Subdiffraction fluorescence imaging of biomolecular structure and distributions with quantum dots

We introduce semiconductor quantum dot-based fluorescence imaging with approximately 2-fold increased optical resolution in three dimensions as a method that allows both studying cellular structures and spatial organization of biomolecules in membranes and subcellular organelles. Target biomolecules are labelled with quantum dots via immunocytochemistry. The resolution enhancement is achieved by three-photon absorption of quantum dots and subsequent fluorescence emission from a higher-order excitonic state. Different from conventional multiphoton microscopy, this approach can be realized on any confocal microscope without the need for pulsed excitation light. We demonstrate quantum dot triexciton imaging (QDTI) of the microtubule network of U373 cells, 3D imaging of TNF receptor 2 on the plasma membrane of HeLa cells, and multicolor 3D imaging of mitochondrial cytochrome c oxidase and actin in COS-7 cells.

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts.

Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics

To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales

Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Drizzle and Fog Analysis in the Sao Paulo Metropolitan Area: Changes 1933-2005 and Correlations with other Climate Factors

In order to improve our understanding of climate change, the aim of this research project was to study the climatology and the time trends of drizzle and fog events in the Sao Paulo Metropolitan Area, and the possible connections of this variability with the sea surface temperature (SST) of the Atlantic and Pacific Oceans. The climatology of both phenomena presents differences and similarities. Fog shows a marked maximum frequency in winter and a minimum frequency in summer, while the seasonal differences of drizzle occurrence are less pronounced, there is a maximum in spring, whereas the other seasons present smaller and similar numbers of events. Both phenomena present a negative trend from 1933 to 2005 which is stronger for fog events. A multivariate statistical analysis indicates that the South Atlantic SST could increase warm temperature advection to the continent. This could be one of the responsible factors for the negative tendency in the number of both fog and drizzle events.

Clinical correlations of human cytomegalovirus strains and viral load in kidney transplant recipients

Little is known about clinical differences associated with cytomegalovirus (CMV) infection by distinct strains in renal transplant patients. Different clinical pictures may be associated with specific viral genotypes. viral load, as well as host factors. The objective of this study was to identify CMV strains to determine viral load (antigenemia), and their correlation with clinical data in renal transplant recipients. Seventy-one patients were enrolled, comprising 91 samples. After selection, polymorphonuclear cells were used to amplify and sequence the gB region of CMV DNA. The sequences were analyzed to ascertain the frequency of different genotypes. Additionally, the results of this Study showed that the gB coding gene presents a great variability, revealing a variety of patterns: classical gB (1.4%), gB1V (46.4%), classical gB2 (35.2%), gB2V (2.8%), gB3 (1.4%), classical gB4 (4.9%) and gB4V (4.9%). The mean viral load in kidney transplant patient was 75.1 positive cells (1-1000). A higher viral load was observed in patients with genotype 4 infection. Statistically significant differences were detected between gB1 and gB4 (p=0.010), and between gB2 and gB4 (p=0.021). The average numbers of positive cells in relation to clinical presentation were: 34.5 in asymptomatic, 49.5 in CMV associated syndrome and 120.7 in patients with invasive disease (p=0.048). As a group, gB1 was the most frequent strain and revealed a potential risk for developing invasive disease. Viral load also seemed to be important as a marker associated with clinical presentation of the disease. (C) 2008 Elsevier B.V. All rights reserved.

Influence of quantum-dots density on average in-plane strain of optoelectronic devices investigated by high-resolution X-ray diffraction

High-resolution X-ray diffractometry is used to probe the nature of a diffraction-peak broadening previously noticed in quantum dots (QDs) systems with freestanding InAs islands on top of GaAs (001) substrates [Freitas et al., Phys. Status Solidi (A) 204, 2548 (2007)]. The procedure is hence extended to further investigate the capping process of InAs/GaAs QDs. A direct correlation is established between QDs growth rates and misorientation of lattice-planes at the samples surfaces. This effect provides an alternative too] for studying average strain fields on QDs systems in standard triple axis diffractometers running on X-ray tube sources, which are much more common than synchrotron facilities. (C) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

All-optical switching device for infrared based on PbTe quantum dots

Multilayers of PbTe quantum dots embedded in SiO2 were fabricated by alternate use of Pulsed Laser Deposition (PLD) and Plasma Enhanced Chemical Vapor Deposition (PECVD) techniques. The morphological properties of the nanostructured material were studied by means of High Resolution Transmission Electron Microscopy (HRTEM), Grazing-Incidence Small-Angle X-ray scattering (GISAXS) and X-ray Reflectometry (XRR) techniques. A preliminary analysis of the GISAXS spectra provided information about the multilayer periodicity and its relationship to the size of the deposited PbTe nanoparticles. Finally multilayers were fabricated inside a Fabry-Perot cavity. The device was characterized by means of Scanning Electron Microscopy (SEM). Transmittance measurements show the device functionality in the infrared region. (C) 2007 Elsevier Ltd. All rights reserved.

Exciton behavior in GaAs/AlGaAs coupled double quantum wells with interface disorder

In this work, we present a detailed study on the optical properties of two GaAs/Al(0.35)Ga(0.65)As coupled double quantum wells (CDQWs) with inter-well barriers of different thicknesses, by using photoluminescence (PL) spectroscopy. The two CDQWs were grown in a single sample, assuring very similar experimental conditions for measurements of both. The PL spectrum of each CDQW exhibits two recombination channels which can be accurately identified as the excitonic e(1)-hh(1) transitions originated from CDQWs of different effective dimensions. The PL spectra characteristics and the behavior of the emissions as a function of temperature and excitation power are interpreted in the scenario of the bimodal interface roughness model, taking into account the exciton migration between the two regions considered in this model and the difference in the potential fluctuation levels between those two regions. The details of the PL spectra behavior as a function of excitation power are explained in terms of the competition between the band gap renormalization (BGR) and the potential fluctuation effects. The results obtained for the two CDQWs, which have different degrees of potential fluctuation, are also compared and discussed. (C) 2009 Elsevier B.V. All rights reserved.

Electronic properties of liquid hydrogen fluoride: A sequential quantum mechanical/Born-Oppenheimer molecular dynamics approach

The electronic properties of liquid hydrogen fluoride (HF) were investigated by carrying out sequential quantum mechanics/Born-Oppenheimer molecular dynamics. The structure of the liquid is in good agreement with recent experimental information. Emphasis was placed on the analysis of polarisation effects, dynamic polarisability and electronic excitations in liquid HF. Our results indicate an increase in liquid phase of the dipole moment (similar to 0.5 D) and isotropic polarisability (5%) relative to their gas-phase values. Our best estimate for the first vertical excitation energy in liquid HF indicates a blue-shift of 0.4 +/- 0.2 eV relative to that of the gas-phase monomer (10.4 eV). (C) 2010 Elsevier B.V. All rights reserved.

Quantum States Allowing Minimum Uncertainty Product of phi and L(z)

We provide necessary and sufficient conditions for states to have an arbitrarily small uncertainty product of the azimuthal angle phi and its canonical moment L(z). We illustrate our results with analytical examples.

(85)Rb Bose-Einstein condensate with tunable interaction: A quantum many body approach

We present a quantum many body approach with van der Waal type of interaction to achieve (85)Rb Bose-Einstein condensate with tunable interaction which has been produced by magnetic field induced Feshbach resonance in the JILA experiment. (C) 2008 Elsevier B.V. All rights reserved.

A closer look at the influence of tubular initial conditions on two-particle correlations

In a recent paper, the hydrodynamic code NEXSPheRIO was used in conjunction with STAR analysis methods to study two-particle correlations as a function of Delta(eta) and Delta phi. The various structures observed in the data were reproduced. In this work, we discuss the origin of these structures as well as present new results.

Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.