Age-related differences in emotion recognition ability: A cross-sectional study.

Experimental studies indicate that recognition of emotions, particularly negative emotions, decreases with age. However, there is no consensus at which age the decrease in emotion recognition begins, how selective this is to negative emotions, and whether this applies to both facial and vocal expression. In the current cross-sectional study, 607 participants ranging in age from 18 to 84 years (mean age = 32.6 ± 14.9 years) were asked to recognize emotions expressed either facially or vocally. In general, older participants were found to be less accurate at recognizing emotions, with the most distinctive age difference pertaining to a certain group of negative emotions. Both modalities revealed an age-related decline in the recognition of sadness and—to a lesser degree—anger, starting at about 30 years of age. Although age-related differences in the recognition of expression of emotion were not mediated by personality traits, 2 of the Big 5 traits, openness and conscientiousness, made an independent contribution to emotion-recognition performance. Implications of age-related differences in facial and vocal emotion expression and early onset of the selective decrease in emotion recognition are discussed in terms of previous findings and relevant theoretical models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Three-dimensional respiratory-gated MR angiography of coronary arteries: comparison with conventional coronary angiography

OBJECTIVE: MR coronary angiography is most often performed using two-dimensional techniques. Although three-dimensional (3D) acquisitions do have important advantages, they take too long for a single breath-hold and are thus susceptible to respiratory motion artifacts. The purpose of this study was to investigate the accuracy of a unique respiratory-gated 3D MR angiographic technique in identifying the proximal coronary arteries in patients suspected of having coronary artery disease. In addition, we investigated the capability of this technique to detect proximal stenoses. SUBJECTS AND METHODS: We performed a prospective blinded study in 20 patients who were referred for conventional coronary angiography. A cardiac-gated 3D gradient-echo sequence with fat suppression was used. Retrospective respiratory gating was performed using navigator echoes of the diaphragm position. Using multiplanar reformatting, two independent readers blindly analyzed the data sets for visualization of major coronary arteries, lengths of imaged segments, and detection of significant stenoses (> 50% occlusion of the luminal diameter by conventional angiography). RESULTS: Seventy-seven of 80 (96%) coronary arteries were positively identified. In one patient, an anomalous coronary anatomy was readily identified and confirmed by conventional angiography. The average lengths of the imaged segments of the right, left main, left anterior descending, and left circumflex coronary arteries were 58 +/- 13 mm, 9 +/- 5 mm, 59 +/- 16 mm, and 24 +/- 10 mm, respectively. Overall sensitivity for the detection of stenoses was low (38%), with a specificity of 95%. Interobserver agreement was 0.92, with a kappa value of 0.65. CONCLUSION: Respiratory-gated 3D MR angiography allows accurate identification of proximal coronary arteries and may be valuable for 3D imaging of coronary anomalies. Further technical improvements are required to enhance the value of the technique in detecting stenoses.     

Nonlinear parameter estimation through particle swarm optimization

Parameter estimation procedures are very important in the chemical engineering field for development of mathematical models, since design, optimization and advanced control of chemical processes depend on model parameter values obtained from experimental data. Model nonlinearity makes the estimation of parameter and the statistical analysis of parameter estimates more difficult and more challenging. In this work, it is shown that many of these difficulties can be overcome with the use of heuristic optimization methods, such as the particle swarm optimization (PSO) method. Parameter estimation problems are solved here with PSO and it is shown that the PSO method is efficient for both minimization and construction of the confidence region of parameter estimates. Moreover, it is shown that the elliptical approximation of confidence regions of nonlinear model parameters can be very poor sometimes and that more accurate likelihood confidence regions can be constructed with PSO, allowing for more reliable statistical analysis of the significance of parameter estimates.     

Retrieval of textured images through the use of quantization and modal analysis

This paper proposes a new method for textured image retrieval, by the modal analysis of quantized spectral point patterns as the modal correspondence method of Shapiro and Brady, to match point sets by comparing the eigenvectors of a pairwise point proximity matrix taken from the power spectrum peaks. A variant of the Carcassoni, Ribeiro and Hancock method for performing recognition is taken into account. For choosing image features to represent an image, a quantization scheme is applied. This quantization scheme acts in the spectral space given by the Fourier transform of each image. Its goal is to find a small set which represents an image efficiently, where the most important features are presented. The proposed technique is invariant to rotation and is robust in the presence of noise and damaged images. The techniques here presented are compared, and the commonly used retrieval performance measurement—precision and recall—is used as evaluation of the query results.     

First experiences with the modelling and simulation package MIRACLES applied to a picture archiving and communication system (PACS) in a clinical environment

Since the construction of picture archiving and communication systems (PACS) appears to be extremely difficult, computer modelling and simulation are used as decision support tools. The package MIRACLES (Medical Image Representation, Archiving and Communication Learned from Extensive Simulation) has been developed at BAZIS in order to support the construction of simulation models of image information systems. This article discusses the application of MIRACLES to a prototypical PACS as being installed in a clinical environment. Attention is focussed to the required system analysis and difficulties which arose during the construction of the simulation model. The emphasis is on the presentation of the results of the simulation study, which show that simulation can be fruitfully used to predict, to analyse and to assist in solving performance problems. The simulation study confirmed assumptions and suppositions concerning both the system performance itself and strategies to improve the performance. The study also resulted in a number of concrete recommendations which might be useful for the set-up of the prototypical PACS.     

Sugarcane Serine Peptidase Inhibitors,Serine Peptidases,and Clp Protease System Subunits Associated with Sugarcane Borer (Diatraea saccharalis) Herbivory and Wounding

Sugarcane’s (Saccharum spp.) response to Diatraea saccharalis (F.) (Lepidoptera: (Crambidae) herbivory was investigated using a macroarray spotted with 248 sugarcane Expressed Sequence Tags (ESTs) encoding serine peptidase inhibitors, serine peptidases. and Clp protease system subunits. Our results showed that after nine hours of herbivory, 13 sugarcane genes were upregulated and nine were downregulated. Among the upregulated genes, nine were similar to serine peptidase inhibitors and four were similar to Bowman-Birk Inhibitors (BBIs). Phylogenetic analysis revealed that these sequences belong to a phylogenetic group of sugarcane BBIs that are potentially involved in plant defense against insect predation. The remaining four upregulated genes included serine peptidases and one homolog to the Arabidopsis AAA+ chaperone subunit ClpD, which is a member of the Clp protease system. Among the downregulated genes, five were homologous to serine peptidases and four were homologous to Arabidopsis Clp subunits (three homologous to Clp AAA+ chaperones and one to a ClpP-related ClpR subunit). Although the roles of serine peptidase inhibitors in plant defenses against herbivory have been extensively investigated, the roles of plant serine peptidases and the Clp protease system represent a new and underexplored field of study. The up- and downregulated D. saccharalis genes presented in this study may be candidate genes for the further investigation of the sugarcane response to herbivory.     

Hybrid modeling of inulinase bio‐production process

BACKGROUND: A potential application of inulinase in the food industry is the production of fructooligosaccharides (FOS) through transfructosilation of sucrose. Besides their ability to increase the shelf‐life and flavor of many products, FOS have many interesting functional properties. The use of an industrial medium may represent a good, cost‐effective alternative to produce inulinase, since the activity of the enzyme produced may be improved or at least remain the same compared with that obtained using a synthetic medium. Thus, inulinase production for use in FOS synthesis is of considerable scientific and technological appeal, as is the development of a reliable mathematical model of the process. This paper describes a hybrid neural network approach to model inulinase production in a batch bioreactor using agroindustrial residues as substrate. The hybrid modeling makes use of a series artificial neural network to estimate the kinetic parameters of the process and the mass balance as constitutive equations. RESULTS: The proposed model was shown to be capable of describing the complex behavior of inulinase production employing agroindustrial residues as substrate, so that the mathematical framework developed is a useful tool for simulation of this process. CONCLUSION: The hybrid neural network model developed was shown to be an interesting alternative to estimate model parameters since complete elucidation of the phenomena and mechanisms involved in the fermentation is not required owing to the black‐box nature of the ANN used as parameter estimator. Copyright © 2010 Society of Chemical Industry     

Is cluster policy useful for the energy sector? Assessing self-declared hydrogen clusters in the Netherlands

Research on science-based industries has shown that it is important for organisations to be active in interorganisational networks. Cluster policy has been developed as a means to stimulate the development of these networks and thereby the success rate of these industries. Cluster policy is however not a common policy instrument in the energy sector. In this paper, we focus on three self-declared clusters active in hydrogen-related R&D in the Netherlands and address several characteristics of these clusters. We conclude that cluster policy is a useful addition to existing energy R&D policies but that monitoring whether self-declared clusters actually function as clusters and what their contribution is to the overall system is pivotal in reaping the benefits of cluster policy.