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https://www.thm.lu.se/internt/staff/when-you-are-away-work - 2026-07-09

RNA medicines represent a paradigm shift in treatment and prevention of critical diseases of global significance, e.g., infectious diseases. The highly successful messenger RNA (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were developed at record speed during the coronavirus disease 2019 pandemic. A consequence of this is exceptionally shortened vaccine deve

This article discusses the role of the protein corona in delivery systems with tagged nanoparticles and how knowledge of the protein corona can help in optimizing delivery. The basic question is whether and how the binding of proteins and other biomolecules at the nanoparticle surface interfere with the interaction between a tag and its receptor. This is an interesting problem in many respects, bu

Automatic composition of geospatial web services increases the possibility of taking full advantage of spatial data and processing capabilities that have been published over the internet. In this paper, a multi-agent artificial intelligence (AI) planning solution was proposed, which works within the geoportal architecture and enables the geoportal to compose semantically annotated Open Geospatial

Objectives: The purpose of this study was to modify a clinical linear accelerator, making it capable of electron beam ultra-high dose rate (FLASH) irradiation. Modifications had to be quick, reversible, and without interfering with clinical treatments. Methods: Performed modifications: (1) reduced distance with three setup positions, (2) adjusted/optimized gun current, modulator charge rate and be

A previous caesarean delivery is no longer an indication per se for a subsequent, planned caesarean. We performed this study to identify women suitable for trial of labour after caesarean (TOLAC), investigating the association between the indication for the first caesarean and the risk of unplanned caesarean in the second pregnancy.

Försörjningskedjan har stor potential till optimering. Många olika delar av kedjan kan optimeras och alla tänkbara förbättringar har inte testats än. Denna studien har sitt fokus på ruttoptimering, med det specifika målet att förstå hur maskininlärning kan användas inom ruttplanering, samt hur nyckelfaktorer som påverkar restiden för en rutt kan tas i åtanke för problemet. Tid lades på att studerThe supply chain has potential for growth. Many different parts can be optimized, and every possible improvement has not yet been tested. This study focuses on route optimization with the specific goal of figuring out how machine learning can be applied to route planning and how key factors that impact travel time for a route can be taken into account for this problem. Time was dedicated to learn