Swedish Defence Research Agency

About: Swedish Defence Research Agency is a government organization based out in Stockholm, Sweden. It is known for research contribution in the topics: Radar & Laser. The organization has 1413 authors who have published 2731 publications receiving 56083 citations. The organization is also known as: Totalförsvarets forskningsinstitut.

Feasibility Study of Mesoporous Silica Particles for Pulmonary Drug Delivery: Therapeutic Treatment with Dexamethasone in a Mouse Model of Airway Inflammation

Abstract: Diseases in the respiratory tract rank among the leading causes of death in the world, and thus novel and optimized treatments are needed. The lungs offer a large surface for drug absorption, and the inhalation of aerosolized drugs are a well-established therapeutic modality for local treatment of lung conditions. Nanoparticle-based drug delivery platforms are gaining importance for use through the pulmonary route. By using porous carrier matrices, higher doses of especially poorly soluble drugs can be administered locally, reducing their side effects and improving their biodistribution. In this study, the feasibility of mesoporous silica particles (MSPs) as carriers for anti-inflammatory drugs in the treatment of airway inflammation was investigated. Two different sizes of particles on the micron and nanoscale (1 µm and 200 nm) were produced, and were loaded with dexamethasone (DEX) to a loading degree of 1:1 DEX:MSP. These particles were further surface-functionalized with a polyethylene glycol–polyethylene imine (PEG–PEI) copolymer for optimal aqueous dispersibility. The drug-loaded particles were administered as an aerosol, through inhalation to two different mice models of neutrophil-induced (by melphalan or lipopolysaccharide) airway inflammation. The mice received treatment with either DEX-loaded MSPs or, as controls, empty MSPs or DEX only; and were evaluated for treatment effects 24 h after exposure. The results show that the MEL-induced airway inflammation could be treated by the DEX-loaded MSPs to the same extent as free DEX. Interestingly, in the case of LPS-induced inflammation, even the empty MSPs significantly down-modulated the inflammatory response. This study highlights the potential of MSPs as drug carriers for the treatment of diseases in the airways.

Viscous and Aeroelastic Effects on Wind Turbine Blades. The VISCEL project. Part I: 3D Navier–Stokes Rotor simulations

Abstract: Aerodynamic modelling of HAWT rotors by means of “engineering methods” has reached a saddle point, where no further development can be expected without a breakthrough in understanding the physics of unsteady, rotating three-dimensional flows. However, such a breakthrough becomes ever more necessary, as the size of the wind turbines increases. With the experimental work in that direction being mostly limited to observing the phenomena and interpreting the associated mechanisms, and its increased cost, alternatives are being sought. The use of CFD techniques and state-of-the-art Navier–Stokes solvers is considered a very serious contender, a belief shared by the members of the present consortium, which has worked on the VISCEL JOR3-CT98-0208 Joule III project. This project's goal was to determine the aerodynamic characteristics as well as the aeroelastic behaviour of wind turbine blades across their broad range of operational conditions, from attached to highly separated flow regimes. The work programme included specific tasks for the validation and assessment of existing 3D solvers, for the parametric study of 3D flow around realistic blades and for the investigation of aeroelastic stability, at the blade section level. Copyright © 2003 John Wiley & Sons, Ltd.

Timeprints for identifying social media users with multiple aliases

Abstract: Many people who discuss sensitive or private issues on social media services are using pseudonyms or aliases in order to not reveal their true identity, while using their usual, non-private accounts when posting messages on less sensitive issues. Previous research has shown that if those individuals post large amounts of user-generated content, stylometric techniques can be used to identify the author based on the characteristics of the textual content. In this article we show how an author’s identity can be unmasked in a similar way using various time features (e.g., period of the day and the day of the week when a user’s posts have been published). We combine several different time features into a timeprint, which can be seen as a type of fingerprint when identifying users on social media. We use supervised machine learning (i.e., author identification) and unsupervised alias matching (similarity detection) in a number of different experiments with forum data to get an understanding of to what extent timeprints can be used for identifying users in social media, both in isolation and when combined with stylometric features. The obtained results show that timeprints indeed can be a very powerful tool for both author identification and alias matching in social media.