Holographic digital Fourier microscopy for selective imaging of biological tissue

We present an application of digital Fourier holography for selective imaging of scatterers with different sizes in turbid media such as biological tissues. A combination of Fourier holography and high‐resolution digital recording, digital Fourier microscopy (DFM) permits crucial flexibility in applying filtering to highlight scatterers of interest in the tissue. The high‐resolution digital hologram is a result of the collation of Fourier holographic frames to form a large‐size composite hologram. It is expected that DFM has an improved signal‐to‐noise ratio as compared to conventional direct digital imaging, e.g., phase microscopy, as applied to imaging of small‐size objects. The demonstration of the Fourier filtering capacity of DFM using a biological phantom represents the main focus of this article. © 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 14, 253–258, 2004; Published online inWiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20031     

Two-Dimensional Nuclear Magnetic Resonance Studies of Starch and Starch Products

The use of two-dimensional Nuclear Magnetic Resonance (NMR) spectroscopy as applied to studies of starch, starch products and glycogen is reported. The use of both homonuclear correlation (COSY, relay-COSY and HOHAHA) and heteronuclear correlation (HMQC, HETCOR) experiments is discussed. This approach makes it possible to obtain complete assignments of the proton NMR spectra of these polysaccharides. This is not possible from 1-D spectra due to excessive overlap of the non-anomeric proton signals. The resulting assignments are useful in obtaining structural information regarding starch and related products. Moreover, the greater inherent resolution of the two-dimensional spectra can reveal the presence of low molecular weight carbohydrates (glucose, maltose etc.) in dextrin samples, thus providing information about carbohydrate composition.     

Suitability of European climate for the Asian tiger mosquito Aedes albopictus: recent trends and future scenarios

The Asian tiger mosquito (Aedes albopictus) is an invasive species that has the potential to transmit infectious diseases such as dengue and chikungunya fever. Using high-resolution observations and regional climate model scenarios for the future, we investigated the suitability of Europe for A. albopictus using both recent climate and future climate conditions. The results show that southern France, northern Italy, the northern coast of Spain, the eastern coast of the Adriatic Sea and western Turkey were climatically suitable areas for the establishment of the mosquito during the 1960–1980s. Over the last two decades, climate conditions have become more suitable for the mosquito over central northwestern Europe (Benelux, western Germany) and the Balkans, while they have become less suitable over southern Spain. Similar trends are likely in the future, with an increased risk simulated over northern Europe and slightly decreased risk over southern Europe. These distribution shifts are related to wetter and warmer conditions favouring the overwintering of A. albopictus in the north, and drier and warmer summers that might limit its southward expansion.     

A Bayesian spatial econometric analysis of the 2010 UK General Election

The Conservative Party won the 2010 General Election in the United Kingdom, gaining the most votes and seats of any single party. Using Bayesian spatial econometric methods, we show that significant spatial dependence exists in Conservative voting behaviour and select the spatial Durbin model as the best model to explain this phenomenon. This paper examines these spatial effects as well as the effects of a range of economic, socio‐economic, and political variables. Perhaps the most interesting result is that incumbency has effects beyond an incumbent's own constituency.     

Fault identification for robot manipulators

Several factors must be considered for robotic task execution in the presence of a fault, including: detection, identification, and accommodation for the fault. In this paper, a nonlinear observer is used to identify a class of actuator faults once the fault has been detected by some other method. Advantages of the proposed fault-identification method are that it is based on the nonlinear dynamic model of a robot manipulator (and hence, can be extended to a number of general Euler Lagrange systems), it does not require acceleration measurements, and it is independent from the controller. A Lyapunov-based analysis is provided to prove that the developed fault observer converges to the actual fault. Experimental results are provided to illustrate the performance of the identification method.     

Homography-based visual servo tracking control of a wheeled mobile robot

A visual servo tracking controller is developed in this paper for a monocular camera system mounted on an underactuated wheeled mobile robot (WMR) subject to nonholonomic motion constraints (i.e., the camera-in-hand problem). A prerecorded image sequence (e.g., a video) of three target points is used to define a desired trajectory for the WMR. By comparing the target points from a stationary reference image with the corresponding target points in the live image and the prerecorded sequence of images, projective geometric relationships are exploited to construct Euclidean homographies. The information obtained by decomposing the Euclidean homography is used to develop a kinematic controller. A Lyapunov-based analysis is used to develop an adaptive update law to actively compensate for the lack of depth information required for the translation error system. Experimental results are provided to demonstrate the control design.