GELIFICATION - A SIMPLE AND EFFICIENT METHOD FOR ON-CHIP STORAGE OF REAGENTS: TOWARDS LAB-ON-A-CHIP SYSTEMS FOR POINT-OF-CARE DIAGNOSTICS

In this study, we describe a simple and efficient method for on-chip storage of reagents for point-of-care (POC) diagnostics. The method is based on gelification of all reagents required for on-chip PCR-based diagnostics as a ready-to-use product. The result reported here is a key step towards the development of a ready and easy to use fully integrated Lab-on-a-chip (LOC) system for fast, cost-effective and efficient POC diagnostics analysis.

Measurement of the full stress tensor in a crystal using photoluminescence from point defects: The example of nitrogen vacancy centers in diamond

We introduce a method for measuring the full stress tensor in a crystal utilising the properties of individual point defects. By measuring the perturbation to the electronic states of three point defects with C 3 v symmetry in a cubic crystal, sufficient information is obtained to construct all six independent components of the symmetric stress tensor. We demonstrate the method using photoluminescence from nitrogen-vacancy colour centers in diamond. The method breaks the inverse relationship between spatial resolution and sensitivity that is inherent to existing bulk strain measurement techniques, and thus, offers a route to nanoscale strain mapping in diamond and other materials in which individual point defects can be interrogated.

The mend of the bend-flexor pollicis longus tendon has an additional pulley distal to its point of angulation

The tendon of flexor pollicis longus angulates at the trapezio-metacarpal joint level. The degree of angulation varies with extent of radial/ulnar deviation (Rack and Ross [1984] J. Physiol. 351:99–110). We report a fibrous pulley at this level that helps stabilize the tendon and facilitates its action. The morphology of the pulley is described. We believe that it has an important role to play in the unique function of the tendon facilitating the movement of the thumb perpendicular to the plane of the thumbnail. Clin. Anat. 21:427–432, 2008. © 2008 Wiley-Liss, Inc

Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

Robust 2D Ear Registration and Recognition Based on SIFT Point Matching

Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees and with over 20% occlusion.

Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors

Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.