974 resultados para Acoustic signal classification
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The glasses of the rosette forming the main window of the transept of the Gothic Cathedral of Tarragona have been characterised by means of SEM/EDS, XRD, FTIR and electronic microprobe. The multivariate statistical treatment of these data allow to establish a classification of the samples forming groups having an historical significance and reflecting ancient restorations. Furthermore, the decay patterns and mechanisms have been determined and the weathering by-products characterised. It has been demonstrated a clear influence of the bioactivity in the decay of these glasses, which activity is partially controlled by the chemical composition of the glasses.
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This manual provides a set of procedural rules and regulations for use in functionally classifying all roads and streets in Iowa according to the character of service they are intended to provide. Functional classification is a requirement of House File 394 (Functional Highway Classification Bill) enacted by the 63rd General Assembly of the Iowa Legislature. Functional classification is defined in this Bill as: "The grouping of roads and streets into systems according to the character of service they will be expected to provide, and the assignment of jurisdiction over each class to the governmental unit having primary interest in each type of service."
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This manual provides a set of procedural rules and regulations for use in functionally classifying all roads and streets in Iowa according to the character of service they are intended to provide. Functional classification is a requirement of the 1973 Code of Iowa (Chapter 306) as amended by Senate File 1062 enacted by the 2nd session of the 65th General Assembly of Iowa. Functional classification is defined as the grouping of roads and streets into systems according to the character of service they will be expected to provide, and the assignment of jurisdiction over each class to the governmental unit having primary interest in each type of service. Stated objectives of the legislation are: "Functional classification will serve the legislator by providing an equitable basis for determination of proper source of tax support and providing for the assignment of financial resources to the governmental unit having responsibility for each class of service. Functional classification promotes the ability of the administrator to effectively prepare and carry out long range programs which reflect the transportation needs of the public." All roads and streets in legal existence will be classified. Instructions are also included in this manual for a continuous reporting to the Highway Commission of changes in classification and/or jurisdiction resulting from new construction, corporation line changes, relocations, and deletions. This continuous updating of records is absolutely essential for modern day transportation planning as it is the only possible way to monitor the status of existing road systems, and consequently determine adequacy and needs with accuracy.
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Exophthalmos is the main symptom revealing orbital masses. This sign needs to be imaged mainly by MRI and/or CT. As Graves disease is the main etiology of exophthalmos, CT scan should be performed as the initial imaging modality. Indications for US and Doppler are mostly limited to the study of ocular masses, and eventually may help the characterization of extra-ocular lesions. In all cases, imaging is useful to characterize: the precise location of the lesion which can be the intra-conal space (including muscles), the extra-conal space (associated or not to an extra-orbital lesion), or the eyeball; the features of the lesion (density, signal, enhancement.). These findings are used to generate a differential diagnosis. Imaging is also useful to precise the extension of the mass, and in some cases to select the appropriate surgical approach, and for follow-up.
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Biological control of root pathogens--mostly fungi--can be achieved by the introduction of selected bacterial inoculants acting as 'biopesticides'. Successful inoculants have been identified among Gram-negative and Gram-positive bacteria, often belonging to Pseudomonas spp. and Bacillus spp., respectively. Biocontrol activity of a model rhizobacterium, P. fluorescens CHAO, depends to a considerable extent on the synthesis of extracellular antimicrobial secondary metabolites and exoenzymes, thought to antagonize the pathogenicity of a variety of phytopathogenic fungi. The regulation of exoproduct formation in P. fluorescens (as well as in other bacteria) depends essentially on the GacS/GacA two-component system, which activates a largely unknown signal transduction pathway. However, recent evidence indicates that GacS/GacA control has a major impact on target gene expression at a post-transcriptional level, involving an mRNA target sequence (typically near the ribosome binding site), two RNA binding proteins (designated RsmA and RsmE), and a regulatory RNA (RsmZ) capable of binding RsmA. The expression and activity of the regulatory system is stimulated by at least one low-molecular-weight signal. The timing and specificity of this switch from primary to secondary metabolism are essential for effective biocontrol.
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The objective of this work was to assess and characterize two clones, 169 and 685, of Cabernet Sauvignon grapes and to evaluate the wine produced from these grapes. The experiment was carried out in São Joaquim, SC, Brazil, during the 2009 harvest season. During grape ripening, the evolution of physical-chemical properties, phenolic compounds, organic acids, and anthocyanins was evaluated. During grape harvest, yield components were determined for each clone. Individual and total phenolics, individual and total anthocyanins, and antioxidant activity were evaluated for wine. The clones were also assessed regarding the duration of their phenological cycle. During ripening, the evolution of phenolic compounds and of physical-chemical parameters was similar for both clones; however, during harvest, significant differences were observed regarding yield, number of bunches per plant and berries per bunch, leaf area, and organic acid, polyphenol, and anthocyanin content. The wines produced from these clones showed significant differences regarding chemical composition. The clones showed similar phenological cycle and responses to bioclimatic parameters. Principal component analysis shows that clone 685 is strongly correlated with color characteristics, mainly monomeric anthocyanins, while clone 169 is correlated with individual phenolic compounds.
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This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.
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In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets.
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Studies on the potential benefits of conveying biofeedback stimulus using a musical signal have appeared in recent years with the intent of harnessing the strong effects that music listening may have on subjects. While results are encouraging, the fundamental question has yet to be addressed, of how combined music and biofeedback compares to the already established use of either of these elements separately. This experiment, involving young adults (N = 24), compared the effectiveness at modulating participants' states of physiological arousal of each of the following conditions: A) listening to pre-recorded music, B) sonification biofeedback of the heart rate, and C) an algorithmically modulated musical feedback signal conveying the subject's heart rate. Our hypothesis was that each of the conditions (A), (B) and (C) would differ from the other two in the extent to which it enables participants to increase and decrease their state of physiological arousal, with (C) being more effective than (B), and both more than (A). Several physiological measures and qualitative responses were recorded and analyzed. Results show that using musical biofeedback allowed participants to modulate their state of physiological arousal at least equally well as sonification biofeedback, and much better than just listening to music, as reflected in their heart rate measurements, controlling for respiration-rate. Our findings indicate that the known effects of music in modulating arousal can therefore be beneficially harnessed when designing a biofeedback protocol.
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Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis.
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Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.
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The objective of this work was to evaluate the efficiency of superficial application of limestone and slag, and their effects on soil chemical attributes and on yield and mineral nutrition of soybean, maize, and Congo signal grass (Urochloa ruziziensis). The experiment was carried out in a Rhodic Hapludox under no tillage system. The treatments consisted of the use of limestone or slag (silicates of calcium and magnesium) to correct soil acidity, and of a control treatment without the use of soil correctives. Rates were calculated in order to raise soil base saturation up to 70%. Soybean was sown in November 2006 and maize in December 2007. Congo signal grass was sown right after the harvests of soybean and maize, and it was cropped during the off-seasons. Soil chemical attributes were evaluated at 6, 12, and 18 months after the application of the corrective materials. Slag is an efficient source for soil acidity correction, being able to raise the exchangeable base levels in the soil profile faster than lime. Both limestone and slag increase dry matter yield of Congo signal grass, and grain yield of soybean and maize. Slag is more effective in improving maize grain yield.
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Cancer cell metabolism differs from that of non-transformed cells in the same tissue. This specific metabolism gives tumor cells growing advantages besides the effect in increasing anabolism. One of these advantages is immune evasion mediated by a lower expression of the mayor histocompatibility complex class I molecules. The extracellular-signal-regulated kinase-5 regulates both mayor histocompatibility complex class I expression and metabolic activity. However, the mechanisms underlying are largely unknown. We show here that extracellular-signal-regulated kinase-5 regulates the transcription of the NADH(+)-dependent histone deacetylase silent mating type information regulation 2 homolog 1 (Sirtuin 1) in leukemic Jurkat T cells. This involves the activation of the transcription factor myocyte enhancer factor-2 and its binding to the sirt1 promoter. In addition, extracellular-signal-regulated kinase-5 is required for T cell receptor-induced and oxidative stress-induced full Sirtuin 1 expression. Extracellular-signal-regulated kinase-5 induces the expression of promoters containing the antioxidant response elements through a Sirtuin 1-dependent pathway. On the other hand, down modulation of extracellular-signal-regulated kinase-5 expression impairs the anti-oxidant response. Notably, the extracellular-signal-regulated kinase-5 inhibitor BIX02189 induces apoptosis in acute myeloid leukemia tumor cells without affecting T cells from healthy donors. Our results unveil a new pathway that modulates metabolism in tumor cells. This pathway represents a promising therapeutic target in cancers with deep metabolic layouts such as acute myeloid leukemia.
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The objective of this work was to evaluate the biochemical composition of six berry types belonging to Fragaria, Rubus, Vaccinium and Ribes genus. Fruit samples were collected in triplicate (50 fruit each) from 18 different species or cultivars of the mentioned genera, during three years (2008 to 2010). Content of individual sugars, organic acids, flavonols, and phenolic acids were determined by high performance liquid chromatography (HPLC) analysis, while total phenolics (TPC) and total antioxidant capacity (TAC), by using spectrophotometry. Principal component analysis (PCA) and hierarchical cluster analysis (CA) were performed to evaluate the differences in fruit biochemical profile. The highest contents of bioactive components were found in Ribes nigrum and in Fragaria vesca, Rubus plicatus, and Vaccinium myrtillus. PCA and CA were able to partially discriminate between berries on the basis of their biochemical composition. Individual and total sugars, myricetin, ellagic acid, TPC and TAC showed the highest impact on biochemical composition of the berry fruits. CA separated blackberry, raspberry, and blueberry as isolate groups, while classification of strawberry, black and red currant in a specific group has not occurred. There is a large variability both between and within the different types of berries. Metabolite fingerprinting of the evaluated berries showed unique biochemical profiles and specific combination of bioactive compound contents.
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Animals can compete for resources by displaying various acoustic signals that may differentially affect the outcome of competition. We propose the hypothesis that the most efficient signal to deter opponents should be the one that most honestly reveals motivation to compete. We tested this hypothesis in the barn owl (Tyto alba) in which nestlings produce more calls of longer duration than siblings to compete for priority access to the indivisible prey item their parents will deliver next. Because nestlings increase call rate to a larger extent than call duration when they become hungrier, call rate would signal more accurately hunger level. This leads us to propose three predictions. First, a high number of calls should be more efficient in deterring siblings to compete than long calls. Second, the rate at which an individual calls should be more sensitive to variation in the intensity of the sibling vocal competition than the duration of its calls. Third, call rate should influence competitors' vocalization for a longer period of time than call duration. To test these three predictions we performed playback experiments by broadcasting to singleton nestlings calls of varying durations and at different rates. According to the first prediction, singleton nestlings became less vocal to a larger extent when we broadcasted more calls compared to longer calls. In line with the second prediction, nestlings reduced vocalization rate to a larger extent than call duration when we broadcasted more or longer calls. Finally, call rate had a longer influence on opponent's vocal behavior than call duration. Young animals thus actively and differentially use multiple signaling components to compete with their siblings over parental resources.