A Web-Based Distributed Virtual Educational Laboratory

Evolution and cost of measurement equipment, continuous training, and distance learning make it difficult to provide a complete set of updated workbenches to every student. For a preliminary familiarization and experimentation with instrumentation and measurement procedures, the use of virtual equipment is often considered more than sufficient from the didactic point of view, while the hands-on approach with real instrumentation and measurement systems still remains necessary to complete and refine the student's practical expertise. Creation and distribution of workbenches in networked computer laboratories therefore becomes attractive and convenient. This paper describes specification and design of a geographically distributed system based on commercially standard components

Stress Relaxation Behavior of Additively Manufactured Polylactic Acid (PLA)

In this work, the stress relaxation behavior of 3D printed PLA was experimentally investigated and analytically modeled. First, a quasi-static tensile characterization of additively manufactured samples was conducted by considering the effect of printing parameters like the material infill orientation and the outer wall presence. The effect of two thermal conditioning treatments on the material tensile properties was also investigated. Successively, stress relaxation tests were conducted, on both treated and unconditioned specimens, undergoing three different strains levels. Analytical predictive models of the viscous behavior of additive manufactured material were compared, highlighting and discussing the effects of considered printing parameters

Drop-out rate among patients treated with omalizumab for severe asthma: Literature review and real-life experience

BACKGROUND: In patients with asthma, particularly severe asthma, poor adherence to inhaled drugs negatively affects the achievement of disease control. A better adherence rate is expected in the case of injected drugs, such as omalizumab, as they are administered only in a hospital setting. However, adherence to omalizumab has never been systematically investigated. The aim of this study was to review the omalizumab drop-out rate in randomized controlled trials (RCTs) and real-life studies. A comparative analysis was performed between published data and the Italian North East Omalizumab Network (NEONet) database. RESULTS: In RCTs the drop-out rate ranged from 7.1 to 19.4 %. Although the reasons for withdrawal were only occasionally reported, patient decision and adverse events were the most frequently reported causes. In real-life studies the drop-out rate ranged from 0 to 45.5 %. In most cases lack of efficacy was responsible for treatment discontinuation. According to NEONet data, 32 % of treated patients dropped out, with an increasing number of drop outs observed over time. Patient decision and lack of efficacy accounted for most treatment withdrawals. CONCLUSIONS: Treatment adherence is particularly crucial in patients with severe asthma considering the clinical impact of the disease and the cost of non-adherence. The risk of treatment discontinuation has to be carefully considered both in the experimental and real-life settings. Increased knowledge regarding the main reasons for patient withdrawal is important to improve adherence in clinical practice

Drop-out rate among patients treated with omalizumab for severe asthma: Literature review and real-life experience

In patients with asthma, particularly severe asthma, poor adherence to inhaled drugs negatively affects the achievement of disease control. A better adherence rate is expected in the case of injected drugs, such as omalizumab, as they are administered only in a hospital setting. However, adherence to omalizumab has never been systematically investigated. The aim of this study was to review the omalizumab drop-out rate in randomized controlled trials (RCTs) and real-life studies. A comparative analysis was performed between published data and the Italian North East Omalizumab Network (NEONet) database

BeyondPlanck II. CMB map-making through Gibbs sampling

We present a Gibbs sampling solution to the map-making problem for CMB measurements, building on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps; noise filtering and map binning. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods, and allows us for the first time to bring the destriping baseline length to a single sample. We apply the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we may compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction, and this methodology forms the conceptual basis for the map-making algorithm employed in the BeyondPlanck framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations.Comment: 11 pages, 10 figures. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science during the online release conference (November 18-20, 2020). Connection details will be made available at the same website. Registration is mandatory for the online tutorial, but optional for the conferenc