35 resultados para Enthalpy-entropy Compensation
Resumo:
The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.
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Researchers working with thermal comfort have been using enthalpy to measure thermal energy inside rural facilities, establishing indicator values for many situations of thermal comfort and heat stress. This variable turned out to be helpful in analyzing thermal exchange in livestock systems. The animals are exposed to an environment which is decisive for the thermoregulatory process, and, consequently, the reactions reflect states of thermal comfort or heat stress, the last being responsable for problems of sanity, behavior and productivity. There are researchers using enthalpy as a qualitative indicator of thermal environment of livestock such as poultry, cattle and hogs in tropical regions. This preliminary work intends to check different enthalpy equations using information from classical thermodynamics, and proposes a direct equation as thermal comfort index for livestock systems.
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We employ comprehensive linked employer-employee data for Brazil to analyze wage determinants and compare results to Abowd et al. (2001) for French and U.S. manufacturing. While returns to human capita in Brazilian manufacturing exceed those of the other countries, occupation and gender differentials are similar. The worker-characteristics component accounts for much of the greater wage inequality in Brazil, but the establishment-fixed component has scant explanatory power. Thus, firm-or industry-level factors offer little scope for explaining the differences in wage inequality. Brazil`s wage structure resembles that of France, a country with some similarity in labor market institutions.
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The knowledge of thermochemical parameters such as the enthalpy of formation, gas-phase basicity, and proton affinity may be the key to understanding molecular reactivity. The obtention of these thermochemical parameters by theoretical chemical models may be advantageous when experimental measurements are difficult to accomplish. The development of ab initio composite models represents a major advance in the obtention of these thermochemical parameters,. but these methods do not always lead to accurate values. Aiming at achieving a comparison between the ab initio models and the hybrid models based on the density functional theory (DFT), we have studied gamma-butyrolactone and 2-pyrrolidinone with a goal of obtaining high-quality thermochemical parameters using the composite chemical models G2, G2MP2, MP2, G3, CBS-Q, CBS-4, and CBS-QB3; the DFT methods B3LYP, B3P86, PW91PW91, mPW1PW, and B98; and the basis sets 6-31G(d), 6-31+G(d), 6-31G(d,p), 6-31+G(d,p), 6-31++G(d,p), 6-311G(d), 6-311+G(d), 6-311G(d,p), 6-311+G(d,p), 6-311++G(d,p), aug-cc-pVDZ, and aug-cc-pVTZ. Values obtained for the enthalpies of formation, proton affinity, and gas-phase basicity of the two target molecules were compared to the experimental data reported in the literature. The best results were achieved with the use of DFT models, and the B3LYP method led to the most accurate data.
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PURPOSE: To evaluate the impact of atypical retardation patterns (ARP) on detection of progressive retinal nerve fiber layer (RNFL) loss using scanning laser polarimetry with variable corneal compensation (VCC). DESIGN: Observational cohort study. METHODS: The study included 377 eyes of 221 patients with a median follow-up of 4.0 years. Images were obtained annually with the GDx VCC (Carl Zeiss Med, itec Inc, Dublin, California, USA), along with optic disc stereophotographs and standard automated perimetry (SAP) visual fields. Progression was determined by the Guided Progression Analysis software for SAP and by masked assessment of stereophotographs by expert graders. The typical scan score (TSS) was used to quantify the presence of ARPs on GDx VCC images. Random coefficients models were used to evaluate the relationship between ARP and RNFL thickness measurements over time. RESULTS: Thirty-eight eyes (10%) showed progression over time on visual fields, stereophotographs, or both. Changes in TSS scores from baseline were significantly associated with changes in RNFL thickness measurements in both progressing and nonprogressing eyes. Each I unit increase in TSS score was associated with a 0.19-mu m decrease in RNFL thickness measurement (P < .001) over time. CONCLUSIONS: ARPs had a significant effect on detection of progressive RNFL loss with the GDx VCC. Eyes with large amounts of atypical patterns, great fluctuations on these patterns over time, or both may show changes in measurements that can appear falsely as glaucomatous progression or can mask true changes in the RNFL. (Am J Ophthalmol 2009;148:155-163. (C) 2009 by Elsevier Inc. All rights reserved.)
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PURPOSE: To compare the abilities of scanning laser polarimetry (SLP) with enhanced corneal compensation (ECC) and variable corneal compensation (VCC) modes for detection of retinal nerve fiber layer (RNFL) loss in eyes with band atrophy (BA) of the optic nerve. DESIGN. Cross-sectional study. METHODS: Thirty-seven eyes from 37 patients with BA and temporal visual field defect from chiasmal compression and 40 eyes from 40 healthy subjects were studied. Subjects underwent standard automated perimetry and RNFL measurements using an SLP device equipped with VCC and ECC. Receiver operating characteristic (ROC) curves were calculated for each parameter. Pearson correlation coefficients were obtained to evaluate the relationship between RNFL thickness parameters and severity of visual field loss, as assessed by the temporal mean defect. RESULTS: All RNFL thickness parameters were significantly lower in eyes with BA compared with normal eyes with both compensation modes. However, no statistically significant differences were observed in the areas under the ROC curves for the different parameters between GDx VCC and ECC (Carl Zeiss Meditec, Inc, Dublin, California, USA). Structure-function relationships also were similar for both compensation modes. CONCLUSIONS: No significant differences were found between the diagnostic accuracy of GDx ECC and that of VCC for detection of BA of the optic nerve. The use of GDx ECC does not seem to provide a better evaluation of RNFL loss on the temporal and nasal sectors of the peripapillary retina in subjects with BA of the optic nerve.
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Evidence of jet precession in many galactic and extragalactic sources has been reported in the literature. Much of this evidence is based on studies of the kinematics of the jet knots, which depends on the correct identification of the components to determine their respective proper motions and position angles on the plane of the sky. Identification problems related to fitting procedures, as well as observations poorly sampled in time, may influence the follow-up of the components in time, which consequently might contribute to a misinterpretation of the data. In order to deal with these limitations, we introduce a very powerful statistical tool to analyse jet precession: the cross-entropy method for continuous multi-extremal optimization. Only based on the raw data of the jet components (right ascension and declination offsets from the core), the cross-entropy method searches for the precession model parameters that better represent the data. In this work we present a large number of tests to validate this technique, using synthetic precessing jets built from a given set of precession parameters. With the aim of recovering these parameters, we applied the cross-entropy method to our precession model, varying exhaustively the quantities associated with the method. Our results have shown that even in the most challenging tests, the cross-entropy method was able to find the correct parameters within a 1 per cent level. Even for a non-precessing jet, our optimization method could point out successfully the lack of precession.
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We present a new technique for obtaining model fittings to very long baseline interferometric images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model image is constructed by summing N(s) elliptical Gaussian sources characterized by six parameters: two-dimensional peak position, peak intensity, eccentricity, amplitude, and orientation angle of the major axis. We present results for the fitting of two main benchmark jets: the first constructed from three individual Gaussian sources, the second formed by five Gaussian sources. Both jets were analyzed by our cross-entropy technique in finite and infinite signal-to-noise regimes, the background noise chosen to mimic that found in interferometric radio maps. Those images were constructed to simulate most of the conditions encountered in interferometric images of active galactic nuclei. We show that the cross-entropy technique is capable of recovering the parameters of the sources with a similar accuracy to that obtained from the very traditional Astronomical Image Processing System Package task IMFIT when the image is relatively simple (e. g., few components). For more complex interferometric maps, our method displays superior performance in recovering the parameters of the jet components. Our methodology is also able to show quantitatively the number of individual components present in an image. An additional application of the cross-entropy technique to a real image of a BL Lac object is shown and discussed. Our results indicate that our cross-entropy model-fitting technique must be used in situations involving the analysis of complex emission regions having more than three sources, even though it is substantially slower than current model-fitting tasks (at least 10,000 times slower for a single processor, depending on the number of sources to be optimized). As in the case of any model fitting performed in the image plane, caution is required in analyzing images constructed from a poorly sampled (u, v) plane.
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Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.
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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.
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We study and compare the information loss of a large class of Gaussian bipartite systems. It includes the usual Caldeira-Leggett-type model as well as Anosov models ( parametric oscillators, the inverted oscillator environment, etc), which exhibit instability, one of the most important characteristics of chaotic systems. We establish a rigorous connection between the quantum Lyapunov exponents and coherence loss, and show that in the case of unstable environments coherence loss is completely determined by the upper quantum Lyapunov exponent, a behavior which is more universal than that of the Caldeira-Leggett-type model.
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Measurements of X-ray diffraction, electrical resistivity, and magnetization are reported across the Jahn-Teller phase transition in LaMnO(3). Using a thermodynamic equation, we obtained the pressure derivative of the critical temperature (T(JT)), dT(JT)/dP = -28.3 K GPa(-1). This approach also reveals that 5.7(3)J(mol K)(-1) comes from the volume change and 0.8(2)J(mol K)(-1) from the magnetic exchange interaction change across the phase transition. Around T(JT), a robust increase in the electrical conductivity takes place and the electronic entropy change, which is assumed to be negligible for the majority of electronic systems, was found to be 1.8(3)J(mol K)(-1).
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An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.
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The time evolution of the out-of-equilibrium Mott insulator is investigated numerically through calculations of space-time-resolved density and entropy profiles resulting from the release of a gas of ultracold fermionic atoms from an optical trap. For adiabatic, moderate and sudden switching-off of the trapping potential, the out-of-equilibrium dynamics of the Mott insulator is found to differ profoundly from that of the band insulator and the metallic phase, displaying a self-induced stability that is robust within a wide range of densities, system sizes and interaction strengths. The connection between the entanglement entropy and changes of phase, known for equilibrium situations, is found to extend to the out-of-equilibrium regime. Finally, the relation between the system`s long time behavior and the thermalization limit is analyzed. Copyright (C) EPLA, 2011
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Nuclear receptors are important targets for pharmaceuticals, but similarities between family members cause difficulties in obtaining highly selective compounds. Synthetic ligands that are selective for thyroid hormone (TH) receptor beta (TR beta) vs. TR alpha reduce cholesterol and fat without effects on heart rate; thus, it is important to understand TR beta-selective binding. Binding of 3 selective ligands (GC-1, KB141, and GC-24) is characterized at the atomic level; preferential binding depends on a nonconserved residue (Asn-331 beta) in the TR beta ligand-binding cavity (LBC), and GC-24 gains extra selectivity from insertion of a bulky side group into an extension of the LBC that only opens up with this ligand. Here we report that the natural TH 3,5,3`-triodothyroacetic acid (Triac) exhibits a previously unrecognized mechanism of TR beta selectivity. TR x-ray structures reveal better fit of ligand with the TR alpha LBC. The TR beta LBC, however, expands relative to TR alpha in the presence of Triac (549 angstrom(3) vs. 461 angstrom(3)), and molecular dynamics simulations reveal that water occupies the extra space. Increased solvation compensates for weaker interactions of ligand with TR beta and permits greater flexibility of the Triac carboxylate group in TR beta than in TR alpha. We propose that this effect results in lower entropic restraint and decreases free energy of interactions between Triac and TR beta, explaining subtype-selective binding. Similar effects could potentially be exploited in nuclear receptor drug design.