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The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks. An important line of research in this regard is grasp force control, which aims to manipulate objects safely by limiting the amount of force exerted on the object. While prior works have either hand-modeled their fo
Response determinants to immunotherapy in metastatic pancreatic ductal adenocarcinoma (mPDAC) remain unclear, limiting treatment advancements. We report a single-arm phase 1b/2 study (OPTIMIZE-1) evaluating the safety and efficacy of the cluster of differentiation 40 (CD40) agonist mitazalimab combined with modified FOLFIRINOX (mFOLFIRINOX), in chemotherapy-naive patients with mPDAC. Patients rece
Safety is one of the key issues preventing the deployment of reinforcement learning techniques in real-world robots. While most approaches in the Safe Reinforcement Learning area do not require prior knowledge of constraints and robot kinematics and rely solely on data, it is often difficult to deploy them in complex real-world settings. Instead, model-based approaches that incorporate prior knowl
The construction sector contributes around 37 % of global CO2 emissions, highlighting the need for de-carbonization. Part of the emissions originate in the use of diesel-driven heavy equipment. Considering the fast pace of transitioning from fossil fuels to electricity in other vehicle sectors, this may be a possible path for heavy equipment, considering the introduction of electric heavy equipmen
Stateful policies play an important role in reinforcement learning, such as handling partially observable environments, enhancing robustness, or imposing an inductive bias directly into the policy structure. The conventional method for training stateful policies is Backpropagation Through Time (BPTT), which comes with significant drawbacks, such as slow training due to sequential gradient propagat
Safety is a fundamental property for the real-world deployment of robotic platforms. Any control policy should avoid dangerous actions that could harm the environment, humans, or the robot itself. In reinforcement learning (RL), safety is crucial when exploring a new environment to learn a new skill. This paper introduces a new formulation of safe exploration for robotic RL in the tangent space of
Deep Reinforcement Learning techniques are achieving state-of-the-art results in robust legged locomotion. While there exists a wide variety of legged platforms such as quadruped, humanoids, and hexapods, the field is still missing a single learning framework that can control all these different embodiments easily and effectively and possibly transfer, zero or few-shot, to unseen robot embodiments
Background: Ageing-in-place policies have increasingly shifted elder care responsibilities onto family members. Among older cohabiting couples, one’s partner’s illness significantly impacts the other’s daily life and well-being.Aim: To explore the responsibilities and strategies of caregiving partners in older cohabiting couples from the perspectives of cohabiting caregivers.Methods: A qualitative
Carbon-14 (14C) is an important contributor to the collective effective dose to the public due to releases from nuclear power plants (NPPs). In Sweden, only airborne emissions of 14C from NPPs are currently routinely monitored, and the existing data on waterborne 14C discharges are limited. A recent study of 14C in brown algae (Fucus spp.) in Swedish coastal waters showed higher F14C values collec
Carbon-14 often dominates the effective dose to the public from authorized discharges from Swedish nuclear power plants (NPPs). In contrast to air-borne releases, water-borne discharges of 14C are currently not routinely monitored at Swedish NPPs. We have measured 14C in Fucus spp. (brown algae, used as bioindicators of 14C) in shallow waters at the Swedish west coast from 2020 to 2024. At Ringhal
The development of thermally stable nanoparticles is of utmost importance for applications like catalysis. In particular, Cu nanoparticles supported on metal oxides are easily deactivated under thermal treatments at low temperatures by sintering of the Cu nanoparticles. The formation of thermally stable nanoparticles is typically obtained with secondary drawbacks. In this study, an alternative met
Atomic vacancies are primordial for controlling the photocatalytic activity of perovskites. On the one hand, they are useful adsorption sites and help narrow the band gap, but they may also trap the electron-hole pair created after light absorption. Its precise control, although essential, is hardly achieved with traditional methods. In this work, an alternative experimental approach is employed t
This Master’s thesis is a study of the existence of yogaphobia in the swedish debate between the years 2012 and 2020 concerning the religious nature yoga. Via deconstructing misconceptions of yoga from a historical standpoint combined with the use of critical discourse analysis, the thesis explores the arguments found in news articles and submitters from the swedish newspapers Dagen and Världen id
Denna uppsats närmar sig svenskt plein-air måleri i Fontainebleau och inom konstnärskolonin Grèz-sur-Loing från slutet av 1800-talet genom längtans lins. Med utgångspunkt i temat nostalgi och apodemialgi – längtan hem och längtan att bort – undersöks landskapsmåleriet och hur det visualiserar teman om natur och modernitet. Denna tid av exil är en viktig punkt i svensk konsthistoria eftersom den haThis thesis examines late 19th-century Swedish plein-air painting in Fontainebleau and within the artists’ colony Grèz-sur-Loing through the lens of longing. Drawing on the theme of nostalgia and apodemialgia—longing for home and the longing to leave—it investigates how landscape painting visualizes themes of nature and modernity. This time of exile is an important point in Swedish art history as
In the late 17th century, a new style of decorations was developing in Sweden. Brutal flaming depictions of hell started covering the ceilings of the small parish churches. The trend would catch fire and over the course of the 18th century over 500 decorations were made in churches across western Sweden. This essay studies iconographic starting points for the style in the depictions the final judg
As a core component of an ITS, CAVs have garnered significant attention and expect to play an important role in enhancing traffic safety. To enable (future) practical deployment of CAVs, safety strategies must be incorporated into the control design. This includes, in particular, strategies for ensuring avoidance or mitigation of multi-vehicle collisions. Conventional control strategies exhibit so
Denna avhandling undersöker konceptet Rolling Magnet Energy Harvester (RMEH), en kinetisk energifångare, baserad på principerna för elektromagnetisk induktion. RMEH är utformad med fraktcontainrar i åtanke och utnyttjar energin från fordonets rörelser för att driva potentiella sensorer ombord. Det långsiktiga målet är att förbättra logistiken genom att tillhandahålla en enkel, hållbar och underhålThis thesis investigates the concept of a Rolling Magnet Energy Harvester (RMEH), a kinetic energy harvester based on the principles of electromagnetic induction. Designed with shipping containers in mind, the RMEH harnesses energy from the rolling motion of vehicles to power potential onboard sensors. The long term objective is to enhance logistics by providing a simple, sustainable, and maintena
Titel: Upplevelser och erfarenheter av fantomsensationer/-smärta vid amputation i nedre extremiteten, en kvalitativ intervjustudie. Introduktion: Fantomsmärta (PLP) och fantomsensationer (PS) är vanliga fenomen som amputerade upplever. Tidigare forskning visar stor spridning angående resultat och det återfinns en begränsad representation av upplevelser och erfarenheter av personer med påverkan av
Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing approaches rely on training in carefully calibrated simulators before being deployed on real robots, often without real-world fine-tuning. While effective in controlled settings, this framework falls short in applicatio
