Universal interface width distributions at the depinning threshold

We compute the probability distribution of the interface width at the depinning threshold, using recent powerful algorithms. It confirms the universality classes found previously. In all cases, the distribution is surprisingly well approximated by a generalized Gaussian theory of independant modes which decay with a characteristic propagator G(q)=1/q^(d+2 zeta); zeta, the roughness exponent, is computed independently. A functional renormalization analysis explains this result and allows to compute the small deviations, i.e. a universal kurtosis ratio, in agreement with numerics. We stress the importance of the Gaussian theory to interpret numerical data and experiments.Comment: 4 pages revtex4. See also the following article cond-mat/030146

Surveyed common data access policies preferences amongst European Reference Networks

Background: Data sharing amongst existing Rare Disease (RD) registries, even though being a process that presents multiple barriers, would enrich and ease research, as well as facilitate interoperability between the registries themselves. Methods: To understand their preferences on sharing data, we surveyed 24 European Reference Networks (ERNs) from the RD Domain. Results: The answers show that most ERNs are willing to share a set of Common Data Elements for free with authenticated users at an aggregated or pseudonymized level the moment the data is collected. The one exception is the industry sector, to which ERNs prefer to ask for a fee. Objective: Our aim is to create a reference for how most RD registries are willing to share their data, improving the ability of other stakeholders to make informed decisions to make their data interoperable.</p

Surveyed common data access policies preferences amongst European Reference Networks

Background: Data sharing amongst existing Rare Disease (RD) registries, even though being a process that presents multiple barriers, would enrich and ease research, as well as facilitate interoperability between the registries themselves. Methods: To understand their preferences on sharing data, we surveyed 24 European Reference Networks (ERNs) from the RD Domain. Results: The answers show that most ERNs are willing to share a set of Common Data Elements for free with authenticated users at an aggregated or pseudonymized level the moment the data is collected. The one exception is the industry sector, to which ERNs prefer to ask for a fee. Objective: Our aim is to create a reference for how most RD registries are willing to share their data, improving the ability of other stakeholders to make informed decisions to make their data interoperable.</p

Surveyed common data access policies preferences amongst European Reference Networks

Background: Data sharing amongst existing Rare Disease (RD) registries, even though being a process that presents multiple barriers, would enrich and ease research, as well as facilitate interoperability between the registries themselves. Methods: To understand their preferences on sharing data, we surveyed 24 European Reference Networks (ERNs) from the RD Domain. Results: The answers show that most ERNs are willing to share a set of Common Data Elements for free with authenticated users at an aggregated or pseudonymized level the moment the data is collected. The one exception is the industry sector, to which ERNs prefer to ask for a fee. Objective: Our aim is to create a reference for how most RD registries are willing to share their data, improving the ability of other stakeholders to make informed decisions to make their data interoperable.</p

Inflationary potentials yielding constant scalar perturbation spectral indices

We explore the types of slow-roll inflationary potentials that result in scalar perturbations with a constant spectral index, i.e., perturbations that may be described by a single power-law spectrum over all observable scales. We devote particular attention to the type of potentials that result in the Harrison--Zel'dovich spectrum.Comment: 8 pages, 3 figures. New general derivation method, structure change