18 resultados para Associative Classifier

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The use of stones to crack open encapsulated fruit is widespread among wild bearded capuchin monkeys (Cebus libidinosus) inhabiting savanna-like environments. Some populations in Serra da Capivara National Park (Piaui, Brazil), though, exhibit a seemingly broader toolkit, using wooden sticks as probes, and employing stone tools for a variety of purposes. Over the course of 701.5 hr of visual contact of two wild capuchin groups we recorded 677 tool use episodes. Five hundred and seventeen of these involved the use of stones, and 160 involved the use of sticks (or other plant parts) as probes to access water, arthropods, or the contents of insects` nests. Stones were mostly used as ""hammers""-not only to open fruit or seeds, or smash other food items, but also to break dead wood, conglomerate rock, or cement in search of arthropods, to dislodge bigger stones, and to pulverize embedded quartz pebbles (licking, sniffing, or rubbing the body with the powder produced). Stones also were used in a ""hammer-like"" fashion to loosen the soil for digging out roots and arthropods, and sometimes as ""hoes"" to pull the loosened soil. In a few cases, we observed the re-utilization of stone tools for different purposes (N = 3), or the combined use of two tools-stones and sticks (N = 4) or two stones (N = 5), as sequential or associative tools. On three occasions, the monkeys used smaller stones to loosen bigger quartz pebbles embedded in conglomerate rock, which were subsequently used as tools. These could be considered the first reports of secondary tool use by wild capuchin monkeys. Am. J. Primatol. 71:242-251, 2009. (c) 2008 Wiley-Liss, Inc.

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The present experiment investigated whether pigeons can show associative symmetry on a two-alternative matching to-sample procedure The procedure consisted of a within subject sequence of training and testing with reinforcement and It provided (a) exemplars of symmetrical responding and (b) all prerequisite discriminations among test samples and comparisons After pigeons had learned two arbitrary matching tasks (A B and C D) they were given a reinforced symmetry test for half of the baseline relations (B1-A1 and D1-C1) To control for the effects of reinforcement during testing two novel nonsymmetrical responses were concurrently reinforced using the other baseline stimuli (D2-A2 and B2-C2) Pigeons matched at chance on both types of relations thus indicating no evidence for symmetry These symmetrical and nonsymmetrical relations were then directly trained in order to provide exemplars of symmetry and all prerequisite discriminations for a second test The symmetrical test relations were now B2-A2 and D2-C2 and the nonsymmetrical relations were D1-A1 and B1-C1 On this test 1 pigeon showed clear evidence of symmetry 2 pigeons showed weak evidence and 1 pigeon showed no evidence The previous training of all prerequisite discriminations among stimuli and the within subject control for testing with reinforcement seem to have set favorable conditions for the emergence of symmetry in nonhumans However the variability across subjects shows that methodological variables still remain to be controlled

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Abstract Background Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall. Methods Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration. Results Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks. Conclusion It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object.

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The associationist account for early word learning is based on the co-occurrence between referents and words. Here we introduce a noisy cross-situational learning scenario in which the referent of the uttered word is eliminated from the context with probability gamma, thus modeling the noise produced by out-of-context words. We examine the performance of a simple associative learning algorithm and find a critical value of the noise parameter gamma(c) above which learning is impossible. We use finite-size scaling to show that the sharpness of the transition persists across a region of order tau(-1/2) about gamma(c), where tau is the number of learning trials, as well as to obtain the learning error (scaling function) in the critical region. In addition, we show that the distribution of durations of periods when the learning error is zero is a power law with exponent -3/2 at the critical point. Copyright (C) EPLA, 2012

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The dorsolateral column of the periaqueductal gray (dlPAG) integrates aversive emotional experiences and represents an important site responding to life threatening situations, such as hypoxia, cardiac pain and predator threats. Previous studies have shown that the dorsal PAG also supports fear learning; and we have currently explored how the dlPAG influences associative learning. We have first shown that N-methyl-D-aspartate (NMDA) 100 pmol injection in the dlPAG works as a valuable unconditioned stimulus (US) for the acquisition of olfactory fear conditioning (OFC) using amyl acetate odor as conditioned stimulus (CS). Next, we revisited the ascending projections of the dlPAG to the thalamus and hypothalamus to reveal potential paths that could mediate associative learning during OFC. Accordingly, the most important ascending target of the dlPAG is the hypothalamic defensive circuit, and we were able to show that pharmacological inactivation using beta-adrenoceptor blockade of the dorsal premammillary nucleus, the main exit way for the hypothalamic defensive circuit to thalamo-cortical circuits involved in fear learning, impaired the acquisition of the OFC promoted by NMDA stimulation of the dlPAG. Moreover, our tracing study revealed multiple parallel paths from the dlPAG to several thalamic targets linked to cortical-hippocampal-amygdalar circuits involved in fear learning. Overall, the results point to a major role of the dlPAG in the mediation of aversive associative learning via ascending projections to the medial hypothalamic defensive circuit, and perhaps, to other thalamic targets, as well. These results provide interesting perspectives to understand how life threatening events impact on fear learning, and should be useful to understand pathological fear memory encoding in anxiety disorders.

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We use computer algebra to study polynomial identities for the trilinear operation [a, b, c] = abc - acb - bac + bca + cab - cba in the free associative algebra. It is known that [a, b, c] satisfies the alternating property in degree 3, no new identities in degree 5, a multilinear identity in degree 7 which alternates in 6 arguments, and no new identities in degree 9. We use the representation theory of the symmetric group to demonstrate the existence of new identities in degree 11. The only irreducible representations of dimension <400 with new identities correspond to partitions 2(5), 1 and 2(4), 1(3) and have dimensions 132 and 165. We construct an explicit new multilinear identity for partition 2(5), 1 and we demonstrate the existence of a new non-multilinear identity in which the underlying variables are permutations of a(2)b(2)c(2)d(2)e(2) f.

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The generalizations of Lie algebras appeared in the modern mathematics and mathematical physics. In this paper we consider recent developments and remaining open problems on the subject. Some of that developments have been influenced by lectures given by Professor Jaime Keller in his research seminar. The survey includes Lie superalgebras, color Lie algebras, Lie algebras in symmetric categories, free Lie tau-algebras, and some generalizations with non-associative enveloping algebras: tangent algebras to analytic loops, bialgebras and primitive elements, non-associative Hopf algebras.

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Alzheimer's disease (AD) is the most common cause of dementia in the human population, characterized by a spectrum of neuropathological abnormalities that results in memory impairment and loss of other cognitive processes as well as the presence of non-cognitive symptoms. Transcriptomic analyses provide an important approach to elucidating the pathogenesis of complex diseases like AD, helping to figure out both pre-clinical markers to identify susceptible patients and the early pathogenic mechanisms to serve as therapeutic targets. This study provides the gene expression profile of postmortem brain tissue from subjects with clinic-pathological AD (Braak IV, V, or V and CERAD B or C; and CDR >= 1), preclinical AD (Braak IV, V, or VI and CERAD B or C; and CDR = 0), and healthy older individuals (Braak <= II and CERAD 0 or A; and CDR = 0) in order to establish genes related to both AD neuropathology and clinical emergence of dementia. Based on differential gene expression, hierarchical clustering and network analysis, genes involved in energy metabolism, oxidative stress, DNA damage/repair, senescence, and transcriptional regulation were implicated with the neuropathology of AD; a transcriptional profile related to clinical manifestation of AD could not be detected with reliability using differential gene expression analysis, although genes involved in synaptic plasticity, and cell cycle seems to have a role revealed by gene classifier. In conclusion, the present data suggest gene expression profile changes secondary to the development of AD-related pathology and some genes that appear to be related to the clinical manifestation of dementia in subjects with significant AD pathology, making necessary further investigations to better understand these transcriptional findings on the pathogenesis and clinical emergence of AD.

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We examined the effects of listening to music on attentional focus, rating of perceived exertion (RPE), pacing strategy and performance during a simulated 5-km running race. 15 participants performed 2 controlled trials to establish their best baseline time, followed by 2 counterbalanced experimental trials during which they listened to music during the first (M-start) or the last (M-finish) 1.5 km. The mean running velocity during the first 1.5 km was significantly higher in M-start than in the fastest control condition (p < 0.05), but there was no difference in velocity between conditions during the last 1.5 km (p > 0.05). The faster first 1.5 m in M-start was accompanied by a reduction in associative thoughts compared with the fastest control condition. There were no significant differences in RPE between conditions (p > 0.05). These results suggest that listening to music at the beginning of a trial may draw the attentional focus away from internal sensations of fatigue to thoughts about the external environment. However, along with the reduction in associative thoughts and the increase in running velocity while listening to music, the RPE increased linearly and similarly under all conditions, suggesting that the change in velocity throughout the race may be to maintain the same rate of RPE increase.

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Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

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In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.

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The ability to entrap drugs within vehicles and subsequently release them has led to new treatments for a number of diseases. Based on an associative phase separation and interfacial diffusion approach, we developed a way to prepare DNA gel particles without adding any kind of cross-linker or organic solvent. Among the various agents studied, cationic surfactants offered particularly efficient control for encapsulation and DNA release from these DNA gel particles. The driving force for this strong association is the electrostatic interaction between the two components, as induced by the entropic increase due to the release of the respective counter-ions. However, little is known about the influence of the respective counter-ions on this surfactant-DNA interaction. Here we examined the effect of different counter-ions on the formation and properties of the DNA gel particles by mixing DNA (either single-(ssDNA) or double-stranded (dsDNA)) with the single chain surfactant dodecyltrimethylammonium (DTA). In particular, we used as counter-ions of this surfactant the hydrogen sulfate and trifluoromethane sulfonate anions and the two halides, chloride and bromide. Effects on the morphology of the particles obtained, the encapsulation of DNA and its release, as well as the haemocompatibility of these particles are presented, using counter-ion structure and DNA conformation as controlling parameters. Analysis of the data indicates that the degree of counter-ion dissociation from the surfactant micelles and the polar/hydrophobic character of the counter-ion are important parameters in the final properties of the particles. The stronger interaction with amphiphiles for ssDNA than for dsDNA suggests the important role of hydrophobic interactions in DNA.

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To identify a classifier in schizophrenia, blood gene expression profiling was applied to patients with schizophrenia under different treatments and to controls. Expression of six genes discriminated patients with sensitivity of 89.3% and specificity of 90%, supporting the use of peripheral blood as biological material for diagnosis in schizophrenia. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

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Premise of the study: A new set of microsatellite or simple sequence repeat (SSR) markers for garlic, an important medicinal spice, was developed to aid studies of genetic diversity and to define efficient strategies for germplasm conservation. Methods and Results: Using a (CT)(8)- and (GT)(8)-enriched library, a total of 16 SSR loci were developed and optimized in garlic. Ten loci were found to be polymorphic after screening 75 accessions. The parameters used to characterize the loci were observed and expected heterozygosity, number of alleles, Shannon Index, and polymorphism information content (PIC). A total of 44 alleles were identified, with an average of 4.4 alleles per loci. The vast majority of loci were moderate to highly informative according to PIC and the Shannon Index. Conclusion: The new SSR markers have the potential to be informative tools for genetic diversity, allele mining, mapping and associative studies, and in the management and conservation of garlic collections.