Filtyp
The purpose of the present chapter is to outline the principles of experimental phenomenology as an approach to research on spirituality. Experimental phenomenology is the investigation of phenomenological practices and their impact. Essential to phenomenological practices is that they involve intentional variations of experiencing by means of changes in the direction of attention and the choice o
Human–robot collaboration (HRC) in manufacturing environments requires that physical safety can be guaranteed. Control methods that implicitly regulate the interaction forces between a controlled robot and its environment, such as impedance control, are often used for safety in HRC. However, these methods could be complemented by restricting the robot operational space for additional safety guaran
In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was perfo
Den 6 juli 2023 tillsattes en särskild utredare med uppdraget att ”överväga och föreslå ändringar av den straffrättsliga särbehandlingen av unga lagöverträdare”. Som en del av detta skulle möjligheten till en sänkt straffbarhetsålder undersökas. I slutbetänkandet som presenterades i januari 2025, föreslogs en differentierad sänkning av straffbarhetsåldern till 14 år. I den efterföljande lagrådsremOn July 6, 2023, an inquiry chair was appointed with the mandate to “consider and propose changes to the special treatment of young offenders under criminal law”. The possibility of lowering the age of criminal responsibility was to be examined. In the final report presented in January 2025, a reduction of the age of criminal responsibility to 14 years was proposed. The subsequent referral to the
Generative AI promises substantial productivity gains, but many initiatives fail. This column argues that outcomes depend on readiness, not technology alone. We examine AI transformation requirements across organizational, individual, and technological dimensions, highlighting why engineering practices, human factors, and strategic clarity determine success.
This paper introduces an improved method for real-time brain computer interface control. We demonstrate how Bayesian optimization and feedback can be used to achieve faster statistical convergence by controlling the sequence of stimuli shown in a brain computer interface based on a visual oddball paradigm.
It is common that PID control loops function satisfactorily most of the time, but that they have issues with violating input, state, or output constraints. While MPC solves this problem in principle, it is in practice not straightforward to replace a functioning PID controller with an MPC implementation. This is particularly true for loops that are critical to plant operation, where stops associat
The PID controller is the by far most frequently employed type of controller. As you read, billions of digitally implemented PID controllers are running, shaping the dynamic behavior of anything from the fan speed in your laptop to safety-critical components in nuclear power plants. Given the abundance of commissioned PID controllers, it is surprisingly hard to find a single source that provides a
With increased autonomy in marine vessels, autonomous surface vessels (ASVs) and conventionally manned vessels need to coexist at sea. Any relocation needs to include collision avoidance according to the traffic rules at sea, COLREGs. Here, a local collision-avoidance planner for an archipelago environment is presented. The optimization-based local planner presented considers a predefined nominal
Probing the cellular structure of in vivo biological tissue is a fundamental problem in biomedical imaging and medical science. This work introduces an approach for analyzing diffusion magnetic resonance imaging data acquired by the novel tensor-valued encoding technique for characterizing tissue microstructure. Our approach first uses a signal model to estimate the variance and skewness of the di
Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distributions of diffusion ten
The Soma and Neurite Density Imaging (SANDI) three-compartment model was recently proposed to disentangle cylindrical and spherical geometries, attributed to neurite and soma compartments, respectively, in brain tissue. There are some recent advances in diffusion-weighted MRI signal encoding and analysis (including the use of multiple so-called ’b-tensor’ encodings and analysing the signal in the
Carefully selecting the source data is crucial to achieve high performance of transfer learning methods for brain–computer interfaces (BCIs). Especially so in settings where a large amount of source data is available, and finding the optimal source is not computationally feasible. This paper presents a novel method for source selection, the so-called Transfer Performance Predictor (TPP) method. Th
The healthcare systems of today are facing large challenges, with increasing amounts of patients and overworked hospital staff. Prostate cancer and Alzheimer’s disease are two of the most prevalent diseases, with incidence numbers expected to rise over the coming decade. Medical imaging plays a central role in current diagnostic procedures for these diseases, enabling the potential use of machine-
Levodopa-induced dyskinesia (LID) is a debilitating complication of symptomatic therapy in Parkinson's disease. Although there is compelling evidence that striatal pathophysiology is a major driver of LID, the specific circuit mechanisms governing its expression remain obscure. To address this gap, molecular, cellular, and behavioral strategies were used to interrogate circuits in a mouse model of
Ex vivo (outside of the body) working heart models enable the evaluation of isolated hearts. They are envisioned to play an important role in increasing the currently low utilization rate of donor hearts for transplantation. For the heart to work in isolation, an afterload (flow impedance) is needed. To date, afterload devices have been constructed by combining multiple constituent elements such a
Fast simulation of linear time-invariant (LTI) pharmacokinetic (PK) models is crucial to mixed-effect modeling techniques, used extensively in pharmacological research and development. The by far most common LTI PK models are particularly structured compartmental systems with one, two or three compartments. Here we develop and demonstrate very efficient, and down to machine precision exact, simula
An integration of distributionally robust risk allocation into sampling-based motion planning algorithms for robots operating in uncertain environments is proposed. We perform non-uniform risk allocation by decomposing the distributionally robust joint risk constraints defined over the entire planning horizon into individual risk constraints given the total risk budget. Specifically, the determini
