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Atmospheric inversions provide estimates of carbon dioxide (CO2) fluxes between the surface and atmosphere based on atmospheric CO2 concentration observations. The number of CO2 observations is projected to increase severalfold in the next decades from expanding in situ networks and next-generation CO2-observing satellites, providing both an opportunity and a challenge for inversions. This study i
One of the biggest challenges in urban densifications is securing adequate daylight access. This study examines the potential of using semantic 3D city models as input to daylight simulations. It is focusing on investigating input data requirements to these simulations from a geodata, 3D city model specification and measuring guideline perspective. To achieve this, geodata simulation input require
Background: Primary graft failure (PGF) remains the most common cause of short-term mortality after heart transplantation. The main objective was to develop and validate a risk model for prediction of short-term mortality due to PGF after heart transplantation using the ISHLT Heart Transplant Registry. Methods: We developed a non-linear artificial neural networks (ANN) model to evaluate the associ
Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prio
Background: The absence of Epithelial Membrane Protein 3 (EMP3) on red blood cells (RBCs) underlies the MAM-negative (MAM−) phenotype. EMP3 is a ubiquitous protein found at low levels in most tissues but with higher expression in hematopoietic cells. Low levels of CD44 are a signature of MAM− RBCs due its proposed physical interaction with EMP3, indicating that EMP3 stabilises CD44 in the membrane
Recently, many forms of audio industrial applications, such as sound monitoring and source localization, have begun exploiting smart multi-modal devices equipped with a microphone array. Regrettably, model-based methods are often difficult to employ for such devices due to their high computational complexity, as well as the difficulty of appropriately selecting the user-determined parameters. As a
In this paper, we revisit the problem of estimating the relative pose from a sparse set of point-correspondences. For each point-correspondence we also estimate the relative depth, i.e. the relative distance to the scene point in the two images. This yields an additional constraint, allowing us to use fewer matches in RANSAC to generate the pose candidates. In the paper we propose two novel minima
BACKGROUND: Previous studies have demonstrated an association between transplantation rate per center and postoperative mortality after heart transplantation. In 2011, Sweden centralized heart transplants and waiting lists, reducing the number of centers from 3 to 2. We aimed to assess the active waiting time and pre- and post-transplant mortality before and after centralization.METHODS: Heart tra
Natural killer (NK) cells represent the cytotoxic member within the innate lymphoid cell (ILC) family that are important against viral infections and cancer. Although the NK cell emergence from hematopoietic stem and progenitor cells through multiple intermediate stages and the underlying regulatory gene network has been extensively studied in mice, this process is not well characterized in humans
Many forms of small-size radars suffer from minor clock oscillations due to crystalline impurities in their internal clocks, causing time-varying clock offsets between the transmitter and the receivers. This offset causes a bias and an increased variance in the positioning of close-range targets, limiting the achievable accuracy well beyond the expected estimation limitations. This performance is
This paper develops an adaptive grid two-dimensional (2-D) direction-of-arrival (DOA) estimation technique employing an integrated dictionary framework. In contrast to using a traditional grid over distinct angles, combined angle information atoms are adopted to construct the dictionary, using a SPICE-based noise power estimate to select the active regions. To compensate for off-grid bias effects,
Uncertainty in our calculations of a system reveals the limits of our knowledge. This limitation makes model representations of the Earth system challenging and our predictions less reliable. However, despite appearing chaotic and non-linear, a system always follows a deterministic trajectory, which can often be expressed probabilistically. Building on this concept, this thesis applies data assimi
Post-marketing reports of suspected adverse drug reactions are important for establishing the safety profile of a medicinal product. However, a high influx of reports poses a challenge for regulatory authorities as a delay in identification of previously unknown adverse drug reactions can potentially be harmful to patients. In this study, we use natural language processing (NLP) to predict whether
Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH4). The FLUXNET-CH4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH4 Community Product v1.0 have provided inval
Background: Long-term recovery following critical COVID-19 has not been sufficiently studied. Objective: The primary objective was to describe changes in functional outcome and Health-Related Quality of Life (HRQoL) between 3 and 12 months in critically ill COVID-19 survivors. The secondary objective was to investigate factors associated with good functional outcome and HRQoL at 12 months. Methods
This article addresses the problem of multi-target localization from acoustic time delay measurements in a 3-D underwater environment, taking into account the depth-dependent sound speed of the underwater wave propagation. Specifically, we formulate the problem as an optimal mass transport (OMT) optimization over a grid of potential candidate positions. By exploiting an iterative refinement approa
Filter exchange imaging (FEXI) is a double diffusion-encoding (DDE) sequence that is specifically sensitive to exchange between sites with different apparent diffusivities. FEXI uses a diffusion-encoding filtering block followed by a detection block at varying mixing times to map the exchange rate. Long mixing times enhance the sensitivity to exchange, but they pose challenges for imaging applicat
Objectives: To evaluate the feasibility of AI-assisted reading of prostate magnetic resonance imaging (MRI) in Organized Prostate cancer Testing (OPT). Methods: Retrospective cohort study including 57 men with elevated prostate-specific antigen (PSA) levels ≥3 µg/L that performed bi-parametric MRI in OPT. The results of a CE-marked deep learning (DL) algorithm for prostate MRI lesion detection wer
