An investigation of planar array system artefacts generated within an electrical impedance mammography system developed for breast cancer detection

An Electrical Impedance Mammography (EIM) planar array imaging system is being developed at the University of Sussex for the detection of breast cancers. Investigations have shown that during data collection, systematic errors and patient artefacts are frequently introduced during signal acquisition from different electrodes pairs. This is caused, in particular, by the large variations in the electrode-skin contact interface conditions occurring between separate electrode positions both with the same and different patients. As a result, the EIM image quality is seriously affected by these errors. Hence, this research aims to experimentally identify, analyse and propose effective methods to reduce the systematic errors at the electrode-skin interface. Experimental studies and subsequent analysis is presented to determine what ratio of electrode blockage seriously affects the acquired raw data which may in turn compromise the reconstruction. This leads to techniques for the fast and accurate detection of any such occurrences. These methodologies can be applied to any planar array based EIM system

A note on the fine structure constant

We derive the numerical value of the fine structure constant $\alpha$ in purely number-theoretic terms, under the assumption that in a system of charges between two parallel conducting plates, the Casimir energy and the mutual Coulomb interaction energy agree

A note on the fine structure constant

We derive the numerical value of the fine structure constant in purely number-theoretic terms, under the assumption that in a system of charges between two parallel conducting plates, the Casimir energy and the mutual Coulomb interaction energy agree

A note on the fine structure constant

We derive the numerical value of the fine structure constant in purely number-theoretic terms, under the assumption that in a system of charges between two parallel conducting plates, the Casimir energy and the mutual Coulomb interaction energy agree

One-step Estimation of Networked Population Size: Respondent-Driven Capture-Recapture with Anonymity

Population size estimates for hidden and hard-to-reach populations are particularly important when members are known to suffer from disproportion health issues or to pose health risks to the larger ambient population in which they are embedded. Efforts to derive size estimates are often frustrated by a range of factors that preclude conventional survey strategies, including social stigma associated with group membership or members' involvement in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, to be used in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. Provably sufficient conditions for the consistency of these estimators (in large configuration networks) are given. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which are seen to perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population estimates can be derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. Limitations and future work are discussed in the concluding section