The automation of map labeling is an ongoing research challenge. Currently, the map labeling algorithms are based on rules defined by experts for optimizing the placement of the text labels on maps. In this paper, we investigate the feasibility of using well-labeled map samples as a source of knowledge for automating the labeling process. The basic idea is to train deep learning models, specifical

Stochastic reconstruction is widely employed for effective and flexible imitation of Gas Diffusion Layers (GDLs), e.g., to facilitate the study of their properties. However, the reconstruction often overlooks crucial factors such as fiber curvature, fiber stack arrangement, and fiber anisotropy. Consequently, the impact of these structural characteristics remains poorly understood. In this study,

The bacterial ribosome is an essential drug target as many clinically important antibiotics bind and inhibit its functional centers. The catalytic peptidyl transferase center (PTC) is targeted by the broadest array of inhibitors belonging to several chemical classes. One of the most abundant and clinically prevalent resistance mechanisms to PTC-acting drugs in Gram-positive bacteria is C8-methylat

In this paper, we aggregate, analyze, and exemplify several metrics for the information value. The metrics vary by absolute value, normalizations, or full probabilistic quantification. The normalization of the information value encompasses the division by (1) the expected and maximized utility of the base scenario (usually without additional information), (2) by the system performance, or (3) by t

Purpose: Glaucoma is a heterogeneous group of optic neuropathies that potentially may be associated with other cerebral neurodegenerative processes leading to dementia. However, prior studies have been inconsistent. We examined dementia risks after glaucoma diagnosis in a large population-based cohort. Design: National matched cohort study. Participants: A total of 324 730 persons diagnosed with g

Background: Surgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based

Background: Few individuals with alcohol use disorders receive treatment. Primary care has been suggested as an arena for early treatment for these disorders. Aim: To evaluate whether the presence of a specialized addiction nurse can increase alcohol-related physician consultations in a primary care setting. Method: This controlled intervention study included one intervention and one control prima

Ground-based geophysical surveys were conducted at eight mine-tailings repositories during 2021 and 2022 to help preparing an inventory of potential sources of critical raw materials in mine-waste. Geophysical methods included ERT, DCIP, RMT, and tTEM. In this study, we show results obtained on two of the sites as an example. Integration of models of electrical properties, geological observations,

The paper explores synergies by bundling High-Capacity Transport - Intelligent Access - Zero Emission Vehicle reforms. State of the art is analyzed, and research questions are formulated. One joint policy framework is proposed and applied to three use cases: one vehicle, one real use case, and one scenario for the whole of EU. In the later, the cost savings 2024 to 2028 from allowing longer and/or

The development of lipid nanoparticle (LNP) based therapeutics for delivery of RNA has triggered the advance of new strategies for formulation, such as high throughput microfluidics for precise mixing of components into well-defined particles. In this study, we have characterised the structure of LNPs throughout the formulation process using in situ small angle x-ray scattering in the microfluidic

Configuring reconfigurable intelligent surfaces (RISs) based on a practical RIS model is a fundamental problem in RIS-assisted wireless transmission. In this work, we propose a concept named optimal phasor (OP), a latent quantity that can considerably help the practical model-based RIS configuration. Under such a concept, we can design versatile algorithms that are applicable to different RIS mode

In this work, we use a time-warping-based morphology variation index, d_{w}, computed between the peak and the end of the T-wave, and assess its association with the occurrence of ventricular fibrillation (VF) episodes in ischemic conditions. ECG recordings from 26 pigs under-going a 40-minute coronary occlusion were analyzed. The d_{w} series was obtained by quantifying the morphological differen

Background: Brain CT can be used to evaluate pediatric patients with suspicion of cerebral pathology when anesthetic and MRI resources are scarce. This study aimed to assess if pediatric patients referred for an elective brain CT could endure a diagnostic fast brain MRI without general anesthesia using a one-minute multi-contrast EPI-based sequence (EPIMix) with comparable diagnostic performance.

This project studies how the HCT-concept (High Capacity Transport) can be applied in cities, by performing pilots in Varberg and Stockholm. The project will test the hypothesis that the HCT-concept will improve both productivity construction and transport efficiency and thereby reduce CO2 by up to 40%. The pilots include tests of new optimized trucks and new concepts with sensors in trucks, machin

Ensembles of independently trained deep neural networks yield uncertainty estimates that rival Bayesian networks in performance. They also offer sizable improvements in terms of predictive performance over single models. However, deep ensembles are not commonly used in environments with limited computational budget - such as autonomous driving - since the complexity grows linearly with the number

Molecular Biomarkers in Cancer Detection and Monitoring of Therapeutics: Volume Two: Diagnostic and Therapeutic Applications discusses how molecular biomarkers are used to determine predisposition, facilitate detection, improve treatment and offer prevention guidelines for different cancers. It focuses on novel diagnostic techniques based on molecular biomarkers and their impact on treatment, cove

This paper presents a neural network based semantic plane detection method utilizing polygon representations. The method can for example be used to solve room layout estimations tasks and is built on, combines and further develops several different modules from previous research. The network takes an RGB image and estimates a wireframe as well as a feature space using an hourglass backbone. From t

Seagrass meadows constitute important habitat for a plethora of organisms, rendering them important habitats for conserving biodiversity. Seagrass meadows also modify the environment by attenuating wave and current energy. As a result of this, seagrass meadows trap organic matter and in addition to their high productivity, are able to sequester carbon that is stored in their underlying sediments.

Samhällets omställning till fossilfri energi innebär bland annat en ökad elektrifiering. I sin tur innebär en ökad elektrifiering också en högre efterfrågan på nya anslutningar till och behov av ökad kapacitet i elnätet. Syftet med delrapporten är att beskriva processen för att ansluta laddstationer till elnätet, den reglering som styr detta samt de olika aktörer som kan bli inblandade och vilka r