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The random fluctuations of spins give rise to many interesting physical phenomena, such as the 'order-from-disorder' arising in frustrated magnets and unconventional Cooper pairing in magnetic superconductors. Here we show that the exchange of spin waves between extended topological defects, such as domain walls, can result in novel magnetic states. We report the discovery of an unusual incommensu
Regulatory frameworks within the European Union demand that chemical substances are investigated for their ability to induce sensitization, an adverse health effect caused by the human immune system in response to chemical exposure. A recent ban on the use of animal tests within the cosmetics industry has led to an urgent need for alternative animal-free test methods that can be used for assessmen
Diabetes is a much more heterogeneous disease than the present subdivision into types 1 and 2 assumes; type 1 and type 2 diabetes probably represent extremes on a range of diabetic disorders. Both type 1 and type 2 diabetes seem to result from a collision between genes and environment. Although genetic predisposition establishes susceptibility, rapid changes in the environment (ie, lifestyle facto
We demonstrate experimentally nonequilibrium transport in unipolar quasi-1D hot electron devices reaching the ballistic limit at room temperature. The devices are realized with heterostructure engineering in nanowires to obtain dopant- and dislocation-free 1D-epitaxy and flexible bandgap engineering. We show experimentally the control of hot electron injection with a graded conduction band profile
In this paper, we address the multi pursuer version of the pursuit evasion problem in polygonal environments. It is well known that this problem is NP-hard, and therefore we seek efficient, but not optimal, solutions by relaxing the problem and applying the tools of Mixed Integer Linear Programming (MILP) and Receding Horizon Control (RHC). Approaches using MILP and RHC are known to produce effici
Extrapolation in Time in Thermal Fluid Structure Interaction Philipp Birken, Tobias Gleim, Detlef Kuhl and Andreas Meister Abstract We consider time dependent thermal fluid structure interaction. The re- spective models are the compressible Navier-Stokes equations and the nonlinear heat equation. A partitioned coupling approach via a Dirichlet-Neumann method and a fixed point iteration is employed
https://www.maths.lu.se/fileadmin/maths/personal_staff/Philipp_Birken/BirkenGleimKuhlMeisterCE14.pdf - 2026-07-10
Dividends effect on stock prices and shareholders return is a disputed subject in finance. The purpose of this thesis is to expand on the existing research both the effect of dividends in general and on stocks on the Swedish market in particular. This thesis establishes an index of stocks with 5 or more years of dividend growth for at least the last 5 years on the Swedish market, by comparing this
This study has been carried out, as part of the course Fire Safety Evaluation at Lund Technical University, to assess the fire safety of an elementary school in Flen. The study is made up of three parts, an overview and description of the school, an analysis of possible fire scenarios within the school compound, and a set of action proposals based on the findings from the analysis. In the analysis
This report was made in order to evaluate the safety of persons within the hotel Scandic Arvika in case of fire. Except for the hotel rooms, Scandic Arvika is also arranging conferences and festivities throughout the year. The building was constructed in 1815 and has since then been updated with several changes which have made the evacuation situation of the hotel complex, and therefore this is th
There have been many studies made which measure the effects of trade facilitation on trade flows, and it is has been established that there are large gains from improving inefficient and cumbersome trade procedures that act as a barrier to trade. Still there are differences between countries and their level of trade facilitation. With a framework defining resources indicator and protectionist indi
Accurately predicting future stock prices is a dream for many investors. The inherent uncertainty and complexity of financial markets makes price prediction a difficult task. However, the recent advancements of neural networks in the field of machine learning have introduced new possibilities for accurately predicting future prices. We explore the application of the Transformer, a recent model whi
