Insertion/deletion-related polymorphisms in the human T cell receptor beta gene complex.

Insertion/deletion related polymorphisms (IDRP) involving stretches of 15-30 kb within the human TCR-beta gene complex were revealed by pulse-field gel electrophoresis. Two independent IDRP systems were detected by analysis of Sfi I- and Sal I-digested human DNA samples using probes for TCR C and V region gene segments. The allelic nature of these systems was verified in family studies, and mapping data allowed localization of one area of insertion/deletion among the V gene segments and the other near the C region genes. All but one of 50 individuals tested could be typed for the two allelic systems, and gene frequencies for the two allelic forms were 0.37/0.61 and 0.46/0.54, indicating that these polymorphisms are widespread

Three-dimensional Imaging of Microstructure in Gold Nanocrystals

X-ray diffraction using a coherent beam involves the mutual interference among all the extremities of small crystals. The continuous diffraction pattern so produced can be phased because it can be oversampled. We have thus obtained three-dimensional images of the interiors of Au nanocrystals that show 50 nm wide bands of contrast with f111g orientation that probably arise from internal twinning by dynamic recrystallization during their formation at high temperature

Reconstruction of the Shapes of Gold Nanocrystals using Coherent X-ray Diffraction

Inverse problems arise frequently in physics: The magnitude of the Fourier transform of some function is measurable, but not its phase. The “phase problem” in crystallography arises because the number of discrete measurements (Bragg peak intensities) is only half the number of unknowns (electron density points in space). Sayre first proposed that oversampling of diffraction data should allow a solution, and this has recently been demonstrated. Here we report the successful phasing of an oversampled hard x-ray diffraction pattern measured from a single nanocrystal of gold

An evaluation of two distributed deployment algorithms for Mobile Wireless Sensor Networks

Deployment is important in large wireless sensor networks (WSN), specially because nodes may fall due to failure or battery issues. Mobile WSN cope with deployment and reconfiguration at the same time: nodes may move autonomously: i) to achieve a good area coverage; and ii) to distribute as homogeneously as possible. Optimal distribution is computationally expensive and implies high tra c load, so local, distributed approaches may be preferable. This paper presents an experimental evaluation of role-based and behavior based ones. Results show that the later are better, specially for a large number of nodes in areas with obstacles.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The Imperial IRAS-FSC Redshift Catalogue: luminosity functions, evolution and galaxy bias

We present the luminosity function and selection function of 60 micron galaxies selected from the Imperial IRAS-FSC Redshift Catalogue (IIFSCz). Three methods, including the 1/Vmax} and the parametric and non-parametric maximum likelihood estimator, are used and results agree well with each other. A density evolution proportional to (1+z)^3.4 or a luminosity evolution exp(1.7 t_L / \tau)$ where t_L is the look-back time is detected in the full sample in the redshift range [0.02, 0.1], consistent with previous analyses. Of the four infrared subpopulations, cirrus-type galaxies and M82-type starbursts show similar evolutionary trends, galaxies with significant AGN contributions show stronger positive evolution and Arp 220-type starbursts exhibit strong negative evolution. The dominant subpopulation changes from cirrus-type galaxies to M82-type starbursts at log (L_60 / L_Sun) ~ 10.3. In the second half of the paper, we derive the projected two-point spatial correlation function for galaxies of different infrared template type. The mean relative bias between cirrus-type galaxies and M82-type starbursts, which correspond to quiescent galaxies with optically thin interstellar dust and actively star-forming galaxies respectively, is calculated to be around 1.25. The relation between current star formation rate (SFR) in star-forming galaxies and environment is investigated by looking at the the dependence of clustering on infrared luminosity. We found that M82-type actively star-forming galaxies show stronger clustering as infrared luminosity / SFR increases. The correlation between clustering strength and SFR in the local Universe seems to echo the basic trend seen in star-forming galaxies in the Great Observatories Origins Deep Survey (GOODS) fields at z ~ 1.Comment: 15 pages, 11 figures, accepted for publication in MNRA

Rubidium "whiskers" in a vapor cell

Crystals of metallic rubidium are observed ``growing'' from paraffin coating of buffer-gas-free glass vapor cells. The crystals have uniform square cross-section, $\approx 30 \mu$m on the side, and reach several mm in length.Comment: 2 pages, 1 figur

Statistical Parametric Mapping (SPM) for alpha-based statistical analyses of multi-muscle EMG time-series.

Multi-muscle EMG time-series are highly correlated and time dependent yet traditional statistical analysis of scalars from an EMG time-series fails to account for such dependencies. This paper promotes the use of SPM vector-field analysis for the generalised analysis of EMG time-series. We reanalysed a publicly available dataset of Young versus Adult EMG gait data to contrast scalar and SPM vector-field analysis. Independent scalar analyses of EMG data between 35% and 45% stance phase showed no statistical differences between the Young and Adult groups. SPM vector-field analysis did however identify statistical differences within this time period. As scalar analysis failed to consider the multi-muscle and time dependence of the EMG time-series it exhibited Type II error. SPM vector-field analysis on the other hand accounts for both dependencies whilst tightly controlling for Type I and Type II error making it highly applicable to EMG data analysis. Additionally SPM vector-field analysis is generalizable to linear and non-linear parametric and non-parametric statistical models, allowing its use under constraints that are common to electromyography and kinesiology

Can segmental model reductions quantify whole-body balance accurately during dynamic activities?

When investigating whole-body balance in dynamic tasks, adequately tracking the whole-body centre of mass (CoM) or derivatives such as the extrapolated centre of mass (XCoM) can be crucial but add considerable measurement efforts. The aim of this study was to investigate whether reduced kinematic models can still provide adequate CoM and XCoM representations during dynamic sporting tasks. Seventeen healthy recreationally active subjects (14 males and 3 females; age, 24.9±3.2years; height, 177.3±6.9cm; body mass 72.6±7.0kg) participated in this study. Participants completed three dynamic movements, jumping, kicking, and overarm throwing. Marker-based kinematic data were collected with 10 optoelectronic cameras at 250Hz (Oqus Qualisys, Gothenburg, Sweden). The differences between (X)CoM from a full-body model (gold standard) and (X)CoM representations based on six selected model reductions were evaluated using a Bland-Altman approach. A threshold difference was set at ±2cm to help the reader interpret which model can still provide an acceptable (X)CoM representation. Antero-posterior and medio-lateral displacement profiles of the CoM representation based on lower limbs, trunk and upper limbs showed strong agreement, slightly reduced for lower limbs and trunk only. Representations based on lower limbs only showed less strong agreement, particularly for XCoM in kicking. Overall, our results provide justification of the use of certain model reductions for specific needs, saving measurement effort whilst limiting the error of tracking (X)CoM trajectories in the context of whole-body balance investigation

The probability of false positives in zero-dimensional analyses of one-dimensional kinematic, force and EMG trajectories

A false positive is the mistake of inferring an e↵ect when none exists, and although alpha controls the false positive (Type I error) rate in classical hypothesis testing, a given alpha value is accurate only if the underlying model of randomness appropriately reflects experimentally observed variance. Hypotheses pertaining to one-dimensional (1D) (e.g. time-varying) biomechanical trajectories are most often tested using a traditional zero-dimensional (0D) Gaussian model of randomness, but variance in these datasets variance is clearly 1D. The purpose of this study was to determine the likelihood that analyzing smooth 1D data with a 0D model of variance will produce false positives. We first used random field theory (RFT) to predict the probability of false positives in 0D analyses. We then validated RFT predictions via numerical simulations of smooth Gaussian 1D trajectories. Results showed that, across a range of public kinematic, force and EMG datasets, the median false positive rate was 0.382 and not the assumed alpha=0.05, even for a simple two-sample t test involving N=10 trajectories per group. The median false positive rates for experiments involving three-component vector trajectories was p=0.764. This rate increased to p=0.945 for two three-component vector trajectories, and to p=0.999 for six three-component vectors. This implies that experiments involving vector trajectories have a high probability of yielding 0D statistical significance when there is, in fact, no 1D effect. Either (a) explicit a priori identification of 0D metrics or (b) adoption of 1D methods can more tightly control alpha