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De Vries R.,Janssen R and D NV | Barfield M.,Glaxosmithkline | Van De Merbel N.,PRA | Schmid B.,Nuvisan GmbH | And 7 more authors.
Bioanalysis | Year: 2013

Background: The European Bioanalysis Forum dried blood spots (DBS)/microsampling consortium is reporting back from the experiments they performed on further documenting the potential hurdles of the DBS technology. This paper is focused on the impact of hematocrit changes on DBS analyses. Results: The hematocrit can have an effect on the size of the blood spot, on spot homogeneity and on extraction recovery in a compound-dependent manner. The extraction recovery can change upon aging in an hematocrit-dependent way. Different card materials can give different outcomes. Conclusions: The results from the conducted experiments show that the issues of DBS in regulated bioanalysis are real and that the technology will need improvements to be ready for use as a general tool for regulated bioanalysis. © 2013 Future Science Ltd.

Cobb Z.,Quotient Bio Analytical science Part of the LGC Group | De Vries R.,Janssen R and D | Spooner N.,Glaxosmithkline | Williams S.,Charles River Laboratories | And 12 more authors.
Bioanalysis | Year: 2013

Background: At the start of their work, the European Bioanalysis Forum dried blood spots microsampling consortium did not form a dedicated team to investigate the spot homogeneity. However, two teams performed experiments that produced results relating to sample homogeneity. Results: The data, which were produced via two different approaches (a radiolabeled and a nonradiolabeled approach), are highly complementary and demonstrate clear effects on sample inhomogeneity due to the substrate type, compound and hematocrit levels. Conclusion: The results demonstrate that sample inhomogeneity is a significant hurdle to the use of dried blood spots for regulated bioanalysis that should be investigated further in the method establishment phase if the whole spot is not sampled. © 2013 Future Science Ltd.

An Y.K.,University of Alabama in Huntsville | Yoo S.-M.,University of Alabama in Huntsville | An C.,PRA | Wells E.,University of Alabama in Huntsville
KSII Transactions on Internet and Information Systems | Year: 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking. © 2013 KSII.

An Y.K.,University of Alabama in Huntsville | Yoo S.-M.,University of Alabama in Huntsville | An C.,PRA | Earl Wells B.,University of Alabama in Huntsville
Computer Communications | Year: 2013

This paper presents a new detection algorithm and high speed/accuracy tracker for tracking ground targets in acoustic wireless sensor networks (WSNs). Our detection algorithm naturally accounts for the Doppler effect which is an important consideration for tracking higher-speed targets. This algorithm employs Kalman filtering (KF) with the weighted sensor position centroid being used as the target position measurement. The weighted centroid makes the tracker to be independent of the detection model and changes the tracker to be near optimal, at least within the detection parameters used in this study. Our approach contrasts with previous approaches that employ more sophisticated tracking algorithms with higher computational complexity and use a power law detection model. The power law detection model is valid only for low speed targets and is susceptible to mismatch with detection by the sensors in the field. Our tracking model also enables us to uniquely study various environmental effects on track accuracy, such as the Doppler effect, signal collision, signal delay, and different sampling time. Our WSN tracking model is shown to be highly accurate for a moving target in both linear and accelerated motions. The computing speed is estimated to be 50-100 times faster than the previous more sophisticated methods and track accuracy compares very favorably. © 2013 Elsevier B.V. All rights reserved.

Maker D.,PRA
AIP Conference Proceedings | Year: 2010

From the Occam's razor optimized assumption of a geometric point we derive a new generally covariant generalization of the Dirac equation. We solve that equation in domains r>rH, r≈rH, and r

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