15 research outputs found
Model Calculations for the Two-Fragment Electro-Disintegration of He
Differential cross sections for the electro-disintegration process are calculated, using a model in which
the final state interaction is included by means of a nucleon-nucleus (3+1)
potential constructed via Marchenko inversion. The required bound-state wave
functions are calculated within the integrodifferential equation approach
(IDEA). In our model the important condition that the initial bound state and
the final scattering state are orthogonal is fulfilled. The sensitivity of the
cross section to the input interaction in certain kinematical regions
is investigated. The approach adopted could be useful in reactions involving
few cluster systems where effective interactions are not well known and exact
methods are presently unavailable. Although, our Plane-Wave Impulse
Approximation results exhibit, similarly to other calculations, a dip in the
five-fold differential cross-section around a missing momentum of , it is argued that this is an artifact of the omission of re-scattering
four-nucleon processes.Comment: 16 pages, 6 figures, accepted for publication by Phys.Rev.
The re-identification risk of Canadians from longitudinal demographics
<p>Abstract</p> <p>Background</p> <p>The public is less willing to allow their personal health information to be disclosed for research purposes if they do not trust researchers and how researchers manage their data. However, the public is more comfortable with their data being used for research if the risk of re-identification is low. There are few studies on the risk of re-identification of Canadians from their basic demographics, and no studies on their risk from their longitudinal data. Our objective was to estimate the risk of re-identification from the basic cross-sectional and longitudinal demographics of Canadians.</p> <p>Methods</p> <p>Uniqueness is a common measure of re-identification risk. Demographic data on a 25% random sample of the population of Montreal were analyzed to estimate population uniqueness on postal code, date of birth, and gender as well as their generalizations, for periods ranging from 1 year to 11 years.</p> <p>Results</p> <p>Almost 98% of the population was unique on full postal code, date of birth and gender: these three variables are effectively a unique identifier for Montrealers. Uniqueness increased for longitudinal data. Considerable generalization was required to reach acceptably low uniqueness levels, especially for longitudinal data. Detailed guidelines and disclosure policies on how to ensure that the re-identification risk is low are provided.</p> <p>Conclusions</p> <p>A large percentage of Montreal residents are unique on basic demographics. For non-longitudinal data sets, the three character postal code, gender, and month/year of birth represent sufficiently low re-identification risk. Data custodians need to generalize their demographic information further for longitudinal data sets.</p