat capacities.

  14. Conditional reduction of adult born doublecortin-positive neurons reversibly impairs selective behaviours

    Directory of Open Access Journals (Sweden)

    Lillian eGarrett

    2015-11-01

    Full Text Available Adult neurogenesis occurs in the adult mammalian subventricular zone (SVZ along the walls of the lateral ventricles and the subgranular zone (SGZ of the hippocampal dentate gyrus. While a burgeoning body of research implicates adult neurogenesis in olfactory bulb (OB - and hippocampal-related behaviors, the precise function continues to elude. To further assess the behavioral importance of adult neurogenesis, we herein generated a novel inducible transgenic mouse model of adult neurogenesis reduction where mice with CreERT2 under doublecortin (DCX promoter control were crossed with mice where diphtheria toxin A (DTA was driven by the Rosa26 promoter. Activation of DTA, through the administration of tamoxifen (TAM, results in a specific reduction of DCX+ immature neurons in both the hippocampal dentate gyrus and OB. We show that the decrease of DCX+ cells causes impaired social discrimination ability in both young adult (from 3 months and middle (from 10 months aged mice. Furthermore, these animals showed an age-independent altered coping behavior in the Forced Swim Test without clear changes in anxiety-related behavior. Notably, these behavior changes were reversible on repopulating the neurogenic zones with DCX+ cells on cessation of the tamoxifen treatment, demonstrating the specificity of this effect. Overall, these results support the notion that adult neurogenesis plays a role in social memory and in stress coping but not necessarily in anxiety-related behavior.

  15. Column selectivity in reversed-phase liquid chromatography I. A general quantitative relationship.

    Science.gov (United States)

    Wilson, N S; Nelson, M D; Dolan, J W; Snyder, L R; Wolcott, R G; Carr, P W

    2002-07-05

    Retention factors k have been measured for 67 neutral, acidic and basic solutes of highly diverse molecular structure (size, shape, polarity, hydrogen bonding, pKa, etc.) on 10 different C18 columns (other conditions constant). These data have been combined with k values from a previous study (86 solutes, five different C8 and C18 columns) to develop a six-term equation for the correlation of retention as a function of solute and column. Values of k can be correlated with an accuracy of +/- 1-2% (1 standard deviation). This suggests that all significant contributions to column selectivity have been identified (and can be measured) for individual alkyl-silica columns which do not have an embedded polar group. That is, columns of the latter kind can be quantitatively characterized in terms of selectivity for use in the separation of any sample.

  16. Dopamine D2 receptors mediate two-odor discrimination and reversal learning in C57BL/6 mice

    Directory of Open Access Journals (Sweden)

    Grandy David K

    2004-04-01

    Full Text Available Abstract Background Dopamine modulation of neuronal signaling in the frontal cortex, midbrain, and striatum is essential for processing and integrating diverse external sensory stimuli and attaching salience to environmental cues that signal causal relationships, thereby guiding goal-directed, adaptable behaviors. At the cellular level, dopamine signaling is mediated through D1-like or D2-like receptors. Although a role for D1-like receptors in a variety of goal-directed behaviors has been identified, an explicit involvement of D2 receptors has not been clearly established. To determine whether dopamine D2 receptor-mediated signaling contributes to associative and reversal learning, we compared C57Bl/6J mice that completely lack functional dopamine D2 receptors to wild-type mice with respect to their ability to attach appropriate salience to external stimuli (stimulus discrimination and disengage from inappropriate behavioral strategies when reinforcement contingencies change (e.g. reversal learning. Results Mildly food-deprived female wild-type and dopamine D2 receptor deficient mice rapidly learned to retrieve and consume visible food reinforcers from a small plastic dish. Furthermore, both genotypes readily learned to dig through the same dish filled with sterile sand in order to locate a buried food pellet. However, the dopamine D2 receptor deficient mice required significantly more trials than wild-type mice to discriminate between two dishes, each filled with a different scented sand, and to associate one of the two odors with the presence of a reinforcer (food. In addition, the dopamine D2 receptor deficient mice repeatedly fail to alter their response patterns during reversal trials where the reinforcement rules were inverted. Conclusions Inbred C57Bl/6J mice that develop in the complete absence of functional dopamine D2 receptors are capable of olfaction but display an impaired ability to acquire odor-driven reinforcement contingencies

  17. Effects of stimulus salience on touchscreen serial reversal learning in a mouse model of fragile X syndrome

    Science.gov (United States)

    Dickson, Price E.; Corkill, Beau; McKimm, Eric; Miller, Mellessa M.; Calton, Michele A.; Goldowitz, Daniel; Blaha, Charles D.; Mittleman, Guy

    2013-01-01

    Fragile X syndrome (FXS) is the most common inherited form of intellectual disability in males and the most common genetic cause of autism. Although executive dysfunction is consistently found in humans with FXS, evidence of executive dysfunction in Fmr1 KO mice, a mouse model of FXS, has been inconsistent. One possible explanation for this is that executive dysfunction in Fmr1 KO mice, similar to humans with FXS, is only evident when cognitive demands are high. Using touchscreen operant conditioning chambers, male Fmr1 KO mice and their male wildtype littermates were tested on the acquisition of a pairwise visual discrimination followed by four serial reversals of the response rule. We assessed reversal learning performance under two different conditions. In the first, the correct stimulus was salient and the incorrect stimulus was non-salient. In the second and more challenging condition, the incorrect stimulus was salient and the correct stimulus was non-salient; this increased cognitive load by introducing conflict between sensory-driven (i.e., bottom-up) and task-dependent (i.e., top-down) signals. Fmr1 KOs displayed two distinct impairments relative to wildtype littermates. First, Fmr1 KOs committed significantly more learning-type errors during the second reversal stage, but only under high cognitive load. Second, during the first reversal stage, Fmr1 KOs committed significantly more attempts to collect a reward during the timeout following an incorrect response. These findings indicate that Fmr1 KO mice display executive dysfunction that, in some cases, is only evident under high cognitive load. PMID:23747611

  18. Evolution and natural selection: learning by playing and reflecting

    Directory of Open Access Journals (Sweden)

    David Herrero

    2014-01-01

    Full Text Available Scientific literacy is more than the simple reproduction of traditional school science knowledge and requires a set of skills, among them identifying scientific issues, explaining phenomena scientifically and using scientific evidence. Several studies have indicated that playing computer games in the classroom can support the development of students’ conceptual understanding about scientific phenomena and theories. Our paper presents a research study where the role of the video game Spore as a learning tool was analysed in a Biology class. An ethnographical perspective served as the framework for the organization and development of a workshop comprised of five sessions with 22 4th grade students, and their Biology teacher. The results show that this video game could become an interesting learning tool to improve students’ understanding of evolution and natural selection. The students could combine their previous knowledge with the academic knowledge obtained though the simulation presented by the video game. To sum up, an attempt has been made to give some empirical guidance about effective approaches to the utilisation of games in classrooms, additionally paying attention to a number of concerns related to the effectiveness of video games as learning tools.

  19. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  20. Selective attention and recognition: effects of congruency on episodic learning.

    Science.gov (United States)

    Rosner, Tamara M; D'Angelo, Maria C; MacLellan, Ellen; Milliken, Bruce

    2015-05-01

    Recent research on cognitive control has focused on the learning consequences of high selective attention demands in selective attention tasks (e.g., Botvinick, Cognit Affect Behav Neurosci 7(4):356-366, 2007; Verguts and Notebaert, Psychol Rev 115(2):518-525, 2008). The current study extends these ideas by examining the influence of selective attention demands on remembering. In Experiment 1, participants read aloud the red word in a pair of red and green spatially interleaved words. Half of the items were congruent (the interleaved words had the same identity), and the other half were incongruent (the interleaved words had different identities). Following the naming phase, participants completed a surprise recognition memory test. In this test phase, recognition memory was better for incongruent than for congruent items. In Experiment 2, context was only partially reinstated at test, and again recognition memory was better for incongruent than for congruent items. In Experiment 3, all of the items contained two different words, but in one condition the words were presented close together and interleaved, while in the other condition the two words were spatially separated. Recognition memory was better for the interleaved than for the separated items. This result rules out an interpretation of the congruency effects on recognition in Experiments 1 and 2 that hinges on stronger relational encoding for items that have two different words. Together, the results support the view that selective attention demands for incongruent items lead to encoding that improves recognition.

  1. How Important Are Student-Selected versus Instructor-Selected Literature Resources for Students' Learning and Motivation in Problem-Based Learning?

    Science.gov (United States)

    Wijnia, Lisette; Loyens, Sofie M.; Derous, Eva; Schmidt, Henk G.

    2015-01-01

    In problem-based learning students are responsible for their own learning process, which becomes evident when they must act independently, for example, when selecting literature resources for individual study. It is a matter of debate whether it is better to have students select their own literature resources or to present them with a list of…

  2. Dual fluorescent molecular substrates selectively report the activation, sustainability and reversibility of cellular PKB/Akt activity.

    Science.gov (United States)

    Shen, Duanwen; Bai, Mingfeng; Tang, Rui; Xu, Baogang; Ju, Xiaoming; Pestell, Richard G; Achilefu, Samuel

    2013-01-01

    Using a newly developed near-infrared (NIR) dye that fluoresces at two different wavelengths (dichromic fluorescence, DCF), we discovered a new fluorescent substrate for Akt, also known as protein kinase B, and a method to quantitatively report this enzyme's activity in real time. Upon insulin activation of cellular Akt, the enzyme multi-phosphorylated a single serine residue of a diserine DCF substrate in a time-dependent manner, culminating in monophospho- to triphospho-serine products. The NIR DCF probe was highly selective for the Akt1 isoform, which was demonstrated using Akt1 knockout cells derived from MMTV-ErbB2 transgenic mice. The DCF mechanism provides unparalleled potential to assess the stimulation, sustainability, and reversibility of Akt activation longitudinally. Importantly, NIR fluorescence provides a pathway to translate findings from cells to living organisms, a condition that could eventually facilitate the use of these probes in humans.

  3. Learning Curve for Seawater Reverse Osmosis Desalination Plants: Capital Cost Trend of the Past, Present, and Future

    Science.gov (United States)

    Caldera, Upeksha; Breyer, Christian

    2017-12-01

    Seawater reverse osmosis (SWRO) desalination is expected to play a pivotal role in helping to secure future global water supply. While the global reliance on SWRO plants for water security increases, there is no consensus on how the capital costs of SWRO plants will vary in the future. The aim of this paper is to analyze the past trends of the SWRO capital expenditures (capex) as the historic global cumulative online SWRO capacity increases, based on the learning curve concept. The SWRO capex learning curve is found based on 4,237 plants that came online from 1977 to 2015. A learning rate of 15% is determined, implying that the SWRO capex reduced by 15% when the cumulative capacity was doubled. Based on SWRO capacity annual growth rates of 10% and 20%, by 2030, the global average capex of SWRO plants is found to fall to 1,580 USD/(m3/d) and 1,340 USD/(m3/d), respectively. A learning curve for SWRO capital costs has not been presented previously. This research highlights the potential for decrease in SWRO capex with the increase in installation of SWRO plants and the value of the learning curve approach to estimate future SWRO capex.

  4. Positive selection results in frequent reversible amino acid replacements in the G protein gene of human respiratory syncytial virus.

    Science.gov (United States)

    Botosso, Viviane F; Zanotto, Paolo M de A; Ueda, Mirthes; Arruda, Eurico; Gilio, Alfredo E; Vieira, Sandra E; Stewien, Klaus E; Peret, Teresa C T; Jamal, Leda F; Pardini, Maria I de M C; Pinho, João R R; Massad, Eduardo; Sant'anna, Osvaldo A; Holmes, Eddie C; Durigon, Edison L

    2009-01-01

    Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a "flip-flop" phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

  5. Positive selection results in frequent reversible amino acid replacements in the G protein gene of human respiratory syncytial virus.

    Directory of Open Access Journals (Sweden)

    Viviane F Botosso

    2009-01-01

    Full Text Available Human respiratory syncytial virus (HRSV is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a "flip-flop" phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

  6. Combining selected immunomodulatory Propionibacterium freudenreichii and Lactobacillus delbrueckii strains: Reverse engineering development of an anti-inflammatory cheese.

    Science.gov (United States)

    Plé, Coline; Breton, Jérôme; Richoux, Romain; Nurdin, Marine; Deutsch, Stéphanie-Marie; Falentin, Hélène; Hervé, Christophe; Chuat, Victoria; Lemée, Riwanon; Maguin, Emmanuelle; Jan, Gwénaël; Van de Guchte, Maarten; Foligné, Benoit

    2016-04-01

    Inflammatory bowel disease (IBD) constitutes a growing public health concern in western countries. Bacteria with anti-inflammatory properties are lacking in the dysbiosis accompanying IBD. Selected strains of probiotic bacteria with anti-inflammatory properties accordingly alleviate symptoms and enhance treatment of ulcerative colitis in clinical trials. Such properties are also found in selected strains of dairy starters such as Propionibacterium freudenreichii and Lactobacillus delbrueckii (Ld). We thus investigated the possibility to develop a fermented dairy product, combining both starter and probiotic abilities of both lactic acid and propionic acid bacteria, designed to extend remissions in IBD patients. We developed a single-strain Ld-fermented milk and a two-strain P. freudenreichii and Ld-fermented experimental pressed cheese using strains previously selected for their anti-inflammatory properties. Consumption of these experimental fermented dairy products protected mice against trinitrobenzenesulfonic acid induced colitis, alleviating severity of symptoms, modulating local and systemic inflammation, as well as colonic oxidative stress and epithelial cell damages. As a control, the corresponding sterile dairy matrix failed to afford such protection. This work reveals the probiotic potential of this bacterial mixture, in the context of fermented dairy products. It opens new perspectives for the reverse engineering development of anti-inflammatory fermented foods designed for target populations with IBD, and has provided evidences leading to an ongoing pilot clinical study in ulcerative colitis patients. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Retention behavior of selected alkaloids in Reversed Phase micellar chromatographic systems

    Directory of Open Access Journals (Sweden)

    Petruczynik Anna

    2015-06-01

    Full Text Available In this work, the effects of sodium dodecyl sulfate (SDS concentrations on retention, separation selectivity, peak shapes and systems efficiency were investigated. Herein, the retention data for 11 alkaloids were determined on an RP18 silica column with mobile phases containing methanol as organic modifier, with acetate buffer at pH 3.5, and, subsequently, with the addition of sodium dodecyl sulfate (SDS. The results of this study indicate that the retention of alkaloids decreases with the increase of SDS concentration in the mobile phase. The increase of SDS concentration, however, leads to the significantly improvement of peak symmetry and the increase of theoretical plate number in all cases. The best system efficiency for most of the investigated alkaloids was obtained in a mobile phase containing 0.1 M SDS, while most symmetrical peaks were obtained through the addition of 0.3 M of SDS to the mobile phase.

  8. Forced selection of a human immunodeficiency virus type 1 variant that uses a non-self tRNA primer for reverse transcription: Involvement of viral RNA sequences and the reverse transcriptase enzyme

    NARCIS (Netherlands)

    Abbink, Truus E. M.; Beerens, Nancy; Berkhout, Ben

    2004-01-01

    Human immunodeficiency virus type 1 uses the tRNA(3)(Lys) molecule as a selective primer for reverse transcription. This primer specificity is imposed by sequence complementarity between the tRNA primer and two motifs in the viral RNA genome: the primer-binding site (PBS) and the primer activation

  9. Selective Inducible Nitric Oxide Synthase Inhibitor Reversed Zinc Chloride-Induced Spatial Memory Impairment via Increasing Cholinergic Marker Expression.

    Science.gov (United States)

    Tabrizian, Kaveh; Azami, Kian; Belaran, Maryam; Soodi, Maliheh; Abdi, Khosrou; Fanoudi, Sahar; Sanati, Mehdi; Mottaghi Dastjerdi, Negar; Soltany Rezaee-Rad, Mohammad; Sharifzadeh, Mohammad

    2016-10-01

    Zinc, an essential micronutrient and biochemical element of the human body, plays structural, catalytic, and regulatory roles in numerous physiological functions. In the current study, the effects of a pretraining oral administration of zinc chloride (10, 25, and 50 mg/kg) for 14 consecutive days and post-training bilateral intra-hippocampal infusion of 1400W as a selective inducible nitric oxide synthase (iNOS) inhibitor (10, 50, and 100 μM/side), alone and in combination, on the spatial memory retention in Morris water maze (MWM) were investigated. Animals were trained for 4 days and tested 48 h after completion of training. Also, the molecular effects of these compounds on the expression of choline acetyltransferase (ChAT), as a cholinergic marker in the CA1 region of the hippocampus and medial septal area (MSA), were evaluated. Behavioral and molecular findings of this study showed that a 2-week oral administration of zinc chloride (50 mg/kg) impaired spatial memory retention in MWM and decreased ChAT expression. Immunohistochemical analysis of post-training bilateral intra-hippocampal infusion of 1400W revealed a significant increase in ChAT immunoreactivity. Furthermore, post-training bilateral intra-hippocampal infusion of 1400W into the CA1 region of the hippocampus reversed zinc chloride-induced spatial memory impairment in MWM and significantly increased ChAT expression in comparison with zinc chloride-treated animals. Taken together, these results emphasize the role of selective iNOS inhibitors in reversing zinc chloride-induced spatial memory deficits via modulation of cholinergic marker expression.

  10. Spatial and Reversal Learning in the Morris Water Maze Are Largely Resistant to Six Hours of REM Sleep Deprivation Following Training

    Science.gov (United States)

    Walsh, Christine M.; Booth, Victoria; Poe, Gina R.

    2011-01-01

    This first test of the role of REM (rapid eye movement) sleep in reversal spatial learning is also the first attempt to replicate a much cited pair of papers reporting that REM sleep deprivation impairs the consolidation of initial spatial learning in the Morris water maze. We hypothesized that REM sleep deprivation following training would impair…

  11. Reverse engineering of fluid selection for thermodynamic cycles with cubic equations of state, using a compression heat pump as example

    International Nuclear Information System (INIS)

    Roskosch, Dennis; Atakan, Burak

    2015-01-01

    Fluid selection for thermodynamic cycles like refrigeration cycles, heat pumps or organic Rankine cycles remains an actual topic. Generally the search for a working fluid is based on experimental approaches or on a not very systematic trial and error approach, far from being elegant. An alternative method may be a theory based reverse engineering approach, proposed and investigated here: The design process should start with an optimal process and with (abstract) properties of the fluid needed to fit into this optimal process, best described by some general equation of state and the corresponding fluid-describing parameters. These should be analyzed and optimized with respect to the defined model process, which also has to be optimized simultaneously. From this information real fluids can be selected or even synthesized which have fluid defining properties in the optimum regime like critical temperature or ideal gas capacities of heat, allowing to find new working fluids, not considered so far. The number and kind of the fluid-defining parameters is mainly based on the choice of the used EOS (equation of state). The property model used in the present work is based on the cubic Peng–Robinson equation, chosen due to its moderate numerical expense, sufficient accuracy as well as a general availability of the fluid-defining parameters for many compounds. The considered model-process works between the temperature levels of 273.15 and 333.15 K and can be used as heat pump for supplying buildings with heat, typically. The objective functions are the COP (coefficient of performance) and the VHC (volumetric heating capacity) as a function of critical pressure, critical temperature, acentric factor and two coefficients for the temperature-dependent isobaric ideal gas heat capacity. Also, the steam quality at the compressor entrance has to be regarded as a problem variable. The results give clear hints regarding optimal fluid parameters of the analyzed process and deepen

  12. Fluorescent probe encapsulated hydrogel microsphere for selective and reversible detection of Hg{sup 2+}

    Energy Technology Data Exchange (ETDEWEB)

    Song, Zhenhu; Wang, Fang; Qiang, Jian; Zhang, Zhijie; Chen, Yahui; Wang, Yong; Zhang, Wei; Chen, Xiaoqiang

    2017-03-15

    We developed a simple and sensitive hydrogel sensor in the form of microspheres by using fluorescence probe encapsulated within a hydrogel matrix for the detection of Hg{sup 2+}. The traditional fluorescence probes suspended in solution are not transportable and recoverable. To overcome these disadvantages, we devised poly(ethylene glycol) diacrylate-based hydrogel microspheres in which fluorescence probe (R19S) was embedded at high density. The functionalized hydrogel microspheres were prepared by combining a microfluidic device with UV light. The hydrogel microspheres-based sensor exhibited good selectivity to Hg{sup 2+} among various metal ions and high sensitivity with a detection limit of 90 nM. Furthermore, after binding with Hg{sup 2+}, the R19S encapsulated hydrogel microspheres can be separated from testing samples easily and treated with the solution containing KI to remove Hg{sup 2+} and realize reusable detection. The current work may offer a new method for Hg{sup 2+} recognition with a more efficient manner.

  13. Awake, long-term intranasal insulin treatment does not affect object memory, odor discrimination, or reversal learning in mice.

    Science.gov (United States)

    Bell, Genevieve A; Fadool, Debra Ann

    2017-05-15

    Intranasal insulin delivery is currently being used in clinical trials to test for improvement in human memory and cognition, and in particular, for lessening memory loss attributed to neurodegenerative diseases. Studies have reported the effects of short-term intranasal insulin treatment on various behaviors, but less have examined long-term effects. The olfactory bulb contains the highest density of insulin receptors in conjunction with the highest level of insulin transport within the brain. Previous research from our laboratory has demonstrated that acute insulin intranasal delivery (IND) enhanced both short- and long-term memory as well as increased two-odor discrimination in a two-choice paradigm. Herein, we investigated the behavioral and physiological effects of chronic insulin IND. Adult, male C57BL6/J mice were intranasally treated with 5μg/μl of insulin twice daily for 30 and 60days. Metabolic assessment indicated no change in body weight, caloric intake, or energy expenditure following chronic insulin IND, but an increase in the frequency of meal bouts selectively in the dark cycle. Unlike acute insulin IND, which has been shown to cause enhanced performance in odor habituation/dishabituation and two-odor discrimination tasks in mice, chronic insulin IND did not enhance olfactometry-based odorant discrimination or olfactory reversal learning. In an object memory recognition task, insulin IND-treated mice did not perform differently than controls, regardless of task duration. Biochemical analyses of the olfactory bulb revealed a modest 1.3 fold increase in IR kinase phosphorylation but no significant increase in Kv1.3 phosphorylation. Substrate phosphorylation of IR kinase downstream effectors (MAPK/ERK and Akt signaling) proved to be highly variable. These data indicate that chronic administration of insulin IND in mice fails to enhance olfactory ability, object memory recognition, or a majority of systems physiology metabolic factors - as reported to

  14. Spatial midsession reversal learning in rats: Effects of egocentric Cue use and memory.

    Science.gov (United States)

    Rayburn-Reeves, Rebecca M; Moore, Mary K; Smith, Thea E; Crafton, Daniel A; Marden, Kelly L

    2018-07-01

    The midsession reversal task has been used to investigate behavioral flexibility and cue use in non-human animals, with results indicating differences in the degree of control by environmental cues across species. For example, time-based control has been found in rats only when tested in a T-maze apparatus and under specific conditions in which position and orientation (i.e., egocentric) cues during the intertrial interval could not be used to aid performance. Other research in an operant setting has shown that rats often produce minimal errors around the reversal location, demonstrating response patterns similar to patterns exhibited by humans and primates in this task. The current study aimed to reduce, but not eliminate, the ability for rats to utilize egocentric cues by placing the response levers on the opposite wall of the chamber in relation to the pellet dispenser. Results showed that rats made minimal errors prior to the reversal, suggesting time-based cues were not controlling responses, and that they switched to the second correct stimulus within a few trials after the reversal event. Video recordings also revealed highly structured patterns of behavior by the majority of rats, which often differed depending on which response was reinforced. We interpret these findings as evidence that rats are adept at utilizing their own egocentric cues and that these cues, along with memory for the recent response-reinforcement contingencies, aid in maximizing reinforcement over the session. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Meta-Analytic Evidence for a Reversal Learning Effect on the Iowa Gambling Task in Older Adults

    Directory of Open Access Journals (Sweden)

    Rita Pasion

    2017-10-01

    Full Text Available Iowa Gambling Task (IGT is one of the most widely used tools to assess economic decision-making. However, the research tradition on aging and the Iowa Gambling Task (IGT has been mainly focused on the overall performance of older adults in relation to younger or clinical groups, remaining unclear whether older adults are capable of learning along the task. We conducted a meta-analysis to examine older adults' decision-making on the IGT, to test the effects of aging on reversal learning (45 studies and to provide normative data on total and block net scores (55 studies. From the accumulated empirical evidence, we found an average total net score of 7.55 (±25.9. We also observed a significant reversal learning effect along the blocks of the IGT, indicating that older adults inhibit the prepotent response toward immediately attractive options associated with high losses, in favor of initially less attractive options associated with long-run profit. During block 1, decisions of older adults led to a negative gambling net score, reflecting the expected initial pattern of risk-taking. However, the shift toward more safe options occurred between block 2 (small-to-medium effect size and blocks 3, 4, 5 (medium-to-large effect size. These main findings highlight that older adults are able to move from the initial uncertainty, when the possible outcomes are unknown, to decisions based on risk, when the outcomes are learned and may be used to guide future adaptive decision-making.

  16. System Quality Characteristics for Selecting Mobile Learning Applications

    Science.gov (United States)

    Sarrab, Mohamed; Al-Shihi, Hafedh; Al-Manthari, Bader

    2015-01-01

    The majority of M-learning (Mobile learning) applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased…

  17. Selection of Learning Media Mathematics for Junior School Students

    Science.gov (United States)

    Widodo, Sri Adi; Wahyudin

    2018-01-01

    One of the factors that determine the success of mathematics learning is the learning media used. Learning media can help students to create mathematical abstract mathematics that is abstract. In addition to media, meaningful learning is a learning that is adapted to the students' cognitive development. According to Piaget, junior high school…

  18. Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis

    NARCIS (Netherlands)

    Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

    2016-01-01

    Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require

  19. Rapid Association Learning in the Primate Prefrontal Cortex in the Absence of Behavioral Reversals

    Science.gov (United States)

    Cromer, Jason A.; Machon, Michelle; Miller, Earl K.

    2011-01-01

    The PFC plays a central role in our ability to learn arbitrary rules, such as "green means go." Previous experiments from our laboratory have used conditional association learning to show that slow, gradual changes in PFC neural activity mirror monkeys' slow acquisition of associations. These previous experiments required monkeys to repeatedly…

  20. Analysis of an Interactive Technology Supported Problem-Based Learning STEM Project Using Selected Learning Sciences Interest Areas (SLSIA)

    Science.gov (United States)

    Kumar, David Devraj

    2017-01-01

    This paper reports an analysis of an interactive technology-supported, problem-based learning (PBL) project in science, technology, engineering and mathematics (STEM) from a Learning Sciences perspective using the Selected Learning Sciences Interest Areas (SLSIA). The SLSIA was adapted from the "What kinds of topics do ISLS [International…

  1. Adolescent Corticosterone and TrkB Pharmaco-Manipulations Sex-Dependently Impact Instrumental Reversal Learning Later in Life

    Directory of Open Access Journals (Sweden)

    Elizabeth T. Barfield

    2017-12-01

    Full Text Available Early-life trauma can increase the risk for, and severity of, several psychiatric illnesses. These include drug use disorders, and some correlations appear to be stronger in women. Understanding the long-term consequences of developmental stressor or stress hormone exposure and possible sex differences is critically important. So-called “reversal learning” tasks are commonly used in rodents to model cognitive deficits in stress- and addiction-related illnesses in humans. Here, we exposed mice to the primary stress hormone corticosterone (CORT during early adolescence (postnatal days 31–42, then tested behavioral flexibility in adulthood using an instrumental reversal learning task. CORT-exposed female, but not male, mice developed perseverative errors. Despite resilience to subchronic CORT exposure, males developed reversal performance impairments following exposure to physical stressors. Administration of a putative tyrosine kinase receptor B (trkB agonist, 7,8-dihydroxyflavone (7,8-DHF, during adolescence blocked CORT-induced errors in females and improved performance in males. Conversely, blockade of trkB by ANA-12 impaired performance. These data suggest that trkB-based interventions could have certain protective benefits in the context of early-life stressor exposure. We consider the implications of our findings in an extended “Discussion” section.

  2. Repeated Blockade of NMDA Receptors during Adolescence Impairs Reversal Learning and Disrupts GABAergic Interneurons in Rat Medial Prefrontal Cortex

    Directory of Open Access Journals (Sweden)

    Jitao eLi

    2016-03-01

    Full Text Available Adolescence is of particular significance to schizophrenia, since psychosis onset typically occurs in this critical period. Based on the N-methyl-D-aspartate (NMDA receptor hypofunction hypothesis of schizophrenia, in this study, we investigated whether and how repeated NMDA receptor blockade during adolescence would affect GABAergic interneurons in rat medial prefrontal cortex (mPFC and mPFC-mediated cognitive functions. Specifically, adolescent rats were subjected to intraperitoneal administration of MK-801 (0.1, 0.2, 0.4 mg/kg, a non-competitive NMDA receptor antagonist, for 14 days and then tested for reference memory and reversal learning in the water maze. The density of parvabumin (PV-, calbindin (CB- and calretinin (CR-positive neurons in mPFC were analyzed at either 24 hours or 7 days after drug cessation. We found that MK-801 treatment delayed reversal learning in the water maze without affecting initial acquisition. Strikingly, MK-801 treatment also significantly reduced the density of PV+ and CB+ neurons, and this effect persisted for 7 days after drug cessation at the dose of 0.2 mg/kg. We further demonstrated that the reduction in PV+ and CB+ neuron densities was ascribed to a downregulation of the expression levels of PV and CB, but not to neuronal death. These results parallel the behavioral and neuropathological changes of schizophrenia and provide evidence that adolescent NMDA receptors antagonism offers a useful tool for unraveling the etiology of the disease.

  3. Using a multi-state Learning Community as an implementation strategy for immediate postpartum long-acting reversible contraception.

    Science.gov (United States)

    DeSisto, Carla L; Estrich, Cameron; Kroelinger, Charlan D; Goodman, David A; Pliska, Ellen; Mackie, Christine N; Waddell, Lisa F; Rankin, Kristin M

    2017-11-21

    Implementation strategies are imperative for the successful adoption and sustainability of complex evidence-based public health practices. Creating a learning collaborative is one strategy that was part of a recently published compilation of implementation strategy terms and definitions. In partnership with the Centers for Disease Control and Prevention and other partner agencies, the Association of State and Territorial Health Officials recently convened a multi-state Learning Community to support cross-state collaboration and provide technical assistance for improving state capacity to increase access to long-acting reversible contraception (LARC) in the immediate postpartum period, an evidence-based practice with the potential for reducing unintended pregnancy and improving maternal and child health outcomes. During 2015-2016, the Learning Community included multi-disciplinary, multi-agency teams of state health officials, payers, clinicians, and health department staff from 13 states. This qualitative study was conducted to better understand the successes, challenges, and strategies that the 13 US states in the Learning Community used for increasing access to immediate postpartum LARC. We conducted telephone interviews with each team in the Learning Community. Interviews were semi-structured and organized by the eight domains of the Learning Community. We coded transcribed interviews for facilitators, barriers, and implementation strategies, using a recent compilation of expert-defined implementation strategies as a foundation for coding the latter. Data analysis showed three ways that the activities of the Learning Community helped in policy implementation work: structure and accountability, validity, and preparing for potential challenges and opportunities. Further, the qualitative data demonstrated that the Learning Community integrated six other implementation strategies from the literature: organize clinician implementation team meetings, conduct

  4. Determination of Diffusion Coefficients and Activation Energy of Selected Organic Liquids using Reversed-Flow Gas Chromatographic Technique

    International Nuclear Information System (INIS)

    Khalisanni Khalid; Rashid Atta Khan; Sharifuddin Mohd Zain

    2012-01-01

    Evaporation of vaporize organic liquid has ecological consequences when the compounds are introduced into both freshwater and marine environments through industrial effluents, or introduced directly into the air from industrial unit processes such as bioreactors and cooling towers. In such cases, a rapid and simple method are needed to measure physicochemical properties of the organic liquids. The Reversed-Flow Gas Chromatography (RF-GC) sampling technique is an easy, fast and accurate procedure. It was used to measure the diffusion coefficients of vapors from liquid into a carrier gas and at the same time to determine the rate coefficients for the evaporation of the respective liquid. The mathematical expression describing the elution curves of the samples peaks was derived and used to calculate the respective parameters for the selected liquid pollutants selected such as methanol, ethanol, 1-propanol, 1-butanol, n-pentane, n-hexane, n-heptane and n-hexadecane, evaporating into the carrier gas of nitrogen. The values of diffusion coefficients found were compared with those calculated theoretically or reported in the literature. The values of evaporation rate were used to determine the activation energy of respective samples using Arrhenius equation. An interesting finding of this work is by using an alternative mathematical analysis based on equilibrium at the liquid-gas interphase, the comparison leads to profound agreement between theoretical values of diffusion coefficients and experimental evidence. (author)

  5. Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

    Science.gov (United States)

    Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

    2010-12-12

    Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.

  6. Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

    Science.gov (United States)

    Manouselis, Nikos; Sampson, Demetrios

    This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

  7. Expression profile of genes during resistance reversal in a temephos selected strain of the dengue vector, Aedes aegypti.

    Directory of Open Access Journals (Sweden)

    Clare Strode

    Full Text Available BACKGROUND: The mosquito Aedes aegypti is one of the most important disease vectors because it transmits two major arboviruses, dengue and yellow fever, which cause significant global morbidity and mortality. Chemical insecticides form the cornerstone of vector control. The organophosphate temephos a larvicide recommended by WHO for controlling Ae. aegypti, however, resistance to this compound has been reported in many countries, including Brazil. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this study was to identify genes implicated in metabolic resistance in an Ae. aegypti temephos resistant strain, named RecR, through microarray analysis. We utilized a custom 'Ae. aegypti detox chip' and validated microarray data through RT-PCR comparing susceptible and resistant individuals. In addition, we analyzed gene expression in 4(th instar larvae from a reversed susceptible strain (RecRev, exposed and unexposed to temephos. The results obtained revealed a set of 13 and 6 genes significantly over expressed in resistant adult mosquitoes and larvae, respectively. One of these genes, the cytochrome P450 CYP6N12, was up-regulated in both stages. RT-PCR confirmed the microarray results and, additionally, showed no difference in gene expression between temephos exposed and unexposed RecRev mosquitoes. This suggested that the differences in the transcript profiles among the strains are heritable due to a selection process and are not caused by immediate insecticide exposure. Reversal of temephos resistance was demonstrated and, importantly, there was a positive correlation between a decrease in the resistance ratio and an accompanying decrease in the expression levels of previously over expressed genes. Some of the genes identified here have also been implicated in metabolic resistance in other mosquito species and insecticide resistant populations of Ae. aegypti. CONCLUSIONS/SIGNIFICANCE: The identification of gene expression signatures associated to

  8. Dissociable contributions of the orbitofrontal and infralimbic cortex to pavlovian autoshaping and discrimination reversal learning: further evidence for the functional heterogeneity of the rodent frontal cortex.

    Science.gov (United States)

    Chudasama, Y; Robbins, Trevor W

    2003-09-24

    To examine possible heterogeneity of function within the ventral regions of the rodent frontal cortex, the present study compared the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) and the infralimbic cortex (ILC) on pavlovian autoshaping and discrimination reversal learning. During the pavlovian autoshaping task, in which rats learn to approach a stimulus predictive of reward [conditional stimulus (CS+)], only the OFC group failed to acquire discriminated approach but was unimpaired when preoperatively trained. In the visual discrimination learning and reversal task, rats were initially required to discriminate a stimulus positively associated with reward. There was no effect of either OFC or ILC lesions on discrimination learning. When the stimulus-reward contingencies were reversed, both groups of animals committed more errors, but only the OFC-lesioned animals were unable to suppress the previously rewarded stimulus-reward association, committing more "stimulus perseverative" errors. In contrast, the ILC group showed a pattern of errors that was more attributable to "learning" than perseveration. These findings suggest two types of dissociation between the effects of OFC and ILC lesions: (1) OFC lesions impaired the learning processes implicated in pavlovian autoshaping but not instrumental simultaneous discrimination learning, whereas ILC lesions were unimpaired at autoshaping and their reversal learning deficit did not reflect perseveration, and (2) OFC lesions induced perseverative responding in reversal learning but did not disinhibit responses to pavlovian CS-. In contrast, the ILC lesion had no effect on response inhibitory control in either of these settings. The findings are discussed in the context of dissociable executive functions in ventral sectors of the rat prefrontal cortex.

  9. Zidovudine (AZT monotherapy selects for the A360V mutation in the connection domain of HIV-1 reverse transcriptase.

    Directory of Open Access Journals (Sweden)

    Jessica H Brehm

    Full Text Available We previously demonstrated in vitro that zidovudine (AZT selects for A371V in the connection domain and Q509L in ribonuclease H (RNase H domain of HIV-1 reverse transcriptase (RT which, together with the thymidine analog mutations D67N, K70R and T215F, confer greater than 100-fold AZT resistance. The goal of the current study was to determine whether AZT monotherapy in HIV-1 infected patients also selects the A371V, Q509L or other mutations in the C-terminal domains of HIV-1 RT.Full-length RT sequences in plasma obtained pre- and post-therapy were compared in 23 participants who received AZT monotherapy from the AIDS Clinical Trials Group study 175. Five of the 23 participants reached a primary study endpoint. Mutations significantly associated with AZT monotherapy included K70R (p = 0.003 and T215Y (p = 0.013 in the polymerase domain of HIV-1 RT, and A360V (p = 0.041 in the connection domain of HIV-1 RT. HIV-1 drug susceptibility assays demonstrated that A360V, either alone or in combination with thymidine analog mutations, decreased AZT susceptibility in recombinant viruses containing participant-derived full-length RT sequences or site-directed mutant RT. Biochemical studies revealed that A360V enhances the AZT-monophosphate excision activity of purified RT by significantly decreasing the frequency of secondary RNase H cleavage events that reduce the RNA/DNA duplex length and promote template/primer dissociation.The A360V mutation in the connection domain of RT was selected in HIV-infected individuals that received AZT monotherapy and contributed to AZT resistance.

  10. The attention habit: how reward learning shapes attentional selection.

    Science.gov (United States)

    Anderson, Brian A

    2016-04-01

    There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications. © 2015 New York Academy of Sciences.

  11. Learners' experiences of learning support in selected Western Cape ...

    African Journals Online (AJOL)

    The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance. Keywords: academic needs; academic performance; barriers to learning; ...

  12. Pioglitazone improves reversal learning and exerts mixed cerebrovascular effects in a mouse model of Alzheimer's disease with combined amyloid-β and cerebrovascular pathology.

    Directory of Open Access Journals (Sweden)

    Panayiota Papadopoulos

    Full Text Available Animal models of Alzheimer's disease (AD are invaluable in dissecting the pathogenic mechanisms and assessing the efficacy of potential new therapies. Here, we used the peroxisome proliferator-activated receptor gamma agonist pioglitazone in an attempt to rescue the pathogenic phenotype in adult (12 months and aged (>18 months bitransgenic A/T mice that overexpress a mutated human amyloid precursor protein (APPSwe,Ind and a constitutively active form of transforming growth factor-β1 (TGF-β1. A/T mice recapitulate the AD-related cognitive deficits, amyloid beta (Aβ and cerebrovascular pathologies, as well as the altered metabolic and vascular coupling responses to increased neuronal activity. Pioglitazone normalized neurometabolic and neurovascular coupling responses to sensory stimulation, and reduced cortical astroglial and hippocampal microglial activation in both age groups. Spatial learning and memory deficits in the Morris water maze were not rescued by pioglitazone, but reversal learning was improved in the adult cohort notwithstanding a progressing Aβ pathology. While pioglitazone preserved the constitutive nitric oxide synthesis in the vessel wall, it unexpectedly failed to restore cerebrovascular reactivity in A/T mice and even exacerbated the dilatory deficits. These data demonstrate pioglitazone's efficacy on selective AD hallmarks in a complex AD mouse model of comorbid amyloidosis and cerebrovascular pathology. They further suggest a potential benefit of pioglitazone in managing neuroinflammation, cerebral perfusion and glucose metabolism in AD patients devoid of cerebrovascular pathology.

  13. Adult neurogenesis reduction by a cytostatic treatment improves spatial reversal learning in rats

    Czech Academy of Sciences Publication Activity Database

    Brožka, Hana; Pištíková, Adéla; Radostová, Dominika; Valeš, Karel; Svoboda, Jan; Grzyb, A. N.; Stuchlík, Aleš

    2017-01-01

    Roč. 141, May (2017), s. 93-100 ISSN 1074-7427 R&D Projects: GA ČR(CZ) GA14-03627S; GA MŠk(CZ) LH14053 Grant - others:Rada Programu interní podpory projektů mezinárodní spolupráce AV ČR(CZ) M200111204 Institutional support: RVO:67985823 Keywords : active avoidance * hippocampus * adult neurogenesis * discrimination * generalization * reversal Subject RIV: FH - Neurology OBOR OECD: Neurosciences (including psychophysiology Impact factor: 3.543, year: 2016

  14. An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

    Science.gov (United States)

    Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

    2016-01-01

    Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

  15. Unweaving misconceptions: Guided learning, simulations, and misconceptions in learning principles of natural selection

    Science.gov (United States)

    Weeks, Brian E.

    College students often come to the study of evolutionary biology with many misconceptions of how the processes of natural selection and speciation occur. How to relinquish these misconceptions with learners is a question that many educators face in introductory biology courses. Constructivism as a theoretical framework has become an accepted and promoted model within the epistemology of science instruction. However, constructivism is not without its skeptics who see some problems of its application in lacking necessary guidance for novice learners. This study within a quantitative, quasi-experimental format tested whether guided online instruction in a video format of common misconceptions in evolutionary biology produced higher performance on a survey of knowledge of natural selection versus more constructivist style learning in the form of student exploration of computer simulations of the evolutionary process. Performances on surveys were also explored for a combination of constructivist and guided techniques to determine if a consolidation of approaches produced higher test scores. Out of the 94 participants 95% displayed at least one misconception of natural selection in the pre-test while the study treatments produced no statistically significant improvements in post-test scores except within the video (guided learning treatment). These overall results demonstrated the stubbornness of misconceptions involving natural selection for adult learners and the difficulty of helping them overcome them. It also bolsters the idea that some misconceptions of natural selection and evolution may be hardwired in a neurological sense and that new, more long-term teaching techniques may be warranted. Such long-term strategies may not be best implemented with constructivist techniques alone, and it is likely that some level of guidance may be necessary for novice adult learners. A more substantial, nuanced approach for undergraduates is needed that consolidates successful

  16. Effects of befloxatone, a reversible selective monoamine oxidase-A inhibitor, on psychomotor function and memory in healthy subjects.

    Science.gov (United States)

    Warot, D; Berlin, I; Patat, A; Durrieu, G; Zieleniuk, I; Puech, A J

    1996-10-01

    Befloxatone is a new reversible and selective monoamine oxidase (MAO-A) inhibitor that has been shown to have antidepressant activity in various animal models. To assess the effects of single oral doses of befloxatone (5, 10, and 20 mg) on psychomotor performance and memory, a randomized, double-blind, five-way, crossover study with both placebo and amitriptyline (50 mg) was carried out in 15 healthy male volunteers. Psychomotor and cognitive functions were evaluated using both objective measures, including Critical Flicker Frequency (CFF), Choice Reaction Time (CRT), Digit Symbol Substitution Test (DSST), and a picture memory test and subjective measures, including Visual Analog Scales (VAS) and Addiction Research Center Inventory (ARCI), before and 2, 4, and 8 hours after administration. Pupil diameter was recorded by videopupillography. Single doses of befloxatone from 5 to 20 mg did not result in any detrimental effects on skilled performance and memory. In contrast, amitriptyline significantly impaired arousal (CFF), speed of reaction (CRT), information processing (DSST) and long-term memory (delayed free recall of pictures) and produced subjective sedation from 2 to 8 hours after administration. At the doses studied amitriptyline induced miosis but befloxatone did not modify pupil diameter. There was no evidence in this study to suggest that befloxatone, at the doses studied, has any sedative or amnesic effects in healthy subjects.

  17. Depression-biased reverse plasticity rule is required for stable learning at top-down connections.

    Directory of Open Access Journals (Sweden)

    Kendra S Burbank

    Full Text Available Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.

  18. Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections

    Science.gov (United States)

    Burbank, Kendra S.; Kreiman, Gabriel

    2012-01-01

    Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630

  19. Fusing a Reversed and Informal Learning Scheme and Space: Student Perceptions of Active Learning in Physical Chemistry

    Science.gov (United States)

    Donnelly, Julie; Hernández, Florencio E.

    2018-01-01

    Physical chemistry students often have negative perceptions and low expectations for success in physical chemistry, attitudes that likely affect their performance in the course. Despite the results of several studies indicating increased positive perception of physical chemistry when active learning strategies are used, a recent survey of faculty…

  20. Feedback-related negativity codes outcome valence, but not outcome expectancy, during reversal learning

    NARCIS (Netherlands)

    Borries, A.K.L. von; Verkes, R.J.; Bulten, B.H.; Cools, R.; Bruijn, E.R.A. de

    2013-01-01

    Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures-that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model

  1. Feedback-related negativity codes outcome valence, but not outcome expectancy, during reversal learning

    NARCIS (Netherlands)

    Borries, A.K.L. von; Verkes, R.J.; Bulten, B.H.; Cools, R.

    2013-01-01

    Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures--that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model

  2. 2-Methyl-6-(phenylethynyl pyridine (MPEP reverses maze learning and PSD-95 deficits in Fmr1 knock-out mice.

    Directory of Open Access Journals (Sweden)

    Réno Michelle Gandhi

    2014-03-01

    Full Text Available Fragile X syndrome (FXS is caused by the lack of expression of the fragile X mental retardation protein (FMRP, which results in intellectual disability and other debilitating symptoms including impairment of visual-spatial functioning. FXS is the only single-gene disorder that is highly co-morbid with autism spectrum disorder and can therefore provide insight into its pathophysiology. Lack of FMRP results in altered group I metabotropic glutamate receptor (mGluR signalling, which is a target for putative treatments. The Hebb-Williams (H-W mazes are a set of increasingly complex spatial navigation problems that depend on intact hippocampal and thus mGluR-5 functioning. In the present investigation, we examined whether an antagonist of mGluR-5 would reverse previously described behavioural deficits in Fmr1 KO mice. Mice were trained on a subset of the H-W mazes and then treated with either 20 mg/kg of an mGluR-5 antagonist, 2-Methyl-6-(phenylethynyl pyridine (MPEP; n = 11 or an equivalent dose of saline (n = 11 prior to running test mazes. Latency and errors were dependent variables recorded during the test phase. Immediately after completing each test, marble-burying behavior was assessed which confirmed that the drug treatment was pharmacologically active during maze learning. Although latency was not statistically different between the groups, MPEP treated Fmr1 KO mice made significantly fewer errors on mazes deemed more difficult suggesting a reversal of the behavioural deficit. MPEP treated mice were also less perseverative and impulsive when navigating mazes. Furthermore, MPEP treatment reversed PSD-95 protein deficits in Fmr1 KO treated mice, whereas levels of a control protein (β-tubulin remained unchanged. These data further validate MPEP as a potentially beneficial treatment for FXS. Our findings also suggest that adapted H-W mazes may be a useful tool to document alterations in behavioural functioning following pharmacological

  3. Quantitative measures of sexual selection reveal no evidence for sex-role reversal in a sea spider with prolonged paternal care

    OpenAIRE

    Barreto, Felipe S.; Avise, John C.

    2010-01-01

    Taxa in which males alone invest in postzygotic care of offspring are often considered good models for investigating the proffered relationships between sexual selection and mating systems. In the pycnogonid sea spider Pycnogonum stearnsi, males carry large egg masses on their bodies for several weeks, so this species is a plausible candidate for sex-role reversal (greater intensity of sexual selection on females than on males). Here, we couple a microsatellite-based assessment of the mating ...

  4. Alteration of a motor learning rule under mirror-reversal transformation does not depend on the amplitude of visual error.

    Science.gov (United States)

    Kasuga, Shoko; Kurata, Makiko; Liu, Meigen; Ushiba, Junichi

    2015-05-01

    Human's sophisticated motor learning system paradoxically interferes with motor performance when visual information is mirror-reversed (MR), because normal movement error correction further aggravates the error. This error-increasing mechanism makes performing even a simple reaching task difficult, but is overcome by alterations in the error correction rule during the trials. To isolate factors that trigger learners to change the error correction rule, we manipulated the gain of visual angular errors when participants made arm-reaching movements with mirror-reversed visual feedback, and compared the rule alteration timing between groups with normal or reduced gain. Trial-by-trial changes in the visual angular error was tracked to explain the timing of the change in the error correction rule. Under both gain conditions, visual angular errors increased under the MR transformation, and suddenly decreased after 3-5 trials with increase. The increase became degressive at different amplitude between the two groups, nearly proportional to the visual gain. The findings suggest that the alteration of the error-correction rule is not dependent on the amplitude of visual angular errors, and possibly determined by the number of trials over which the errors increased or statistical property of the environment. The current results encourage future intensive studies focusing on the exact rule-change mechanism. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  5. Feature selection for domain knowledge representation through multitask learning

    CSIR Research Space (South Africa)

    Rosman, Benjamin S

    2014-10-01

    Full Text Available represent stimuli of interest, and rich feature sets which increase the dimensionality of the space and thus the difficulty of the learning problem. We focus on a multitask reinforcement learning setting, where the agent is learning domain knowledge...

  6. Rapid tryptophan depletion improves decision-making cognition in healthy humans without affecting reversal learning or set shifting.

    Science.gov (United States)

    Talbot, Peter S; Watson, David R; Barrett, Suzanne L; Cooper, Stephen J

    2006-07-01

    Rapid tryptophan (Trp) depletion (RTD) has been reported to cause deterioration in the quality of decision making and impaired reversal learning, while leaving attentional set shifting relatively unimpaired. These findings have been attributed to a more powerful neuromodulatory effect of reduced 5-HT on ventral prefrontal cortex (PFC) than on dorsolateral PFC. In view of the limited number of reports, the aim of this study was to independently replicate these findings using the same test paradigms. Healthy human subjects without a personal or family history of affective disorder were assessed using a computerized decision making/gambling task and the CANTAB ID/ED attentional set-shifting task under Trp-depleted (n=17; nine males and eight females) or control (n=15; seven males and eight females) conditions, in a double-blind, randomized, parallel-group design. There was no significant effect of RTD on set shifting, reversal learning, risk taking, impulsivity, or subjective mood. However, RTD significantly altered decision making such that depleted subjects chose the more likely of two possible outcomes significantly more often than controls. This is in direct contrast to the previous report that subjects chose the more likely outcome significantly less often following RTD. In the terminology of that report, our result may be interpreted as improvement in the quality of decision making following RTD. This contrast between studies highlights the variability in the cognitive effects of RTD between apparently similar groups of healthy subjects, and suggests the need for future RTD studies to control for a range of personality, family history, and genetic factors that may be associated with 5-HT function.

  7. Learners' experiences of learning support in selected Western Cape schools

    Directory of Open Access Journals (Sweden)

    Olaniyi Bojuwoye

    2014-01-01

    Full Text Available The study explored Western Cape primary and secondary school learners' experiences regarding the provision and utilization of support services for improving learning. A qualitative interpretive approach was adopted and data gathered through focus group interviews involving 90 learners. Results revealed that learners received and utilized various forms of learning support from their schools, teachers, and peers. The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance.

  8. Feature Selection and Kernel Learning for Local Learning-Based Clustering.

    Science.gov (United States)

    Zeng, Hong; Cheung, Yiu-ming

    2011-08-01

    The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

  9. Novel Automatic Filter-Class Feature Selection for Machine Learning Regression

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Hallam, John; Jørgensen, Bo Nørregaard

    2017-01-01

    With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require...... model in the feature selection process. PCA is often used in machine learning litterature and can be considered the default feature selection method. RDESF outperformed PCA in both experiments in both prediction error and computational speed. RDESF is a new step into filter-based automatic feature...

  10. Is it better to select or to receive? Learning via active and passive hypothesis testing.

    Science.gov (United States)

    Markant, Douglas B; Gureckis, Todd M

    2014-02-01

    People can test hypotheses through either selection or reception. In a selection task, the learner actively chooses observations to test his or her beliefs, whereas in reception tasks data are passively encountered. People routinely use both forms of testing in everyday life, but the critical psychological differences between selection and reception learning remain poorly understood. One hypothesis is that selection learning improves learning performance by enhancing generic cognitive processes related to motivation, attention, and engagement. Alternatively, we suggest that differences between these 2 learning modes derives from a hypothesis-dependent sampling bias that is introduced when a person collects data to test his or her own individual hypothesis. Drawing on influential models of sequential hypothesis-testing behavior, we show that such a bias (a) can lead to the collection of data that facilitates learning compared with reception learning and (b) can be more effective than observing the selections of another person. We then report a novel experiment based on a popular category learning paradigm that compares reception and selection learning. We additionally compare selection learners to a set of "yoked" participants who viewed the exact same sequence of observations under reception conditions. The results revealed systematic differences in performance that depended on the learner's role in collecting information and the abstract structure of the problem.

  11. STRATEGY FOR EVALUATION AND SELECTION OF SYSTEMS FOR ELECTRONIC LEARNING

    OpenAIRE

    Dubravka Mandušić; Lucija Blašković

    2012-01-01

    Today`s technology supported and accelerated learning time requires constant and continuous acquisition of new knowledge. On the other hand, it does not leave enough time for additional education. Increasing number of E-learning systems, withdraws a need for precise evaluation of functionality that those systems provide; so they could be reciprocally compared. While implementing new systems for electronic learning, it is very important to pre-evaluate existing systems in order to ...

  12. Preservation of Essential Odor-Guided Behaviors and Odor-Based Reversal Learning after Targeting Adult Brain Serotonin Synthesis.

    Science.gov (United States)

    Carlson, Kaitlin S; Whitney, Meredith S; Gadziola, Marie A; Deneris, Evan S; Wesson, Daniel W

    2016-01-01

    The neurotransmitter serotonin (5-HT) is considered a powerful modulator of sensory system organization and function in a wide range of animals. The olfactory system is innervated by midbrain 5-HT neurons into both its primary and secondary odor-processing stages. Facilitated by this circuitry, 5-HT and its receptors modulate olfactory system function, including odor information input to the olfactory bulb. It is unknown, however, whether the olfactory system requires 5-HT for even its most basic behavioral functions. To address this question, we established a conditional genetic approach to specifically target adult brain tryptophan hydroxylase 2 ( Tph2 ), encoding the rate-limiting enzyme in brain 5-HT synthesis, and nearly eliminate 5-HT from the mouse forebrain. Using this novel model, we investigated the behavior of 5-HT-depleted mice during performance in an olfactory go/no-go task. Surprisingly, the near elimination of 5-HT from the forebrain, including the olfactory bulbs, had no detectable effect on the ability of mice to perform the odor-based task. Tph2 -targeted mice not only were able to learn the task, but also had levels of odor acuity similar to those of control mice when performing coarse odor discrimination. Both groups of mice spent similar amounts of time sampling odors during decision-making. Furthermore, odor reversal learning was identical between 5-HT-depleted and control mice. These results suggest that 5-HT neurotransmission is not necessary for the most essential aspects of olfaction, including odor learning, discrimination, and certain forms of cognitive flexibility.

  13. Edaravone injection reverses learning and memory deficits in a rat model of vascular dementia.

    Science.gov (United States)

    Li, Xu; Lu, Fen; Li, Wei; Qin, Lingzhi; Yao, Yong; Ge, Xuerong; Yu, Qingkai; Liang, Xinliang; Zhao, Dongmei; Li, Xiaohong; Zhang, Jiewen

    2017-01-01

    Edaravone is a novel free radical scavenger that exerts neuroprotective effects by inhibiting endothelial injury and by ameliorating neuronal damage in brain ischemia. Recently, it was reported that edaravone could alleviate the pathology and cognitive deficits of Alzheimer's disease patients. However, its relevance to vascular dementia (VaD) is not clear. In this study, we partially occluded the bilateral carotid arteries of rats surgically to induce chronic cerebral hypoperfusion (CCH), a well-known rat model of VaD. Water maze and step-down inhibitory test were used to evaluate the memory deficit. The activities of superoxide dismutase (SOD) and lactate dehydrogenase (LDH), the content of malondialdehyde (MDA) and total reactive oxygen species were measured to evaluate the oxidative stress level. Western blot analysis was used to evaluate the synaptic protein expression. It was found that treatment with edaravone for a 5-week period was able to reverse both spatial and fear-memory deficits in rats with CCH. Edaravone significantly reduced the level of oxidative stress in the brains of rats with CCH by increasing SOD activity and decreasing the content of MDA, LDH, and total reactive oxygen species. Furthermore, edaravone treatment also restored the levels of multiple synaptic proteins in the hippocampi of rats with CCH. Our data provide direct evidence supporting the neuroprotective effects of edaravone in VaD. We propose that the alleviation of oxidative stress and restoration of synaptic proteins play important roles in neuroprotection. © The Author 2016. Published by Oxford University Press on behalf of the Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. A Novel Leu92 Mutant of HIV-1 Reverse Transcriptase with a Selective Deficiency in Strand Transfer Causes a Loss of Viral Replication.

    Science.gov (United States)

    Herzig, Eytan; Voronin, Nickolay; Kucherenko, Nataly; Hizi, Amnon

    2015-08-01

    The process of reverse transcription (RTN) in retroviruses is essential to the viral life cycle. This key process is catalyzed exclusively by the viral reverse transcriptase (RT) that copies the viral RNA into DNA by its DNA polymerase activity, while concomitantly removing the original RNA template by its RNase H activity. During RTN, the combination between DNA synthesis and RNA hydrolysis leads to strand transfers (or template switches) that are critical for the completion of RTN. The balance between these RT-driven activities was considered to be the sole reason for strand transfers. Nevertheless, we show here that a specific mutation in HIV-1 RT (L92P) that does not affect the DNA polymerase and RNase H activities abolishes strand transfer. There is also a good correlation between this complete loss of the RT's strand transfer to the loss of the DNA clamp activity of the RT, discovered recently by us. This finding indicates a mechanistic linkage between these two functions and that they are both direct and unique functions of the RT (apart from DNA synthesis and RNA degradation). Furthermore, when the RT's L92P mutant was introduced into an infectious HIV-1 clone, it lost viral replication, due to inefficient intracellular strand transfers during RTN, thus supporting the in vitro data. As far as we know, this is the first report on RT mutants that specifically and directly impair RT-associated strand transfers. Therefore, targeting residue Leu92 may be helpful in selectively blocking this RT activity and consequently HIV-1 infectivity and pathogenesis. Reverse transcription in retroviruses is essential for the viral life cycle. This multistep process is catalyzed by viral reverse transcriptase, which copies the viral RNA into DNA by its DNA polymerase activity (while concomitantly removing the RNA template by its RNase H activity). The combination and balance between synthesis and hydrolysis lead to strand transfers that are critical for reverse transcription

  15. CREB Selectively Controls Learning-Induced Structural Remodeling of Neurons

    Science.gov (United States)

    Middei, Silvia; Spalloni, Alida; Longone, Patrizia; Pittenger, Christopher; O'Mara, Shane M.; Marie, Helene; Ammassari-Teule, Martine

    2012-01-01

    The modulation of synaptic strength associated with learning is post-synaptically regulated by changes in density and shape of dendritic spines. The transcription factor CREB (cAMP response element binding protein) is required for memory formation and in vitro dendritic spine rearrangements, but its role in learning-induced remodeling of neurons…

  16. The cost of selective attention in category learning: developmental differences between adults and infants.

    Science.gov (United States)

    Best, Catherine A; Yim, Hyungwook; Sloutsky, Vladimir M

    2013-10-01

    Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6-8months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. The cost of selective attention in category learning: Developmental differences between adults and infants

    Science.gov (United States)

    Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.

    2013-01-01

    Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914

  18. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    Science.gov (United States)

    Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

    2017-11-01

    This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

  19. Dissociable effects of 5-HT2C receptor antagonism and genetic inactivation on perseverance and learned non-reward in an egocentric spatial reversal task.

    Directory of Open Access Journals (Sweden)

    Simon R O Nilsson

    Full Text Available Cognitive flexibility can be assessed in reversal learning tests, which are sensitive to modulation of 5-HT2C receptor (5-HT2CR function. Successful performance in these tests depends on at least two dissociable cognitive mechanisms which may separately dissipate associations of previous positive and negative valence. The first is opposed by perseverance and the second by learned non-reward. The current experiments explored the effect of reducing function of the 5-HT2CR on the cognitive mechanisms underlying egocentric reversal learning in the mouse. Experiment 1 used the 5-HT2CR antagonist SB242084 (0.5 mg/kg in a between-groups serial design and Experiment 2 used 5-HT2CR KO mice in a repeated measures design. Animals initially learned to discriminate between two egocentric turning directions, only one of which was food rewarded (denoted CS+, CS-, in a T- or Y-maze configuration. This was followed by three conditions; (1 Full reversal, where contingencies reversed; (2 Perseverance, where the previous CS+ became CS- and the previous CS- was replaced by a novel CS+; (3 Learned non-reward, where the previous CS- became CS+ and the previous CS+ was replaced by a novel CS-. SB242084 reduced perseverance, observed as a decrease in trials and incorrect responses to criterion, but increased learned non-reward, observed as an increase in trials to criterion. In contrast, 5-HT2CR KO mice showed increased perseverance. 5-HT2CR KO mice also showed retarded egocentric discrimination learning. Neither manipulation of 5-HT2CR function affected performance in the full reversal test. These results are unlikely to be accounted for by increased novelty attraction, as SB242084 failed to affect performance in an unrewarded novelty task. In conclusion, acute 5-HT2CR antagonism and constitutive loss of the 5-HT2CR have opposing effects on perseverance in egocentric reversal learning in mice. It is likely that this difference reflects the broader impact of 5HT2CR loss

  20. Helping reasoners succeed in the Wason selection task: when executive learning discourages heuristic response but does not necessarily encourage logic.

    Directory of Open Access Journals (Sweden)

    Sandrine Rossi

    Full Text Available Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL on adults who have transferred knowledge acquired on the Wason selection task (WST to another isomorphic task, the rule falsification task (RFT. The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.

  1. Helping reasoners succeed in the Wason selection task: when executive learning discourages heuristic response but does not necessarily encourage logic.

    Science.gov (United States)

    Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier

    2015-01-01

    Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.

  2. Reversible Thermoset Adhesives

    Science.gov (United States)

    Mac Murray, Benjamin C. (Inventor); Tong, Tat H. (Inventor); Hreha, Richard D. (Inventor)

    2016-01-01

    Embodiments of a reversible thermoset adhesive formed by incorporating thermally-reversible cross-linking units and a method for making the reversible thermoset adhesive are provided. One approach to formulating reversible thermoset adhesives includes incorporating dienes, such as furans, and dienophiles, such as maleimides, into a polymer network as reversible covalent cross-links using Diels Alder cross-link formation between the diene and dienophile. The chemical components may be selected based on their compatibility with adhesive chemistry as well as their ability to undergo controlled, reversible cross-linking chemistry.

  3. Reversal of Trimethyltin-Induced Learning and Memory Deficits by 3,5-Dicaffeoylquinic Acid

    Directory of Open Access Journals (Sweden)

    Jin Yong Kang

    2016-01-01

    Full Text Available The antiamnesic effect of 3,5-dicaffeoylquinic acid (3,5-diCQA as the main phenolic compound in Artemisia argyi H. extract on cognitive dysfunction induced by trimethyltin (TMT (7.1 μg/kg of body weight; intraperitoneal injection was investigated in order to assess its ameliorating function in mice. In several behavioral tests, namely, the Y-maze, passive avoidance, and Morris water maze (MWM test, 3,5-diCQA significantly ameliorated learning and memory deficits. After the behavioral tests, brain tissues from the mice were analyzed to characterize the basis of the neuroprotective effect. Acetylcholine (ACh levels increased, whereas the activity of acetylcholinesterase (AChE decreased upon administration of 3,5-diCQA. In addition, 3,5-diCQA effectively protected against an increase in malondialdehyde (MDA content, an increase in the oxidized glutathione (GSH ratio, and a decline of total superoxide dismutase (SOD level. 3,5-diCQA may prevent neuronal apoptosis through the protection of mitochondrial activities and the repression of apoptotic signaling molecules such as p-Akt, BAX, and p-tau (Ser 404.

  4. PENINGKATKAN HASIL BELAJAR PKN KELAS V MELALUI MODEL ACTIVE LEARNING (TIPE ROLE REVERSAL QUESTION SDN 4 DOPLANG KECAMATAN JATI KABUPATEN BLORA

    Directory of Open Access Journals (Sweden)

    Ambar Susilo Murti

    2016-12-01

    Full Text Available Constitution No. 20 of 2003, concerning Citizenship Education (PKN is a compulsory subject for primary education, secondary, and compulsory subjects for higher education. The purpose of this study is to improve learning outcomes Civics using Active Learning Model Type Question Role Reversal in Class V SDN 4 Doplang Jati district of  Blora. This research was a class action (classroom action research. The stages as follows: (1 planning, (2 implementation, (3 observation and (4 reflection. The result of research indicating that students who received grades ≥70 the first cycle increased by 25%  from the initial 44% to 69%. Then students who scored ≥70 on the second cycle increased 28% to 97%. The average value of the first cycle increased by 8.75% from 66.53 into 75.28 early in the first cycle and then the second cycle of the average value increased again by 10.97% to 86.25. Researchers suggest teachers should encourage students to be more daring in expressing opinions, questions and ideas that are not held only in Civics alone but on other subjects. In addition, teachers are expected to use active learning model of the type of role reversal question in improving student learning outcomes in other subjects. As for the school is expected to provide training to teachers on implementing learning activities are innovative and creative. Keywords: active learning, civic education, learning outcomes.

  5. You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention.

    Science.gov (United States)

    Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna

    2015-11-01

    Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4). © 2015 Society for Psychophysiological Research.

  6. Robust outer-selective thin-film composite polyethersulfone hollow fiber membranes with low reverse salt flux for renewable salinity-gradient energy generation

    KAUST Repository

    Cheng, Zhen Lei; Li, Xue; Liu, Ying Da; Chung, Neal Tai-Shung

    2016-01-01

    This study reports outer-selective thin-film composite (TFC) hollow fiber membranes with extremely low reverse salt fluxes and robustness for harvesting salinity-gradient energy from pressure retarded osmosis (PRO) processes. Almost defect-free polyamide layers with impressive low salt permeabilities were synthesized on top of robust polyethersulfone porous supports. The newly developed TFC-II membrane shows a maximum power density of 7.81 W m−2 using 1 M NaCl and DI water as feeds at 20 bar. Reproducible data obtained in the 2nd and 3rd runs confirm its stability under high hydraulic pressure differences. Comparing to other PRO membranes reported in the literature, the newly developed membrane exhibits not only the smallest slope between water flux decline and ΔPΔP increase but also the lowest ratio of reverse salt flux to water flux. Thus, the effective osmotic driving force could be well maintained even under high pressure operations. For the first time, the effect of feed pressure buildup induced by feed flowrate was evaluated towards PRO performance. A slight increment in feed pressure buildup was found to be beneficial to water flux and power density up to 10.06 W m−2 without comprising the reverse salt flux. We believe this study may open up new perspectives on outer-selective PRO hollow fiber membranes and provide useful insights to understand and design next-generation outer-selective TFC hollow fiber membranes for osmotic power generation.

  7. Robust outer-selective thin-film composite polyethersulfone hollow fiber membranes with low reverse salt flux for renewable salinity-gradient energy generation

    KAUST Repository

    Cheng, Zhen Lei

    2016-01-08

    This study reports outer-selective thin-film composite (TFC) hollow fiber membranes with extremely low reverse salt fluxes and robustness for harvesting salinity-gradient energy from pressure retarded osmosis (PRO) processes. Almost defect-free polyamide layers with impressive low salt permeabilities were synthesized on top of robust polyethersulfone porous supports. The newly developed TFC-II membrane shows a maximum power density of 7.81 W m−2 using 1 M NaCl and DI water as feeds at 20 bar. Reproducible data obtained in the 2nd and 3rd runs confirm its stability under high hydraulic pressure differences. Comparing to other PRO membranes reported in the literature, the newly developed membrane exhibits not only the smallest slope between water flux decline and ΔPΔP increase but also the lowest ratio of reverse salt flux to water flux. Thus, the effective osmotic driving force could be well maintained even under high pressure operations. For the first time, the effect of feed pressure buildup induced by feed flowrate was evaluated towards PRO performance. A slight increment in feed pressure buildup was found to be beneficial to water flux and power density up to 10.06 W m−2 without comprising the reverse salt flux. We believe this study may open up new perspectives on outer-selective PRO hollow fiber membranes and provide useful insights to understand and design next-generation outer-selective TFC hollow fiber membranes for osmotic power generation.

  8. Class 1-Selective Histone Deacetylase (HDAC) Inhibitors Enhance HIV Latency Reversal while Preserving the Activity of HDAC Isoforms Necessary for Maximal HIV Gene Expression.

    Science.gov (United States)

    Zaikos, Thomas D; Painter, Mark M; Sebastian Kettinger, Nadia T; Terry, Valeri H; Collins, Kathleen L

    2018-03-15

    Combinations of drugs that affect distinct mechanisms of HIV latency aim to induce robust latency reversal leading to cytopathicity and elimination of the persistent HIV reservoir. Thus far, attempts have focused on combinations of protein kinase C (PKC) agonists and pan-histone deacetylase inhibitors (HDIs) despite the knowledge that HIV gene expression is regulated by class 1 histone deacetylases. We hypothesized that class 1-selective HDIs would promote more robust HIV latency reversal in combination with a PKC agonist than pan-HDIs because they preserve the activity of proviral factors regulated by non-class 1 histone deacetylases. Here, we show that class 1-selective agents used alone or with the PKC agonist bryostatin-1 induced more HIV protein expression per infected cell. In addition, the combination of entinostat and bryostatin-1 induced viral outgrowth, whereas bryostatin-1 combinations with pan-HDIs did not. When class 1-selective HDIs were used in combination with pan-HDIs, the amount of viral protein expression and virus outgrowth resembled that of pan-HDIs alone, suggesting that pan-HDIs inhibit robust gene expression induced by class 1-selective HDIs. Consistent with this, pan-HDI-containing combinations reduced the activity of NF-κB and Hsp90, two cellular factors necessary for potent HIV protein expression, but did not significantly reduce overall cell viability. An assessment of viral clearance from in vitro cultures indicated that maximal protein expression induced by class 1-selective HDI treatment was crucial for reservoir clearance. These findings elucidate the limitations of current approaches and provide a path toward more effective strategies to eliminate the HIV reservoir. IMPORTANCE Despite effective antiretroviral therapy, HIV evades eradication in a latent form that is not affected by currently available drug regimens. Pharmacologic latency reversal that leads to death of cellular reservoirs has been proposed as a strategy for

  9. Endogenously and exogenously driven selective sustained attention: Contributions to learning in kindergarten children.

    Science.gov (United States)

    Erickson, Lucy C; Thiessen, Erik D; Godwin, Karrie E; Dickerson, John P; Fisher, Anna V

    2015-10-01

    Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of endogenous and exogenous factors to selective sustained attention within the same task. Behavioral accuracy and eye-tracking data on the Track-It task were correlated with performance on an explicit learning task. Behavioral accuracy and fixations to distractors during the Track-It task did not predict learning when exogenous factors supported selective sustained attention. In contrast, when endogenous factors supported selective sustained attention, fixations to distractors were negatively correlated with learning. Similarly, when endogenous factors supported selective sustained attention, higher behavioral accuracy was correlated with greater learning. These findings suggest that endogenously and exogenously driven selective sustained attention, as measured through different conditions of the Track-It task, may support different kinds of learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Selection of appropriates E-learning personalization strategies from ontological perspectives

    Directory of Open Access Journals (Sweden)

    Fathi Essalmi

    2010-10-01

    Full Text Available When there are several personalization strategies of E-learning, authors of courses need to be supported for deciding which strategy will be applied for personalizing each course. In fact, the time, the efforts and the learning objects needed for preparing personalized learning scenarios depend on the personalization strategy to be applied. This paper presents an approach for selecting personalization strategies according to the feasibility of generating personalized learning scenarios with minimal intervention of the author. Several metrics are proposed for putting in order and selecting useful personalization strategies. The calculus of these metrics is automated based on the analyses of the LOM (Learning Object Metadata standard according to the semantic relations between data elements and learners’ characteristics represented in the Ontology for Selection of Personalization Strategies (OSPS.

  11. Selective role for DNMT3a in learning and memory.

    Science.gov (United States)

    Morris, Michael J; Adachi, Megumi; Na, Elisa S; Monteggia, Lisa M

    2014-11-01

    Methylation of cytosine nucleotides is governed by DNA methyltransferases (DNMTs) that establish de novo DNA methylation patterns in early embryonic development (e.g., DNMT3a and DNMT3b) or maintain those patterns on hemimethylated DNA in dividing cells (e.g., DNMT1). DNMTs continue to be expressed at high levels in mature neurons, however their impact on neuronal function and behavior are unclear. To address this issue we examined DNMT1 and DNMT3a expression following associative learning. We also generated forebrain specific conditional Dnmt1 or Dnmt3a knockout mice and characterized them in learning and memory paradigms as well as for alterations in long-term potentiation (LTP) and synaptic plasticity. Here, we report that experience in an associative learning task impacts expression of Dnmt3a, but not Dnmt1, in brain areas that mediate learning of this task. We also found that Dnmt3a knockout mice, and not Dnmt1 knockouts have synaptic alterations as well as learning deficits on several associative and episodic memory tasks. These findings indicate that the de novo DNA methylating enzyme DNMT3a in postmitotic neurons is necessary for normal memory formation and its function cannot be substituted by the maintenance DNA methylating enzyme DNMT1. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. The Role of Executive Control of Attention and Selective Encoding for Preschoolers' Learning

    Science.gov (United States)

    Roderer, Thomas; Krebs, Saskia; Schmid, Corinne; Roebers, Claudia M.

    2012-01-01

    Selectivity in encoding, aspects of attentional control and their contribution to learning performance were explored in a sample of preschoolers. While the children are performing a learning task, their encoding of relevant and attention towards irrelevant information was recorded through an eye-tracking device. Recognition of target items was…

  13. When Average Is Not Good Enough: Students with Learning Disabilities at Selective, Private Colleges

    Science.gov (United States)

    Weis, Robert; Erickson, Celeste P.; Till, Christina H.

    2017-01-01

    Adolescents with learning disabilities disproportionately come from lower socioeconomic status backgrounds, show normative deficits in academic skills, and attend 2-year, public colleges instead of 4-year institutions. However, students with learning disabilities are well represented at the United States' most expensive and selective postsecondary…

  14. Lessons learned? Selected public acceptance case studies since Three Mile Island

    Energy Technology Data Exchange (ETDEWEB)

    Blee, D. [NAC International, Atlanta Corporate Headquarters, Atlanta, GA (United States)

    2001-02-01

    This paper will present an overview of the present situation, some recent polling survey information, and then look at lessons learned in terms of selected case studies and some global issues over the 22 years since the Three Mile Island (TMI) accident. That is quite an ambitious topic but there are some important lessons we can learn from the post-TMI era. (author)

  15. Learning strategy refinement reverses early sensory cortical map expansion but not behavior: Support for a theory of directed cortical substrates of learning and memory.

    Science.gov (United States)

    Elias, Gabriel A; Bieszczad, Kasia M; Weinberger, Norman M

    2015-12-01

    Primary sensory cortical fields develop highly specific associative representational plasticity, notably enlarged area of representation of reinforced signal stimuli within their topographic maps. However, overtraining subjects after they have solved an instrumental task can reduce or eliminate the expansion while the successful behavior remains. As the development of this plasticity depends on the learning strategy used to solve a task, we asked whether the loss of expansion is due to the strategy used during overtraining. Adult male rats were trained in a three-tone auditory discrimination task to bar-press to the CS+ for water reward and refrain from doing so during the CS- tones and silent intertrial intervals; errors were punished by a flashing light and time-out penalty. Groups acquired this task to a criterion within seven training sessions by relying on a strategy that was "bar-press from tone-onset-to-error signal" ("TOTE"). Three groups then received different levels of overtraining: Group ST, none; Group RT, one week; Group OT, three weeks. Post-training mapping of their primary auditory fields (A1) showed that Groups ST and RT had developed significantly expanded representational areas, specifically restricted to the frequency band of the CS+ tone. In contrast, the A1 of Group OT was no different from naïve controls. Analysis of learning strategy revealed this group had shifted strategy to a refinement of TOTE in which they self-terminated bar-presses before making an error ("iTOTE"). Across all animals, the greater the use of iTOTE, the smaller was the representation of the CS+ in A1. Thus, the loss of cortical expansion is attributable to a shift or refinement in strategy. This reversal of expansion was considered in light of a novel theoretical framework (CONCERTO) highlighting four basic principles of brain function that resolve anomalous findings and explaining why even a minor change in strategy would involve concomitant shifts of involved brain

  16. LEARNING STRATEGY REFINEMENT REVERSES EARLY SENSORY CORTICAL MAP EXPANSION BUT NOT BEHAVIOR: SUPPORT FOR A THEORY OF DIRECTED CORTICAL SUBSTRATES OF LEARNING AND MEMORY

    Science.gov (United States)

    Elias, Gabriel A.; Bieszczad, Kasia M.; Weinberger, Norman M.

    2015-01-01

    Primary sensory cortical fields develop highly specific associative representational plasticity, notably enlarged area of representation of reinforced signal stimuli within their topographic maps. However, overtraining subjects after they have solved an instrumental task can reduce or eliminate the expansion while the successful behavior remains. As the development of this plasticity depends on the learning strategy used to solve a task, we asked whether the loss of expansion is due to the strategy used during overtraining. Adult male rats were trained in a three-tone auditory discrimination task to bar-press to the CS+ for water reward and refrain from doing so during the CS− tones and silent intertrial intervals; errors were punished by a flashing light and time-out penalty. Groups acquired this task to a criterion within seven training sessions by relying on a strategy that was “bar-press from tone-onset-to-error signal” (“TOTE”). Three groups then received different levels of overtraining: Group ST, none; Group RT, one week; Group OT, three weeks. Post-training mapping of their primary auditory fields (A1) showed that Groups ST and RT had developed significantly expanded representational areas, specifically restricted to the frequency band of the CS+ tone. In contrast, the A1 of Group OT was no different from naïve controls. Analysis of learning strategy revealed this group had shifted strategy to a refinement of TOTE in which they self-terminated bar-presses before making an error (“iTOTE”). Across all animals, the greater the use of iTOTE, the smaller was the representation of the CS+ in A1. Thus, the loss of cortical expansion is attributable to a shift or refinement in strategy. This reversal of expansion was considered in light of a novel theoretical framework (CONCERTO) highlighting four basic principles of brain function that resolve anomalous findings and explaining why even a minor change in strategy would involve concomitant shifts of

  17. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

    Science.gov (United States)

    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.

  18. Learning a New Selection Rule in Visual and Frontal Cortex

    NARCIS (Netherlands)

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

    2016-01-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the

  19. Examining Self Regulated Learning in Relation to Certain Selected Variables

    Science.gov (United States)

    Johnson, N.

    2012-01-01

    Self-regulation is the controlling of a process or activity by the students who are involved in Problem solving in Physics rather than by an external agency (Johnson, 2011). Selfregulated learning consists of three main components: cognition, metacognition, and motivation. Cognition includes skills necessary to encode, memorise, and recall…

  20. Understanding Sample Surveys: Selective Learning about Social Science Research Methods

    Science.gov (United States)

    Currin-Percival, Mary; Johnson, Martin

    2010-01-01

    We investigate differences in what students learn about survey methodology in a class on public opinion presented in two critically different ways: with the inclusion or exclusion of an original research project using a random-digit-dial telephone survey. Using a quasi-experimental design and data obtained from pretests and posttests in two public…

  1. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  2. Selection based on the size of the black tie of the great tit may be reversed in urban habitats

    OpenAIRE

    Senar, Juan Carlos; Conroy, Michael J; Quesada, Javier; Mateos-Gonzalez, Fernando

    2014-01-01

    A standard approach to model how selection shapes phenotypic traits is the analysis of capture-recapture data relating trait variation to survival. Divergent selection, however, has never been analyzed by the capture-recapture approach. Most reported examples of differences between urban and nonurban animals reflect behavioral plasticity rather than divergent selection. The aim of this paper was to use a capture-recapture approach to test the hypothesis that divergent selection can also drive...

  3. Quantitative measures of sexual selection reveal no evidence for sex-role reversal in a sea spider with prolonged paternal care.

    Science.gov (United States)

    Barreto, Felipe S; Avise, John C

    2010-10-07

    Taxa in which males alone invest in postzygotic care of offspring are often considered good models for investigating the proffered relationships between sexual selection and mating systems. In the pycnogonid sea spider Pycnogonum stearnsi, males carry large egg masses on their bodies for several weeks, so this species is a plausible candidate for sex-role reversal (greater intensity of sexual selection on females than on males). Here, we couple a microsatellite-based assessment of the mating system in a natural population with formal quantitative measures of genetic fitness to investigate the direction of sexual selection in P. stearnsi. Both sexes proved to be highly polygamous and showed similar standardized variances in reproductive and mating successes. Moreover, the fertility (number of progeny) of males and females appeared to be equally and highly dependent on mate access, as shown by similar Bateman gradients for the two sexes. The absence of sex-role reversal in this population of P. stearnsi is probably attributable to the fact that males are not limited by brooding space but have evolved an ability to carry large numbers of progeny. Body length was not a good predictor of male mating or reproductive success, so the aim of future studies should be to determine what traits are the targets of sexual selection in this species.

  4. Trip Travel Time Forecasting Based on Selective Forgetting Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Zhiming Gui

    2014-01-01

    Full Text Available Travel time estimation on road networks is a valuable traffic metric. In this paper, we propose a machine learning based method for trip travel time estimation in road networks. The method uses the historical trip information extracted from taxis trace data as the training data. An optimized online sequential extreme machine, selective forgetting extreme learning machine, is adopted to make the prediction. Its selective forgetting learning ability enables the prediction algorithm to adapt to trip conditions changes well. Experimental results using real-life taxis trace data show that the forecasting model provides an effective and practical way for the travel time forecasting.

  5. Selective effects of explanation on learning during early childhood.

    Science.gov (United States)

    Legare, Cristine H; Lombrozo, Tania

    2014-10-01

    Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  6. An Evaluation Model To Select an Integrated Learning System in a Large, Suburban School District.

    Science.gov (United States)

    Curlette, William L.; And Others

    The systematic evaluation process used in Georgia's DeKalb County School System to purchase comprehensive instructional software--an integrated learning system (ILS)--is described, and the decision-making model for selection is presented. Selection and implementation of an ILS were part of an instructional technology plan for the DeKalb schools…

  7. Endogenously- and Exogenously-Driven Selective Sustained Attention: Contributions to Learning in Kindergarten Children

    Science.gov (United States)

    Erickson, Lucy C.; Thiessen, Erik D.; Godwin, Karrie E.; Dickerson, John P.; Fisher, Anna V.

    2015-01-01

    Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of…

  8. Feature selection is the ReliefF for multiple instance learning

    NARCIS (Netherlands)

    Zafra, A.; Pechenizkiy, M.; Ventura, S.

    2010-01-01

    Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature selection techniques have been proposed for the traditional settings, where each instance is expected to have a label. In

  9. Code-specific learning rules improve action selection by populations of spiking neurons.

    Science.gov (United States)

    Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

    2014-08-01

    Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

  10. Electromagnetic treatment to old Alzheimer's mice reverses β-amyloid deposition, modifies cerebral blood flow, and provides selected cognitive benefit.

    Directory of Open Access Journals (Sweden)

    Gary W Arendash

    Full Text Available Few studies have investigated physiologic and cognitive effects of "long-term" electromagnetic field (EMF exposure in humans or animals. Our recent studies have provided initial insight into the long-term impact of adulthood EMF exposure (GSM, pulsed/modulated, 918 MHz, 0.25-1.05 W/kg by showing 6+ months of daily EMF treatment protects against or reverses cognitive impairment in Alzheimer's transgenic (Tg mice, while even having cognitive benefit to normal mice. Mechanistically, EMF-induced cognitive benefits involve suppression of brain β-amyloid (Aβ aggregation/deposition in Tg mice and brain mitochondrial enhancement in both Tg and normal mice. The present study extends this work by showing that daily EMF treatment given to very old (21-27 month Tg mice over a 2-month period reverses their very advanced brain Aβ aggregation/deposition. These very old Tg mice and their normal littermates together showed an increase in general memory function in the Y-maze task, although not in more complex tasks. Measurement of both body and brain temperature at intervals during the 2-month EMF treatment, as well as in a separate group of Tg mice during a 12-day treatment period, revealed no appreciable increases in brain temperature (and no/slight increases in body temperature during EMF "ON" periods. Thus, the neuropathologic/cognitive benefits of EMF treatment occur without brain hyperthermia. Finally, regional cerebral blood flow in cerebral cortex was determined to be reduced in both Tg and normal mice after 2 months of EMF treatment, most probably through cerebrovascular constriction induced by freed/disaggregated Aβ (Tg mice and slight body hyperthermia during "ON" periods. These results demonstrate that long-term EMF treatment can provide general cognitive benefit to very old Alzheimer's Tg mice and normal mice, as well as reversal of advanced Aβ neuropathology in Tg mice without brain heating. Results further underscore the potential for EMF

  11. Learning spectrum's selection in OLAM network for analysis cement samples

    International Nuclear Information System (INIS)

    Huang Ning; Wang Peng; Tang Daiquan; Hu Renlan

    2010-01-01

    It uses OLAM artificial neural network to analyze the samples of cement raw material. Two kinds of spectrums are used for network learning: pure-element spectrum and mix-element spectrum. The output of pure-element method can be used to construct a simulate spectrum, which can be compared with the original spectrum and judge the shift of spectrum; the mix-element method can store more message and correct the matrix effect, but the multicollinearity among spectrums can cause some side effect to the results. (authors)

  12. Sex Role Learning: A Test of the Selective Attention Hypothesis.

    Science.gov (United States)

    Bryan, Janice Westlund; Luria, Zella

    This paper reports three studies designed to determine whether children show selective attention and/or differential memory to slide pictures of same-sex vs. opposite-sex models and activities. Attention was measured using a feedback EEG procedure, which measured the presence or absence of alpha rhythms in the subjects' brains during presentation…

  13. Evolution of learning and levels of selection: a lesson from avian parent-offspring communication.

    Science.gov (United States)

    Lotem, Arnon; Biran-Yoeli, Inbar

    2014-02-01

    In recent years, it has become increasingly clear that the evolution of behavior may be better understood as the evolution of the learning mechanisms that produce it, and that such mechanisms should be modeled and tested explicitly. However, this approach, which has recently been applied to animal foraging and decision-making, has rarely been applied to the social and communicative behaviors that are likely to operate in complex social environments and be subject to multi-level selection. Here we use genetic, agent-based evolutionary simulations to explore how learning mechanisms may evolve to adjust the level of nestling begging (offspring signaling of need), and to examine the possible consequences of this process for parent-offspring conflict and communication. In doing so, we also provide the first step-by-step dynamic model of parent-offspring communication. The results confirm several previous theoretical predictions and demonstrate three novel phenomena. First, negatively frequency-dependent group-level selection can generate a stable polymorphism of learning strategies and parental responses. Second, while conventional reinforcement learning models fail to cope successfully with family dynamics at the nest, a newly developed learning model (incorporating behaviors that are consistent with recent experimental results on learning in nestling begging) produced effective learning, which evolved successfully. Third, while kin-selection affects the frequency of the different learning genes, its impact on begging slope and intensity was unexpectedly negligible, demonstrating that evolution is a complex process, and showing that the effect of kin-selection on behaviors that are shaped by learning may not be predicted by simple application of Hamilton's rule. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. How motivation and reward learning modulate selective attention.

    Science.gov (United States)

    Bourgeois, A; Chelazzi, L; Vuilleumier, P

    2016-01-01

    Motivational stimuli such as rewards elicit adaptive responses and influence various cognitive functions. Notably, increasing evidence suggests that stimuli with particular motivational values can strongly shape perception and attention. These effects resemble both selective top-down and stimulus-driven attentional orienting, as they depend on internal states but arise without conscious will, yet they seem to reflect attentional systems that are functionally and anatomically distinct from those classically associated with frontoparietal cortical networks in the brain. Recent research in human and nonhuman primates has begun to reveal how reward can bias attentional selection, and where within the cognitive system the signals providing attentional priority are generated. This review aims at describing the different mechanisms sustaining motivational attention, their impact on different behavioral tasks, and current knowledge concerning the neural networks governing the integration of motivational influences on attentional behavior. © 2016 Elsevier B.V. All rights reserved.

  15. The Geomagnetic Field During a Reversal

    Science.gov (United States)

    Heirtzler, James R.

    2003-01-01

    By modifying the IGRF it is possible to learn what may happen to the geomagnetic field during a geomagnetic reversal. If the entire IGRF reverses then the declination and inclination only reverse when the field strength is zero. If only the dipole component of the IGRF reverses a large geomagnetic field remains when the dipole component is zero and he direction of the field at the end of the reversal is not exactly reversed from the directions at the beginning of the reversal.

  16. Effects of subchronic phencyclidine (PCP treatment on social behaviors, and operant discrimination and reversal learning in C57BL/6J mice

    Directory of Open Access Journals (Sweden)

    Jonathan L Brigman

    2009-02-01

    Full Text Available Subchronic treatment with the psychotomimetic phencyclidine (PCP has been proposed as a rodent model of the negative and cognitive/executive symptoms of schizophrenia. There has, however, been a paucity of studies on this model in mice, despite the growing use of the mouse as a subject in genetic and molecular studies of schizophrenia. In the present study, we evaluated the effects of subchronic PCP treatment (5 mg/kg twice daily x 7 days, followed by 7 days withdrawal in C57BL/6J mice on 1 social behaviors using a sociability/social novelty-preference paradigm, and 2 pairwise visual discrimination and reversal learning using a touchscreen-based operant system. Results showed that mice subchronically treated with PCP made more visits to (but did not spend more time with a social stimulus relative to an inanimate one, and made more visits and spent more time investigating a novel social stimulus over a familiar one. Subchronic PCP treatment did not significantly affect behavior in either the discrimination or reversal learning tasks. These data encourage further analysis of the potential utility of mouse subchronic PCP treatment for modeling the social withdrawal component of schizophrenia. They also indicate that the treatment regimen employed was insufficient to impair our measures of discrimination and reversal learning in the C57BL/6J strain. Further work will be needed to identify alternative methods (e.g., repeated cycles of subchronic PCP treatment, use of different mouse strains that produce discrimination and/or reversal impairment, as well as other cognitive/executive measures that are sensitive to chronic PCP treatment in mice.

  17. Characterizing the selectivity of stationary phases and organic modifiers in reversed-phase high-performance liquid chromatographic systems by a general solvation equation using gradient elution.

    Science.gov (United States)

    Du, C M; Valko, K; Bevan, C; Reynolds, D; Abraham, M H

    2000-11-01

    Retention data for a set of 69 compounds using rapid gradient elution are obtained on a wide range of reversed-phase stationary phases and organic modifiers. The chromatographic stationary phases studied are Inertsil (IN)-ODS, pentafluorophenyl, fluoro-octyl, n-propylcyano, Polymer (PLRP-S 100), and hexylphenyl. The organic solvent modifiers are 2,2,2-trifluoroethanol (TFE); 1,1,1,3,3,3-hexafluoropropan-2-ol (HFIP); isopropanol; methanol (MeOH); acetonitrile (AcN); tetrahydrofuran; 1,4-dioxane; N,N-dimethylformamide; and mixed solvents of dimethylsulfoxide (DMSO) with AcN and DMSO with MeOH (1:1). A total of 25 chromatographic systems are analyzed using a solvation equation. In general, most of the systems give reasonable statistics. The selectivity of the reversed phase-high-performance liquid chromatographic (HPLC) systems with respect to the solute's dipolarity-polarity, hydrogen-bond acidity, and basicity are reflected in correspondingly large coefficients in the solvation equation. We wanted to find the most orthogonal HPLC systems, showing the highest possible selectivity difference in order to derive molecular descriptors using the gradient retention times of a compound. We selected eight chromatographic systems that have a large range of coefficients of interest (s, a, and b) similar to those found in water-solvent partitions used previously to derive molecular descriptors. The systems selected are IN-ODS phases with AcN, MeOH, TFE, and HFIP as mobile phase, PLRP-S 100 phase with AcN, propylcyano phase with AcN and MeOH, and fluorooctyl phase with TFE. Using the retention data obtained for a compound in the selected chromatographic systems, we can estimate the molecular descriptors with the faster and simpler gradient elution method.

  18. Reverse Algols

    Science.gov (United States)

    Leung, K. C.

    1989-01-01

    Reverse Algols, binary systems with a semidetached configuration in which the more massive component is in contact with the critical equipotential surface, are examined. Observational evidence for reverse Algols is presented and the parameters of seven reverse Algols are listed. The evolution of Algols and reverse Algols is discussed. It is suggested that, because reverse Algols represent the premass-reversal semidetached phase of close binary evolution, the evolutionary time scale between regular and reverse Algols is the ratio of the number of confirmed systems of these two Algol types.

  19. USING A MULTI CRITERIA DECISION MAKING APPROACH FOR OPEN AND DISTANCE LEARNING SYSTEM SELECTION

    OpenAIRE

    KAMIŞLI ÖZTÜRK, Zehra

    2015-01-01

    Today, there's a wide variety of open and distance learning (ODL) systems around the world. Herein, for lifelong learning how to select an ODL program becomes a critic question for a learner who wants to extent abilities on his/her career path. This is a complex decision problem with interdependent criteria. The Analytic Network Process (ANP) is a multicriteria decision making methodology  that  reflects  these  interdependencies.  Within &...

  20. Reverse Logistics

    OpenAIRE

    Kulikova, Olga

    2016-01-01

    This thesis was focused on the analysis of the concept of reverse logistics and actual reverse processes which are implemented in mining industry and finding solutions for the optimization of reverse logistics in this sphere. The objective of this paper was the assessment of the development of reverse logistics in mining industry on the example of potash production. The theoretical part was based on reverse logistics and mining waste related literature and provided foundations for further...

  1. Multi-component transport in polymers: hydrocarbon / hydrogen separation by reverse selectivity membrane; Transport multi-composants dans les polymeres: separation hydrocarbures / hydrogene par membrane a selectivite inverse

    Energy Technology Data Exchange (ETDEWEB)

    Mauviel, G.

    2003-12-15

    Hydrogen separation by reverse selectivity membranes is investigated. The first goal is to develop materials showing an increased selectivity. Silicone membranes loaded with inorganic fillers have been prepared, but the expected enhancement is not observed. The second goal is to model the multi- component transport through rubbers. Indeed the permeability model is not able to predict correctly permeation when a vapour is present. Thus many phenomena have to be considered: diffusional inter-dependency, sorption synergy, membrane swelling and drag effect. The dependence of diffusivities with the local composition is modelled according to free-volume theory. The model resolution allows to predict the permeation flow-rates of mixed species from their pure sorption and diffusion data. For the systems under consideration, the diffusional inter-dependency is shown to be preponderant. Besides, sorption synergy importance is pointed out, whereas it is most often neglected. (author)

  2. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

    Science.gov (United States)

    Lindsay, Grace W.

    2017-01-01

    Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (

  3. Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder.

    Science.gov (United States)

    Gabay, Yafit; Goldfarb, Liat

    2017-07-01

    Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both

  4. Selective Reversible Absorption of the Industrial Off-Gas Components CO2 and NOx by Ionic Liquids

    DEFF Research Database (Denmark)

    Kaas-Larsen, Peter Kjartan; Thomassen, P.; Schill, Leonhard

    2016-01-01

    Ionic liquids are promising new materials for climate and pollution control by selective absorption of CO2 and NOx in industrial off-gases. In addition practical cleaning of industrial off gases seems to be attractive by use of ionic liquids distributed on the surface of porous, high surface area...... carriers in the form of so-called Supported Ionic Liquid Phase (SILP) materials. The potential of selected ionic liquids for absorption of CO2 and NOx are demonstrated and the possible interference of other gases influencing the stability and absorption capacity of the ionic liquids are investigated...

  5. Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

    Science.gov (United States)

    Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

    2014-01-01

    Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

  6. Optimal Channel Selection Based on Online Decision and Offline Learning in Multichannel Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mu Qiao

    2017-01-01

    Full Text Available We propose a channel selection strategy with hybrid architecture, which combines the centralized method and the distributed method to alleviate the overhead of access point and at the same time provide more flexibility in network deployment. By this architecture, we make use of game theory and reinforcement learning to fulfill the optimal channel selection under different communication scenarios. Particularly, when the network can satisfy the requirements of energy and computational costs, the online decision algorithm based on noncooperative game can help each individual sensor node immediately select the optimal channel. Alternatively, when the network cannot satisfy the requirements of energy and computational costs, the offline learning algorithm based on reinforcement learning can help each individual sensor node to learn from its experience and iteratively adjust its behavior toward the expected target. Extensive simulation results validate the effectiveness of our proposal and also prove that higher system throughput can be achieved by our channel selection strategy over the conventional off-policy channel selection approaches.

  7. Selective Reversible Absorption of the Industrial Off-Gas Components CO2 and NOx by Ionic Liquids

    DEFF Research Database (Denmark)

    Kaas-Larsen, Peter Kjartan; Thomassen, Peter; Schill, Leonard

    2016-01-01

    Ionic liquids are promising new materials for climate and pollution control by selective absorption of CO2 and NOx in industrial off-gases. In addition pratical cleaning of industrial off gases seems to be attractive by use of ionic liquids distributed on the surface of porous, high surface area...

  8. A thermodynamic approach for selecting operating conditions in the design of reversible solid oxide cell energy systems

    Science.gov (United States)

    Wendel, Christopher H.; Kazempoor, Pejman; Braun, Robert J.

    2016-01-01

    Reversible solid oxide cell (ReSOC) systems are being increasingly considered for electrical energy storage, although much work remains before they can be realized, including cell materials development and system design optimization. These systems store electricity by generating a synthetic fuel in electrolysis mode and subsequently recover electricity by electrochemically oxidizing the stored fuel in fuel cell mode. System thermal management is improved by promoting methane synthesis internal to the ReSOC stack. Within this strategy, the cell-stack operating conditions are highly impactful on system performance and optimizing these parameters to suit both operating modes is critical to achieving high roundtrip efficiency. Preliminary analysis shows the thermoneutral voltage to be a useful parameter for analyzing ReSOC systems and the focus of this study is to quantitatively examine how it is affected by ReSOC operating conditions. The results reveal that the thermoneutral voltage is generally reduced by increased pressure, and reductions in temperature, fuel utilization, and hydrogen-to-carbon ratio. Based on the thermodynamic analysis, many different combinations of these operating conditions are expected to promote efficient energy storage. Pressurized systems can achieve high efficiency at higher temperature and fuel utilization, while non-pressurized systems may require lower stack temperature and suffer from reduced energy density.

  9. How learning might strengthen existing visual object representations in human object-selective cortex.

    Science.gov (United States)

    Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

    2016-02-15

    Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Secure relay selection based on learning with negative externality in wireless networks

    Science.gov (United States)

    Zhao, Caidan; Xiao, Liang; Kang, Shan; Chen, Guiquan; Li, Yunzhou; Huang, Lianfen

    2013-12-01

    In this paper, we formulate relay selection into a Chinese restaurant game. A secure relay selection strategy is proposed for a wireless network, where multiple source nodes send messages to their destination nodes via several relay nodes, which have different processing and transmission capabilities as well as security properties. The relay selection utilizes a learning-based algorithm for the source nodes to reach their best responses in the Chinese restaurant game. In particular, the relay selection takes into account the negative externality of relay sharing among the source nodes, which learn the capabilities and security properties of relay nodes according to the current signals and the signal history. Simulation results show that this strategy improves the user utility and the overall security performance in wireless networks. In addition, the relay strategy is robust against the signal errors and deviations of some user from the desired actions.

  11. Insight into the mechanism of action and selectivity of caspase-3 reversible inhibitors through in silico studies

    Science.gov (United States)

    Minini, Lucía; Ferraro, Florencia; Cancela, Saira; Merlino, Alicia

    2017-11-01

    Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide for which there is currently no cure. Recently, caspase-3 has been proposed as a potential therapeutic target for treating AD. Since this enzyme is overexpressed in brains from AD patients its selective modulation by non-covalent inhibitors becomes an interesting strategy in the search of potential drugs against this neuropathology. With this in mind, we have combined molecular docking, molecular dynamics simulations and QM calculations of unliganded caspase-3 and caspase-7 and in complex with a series of known inhibitors of caspase-3 described in the literature in order to assess the structural features responsible for good inhibitory activity and selectivity against this potential target. This work has allowed us to identify hotspots for drug binding as well as the importance of shape and charge distribution for interacting into the substrate binding cleft or into the dimer interface in each enzyme. Our results showed that most selective compounds against caspsase-3 bind into the substrate binding cleft acting as competitive inhibitors whereas in caspase-7 they bind close to an allosteric site at the dimer interface but since they are weakly bound their presence would not be affecting enzyme dynamics or function. In addition, for both enzymes we have found evidence indicating that differences in shape and accessibility exist between the substrate binding site of each monomer which could be modulating the binding affinity of non-covalent molecules.

  12. Deep Learning Questions Can Help Selection of High Ability Candidates for Universities

    Science.gov (United States)

    Mellanby, Jane; Cortina-Borja, Mario; Stein, John

    2009-01-01

    Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates' "deep learning" approach since this assesses the motivation and creative thinking…

  13. Training Self-Regulated Learning Skills with Video Modeling Examples: Do Task-Selection Skills Transfer?

    Science.gov (United States)

    Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara

    2018-01-01

    Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…

  14. Learning by Exporting or Self Selection? Which Way for the Kenyan ...

    African Journals Online (AJOL)

    The results obtained show some significant differences between exporters and non exporters. The results also show some evidence for learning-by-doing hypothesis and evidence for self-selection of more efficient firms into exporting. On the policy front the paper calls for more focus on improving exports in order for Kenya ...

  15. Reverse Osmosis

    Indian Academy of Sciences (India)

    many applications, one of which is desalination of seawater. The inaugural Nobel Prize in Chemistry was awarded in 1901 to van 't Hoff for his seminal work in this area. The present article explains the principle of osmosis and reverse osmosis. Osmosis and Reverse Osmosis. As the name suggests, reverse osmosis is the ...

  16. Performance of Reverse-Link Synchronous DS-CDMA System on a Frequency-Selective Multipath Fading Channel with Imperfect Power Control

    Directory of Open Access Journals (Sweden)

    Duk Kyung Kim

    2002-08-01

    Full Text Available We analyze the performance for reverse-link synchronous DS-CDMA system in a frequency-selective Rayleigh fading channel with an imperfect power control scheme. The performance degradation due to power control error (PCE, which is approximated by a log-normally distributed random variable, is estimated as a function of the standard deviation of the PCE. In addition, we investigate the impacts of the multipath intensity profile (MIP shape and the number of resolvable paths on the performance. Finally, the coded bit error performance is evaluated in order to estimate the system capacity. Comparing with the conventional CDMA system, we show an achievable gain of from 59% to 23% for reverse-link synchronous transmission technique (RLSTT in the presence of imperfect power control over asynchronous transmission for BER=10−6. As well, the effect of tradeoff between orthogonality and diversity can be seen according to the number of multipaths, and the tendency is kept even in the presence of PCE. We conclude that the capacity can be further improved via the RLSTT, because the DS-CDMA system is very sensitive to power control imperfections.

  17. REM sleep selectively prunes and maintains new synapses in development and learning.

    Science.gov (United States)

    Li, Wei; Ma, Lei; Yang, Guang; Gan, Wen-Biao

    2017-03-01

    The functions and underlying mechanisms of rapid eye movement (REM) sleep remain unclear. Here we show that REM sleep prunes newly formed postsynaptic dendritic spines of layer 5 pyramidal neurons in the mouse motor cortex during development and motor learning. This REM sleep-dependent elimination of new spines facilitates subsequent spine formation during development and when a new motor task is learned, indicating a role for REM sleep in pruning to balance the number of new spines formed over time. Moreover, REM sleep also strengthens and maintains newly formed spines, which are critical for neuronal circuit development and behavioral improvement after learning. We further show that dendritic calcium spikes arising during REM sleep are important for pruning and strengthening new spines. Together, these findings indicate that REM sleep has multifaceted functions in brain development, learning and memory consolidation by selectively eliminating and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.

  18. The study of selective property of college student’s learning space

    Science.gov (United States)

    Nagai, Mizuki; Matsumoto, Yuji; Naka, Ryusuke

    2018-05-01

    These days, college students study not only at places designed for learning such as libraries in colleges, but also cafes in downtown while the number of facilities for learning run by colleges is increasing. Then I have researched facilities in college and those in downtown to find selective properties of college students’ learning space. First, I found by questionnaire survey that students chose “3rd place” such as cafes and fast food shops, second to their houses and libraries in college. Next, I found “psychological factor” were also affected their choice. Furthermore, they studied different subjects at different places. In experiments, I researched how effectively they studied each subject at every place. The results show that I find that places you like and places where learning efficiency is good are different. They learned the least effective at “3d place” regardless of what they learned. The result of how long they kept high-level intellectual activity at each place shows that they could work on the study with more motivation at their favorite place and 3rd place. On the other hand, at the 2nd place, they could study rather effectively, but could not keep concentration and motivation for a long time. In this way, college students have 2 patterns of choosing learning space.

  19. Spatial reversal learning in chronically sensitized rats and in undrugged sensitized rats with dopamine D2-like receptor agonist quinpirole

    Czech Academy of Sciences Publication Activity Database

    Hatalová, Hana; Radostová, Dominika; Pištíková, Adéla; Valeš, Karel; Stuchlík, Aleš

    2014-01-01

    Roč. 8, APR 11 (2014), s. 122 ISSN 1662-5153 R&D Projects: GA MZd(CZ) NT13386; GA ČR(CZ) GA14-03627S Institutional support: RVO:67985823 Keywords : flexibility * reversal * rats * quinpirol * obsessive-compulsive disorder Subject RIV: FH - Neurology Impact factor: 3.270, year: 2014

  20. Dynamic Covalent Chemistry within Biphenyl Scaffolds: Reversible Covalent Bonding, Control of Selectivity, and Chirality Sensing with a Single System.

    Science.gov (United States)

    Ni, Cailing; Zha, Daijun; Ye, Hebo; Hai, Yu; Zhou, Yuntao; Anslyn, Eric V; You, Lei

    2018-01-26

    Axial chirality is a prevalent and important phenomenon in chemistry. Herein we report a combination of dynamic covalent chemistry and axial chirality for the development of a versatile platform for the binding and chirality sensing of multiple classes of mononucleophiles. An equilibrium between an open aldehyde and its cyclic hemiaminal within biphenyl derivatives enabled the dynamic incorporation of a broad range of alcohols, thiols, primary amines, and secondary amines with high efficiency. Selectivity toward different classes of nucleophiles was also achieved by regulating the distinct reactivity of the system with external stimuli. Through induced helicity as a result of central-to-axial chirality transfer, the handedness and ee values of chiral monoalcohol and monoamine analytes were reported by circular dichroism. The strategies introduced herein should find application in many contexts, including assembly, sensing, and labeling. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

    International Nuclear Information System (INIS)

    Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard

    2015-01-01

    Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features

  2. Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

    Energy Technology Data Exchange (ETDEWEB)

    Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)

    2015-01-01

    Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.

  3. Goal selection versus process control while learning to use a brain-computer interface

    Science.gov (United States)

    Royer, Audrey S.; Rose, Minn L.; He, Bin

    2011-06-01

    A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.

  4. Plant experience with temporary reverse osmosis makeup water systems

    International Nuclear Information System (INIS)

    Polidoroff, C.

    1986-01-01

    Pacific Gas and Electric (PG and E) Company's Diablo Canyon Power Plant (DCPP), which is located on California's central coast, has access to three sources of raw water: creek water, well water, and seawater. Creek and well water are DCPP's primary sources of raw water; however, because their supply is limited, these sources are supplemented with seawater. The purpose of this paper is to discuss the temporary, rental, reverse osmosis systems used by PG and E to process DCPP's raw water into water suitable for plant makeup. This paper addresses the following issues: the selection of reverse osmosis over alternative water processing technologies; the decision to use vendor-operated temporary, rental, reverse osmosis equipment versus permanent PG and E-owned and -operated equipment; the performance of DCPP's rental reverse osmosis systems; and, the lessons learned from DCPP's reverse osmosis system rental experience that might be useful to other plants considering renting similar equipment

  5. Lifelong disturbance of serotonin transporter functioning results in fear learning deficits : Reversal by blockade of CRF1 receptors

    NARCIS (Netherlands)

    Bijlsma, Elisabeth Y; Hendriksen, Hendrikus; Baas, Johanna M P; Millan, Mark J; Groenink, Lucianne

    2015-01-01

    The inability to associate aversive events with relevant cues (i.e. fear learning) may lead to maladaptive anxiety. To further study the role of the serotonin transporter (SERT) in fear learning, classical fear conditioning was studied in SERT knockout rats (SERT(-/-)) using fear potentiation of the

  6. Encoding changes in orbitofrontal cortex in reversal-impaired aged rats.

    Science.gov (United States)

    Schoenbaum, Geoffrey; Setlow, Barry; Saddoris, Michael P; Gallagher, Michela

    2006-03-01

    Previous work in rats and primates has shown that normal aging can be associated with a decline in cognitive flexibility mediated by prefrontal circuits. For example, aged rats are impaired in rapid reversal learning, which in young rats depends critically on the orbitofrontal cortex. To assess whether aging-related reversal impairments reflect orbitofrontal dysfunction, we identified aged rats with reversal learning deficits and then recorded single units as these rats, along with unimpaired aged cohorts and young control rats, learned and reversed a series of odor discrimination problems. We found that the flexibility of neural correlates in orbitofrontal cortex was markedly diminished in aged rats characterized as reversal-impaired in initial training. In particular, although many cue-selective neurons in young and aged-unimpaired rats reversed odor preference when the odor-outcome associations were reversed, cue-selective neurons in reversal-impaired aged rats did not. In addition, outcome-expectant neurons in aged-impaired rats failed to become active during cue sampling after learning. These altered features of neural encoding could provide a basis for cognitive inflexibility associated with normal aging.

  7. Training self-assessment and task-selection skills : A cognitive approach to improving self-regulated learning

    NARCIS (Netherlands)

    Kostons, Danny; van Gog, Tamara; Paas, Fred

    For self-regulated learning to be effective, students need to be able to accurately assess their own performance on a learning task and use this assessment for the selection of a new learning task. Evidence suggests, however, that students have difficulties with accurate self-assessment and task

  8. Yeast tRNAPhe expressed in human cells can be selected by HIV-1 for use as a reverse transcription primer

    International Nuclear Information System (INIS)

    Kelly, Nathan J.; Morrow, Casey D.

    2003-01-01

    All naturally occurring human immune deficiency viruses (HIV-1) select and use tRNA Lys,3 as the primer for reverse transcription. Studies to elucidate the mechanism of tRNA selection from the intracellular milieu have been hampered due to the difficulties in manipulating the endogenous levels of tRNA Lys,3 . We have previously described a mutant HIV-1 with a primer binding site (PBS) complementary to yeast tRNA Phe (psHIV-Phe) that relies on transfection of yeast tRNA Phe for infectivity. To more accurately recapitulate the selection process, a cDNA was designed for the intracellular expression of the yeast tRNA Phe . Increasing amounts of the plasmid encoding tRNA Phe resulted in a corresponding increase in levels of yeast tRNA Phe in the cell. The yeast tRNA Phe isolated from cells transfected with the cDNA for yeast tRNA Phe , or in the cell lines expressing yeast tRNA Phe , were aminoacylated, indicating that the expressed yeast tRNA Phe was incorporated into tRNA biogenesis pathways and translation. Increasing the cytoplasmic levels of tRNA Phe resulted in increased encapsidation of tRNA Phe in viruses with a PBS complementary to tRNA Phe (psHIV-Phe) or tRNA Lys,3 (wild-type HIV-1). Production of infectious psHIV-Phe was dependent on the amount of cotransfected tRNA Phe cDNA. Increasing amounts of plasmids encoding yeast tRNA Phe produced an increase of infectious psHIV-Phe that plateaued at a level lower than that from the transfection of the wild-type genome, which uses tRNA Lys,3 as the primer for reverse transcription. Cell lines were generated that expressed yeast tRNA Phe at levels approximately 0.1% of that for tRNA Lys,3 . Even with this reduced level of yeast tRNA Phe , the cell lines complemented psHIV-Phe over background levels. The results of these studies demonstrate that intracellular levels of primer tRNA can have a direct effect on HIV-1 infectivity and further support the role for PBS-tRNA complementarity in the primer selection process

  9. FACTORS THAT INFLUENCE THE SELECTION OF LEARNING OPPORTUNITIES FOR STUDENT NURSES IN PRIMARY HEALTH CARE

    Directory of Open Access Journals (Sweden)

    H. lita

    2002-11-01

    The study therefore focused on the following objective: To identify the factors that influence the selection of learning opportunities for primary health care in hospital units. A qualitative research design utilising focus group discussions were used. The population consisted of conveniently selected lecturers, student nurses and registered nurses. The same initial question was asked in each focus group to initiate the discussions. The data were analysed according to Tesch's method. The results indicated that there is positive commitment from the lecturers and registered nurses to be involved in selecting appropriate learning opportunities. The student nurses also demonstrated a willingness to learn and to be exposed to learning opportunities in primary health care. There were however certain constraints that emerged as themes, namely: • Managerial constraints • Educational constraints Under the theme "managerial constraints" categories such as workload, nursing staff shortages and communication problems were identified. Under the theme "educational constraints" categories such as a lack of guidance, and the correlation of theory and practice emerged. Recommendations based on this research report include improvement of in-service education on managerial and educational aspects to facilitate the primary health care approach in hospitals.

  10. Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-20

    Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

  11. LEARNING MATERIALS SELECTION FOR DIFFERENTIATED INSTRUCTION OF ENGLISH FOR SPECIFIC PURPOSES OF FUTURE PROFESSIONALS IN THE FIELD OF INFORMATION TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Oksana Synekop

    2017-09-01

    Full Text Available In conditions of differentiation the learning materials selection will optimize the training English for Specific Purposes of the future professionals in the field of information technology at university level. The purpose of the article is to define the basic unit of learning material, the factors of influence on the learning material selection, principles, criteria and the procedure of learning material selection in this paper. Reviewing the scientific achievements in the learning material selection in teaching English has become a basis for defining the factors of influence, principles and criteria in the research. The basic unit of learning material (learning English text for professional purposes is outlined. The factors of influence and principles (correspondence of learning materials to professional interests and needs of information technology students; necessary ability and accessibility; regarding the linguistic and stylistic necessity and sufficiency; availability of Internet sources information of the learning material selection are defined. Also, the qualitative criteria (authenticity; professional significance, relevance and informativeness; conformity of foreign language level and intellectual development of students; variety of genres and forms of speech, their sufficient filling by linguistic material; coherence, integrity, consistency, semantic completeness; topic conformity; situation conformity; unlimited access, reliability and exemplarity of Internet sources and the quantitative criteria (the amount of material of the learning material selection are highlighted. The process of English for Specific Purposes material selection (defining the disciplines of different cycles; defining spheres and related topics; outlining situations, communicative roles and intentions of professional communication; specifying the sources of selection; evaluating the texts; analysis of the knowledge, skills and sub-skills required for the

  12. An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2018-03-01

    Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

  13. Reversal of rocuronium-induced neuromuscular block by the selective relaxant binding agent sugammadex: a dose-finding and safety study

    DEFF Research Database (Denmark)

    Sorgenfrei, Iben F; Norrild, Kathrine; Larsen, Per Bo

    2006-01-01

    Sugammadex (Org 25969) forms a complex with steroidal neuromuscular blocking agents, thereby reversing neuromuscular block. This study investigated the dose-response relation, safety, and pharmacokinetics of sugammadex to reverse rocuronium-induced block.......Sugammadex (Org 25969) forms a complex with steroidal neuromuscular blocking agents, thereby reversing neuromuscular block. This study investigated the dose-response relation, safety, and pharmacokinetics of sugammadex to reverse rocuronium-induced block....

  14. Unweaving Misconceptions: Guided Learning, Simulations, and Misconceptions in Learning Principles of Natural Selection

    Science.gov (United States)

    Weeks, Brian E.

    2013-01-01

    College students often come to the study of evolutionary biology with many misconceptions of how the processes of natural selection and speciation occur. How to relinquish these misconceptions with learners is a question that many educators face in introductory biology courses. Constructivism as a theoretical framework has become an accepted and…

  15. Reversibility of female sterilization.

    Science.gov (United States)

    Siegler, A M; Hulka, J; Peretz, A

    1985-04-01

    The discussion considers the current status of reversibility of sterilization in the US and describes clinical and experimental efforts for developing techniques designed for reversibility. It focuses on regret following sterilization, reversal potential of current sterilization techniques, patient selection, current reversal techniques, results of sterilization procedures, experimental approaches to reversal of current techniques of sterilization, and sterilization procedures devised for reversibility, in humans and in animals. Request is the 1st stage of reversal, but a request for sterilization reversal (SR) does not always mean regret for a decision made at the time. Frequently it is a wish to restore fertility because life circumstances have changed after a sterilization that was ppropriate at the time it was performed. Schwyhart and Kutner reviewed 22 studies published between 1949-69 in which they found that the percentage of patients regretting the procedure ranged from 1.3-15%. Requests for reversal remain low in most countries, but if sterilization becomes a more popular method of contraception, requests will also increase. The ideal operation considered as a reversaible method of sterilization should include an easy, reliable outpatient method of tubal occlusion with miniml risk or patient discomfort that subsequently could be reversed without the need for a major surgical intervention. Endoscopic methods have progressed toward the 1st objective. A recent search of the literature uncovered few series of SR of more than 50 cases. The 767 operations found were analyzed with regard to pregnancy outcome. The precent of live births varied from 74-78.8%, and the occurance of tubal pregnancies ranged from 1.7-6.5%. All of the confounding variables in patient selection and small numbers of reported procedures preclude any conclusion about the different techniques or the number of operations that give a surgeon a level of expertise. Few authors classify their

  16. Dress Nicer = Know More? Young Children's Knowledge Attribution and Selective Learning Based on How Others Dress.

    Directory of Open Access Journals (Sweden)

    Kyla P McDonald

    Full Text Available This research explored whether children judge the knowledge state of others and selectively learn novel information from them based on how they dress. The results indicated that 4- and 6-year-olds identified a formally dressed individual as more knowledgeable about new things in general than a casually dressed one (Study 1. Moreover, children displayed an overall preference to seek help from a formally dressed individual rather than a casually dressed one when learning about novel objects and animals (Study 2. These findings are discussed in relation to the halo effect, and may have important implications for child educators regarding how instructor dress might influence young students' knowledge attribution and learning preferences.

  17. The impact of computer-based versus "traditional" textbook science instruction on selected student learning outcomes

    Science.gov (United States)

    Rothman, Alan H.

    -inquiry skills. These conclusions support the value of a non-traditional, computer-based approach to instruction, such as exemplified by The Voyage of the Mimi curriculum, and a recommendation for reform in science teaching that has recommended the use of computer technology to enhance learning outcomes from science instruction to assist in reversing the trend toward what has been perceived to be relatively poor science performance by American students, as documented by the 1996 Third International Mathematics and Science Study (TIMSS).

  18. Allelic variant in the anti-Müllerian hormone gene leads to autosomal and temperature-dependent sex reversal in a selected Nile tilapia line.

    Directory of Open Access Journals (Sweden)

    Stephan Wessels

    Full Text Available Owing to the demand for sustainable sex-control protocols in aquaculture, research in tilapia sex determination is gaining momentum. The mutual influence of environmental and genetic factors hampers disentangling the complex sex determination mechanism in Nile tilapia (Oreochromis niloticus. Previous linkage analyses have demonstrated quantitative trait loci for the phenotypic sex on linkage groups 1, 3, and 23. Quantitative trait loci for temperature-dependent sex reversal similarly reside on linkage group 23. The anti-Müllerian hormone gene (amh, located in this genomic region, is important for sexual fate in higher vertebrates, and shows sexually dimorphic expression in Nile tilapia. Therefore this study aimed at detecting allelic variants and marker-sex associations in the amh gene. Sequencing identified six allelic variants. A significant effect on the phenotypic sex for SNP ss831884014 (p<0.0017 was found by stepwise logistic regression. The remaining variants were not significantly associated. Functional annotation of SNP ss831884014 revealed a non-synonymous amino acid substitution in the amh protein. Consequently, a fluorescence resonance energy transfer (FRET based genotyping assay was developed and validated with a representative sample of fish. A logistic linear model confirmed a highly significant effect of the treatment and genotype on the phenotypic sex, but not for the interaction term (treatment: p<0.0001; genotype: p<0.0025. An additive genetic model proved a linear allele substitution effect of 12% in individuals from controls and groups treated at high temperature, respectively. Moreover, the effect of the genotype on the male proportion was significantly higher in groups treated at high temperature, giving 31% more males on average of the three genotypes. In addition, the groups treated at high temperature showed a positive dominance deviation (+11.4% males. In summary, marker-assisted selection for amh variant ss831884014

  19. Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

  20. [Multilingualism and child psychiatry: on differential diagnoses of language disorder, specific learning disorder, and selective mutism].

    Science.gov (United States)

    Tamiya, Satoshi

    2014-01-01

    Multilingualism poses unique psychiatric problems, especially in the field of child psychiatry. The author discusses several linguistic and transcultural issues in relation to Language Disorder, Specific Learning Disorder and Selective Mutism. Linguistic characteristics of multiple language development, including so-called profile effects and code-switching, need to be understood for differential diagnosis. It is also emphasized that Language Disorder in a bilingual person is not different or worse than that in a monolingual person. Second language proficiency, cultural background and transfer from the first language all need to be considered in an evaluation for Specific Learning Disorder. Selective Mutism has to be differentiated from the silent period observed in the normal successive bilingual development. The author concludes the review by remarking on some caveats around methods of language evaluation in a multilingual person.

  1. Engineering Encounters: Reverse Engineering

    Science.gov (United States)

    McGowan, Veronica Cassone; Ventura, Marcia; Bell, Philip

    2017-01-01

    This column presents ideas and techniques to enhance your science teaching. This month's issue shares information on how students' everyday experiences can support science learning through engineering design. In this article, the authors outline a reverse-engineering model of instruction and describe one example of how it looked in our fifth-grade…

  2. Criteria to assess potential reverse innovations: opportunities for shared learning between high- and low-income countries.

    Science.gov (United States)

    Bhattacharyya, Onil; Wu, Diane; Mossman, Kathryn; Hayden, Leigh; Gill, Pavan; Cheng, Yu-Ling; Daar, Abdallah; Soman, Dilip; Synowiec, Christina; Taylor, Andrea; Wong, Joseph; von Zedtwitz, Max; Zlotkin, Stanley; Mitchell, William; McGahan, Anita

    2017-01-25

    Low- and middle-income countries (LMICs) are developing novel approaches to healthcare that may be relevant to high-income countries (HICs). These include products, services, organizational processes, or policies that improve access, cost, or efficiency of healthcare. However, given the challenge of replication, it is difficult to identify innovations that could be successfully adapted to high-income settings. We present a set of criteria for evaluating the potential impact of LMIC innovations in HIC settings. An initial framework was drafted based on a literature review, and revised iteratively by applying it to LMIC examples from the Center for Health Market Innovations (CHMI) program database. The resulting criteria were then reviewed using a modified Delphi process by the Reverse Innovation Working Group, consisting of 31 experts in medicine, engineering, management and political science, as well as representatives from industry and government, all with an expressed interest in reverse innovation. The resulting 8 criteria are divided into two steps with a simple scoring system. First, innovations are assessed according to their success within the LMIC context according to metrics of improving accessibility, cost-effectiveness, scalability, and overall effectiveness. Next, they are scored for their potential for spread to HICs, according to their ability to address an HIC healthcare challenge, compatibility with infrastructure and regulatory requirements, degree of novelty, and degree of current collaboration with HICs. We use examples to illustrate where programs which appear initially promising may be unlikely to succeed in a HIC setting due to feasibility concerns. This study presents a framework for identifying reverse innovations that may be useful to policymakers and funding agencies interested in identifying novel approaches to addressing cost and access to care in HICs. We solicited expert feedback and consensus on an empirically-derived set of criteria

  3. Selective and membrane-permeable small molecule inhibitors of nicotinamide N-methyltransferase reverse high fat diet-induced obesity in mice.

    Science.gov (United States)

    Neelakantan, Harshini; Vance, Virginia; Wetzel, Michael D; Wang, Hua-Yu Leo; McHardy, Stanton F; Finnerty, Celeste C; Hommel, Jonathan D; Watowich, Stanley J

    2018-01-01

    There is a critical need for new mechanism-of-action drugs that reduce the burden of obesity and associated chronic metabolic comorbidities. A potentially novel target to treat obesity and type 2 diabetes is nicotinamide-N-methyltransferase (NNMT), a cytosolic enzyme with newly identified roles in cellular metabolism and energy homeostasis. To validate NNMT as an anti-obesity drug target, we investigated the permeability, selectivity, mechanistic, and physiological properties of a series of small molecule NNMT inhibitors. Membrane permeability of NNMT inhibitors was characterized using parallel artificial membrane permeability and Caco-2 cell assays. Selectivity was tested against structurally-related methyltransferases and nicotinamide adenine dinucleotide (NAD + ) salvage pathway enzymes. Effects of NNMT inhibitors on lipogenesis and intracellular levels of metabolites, including NNMT reaction product 1-methylnicotianamide (1-MNA) were evaluated in cultured adipocytes. Effects of a potent NNMT inhibitor on obesity measures and plasma lipid were assessed in diet-induced obese mice fed a high-fat diet. Methylquinolinium scaffolds with primary amine substitutions displayed high permeability from passive and active transport across membranes. Importantly, methylquinolinium analogues displayed high selectivity, not inhibiting related SAM-dependent methyltransferases or enzymes in the NAD + salvage pathway. NNMT inhibitors reduced intracellular 1-MNA, increased intracellular NAD + and S-(5'-adenosyl)-l-methionine (SAM), and suppressed lipogenesis in adipocytes. Treatment of diet-induced obese mice systemically with a potent NNMT inhibitor significantly reduced body weight and white adipose mass, decreased adipocyte size, and lowered plasma total cholesterol levels. Notably, administration of NNMT inhibitors did not impact total food intake nor produce any observable adverse effects. These results support development of small molecule NNMT inhibitors as therapeutics to

  4. Feature selection and multi-kernel learning for sparse representation on a manifold

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-03-01

    Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao etal. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. © 2013 Elsevier Ltd.

  5. Feature selection and multi-kernel learning for sparse representation on a manifold.

    Science.gov (United States)

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2014-03-01

    Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao et al. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands

    Directory of Open Access Journals (Sweden)

    Krzysztof Rataj

    2018-05-01

    Full Text Available The identification of subtype-selective GPCR (G-protein coupled receptor ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP. This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds’ selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.

  7. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  8. Tautomerism of N-(3,4-dichlorophenyl)-1H-indazole-5-carboxamide - A new selective, highly potent and reversible MAO-B inhibitor

    Science.gov (United States)

    Tzvetkov, Nikolay T.; Stammler, Hans-Georg; Antonov, Liudmil

    2017-12-01

    The tautomeric properties of an N-(3,4-dichlorophenyl)-1H-indazole-5-carboxamide (NTZ-1006, 2) derivative, developed as highly potent, reversible and selective MAO-B inhibitor useful for the treatment of Parkinson's disease (PD) and other neurological disorders, have been studied both experimentally and theoretically. The theoretical data (M06-2X, B3LYP and MP2-4 quantum chemical calculations) have shown that due to aromaticity reasons the 1H tautomer strongly dominates over the 2H form. There are no substantial spectral changes by changing the solvent and the concentration, which leads to a conclusion that compound 2 exists in solution as 1H tautomer and its tautomerism is not influenced by the solvents and the concentration. The results are in line with the understanding for the tautomerism of 1H-indazole and shows that substitution at the C5 position in the indazole unit does not influence the tautomeric state. The isolated crystal structure of 2 is in an excellent agreement with the computation in respect of the most stable tautomer. Combined single X-ray/molecular modeling studies including HYdrogen-DEsolvation (HYDE) analysis provided not only insights into the enzyme-inhibitor interaction within the binding site of the human MAO-B isoform, but also a valuable information regarding the most stable 1H-indazole tautomeric form of NTZ-1006 that contributes to its high potency against hMAO-B enzyme (IC50 0.586 nm) and selectivity (>17000-fold) over the hMAO-A isoenzyme.

  9. Negative mood reverses devaluation of goal-directed drug-seeking favouring an incentive learning account of drug dependence.

    Science.gov (United States)

    Hogarth, Lee; He, Zhimin; Chase, Henry W; Wills, Andy J; Troisi, Joseph; Leventhal, Adam M; Mathew, Amanda R; Hitsman, Brian

    2015-09-01

    Two theories explain how negative mood primes smoking behaviour. The stimulus-response (S-R) account argues that in the negative mood state, smoking is experienced as more reinforcing, establishing a direct (automatic) association between the negative mood state and smoking behaviour. By contrast, the incentive learning account argues that in the negative mood state smoking is expected to be more reinforcing, which integrates with instrumental knowledge of the response required to produce that outcome. One differential prediction is that whereas the incentive learning account anticipates that negative mood induction could augment a novel tobacco-seeking response in an extinction test, the S-R account could not explain this effect because the extinction test prevents S-R learning by omitting experience of the reinforcer. To test this, overnight-deprived daily smokers (n = 44) acquired two instrumental responses for tobacco and chocolate points, respectively, before smoking to satiety. Half then received negative mood induction to raise the expected value of tobacco, opposing satiety, whilst the remainder received positive mood induction. Finally, a choice between tobacco and chocolate was measured in extinction to test whether negative mood could augment tobacco choice, opposing satiety, in the absence of direct experience of tobacco reinforcement. Negative mood induction not only abolished the devaluation of tobacco choice, but participants with a significant increase in negative mood increased their tobacco choice in extinction, despite satiety. These findings suggest that negative mood augments drug-seeking by raising the expected value of the drug through incentive learning, rather than through automatic S-R control.

  10. Negative mood reverses devaluation of goal-directed drug-seeking favouring an incentive learning account of drug dependence

    OpenAIRE

    Hogarth, L; Zhimin, H; Chase, HW; Wills, AJ; Troisi II, J; Leventhal, M; Mathew, AR; Hitsman, B

    2015-01-01

    Background Two theories explain how negative mood primes smoking behaviour. The stimulus?response (S-R) account argues that in the negative mood state, smoking is experienced as more reinforcing, establishing a direct (automatic) association between the negative mood state and smoking behaviour. By contrast, the incentive learning account argues that in the negative mood state smoking is expected to be more reinforcing, which integrates with instrumental knowledge of the response required to ...

  11. Feature Selection Methods for Zero-Shot Learning of Neural Activity

    Directory of Open Access Journals (Sweden)

    Carlos A. Caceres

    2017-06-01

    Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

  12. Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA – A statistical learning approach

    Directory of Open Access Journals (Sweden)

    R. Jegadeeshwaran

    2015-03-01

    Full Text Available In automobile, brake system is an essential part responsible for control of the vehicle. Any failure in the brake system impacts the vehicle's motion. It will generate frequent catastrophic effects on the vehicle cum passenger's safety. Thus the brake system plays a vital role in an automobile and hence condition monitoring of the brake system is essential. Vibration based condition monitoring using machine learning techniques are gaining momentum. This study is one such attempt to perform the condition monitoring of a hydraulic brake system through vibration analysis. In this research, the performance of a Clonal Selection Classification Algorithm (CSCA for brake fault diagnosis has been reported. A hydraulic brake system test rig was fabricated. Under good and faulty conditions of a brake system, the vibration signals were acquired using a piezoelectric transducer. The statistical parameters were extracted from the vibration signal. The best feature set was identified for classification using attribute evaluator. The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed. The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96% for the fault diagnosis of a hydraulic brake system.

  13. Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

    Science.gov (United States)

    King, Adam C; Newell, Karl M

    2015-10-01

    The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

  14. Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning

    Science.gov (United States)

    Yu, Jianbo

    2016-11-01

    The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.

  15. From Reactionary to Responsive: Applying the Internal Environmental Scan Protocol to Lifelong Learning Strategic Planning and Operational Model Selection

    Science.gov (United States)

    Downing, David L.

    2009-01-01

    This study describes and implements a necessary preliminary strategic planning procedure, the Internal Environmental Scanning (IES), and discusses its relevance to strategic planning and university-sponsored lifelong learning program model selection. Employing a qualitative research methodology, a proposed lifelong learning-centric IES process…

  16. Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning

    NARCIS (Netherlands)

    Kostons, Danny; Van Gog, Tamara; Paas, Fred

    2012-01-01

    Kostons, D., Van Gog, T., & Paas, F. (2012). Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning. Learning and Instruction, 22(2), 121-132. doi:10.1016/j.learninstruc.2011.08.004

  17. The Post-mating Switch in the Pheromone Response of Nasonia Females Is Mediated by Dopamine and Can Be Reversed by Appetitive Learning

    Directory of Open Access Journals (Sweden)

    Maria Lenschow

    2018-01-01

    Full Text Available The olfactory sense is of crucial importance for animals, but their response to chemical stimuli is plastic and depends on their physiological state and prior experience. In many insect species, mating status influences the response to sex pheromones, but the underlying neuromodulatory mechanisms are poorly understood. After mating, females of the parasitic wasp Nasonia vitripennis are no longer attracted to the male sex pheromone. Here we show that this post-mating behavioral switch is mediated by dopamine (DA. Females fed a DA-receptor antagonist prior to mating maintained their attraction to the male pheromone after mating while virgin females injected with DA became unresponsive. However, the switch is reversible as mated females regained their pheromone preference after appetitive learning. Feeding mated N. vitripennis females with antagonists of either octopamine- (OA or DA-receptors prevented relearning of the pheromone preference suggesting that both receptors are involved in appetitive learning. Moreover, DA injection into mated females was sufficient to mimic the oviposition reward during odor conditioning with the male pheromone. Our data indicate that DA plays a key role in the plastic pheromone response of N. vitripennis females and reveal some striking parallels between insects and mammals in the neuromodulatory mechanisms underlying olfactory plasticity.

  18. Altering spatial priority maps via statistical learning of target selection and distractor filtering.

    Science.gov (United States)

    Ferrante, Oscar; Patacca, Alessia; Di Caro, Valeria; Della Libera, Chiara; Santandrea, Elisa; Chelazzi, Leonardo

    2018-05-01

    The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering. Crucially, it is unclear whether the two processes rely on shared neuronal machinery, with unavoidable cross-talk, or they are fully independent, an issue that we directly addressed here. In a series of visual search experiments, participants had to discriminate a target stimulus, while ignoring a task-irrelevant salient distractor (when present). We systematically manipulated spatial probabilities of either one or the other stimulus, or both. We then measured performance to evaluate the direct effects of the applied contingent probability distribution (e.g., effects on target selection of the spatial imbalance in target occurrence across locations) as well as its indirect or "transfer" effects (e.g., effects of the same spatial imbalance on distractor filtering across locations). By this approach, we confirmed that SL of both target and distractor location implicitly bias attention. Most importantly, we described substantial indirect effects, with the unequal spatial probability of the target affecting filtering efficiency and, vice versa, the unequal spatial probability of the distractor affecting target selection efficiency across locations. The observed cross-talk demonstrates that SL of target selection and distractor filtering are instantiated via (at least partly) shared neuronal machinery, as further corroborated by strong correlations between direct and indirect effects at the level of individual participants. Our findings are compatible

  19. A calpain-2 selective inhibitor enhances learning & memory by prolonging ERK activation.

    Science.gov (United States)

    Liu, Yan; Wang, Yubin; Zhu, Guoqi; Sun, Jiandong; Bi, Xiaoning; Baudry, Michel

    2016-06-01

    While calpain-1 activation is required for LTP induction by theta burst stimulation (TBS), calpain-2 activation limits its magnitude during the consolidation period. A selective calpain-2 inhibitor applied either before or shortly after TBS enhanced the degree of potentiation. In the present study, we tested whether the selective calpain-2 inhibitor, Z-Leu-Abu-CONH-CH2-C6H3 (3, 5-(OMe)2 (C2I), could enhance learning and memory in wild-type (WT) and calpain-1 knock-out (C1KO) mice. We first showed that C2I could reestablish TBS-LTP in hippocampal slices from C1KO mice, and this effect was blocked by PD98059, an inhibitor of ERK. TBS resulted in PTEN degradation in hippocampal slices from both WT and C1KO mice, and C2I treatment blocked this effect in both mouse genotypes. Systemic injection of C2I 30 min before training in the fear-conditioning paradigm resulted in a biphasic dose-response curve, with low doses enhancing and high doses inhibiting freezing behavior. The difference between the doses needed to enhance and inhibit learning matches the difference in concentrations producing inhibition of calpain-2 and calpain-1. A low dose of C2I also restored normal learning in a novel object recognition task in C1KO mice. Levels of SCOP, a ERK phosphatase known to be cleaved by calpain-1, were decreased in dorsal hippocampus early but not late following training in WT mice; C2I treatment did not affect the early decrease in SCOP levels but prevented its recovery at the later time-point and prolonged ERK activation. The results indicate that calpain-2 activation limits the extent of learning, an effect possibly due to temporal limitation of ERK activation, as a result of SCOP synthesis induced by calpain-2-mediated PTEN degradation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Gene selection for microarray data classification via subspace learning and manifold regularization.

    Science.gov (United States)

    Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

    2017-12-19

    With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

  1. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    Energy Technology Data Exchange (ETDEWEB)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)

    2012-01-10

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  2. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    International Nuclear Information System (INIS)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  3. Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

    Science.gov (United States)

    Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  4. Comparison of Reversal Test Pictures among Three Groups of Students: Normal, Education Mental Retarded and Students with Learning Disabilities in Tehran

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Koushesh

    2007-01-01

    Full Text Available Objective: Riversal visual perception discrimination test is one of the dyslexia diagnostic tests in children which can be performed in the group (group-based and it is reliable to detect these disorders in students of the primary schools especially those who spend their first educational weeks or months. The aim of this survey is comparison of Riversal test pictures among three groups of students: normal, educable mental retarded students and students with learning disabilities, aged 8-12 years old that were under coverage of Tehran Welfare Department. Materials & Methods: This Comparative cross – sectional study has performed on 150 girls and boys of mentioned groups that were selected by simple randomize selection. Results: The findings suggested that there was significant difference between surveyed groups (P=0.001. The highest scores were related to normal students and the lowest scores to educable mental retarded. The interval of negative scores of educable mental retarded from normal students was more than that of between educable mental retarded and learning disabilities. Conclusion: This survey indicates that students with learning disabilities (dyslexia have problems in their visual perception and this test can help to diagnose and determine abnormal children as soon as possible in order to better treatment.

  5. Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae using reverse-transcription quantitative PCR.

    Directory of Open Access Journals (Sweden)

    Miao Yuan

    Full Text Available The brown planthopper (BPH, Nilaparvata lugens (Hemiptera, Delphacidae, is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR. Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT, muscle actin (MACT, ribosomal protein S11 (RPS11, ribosomal protein S15e (RPS15, alpha 2-tubulin (TUB, elongation factor 1 delta (EF, 18S ribosomal RNA (18S, and arginine kinase (AK and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for

  6. Diffusion-weighted imaging of the liver at 3 T using section-selection gradient reversal: emphasis on chemical shift artefacts and lesion conspicuity

    International Nuclear Information System (INIS)

    Lee, J.S.; Kim, Y.K.; Jeong, W.K.; Choi, D.; Lee, W.J.

    2015-01-01

    Aim: To assess the value of section-selection gradient reversal (SSGR) in liver diffusion-weighted imaging (DWI) by comparing it to conventional DWI with an emphasis on chemical shift artefacts and lesion conspicuity. Materials and methods: Forty-eight patients (29 men and 19 women; age range 33–80 years) with 48 liver lesions underwent two DWI examinations using spectral presaturation with inversion recovery fat suppression with and without SSGR at 3 T. Two reviewers evaluated each DWI (b = 100 and b = 800 image) with respect to chemical shift artefacts and liver lesion conspicuity using five-point scales and performed pairwise comparisons between the two DWIs. The signal-to-noise ratio (SNR) of the liver and the lesion and the lesion–liver contrast-to-noise ratio (CNR) were also calculated. Results: SSGR-DWI was significantly better than conventional DWI with respect to chemical shift artefacts and lesion conspicuity in both separate reviews and pairwise comparisons (p < 0.05). There were significant differences in the SNR of the liver (b = 100 and b = 800 images) and lesion (b = 800) between SSGR-DWI and conventional DWI (p < 0.05). Conclusion: Applying the SSGR method to DWI using SPIR fat suppression at 3 T could significantly reduce chemical shift artefacts without incurring additional acquisition time or SNR penalties, which leads to increased conspicuity of focal liver lesions. - Highlights: • Chemical shift artefact in liver DWI is markedly decreased by applying SSGR. • Liver lesion conspicuity is improved by applying SSGR to DWI. • In SNR of the liver, SSGR-DWI is better than conventional DWI

  7. Application of perfluorinated acids as ion-pairing reagents for reversed-phase chromatography and retention-hydrophobicity relationships studies of selected beta-blockers.

    Science.gov (United States)

    Flieger, J

    2010-01-22

    The addition of the homologous series of perfluorinated acids-trifluoroacetic acid (TFAA), pentafluoropropionic acid (PFPA), heptafluorobutyric acid (HFBA) to mobile phases for reversed-phase high-performance liquid chromatography (RP-HPLC) of beta-blockers was tested. Acidic modifiers were responsible for acidification of mobile phase (pH 3) ensuring the protonation of the beta-blockers and further ion pairs creation. The effect of the type and concentration of mobile phase additives on retention parameters, the efficiency of the peaks, their symmetry and separation selectivity of the beta-blockers mixture were all studied. It appeared that at increasing acid concentration, the retention factor, for all compounds investigated, increased to varying degrees. It should be stressed that the presence of acids more significantly affected the retention of the most hydrophobic beta-blockers. Differences in hydrophobicity of drugs can be maximized through variation of the hydrophobicity of additives. Thus, the relative increase in the retention depends on either concentration and hydrophobicity of the anionic mobile phase additive or hydrophobicity of analytes. According to QSRR (quantitative structure retention relationship) methodology, chromatographic lipophilicity parameters: isocratic log k and log k(w) values (extrapolated retention to pure water) were correlated with the molecular (log P(o/w)) and apparent (log P(app)) octanol-water partition coefficients obtained experimentally by countercurrent chromatography (CCC) or predicted by Pallas software. The obtained, satisfactory retention-hydrophobicity correlations indicate that, in the case of the basic drugs examined in RP-HPLC systems modified with perfluorinated acids, the retention is mainly governed by their hydrophobicity. Copyright 2009 Elsevier B.V. All rights reserved.

  8. Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

    Science.gov (United States)

    Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

    2016-09-15

    Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.

  9. Facile preparation of an alternating copolymer-based high molecular shape-selective organic phase for reversed-phase liquid chromatography.

    Science.gov (United States)

    Mallik, Abul K; Noguchi, Hiroki; Rahman, Mohammed Mizanur; Takafuji, Makoto; Ihara, Hirotaka

    2018-06-22

    The synthesis of a new alternating copolymer-grafted silica phase is described for the separation of shape-constrained isomers of polycyclic aromatic hydrocarbons (PAHs) and tocopherols in reversed-phase high-performance liquid chromatography (RP-HPLC). Telomerization of the monomers (octadecyl acrylate and N-methylmaleimide) was carried out with a silane coupling agent; 3-mercaptopropyltrimethoxysilane (MPS), and the telomer (T) was grafted onto porous silica surface to prepare the alternating copolymer-grafted silica phase (Sil-alt-T). The new hybrid material was characterized by elemental analyses, diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy, and solid-state 13 C and 29 Si cross-polarization magic-angle spinning (CP/MAS) NMR spectroscopy. The results of 13 C CP/MAS NMR demonstrated that the alkyl chains of the grafted polymers in Sil-alt-T remained disordered, amorphous, and mobile represented by gauche conformational form. Separation abilities and molecular-shape selectivities of the prepared organic phase were evaluated by the separation of PAHs isomers and Standard Reference Material 869b, Column Selectivity Test Mixture for Liquid Chromatography, respectively and compared with commercially available octadecylsilylated silica (ODS) and C 30 columns as well as previously reported alternating copolymer-based column. The effectiveness of this phase is also demonstrated by the separation of tocopherol isomers. Oriented functional groups along the polymer main chains and cavity formations are investigated to be the driving force for better separation with multiple-interactions with the solutes. One of the advantages of the Sil-alt-T phase to that of the previously reported phase is the synthesis of the telomer first and then immobilized onto silica surface. In this case, the telomer was characterized easily with simple spectroscopic techniques and the molecular mass and polydispersity index of the telomer were determined by size exclusion

  10. Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

    Science.gov (United States)

    Imbalzano, Giulio; Anelli, Andrea; Giofré, Daniele; Klees, Sinja; Behler, Jörg; Ceriotti, Michele

    2018-06-01

    Machine learning of atomic-scale properties is revolutionizing molecular modeling, making it possible to evaluate inter-atomic potentials with first-principles accuracy, at a fraction of the costs. The accuracy, speed, and reliability of machine learning potentials, however, depend strongly on the way atomic configurations are represented, i.e., the choice of descriptors used as input for the machine learning method. The raw Cartesian coordinates are typically transformed in "fingerprints," or "symmetry functions," that are designed to encode, in addition to the structure, important properties of the potential energy surface like its invariances with respect to rotation, translation, and permutation of like atoms. Here we discuss automatic protocols to select a number of fingerprints out of a large pool of candidates, based on the correlations that are intrinsic to the training data. This procedure can greatly simplify the construction of neural network potentials that strike the best balance between accuracy and computational efficiency and has the potential to accelerate by orders of magnitude the evaluation of Gaussian approximation potentials based on the smooth overlap of atomic positions kernel. We present applications to the construction of neural network potentials for water and for an Al-Mg-Si alloy and to the prediction of the formation energies of small organic molecules using Gaussian process regression.

  11. Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

    Science.gov (United States)

    Shah, M; Marchand, M; Corbeil, J

    2012-01-01

    One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

  12. Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning.

    Science.gov (United States)

    Iwata, Kazunori

    2016-05-11

    Softmax selection is one of the most popular methods for action selection in reinforcement learning. Although various recently proposed methods may be more effective with full parameter tuning, implementing a complicated method that requires the tuning of many parameters can be difficult. Thus, softmax selection is still worth revisiting, considering the cost savings of its implementation and tuning. In fact, this method works adequately in practice with only one parameter appropriately set for the environment. The aim of this paper is to improve the variable setting of this method to extend the bandwidth of good parameters, thereby reducing the cost of implementation and parameter tuning. To achieve this, we take advantage of the asymptotic equipartition property in a Markov decision process to extend the peak bandwidth of softmax selection. Using a variety of episodic tasks, we show that our setting is effective in extending the bandwidth and that it yields a better policy in terms of stability. The bandwidth is quantitatively assessed in a series of statistical tests.

  13. Applications of machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet stars

    Science.gov (United States)

    Morello, Giuseppe; Morris, P. W.; Van Dyk, S. D.; Marston, A. P.; Mauerhan, J. C.

    2018-01-01

    We have investigated and applied machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet (WR) candidates. Objects taken from the Spitzer Galactic Legacy Infrared Midplane Survey Extraordinaire (GLIMPSE) catalogue of the infrared objects in the Galactic plane can be classified into different stellar populations based on the colours inferred from their broad-band photometric magnitudes [J, H and Ks from 2 Micron All Sky Survey (2MASS), and the four Spitzer/IRAC bands]. The algorithms tested in this pilot study are variants of the k-nearest neighbours approach, which is ideal for exploratory studies of classification problems where interrelations between variables and classes are complicated. The aims of this study are (1) to provide an automated tool to select reliable WR candidates and potentially other classes of objects, (2) to measure the efficiency of infrared colour selection at performing these tasks and (3) to lay the groundwork for statistically inferring the total number of WR stars in our Galaxy. We report the performance results obtained over a set of known objects and selected candidates for which we have carried out follow-up spectroscopic observations, and confirm the discovery of four new WR stars.

  14. Informative sensor selection and learning for prediction of lower limb kinematics using generative stochastic neural networks.

    Science.gov (United States)

    Eunsuk Chong; Taejin Choi; Hyungmin Kim; Seung-Jong Kim; Yoha Hwang; Jong Min Lee

    2017-07-01

    We propose a novel approach of selecting useful input sensors as well as learning a mathematical model for predicting lower limb joint kinematics. We applied a feature selection method based on the mutual information called the variational information maximization, which has been reported as the state-of-the-art work among information based feature selection methods. The main difficulty in applying the method is estimating reliable probability density of input and output data, especially when the data are high dimensional and real-valued. We addressed this problem by applying a generative stochastic neural network called the restricted Boltzmann machine, through which we could perform sampling based probability estimation. The mutual informations between inputs and outputs are evaluated in each backward sensor elimination step, and the least informative sensor is removed with its network connections. The entire network is fine-tuned by maximizing conditional likelihood in each step. Experimental results are shown for 4 healthy subjects walking with various speeds, recording 64 sensor measurements including electromyogram, acceleration, and foot-pressure sensors attached on both lower limbs for predicting hip and knee joint angles. For test set of walking with arbitrary speed, our results show that our suggested method can select informative sensors while maintaining a good prediction accuracy.

  15. The Toyota Production Systems fundamental nature at selected South African organisations A learning perspective

    Directory of Open Access Journals (Sweden)

    Nortje, F. D.

    2013-05-01

    Full Text Available The Toyota Production System (TPS has been cited as being the pinnacle of continuous improvement approaches in manufacturing organisations, and many models of the TPS are well known. However, some authors question the effectiveness of established approaches, and propose Batesons theory of learning [1] to be an effective way to explain phenomena like the TPS. This paper investigates the degree to which TPS elements are found in selected South African organisations. It constructs a model of the TPS using Bateson's theory of learning as a framework. The adoption of TPS elements is investigated through multiple qualitative case studies in seven organisations. The analysis follows a clustering and cross-case approach combined with pattern matching. While elements vary in their use, the selected organisations practise the TPS substantially less than the model advocates, with the model being least practised in low volume job/batch manufacturing. Product-process differences and higher levels of the TPS model may clarify peculiar outcomes.

  16. Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Yang Sun

    2018-01-01

    Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.

  17. Selective immunotoxic lesions of basal forebrain cholinergic cells: effects on learning and memory in rats.

    Science.gov (United States)

    Baxter, Mark G; Bucci, David J; Gorman, Linda K; Wiley, Ronald G; Gallagher, Michela

    2013-10-01

    Male Long-Evans rats were given injections of either 192 IgG-saporin, an apparently selective toxin for basal forebrain cholinergic neurons (LES), or vehicle (CON) into either the medial septum and vertical limb of the diagonal band (MS/VDB) or bilaterally into the nucleus basalis magnocellularis and substantia innominata (nBM/SI). Place discrimination in the Morris water maze assessed spatial learning, and a trial-unique matching-to-place task in the water maze assessed memory for place information over varying delays. MS/VDB-LES and nBM/SI-LES rats were not impaired relative to CON rats in acquisition of the place discrimination, but were mildly impaired relative to CON rats in performance of the memory task even at the shortest delay, suggesting a nonmnemonic deficit. These results contrast with effects of less selective lesions, which have been taken to support a role for basal forebrain cholinergic neurons in learning and memory. 2013 APA, all rights reserved

  18. Reinforcement learning modulates the stability of cognitive control settings for object selection

    Directory of Open Access Journals (Sweden)

    Anthony William Sali

    2013-12-01

    Full Text Available Cognitive flexibility reflects both a trait that reliably differs between individuals and a state that can fluctuate moment-to-moment. Whether individuals can undergo persistent changes in cognitive flexibility as a result of reward learning is less understood. Here, we investigated whether reinforcing a periodic shift in an object selection strategy can make an individual more prone to switch strategies in a subsequent unrelated task. Participants completed two different choice tasks in which they selected one of four objects in an attempt to obtain a hidden reward on each trial. During a training phase, objects were defined by color. Participants received either consistent reward contingencies in which one color was more often rewarded, or contingencies in which the color that was more often rewarded changed periodically and without warning. Following the training phase, all participants completed a test phase in which reward contingencies were defined by spatial location and the location that was more often rewarded remained constant across the entire task. Those participants who received inconsistent contingencies during training continued to make more variable selections during the test phase in comparison to those who received the consistent training. Furthermore, a difference in the likelihood to switch selections on a trial-by-trial basis emerged between training groups: participants who received consistent contingencies during training were less likely to switch object selections following an unrewarded trial and more likely to repeat a selection following reward. Our findings provide evidence that the extent to which priority shifting is reinforced modulates the stability of cognitive control settings in a persistent manner, such that individuals become generally more or less prone to shifting priorities in the future.

  19. TGF-β Signaling in Dopaminergic Neurons Regulates Dendritic Growth, Excitatory-Inhibitory Synaptic Balance, and Reversal Learning

    Directory of Open Access Journals (Sweden)

    Sarah X. Luo

    2016-12-01

    Full Text Available Neural circuits involving midbrain dopaminergic (DA neurons regulate reward and goal-directed behaviors. Although local GABAergic input is known to modulate DA circuits, the mechanism that controls excitatory/inhibitory synaptic balance in DA neurons remains unclear. Here, we show that DA neurons use autocrine transforming growth factor β (TGF-β signaling to promote the growth of axons and dendrites. Surprisingly, removing TGF-β type II receptor in DA neurons also disrupts the balance in TGF-β1 expression in DA neurons and neighboring GABAergic neurons, which increases inhibitory input, reduces excitatory synaptic input, and alters phasic firing patterns in DA neurons. Mice lacking TGF-β signaling in DA neurons are hyperactive and exhibit inflexibility in relinquishing learned behaviors and re-establishing new stimulus-reward associations. These results support a role for TGF-β in regulating the delicate balance of excitatory/inhibitory synaptic input in local microcircuits involving DA and GABAergic neurons and its potential contributions to neuropsychiatric disorders.

  20. Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

    Science.gov (United States)

    Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.

    2017-12-01

    At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.

  1. Bias correction for selecting the minimal-error classifier from many machine learning models.

    Science.gov (United States)

    Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C

    2014-11-15

    Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Selected engagement factors and academic learning outcomes of undergraduate engineering students

    Science.gov (United States)

    Justice, Patricia J.

    The concept of student engagement and its relationship to successful student performance and learning outcomes has a long history in higher education (Kuh, 2007). Attention to faculty and student engagement has only recently become of interest to the engineering education community. This interest can be attributed to long-standing research by George Kuh's, National Survey of Student Engagement (NSSE) at the Indiana University Center for Postsecondary Research. In addition, research projects sponsored by the National Science Foundation, the Academic Pathway Study (APS) at the Center for the Advancement of Engineering Education (CAEE) and the Center for the Advancement of Scholarship on Engineering Education (CASEE), Measuring Student and Faculty Engagement in Engineering Education, at the National Academy of Engineering. These research studies utilized the framework and data from the Engineering Change study by the Center for the Study of Higher Education, Pennsylvania State, that evaluated the impact of the new Accreditation Board of Engineering and Technology (ABET) EC2000 "3a through k" criteria identify 11 learning outcomes expected of engineering graduates. The purpose of this study was to explore the extent selected engagement factors of 1. institution, 2. social, 3. cognitive, 4. finance, and 5. technology influence undergraduate engineering students and quality student learning outcomes. Through the descriptive statistical analysis indicates that there maybe problems in the engineering program. This researcher would have expected at least 50% of the students to fall in the Strongly Agree and Agree categories. The data indicated that the there maybe problems in the engineering program problems in the data. The problems found ranked in this order: 1). Dissatisfaction with faculty instruction methods and quality of instruction and not a clear understanding of engineering majors , 2). inadequate Engineering faculty and advisors availability especially applicable

  3. Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

    Science.gov (United States)

    Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

    2016-01-01

    Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

  4. Memory and selective learning in children with spina bifida-myelomeningocele and shunted hydrocephalus: A preliminary study

    Directory of Open Access Journals (Sweden)

    Vachha Behroze

    2005-11-01

    Full Text Available Abstract Background Selective learning is the ability to select items of relevance from among less important items. Limited evidence exists regarding the efficiency with which children with spina bifida-myelomeningocele and shunted hydrocephalus (SB/SH are able to learn information. This report describes initial data related to components of learning and metacognitive skills in children with SB/SH. Methods Twenty six children with SB/SH and 26 controls (age: 7 – 16 y with average intelligence, and monolingual English-speaking backgrounds participated in the study. Exclusion criteria for the SB/SH group were: prior history of shunt infection, history of seizure or shunt malfunction within the previous three months, prior diagnoses of attention disorders and/or clinical depression. Children were presented lists of words with equal exemplars each of two distinct semantic categories (e.g. fruits, animals, and told to make as high a score as possible by learning the words. The value of the words was designated by category membership (e.g. animals = low value; fruits = high value. The total number of words learned across three learning trials was used to determine memory span. Selective learning efficiency (SLE was computed as the efficiency with which items of greater value were selectively learned across three trials. Results Children with SB/SH did worse than controls on memory span (P Conclusion Success in school is often dependent on the ability to recall important facts selectively and ignore less important information. Children with SB/SH in our study had a poor memory span and were unable to monitor and report an efficient and workable metacognitive strategy required to remember a list of words. Preliminary findings may begin to explain our previous clinical and research findings wherein children with SB/SH often focus on extraneous details, but demonstrate difficulty remembering the main gist of a story/event.

  5. Selective suppression of autocatalytic caspase-3 driven by two-step transcriptional amplified human telomerase reverse transcriptase promoter on ovarian carcinoma growth in vitro and in mice.

    Science.gov (United States)

    Song, Yue; Xin, Xing; Xia, Zhijun; Zhai, Xingyue; Shen, Keng

    2014-07-01

    The objective of our study was to construct recombinant adenovirus (rAd) AdHTVP2G5-rev-casp3, which expresses autocatalytic caspase-3 driven by human telomerase reverse transcriptase promoter (hTERTp) with a two-step transcription amplification (TSTA) system and investigate its antitumor effects on ovarian cancer in vitro and in vivo. Fluorescent detection was used to detect EGFP expression in various cells. Cell viabilities were determined using the Cell Counting Kit-8 and flow cytometry. RT-PCR and immunoblotting assays were used to detect cellular apoptotic activities. Tumor growth and survival of tumor-bearing mice were studied. The hTERTp-TSTA system showed the strongest activity in hTERT-positive cancer cells when compared with hTERTp and cytomeglovirus promoter (CMVp). In contrast, it showed no activity in hTERT‑negative HUVECs. AdHTVP2G5‑rev-casp3 markedly suppressed the survival of AO cells in a dose-dependent modality with a viability rate of 17.8 ± 3.5% at an MOI of 70, which was significantly lower than that by AdHT-rev-casp3 and Ad-rev-casp3 (rAds which express rev-caspase-3 driven by hTERTp and CMVp, respectively). In contrast, AdHTVP2G5‑rev-casp3 induced little HUVEC death with a viability rate of 92.7 ± 5.2% at the same MOI. Additionally, AdHTVP2G5-rev-casp3 (MOI=70) caused significant apoptosis in AO cells with an apoptotic rate of 42%. The tumor growth suppression rate of AdHTVP2G5-rev-casp3 was 81.52%, significantly higher than that of AdHT-rev-casp3 (54.94%) or Ad-rev-casp3 (21.35%). AdHTVP2G5-rev-casp3 significantly improved the survival of tumor-bearing mice with little liver damage, with a mean survival of 258 ± 28 days. These results showed that AdHTVP2G5-rev-casp3 caused effective apoptosis with significant tumor selectivity, strongly suppressed tumor growth and improved mouse survival with little liver toxicity. It can be a potent therapeutic agent for tumor targeted treatment of ovarian cancer.

  6. Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill.

    Science.gov (United States)

    de Almeida, Márcia R; Ruedell, Carolina M; Ricachenevsky, Felipe K; Sperotto, Raul A; Pasquali, Giancarlo; Fett-Neto, Arthur G

    2010-09-20

    Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings. By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs identified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm. Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression

  7. Effects of gender and role selection in cooperative learning groups on science inquiry achievement

    Science.gov (United States)

    Affhalter, Maria Geralyn

    An action research project using science inquiry labs and cooperative learning groups examined the effects of same-gender and co-educational classrooms on science achievement and teacher-assigned or self-selected group roles on students' role preferences. Fifty-nine seventh grade students from a small rural school district participated in two inquiry labs in co-educational classrooms or in an all-female classroom, as determined by parents at the beginning of the academic year. Students were assigned to the same cooperative groups for the duration of the study. Pretests and posttests were administered for each inquiry-based science lab. Posttest assessments included questions for student reflection on role assignment and role preference. Instruction did not vary and a female science teacher taught all class sections. The same-gender classroom and co-ed classrooms produced similar science achievement scores on posttests. Students' cooperative group roles, whether teacher-assigned or self-selected, produced similar science achievement scores on posttests. Male and female students shared equally in favorable and unfavorable reactions to their group roles during the science inquiry labs. Reflections on the selection of the leader role revealed a need for females in co-ed groups to be "in charge". When reflecting on her favorite role of leader, one female student in a co-ed group stated, "I like to have people actually listen to me".

  8. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sang Hyun [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong, E-mail: yzgao@cs.unc.edu [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Yinghuan, E-mail: syh@nju.edu.cn [State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-11-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  9. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    International Nuclear Information System (INIS)

    Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

    2014-01-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  10. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

    Science.gov (United States)

    Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

    2014-11-01

    Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency

  11. SSP-002392, a new 5-HT4 receptor agonist, dose-dependently reverses scopolamine-induced learning and memory impairments in C57Bl/6 mice.

    Science.gov (United States)

    Lo, Adrian C; De Maeyer, Joris H; Vermaercke, Ben; Callaerts-Vegh, Zsuzsanna; Schuurkes, Jan A J; D'Hooge, Rudi

    2014-10-01

    5-HT4 receptors (5-HT4R) are suggested to affect learning and memory processes. Earlier studies have shown that animals treated with 5-HT4R agonists, often with limited selectivity, show improved learning and memory with retention memory often being assessed immediately after or within 24 h after the last training session. In this study, we characterized the effect of pre-training treatment with the selective 5-HT4R agonist SSP-002392 on memory acquisition and the associated long-term memory retrieval in animal models of impaired cognition. Pre-training treatment with SSP-002392 (0.3 mg/kg, 1.5 mg/kg and 7.5 mg/kg p.o.) dose-dependently inhibited the cognitive deficits induced by scopolamine (0.5 mg/kg s.c.) in two different behavioral tasks: passive avoidance and Morris water maze. In the Morris water maze, spatial learning was significantly improved after treatment with SSP-002392 translating in an accelerated and more efficient localization of the hidden platform compared to scopolamine-treated controls. Moreover, retention memory was assessed 24 h (passive avoidance) and 72 h (Morris water maze) after the last training session of cognitive-impaired animals and this was significantly improved in animals treated with SSP-002392 prior to the training sessions. Furthermore, the effects of SSP-002392 were comparable to galanthamine hydrobromide. We conclude that SSP-002392 has potential as a memory-enhancing compound. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Selective increase of auditory cortico-striatal coherence during auditory-cued Go/NoGo discrimination learning.

    Directory of Open Access Journals (Sweden)

    Andreas L. Schulz

    2016-01-01

    Full Text Available Goal directed behavior and associated learning processes are tightly linked to neuronal activity in the ventral striatum. Mechanisms that integrate task relevant sensory information into striatal processing during decision making and learning are implicitly assumed in current reinforcementmodels, yet they are still weakly understood. To identify the functional activation of cortico-striatal subpopulations of connections during auditory discrimination learning, we trained Mongolian gerbils in a two-way active avoidance task in a shuttlebox to discriminate between falling and rising frequency modulated tones with identical spectral properties. We assessed functional coupling by analyzing the field-field coherence between the auditory cortex and the ventral striatum of animals performing the task. During the course of training, we observed a selective increase of functionalcoupling during Go-stimulus presentations. These results suggest that the auditory cortex functionally interacts with the ventral striatum during auditory learning and that the strengthening of these functional connections is selectively goal-directed.

  13. Selective Use of the Mother Tongue to Enhance Students’ English Learning Processes...Beyond the Same Assumptions

    Directory of Open Access Journals (Sweden)

    Luis Fernando Cuartas Alvarez

    2014-04-01

    Full Text Available This article reports the results of an action-research project that examines enhancing students’ English learning processes through the selective use of their mother tongues with the aim of overcoming their reluctant attitudes toward learning English in the classroom. This study involves forty ninth-graders from an all-girls public school in Medellin, Colombia. The data gathered included field notes, questionnaires, and participants’ focus group interviews. The findings show that the mother tongue plays an important role in students’ English learning processes by fostering students’ affective, motivational, cognitive, and attitudinal aspects. Thus, the mother tongue serves as the foothold for further advances in learning English when used selectively.

  14. Cognitive communication and cooperative hetnet coexistence selected advances on spectrum sensing, learning, and security approaches

    CERN Document Server

    Bader, Faouzi

    2014-01-01

    This book, written by experts from universities and major industrial research laboratories, is devoted to the very hot topic of cognitive radio and networking for cooperative coexistence of heterogeneous wireless networks. Selected highly relevant advanced research is presented on spectrum sensing and progress toward the realization of accurate radio environment mapping, biomimetic learning for self-organizing networks, security threats (with a special focus on primary user emulation attack), and cognition as a tool for green next-generation networks. The research activities covered include work undertaken within the framework of the European COST Action IC0902, which is geared towards the definition of a European platform for cognitive radio and networks. Communications engineers, R&D engineers, researchers, and students will all benefit from this complete reference on recent advances in wireless communications and the design and implementation of cognitive radio systems and networks.

  15. Identification of learning and memory genes in canine; promoter investigation and determining the selective pressure.

    Science.gov (United States)

    Seifi Moroudi, Reihane; Masoudi, Ali Akbar; Vaez Torshizi, Rasoul; Zandi, Mohammad

    2014-12-01

    One of the important behaviors of dogs is trainability which is affected by learning and memory genes. These kinds of the genes have not yet been identified in dogs. In the current research, these genes were found in animal models by mining the biological data and scientific literatures. The proteins of these genes were obtained from the UniProt database in dogs and humans. Not all homologous proteins perform similar functions, thus comparison of these proteins was studied in terms of protein families, domains, biological processes, molecular functions, and cellular location of metabolic pathways in Interpro, KEGG, Quick Go and Psort databases. The results showed that some of these proteins have the same performance in the rat or mouse, dog, and human. It is anticipated that the protein of these genes may be effective in learning and memory in dogs. Then, the expression pattern of the recognized genes was investigated in the dog hippocampus using the existing information in the GEO profile. The results showed that BDNF, TAC1 and CCK genes are expressed in the dog hippocampus, therefore, these genes could be strong candidates associated with learning and memory in dogs. Subsequently, due to the importance of the promoter regions in gene function, this region was investigated in the above genes. Analysis of the promoter indicated that the HNF-4 site of BDNF gene and the transcription start site of CCK gene is exposed to methylation. Phylogenetic analysis of protein sequences of these genes showed high similarity in each of these three genes among the studied species. The dN/dS ratio for BDNF, TAC1 and CCK genes indicates a purifying selection during the evolution of the genes.

  16. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach

    Directory of Open Access Journals (Sweden)

    Niu AQ

    2016-07-01

    Full Text Available Ai-qin Niu,1 Liang-jun Xie,2 Hui Wang,1 Bing Zhu,1 Sheng-qi Wang3 1Department of Gynecology, the First People’s Hospital of Shangqiu, Shangqiu, Henan, People’s Republic of China; 2Department of Image Diagnoses, the Third Hospital of Jinan, Jinan, Shandong, People’s Republic of China; 3Department of Mammary Disease, Guangdong Provincial Hospital of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China Background: Estrogen receptors (ERs are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods: Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML methods. Results: The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior

  17. Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

    Science.gov (United States)

    Wang, Xiao; Li, Guo-Zheng

    2013-03-12

    Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

  18. Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

    Directory of Open Access Journals (Sweden)

    Dongrui Wu

    Full Text Available Brain-computer interaction (BCI and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL, active class selection (ACS, and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.

  19. Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

    Science.gov (United States)

    Wu, Dongrui; Lance, Brent J; Parsons, Thomas D

    2013-01-01

    Brain-computer interaction (BCI) and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL), active class selection (ACS), and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.

  20. Parental prey selection affects risk-taking behaviour and spatial learning in avian offspring.

    Science.gov (United States)

    Arnold, Kathryn E; Ramsay, Scot L; Donaldson, Christine; Adam, Aileen

    2007-10-22

    Early nutrition shapes life history. Parents should, therefore, provide a diet that will optimize the nutrient intake of their offspring. In a number of passerines, there is an often observed, but unexplained, peak in spider provisioning during chick development. We show that the proportion of spiders in the diet of nestling blue tits, Cyanistes caeruleus, varies significantly with the age of chicks but is unrelated to the timing of breeding or spider availability. Moreover, this parental prey selection supplies nestlings with high levels of taurine particularly at younger ages. This amino acid is known to be both vital and limiting for mammalian development and consequently found in high concentrations in placenta and milk. Based on the known roles of taurine in mammalian brain development and function, we then asked whether by supplying taurine-rich spiders, avian parents influence the stress responsiveness and cognitive function of their offspring. To test this, we provided wild blue tit nestlings with either a taurine supplement or control treatment once daily from the ages of 2-14 days. Then pairs of size- and sex-matched siblings were brought into captivity for behavioural testing. We found that juveniles that had received additional taurine as neonates took significantly greater risks when investigating novel objects than controls. Taurine birds were also more successful at a spatial learning task than controls. Additionally, those individuals that succeeded at a spatial learning task had shown intermediate levels of risk taking. Non-learners were generally very risk-averse controls. Early diet therefore has downstream impacts on behavioural characteristics that could affect fitness via foraging and competitive performance. Fine-scale prey selection is a mechanism by which parents can manipulate the behavioural phenotype of offspring.

  1. Selection and Use of Online Learning Resources by First-Year Medical Students: Cross-Sectional Study.

    Science.gov (United States)

    Judd, Terry; Elliott, Kristine

    2017-10-02

    Medical students have access to a wide range of learning resources, many of which have been specifically developed for or identified and recommended to them by curriculum developers or teaching staff. There is an expectation that students will access and use these resources to support their self-directed learning. However, medical educators lack detailed and reliable data about which of these resources students use to support their learning and how this use relates to key learning events or activities. The purpose of this study was to comprehensively document first-year medical student selection and use of online learning resources to support their bioscience learning within a case-based curriculum and assess these data in relation to our expectations of student learning resource requirements and use. Study data were drawn from 2 sources: a survey of student learning resource selection and use (2013 cohort; n=326) and access logs from the medical school learning platform (2012 cohort; n=337). The paper-based survey, which was distributed to all first-year students, was designed to assess the frequency and types of online learning resources accessed by students and included items about their perceptions of the usefulness, quality, and reliability of various resource types and sources. Of 237 surveys returned, 118 complete responses were analyzed (36.2% response rate). Usage logs from the learning platform for an entire semester were processed to provide estimates of first-year student resource use on an individual and cohort-wide basis according to method of access, resource type, and learning event. According to the survey data, students accessed learning resources via the learning platform several times per week on average, slightly more often than they did for resources from other online sources. Google and Wikipedia were the most frequently used nonuniversity sites, while scholarly information sites (eg, online journals and scholarly databases) were accessed

  2. Do children go for the nice guys? The influence of speaker benevolence and certainty on selective word learning.

    Science.gov (United States)

    Bergstra, Myrthe; DE Mulder, Hannah N M; Coopmans, Peter

    2018-04-06

    This study investigated how speaker certainty (a rational cue) and speaker benevolence (an emotional cue) influence children's willingness to learn words in a selective learning paradigm. In two experiments four- to six-year-olds learnt novel labels from two speakers and, after a week, their memory for these labels was reassessed. Results demonstrated that children retained the label-object pairings for at least a week. Furthermore, children preferred to learn from certain over uncertain speakers, but they had no significant preference for nice over nasty speakers. When the cues were combined, children followed certain speakers, even if they were nasty. However, children did prefer to learn from nice and certain speakers over nasty and certain speakers. These results suggest that rational cues regarding a speaker's linguistic competence trump emotional cues regarding a speaker's affective status in word learning. However, emotional cues were found to have a subtle influence on this process.

  3. Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

    Directory of Open Access Journals (Sweden)

    Aiming Liu

    2017-11-01

    Full Text Available Motor Imagery (MI electroencephalography (EEG is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP and local characteristic-scale decomposition (LCD algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems.

  4. Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

    Science.gov (United States)

    Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

    2017-11-08

    Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

  5. Object learning improves feature extraction but does not improve feature selection.

    Directory of Open Access Journals (Sweden)

    Linus Holm

    Full Text Available A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1 select more informative image locations upon which to fixate their eyes, or 2 extract more information from a given eye fixation. To test these possibilities, we had observers localize fragmented objects embedded in dense displays of random contour fragments. Eight participants searched for objects in 600 images while their eye movements were recorded in three daily sessions. Performance improved as subjects trained with the objects: The number of fixations required to find an object decreased by 64% across the 3 sessions. An ideal observer model that included measures of fragment confusability was used to calculate the information available from a single fixation. Comparing human performance to the model suggested that across sessions information extraction at each eye fixation increased markedly, by an amount roughly equal to the extra information that would be extracted following a 100% increase in functional field of view. Selection of fixation locations, on the other hand, did not improve with practice.

  6. A Comparison of Participation Patterns in Selected Formal, Non-Formal, and Informal Online Learning Environments

    Science.gov (United States)

    Schwier, Richard A.; Seaton, J. X.

    2013-01-01

    Does learner participation vary depending on the learning context? Are there characteristic features of participation evident in formal, non-formal, and informal online learning environments? Six online learning environments were chosen as epitomes of formal, non-formal, and informal learning contexts and compared. Transcripts of online…

  7. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

    Science.gov (United States)

    Niu, Ai-Qin; Xie, Liang-Jun; Wang, Hui; Zhu, Bing; Wang, Sheng-Qi

    2016-01-01

    Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML) methods. The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic) curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists.

  8. Redox Cycling Realized in Paper-Based Biochemical Sensor for Selective Detection of Reversible Redox Molecules Without Micro/Nano Fabrication Process.

    Science.gov (United States)

    Yamamoto, So; Uno, Shigeyasu

    2018-02-28

    This paper describes a paper-based biochemical sensor that realizes redox cycling with close interelectrode distance. Two electrodes, the generator and collector electrodes, can detect steady-state oxidation and reduction currents when suitable potential is held at each electrode. The sensor has two gold plates on both sides of a piece of chromatography paper and defines the interelectrode distance by the thickness of the paper (180 μm) without any micro-fabrication processes. Our proposed sensor geometry has successfully exhibited signatures of redox cycling. As a result, the concentration of ferrocyanide as reversible redox molecules was successfully quantified under the interference by ascorbic acid as a strong irreversible reducing agent. This was possible because the ascorbic acids are completely consumed by the irreversible reaction, while maintaining redox cycling of reversible ferrocyanide. This suggests that a sensor based on the redox cycling method will be suitable for detecting target molecules at low concentration.

  9. Dopamine selectively remediates 'model-based' reward learning: a computational approach.

    Science.gov (United States)

    Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

    2016-02-01

    Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  10. Challenges of Learning English in Australia towards Students Coming from Selected Southeast Asian Countries: Vietnam, Thailand and Indonesia

    Science.gov (United States)

    Nguyen, Cao Thanh

    2011-01-01

    The paper will explore the challenges students from selected South East Asian countries (Vietnam, Thailand and Indonesia) face while studying English in Australia before entering into Australian University courses. These students must contend not only with different styles of teaching and learning, but also with the challenge of adapting to a new…

  11. The Relationship Between Selected Subtests of the Detroit Tests of Learning Aptitude and Second Grade Reading Achievement.

    Science.gov (United States)

    Sherwood, Charles; Chambless, Martha

    Relationships between reading achievement and perceptual skills as measured by selected subtests of the Detroit Tests of Learning Aptitude were investigated in a sample of 73 second graders. Verbal opposites, visual memory for designs, and visual attention span for letters were significantly correlated with both word meaning and vocabulary…

  12. Selected Lessons Learned through the ISS Design, Development, Assembly, and Operations: Applicability to International Cooperation for Standardization

    Science.gov (United States)

    Hirsch, David B.

    2009-01-01

    This slide presentation reviews selected lessons that were learned during the design, development, assembly and operation of the International Space Station. The critical importance of standards and common interfaces is emphasized to create a common operation environment that can lead to flexibility and adaptability.

  13. Reversible Statistics

    DEFF Research Database (Denmark)

    Tryggestad, Kjell

    2004-01-01

    The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit...... in different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved...

  14. Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

    Science.gov (United States)

    Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

    2018-01-01

    Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

  15. Using Selective Redundancy and Testing to Optimize Learning from Multimedia Lessons

    OpenAIRE

    Yue, Carole Leigh

    2014-01-01

    Multimedia learning refers to learning from a combination of words and images. In the present dissertation, a multimedia lesson is defined as an animated, narrated educational video that depicts a scientific process--a format of instructional material becoming increasingly common in online, hybrid, and traditional classrooms. The overarching goal of the present research was to investigate how to optimize learning from multimedia lessons using two related theories of multimedia learning (the...

  16. Utilization of Smartphones in Science Teaching and Learning in Selected Universities in Ghana

    Science.gov (United States)

    Twum, Rosemary

    2017-01-01

    This study was designed to examine the use of mobile phone, a widespread technology, and determined how this technology influences science students' learning. The study intended to examine the use of smartphones in science teaching and learning and propose of model in the use of smartphones for teaching and learning. The research design employed…

  17. Greeting You Online: Selecting Web-Based Conferencing Tools for Instruction in E-Learning Mode

    Science.gov (United States)

    Li, Judy

    2014-01-01

    Academic distance learning programs have gained popularity and added to the demand for online library services. Librarians are now conducting instruction for distance learning students beyond their traditional work. Technology advancements have enhanced the delivery mode in distance learning across academic disciplines. Online conference tools…

  18. Neuropsychological characteristics of selective attention in children with nonverbal learning disabilities

    Institute of Scientific and Technical Information of China (English)

    静进; 王庆雄; 杨斌让; 陈学彬

    2004-01-01

    Background Children with nonverbal learning disabilities (NLD) usually manifest defective attention function. This study sought to investigate the neuropsychological characteristics of selective attention, such as attention control, working memory, and attention persistence of the frontal lobe in children with NLD. Methods Using the auditory detection test (ADT), Wisconsin card sorting test (WCST), and C-WISC, 27 children with NLD and 33 normal children in the control group were tested, and the results of C-WISC subtests were analyzed with factor analysis. Results Compared with the control group, the correct response rate in the auditory detection test in the NLD group was much lower (P<0.01), and the number of incorrect responses was much higher (P<0.01); NLD children also scored lower in WCST categories achieved (CA) and perseverative errors (PE) (P<0.05). Factor analysis showed that perceptual organization (PO) related to visual space and freedom from distractibility (FD) relating to attention persistence in the NLD group were obviously lower than in the control group (P<0.01). Conclusions Children with NLD have attention control disorder and working memory disorder mainly in the frontal lobe. We believe that the disorder is particularly prominent in the right frontal lobe.

  19. Learning to selectively attend from context-specific attentional histories: A demonstration and some constraints.

    Science.gov (United States)

    Crump, Matthew J C

    2016-03-01

    Multiple lines of evidence from the attention and performance literature show that attention filtering can be controlled by higher level voluntary processes and lower-level cue-driven processes (for recent reviews see Bugg, 2012; Bugg & Crump, 2012; Egner, 2008). The experiments were designed to test a general hypothesis that cue-driven control learns from context-specific histories of prior acts of selective attention. Several web-based flanker studies were conducted via Amazon Mechanical Turk. Attention filtering demands were induced by a secondary one-back memory task after each trial prompting recall of the last target or distractor letter. Blocking recall demands produced larger flanker effects for the distractor than target recall conditions. Mixing recall demands and associating them with particular stimulus-cues (location, colour, letter, and font) sometimes showed rapid, contextual control of flanker interference, and sometimes did not. The results show that subtle methodological parameters can influence whether or not contextual control is observed. More generally, the results show that contextual control phenomena can be influenced by other sources of control, including other cue-driven sources competing for control. (c) 2016 APA, all rights reserved).

  20. High Potency of Indolyl Aryl Sulfone Nonnucleoside Inhibitors towards Drug-Resistant Human Immunodeficiency Virus Type 1 Reverse Transcriptase Mutants Is Due to Selective Targeting of Different Mechanistic Forms of the Enzyme

    Science.gov (United States)

    Cancio, Reynel; Silvestri, Romano; Ragno, Rino; Artico, Marino; De Martino, Gabriella; La Regina, Giuseppe; Crespan, Emmanuele; Zanoli, Samantha; Hübscher, Ulrich; Spadari, Silvio; Maga, Giovanni

    2005-01-01

    Indolyl aryl sulfone (IAS) nonnucleoside inhibitors have been shown to potently inhibit the growth of wild-type and drug-resistant human immunodeficiency virus type 1 (HIV-1), but their exact mechanism of action has not been elucidated yet. Here, we describe the mechanism of inhibition of HIV-1 reverse transcriptase (RT) by selected IAS derivatives. Our results showed that, depending on the substitutions introduced in the IAS common pharmacophore, these compounds can be made selective for different enzyme-substrate complexes. Moreover, we showed that the molecular basis for this selectivity was a different association rate of the drug to a particular enzymatic form along the reaction pathway. By comparing the activities of the different compounds against wild-type RT and the nonnucleoside reverse transcriptase inhibitor-resistant mutant Lys103Asn, it was possible to hypothesize, on the basis of their mechanism of action, a rationale for the design of drugs which could overcome the steric barrier imposed by the Lys103Asn mutation. PMID:16251294

  1. Local-learning-based neuron selection for grasping gesture prediction in motor brain machine interfaces

    Science.gov (United States)

    Xu, Kai; Wang, Yiwen; Wang, Yueming; Wang, Fang; Hao, Yaoyao; Zhang, Shaomin; Zhang, Qiaosheng; Chen, Weidong; Zheng, Xiaoxiang

    2013-04-01

    Objective. The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron selection for the gesture prediction in a reaching and grasping task. Approach. Nonlinear neural activities are decomposed into a set of linear ones in a weighted feature space. A margin is defined to measure the distance between inter-class and intra-class neural patterns. The weights, reflecting the importance of neurons, are obtained by minimizing a margin-based exponential error function. To find the most dominant neurons in the task, 1-norm regularization is introduced to the objective function for sparse weights, where near-zero weights indicate irrelevant neurons. Main results. The signals of only 10 neurons out of 70 selected by the proposed method could achieve over 95% of the full recording's decoding accuracy of gesture predictions, no matter which different decoding methods are used (support vector machine and K-nearest neighbor). The temporal activities of the selected neurons show visually distinguishable patterns associated with various hand states. Compared with other algorithms, the proposed method can better eliminate the irrelevant neurons with near-zero weights and provides the important neuron subset with the best decoding performance in statistics. The weights of important neurons converge usually within 10-20 iterations. In addition, we study the temporal and spatial variation of neuron importance along a period of one and a half months in the same task. A high decoding performance can be maintained by updating the neuron subset. Significance. The proposed algorithm effectively ascertains the neuronal importance without assuming any coding model and provides a high performance with different

  2. The use of EMG biofeedback for learning of selective activation of intra-muscular parts within the serratus anterior muscle

    DEFF Research Database (Denmark)

    Holtermann, A; Mork, P J; Andersen, L L

    2010-01-01

    the serratus anterior with visual EMG biofeedback, while the activity of four parts of the serratus anterior and four parts of the trapezius muscle was recorded. One subject was able to selectively activate both the upper and the lower serratus anterior respectively. Moreover, three subjects managed...... to selectively activate the lower serratus anterior, and two subjects learned to selectively activate the upper serratus anterior. During selective activation of the lower serratus anterior, the activity of this muscle part was 14.4+/-10.3 times higher than the upper serratus anterior activity (P....05). The corresponding ratio for selective upper serratus vs. lower serratus anterior activity was 6.4+/-1.7 (Ptimes higher synergistic activity of the lower trapezius compared with the upper trapezius (P

  3. The Relationship Between the Learning Style Perceptual Preferences of Urban Fourth Grade Children and the Acquisition of Selected Physical Science Concepts Through Learning Cycle Instructional Methodology.

    Science.gov (United States)

    Adams, Kenneth Mark

    The purpose of this research was to investigate the relationship between the learning style perceptual preferences of fourth grade urban students and the attainment of selected physical science concepts for three simple machines as taught using learning cycle methodology. The sample included all fourth grade children from one urban elementary school (N = 91). The research design followed a quasi-experimental format with a single group, equivalent teacher demonstration and student investigation materials, and identical learning cycle instructional treatment. All subjects completed the Understanding Simple Machines Test (USMT) prior to instructional treatment, and at the conclusion of treatment to measure student concept attainment related to the pendulum, the lever and fulcrum, and the inclined plane. USMT pre and post-test scores, California Achievement Test (CAT-5) percentile scores, and Learning Style Inventory (LSI) standard scores for four perceptual elements for each subject were held in a double blind until completion of the USMT post-test. The hypothesis tested in this study was: Learning style perceptual preferences of fourth grade students as measured by the Dunn, Dunn, and Price Learning Style Inventory (LSI) are significant predictors of success in the acquisition of physical science concepts taught through use of the learning cycle. Analysis of pre and post USMT scores, 18.18 and 30.20 respectively, yielded a significant mean gain of +12.02. A controlled stepwise regression was employed to identify significant predictors of success on the USMT post-test from among USMT pre-test, four CAT-5 percentile scores, and four LSI perceptual standard scores. The CAT -5 Total Math and Total Reading accounted for 64.06% of the variance in the USMT post-test score. The only perceptual element to act as a significant predictor was the Kinesthetic standard score, accounting for 1.72% of the variance. The study revealed that learning cycle instruction does not appear

  4. Oxytocin selectively facilitates learning with social feedback and increases activity and functional connectivity in emotional memory and reward processing regions.

    Science.gov (United States)

    Hu, Jiehui; Qi, Song; Becker, Benjamin; Luo, Lizhu; Gao, Shan; Gong, Qiyong; Hurlemann, René; Kendrick, Keith M

    2015-06-01

    In male Caucasian subjects, learning is facilitated by receipt of social compared with non-social feedback, and the neuropeptide oxytocin (OXT) facilitates this effect. In this study, we have first shown a cultural difference in that male Chinese subjects actually perform significantly worse in the same reinforcement associated learning task with social (emotional faces) compared with non-social feedback. Nevertheless, in two independent double-blind placebo (PLC) controlled between-subject design experiments we found OXT still selectively facilitated learning with social feedback. Similar to Caucasian subjects this OXT effect was strongest with feedback using female rather than male faces. One experiment performed in conjunction with functional magnetic resonance imaging showed that during the response, but not feedback phase of the task, OXT selectively increased activity in the amygdala, hippocampus, parahippocampal gyrus and putamen during the social feedback condition, and functional connectivity between the amygdala and insula and caudate. Therefore, OXT may be increasing the salience and reward value of anticipated social feedback. In the PLC group, response times and state anxiety scores during social feedback were associated with signal changes in these same regions but not in the OXT group. OXT may therefore have also facilitated learning by reducing anxiety in the social feedback condition. Overall our results provide the first evidence for cultural differences in social facilitation of learning per se, but a similar selective enhancement of learning with social feedback under OXT. This effect of OXT may be associated with enhanced responses and functional connectivity in emotional memory and reward processing regions. © 2015 Wiley Periodicals, Inc.

  5. GluN2C/GluN2D subunit-selective NMDA receptor potentiator CIQ reverses MK-801-induced impairment in prepulse inhibition and working memory in Y-maze test in mice

    Science.gov (United States)

    Suryavanshi, P S; Ugale, R R; Yilmazer-Hanke, D; Stairs, D J; Dravid, S M

    2014-01-01

    Background and Purpose Despite ample evidence supporting the N-methyl-d-aspartate receptor (NMDAR) hypofunction hypothesis of schizophrenia, progress in the development of effective therapeutics based on this hypothesis has been limited. Facilitation of NMDA receptor function by co-agonists (d-serine or glycine) only partially alleviates the symptoms in schizophrenia; other means to facilitate NMDA receptors are required. NMDA receptor sub-types differ in their subunit composition, with varied GluN2 subunits (GluN2A-GluN2D) imparting different physiological, biochemical and pharmacological properties. CIQ is a positive allosteric modulator that is selective for GluN2C/GluN2D-containing NMDA receptors (Mullasseril et al.). Experimental Approach The effect of systemic administration of CIQ was tested on impairment in prepulse inhibition (PPI), hyperlocomotion and stereotypy induced by i.p. administration of MK-801 and methamphetamine. The effect of CIQ was also tested on MK-801-induced impairment in working memory in Y-maze spontaneous alternation test. Key Results We found that systemic administration of CIQ (20 mg·kg−1, i.p.) in mice reversed MK-801 (0.15 mg·kg−1, i.p.)-induced, but not methamphetamine (3 mg·kg−1, i.p.)-induced, deficit in PPI. MK-801 increased the startle amplitude to pulse alone, which was not reversed by CIQ. In contrast, methamphetamine reduced the startle amplitude to pulse alone, which was reversed by CIQ. CIQ also partially attenuated MK-801- and methamphetamine-induced hyperlocomotion and stereotyped behaviours. Additionally, CIQ reversed the MK-801-induced working memory deficit in spontaneous alternation in a Y-maze. Conclusion and Implications Together, these results suggest that facilitation of GluN2C/GluN2D-containing receptors may serve as an important therapeutic strategy for treating positive and cognitive symptoms in schizophrenia. PMID:24236947

  6. Highly selective spectrophotometric determination of trace amounts of vanadium(V) with 2-(8-quinolylazo)-5-N,N-diethylaminophenol by reversed-phase partition liquid chromatography

    International Nuclear Information System (INIS)

    Hoshino, Hitoshi; Yotsuyanagi, Takao

    1982-01-01

    A novel reversed-phase partition liquid chromatography-photometric detection system for the determination of trace amounts of vanadium is described. A strongly colored vanadium(V)-2-(8-quinolylazo)-5-N,N-diethylaminophenolato chelate is separated on a μBondapak-CN column using an aqueous acetonitrile mobile phase and is detected at 540 nm(0.02 absorbance unit full-scale). Because the other common cations give no resolved peaks on the chromatogram under the conditions, the determination of vanadium at 5 x 10 -8 to 1 x 10 -6 mol dm -3 level is free from their interferences in case of the total concentration of such cations less than 5 x 10 -5 mol dm -3 (author)

  7. A Combined Antenna Arrays and Reverse-Link Synchronous DS-CDMA System over Frequency-Selective Fading Channels with Power Control Error

    Directory of Open Access Journals (Sweden)

    Yong-Seok Kim

    2004-08-01

    Full Text Available An improved antenna array (AA has been introduced, in which reverse-link synchronous transmission technique (RLSTT is incorporated to effectively make better an estimation of covariance matrices at a beamformer-RAKE receiver. While RLSTT is effective in the first finger at the RAKE receiver in order to reject multiple-access interference (MAI, the beamformer estimates the desired user's complex weights, enhancing its signal and reducing cochannel interference (CCI from the other directions. In this work, it is attempted to provide a comprehensive analysis of user capacity which reflects several important factors such as the shape of multipath intensity profile (MIP, the number of antennas, and power control error (PCE. Theoretical analysis, confirmed by the simulations, demonstrates that the orthogonality provided by employing RLSTT along with AA may make the DS-CDMA system insensitive to the PCE even with fewer numbers of antennas.

  8. Reversible and Selective Encapsulation of Dextromethorphan and β-Estradiol Using an Asymmetric Molecular Capsule Assembled via the Weak-Link Approach.

    Science.gov (United States)

    Mendez-Arroyo, Jose; d'Aquino, Andrea I; Chinen, Alyssa B; Manraj, Yashin D; Mirkin, Chad A

    2017-02-01

    An allosterically regulated, asymmetric receptor featuring a binding cavity large enough to accommodate three-dimensional pharmaceutical guest molecules as opposed to planar, rigid aromatics, was synthesized via the Weak-Link Approach. This architecture is capable of switching between an expanded, flexible "open" configuration and a collapsed, rigid "closed" one. The structure of the molecular receptor can be completely modulated in situ through the use of simple ionic effectors, which reversibly control the coordination state of the Pt(II) metal hinges to open and close the molecular receptor. The substantial change in binding cavity size and electrostatic charge between the two configurations is used to explore the capture and release of two guest molecules, dextromethorphan and β-estradiol, which are widely found as pollutants in groundwater.

  9. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

    Science.gov (United States)

    Janowczyk, Andrew; Madabhushi, Anant

    2016-01-01

    Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classification (e.g., cancerous vs. non-cancerous). Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a) selecting appropriate magnification, (b) managing errors in annotations in the training (or learning) dataset, and (c) identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i) DL experts with minimal digital histology experience, and (ii) DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Specifically, in this tutorial on DL for DP image

  10. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

    Directory of Open Access Journals (Sweden)

    Andrew Janowczyk

    2016-01-01

    Full Text Available Background: Deep learning (DL is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP. The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events, segmentation (e.g., nuclei, and tissue classification (e.g., cancerous vs. non-cancerous. Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a selecting appropriate magnification, (b managing errors in annotations in the training (or learning dataset, and (c identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i DL experts with minimal digital histology experience, and (ii DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. Aims: This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Results : Specifically, in

  11. Poly(4-vinylpyridine) as a reagent with silanol-masking effect for silica and its specific selectivity for PAHs and dinitropyrenes in a reversed phase

    International Nuclear Information System (INIS)

    Ihara, Hirotaka; Fukui, Megumi; Mimaki, Takamasa; Shundo, Atsuomi; Dong, Wei; Derakhshan, Mahnaz; Sakurai, Toshihiko; Takafuji, Makoto; Nagaoka, Shoji

    2005-01-01

    This paper demonstrates that poly(4-vinylpyridine) is applicable as an effective masking reagent for silica to reduce undesirable side effects due to silanol groups. It also shows that this chemical modification brings about unique retention behaviors absolutely different from conventional ODS, which appear in molecular-shape selectivity for polycyclic aromatic hydrocarbons and in selectivity for position isomerism, especially for electron-withdrawing substitution compounds. Separation of 1,6- and 1,8-dinirtopyrenes as carcinogens is also described

  12. Differential investment in pre- vs. post-copulatory sexual selection reinforces a cross-continental reversal of sexual size dimorphism in Sepsis punctum (Diptera: Sepsidae).

    Science.gov (United States)

    Puniamoorthy, Nalini; Blanckenhorn, W U; Schäfer, M A

    2012-11-01

    Theory predicts that males have a limited amount of resources to invest in reproduction, suggesting a trade-off between traits that enhance mate acquisition and those that enhance fertilization success. Here, we investigate the relationship between pre- and post-copulatory investment by comparing the mating behaviour and reproductive morphology of four European and five North American populations of the dung fly Sepsis punctum (Diptera) that display a reversal of sexual size dimorphism (SSD). We show that the geographic reversal in SSD between the continents (male biased in Europe, female biased in North America) is accompanied by differential investment in pre- vs. post-copulatory traits. We find higher remating rates in European populations, where larger males acquire more matings and consequently have evolved relatively larger testes and steeper hyper-allometry with body size. American populations, in sharp contrast, display much reduced, if any, effect of body size on those traits. Instead, North American males demonstrate an increased investment in mate acquisition prior to copulation, with more mounting attempts and a distinctive abdominal courtship display that is completely absent in Europe. When controlling for body size, relative female spermathecal size is similar on both continents, so we find no direct evidence for the co-evolution of male and female internal reproductive morphology. By comparing allopatric populations of the same species that apparently have evolved different mating systems and consequently SSD, we thus indirectly demonstrate differential investment in pre- vs. post-copulatory mechanisms increasing reproductive success. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

  13. Natural variation in learning and memory dynamics studied by artificial selection on learning rate in parasitic wasps

    NARCIS (Netherlands)

    Berg, van den M.; Duivenvoorde, L.; Wang, G.; Tribuhl, S.V.; Bukovinszky, T.; Vet, L.E.M.; Dicke, M.; Smid, H.M.

    2011-01-01

    Although the neural and genetic pathways underlying learning and memory formation seem strikingly similar among species of distant animal phyla, several more subtle inter- and intraspecific differences become evident from studies on model organisms. The true significance of such variation can only

  14. A Fuzzy Logic-Based Quality Function Deployment for Selection of E-Learning Provider

    Science.gov (United States)

    Kazancoglu, Yigit; Aksoy, Murat

    2011-01-01

    According to the Internet World Stats (2010), the growth rate of internet usage in the world is 444.8 % from 2000 to 2010. Since the number of internet users is rapidly increasing with each passed year, e-learning is often identified with web-based learning. The institutions, which deliver e-learning service via the use of computer and internet,…

  15. Use of Physics Innovative Device for Improving Students‟ Motivation and Performance in Learning Selected Concepts in Physics

    Directory of Open Access Journals (Sweden)

    Virginia Songalia Sobremisana

    2017-11-01

    Full Text Available This research was focused on the development and evaluation of physics innovative device in enhancing students’ motivation and performance in learning selected concepts in physics. The Physics innovative device was developed based upon research on student difficulties in learning relevant concepts in physics and their attitudes toward the subject. Basic concepts in mechanics were also made as baselines in the development of the locally-produced Physics innovative learning device. Such learning devices are valuable resources when used either in lecture or demonstration classes. The developmental, descriptive and quasi-experimental research methods were utilized to determine the effectiveness, in terms of motivation and performance, of the innovative device in Physics. The instruments used for the data collection were the Instructional Materials Motivational Scale (IMMS developed by Keller and the students’ performance test. Pretest and posttest mean scores were measured to determine if there is a mean gain score difference between the experimental and control groups. The study revealed that the group taught with the Physics innovative device performed significantly better than those taught in the traditional method and also the use of Physics innovative device generally improved students’ understanding of concepts and led to higher academic achievements. Analysis of the students’ level of motivation showed that their interests were captured, the instructions they received were relevant to their personal goals and motives, their confidence to learn on their own were build-up, and learning for them was rewarding and important. In the four dimensions (ARCS of IMMS students were found to be attentive, confident, and in agreement in using the fun-learning tool having realize its applicability and relevance in learning their Physics lessons. Results of the study disclosed students and teachers consider the novel device acceptable because it is

  16. Dress Nicer = Know More? Young Children’s Knowledge Attribution and Selective Learning Based on How Others Dress

    Science.gov (United States)

    McDonald, Kyla P.; Ma, Lili

    2015-01-01

    This research explored whether children judge the knowledge state of others and selectively learn novel information from them based on how they dress. The results indicated that 4- and 6-year-olds identified a formally dressed individual as more knowledgeable about new things in general than a casually dressed one (Study 1). Moreover, children displayed an overall preference to seek help from a formally dressed individual rather than a casually dressed one when learning about novel objects and animals (Study 2). These findings are discussed in relation to the halo effect, and may have important implications for child educators regarding how instructor dress might influence young students’ knowledge attribution and learning preferences. PMID:26636980

  17. A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

    Science.gov (United States)

    Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

    2016-06-01

    This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Linking a Learning Progression for Natural Selection to Teachers' Enactment of Formative Assessment

    Science.gov (United States)

    Furtak, Erin Marie

    2012-01-01

    Learning progressions, or representations of how student ideas develop in a domain, hold promise as tools to support teachers' formative assessment practices. The ideas represented in a learning progression might help teachers to identify and make inferences about evidence collected of student thinking, necessary precursors to modifying…

  19. A Theoretical Basis for Adult Learning Facilitation: Review of Selected Articles

    Science.gov (United States)

    Muneja, Mussa S.

    2015-01-01

    The aim of this paper is to synthesize a theoretical basis for adult learning facilitation in order to provide a valuable systematic resource in the field of adult education. The paper has reviewed 6 journal articles with topics ranging from theory of andragogy; the effect of globalization on adult learning; the contribution of Malcolm Knowles;…

  20. Instructional Designers' Media Selection Practices for Distributed Problem-Based Learning Environments

    Science.gov (United States)

    Fells, Stephanie

    2012-01-01

    The design of online or distributed problem-based learning (dPBL) is a nascent, complex design problem. Instructional designers are challenged to effectively unite the constructivist principles of problem-based learning (PBL) with appropriate media in order to create quality dPBL environments. While computer-mediated communication (CMC) tools and…

  1. Biogenic nanosilver incorporated reverse osmosis membrane for antibacterial and antifungal activities against selected pathogenic strains: an enhanced eco-friendly water disinfection approach.

    Science.gov (United States)

    Manjumeena, R; Duraibabu, D; Sudha, J; Kalaichelvan, P T

    2014-01-01

    Reverse osmosis (RO) membranes have been used extensively in water desalination plants, waste water treatment in industries, agricultural farms and drinking water production applications. The objective of this work is to impart antibacterial and antifungal activities to commercially available RO membrane used in water purification systems by incorporating biogenic silver nanoparticles(AgNPs) synthesized using Rosa indica wichuriana hybrid leaf extract. The morphology and surface topography of uncoated and AgNPs-coated RO membrane were studied using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Elemental composition of the AgNPs-coated RO membrane was analyzed by energy-dispersive X-ray spectroscopy (EDAX). The functional groups were identified by Fourier Transform Infrared spectroscopy (FT-IR). Hydrophilicity of the uncoated and AgNPs-coated RO membrane was analyzed using water contact angle measurements. The thermal properties were studied by thermogravimetric analysis (TGA). The AgNPs incorporated RO membrane exhibited good antibacterial and antifungal activities against pathogenic bacterial strains such as E. coli, S. aureus, M. luteus, K. pneumoniae, and P. aeruginosa and fungal strains such as Candida tropicalis, C. krusei, C. glabrata, and C. albicans.

  2. Manual and Flow-Injection Detection/Quantification of Polyquaterniums via Fully Reversible Polyion-Sensitive Polymeric Membrane-Based Ion-Selective Electrodes.

    Science.gov (United States)

    Ferguson, Stephen A; Meyerhoff, Mark E

    2017-10-27

    The detection of four different polyquaterniums (PQs) using a fully reversible potentiometric polyion sensor in three different detection modes is described. The polyion sensing "pulstrodes" serve as the detector for direct dose-response experiments, beaker titrations, and in a flow-injection analysis (FIA) system. Direct polycation response toward PQ-2, PQ-6, PQ-10, and poly(2-methacryloxyethyltrimethylammonium) chloride (PMETAC) yields characteristic information about each PQ species (e.g., relative charge densities, etc.) via syringe pump addition of each PQ species to a background electrolyte solution. Quantitative titrations are performed using a syringe pump to deliver heparin as the polyanion titrant to quantify all four PQs at μg/mL levels. Both the direct and indirect methods incorporate the use of a three-electrode system including counter, double junction reference, and working electrodes. The working electrode possesses a plasticized poly(vinyl chloride) (PVC) membrane containing the neutral lipophilic salt of dinonylnaphthalenesulfonate (DNNS - ) tridodecylmethylammonium (TDMA + ). Further, the titration method is shown to be useful to quantify PQ-6 levels in recreational swimming pool water collected in Ann Arbor, MI. Finally, a FIA system equipped with a pulstrode detector is used to demonstrate the ability to potentially quantify PQ levels via a more streamlined and semiautomated testing platform.

  3. Gas release-based prescreening combined with reversed-phase HPLC quantitation for efficient selection of high-γ-aminobutyric acid (GABA)-producing lactic acid bacteria.

    Science.gov (United States)

    Wu, Qinglong; Shah, Nagendra P

    2015-02-01

    High γ-aminobutyric acid (GABA)-producing lactobacilli are promising for the manufacture of GABA-rich foods and to synthesize GRAS (generally recognized as safe)-grade GABA. However, common chromatography-based screening is time-consuming and inefficient. In the present study, Korean kimchi was used as a model of lactic acid-based fermented foods, and a gas release-based prescreening of potential GABA producers was developed. The ability to produce GABA by potential GABA producers in de Man, Rogosa, and Sharpe medium supplemented with or without monosodium glutamate was further determined by HPLC. Based on the results, 9 isolates were regarded as high GABA producers, and were further genetically identified as Lactobacillus brevis based on the sequences of 16S rRNA gene. Gas release-based prescreening combined with reversed-phase HPLC confirmation was an efficient and cost-effective method to identify high-GABA-producing LAB, which could be good candidates for probiotics. The GABA that is naturally produced by these high-GABA-producing LAB could be used as a food additive. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  4. A comparison of the ability of rilpivirine (TMC278 and selected analogues to inhibit clinically relevant HIV-1 reverse transcriptase mutants

    Directory of Open Access Journals (Sweden)

    Johnson Barry C

    2012-12-01

    Full Text Available Abstract Background The recently approved anti-AIDS drug rilpivirine (TMC278, Edurant is a nonnucleoside inhibitor (NNRTI that binds to reverse transcriptase (RT and allosterically blocks the chemical step of DNA synthesis. In contrast to earlier NNRTIs, rilpivirine retains potency against well-characterized, clinically relevant RT mutants. Many structural analogues of rilpivirine are described in the patent literature, but detailed analyses of their antiviral activities have not been published. This work addresses the ability of several of these analogues to inhibit the replication of wild-type (WT and drug-resistant HIV-1. Results We used a combination of structure activity relationships and X-ray crystallography to examine NNRTIs that are structurally related to rilpivirine to determine their ability to inhibit WT RT and several clinically relevant RT mutants. Several analogues showed broad activity with only modest losses of potency when challenged with drug-resistant viruses. Structural analyses (crystallography or modeling of several analogues whose potencies were reduced by RT mutations provide insight into why these compounds were less effective. Conclusions Subtle variations between compounds can lead to profound differences in their activities and resistance profiles. Compounds with larger substitutions replacing the pyrimidine and benzonitrile groups of rilpivirine, which reorient pocket residues, tend to lose more activity against the mutants we tested. These results provide a deeper understanding of how rilpivirine and related compounds interact with the NNRTI binding pocket and should facilitate development of novel inhibitors.

  5. DHT selectively reverses Smad3-mediated/TGF-beta-induced responses through transcriptional down-regulation of Smad3 in prostate epithelial cells.

    Science.gov (United States)

    Song, Kyung; Wang, Hui; Krebs, Tracy L; Wang, Bingcheng; Kelley, Thomas J; Danielpour, David

    2010-10-01

    Androgens suppress TGF-β responses in the prostate through mechanisms that are not fully explored. We have recently reported that 5α-dihydrotestosterone (DHT) suppresses the ability of TGF-β to inhibit proliferation and induce apoptosis of prostatic epithelial cells and provided evidence that such suppression was fueled by transcriptional down-regulation of TGF-β receptor II (ΤβRII). We now show that androgen receptor (AR) activated by DHT suppresses the TGF-β-induced phosphorylation of Sma- and Mad-related protein (Smad)3 in LNCaP cells overexpressing TβRII under the control of a cytomegalovirus promoter, which is not regulated by DHT, suggesting that transcriptional repression of TβRII alone does not fully account for the impact of DHT on TGF-β responses. Instead, we demonstrate that such suppression occurs through loss of total Smad3, resulting from transcriptional suppression of Smad3. We provide evidence that DHT down-regulates the promoter activity of Smad3 in various prostate cancer cell lines, including NRP-154+AR, DU145+AR, LNCaP, and VCaP, at least partly through androgen-dependent inactivation of Sp1. Moreover, we show that overexpression of Smad3 reverses the ability of DHT to protect against TGF-β-induced apoptosis in NRP-154+AR, supporting our model that loss of Smad3 by DHT is involved in the protection against TGF-β-induced apoptosis. Together, these findings suggest that deregulated/enhanced expression and activation of AR in prostate carcinomas may intercept the tumor suppressor function of TGF-β through transcriptional suppression of Smad3, thereby providing new mechanistic insight into the development of castration-resistant prostate cancer.

  6. Formative use of select-and-fill-in concept maps in online instruction: Implications for students of different learning styles

    Science.gov (United States)

    Kaminski, Charles William

    The purpose of this research was to investigate the formative use of Select and Fill-In (SAFI) maps in online instruction and the cognitive, metacognitive, and affective responses of students to their use. In particular, the implications of their use with students of different learning styles was considered. The research question investigated in this qualitative study was: How do students of different learning styles respond to online instruction in which SAFI maps are utilized? This question was explored by using an emergent, collective case study. Each case consisted of community college students who shared a dominant learning style and were enrolled in an online course in environmental studies. Cases in the study were determined using Kolb's Learning Style Inventory (LSI). Seven forms of data were collected during the study. During the first phase of data collection, dominant learning style and background information on student experience with concept mapping and online instruction was determined. In the second phase of data collection, participants completed SAFI maps and quiz items that corresponded to the content of the maps. Achievement data on the map activities and quiz and student responses to a post-SAFI survey and questionnaire were recorded to identify learner cognitive, metacognitive, and affective responses to the tasks. Upon completion of data collection, cases were constructed and compared across learning styles. Cases are presented using the trends, across participants sharing the same dominant learning style, in achievement, behaviors and attitudes as seen in the evidence present in the data. Triangulation of multiple data sources increased reliability and validity, through cross-case analyses, and produced a thick description of the relationship between the cases for each learning style. Evidence suggesting a cognitive response to the SAFI tasks was inconsistent across cases. However, learners with an affinity towards reflective learning

  7. A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

    Science.gov (United States)

    Torija, Antonio J; Ruiz, Diego P

    2015-02-01

    The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Medical student selection and society: Lessons we learned from sociological theories.

    Science.gov (United States)

    Yaghmaei, Minoo; Yazdani, Shahram; Ahmady, Soleiman

    2016-01-01

    The aim of this study was to show the interaction between the society, applicants and medical schools in terms of medical student selection. In this study, the trends to implement social factors in the selection process were highlighted. These social factors were explored through functionalism and conflict theories, each focusing on different categories of social factors. While functionalist theorists pay attention to diversity in the selection process, conflict theorists highlight the importance of socio-economic class. Although both theories believe in sorting, their different views are reflected in their sorting strategies. Both theories emphasize the importance of the person-society relationship in motivation to enter university. Furthermore, the impacts of social goals on the selection policies are derived from both theories. Theories in the sociology of education offer an approach to student selection that acknowledges and supports complexity, plurality of approaches and innovative means of selection. Medical student selection does not solely focus on the individual assessment and qualification, but it focuses on a social and collective process, which includes all the influences and interactions between the medical schools and the society. Sociological perspective of medical student selection proposes a model that envelops the individual and the society. In this model, the selection methods should meet the criteria of merit at the individual level, while the selection policies should aim at the society goals at the institutional level.

  9. A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

    Science.gov (United States)

    Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

    2016-12-01

    The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

  10. An investigation of the impact of selected prereading activities on student content learning through laboratory activities

    Science.gov (United States)

    Kass, Jesse (Shaya)

    This study investigated whether two prereading activities impacted student learning from hands-on science activities. The study was based on constructivist learning theory. Based on the work of Piaget, it was hypothesized that students who activated prior knowledge would learn more from the activities. Based on the work of Vygotsky it was hypothesized that students who talk more and write more would learn more from the activity. The K-W-L chart and anticipation guide strategies were used with eighth grade students at Graves Middle School in Whittier, California before learning about levers and convection currents. D. M. Ogle (1986) created the three-column K-W-L chart to have students activate prior knowledge. In the first column, the students write what they already know about a subject, in the second column, the students write what they want to know about the subject, and the students complete the third column after learning about a subject by writing answers to the questions that they asked in the second column. Duffelmeyer (1994) created the anticipation guide based on Herber's (1978) reasoning guide. In the anticipation guide, the teacher creates three or four sentences that convey the major ideas of the topic and the students either agree or disagree with the statements. After learning about the topic, students revisit their answers and decide if they were correct or incorrect and they must defend their choices. This research used the Solomon (1947) four-square design and compared both the experimental groups to a control group that simply discussed the concepts before completing the activity. The research showed no significant difference between the control group and either of the treatment groups. The reasons for the lack of significant differences are considered. It was hypothesized that since the students were unfamiliar with the prereading activities and did not have much experience with using either writing-to-learn or talking-to-learn strategies, the

  11. Development of potential selective and reversible pyrazoline based MAO-B inhibitors as MAO-B PET tracer precursors and reference substances for the early detection of Alzheimer's disease.

    Science.gov (United States)

    Neudorfer, Catharina; Shanab, Karem; Jurik, Andreas; Schreiber, Veronika; Neudorfer, Carolina; Vraka, Chrysoula; Schirmer, Eva; Holzer, Wolfgang; Ecker, Gerhard; Mitterhauser, Markus; Wadsak, Wolfgang; Spreitzer, Helmut

    2014-09-15

    Since high MAO-B levels are present in early stages of AD, the MAO-B system can be designated as an appropriate and prospective tracer target of molecular imaging biomarkers for the detection of early AD. According to the preceding investigations of Mishra et al. the aim of this work was the development of a compound library of selective and reversible MAO-B inhibitors by performing bioisosteric modifications of the core structure of 3-(anthracen-9-yl)-5-phenyl-4,5-dihydro-1H-pyrazoles. In conclusion, 13 new pyrazoline based derivatives have been prepared, which will serve as precursor substances for future radiolabeling as well as reference compounds for the investigation of increased MAO-B levels in AD. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Different modes of data processing and statistical testing applied to the same set of pharmaco-EEG recordings: effects on the evaluation of a selective and reversible MAO A inhibitor (brofaromine).

    Science.gov (United States)

    Reimann, I W; Jobert, M; Gleiter, C H; Turri, M; Bieck, P R; Herrmann, W M

    1996-01-01

    The comparison of two different modes of data processing and two different approaches to statistical testing both applied to the same set of EEG recordings was the main objective of this pharmacological study. Brofaromine (CGP 11,305 A), a new selective and reversible monoamine oxidase type A inhibitor was used as an example for investigating a potentially antidepressant drug in clinical development. The two modes of pharmaco-EEG (PEEG) data processing differed mainly in the sampling frequency and definition of spectral parameters. Patterns of significant changes were noted in terms of descriptive data analysis using either a nonparametric Wilcoxon signed-rank test or an ANOVA of transformed data, as suggested by Conover and Iman. These data clearly demonstrate that slight discrepancies in the results may simply arise from differences in data processing and statistical approach applied. In spite of these discrepancies, the pattern of brofaromine-induced PEEG changes was very similar regardless of the mode of data handling used.

  13. Advantages of the appropriate selection of reverse osmosis membranes in desalination plants with open intake; Ventajs de una adecuada seleccion de membranas de osmosis inversa en plants desaladoras con captacion superficial abierta

    Energy Technology Data Exchange (ETDEWEB)

    Munoz Elguera, A.; Nishida, M.

    2001-07-01

    It is hoped to make it sufficiently clear with this article that it is of fundamental importance that the reverse osmosis membranes and the conditions under which they will operate be appropriately selected. It is obvious that this choice must be made primarily in function of the quality of the water that will be processed in the water treatment plant ( for which reason it is of vital importance that a detailed study and careful characterisation of this water be carried out previously). This article report the highly encouraging results achieved with Cellulose Tri-acetate membranes in a singular Hollow fibre configuration, known commercially as Hollosep HM 10255FI (of Japanese manufacture), which were evaluated in parallel with LP3 potabilisation membranes that process sea water collected using an open intake system with high levels of microbiological pollution. (Author) 7 refs.

  14. A Reinforcement Learning Approach to Improve the Argument Selection Effectiveness in Argumentation-based Negotiation

    OpenAIRE

    Amandi, Analia Adriana; Monteserin, Ariel José

    2016-01-01

    Argument selection is considered the essence of the strategy in argumentation-based negotiation. An agent, which is arguing during a negotiation, must decide what arguments are the best to persuade the opponent. In fact, in each negotiation step, the agent must select an argument from a set of candidate arguments by applying some selection policy. Following this policy, the agent observes some factors of the negotiation context, for instance: trust in the opponent and expected utility of the...

  15. Mate choice and sexual selection: what have we learned since Darwin?

    Science.gov (United States)

    Jones, Adam G; Ratterman, Nicholas L

    2009-06-16

    Charles Darwin laid the foundation for all modern work on sexual selection in his seminal book The Descent of Man, and Selection in Relation to Sex. In this work, Darwin fleshed out the mechanism of sexual selection, a hypothesis that he had proposed in The Origin of Species. He went well beyond a simple description of the phenomenon by providing extensive evidence and considering the far-reaching implications of the idea. Here we consider the contributions of Darwin to sexual selection with a particular eye on how far we have progressed in the last 150 years. We focus on 2 key questions in sexual selection. First, why does mate choice evolve at all? And second, what factors determine the strength of mate choice (or intensity of sexual selection) in each sex? Darwin provided partial answers to these questions, and the progress that has been made on both of these topics since his time should be seen as one of the great triumphs of modern evolutionary biology. However, a review of the literature shows that key aspects of sexual selection are still plagued by confusion and disagreement. Many of these areas are complex and will require new theory and empirical data for complete resolution. Overall, Darwin's contributions are still surprisingly relevant to the modern study of sexual selection, so students of evolutionary biology would be well advised to revisit his works. Although we have made significant progress in some areas of sexual selection research, we still have much to accomplish.

  16. Selectivity in associative learning: A cognitive stage framework for blocking and cue competition phenomena

    Directory of Open Access Journals (Sweden)

    Yannick eBoddez

    2014-11-01

    Full Text Available Blocking is the most important phenomenon in the history of associative learning theory: For over 40 years, blocking has inspired a whole generation of learning models. Blocking is part of a family of effects that are typically termed cue competition effects. Common amongst all cue competition effects is that a cue-outcome relation is poorly learned or poorly expressed because the cue is trained in the presence of an alternative predictor or cause of the outcome. We provide an overview of the cognitive processes involved in cue competition effects in humans and propose a stage framework that brings these processes together. The framework contends that the behavioral display of cue competition is cognitively construed following three stages that include (1 an encoding stage, (2 a retention stage, and (3 a performance stage. We argue that the stage framework supports a comprehensive understanding of cue competition effects.

  17. The Impact of Learning Curve Model Selection and Criteria for Cost Estimation Accuracy in the DoD

    Science.gov (United States)

    2016-04-30

    different in the future due to machines” • Heightened scrutiny of cost estimates • Budget Control Act of 2011 seeks to reduce federal deficit ...qÜáêíÉÉåíÜ=^ååì~ä= ^Åèìáëáíáçå=oÉëÉ~êÅÜ= póãéçëáìã= qÜìêëÇ~ó=pÉëëáçåë= sçäìãÉ=ff= = The Impact of Learning Curve Model Selection and Criteria for Cost...Assistant Division Director, Institute for Defense Analyses Bruce Harmon, Research Staff Member, Institute for Defense Analyses The Impact of Learning

  18. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  19. Experience during Early Adulthood Shapes the Learning Capacities and the Number of Synaptic Boutons in the Mushroom Bodies of Honey Bees ("Apis mellifera")

    Science.gov (United States)

    Cabirol, Amélie; Brooks, Rufus; Groh, Claudia; Barron, Andrew B.; Devaud, Jean-Marc

    2017-01-01

    The honey bee mushroom bodies (MBs) are brain centers required for specific learning tasks. Here, we show that environmental conditions experienced as young adults affect the maturation of MB neuropil and performance in a MB-dependent learning task. Specifically, olfactory reversal learning was selectively impaired following early exposure to an…

  20. Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

    Science.gov (United States)

    2013-01-01

    Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

  1. Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

    Science.gov (United States)

    Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

    2016-12-15

    MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

  2. Lessons learned from 15 years of non-grades-based selection for medical school

    NARCIS (Netherlands)

    K.M. Stegers-Jager (Karen)

    2018-01-01

    textabstractContext: Thirty years ago, it was suggested in the Edinburgh Declaration that medical school applicants should be selected not only on academic, but also on non-academic, attributes. The main rationale behind extending medical school selection procedures with the evaluation of

  3. Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

    Science.gov (United States)

    Cheng, Yu-Huei

    2014-12-01

    Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

  4. How Select Groups of Preservice Science Teachers with Inquiry Orientations View Teaching and Learning Science through Inquiry

    Science.gov (United States)

    Ward, Peggy

    Although hailed as a powerful form of instruction, in most teaching and learning contexts, inquiry-based instruction is fraught with ambiguous and conflicting definitions and descriptions. Yet little has been written about the experiences preservice science teacher have regarding their learning to teach science through inquiry. This project sought to understand how select preservice secondary science teachers enrolled in three UTeach programs in Arkansas conceptualize inquiry instruction and how they rationalize its value in a teaching and learning context. The three teacher education programs investigated in this study are adoption sites aligned with the UTeach Program in Austin, TX that distinguishes itself in part by its inquiry emphasis. Using a mixed method investigation design, this study utilized two sources of data to explore the preservice science teachers' thinking. In the first phase, a modified version of the Pedagogy of Science teaching Tests (POSTT) was used to identify select program participants who indicated preferences for inquiry instruction over other instructional strategies. Secondly, the study used an open-ended questionnaire to explore the selected subjects' beliefs and conceptions of teaching and learning science in an inquiry context. The study also focused on identifying particular junctures in the prospective science teachers' education preparation that might impact their understanding about inquiry. Using a constant comparative approach, this study explored 19 preservice science teachers' conceptions about inquiry. The results indicate that across all levels of instruction, the prospective teachers tended to have strong student-centered teaching orientations. Except subjects in for the earliest courses, subjects' definitions and descriptions of inquiry tended toward a few of the science practices. More advanced subjects, however, expressed more in-depth descriptions. Excluding the subjects who have completed the program, multiple

  5. Group Selection and Learning for a Lab-Based Construction Management Course

    Science.gov (United States)

    Solanki, Pranshoo; Kothari, Nidhi

    2014-01-01

    In construction industries' projects, working in groups is a normal practice. Group work in a classroom is defined as students working collaboratively in a group so that everyone can participate on a collective task. The results from literature review indicate that group work is more effective method of learning as compared to individual work.…

  6. Selective visual attention and motivation: the consequences of value learning in an attentional blink task.

    Science.gov (United States)

    Raymond, Jane E; O'Brien, Jennifer L

    2009-08-01

    Learning to associate the probability and value of behavioral outcomes with specific stimuli (value learning) is essential for rational decision making. However, in demanding cognitive conditions, access to learned values might be constrained by limited attentional capacity. We measured recognition of briefly presented faces seen previously in a value-learning task involving monetary wins and losses; the recognition task was performed both with and without constraints on available attention. Regardless of available attention, recognition was substantially enhanced for motivationally salient stimuli (i.e., stimuli highly predictive of outcomes), compared with equally familiar stimuli that had weak or no motivational salience, and this effect was found regardless of valence (win or loss). However, when attention was constrained (because stimuli were presented during an attentional blink, AB), valence determined recognition; win-associated faces showed no AB, but all other faces showed large ABs. Motivational salience acts independently of attention to modulate simple perceptual decisions, but when attention is limited, visual processing is biased in favor of reward-associated stimuli.

  7. Selecting the Most Appropriate Primary Learning Medium for Students with Functional Vision.

    Science.gov (United States)

    Mangold, S.; Mangold, P.

    1989-01-01

    Five considerations for determining the most appropriate learning medium for students with functional vision are: (1) working distance from the page; (2) portability of reading skills; (3) reading rates and accuracy; (4) visual fatigue; and (5) interpretation of assessment results. (Author/DB)

  8. Professionals' Perception of Quality Physical Education Learning in Selected Asian Cities

    Science.gov (United States)

    Ho, Walter King Yan; Ahmed, Md. Dilsad; Keh, Nyit Chin; Khoo, Selina; Tan, Cheehian; Dehkordi, Mitra Rouhi; Gallardo, Mila; Lee, Kicheon; Yamaguchi, Yasuo; Wang, Jian; Liu, Min; Huang, Fan

    2017-01-01

    Numerous studies have been published heralding the benefits of physical education in school education. Sport and physical activities form the major content in learning and the arrangement serves as the major source of development in students. This paper identifies "quality" as an internationally concerned issue and within the concept,…

  9. Attitude of Students towards Cooperative Learning in Some Selected Secondary Schools in Nasarawa State

    Science.gov (United States)

    Amedu, Odagboyi Isaiah; Gudi, Kreni Comfort

    2017-01-01

    This study is aimed at investigating the attitude of students toward the cooperative learning approach. A quasiexperimental design was used for the study. The sample was made of 179 SS 1 students drawn from three public secondary schools in Nasarawa state. The Jigsaw Attitude Questionnaire (JAQ) was adapted from Koprowski and Perigo (2000) and was…

  10. Authentic Education by Providing a Situation for Student-Selected Problem-Based Learning

    Science.gov (United States)

    Strimel, Greg

    2014-01-01

    Students are seldom given an authentic experience within school that allows them the opportunity to solve real-life complex engineering design problems that have meaning to their lives and/ or the greater society. They are often confined to learning environments that are limited by the restrictions set by course content for assessment purposes and…

  11. PROGRAMMED LEARNING--THEORY AND RESEARCH, AN ENDURING PROBLEM IN PSYCHOLOGY. SELECTED READINGS.

    Science.gov (United States)

    MOORE, J. WILLIAM, ED.; SMITH, WENDELL I., ED.

    THIS IS A COMPILATION OF ARTICLES DEALING WITH PROGRAMED INSTRUCTION AND AUTO-INSTRUCTIONAL DEVICES (TEACHING-MACHINES). THE LITERATURE IS REVIEWED AND AN OVERVIEW OF THE FIELD IS PRESENTED. THE APPLICATION OF INSTRUCTIONAL TECHNOLOGY AND LEARNING THEORY TO TEACHING MACHINES IS DISCUSSED, AND THE PROCEDURE AND RULES OF PROGRAMING METHOD. SAMPLES…

  12. Characteristics of Criterion-Referenced Instruments: Implications for Materials Selection for the Learning Disabled.

    Science.gov (United States)

    Blasi, Joyce F.

    Discussed are characteristics of criterion referenced reading tests for use with learning disabled (LD) children, and analyzed are the Basic Educational Skills Inventory (BESI), the Prescriptive Reading Inventory (PRI), and the Cooper-McGuire Diagnostic Work-Analysis Test (CooperMcGuire). Criterion referenced tests are defined; and problems in…

  13. Pre-Exposure to Context Affects Learning Strategy Selection in Mice

    Science.gov (United States)

    Tunur, Tumay; Dohanich, Gary P.; Schrader, Laura A.

    2010-01-01

    The multiple memory systems hypothesis proposes that different types of learning strategies are mediated by distinct neural systems in the brain. Male and female mice were tested on a water plus-maze task that could be solved by either a place or response strategy. One group of mice was pre-exposed to the same context as training and testing (PTC)…

  14. The Implications of Selective Learning Models on Teaching Junior High School Mathematics.

    Science.gov (United States)

    Wilson, Roosevelt L.

    1978-01-01

    Providing practitioners with synopses, illustrations based on classroom experiences, and research findings, this article analyzes the learning models of Jean Piaget, Robert Gagne, Robert Karplus, David Ausubel, and Jerome Bruner in terms of the implications for teaching junior high school mathematics. (JC)

  15. MS-377, a novel selective sigma(1) receptor ligand, reverses phencyclidine-induced release of dopamine and serotonin in rat brain.

    Science.gov (United States)

    Takahashi, S; Horikomi, K; Kato, T

    2001-09-21

    A novel selective sigma(1) receptor ligand, (R)-(+)-1-(4-chlorophenyl)-3-[4-(2-methoxyethyl)piperazin-1-yl]methyl-2-pyrrolidinone L-tartrate (MS-377), inhibits phencyclidine (1-(1-phenylcyclohexyl)piperidine; PCP)-induced behaviors in animal models. In this study, we measured extracellular dopamine and serotonin levels in the rat brain after treatment with MS-377 alone, using in vivo microdialysis. We also examined the effects of MS-377 on extracellular dopamine and serotonin levels in the rat medial prefrontal cortex after treatment with PCP. MS-377 itself had no significant effects on dopamine release in the striatum (10 mg/kg, p.o.) nor on dopamine or serotonin release in the medial prefrontal cortex (1 and 10 mg/kg, p.o.). PCP (3 mg/kg, i.p.) markedly increased dopamine and serotonin release in the medial prefrontal cortex. MS-377 (1 mg/kg, p.o.), when administered 60 min prior to PCP, significantly attenuated this effect of PCP. These results suggest that the inhibitory effects of MS-377 on PCP-induced behaviors are partly mediated by inhibition of the increase in dopamine and serotonin release in the rat medial prefrontal cortex caused by PCP.

  16. Managing Reverse Logistics or Reversing Logistics Management?

    OpenAIRE

    Brito, Marisa

    2004-01-01

    textabstractIn the past, supply chains were busy fine-tuning the logistics from raw material to the end customer. Today an increasing flow of products is going back in the chain. Thus, companies have to manage reverse logistics as well.This thesis contributes to a better understanding of reverse logistics. The thesis brings insights on reverse logistics decision-making and it lays down theoretical principles for reverse logistics as a research field.In particular it puts together a framework ...

  17. Selective transfer of visual working memory training on Chinese character learning.

    Science.gov (United States)

    Opitz, Bertram; Schneiders, Julia A; Krick, Christoph M; Mecklinger, Axel

    2014-01-01

    Previous research has shown a systematic relationship between phonological working memory capacity and second language proficiency for alphabetic languages. However, little is known about the impact of working memory processes on second language learning in a non-alphabetic language such as Mandarin Chinese. Due to the greater complexity of the Chinese writing system we expect that visual working memory rather than phonological working memory exerts a unique influence on learning Chinese characters. This issue was explored in the present experiment by comparing visual working memory training with an active (auditory working memory training) control condition and a passive, no training control condition. Training induced modulations in language-related brain networks were additionally examined using functional magnetic resonance imaging in a pretest-training-posttest design. As revealed by pre- to posttest comparisons and analyses of individual differences in working memory training gains, visual working memory training led to positive transfer effects on visual Chinese vocabulary learning compared to both control conditions. In addition, we found sustained activation after visual working memory training in the (predominantly visual) left infero-temporal cortex that was associated with behavioral transfer. In the control conditions, activation either increased (active control condition) or decreased (passive control condition) without reliable behavioral transfer effects. This suggests that visual working memory training leads to more efficient processing and more refined responses in brain regions involved in visual processing. Furthermore, visual working memory training boosted additional activation in the precuneus, presumably reflecting mental image generation of the learned characters. We, therefore, suggest that the conjoint activity of the mid-fusiform gyrus and the precuneus after visual working memory training reflects an interaction of working memory and

  18. Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China.

    Science.gov (United States)

    Liu, Zhijuan; Hubbard, Kenneth G; Lin, Xiaomao; Yang, Xiaoguang

    2013-11-01

    Northeast China (NEC) accounts for about 30% of the nation's maize production in China. In the past three decades, maize yields in NEC have increased under changes in climate, cultivar selection and crop management. It is important to investigate the contribution of these changing factors to the historical yield increases to improve our understanding of how we can ensure increased yields in the future. In this study, we use phenology observations at six sites from 1981 to 2007 to detect trends in sowing dates and length of maize growing period, and then combine these observations with in situ temperature data to determine the trends of thermal time in the maize growing period, as a measure of changes in maize cultivars. The area in the vicinity of these six sites accounts for 30% of NEC's total maize production. The agricultural production systems simulator, APSIM-Maize model, was used to separate the impacts of changes in climate, sowing dates and thermal time requirements on maize phenology and yields. In NEC, sowing dates trended earlier in four of six sites and maturity dates trended later by 4-21 days. Therefore, the period from sowing to maturity ranged from 2 to 38 days longer in 2007 than it was in 1981. Our results indicate that climate trends alone would have led to a negative impact on maize. However, results from the adaptation assessments indicate that earlier sowing dates increased yields by up to 4%, and adoption of longer season cultivars caused a substantial increase in yield ranging from 13% to 38% over the past 27 years. Therefore, earlier sowing dates and introduction of cultivars with higher thermal time requirements in NEC have overcome the negative effects of climate change and turned what would have otherwise been a loss into a significant increase in maize yield. © 2013 John Wiley & Sons Ltd.

  19. Online Reverse Auctions for Procurement of Services

    NARCIS (Netherlands)

    U.L. Radkevitch (Uladzimir)

    2008-01-01

    textabstractOnline reverse auctions, in which a buyer seeks to select a supplier and suppliers compete for contracts by bidding online, revolutionized corporate procurement early this century. Shortly after they had been pioneered by General Electric, many companies rushed to adopt reverse auctions

  20. Fully automatic time-window selection using machine learning for global adjoint tomography

    Science.gov (United States)

    Chen, Y.; Hill, J.; Lei, W.; Lefebvre, M. P.; Bozdag, E.; Komatitsch, D.; Tromp, J.

    2017-12-01

    Selecting time windows from seismograms such that the synthetic measurements (from simulations) and measured observations are sufficiently close is indispensable in a global adjoint tomography framework. The increasing amount of seismic data collected everyday around the world demands "intelligent" algorithms for seismic window selection. While the traditional FLEXWIN algorithm can be "automatic" to some extent, it still requires both human input and human knowledge or experience, and thus is not deemed to be fully automatic. The goal of intelligent window selection is to automatically select windows based on a learnt engine that is built upon a huge number of existing windows generated through the adjoint tomography project. We have formulated the automatic window selection problem as a classification problem. All possible misfit calculation windows are classified as either usable or unusable. Given a large number of windows with a known selection mode (select or not select), we train a neural network to predict the selection mode of an arbitrary input window. Currently, the five features we extract from the windows are its cross-correlation value, cross-correlation time lag, amplitude ratio between observed and synthetic data, window length, and minimum STA/LTA value. More features can be included in the future. We use these features to characterize each window for training a multilayer perceptron neural network (MPNN). Training the MPNN is equivalent to solve a non-linear optimization problem. We use backward propagation to derive the gradient of the loss function with respect to the weighting matrices and bias vectors and use the mini-batch stochastic gradient method to iteratively optimize the MPNN. Numerical tests show that with a careful selection of the training data and a sufficient amount of training data, we are able to train a robust neural network that is capable of detecting the waveforms in an arbitrary earthquake data with negligible detection error

  1. Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

    Directory of Open Access Journals (Sweden)

    Yeom, Ha-Neul

    2014-09-01

    Full Text Available In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

  2. Supervised Variational Relevance Learning, An Analytic Geometric Feature Selection with Applications to Omic Datasets.

    Science.gov (United States)

    Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor

    2015-01-01

    We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.

  3. Managing Reverse Logistics or Reversing Logistics Management?

    NARCIS (Netherlands)

    M.P. de Brito (Marisa)

    2004-01-01

    textabstractIn the past, supply chains were busy fine-tuning the logistics from raw material to the end customer. Today an increasing flow of products is going back in the chain. Thus, companies have to manage reverse logistics as well.This thesis contributes to a better understanding of reverse

  4. The chemotherapeutic agent paclitaxel selectively impairs learning while sparing source memory and spatial memory.

    Science.gov (United States)

    Smith, Alexandra E; Slivicki, Richard A; Hohmann, Andrea G; Crystal, Jonathon D

    2017-03-01

    Chemotherapeutic agents are widely used to treat patients with systemic cancer. The efficacy of these therapies is undermined by their adverse side-effect profiles such as cognitive deficits that have a negative impact on the quality of life of cancer survivors. Cognitive side effects occur across a variety of domains, including memory, executive function, and processing speed. Such impairments are exacerbated under cognitive challenges and a subgroup of patients experience long-term impairments. Episodic memory in rats can be examined using a source memory task. In the current study, rats received paclitaxel, a taxane-derived chemotherapeutic agent, and learning and memory functioning was examined using the source memory task. Treatment with paclitaxel did not impair spatial and episodic memory, and paclitaxel treated rats were not more susceptible to cognitive challenges. Under conditions in which memory was not impaired, paclitaxel treatment impaired learning of new rules, documenting a decreased sensitivity to changes in experimental contingencies. These findings provide new information on the nature of cancer chemotherapy-induced cognitive impairments, particularly regarding the incongruent vulnerability of episodic memory and new learning following treatment with paclitaxel. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Top-down inputs enhance orientation selectivity in neurons of the primary visual cortex during perceptual learning.

    Directory of Open Access Journals (Sweden)

    Samat Moldakarimov

    2014-08-01

    Full Text Available Perceptual learning has been used to probe the mechanisms of cortical plasticity in the adult brain. Feedback projections are ubiquitous in the cortex, but little is known about their role in cortical plasticity. Here we explore the hypothesis that learning visual orientation discrimination involves learning-dependent plasticity of top-down feedback inputs from higher cortical areas, serving a different function from plasticity due to changes in recurrent connections within a cortical area. In a Hodgkin-Huxley-based spiking neural network model of visual cortex, we show that modulation of feedback inputs to V1 from higher cortical areas results in shunting inhibition in V1 neurons, which changes the response properties of V1 neurons. The orientation selectivity of V1 neurons is enhanced without changing orientation preference, preserving the topographic organizations in V1. These results provide new insights to the mechanisms of plasticity in the adult brain, reconciling apparently inconsistent experiments and providing a new hypothesis for a functional role of the feedback connections.

  6. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  7. Glucose Injections into the Dorsal Hippocampus or Dorsolateral Striatum of Rats Prior to T-Maze Training: Modulation of Learning Rates and Strategy Selection

    Science.gov (United States)

    Canal, Clinton E.; Stutz, Sonja J.; Gold, Paul E.

    2005-01-01

    The present experiments examined the effects of injecting glucose into the dorsal hippocampus or dorsolateral striatum on learning rates and on strategy selection in rats trained on a T-maze that can be solved by using either a hippocampus-sensitive place or striatum-sensitive response strategy. Percentage strategy selection on a probe trial…

  8. A comparison of Lewis and Fischer rat strains on autoshaping (sign-tracking), discrimination reversal learning and negative auto-maintenance.

    Science.gov (United States)

    Kearns, David N; Gomez-Serrano, Maria A; Weiss, Stanley J; Riley, Anthony L

    2006-05-15

    Lewis (LEW) and Fischer (F344) rat strains differ on a number of physiological characteristics, such as hypothalamic-pituitary-adrenal (HPA) axis activity, as well as on behavioral tasks, including those that measure impulsivity and drug reward. Since autoshaping, the phenomenon where animals approach and contact reward-paired conditioned stimuli, has been linked to HPA axis functioning, impulsivity and drug taking, the present study compared LEW and F344 rats on the rate of acquisition and performance of the autoshaping response. Rats were trained on an autoshaping procedure where insertions of one retractable lever (CS(+)) were paired response-independently with food, while insertions of another lever (CS(-)) were not paired with food. LEW rats acquired the autoshaping response more rapidly and also performed the autoshaping response at a higher rate than F344 rats. No differences between the strains were observed when rats were trained on a discrimination reversal where the CS(+) and CS(-) levers were reversed or during a negative auto-maintenance phase where CS(+) lever contacts cancelled food delivery. Potential physiological mechanisms that might mediate the present results, including strain differences in HPA axis and monoamine neurotransmitter activity, are discussed. The finding that LEW (as compared to F344 rats) more readily acquire autoshaping and perform more responses is consistent with research indicating that LEW rats behave more impulsively and more readily self-administer drugs of abuse.

  9. An active learning representative subset selection method using net analyte signal

    Science.gov (United States)

    He, Zhonghai; Ma, Zhenhe; Luan, Jingmin; Cai, Xi

    2018-05-01

    To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced.

  10. Uncertainty-handling assessment using nondeterministic learning tasks in pilot selection

    OpenAIRE

    Matton , Nadine; Raufaste , Éric; Vautier , Stéphane

    2008-01-01

    International audience; This paper addresses selection for entry into the French commercial pilot ab initio training, namely the ENAC (École Nationale de l'Aviation Civile). Applicants are mainly (more than 80%) coming from scientific preparatory classes for competitive admission to the "Grandes Écoles". Therefore these applicants are hand-picked based on their school grades in mathematics and physics. To give a hint, in 2005, only 15% of the French GCE A-Level students were selected for entr...

  11. NERVE: New Enhanced Reverse Vaccinology Environment

    Directory of Open Access Journals (Sweden)

    Filippini Francesco

    2006-07-01

    Full Text Available Abstract Background Since a milestone work on Neisseria meningitidis B, Reverse Vaccinology has strongly enhanced the identification of vaccine candidates by replacing several experimental tasks using in silico prediction steps. These steps have allowed scientists to face the selection of antigens from the predicted proteome of pathogens, for which cell culture is difficult or impossible, saving time and money. However, this good example of bioinformatics-driven immunology can be further developed by improving in silico steps and implementing biologist-friendly tools. Results We introduce NERVE (New Enhanced Reverse Vaccinology Environment, an user-friendly software environment for the in silico identification of the best vaccine candidates from whole proteomes of bacterial pathogens. The software integrates multiple robust and well-known algorithms for protein analysis and comparison. Vaccine candidates are ranked and presented in a html table showing relevant information and links to corresponding primary data. Information concerning all proteins of the analyzed proteome is not deleted along selection steps but rather flows into an SQL database for further mining and analyses. Conclusion After learning from recent years' works in this field and analysing a large dataset, NERVE has been implemented and tuned as the first available tool able to rank a restricted pool (~8–9% of the whole proteome of vaccine candidates and to show high recall (~75–80% of known protective antigens. These vaccine candidates are required to be "safe" (taking into account autoimmunity risk and "easy" for further experimental, high-throughput screening (avoiding possibly not soluble antigens. NERVE is expected to help save time and money in vaccine design and is available as an additional file with this manuscript; updated versions will be available at http://www.bio.unipd.it/molbinfo.

  12. Verbal learning and memory outcome in selective amygdalohippocampectomy versus temporal lobe resection in patients with hippocampal sclerosis.

    Science.gov (United States)

    Foged, Mette Thrane; Vinter, Kirsten; Stauning, Louise; Kjær, Troels W; Ozenne, Brice; Beniczky, Sándor; Paulson, Olaf B; Madsen, Flemming Find; Pinborg, Lars H

    2018-02-01

    With the advent of new very selective techniques like thermal laser ablation to treat drug-resistant focal epilepsy, the controversy of resection size in relation to seizure outcome versus cognitive deficits has gained new relevance. The purpose of this study was to test the influence of the selective amygdalohippocampectomy (SAH) versus nonselective temporal lobe resection (TLR) on seizure outcome and cognition in patients with mesial temporal lobe epilepsy (MTLE) and histopathological verified hippocampal sclerosis (HS). We identified 108 adults (>16years) with HS, operated between 1995 and 2009 in Denmark. Exclusion criteria are the following: Intelligence below normal range, right hemisphere dominance, other native languages than Danish, dual pathology, and missing follow-up data. Thus, 56 patients were analyzed. The patients were allocated to SAH (n=22) or TLR (n=34) based on intraoperative electrocorticography. Verbal learning and verbal memory were tested pre- and postsurgery. Seizure outcome did not differ between patients operated using the SAH versus the TLR at 1year (p=0.951) nor at 7years (p=0.177). Verbal learning was more affected in patients resected in the left hemisphere than in the right (p=0.002). In patients with left-sided TLR, a worsening in verbal memory performance was found (p=0.011). Altogether, 73% were seizure-free for 1year and 64% for 7years after surgery. In patients with drug-resistant focal MTLE, HS and no magnetic resonance imaging (MRI) signs of dual pathology, selective amygdalohippocampectomy results in sustained seizure freedom and better memory function compared with patients operated with nonselective temporal lobe resection. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. "Tell Me a Story": The Use of Narrative as a Learning Tool for Natural Selection

    Science.gov (United States)

    Prins, Renate; Avraamidou, Lucy; Goedhart, Martin

    2017-01-01

    Grounded within literature pointing to the value of narrative in communicating scientific information, the purpose of this study was to examine the use of stories as a tool for teaching about natural selection in the context of school science. The study utilizes a mixed method, case study approach which focuses on the design, implementation, and…

  14. Selective Attentional Effects of Textbook Study Questions on Student Learning in Science.

    Science.gov (United States)

    Holliday, William G.

    1981-01-01

    Reports results of a study testing a selective attentional model which predicted that textbook study questions adjunct to a flow diagram will focus students' attention more upon questioned information and less upon nonquestioned information. A picture-word diagram describing biogeochemical cycles to high school biology students (N=176) was used.…

  15. Learning by Exporting or Self Selection? Which Way for the Kenyan ...

    African Journals Online (AJOL)

    African Research Review. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 5, No 4 (2011) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Download this PDF file. The PDF file you selected should load ...

  16. Tubal Ligation Reversal

    Science.gov (United States)

    ... seal off the fallopian tubes, such as the Essure or Adiana systems, generally aren't reversible. Why ... electrocautery). Some types of sterilization, such as the Essure or Adiana systems, aren't considered reversible. Risks ...

  17. Brief, pre-learning stress reduces false memory production and enhances true memory selectively in females.

    Science.gov (United States)

    Zoladz, Phillip R; Peters, David M; Kalchik, Andrea E; Hoffman, Mackenzie M; Aufdenkampe, Rachael L; Woelke, Sarah A; Wolters, Nicholas E; Talbot, Jeffery N

    2014-04-10

    Some of the previous research on stress-memory interactions has suggested that stress increases the production of false memories. However, as accumulating work has shown that the effects of stress on learning and memory depend critically on the timing of the stressor, we hypothesized that brief stress administered immediately before learning would reduce, rather than increase, false memory production. In the present study, participants submerged their dominant hand in a bath of ice cold water (stress) or sat quietly (no stress) for 3 min. Then, participants completed a short-term memory task, the Deese-Roediger-McDermott paradigm, in which they were presented with 10 different lists of semantically related words (e.g., candy, sour, sugar) and, after each list, were tested for their memory of presented words (e.g., candy), non-presented unrelated "distractor" words (e.g., hat), and non-presented semantically related "critical lure" words (e.g., sweet). Stress, overall, significantly reduced the number of critical lures recalled (i.e., false memory) by participants. In addition, stress enhanced memory for the presented words (i.e., true memory) in female, but not male, participants. These findings reveal that stress does not unequivocally enhance false memory production and that the timing of the stressor is an important variable that could mediate such effects. Such results could have important implications for understanding the dependability of eyewitness accounts of events that are observed following stress. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Basic Visual Disciplines in Heritage Conservation: Outline of Selected Perspectives in Teaching and Learning

    Science.gov (United States)

    Lobovikov-Katz, A.

    2017-08-01

    Acknowledgement of the value of a basic freehand sketch by the information and communication community of researchers and developers brought about the advanced developments for the use of sketches as free input to complicated processes of computerized visualization, so as to make them more widely accessible. However, a sharp reduction and even exclusion of this and other basic visual disciplines from education in sciences, technology, engineering and architecture dramatically reduces the number of future users of such applications. The unique needs of conservation of cultural heritage pose specific challenges as well as encourage the formulation of innovative development tasks in related areas of information and communication technologies (ICT). This paper claims that the introduction of basic visual disciplines to both communities is essential to the effectiveness of integration of heritage conservation needs and the advanced ICT development of conservation value, and beyond. It provides an insight into the challenges and advantages of introducing these subjects in a relevant educational context, presents some examples of their teaching and learning in the modern environment, including e-learning, and sketches perspectives to their application.

  19. Human place and response learning: navigation strategy selection, pupil size and gaze behavior.

    Science.gov (United States)

    de Condappa, Olivier; Wiener, Jan M

    2016-01-01

    In this study, we examined the cognitive processes and ocular behavior associated with on-going navigation strategy choice using a route learning paradigm that distinguishes between three different wayfinding strategies: an allocentric place strategy, and the egocentric associative cue and beacon response strategies. Participants approached intersections of a known route from a variety of directions, and were asked to indicate the direction in which the original route continued. Their responses in a subset of these test trials allowed the assessment of strategy choice over the course of six experimental blocks. The behavioral data revealed an initial maladaptive bias for a beacon response strategy, with shifts in favor of the optimal configuration place strategy occurring over the course of the experiment. Response time analysis suggests that the configuration strategy relied on spatial transformations applied to a viewpoint-dependent spatial representation, rather than direct access to an allocentric representation. Furthermore, pupillary measures reflected the employment of place and response strategies throughout the experiment, with increasing use of the more cognitively demanding configuration strategy associated with increases in pupil dilation. During test trials in which known intersections were approached from different directions, visual attention was directed to the landmark encoded during learning as well as the intended movement direction. Interestingly, the encoded landmark did not differ between the three navigation strategies, which is discussed in the context of initial strategy choice and the parallel acquisition of place and response knowledge.

  20. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  1. Modeling PM2.5 Urban Pollution Using Machine Learning and Selected Meteorological Parameters

    Directory of Open Access Journals (Sweden)

    Jan Kleine Deters

    2017-01-01

    Full Text Available Outdoor air pollution costs millions of premature deaths annually, mostly due to anthropogenic fine particulate matter (or PM2.5. Quito, the capital city of Ecuador, is no exception in exceeding the healthy levels of pollution. In addition to the impact of urbanization, motorization, and rapid population growth, particulate pollution is modulated by meteorological factors and geophysical characteristics, which complicate the implementation of the most advanced models of weather forecast. Thus, this paper proposes a machine learning approach based on six years of meteorological and pollution data analyses to predict the concentrations of PM2.5 from wind (speed and direction and precipitation levels. The results of the classification model show a high reliability in the classification of low (25 µg/m3 and low (<10 µg/m3 versus moderate (10–25 µg/m3 concentrations of PM2.5. A regression analysis suggests a better prediction of PM2.5 when the climatic conditions are getting more extreme (strong winds or high levels of precipitation. The high correlation between estimated and real data for a time series analysis during the wet season confirms this finding. The study demonstrates that the use of statistical models based on machine learning is relevant to predict PM2.5 concentrations from meteorological data.

  2. Reverse logistics - a framework

    NARCIS (Netherlands)

    M.P. de Brito (Marisa); R. Dekker (Rommert)

    2002-01-01

    textabstractIn this paper we define and compare Reverse Logistics definitions. We start by giving an understanding framework of Reverse Logistics: the why-what-how. By this means, we put in context the driving forces for Reverse Logistics, a typology of return reasons, a classification of

  3. A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

    Science.gov (United States)

    Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

    2017-09-01

    Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

  4. 'They hear "Africa" and they think that there can't be any good services'--perceived context in cross-national learning: a qualitative study of the barriers to Reverse Innovation.

    Science.gov (United States)

    Harris, Matthew; Weisberger, Emily; Silver, Diana; Macinko, James

    2015-11-19

    Country-of-origin of a product can negatively influence its rating, particularly if the product is from a low-income country. It follows that how non-traditional sources of innovation, such as low-income countries, are perceived is likely to be an important part of a diffusion process, particularly given the strong social and cognitive boundaries associated with the healthcare professions. Between September and December 2014, we conducted eleven in-depth face-to-face or telephone interviews with key informants from innovation, health and social policy circles, experts in international comparative policy research and leaders in Reverse Innovation in the United States. Interviews were open-ended with guiding probes into the barriers and enablers to Reverse Innovation in the US context, specifically also to understand whether, in their experience translating or attempting to translate innovations from low-income contexts into the US, the source of the innovation matters in the adopter context. Interviews were recorded, transcribed and analyzed thematically using the process of constant comparison. Our findings show that innovations from low-income countries tend to be discounted early on because of prior assumptions about the potential for these contexts to offer solutions to healthcare problems in the US. Judgments are made about the similarity of low-income contexts with the US, even though this is based oftentimes on flimsy perceptions only. Mixing levels of analysis, local and national, leads to country-level stereotyping and missed opportunities to learn from low-income countries. Our research highlights that prior expectations, invoked by the Low-income country cue, are interfering with a transparent and objective learning process. There may be merit in adopting some techniques from the cognitive psychology and marketing literatures to understand better the relative importance of source in healthcare research and innovation diffusion. Counter

  5. When Field Experiments Yield Unexpected Results: Lessons Learned from Measuring Selection in White Sands Lizards

    Science.gov (United States)

    Hardwick, Kayla M.; Harmon, Luke J.; Hardwick, Scott D.; Rosenblum, Erica Bree

    2015-01-01

    Determining the adaptive significance of phenotypic traits is key for understanding evolution and diversification in natural populations. However, evolutionary biologists have an incomplete understanding of how specific traits affect fitness in most populations. The White Sands system provides an opportunity to study the adaptive significance of traits in an experimental context. Blanched color evolved recently in three species of lizards inhabiting the gypsum dunes of White Sands and is likely an adaptation to avoid predation. To determine whether there is a relationship between color and susceptibility to predation in White Sands lizards, we conducted enclosure experiments, quantifying survivorship of Holbrookia maculate exhibiting substrate-matched and substrate-mismatched phenotypes. Lizards in our study experienced strong predation. Color did not have a significant effect on survival, but we found several unexpected relationships including variation in predation over small spatial and temporal scales. In addition, we detected a marginally significant interaction between sex and color, suggesting selection for substrate matching may be stronger for males than females. We use our results as a case study to examine six major challenges frequently encountered in field-based studies of natural selection, and suggest that insight into the complexities of selection often results when experiments turn out differently than expected. PMID:25714838

  6. Study of the mechanical behavior of thermo reversible gels of PS-b-poly(ethylene/butylene)-b-PS triblock copolymers in a selective solvent for the middle block of the copolymer

    International Nuclear Information System (INIS)

    Hernaez, E.; Inchausti, I.; Quintana, J. R.; Katime, I.

    2001-01-01

    The thermo reversible gelation of three triblock copolymers polystyrene-b-poly(ethylene/butylene)-b-polystyrene, with different molar mass and a similar chemical composition, in n-octane was studied. The solvent is selective for the middle poly(ethylene/butylene) block of the copolymers. the influence of the molar mass of the three copolymers on the gelation and on the mechanical properties of the gels was analysed. The sol-gel transition temperatures. T g el have been determined and they increase with the copolymer concentration and the copolymer molar mass. On the other land, the mechanical properties of the different gels were examined through oscillatory shear and compressive stress relaxation measurements. The concentration dependence of the elastic storage modules, G' for the three copolymer studied fit a sole straight line in a double-logarithmic scale and its slope (2.22) is close to that expected for systems in good solvents (2.25). As the temperature is near to the sol-gel transition temperate, the elastic modulus are smaller and the relaxation rates are higher. (Author) 12 refs

  7. Development of a method based on on-line reversed phase liquid chromatography and gas chromatography coupled by means of an adsorption-desorption interface for the analysis of selected chiral volatile compounds in methyl jasmonate treated strawberries.

    Science.gov (United States)

    de la Peña Moreno, Fernando; Blanch, Gracia Patricia; Flores, Gema; Ruiz Del Castillo, Maria Luisa

    2010-02-12

    A method based on the use of the through oven transfer adsorption-desorption (TOTAD) interface in on-line coupling between reversed phase liquid chromatography and gas chromatography (RPLC-GC) for the determination of chiral volatile compounds was developed. In particular, the method was applied to the study of the influence of methyl jasmonate (MJ) treatment on the production and enantiomeric composition of selected aroma compounds in strawberry. The compounds studied were ethyl 2-methylbutanoate, linalool and 4-hydroxy-2,5-dimethyl-3(2H)-furanone (i.e. furaneol), which were examined on days 3, 6 and 9 after treatment. The method developed resulted in relative standard deviations (RSDs) of 21.6%, 8.1% and 9.8% and limits of detection (LD) of 0.04, 0.07 and 0.02mg/l for ethyl 2-methylbutanoate, linalool and furaneol, respectively. The application of the RPLC-TOTAD-GC method allowed higher levels of ethyl 2-methylbutanoate, linalool and furaneol to be detected, particularly after 9 days of treatment. Besides, MJ demonstrated to affect the enantiomeric distribution of ethyl 2-methylbutanoate. On the contrary, the enantiomeric composition of linalool and furaneol kept constant in both control and MJ-treated strawberries throughout the study. These results are discussed. Copyright 2009 Elsevier B.V. All rights reserved.

  8. Effects of selective phosphodiesterases-4 inhibitors on learning and memory: a review of recent research.

    Science.gov (United States)

    Peng, Sheng; Sun, Haiyan; Zhang, Xiaoqing; Liu, Gongjian; Wang, Guanglei

    2014-09-01

    Phosphodiesterase-4 (PDE-4) regulates the intracellular level of cyclic adenosine monophosphate. Recent studies demonstrated that PDE-4 inhibitors can counteract deficits in long-term memory caused by aging or increased expression of mutant forms of human amyloid precursor proteins, and can influence the process of memory function and cognitive enhancement. Therapeutics, such as ketamine, a drug used in clinical anesthesia, can also cause memory deficits as adverse effects. Targeting PDE-4 with selective inhibitors may offer a novel therapeutic strategy to prevent, slow the progress, and, eventually, treat memory deficits.

  9. The role of motor memory in action selection and procedural learning: insights from children with typical and atypical development

    Directory of Open Access Journals (Sweden)

    Jessica Tallet

    2015-07-01

    Full Text Available Motor memory is the process by which humans can adopt both persistent and flexible motor behaviours. Persistence and flexibility can be assessed through the examination of the cooperation/competition between new and old motor routines in the motor memory repertoire. Two paradigms seem to be particularly relevant to examine this competition/cooperation. First, a manual search task for hidden objects, namely the C-not-B task, which allows examining how a motor routine may influence the selection of action in toddlers. The second paradigm is procedural learning, and more precisely the consolidation stage, which allows assessing how a previously learnt motor routine becomes resistant to subsequent programming or learning of a new – competitive – motor routine. The present article defends the idea that results of both paradigms give precious information to understand the evolution of motor routines in healthy children. Moreover, these findings echo some clinical observations in developmental neuropsychology, particularly in children with Developmental Coordination Disorder. Such studies suggest that the level of equilibrium between persistence and flexibility of motor routines is an index of the maturity of the motor system.

  10. The role of motor memory in action selection and procedural learning: insights from children with typical and atypical development.

    Science.gov (United States)

    Tallet, Jessica; Albaret, Jean-Michel; Rivière, James

    2015-01-01

    Motor memory is the process by which humans can adopt both persistent and flexible motor behaviours. Persistence and flexibility can be assessed through the examination of the cooperation/competition between new and old motor routines in the motor memory repertoire. Two paradigms seem to be particularly relevant to examine this competition/cooperation. First, a manual search task for hidden objects, namely the C-not-B task, which allows examining how a motor routine may influence the selection of action in toddlers. The second paradigm is procedural learning, and more precisely the consolidation stage, which allows assessing how a previously learnt motor routine becomes resistant to subsequent programming or learning of a new - competitive - motor routine. The present article defends the idea that results of both paradigms give precious information to understand the evolution of motor routines in healthy children. Moreover, these findings echo some clinical observations in developmental neuropsychology, particularly in children with Developmental Coordination Disorder. Such studies suggest that the level of equilibrium between persistence and flexibility of motor routines is an index of the maturity of the motor system.

  11. Process signal selection method to improve the impact mitigation of sensor broken for diagnosis using machine learning

    International Nuclear Information System (INIS)

    Minowa, Hirotsugu; Gofuku, Akio

    2014-01-01

    Accidents of industrial plants cause large loss on human, economic, social credibility. In recent, studies of diagnostic methods using techniques of machine learning are expected to detect early and correctly abnormality occurred in a plant. However, the general diagnostic machines are generated generally to require all process signals (hereafter, signals) for plant diagnosis. Thus if trouble occurs such as process sensor is broken, the diagnostic machine cannot diagnose or may decrease diagnostic performance. Therefore, we propose an important process signal selection method to improve impact mitigation without reducing the diagnostic performance by reducing the adverse effect of noises on multi-agent diagnostic system. The advantage of our method is the general-purpose property that allows to be applied to various supervised machine learning and to set the various parameters to decide termination of search. The experiment evaluation revealed that diagnostic machines generated by our method using SVM improved the impact mitigation and did not reduce performance about the diagnostic accuracy, the velocity of diagnosis, predictions of plant state near accident occurrence, in comparison with the basic diagnostic machine which diagnoses by using all signals. This paper reports our proposed method and the results evaluated which our method was applied to the simulated abnormal of the fast-breeder reactor Monju. (author)

  12. Reversal of age-related learning deficiency by the vertebrate PACAP and IGF-1 in a novel invertebrate model of aging: the pond snail (Lymnaea stagnalis).

    Science.gov (United States)

    Pirger, Zsolt; Naskar, Souvik; László, Zita; Kemenes, György; Reglődi, Dóra; Kemenes, Ildikó

    2014-11-01

    With the increase of life span, nonpathological age-related memory decline is affecting an increasing number of people. However, there is evidence that age-associated memory impairment only suspends, rather than irreversibly extinguishes, the intrinsic capacity of the aging nervous system for plasticity (1). Here, using a molluscan model system, we show that the age-related decline in memory performance can be reversed by administration of the pituitary adenylate cyclase activating polypeptide (PACAP). Our earlier findings showed that a homolog of the vertebrate PACAP38 and its receptors exist in the pond snail (Lymnaea stagnalis) brain (2), and it is both necessary and instructive for memory formation after reward conditioning in young animals (3). Here we show that exogenous PACAP38 boosts memory formation in aged Lymnaea, where endogenous PACAP38 levels are low in the brain. Treatment with insulin-like growth factor-1, which in vertebrates was shown to transactivate PACAP type I (PAC1) receptors (4) also boosts memory formation in aged pond snails. Due to the evolutionarily conserved nature of these polypeptides and their established role in memory and synaptic plasticity, there is a very high probability that they could also act as "memory rejuvenating" agents in humans. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America.

  13. Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors.

    Science.gov (United States)

    Rivera-Borroto, Oscar Miguel; Marrero-Ponce, Yovani; García-de la Vega, José Manuel; Grau-Ábalo, Ricardo del Corazón

    2011-12-27

    Cluster algorithms play an important role in diversity related tasks of modern chemoinformatics, with the widest applications being in pharmaceutical industry drug discovery programs. The performance of these grouping strategies depends on various factors such as molecular representation, mathematical method, algorithmical technique, and statistical distribution of data. For this reason, introduction and comparison of new methods are necessary in order to find the model that best fits the problem at hand. Earlier comparative studies report on Ward's algorithm using fingerprints for molecular description as generally superior in this field. However, problems still remain, i.e., other types of numerical descriptions have been little exploited, current descriptors selection strategy is trial and error-driven, and no previous comparative studies considering a broader domain of the combinatorial methods in grouping chemoinformatic data sets have been conducted. In this work, a comparison between combinatorial methods is performed,with five of them being novel in cheminformatics. The experiments are carried out using eight data sets that are well established and validated in the medical chemistry literature. Each drug data set was represented by real molecular descriptors selected by machine learning techniques, which are consistent with the neighborhood principle. Statistical analysis of the results demonstrates that pharmacological activities of the eight data sets can be modeled with a few of families with 2D and 3D molecular descriptors, avoiding classification problems associated with the presence of nonrelevant features. Three out of five of the proposed cluster algorithms show superior performance over most classical algorithms and are similar (or slightly superior in the most optimistic sense) to Ward's algorithm. The usefulness of these algorithms is also assessed in a comparative experiment to potent QSAR and machine learning classifiers, where they perform

  14. The readiness of teachers to integrate information and communication technology for learning in a selected school in the GautengOnline project.

    OpenAIRE

    2008-01-01

    This study is aimed at providing the reader with a detailed description of the readiness of teachers to integrate Information and Communication Technology (ICT) for learning in a selected school in the GautengOnline (GoL) Project, through qualitative research design that used various data collecting methods: Questionnaire, observations and interview. A large number of teachers showed some interest in using ICT learning but had difficulties on how to get started due to the lack of suitable ICT...

  15. Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation

    Science.gov (United States)

    Tangaro, Sabina; Amoroso, Nicola; Brescia, Massimo; Cavuoti, Stefano; Chincarini, Andrea; Errico, Rosangela; Paolo, Inglese; Longo, Giuseppe; Maglietta, Rosalia; Tateo, Andrea; Riccio, Giuseppe; Bellotti, Roberto

    2015-01-01

    Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic resonance imaging (MRI) scans can show these variations and therefore can be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust, and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach; for each voxel a number of local features were calculated. In this paper, we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) sequential forward selection and (iii) sequential backward elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 feature for each voxel (sequential backward elimination) we obtained comparable state-of-the-art performances with respect to the standard tool FreeSurfer.

  16. Machine learning in infrared object classification - an all-sky selection of YSO candidates

    Science.gov (United States)

    Marton, Gabor; Zahorecz, Sarolta; Toth, L. Viktor; Magnus McGehee, Peregrine; Kun, Maria

    2015-08-01

    Object classification is a fundamental and challenging problem in the era of big data. I will discuss up-to-date methods and their application to classify infrared point sources.We analysed the ALLWISE catalogue, the most recent public source catalogue of the Wide-field Infrared Survey Explorer (WISE) to compile a reliable list of Young Stellar Object (YSO) candidates. We tested and compared classical and up-to-date statistical methods as well, to discriminate source types like extragalactic objects, evolved stars, main sequence stars, objects related to the interstellar medium and YSO candidates by using their mid-IR WISE properties and associated near-IR 2MASS data.In the particular classification problem the Support Vector Machines (SVM), a class of supervised learning algorithm turned out to be the best tool. As a result we classify Class I and II YSOs with >90% accuracy while the fraction of contaminating extragalactic objects remains well below 1%, based on the number of known objects listed in the SIMBAD and VizieR databases. We compare our results to other classification schemes from the literature and show that the SVM outperforms methods that apply linear cuts on the colour-colour and colour-magnitude space. Our homogenous YSO candidate catalog can serve as an excellent pathfinder for future detailed observations of individual objects and a starting point of statistical studies that aim to add pieces to the big picture of star formation theory.

  17. Dissecting children's observational learning of complex actions through selective video displays.

    Science.gov (United States)

    Flynn, Emma; Whiten, Andrew

    2013-10-01

    Children can learn how to use complex objects by watching others, yet the relative importance of different elements they may observe, such as the interactions of the individual parts of the apparatus, a model's movements, and desirable outcomes, remains unclear. In total, 140 3-year-olds and 140 5-year-olds participated in a study where they observed a video showing tools being used to extract a reward item from a complex puzzle box. Conditions varied according to the elements that could be seen in the video: (a) the whole display, including the model's hands, the tools, and the box; (b) the tools and the box but not the model's hands; (c) the model's hands and the tools but not the box; (d) only the end state with the box opened; and (e) no demonstration. Children's later attempts at the task were coded to establish whether they imitated the hierarchically organized sequence of the model's actions, the action details, and/or the outcome. Children's successful retrieval of the reward from the box and the replication of hierarchical sequence information were reduced in all but the whole display condition. Only once children had attempted the task and witnessed a second demonstration did the display focused on the tools and box prove to be better for hierarchical sequence information than the display focused on the tools and hands only. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Selected chapters from general chemistry in physics teaching with the help of e - learning

    Science.gov (United States)

    Feszterová, Melánia

    2017-01-01

    Education in the field of natural disciplines - Mathematics, Physics, Chemistry, Ecology and Biology takes part in general education at all schools on the territory of Slovakia. Its aim is to reach the state of balanced development of all personal characteristics of pupils, to teach them correctly identify and analyse problems, propose solutions and above all how to solve the problem itself. High quality education can be reached only through the pedagogues who have a good expertise knowledge, practical experience and high level of pedagogical abilities. The teacher as a disseminator of natural-scientific knowledge should be not only well-informed about modern tendencies in the field, but he/she also should actively participate in project tasks This is the reason why students of 1st year of study (bachelor degree) at the Department of Physics of Constantine the Philosopher University in Nitra attend lectures in the frame of subject General Chemistry. In this paper we present and describe an e - learning course called General Chemistry that is freely accessible to students. One of the aims of this course is to attract attention towards the importance of cross-curricular approach which seems to be fundamental in contemporary natural-scientific education (e.g. between Physics and Chemistry). This is why it is so important to implement a set of new topics and tasks that support development of abilities to realise cross-curricular goals into the process of preparation of future teachers of Physics.

  19. Reversible flowchart languages and the structured reversible program theorem

    DEFF Research Database (Denmark)

    Yokoyama, Tetsuo; Axelsen, Holger Bock; Glück, Robert

    2008-01-01

    Many irreversible computation models have reversible counterparts, but these are poorly understood at present. We introduce reversible flowcharts with an assertion operator and show that any reversible flowchart can be simulated by a structured reversible flowchart using only three control flow...... operators. Reversible flowcharts are r- Turing-complete, meaning that they can simuluate reversible Turing machines without garbage data. We also demonstrate the injectivization of classical flowcharts into reversible flowcharts. The reversible flowchart computation model provides a theoretical...

  20. Lexical selection in the semantically blocked cyclic naming task: The role of cognitive control and learning

    Directory of Open Access Journals (Sweden)

    Jason E. Crowther

    2014-01-01

    Full Text Available Studies of semantic interference in language production have provided evidence for a role of cognitive control mechanisms in regulating the activation of semantic competitors during naming. The present study investigated the relationship between individual differences in cognitive control abilities, for both younger and older adults, and the degree of semantic interference in a blocked cyclic naming task. We predicted that individuals with lower working memory capacity (as measured by word span, lesser ability to inhibit distracting responses (as measured by Stroop interference, and a lesser ability to resolve proactive interference (as measured by a recent negatives task would show a greater increase in semantic interference in naming, with effects being larger for older adults. Instead, measures of cognitive control were found to relate to specific indices of semantic interference in the naming task, rather than overall degree of semantic interference, and few interactions with age were found, with younger and older adults performing similarly. The increase in naming latencies across naming trials within a cycle were negatively correlated with word span for both related and unrelated conditions, suggesting a strategy of narrowing response alternatives based upon memory for the set of item names. Evidence for a role of inhibition in response selection was obtained, as Stroop interference correlated positively with the change in naming latencies across cycles for the related, but not unrelated, condition. In contrast, recent negatives interference correlated negatively with the change in naming latencies across unrelated cycles, suggesting that individual differences in this tap the degree of strengthening of links in a lexical network based upon prior exposure. Results are discussed in terms of current models of lexical selection and consequences for word retrieval in more naturalistic production.

  1. Gender differences in technology acceptance in selected South African companies: Implications for electronic learning

    Directory of Open Access Journals (Sweden)

    Willie T. Chinyamurindi

    2010-11-01

    Research: The objective of this study was to investigate trainees’ acceptance of electronic coursework as an instruction and learning technique in various industries in the South African context. Motivation for the study: A persistent gender imbalance in the South African work-place has been noted to exist chiefly in the Science, Engineering and Technology (SET sectors, areas that have an important bearing on South Africa’s global competitiveness. This study explores how gender imbalance manifests in terms of trainee acceptance of electronic coursework. Research design, approach and method: A cross-sectional survey design was used. A survey was conducted amongst 191 employees in the SET sector. The measuring instrument used was the Technology Acceptance Instrument (TAI and included measures of Computer Self-Efficacy (CSE, Perceived Ease of Use (PEU, Perceived Usefulness (PU and Behavioural Intention to Use (BI. Main findings: Women ratings of the TAI to use the electronic coursework were slightly higher than men’s ratings. Multiple regression analyses were also carried out to measure the variation in the level of influence with gender as a predictor variable. The results showed that compared to women, men had a lower salient effect of elements of the TAI, notably, CSE–PU; PU–BI and BI–PEU. However, compared to men, women had a higher salient effect in terms of the relationship between CSE–PU and PU–PEU. Practical implications: The implication of the results is that interventions that focus on the human resources development of employees using electronic coursework (namely, CSE, PEU, PU and BI are worth considering as they influence the acceptance of the interventions. Contribution/value-add: The study contributes to existing knowledge about the conditions that precede employee acceptance of an electronic coursework intervention within the South African context. The study shows the important role dimensions of the Technology Acceptance Instrument

  2. Selective influence of prior allocentric knowledge on the kinesthetic learning of a path.

    Science.gov (United States)

    Lafon, Matthieu; Vidal, Manuel; Berthoz, Alain

    2009-04-01

    Spatial cognition studies have described two main cognitive strategies involved in the memorization of traveled paths in human navigation. One of these strategies uses the action-based memory (egocentric) of the traveled route or paths, which involves kinesthetic memory, optic flow, and episodic memory, whereas the other strategy privileges a survey memory of cartographic type (allocentric). Most studies have dealt with these two strategies separately, but none has tried to show the interaction between them in spite of the fact that we commonly use a map to imagine our journey and then proceed using egocentric navigation. An interesting question is therefore: how does prior allocentric knowledge of the environment affect the egocentric, purely kinesthetic navigation processes involved in human navigation? We designed an experiment in which blindfolded subjects had first to walk and memorize a path with kinesthetic cues only. They had previously been shown a map of the path, which was either correct or distorted (consistent shrinking or growing). The latter transformations were studied in order to observe what influence a distorted prior knowledge could have on spatial mechanisms. After having completed the first learning travel along the path, they had to perform several spatial tasks during the testing phase: (1) pointing towards the origin and (2) to specific points encountered along the path, (3) a free locomotor reproduction, and (4) a drawing of the memorized path. The results showed that prior cartographic knowledge influences the paths drawn and the spatial inference capacity, whereas neither locomotor reproduction nor spatial updating was disturbed. Our results strongly support the notion that (1) there are two independent neural bases underlying these mechanisms: a map-like representation allowing allocentric spatial inferences, and a kinesthetic memory of self-motion in space; and (2) a common use of, or a switching between, these two strategies is

  3. A Selective Role for Dopamine in Learning to Maximize Reward But Not to Minimize Effort: Evidence from Patients with Parkinson's Disease.

    Science.gov (United States)

    Skvortsova, Vasilisa; Degos, Bertrand; Welter, Marie-Laure; Vidailhet, Marie; Pessiglione, Mathias

    2017-06-21

    Instrumental learning is a fundamental process through which agents optimize their choices, taking into account various dimensions of available options such as the possible reward or punishment outcomes and the costs associated with potential actions. Although the implication of dopamine in learning from choice outcomes is well established, less is known about its role in learning the action costs such as effort. Here, we tested the ability of patients with Parkinson's disease (PD) to maximize monetary rewards and minimize physical efforts in a probabilistic instrumental learning task. The implication of dopamine was assessed by comparing performance ON and OFF prodopaminergic medication. In a first sample of PD patients ( n = 15), we observed that reward learning, but not effort learning, was selectively impaired in the absence of treatment, with a significant interaction between learning condition (reward vs effort) and medication status (OFF vs ON). These results were replicated in a second, independent sample of PD patients ( n = 20) using a simplified version of the task. According to Bayesian model selection, the best account for medication effects in both studies was a specific amplification of reward magnitude in a Q-learning algorithm. These results suggest that learning to avoid physical effort is independent from dopaminergic circuits and strengthen the general idea that dopaminergic signaling amplifies the effects of reward expectation or obtainment on instrumental behavior. SIGNIFICANCE STATEMENT Theoretically, maximizing reward and minimizing effort could involve the same computations and therefore rely on the same brain circuits. Here, we tested whether dopamine, a key component of reward-related circuitry, is also implicated in effort learning. We found that patients suffering from dopamine depletion due to Parkinson's disease were selectively impaired in reward learning, but not effort learning. Moreover, anti-parkinsonian medication restored the

  4. Strong and Reversible Monovalent Supramolecular Protein Immobilization

    NARCIS (Netherlands)

    Young, Jacqui F.; Nguyen, Hoang D.; Yang, Lanti; Huskens, Jurriaan; Jonkheijm, Pascal; Brunsveld, Luc

    2010-01-01

    Proteins with an iron clasp: Site-selective incorporation of a ferrocene molecule into a protein allows for easy, strong, and reversible supramolecular protein immobilization through a selective monovalent interaction of the ferrocene with a cucurbit[7]uril immobilized on a gold surface. The

  5. Introduction to reversible computing

    CERN Document Server

    Perumalla, Kalyan S

    2013-01-01

    Few books comprehensively cover the software and programming aspects of reversible computing. Filling this gap, Introduction to Reversible Computing offers an expanded view of the field that includes the traditional energy-motivated hardware viewpoint as well as the emerging application-motivated software approach. Collecting scattered knowledge into one coherent account, the book provides a compendium of both classical and recently developed results on reversible computing. It explores up-and-coming theories, techniques, and tools for the application of rever

  6. Distinction of synthetic dl-α-tocopherol from natural vitamin E (d-α-tocopherol) by reversed-phase liquid chromatography. Enhanced selectivity of a polymeric C18 stationary phase at low temperature and/or at high pressure.

    Science.gov (United States)

    Yui, Yuko; Miyazaki, Shota; Ma, Yan; Ohira, Masayoshi; Fiehn, Oliver; Ikegami, Tohru; McCalley, David V; Tanaka, Nobuo

    2016-06-10

    Separation of diastereomers of dl-α-tocopherol was studied by reversed-phase liquid chromatography using three types of stationary phases, polymeric ODS, polymeric C30, and monomeric ODS. Polymeric ODS stationary phase (Inertsil ODS-P, 3mmID, 20cm) was effective for the separation of the isomers created by the presence of three chiral centers on the alkyl chain of synthetic dl-α-tocopherol. Considerable improvement of the separation of isomers was observed on ODS-P phase at high pressure and at low temperature. Complete separation of four pairs of diastereomers was achieved at 12.0°C, 536bar, while three peaks were observed when the separation was carried out either at 12.0°C at low pressure or at 20°C at 488bar. Higher temperature (30.0°C) with the ODS-P phase resulted in only partial separation of the diastereomers even at high pressure. Only slight resolution was observed for the mixture of diastereomers with the C30 stationary phase (Inertsil C30) at 12.0°C and 441bar, although the stationary phase afforded greater resolution for β- and γ-tocopherol than ODS-P. A monomeric C18 stationary phase did not show any separation at 12.0°C and 463bar. The results suggest that the binding site of the polymeric ODS-P phase is selective for flexible alkyl chains that provided the longest retention for the natural form, (R,R,R) form, and the enantiomer, (S,S,S) form, of dl-α-tocopherol. Copyright © 2016. Published by Elsevier B.V.

  7. Modified Borohydrides for Reversible Hydrogen Storage (2)

    International Nuclear Information System (INIS)

    Ming Au

    2006-01-01

    This paper reports the results in the effort to destabilize lithium borohydride for reversible hydrogen storage. A number of metals, metal hydrides, metal chlorides and complex hydrides were selected and evaluated as the destabilization agents for reducing de-hydriding temperature and generating de-hydriding-re-hydriding reversibility. It is found that some additives are effective. The Raman spectroscopic analysis shows the change of B-H binding nature. (authors)

  8. Depletion of Serotonin Selectively Impairs Short-Term Memory without Affecting Long-Term Memory in Odor Learning in the Terrestrial Slug "Limax Valentianus"

    Science.gov (United States)

    Santa, Tomofumi; Kirino, Yutaka; Watanabe, Satoshi; Shirahata, Takaaki; Tsunoda, Makoto

    2006-01-01

    The terrestrial slug "Limax" is able to acquire short-term and long-term memories during aversive odor-taste associative learning. We investigated the effect of the selective serotonergic neurotoxin 5,7-dihydroxytryptamine (5,7-DHT) on memory. Behavioral studies indicated that 5,7-DHT impaired short-term memory but not long-term memory. HPLC…

  9. Contribution of Personality to Self-Efficacy and Outcome Expectations in Selecting a High School Major among Adolescents with Learning Disabilities

    Science.gov (United States)

    Brown, Dikla; Cinamon, Rachel Gali

    2016-01-01

    The current study focuses on the contribution of five personality traits to the development of self-efficacy and outcome expectations regarding selecting a high school major among adolescents with learning disabilities (LD). Social cognitive career theory and the Big Five personality traits model served as the theoretical framework. Participants…

  10. Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia.

    Science.gov (United States)

    Gabryś, Hubert S; Buettner, Florian; Sterzing, Florian; Hauswald, Henrik; Bangert, Mark

    2018-01-01

    The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands. A cohort of 153 head-and-neck cancer patients was used to model xerostomia at 0-6 months (early), 6-15 months (late), 15-24 months (long-term), and at any time (a longitudinal model) after radiotherapy. Predictive power of the features was evaluated by the area under the receiver operating characteristic curve (AUC) of univariate logistic regression models. The multivariate NTCP models were tuned and tested with single and nested cross-validation, respectively. We compared predictive performance of seven classification algorithms, six feature selection methods, and ten data cleaning/class balancing techniques using the Friedman test and the Nemenyi post hoc analysis. NTCP models based on the parotid mean dose failed to predict xerostomia (AUCs  0.85), dose gradients in the right-left (AUCs > 0.78), and the anterior-posterior (AUCs > 0.72) direction. Multivariate models of long-term xerostomia were typically based on the parotid volume, the parotid eccentricity, and the dose-volume histogram (DVH) spread with the generalization AUCs ranging from 0.74 to 0.88. On average, support vector machines and extra-trees were the top performing classifiers, whereas the algorithms based on logistic regression were the best choice for feature selection. We found no advantage in using data cleaning or class balancing methods. We demonstrated that incorporation of organ- and dose-shape descriptors is beneficial for xerostomia prediction in highly conformal radiotherapy treatments. Due to strong reliance on patient-specific, dose-independent factors, our results underscore the need for development of personalized data-driven risk profiles for NTCP models of xerostomia. The facilitated

  11. Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia

    Directory of Open Access Journals (Sweden)

    Hubert S. Gabryś

    2018-03-01

    Full Text Available PurposeThe purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP models based on the mean radiation dose to parotid glands.Material and methodsA cohort of 153 head-and-neck cancer patients was used to model xerostomia at 0–6 months (early, 6–15 months (late, 15–24 months (long-term, and at any time (a longitudinal model after radiotherapy. Predictive power of the features was evaluated by the area under the receiver operating characteristic curve (AUC of univariate logistic regression models. The multivariate NTCP models were tuned and tested with single and nested cross-validation, respectively. We compared predictive performance of seven classification algorithms, six feature selection methods, and ten data cleaning/class balancing techniques using the Friedman test and the Nemenyi post hoc analysis.ResultsNTCP models based on the parotid mean dose failed to predict xerostomia (AUCs < 0.60. The most informative predictors were found for late and long-term xerostomia. Late xerostomia correlated with the contralateral dose gradient in the anterior–posterior (AUC = 0.72 and the right–left (AUC = 0.68 direction, whereas long-term xerostomia was associated with parotid volumes (AUCs > 0.85, dose gradients in the right–left (AUCs > 0.78, and the anterior–posterior (AUCs > 0.72 direction. Multivariate models of long-term xerostomia were typically based on the parotid volume, the parotid eccentricity, and the dose–volume histogram (DVH spread with the generalization AUCs ranging from 0.74 to 0.88. On average, support vector machines and extra-trees were the top performing classifiers, whereas the algorithms based on logistic regression were the best choice for feature selection. We found no advantage in using data cleaning or class balancing

  12. Reversal of laryngotracheal separation in paediatric patients.

    LENUS (Irish Health Repository)

    Young, Orla

    2012-02-01

    OBJECTIVE: Laryngotracheal separation (LTS) is an effective and reliable definitive treatment for intractable aspiration. A major advantage of this treatment for intractable aspiration is its\\' potential reversibility. Should the underlying disorder improve, a reversal of the procedure may be attempted. This has been successfully achieved in the adult population. To our knowledge, no previous cases have been reported of successful reversal of LTS in children. METHODS: A retrospective review from 2003 to 2010 identified four cases of intractable aspiration treated with LTS in our department. Two of these patients displayed objective evidence of sufficient recovery of their underlying aspiration to consider reversal. Patient selection for reversal was dependent upon successful oral intake for 9 months along with videofluoroscopic evidence of normal or minimally impaired swallow. RESULTS: Two children who were successfully treated for intractable aspiration with LTS demonstrated objective evidence of recovery sufficient to attempt reversal. Both children underwent successful surgical reversal of LTS using a cricotracheal resection with end-to-end anastamosis, similar to that used in treatment of subglottic stenosis. Both children can now tolerate oral diet and their speech and language development is in line with their overall developmental level. CONCLUSIONS: Laryngotracheal separation is an effective and reliable definitive treatment for intractable aspiration facilitating protection of the airway and allowing safe swallowing with unimpeded respiration, but with the major drawback of loss of phonation. To our knowledge, we document the first two cases of successful LTS reversal in children.

  13. Quantum reverse hypercontractivity

    Energy Technology Data Exchange (ETDEWEB)

    Cubitt, Toby [Department of Computer Science, University College London, London, United Kingdom and Centre for Quantum Information and Foundations, DAMTP, University of Cambridge, Cambridge (United Kingdom); Kastoryano, Michael [NBIA, Niels Bohr Institute, University of Copenhagen, 2100 Copenhagen (Denmark); Montanaro, Ashley [School of Mathematics, University of Bristol, Bristol (United Kingdom); Temme, Kristan [Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, California 91125 (United States)

    2015-10-15

    We develop reverse versions of hypercontractive inequalities for quantum channels. By generalizing classical techniques, we prove a reverse hypercontractive inequality for tensor products of qubit depolarizing channels. We apply this to obtain a rapid mixing result for depolarizing noise applied to large subspaces and to prove bounds on a quantum generalization of non-interactive correlation distillation.

  14. Atrioventricular Pacemaker Lead Reversal

    Directory of Open Access Journals (Sweden)

    Mehmet K Aktas, MD

    2007-01-01

    Full Text Available During cardiac surgery temporary epicardial atrial and ventricular leads are placed in case cardiac pacing is required postoperatively. We present the first reported series of patients with reversal of atrioventricular electrodes in the temporary pacemaker without any consequent deleterious hemodynamic effect. We review the electrocardiographic findings and discuss the findings that lead to the discovery of atrioventricular lead reversal.

  15. Sodium p-Aminosalicylic Acid Reverses Sub-Chronic Manganese-Induced Impairments of Spatial Learning and Memory Abilities in Rats, but Fails to Restore γ-Aminobutyric Acid Levels

    Science.gov (United States)

    Li, Shao-Jun; Ou, Chao-Yan; He, Sheng-Nan; Huang, Xiao-Wei; Luo, Hai-Lan; Meng, Hao-Yang; Lu, Guo-Dong; Jiang, Yue-Ming; Vieira Peres, Tanara; Luo, Yi-Ni; Deng, Xiang-Fa

    2017-01-01

    Excessive manganese (Mn) exposure is not only a health risk for occupational workers, but also for the general population. Sodium para-aminosalicylic acid (PAS-Na) has been successfully used in the treatment of manganism, but the involved molecular mechanisms have yet to be determined. The present study aimed to investigate the effects of PAS-Na on sub-chronic Mn exposure-induced impairments of spatial learning and memory, and determine the possible involvements of γ-aminobutyric acid (GABA) metabolism in vivo. Sprague-Dawley male rats received daily intraperitoneal injections MnCl2 (as 6.55 mg/kg Mn body weight, five days per week for 12 weeks), followed by daily subcutaneous injections of 100, 200, or 300 mg/kg PAS-Na for an additional six weeks. Mn exposure significantly impaired spatial learning and memory ability, as noted in the Morris water maze test, and the following PAS-Na treatment successfully restored these adverse effects to levels indistinguishable from controls. Unexpectedly, PAS-Na failed to recover the Mn-induced decrease in the overall GABA levels, although PAS-Na treatment reversed Mn-induced alterations in the enzyme activities directly responsible for the synthesis and degradation of GABA (glutamate decarboxylase and GABA-transaminase, respectively). Moreover, Mn exposure caused an increase of GABA transporter 1 (GAT-1) and decrease of GABA A receptor (GABAA) in transcriptional levels, which could be reverted by the highest dose of 300 mg/kg PAS-Na treatment. In conclusion, the GABA metabolism was interrupted by sub-chronic Mn exposure. However, the PAS-Na treatment mediated protection from sub-chronic Mn exposure-induced neurotoxicity, which may not be dependent on the GABA metabolism. PMID:28394286

  16. Strains and Stressors: An Analysis of Touchscreen Learning in Genetically Diverse Mouse Strains

    Science.gov (United States)

    Graybeal, Carolyn; Bachu, Munisa; Mozhui, Khyobeni; Saksida, Lisa M.; Bussey, Timothy J.; Sagalyn, Erica; Williams, Robert W.; Holmes, Andrew

    2014-01-01

    Touchscreen-based systems are growing in popularity as a tractable, translational approach for studying learning and cognition in rodents. However, while mouse strains are well known to differ in learning across various settings, performance variation between strains in touchscreen learning has not been well described. The selection of appropriate genetic strains and backgrounds is critical to the design of touchscreen-based studies and provides a basis for elucidating genetic factors moderating behavior. Here we provide a quantitative foundation for visual discrimination and reversal learning using touchscreen assays across a total of 35 genotypes. We found significant differences in operant performance and learning, including faster reversal learning in DBA/2J compared to C57BL/6J mice. We then assessed DBA/2J and C57BL/6J for differential sensitivity to an environmental insult by testing for alterations in reversal learning following exposure to repeated swim stress. Stress facilitated reversal learning (selectively during the late stage of reversal) in C57BL/6J, but did not affect learning in DBA/2J. To dissect genetic factors underlying these differences, we phenotyped a family of 27 BXD strains generated by crossing C57BL/6J and DBA/2J. There was marked variation in discrimination, reversal and extinction learning across the BXD strains, suggesting this task may be useful