Absorption and fluorescence spectroscopy of rhodamine 6G in titanium dioxide nanocomposites

A comparison has been made between the spectroscopic properties of the laser dye rhodamine 6G (R6G) in mesostructured titanium dioxide (TiO2) and in ethanol. Steady-state excitation and emission techniques have been used to probe the dye-matrix interactions. We show that the TiO2-nanocomposite studied is a good host for R6G, as it allows high dye concentrations, while keeping dye molecules isolated, and preventing aggregation. Our findings have important implications in the context of solid state dye-lasers and microphotonic device applications. (C) 2003 Elsevier B.V. All rights reserved.

Direct observation of mixed-parity excited states in surface-passivated PbS nanocrystals

Photoluminescent emission is observed from surface-passivated PbS nanocrystals following the two-photon excitation of high-energy excitonic states. The emission appears directly at the excitation energy with no detectable Stokes-shift for a wide range of excitation energies. The observation of direct emission from states excited by two-photon absorption indicates that the parity of the excited states of surface-passivated PbS nanocrystals is partially mixed.

The branching gene RAMOSUS1 mediates interactions among two novel signals and auxin in pea

In Pisum sativium, the RAMOSUS genes RMS1, RMS2, and RMS5 regulate shoot branching via physiologically defined mobile signals. RMS1 is most likely a carotenoid cleavage enzyme and acts with RMS5 to control levels of an as yet unidentified mobile branching inhibitor required for auxin inhibition of branching. Our work provides molecular, genetic, and physiological evidence that RMS1 plays a central role in a shoot-to-root-to-shoot feedback system that regulates shoot branching in pea. Indole-3-acetic acid (IAA) positively regulates RMS1 transcript level, a potentially important mechanism for regulation of shoot branching by IAA. In addition, RMS1 transcript levels are dramatically elevated in rms3, rms4, and rms5 plants, which do not contain elevated IAA levels. This degree of upregulation of RMS1 expression cannot be achieved in wild-type plants by exogenous IAA application. Grafting studies indicate that an IAA-independent mobile feedback signal contributes to the elevated RMS1 transcript levels in rms4 plants. Therefore, the long-distance signaling network controlling branching in pea involves IAA, the RMS1 inhibitor, and an IAA-independent feedback signal. Consistent with physiological studies that predict an interaction between RMS2 and RMS1, rms2 mutations appear to disrupt this IAA-independent regulation of RMS1 expression.

Identification of two evolutionarily conserved and functional regulatory elements in intron 2 of the human BRCA1 gene

Cross-species comparative genomics is a powerful strategy for identifying functional regulatory elements within noncoding DNA. In this paper, comparative analysis of human and mouse intronic sequences in the breast cancer susceptibility gene (BRCA1) revealed two evolutionarily conserved noncoding sequences (CNS) in intron 2, 5 kb downstream of the core BRCA1 promoter. The functionality of these elements was examined using homologous-recombination-based mutagenesis of reporter gene-tagged cosmids incorporating these regions and flanking sequences from the BRCA1 locus. This showed that CNS-1 and CNS-2 have differential transcriptional regulatory activity in epithelial cell lines. Mutation of CNS-1 significantly reduced reporter gene expression to 30% of control levels. Conversely mutation of CNS-2 increased expression to 200% of control levels. Regulation is at the level of transcription and shows promoter specificity. Both elements also specifically bind nuclear proteins in vitro. These studies demonstrate that the combination of comparative genomics and functional analysis is a successful strategy to identify novel regulatory elements and provide the first direct evidence that conserved noncoding sequences in BRCA1 regulate gene expression. (c) 2005 Elsevier Inc. All rights reserved.

Comparison of two-dimensional speckle and tissue velocity based strain and validation with harmonic phase magnetic resonance imaging

Two-dimensional (2-D) strain (epsilon(2-D)) on the basis of speckle tracking is a new technique for strain measurement. This study sought to validate epsilon(2-D) and tissue velocity imaging (TVI)based strain (epsilon(TVI)) with tagged harmonic-phase (HARP) magnetic resonance imaging (MRI). Thirty patients (mean age. 62 +/- 11 years) with known or suspected ischemic heart disease were evaluated. Wall motion (wall motion score index 1.55 +/- 0.46) was assessed by an expert observer. Three apical images were obtained for longitudinal strain (16 segments) and 3 short-axis images for radial and circumferential strain (18 segments). Radial epsilon(TVI) was obtained in the posterior wall. HARP MRI was used to measure principal strain, expressed as maximal length change in each direction. Values for epsilon(2-D), epsilon(TVI), and HARP MRI were comparable for all 3 strain directions and were reduced in dysfunctional segments. The mean difference and correlation between longitudinal epsilon(2-D) and HARP MRI (2.1 +/- 5.5%, r = 0.51, p < 0.001) were similar to those between longitudinal epsilon(TVI), and HARP MRI (1.1 +/- 6.7%, r = 0.40, p < 0.001). The mean difference and correlation were more favorable between radial epsilon(2-D) and HARP MRI (0.4 +/- 10.2%, r = 0.60, p < 0.001) than between radial epsilon(TVI), and HARP MRI (3.4 +/- 10.5%, r = 0.47, p < 0.001). For circumferential strain, the mean difference and correlation between epsilon(2-D) and HARP MRI were 0.7 +/- 5.4% and r = 0.51 (p < 0.001), respectively. In conclusion, the modest correlations of echocardiographic and HARP MRI strain reflect the technical challenges of the 2 techniques. Nonetheless, epsilon(2-D) provides a reliable tool to quantify regional function, with radial measurements being more accurate and feasible than with TVI. Unlike epsilon(TVI), epsilon(2-D) provides circumferential measurements. (c) 2006 Elsevier Inc. All rights reserved.

Forecasting exchange rates with linear and nonlinear models

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore, the parameters are chosen according to what the researcher considers to be the best. Such an approach, however,implies that the risk of making bad decisions is extremely high, which could explain why in many studies, neural network models do not consistently perform better than their time series counterparts. In this paper, through extensive experimentation, the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of Forecasting exchange rates with linear and nonlinear models 415 performing well. The results show that in general, neural network models perform better than the traditionally used time series models in forecasting exchange rates.