Variable step-size LMS blind CDMA multiuser detectors

Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to convergence rate. On the other hand, the training-based detector performs better in the steady state, giving a lower excess mean-square error (MSE) for a given adaptation step size. A novel decision-directed LMS detector which achieves the low excess MSE of the training-based detector and the superior convergence performance of the blind detector is proposed.

Structural characterization of a new crystal form of the four-way Holliday junction formed by the DNA sequence d(CCGGTACCGG)2: sequence versus lattice?

DNA-strand exchange is a vital step in the recombination process, of which a key intermediate is the four-way DNA Holliday junction formed transiently in most living organisms. Here, the single-crystal structure at a resolution of 2.35 Å of such a DNA junction formed by d(CCGGTACCGG)2, which has crystallized in a more highly symmetrical packing mode to that previously observed for the same sequence, is presented. In this case, the structure is isomorphous to the mismatch sequence d(CCGGGACCGG)2, which reveals the roles of both lattice and DNA sequence in determining the junction geometry. The helices cross at the larger angle of 43.0° (the previously observed angle for this sequence was 41.4°) as a right-handed X. No metal cations were observed; the crystals were grown in the presence of only group I counter-cations.

Ex vivo expansion of limbal stem cells is affected by substrate properties

Limbal epithelial stem cells play a key role in the maintenance and regulation of the corneal surface. Damage or destruction of these cells results in vascularisation and corneal opacity. Subsequent limbal stem cell transplantation requires an ex vivo expansion step and preserving cells in an undifferentiated state remains vital. In this report we seek to control the phenotype of limbal epithelial stem cells by the novel application of compressed collagen substrates. We have characterised the mechanical and surface properties of conventional collagen gels using shear rheology and scanning electron microscopy. In doing so, we provide evidence to show that compressive load can improve the stiffness of collagen substrates. In addition Western blotting and immunohistochemistry display increased cytokeratin 3 (CK3) protein expression relating to limbal epithelial cell differentiation on stiff collagen substrates. Such gels with an elastic modulus of 2900 Pa supported a significantly higher number of cells than less stiff collagen gels (3 Pa). These findings have substantial influence in the development of ocular surface constructs or experimental models particularly in the fields of stem cell research, tissue engineering and regenerative medicine.

Comment on “A modified leapfrog scheme for shallow water equations” by Wen-Yih Sun and Oliver M.T. Sun

A recent paper published in this journal considers the numerical integration of the shallow-water equations using the leapfrog time-stepping scheme [Sun Wen-Yih, Sun Oliver MT. A modified leapfrog scheme for shallow water equations. Comput Fluids 2011;52:69–72]. The authors of that paper propose using the time-averaged height in the numerical calculation of the pressure-gradient force, instead of the instantaneous height at the middle time step. The authors show that this modification doubles the maximum Courant number (and hence the maximum time step) at which the integrations are stable, doubling the computational efficiency. Unfortunately, the pressure-averaging technique proposed by the authors is not original. It was devised and published by Shuman [5] and has been widely used in the atmosphere and ocean modelling community for over 40 years.

Sea surface temperature from a geostationary satellite by optimal estimation

Optimal estimation (OE) is applied as a technique for retrieving sea surface temperature (SST) from thermal imagery obtained by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on Meteosat 9. OE requires simulation of observations as part of the retrieval process, and this is done here using numerical weather prediction fields and a fast radiative transfer model. Bias correction of the simulated brightness temperatures (BTs) is found to be a necessary step before retrieval, and is achieved by filtered averaging of simulations minus observations over a time period of 20 days and spatial scale of 2.5° in latitude and longitude. Throughout this study, BT observations are clear-sky averages over cells of size 0.5° in latitude and longitude. Results for the OE SST are compared to results using a traditional non-linear retrieval algorithm (“NLSST”), both validated against a set of 30108 night-time matches with drifting buoy observations. For the OE SST the mean difference with respect to drifter SSTs is − 0.01 K and the standard deviation is 0.47 K, compared to − 0.38 K and 0.70 K respectively for the NLSST algorithm. Perhaps more importantly, systematic biases in NLSST with respect to geographical location, atmospheric water vapour and satellite zenith angle are greatly reduced for the OE SST. However, the OE SST is calculated to have a lower sensitivity of retrieved SST to true SST variations than the NLSST. This feature would be a disadvantage for observing SST fronts and diurnal variability, and raises questions as to how best to exploit OE techniques at SEVIRI's full spatial resolution.

Forecasting by factors, by variables, by both or neither?

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for nowcasting or short-term forecasting, but their relative performance declines as the forecast horizon increases. Forecasts for GDP levels highlight the need for robust strategies, such as intercept corrections or differencing, when location shifts occur as in the recent financial crisis.

An “A-train” strategy for quantifying direct climate forcing by anthropogenic aerosols

This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth δ, radiative efficiency per unit optical depth E, fine-mode fraction of optical depth ff, and the anthropogenic fraction of the fine mode faf. The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of ff, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice

Step edges in thin films of lamellar-forming diblock copolymer

Self-consistent field theory (SCFT) is used to study the step edges that occur in thin films of lamellar-forming diblock copolymer, when the surfaces each have an affinity for one of the polymer components. We examine film morphologies consisting of a stack of ν continuous monolayers and one semi-infinite bilayer, the edge of which creates the step. The line tension of each step morphology is evaluated and phase diagrams are constructed showing the conditions under which the various morphologies are stable. The predicted behavior is then compared to experiment. Interestingly, our atomic force microscopy (AFM) images of terraced films reveal a distinct change in the character of the steps with increasing ν, which is qualitatively consistent with our SCFT phase diagrams. Direct quantitative comparisons are not possible because the SCFT is not yet able to probe the large polymer/air surface tensions characteristic of experiment.

Rapid qualitative and quantitative analysis of proanthocyanidin oligomers and polymers by UPLC-MS/MS.

This paper presents the development of a rapid method with ultraperformance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) for the qualitative and quantitative analyses of plant proanthocyanidins directly from crude plant extracts. The method utilizes a range of cone voltages to achieve the depolymerization step in the ion source of both smaller oligomers and larger polymers. The formed depolymerization products are further fragmented in the collision cell to enable their selective detection. This UPLC-MS/MS method is able to separately quantitate the terminal and extension units of the most common proanthocyanidin subclasses, that is, procyanidins and prodelphinidins. The resulting data enable (1) quantitation of the total proanthocyanidin content, (2) quantitation of total procyanidins and prodelphinidins including the procyanidin/prodelphinidin ratio, (3) estimation of the mean degree of polymerization for the oligomers and polymers, and (4) estimation of how the different procyanidin and prodelphinidin types are distributed along the chromatographic hump typically produced by large proanthocyanidins. All of this is achieved within the 10 min period of analysis, which makes the presented method a significant addition to the chemistry tools currently available for the qualitative and quantitative analyses of complex proanthocyanidin mixtures from plant extracts.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

The STEP scale: a measure of short-term export performance improvement

This article is a direct response to a recent observation in the literature that managers appear to be short-term oriented in their assessment of the performance of an export venture (Madsen 1998). On the basis of a cross-national survey of exporting firms, the authors present a three-dimensional scale for assessing managerial judgment of short-term export performance (i.e., the STEP scale). The three dimensions are (1) satisfaction with short-term performance improvement, (2) short-term exporting intensity improvement, and (3) expected short-term performance improvement. The scale presents evidence of reliability as well as convergent, discriminant, and nomological validity, and it reveals factorial similarity and factorial equivalence across both samples. The authors outline managerial and public policy implications that stem from the scale and identify avenues for further export marketing research.

Modulation of UK lightning by heliospheric magnetic field polarity

Observational studies have reported solar magnetic modulation of terrestrial lightning on a range of time scales, from days to decades. The proposed mechanism is two-step: lightning rates vary with galactic cosmic ray (GCR) flux incident on Earth, either via changes in atmospheric conductivity and/or direct triggering of lightning. GCR flux is, in turn, primarily controlled by the heliospheric magnetic field (HMF) intensity. Consequently, global changes in lightning rates are expected. This study instead considers HMF polarity, which doesnʼt greatly affect total GCR flux. Opposing HMF polarities are, however, associated with a 40–60% difference in observed UK lightning and thunder rates. As HMF polarity skews the terrestrial magnetosphere from its nominal position, this perturbs local ionospheric potential at high latitudes and local exposure to energetic charged particles from the magnetosphere. We speculate as to the mechanism(s) by which this may, in turn, redistribute the global location and/or intensity of thunderstorm activity.