Neuromuscular junction morphology, fiber-type proportions, and satellite-cell proliferation rates are altered in MyoD(-/-) mice

Gene compensation by members of the myogenic regulatory factor (MRF) family has been proposed to explain the apparent normal adult phenotype of MyoD(-/-) mice. Nerve and field stimulation were used to investigate contraction properties of muscle from MyoD(-/-) mice, and molecular approaches were used to investigate satellite-cell behavior. We demonstrate that MyoD deletion results in major alterations in the organization of the neuromuscular junction, which have a dramatic influence on the physiological contractile properties of skeletal muscle. Second, we show that the lineage progression of satellite cells (especially initial proliferation) in the absence of MyoD is abnormal and linked to perturbations in the nuclear localization of beta-catenin, a key readout of canonical Wnt signaling. These results show that MyoD has unique functions in both developing and adult skeletal muscle that are not carried out by other members of the MRF family.

Detecting the number of signals using antenna array: a single threshold solution

A new approach is presented to identify the number of incoming signals in antenna array processing. The new method exploits the inherent properties existing in the noise eigenvalues of the covariance matrix of the array output. A single threshold has been established concerning information about the signal and noise strength, data length, and array size. When the subspace-based algorithms are adopted the computation cost of the signal number detector can almost be neglected. The performance of the threshold is robust against low SNR and short data length.

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

The effect of extratropical cyclones on satellite-retrieved aerosol properties over ocean

Extratropical cyclones may have a signicant effect on column aerosol properties over ocean. European Centre for Medium Range Weather Forecasts (ECMWF) derived storm-centric composites of MODerate resolution Imaging Spectroradiometer (MODIS) and Advanced Along-Track Scanning Radiometer (AATSR) aerosol optical depth and aerosol size parameters are produced for the North Atlantic and the South Atlantic oceans. It is found that retrieved aerosol optical depth and aerosol size both increase near the center of the composite extratropical cyclones. Using composites of ECMWF ERA-Interim reanalysis data, it is demonstrated that wind speed is a considerably more likely explanatory variable than relative humidity for the aerosol observations. A comparison of composites for both MODIS and AATSR, which uses a wind speed dependent sea-surface brightness model in the aerosol retrieval, suggests that although surface brightness eects may contribute towards some of the observations, wind speed dependent emission of sea salt also appears to make a signicant contribution to the observed aerosol properties.

On merging gradient estimation with mean-tracking techniques for cluster identification

This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.

Application of a hybrid tracking algorithm to motion analysis

An algorithm for tracking multiple feature positions in a dynamic image sequence is presented. This is achieved using a combination of two trajectory-based methods, with the resulting hybrid algorithm exhibiting the advantages of both. An optimizing exchange algorithm is described which enables short feature paths to be tracked without prior knowledge of the motion being studied. The resulting partial trajectories are then used to initialize a fast predictor algorithm which is capable of rapidly tracking multiple feature paths. As this predictor algorithm becomes tuned to the feature positions being tracked, it is shown how the location of occluded or poorly detected features can be predicted. The results of applying this tracking algorithm to data obtained from real-world scenes are then presented.

Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends

We use microwave retrievals of upper tropospheric humidity (UTH) to estimate the impact of clear-sky-only sampling by infrared instruments on the distribution, variability and trends in UTH. Our method isolates the impact of the clear-sky-only sampling, without convolving errors from other sources. On daily time scales IR-sampled UTH contains large data gaps in convectively active areas, with only about 20-30 % of the tropics (30 S­ 30 N) being sampled. This results in a dry bias of about -9 %RH in the area-weighted tropical daily UTH time series. On monthly scales, maximum clear-sky bias (CSB) is up to -30 %RH over convectively active areas. The magnitude of CSB shows significant correlations with UTH itself (-0.5) and also with the variability in UTH (-0.6). We also show that IR-sampled UTH time series have higher interannual variability and smaller trends compared to microwave sampling. We argue that a significant part of the smaller trend results from the contrasting influence of diurnal drift in the satellite measurements on the wet and dry regions of the tropics.