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Higher hospital level does not improve 30-day survival after road traffic accidents

Globally, road traffic accidents (RTAs) remain a major cause of death, particularly among individuals aged 15–30 years. While Sweden has been at the forefront of traffic safety through the Vision Zero initiative, in-hospital management remains crucial in determining RTA outcomes. Drawing on North American evidence suggesting improved survival at trauma centres, the Swedish healthcare system has in

Efficient Monocular 3D Localisation Using Machine Learning : with Additional Studies on Pose Estimation and Shape Reconstruction

This thesis concerns localisation, shape reconstruction and pose estimation from monocular images. While multiple cameras allows for triangulation to capture depth in scenes, monocular settings require some of relative features, reasonable real-world assumptions, regularisation, Machine Learning (ML) or a combination of these. The accompanying articles to this compilation thesis treats several top

The Impact of Semi-supervised Learning on Line Segment Detection

In this paper we present a method for line segment detection in images, based on a semi-supervised framework. Leveraging the use of a consistency loss based on differently augmented and perturbed unlabeled images with a small amount of labeled data, we show comparable results to fully supervised methods. This opens up application scenarios where annotation is difficult or expensive, and for domain

A Wideband Small-Footprint Platform-Insensitive Monopolar Patch Based on Slot-Assisted High-Order Mode Tailoring

A wideband, compact monopolar patch antenna with an inherent filtering response is presented in this paper. By employing a slot-assisted mode-tailoring technique, the field distributions of several higher-order modes at the patch center are engineered to produce a stable monopolar radiation pattern with enhanced bandwidth. The closed-form analysis indicates that increasing the current intensity at

Stabilized scattering matrix formulation for 2D periodic multilayer dielectrics

This paper proposes an alternative semi-analytical Fourier modal method adapted for general periodic anisotropic gratings made of dielectrics with moderate to low index profiles corresponding to materials ranging from conventional dielectric 3D printing materials to ceramic materials. The proposed method is closely related to the classical rigorous coupled wave analysis built on scattering matrice

Neural Speech Tracking with EEG : Integrating Acoustics and Linguistics for Hearing Aid Users

This study investigates the neural encoding of speech features in hearing aid users using electroencephalography (EEG) during a simulated cocktail party scenario. The objective was to investigate neural tracking of various acoustic and linguistic features and how hearing aid noise reduction influenced this tracking. The features analyzed included the acoustic envelope, phonetic features, word onse

Degrees of Freedom and Characteristic Modes : Estimates for radiating and arbitrarily shaped objects

The number of degrees of freedom is a crucial parameter in many electromagnetic problems. In for example modern communication systems spatial diversity is often employed through multiple beams to enhance capacity and reliability. However, while the degrees of freedom can be computed, their connection to physical quantities is not as easily understood. To address this issue, this paper proposes a s

Spatial Separation of Closely-Spaced Users in Measured Distributed Massive MIMO Channels

Aiming for the sixth generation (6G) wireless communications, distributed massive multiple-input multiple-output (MIMO) systems hold significant potential for spatial multiplexing. In order to evaluate the ability of a distributed massive MIMO system to spatially separate closely spaced users, this paper presents an indoor channel measurement campaign. The measurements are carried out at a carrier

Fading Resilient Backscatter Communication : Low-Complexity Transmission, Detection and Synchronization Schemes

Battery-free IoT devices are becoming increasingly interesting for environmental and practical reasons, with ambient backscatter as one of the candidate technologies. We present a class of balanced transmission patterns for ambient backscatter communication (BSC) and evaluate their performance under different signal-to-interference ratios and fading conditions. These patterns allow for bit synchro

Uncertainty-Aware Decision-Making and Planning for Autonomous Forced Merging

In this paper, we develop an uncertainty-aware decision-making and motion-planning method for an autonomous ego vehicle in forced merging scenarios, considering the motion uncertainty of surrounding vehicles. The method dynamically captures the uncertainty of surrounding vehicles by online estimation of their acceleration bounds, enabling a reactive but rapid understanding of the uncertainty chara

Differentiation of True Nonlinear and Incoherent Mixing of Linear Signals in Action-Detected 2D Spectroscopy

Phase modulation and phase cycling schemes have been commonly used in electronic two-dimensional (2D) spectroscopy where the observables are incoherent signals such as fluorescence or photocurrent. Although the methods have distinct advantages compared to the coherent signal-detected 2D spectroscopy in sensitivity, possibility to measure spectra from isolated quantum systems and direct visualizati

Longitudinal enumeration and cluster evaluation of circulating tumor cells improve prognostication for patients with newly diagnosed metastatic breast cancer in a prospective observational trial

Background: Circulating tumor cells (CTCs) carry independent prognostic information in patients with metastatic breast cancer (MBC) on different lines of therapy. Moreover, CTC clusters are suggested to add prognostic information to CTC enumeration alone but their significance is unknown in patients with newly diagnosed MBC. We aimed to evaluate whether longitudinal enumeration of circulating tumo

Do green roofs and spatial resolution influence flood simulation output? – A case study in Malmö, Southern Sweden

Over recent years many urban areas have experienced severe floods caused by extreme precipitation events. To avoid the devastating socioeconomic and environmental consequences of such floods, countries have issued laws or recommendations on flood risk assessment in urban planning. However, these laws or recommendations seldom include detailed requirements on input data quality or explicit instruct

Why not vaginal?—Nationwide trends and surgical outcomes in low-risk hysterectomies : A retrospective cohort study

Introduction: The rate of vaginal hysterectomies is declining globally. We investigated surgical techniques, outcomes, and costs in a large national cohort of benign hysterectomies with prerequisites for vaginal surgery. Material and Methods: A retrospective register-based cohort study with benign hysterectomies in the Swedish GynOp registry 2014–2023 (n = 17 804). Inclusion criteria were non-prol

Synthetic versus real : an analysis of critical scenarios for autonomous vehicle testing

With the emergence of autonomous vehicles comes the requirement of adequate and rigorous testing, particularly in critical scenarios that are both challenging and potentially hazardous. Generating synthetic simulation-based critical scenarios for testing autonomous vehicles has therefore received considerable interest, yet it is unclear how such scenarios relate to the actual crash or near-crash s

Enhancing Accessibility in Mobile Navigational Services

Abstract in UndeterminedThe success of the Wii and of the iPhone together with the persisting problem of displaying information on the small screens of mobile devices is currently pushing the development of non-visual interaction channels such as gestures, tactile/haptic interaction and sound. This development presents both potential and risk, since new channels of interaction may result either in

Angle estimation using mmWave RSS measurements with enhanced multipath information

mmWave communication has come up as the unexplored spectrum for 5G services. With new standards for 5G NR positioning, more off-the-shelf platforms and algorithms are needed to perform indoor positioning. An object can be accurately positioned in a room either by using an angle and a delay estimate or two angle estimates or three delay estimates. We propose an algorithm to jointly estimate the ang

A Conceptual Framework and Recommendations for Open Data and Artifacts in Empirical Software Engineering

Open science aims to improve research accessibility, replicability, and consequently its quality. Empirical software engineering entails both data and artifacts, which may be shared more or less openly, to support transparency. However, the trade-offs involved in balancing the openness against integrity and secrecy concerns need methodological guidance. Aim. We aim to derive such advice, based on

Optimal Inverse Design Based on Memetic Algorithms - Part II : Examples and Properties

Optimal inverse design, including topology optimization and evaluation of fundamental bounds on performance, which was introduced in Part 1, is applied to various antenna design problems. A memetic scheme for topology optimization combines local and global techniques to accelerate convergence and maintain robustness. Method-of-moments (MoMs) matrices are used to evaluate objective functions and al

Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical data

INTRODUCTION: Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, but its routine clinical use is limited by cost and accessibility barriers. METHODS: We thoroughly investigated the ability of various machine learning models to predict clinically useful tau-PET composites (load and laterality index) from low-cost an