3 resultados para Dynamic economic emission dispatch (DEED)
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Low-density lipoprotein (LDL) particles are the major cholesterol-carrying lipoprotein in the human circulation from the liver to peripheral tissues. High levels of LDL-Cholesterol (LDL-C) are known risk factor for the development of coronary artery disease (CAD). The most common approach to determine the LDLC in the clinical laboratory involves the Friedewald formula. However, in certain situations, this approach is inadequate. In this paper we report on the enhancement on the Europium emission band of Europium chlortetracycline complex (CTEu) in the presence of LDL. The emission intensity at 615 nm of the CTEu increases with increasing amounts of LDL. This phenomenon allowed us to propose a method to determine the LDL concentration in a sample composed by an aqueous solution of LDL. With this result we obtained LDL calibration curve, LOD (limit of detection) of 0.49 mg/mL and SD (standard deviation) of 0.003. We observed that CTEu complex provides a wider dynamic concentration-range for LDL determination than that from Eu-tetracycline previously. The averaged emission lifetimes of the CTEu and CTEu with LDL (1.5 mg/mL) complexes were measured as 15 and 46 Its, respectively. Study with some metallic interferents is presented. (C) 2010 Elsevier Inc. All rights reserved.
Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data
Resumo:
We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.
Resumo:
A dynamic atmosphere generator with a naphthalene emission source has been constructed and used for the development and evaluation of a bioluminescence sensor based on the bacteria Pseudomonas fluorescens HK44 immobilized in 2% agar gel (101 cell mL(-1)) placed in sampling tubes. A steady naphthalene emission rate (around 7.3 nmol min(-1) at 27 degrees C and 7.4 mLmin(-1) of purified air) was obtained by covering the diffusion unit containing solid naphthalene with a PTFE filter membrane. The time elapsed from gelation of the agar matrix to analyte exposure (""maturation time"") was found relevant for the bioluminescence assays, being most favorable between 1.5 and 3 h. The maximum light emission, observed after 80 min, is dependent on the analyte concentration and the exposure time (evaluated between 5 and 20 min), but not on the flow rate of naphthalene in the sampling tube, over the range of 1.8-7.4 nmol min(-1). A good linear response was obtained between 50 and 260 nmol L-1 with a limit of detection estimated in 20 nmol L-1 far below the recommended threshold limit value for naphthalene in air. (c) 2008 Elsevier B.V. All rights reserved.