Extended Validation using DNSSEC

Abstract Remote trust on the web is mostly handled by so called Certificate Authorities. companies, government bodies or other types of organisations that users go to to obtain their own certificates. There is a significant leap of faith involved: why should you blindly trust the hundreds of Certificate Authorities preloaded in your browser to not abuse their root certificates, when many Certificate Authorities are organisations you don't know anything about -which means you might not want to trust them for all purposes, certainly not if you can avoid it. What if the websites and services you care about can publish the certificates they use safely and authoritatively through the DNS? Historically, the answer was that DNS itself was not safe enough. With DNSSEC you get a chain of trust from the signed root of the internet to the service you want to connect to. We have researched different ways of doing this and made available an add-on to the new Firefox 4.0 browser software which enables end-users and server administrators to leverage the DNSSEC chain of trust as anchor for their certificates. February 7, 2011 Acknowledgements We would like to thank the following people and organisations for their guidance and support during our project: • Michiel Leenaars (NLnet Foundation) for his supervision and incredible support; • Rick van Rein (OpenFortress) for his insight, ideas and feedback; • The System and Network Engineering (University of Amsterdam) group for the means and opportunity to conduct the research project.

Permanent and live load model for probabilistic structural fire analysis : a review

Probabilistic analysis is receiving increased attention from fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic structural fire engineering, the models used to describe the permanent and live load differ widely between studies. Through a literature review, it is observed that these diverging load models largely relate to the same underlying datasets and basic methodologies, while differences can be attributed (largely) to specific assumptions in different background papers which have become consolidated through repeated use in application studies by different researchers. Taking into account the uncovered background information, consolidated probabilistic load models are proposed

Structure of the central Sumatran subduction zone revealed by local earthquake travel-time tomography using an amphibious network

The Sumatran subduction zone exhibits strong seismic and tsunamogenic potential with the prominent examples of the 2004, 2005 and 2007 earthquakes. Here, we invert travel time data of local earthquakes for vp and vp/vs velocity models of the central Sumatran forearc. Data were acquired by an amphibious seismometer network consisting of 52 land stations and 10 ocean bottom seismometers located on a segment of the Sumatran subduction zone that had not ruptured in a great earthquake since 1797 but witnessed recent ruptures to the north in 2005 (Nias earthquake, Mw = 8.7) and to the south in 2007 (Bengkulu earthquake, Mw = 8.5). 2D and 3D vp velocity anomalies reveal the downgoing slab and the sedimentary basins. Although the seismicity pattern in the study area appears to be strongly influenced by the obliquely subducting Investigator Fracture Zone to at least 200 km depth, the 3D velocity model shows prevailing trench parallel structures at depths of the plate interface. The tomographic model suggests a thinned crust below the basin east of the forearc islands (Nias, Pulau Batu, Siberut) at ~ 180 km distance to the trench. Vp velocities beneath the magmatic arc and the Sumatran fault zone SFZ are around 5 km/s at 10 km depth and the vp/vs ratios in the uppermost 10 km are low, indicating the presence of felsic lithologies typical for continental crust. We find moderately elevated vp/vs values of 1.85 at ~ 150 km distance to the trench in the region of the Mentawai fault. Vp/vs ratios suggest absence of large scale alteration of the mantle wedge and might explain why the seismogenic plate interface (observed as a locked zone from geodetic data) extends below the continental forearc Moho in Sumatra. Reduced vp velocities beneath the forearc basin covering the region between Mentawai Islands and the Sumatra mainland possibly reflect a reduced thickness of the overriding crust

Technology Readiness Levels for Machine Learning Systems

The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards to streamline development for high-quality, reliable results. The extreme is spacecraft systems, where mission critical measures and robustness are ingrained in the development process. Drawing on experience in both spacecraft engineering and ML (from research through product across domain areas), we have developed a proven systems engineering approach for machine learning development and deployment. Our "Machine Learning Technology Readiness Levels" (MLTRL) framework defines a principled process to ensure robust, reliable, and responsible systems while being streamlined for ML workflows, including key distinctions from traditional software engineering. Even more, MLTRL defines a lingua franca for people across teams and organizations to work collaboratively on artificial intelligence and machine learning technologies. Here we describe the framework and elucidate it with several real world use-cases of developing ML methods from basic research through productization and deployment, in areas such as medical diagnostics, consumer computer vision, satellite imagery, and particle physics

Obstacle tower : a generalization challenge in vision, control, and planning

The rapid pace of recent research in AI has been driven in part by the presence of fast and challenging simulation environments. These environments often take the form of games; with tasks ranging from simple board games, to competitive video games. We propose a new benchmark - Obstacle Tower: a high fidelity, 3D, 3rd person, procedurally generated environment. An agent playing Obstacle Tower must learn to solve both low-level control and high-level planning problems in tandem while learning from pixels and a sparse reward signal. Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment. In this paper we outline the environment and provide a set of baseline results produced by current state-of-the-art Deep RL methods as well as human players. These algorithms fail to produce agents capable of performing near human level.peer-reviewe

Natalizumab treatment shows low cumulative probabilities of confirmed disability worsening to EDSS milestones in the long-term setting.

Abstract Background Though the Expanded Disability Status Scale (EDSS) is commonly used to assess disability level in relapsing-remitting multiple sclerosis (RRMS), the criteria defining disability progression are used for patients with a wide range of baseline levels of disability in relatively short-term trials. As a result, not all EDSS changes carry the same weight in terms of future disability, and treatment benefits such as decreased risk of reaching particular disability milestones may not be reliably captured. The objectives of this analysis are to assess the probability of confirmed disability worsening to specific EDSS milestones (i.e., EDSS scores ≥3.0, ≥4.0, or ≥6.0) at 288 weeks in the Tysabri Observational Program (TOP) and to examine the impact of relapses occurring during natalizumab therapy in TOP patients who had received natalizumab for ≥24 months. Methods TOP is an ongoing, open-label, observational, prospective study of patients with RRMS in clinical practice. Enrolled patients were naive to natalizumab at treatment initiation or had received ≤3 doses at the time of enrollment. Intravenous natalizumab (300 mg) infusions were given every 4 weeks, and the EDSS was assessed at baseline and every 24 weeks during treatment. Results Of the 4161 patients enrolled in TOP with follow-up of at least 24 months, 3253 patients with available baseline EDSS scores had continued natalizumab treatment and 908 had discontinued (5.4% due to a reported lack of efficacy and 16.4% for other reasons) at the 24-month time point. Those who discontinued due to lack of efficacy had higher baseline EDSS scores (median 4.5 vs. 3.5), higher on-treatment relapse rates (0.82 vs. 0.23), and higher cumulative probabilities of EDSS worsening (16% vs. 9%) at 24 months than those completing therapy. Among 24-month completers, after approximately 5.5 years of natalizumab treatment, the cumulative probabilities of confirmed EDSS worsening by 1.0 and 2.0 points were 18.5% and 7.9%, respectively (24-week confirmation), and 13.5% and 5.3%, respectively (48-week confirmation). The risks of 24- and 48-week confirmed EDSS worsening were significantly higher in patients with on-treatment relapses than in those without relapses. An analysis of time to specific EDSS milestones showed that the probabilities of 48-week confirmed transition from EDSS scores of 0.0–2.0 to ≥3.0, 2.0–3.0 to ≥4.0, and 4.0–5.0 to ≥6.0 at week 288 in TOP were 11.1%, 11.8%, and 9.5%, respectively, with lower probabilities observed among patients without on-treatment relapses (8.1%, 8.4%, and 5.7%, respectively). Conclusions In TOP patients with a median (range) baseline EDSS score of 3.5 (0.0–9.5) who completed 24 months of natalizumab treatment, the rate of 48-week confirmed disability worsening events was below 15%; after approximately 5.5 years of natalizumab treatment, 86.5% and 94.7% of patients did not have EDSS score increases of ≥1.0 or ≥2.0 points, respectively. The presence of relapses was associated with higher rates of overall disability worsening. These results were confirmed by assessing transition to EDSS milestones. Lower rates of overall 48-week confirmed EDSS worsening and of transitioning from EDSS score 4.0–5.0 to ≥6.0 in the absence of relapses suggest that relapses remain a significant driver of disability worsening and that on-treatment relapses in natalizumab-treated patients are of prognostic importance