858 resultados para Automatic Recognition
Resumo:
In ovariectomized rats, administration of estradiol, or selective estrogen receptor agonists that activate either the alpha or beta isoforms, have been shown to enhance spatial cognition on a variety of learning and memory tasks, including those that capitalize on the preference of rats to seek out novelty. Although the effects of the putative estrogen G-protein-coupled receptor 30 (GPR30) on hippocampus-based tasks have been reported using food-motivated tasks, the effects of activation of GPR30 receptors on tasks that depend on the preference of rats to seek out spatial novelty remain to be determined. Therefore, the aim of the current study was to determine if short-term treatment of ovariectomized rats with G-1, an agonist for GPR30, would mimic the effects on spatial recognition memory observed following short-term estradiol treatment. In Experiment 1, ovariectomized rats treated with a low dose (1mug) of estradiol 48h and 24h prior to the information trial of a Y-maze task exhibited a preference for the arm associated with the novel environment on the retention trial conducted 48h later. In Experiment 2, treatment of ovariectomized rats with G-1 (25mug) 48h and 24h prior to the information trial of a Y-maze task resulted in a greater preference for the arm associated with the novel environment on the retention trial. Collectively, the results indicated that short-term treatment of ovariectomized rats with a GPR30 agonist was sufficient to enhance spatial recognition memory, an effect that also occurred following short-term treatment with a low dose of estradiol.
Resumo:
Charities need to understand why volunteers choose one brand rather than another in order to attract more volunteers to their organisation. There has been considerable academic interest in understanding why people volunteer generally. However, this research explores the more specific question of why a volunteer chooses one charity brand rather than another. It builds on previous conceptualisations of volunteering as a consumption decision. Seen through the lens of the individual volunteer, it considers the under-researched area of the decision-making process. The research adopts an interpretivist epistemology and subjectivist ontology. Qualitative data was collected through depth interviews and analysed using both Means-End Chain (MEC) and Framework Analysis methodology. The primary contribution of the research is to theory: understanding the role of brand in the volunteer decision-making process. It identifies two roles for brand. The first is as a specific reason for choice, an ‘attribute’ of the decision. Through MEC, volunteering for a well-known brand connects directly through to a sense of self, both self-respect but also social recognition by others. All four components of the symbolic consumption construct are found in the data: volunteers choose a well-known brand to say something about themselves. The brand brings credibility and reassurance, it reduces the risk and enables the volunteer to meet their need to make a difference and achieve a sense of accomplishment. The second closely related role for brand is within the process of making the volunteering decision. Volunteers built up knowledge about the charity brands from a variety of brand touchpoints, over time. At the point of decision-making that brand knowledge and engagement becomes relevant, enabling some to make an automatic choice despite the significant level of commitment being made. The research identifies four types of decision-making behaviour. The research also makes secondary contributions to MEC methodology and to the non-profit context. It concludes within practical implications for management practice and a rich agenda for future research.
Resumo:
Little is known about the way speech in noise is processed along the auditory pathway. The purpose of this study was to evaluate the relation between listening in noise using the R-Space system and the neurophysiologic response of the speech-evoked auditory brainstem when recorded in quiet and noise in adult participants with mild to moderate hearing loss and normal hearing.
Resumo:
The purpose of the present study was to evaluate the effects of bimodal (implant plus hearing aid) listening on speech recognition in four different environment conditions. Results indicate that there was little difference in the cochlear implant only and bimodal conditions.
Resumo:
Phacellophora camtschatica has long been assigned to the semaeostome scyphozoan family Ulmaridae. Early stages (scyphistomae, strobilae, ephyrae, postephyrae, and young medusae) of the species were compared with those of several other semaeostomes currently assigned to Ulmaridae, Pelagiidae, and Cyaneidae. Juveniles of P. camtschatica did not strictly conform with characters of those of any of these families, and appeared intermediate between Cyaneidae and Ulmaridae. A new family, Phacellophoridae, is proposed to accommodate P. camtschatica.
Resumo:
There is evidence that automatic visual attention favors the right side. This study investigated whether this lateral asymmetry interacts with the right hemisphere dominance for visual location processing and left hemisphere dominance for visual shape processing. Volunteers were tested in a location discrimination task and a shape discrimination task. The target stimuli (S2) could occur in the left or right hemifield. They were preceded by an ipsilateral, contralateral or bilateral prime stimulus (S1). The attentional effect produced by the right S1 was larger than that produced by the left S1. This lateral asymmetry was similar between the two tasks suggesting that the hemispheric asymmetries of visual mechanisms do not contribute to it. The finding that it was basically due to a longer reaction time to the left S2 than to the right S2 for the contralateral S1 condition suggests that the inhibitory component of attention is laterally asymmetric.
Resumo:
Mycoplasmal lipid-associated membrane proteins (LAMPs) and Mycoplasma arthritidis mitogen (MAM superantigen) are potent stimulators of the immune system. The objective of this work was to detect antibodies to MAM and LAMPs of Mycoplasma hominis and M. fermentans in the sera of patients affected by rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) to identify mycoplasmal products that can be involved in the etiopathogenesis of these autoimmune diseases. Serum samples from female RA and SLE patients and controls, recombinant MAM, and LAMPs of M. hominis PG21 and M. fermentans PG18 were used in Western blot assays. A similar frequency of sera from patients and controls reactive to MAM was detected. A larger number of M. hominis and M. fermentans LAMPs were recognized by sera from RA patients than controls, but no differences were detected between sera from SLE patients and controls. Among the LAMPs recognized by IgG antibodies from RA patients, proteins of molecular masses in a range of < 49 and a parts per thousand yen20 KDa (M. hominis) and < 102 and a parts per thousand yen58 KDa (M. fermentans) were the most reactive. These preliminary results demonstrate the strong reactivity of antibodies of RA patients with some M. hominis and M. fermentans LAMPs. These LAMPs could be investigated as mycoplasmal antigens that can take part in the induction or amplification of human autoimmune responses.
Resumo:
A modified version of the social habituation/dis-habituation paradigm was employed to examine social recognition memory in Wistar rats during two opposing (active and inactive) circadian phases, using different intertrial intervals (30 and 60 min). Wheel-running activity was monitored continuously to identify circadian phase. To avoid possible masking effects of the light-dark cycle, the rats were synchronized to a skeleton photoperiod, which allowed testing during different circadian phases under identical lighting conditions. In each trial, an infantile intruder was introduced into an adult`s home-cage for a 5-minute interaction session, and social behaviors were registered. Rats were exposed to 5 trials per day for 4 consecutive days: oil days I and 2, each resident was exposed to the same intruder; on days 3 and 4, each resident was exposed to a different intruder in each trial. I he resident`s social investigatory behavior was more intense when different intruders were presented compared to repeated presentation of the same intruder, suggesting social recognition memory. This effect was stronger when the rats were tested during the inactive phase and when the intertrial interval was 60 min, These findings Suggest that social recognition memory, as evaluated in this modified habituation/dis-habituation paradigm, is influenced by the circadian rhythm phase during which testing is performed, and by intertrial interval. (C) 2008 Elsevier Inc. All rights reserved.
Resumo:
Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.
Resumo:
Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.
Resumo:
This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.
Resumo:
The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.
Resumo:
Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.
Resumo:
A rational strategy was employed for design of an orthorhombic structure of lamivudine with maleic acid. On the basis of the lamivudine saccharinate structure reported in the literature, maleic acid was chosen to synthesize a salt with the anti-HIV drug because of the structural similarities between the salt formers. Maleic acid has an acid-ionization constant of the anti first proton and an arrangement of their hydrogen bonding functionalities similar to those of saccharin. Likewise, there is a saccharin-like conformational rigidity in maleic acid because of the hydrogen-bonded ring formation and the Z-configuration around the C=C double bond. As was conceivably predicted, lamivudine maleate assembles into a structure whose intermolecular architecture is related to that of saccharinate salt of the drug. Therefore, a molecular framework responsible for crystal assembly into a lamivudine saccharinate-like structure could be recognized in the salt formers. Furthermore, structural correlations and structure-solubility relationships were established for lamivudine maleate and saccharinate. Although there is a same molecular framework in maleic acid and saccharin, these salt formers are Structurally different in some aspects. When compared to saccharin, neither out-of-plane SO(2) oxygens nor a benzene group occur in maleic acid. Both features could be related to higher solubility of lamivudine maleate. Here, we also anticipate that multicomponent molecular crystals of lamivudine with other salt formers possessing the molecular framework responsible for crystal assembly can be engineered successfully.
Resumo:
A thermodynamic study involving 7-nitro-1,3,5-triaza adamantane, 1, and its interaction with metal cations in nonaqueous media is first reported. Solubility data of 1 in various solvents were used to derive the standard Gibbs energies of solution, Delta G(s)degrees in these solvents. The effect of solvation in the different media was assessed from the Gibbs energy of transfer taking acetonitrile as a reference solvent. (1)H NMR studies of the interaction of 1 and metal cations were carried out in CD(3)CN and CD(3)OD and the data are reported. Conductance measurements revealed that this ligand forms lead(II) or zinc complexes of 1: 1 stoichiometry in acetonitrile. It also revealed a stoichiometry of two molecules of 1 per mercury(II) and two cadmiu (II) ions per molecule of 1. The addition of silver salt to 1 led to the precipitation of the silver-1 complex which was isolated and characterized by X-ray crystallography. At variance with conductance measurements in solution, in the solid state the X-ray structure show`s a 1:1 stoichiometry in the Hg(II) complex. The themiodynamics of complexation of 1 and these cations provide a quantitative assessment of the selective behavior of this ligand for ions of environmental relevance.