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Background: We have previously shown that a Palaeolithic diet consisting of the typical food groups that our ancestors ate during the Palaeolithic era, improves cardiovascular disease risk factors and glucose control compared to the currently recommended diabetes diet in patients with type 2 diabetes. To elucidate the mechanisms behind these effects, we evaluated fasting plasma concentrations of g

In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, and only partially known, sampling times. The problem originates in paleoclimatology, where each data point derives from a separate ice core measurement, resulting in that even though all measurements reflect the same peri

In this work, we study self-supervised representation learning for 3D skeleton-based action recognition. We extend Bootstrap Your Own Latent (BYOL) for representation learning on skeleton sequence data and propose a new data augmentation strategy including two asymmetric transformation pipelines. We also introduce a multi-viewpoint sampling method that leverages multiple viewing angles of the same

In this article, we propose a novel solution to detect multiple targets using a distributed multiple-input multiple-output (MIMO) radar under the so-called 'defocused transmit-defocused receive' operating mode. The proposed method employs a grid-based data matching algorithm, aiming to associate the target responses to potential target locations, solving the resulting data puzzle that evaluates th

The least absolute shrinkage and selection operator (LASSO) algorithm is a promising method for sparse source location in time–division multiplexing (TDM) multiple–input, multiple– output (MIMO) radar systems, with notable performance gains in regard to resolution enhancement and side lobe suppression. However, the current batch LASSO algorithm suffers from high– computational complexity when deal

Variational nonlinear chirp mode decomposition (VNCMD) is a recently introduced method for nonlinear chirp signal decomposition that has aroused notable attention in various fields. One limiting aspect of the method is that its performance relies heavily on the setting of the bandwidth parameter. To overcome this problem, we here propose a Bayesian implementation of the VNCMD, which can adaptively

Well before large-scale quantum computers will be available, traditional cryptosystems must be transitioned to post-quantum (PQ) secure schemes. The NIST PQC competition aims to standardize suitable cryptographic schemes. Candidates are evaluated not only on their formal security strengths, but are also judged based on the security with regard to resistance against side-channel attacks. Although r

In this paper, we propose the first key-recovery side-channel attack on Classic McEliece, a KEM finalist in the NIST Post-quantum Cryptography Standardization Project. Our novel idea is to design an attack algorithm where we submit special ciphertexts to the decryption oracle that correspond to cases of single errors. Decoding of such ciphertexts involves only a single entry in a large secret perm

Code review is a common practice in software development andnumerous studies have described different aspects of the process;its characteristics, the expectations on that process, issues aroundreviewer allocation, and more. However, one aspect that has notbeen studied to a large extent is the experience of the developersin the code review process. This is unfortunate given the signifi-cant amount

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

The immune cell component of the tumor microenvironment is an important modulator of tumor progression. In patients with breast cancer, tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS) represent core aspects of anti-tumor immunity, both increasingly recognized for clinical relevance. In this study, we evaluated immune-related histology features using whole slide H&E

A physics lecture and a mathematics lecture, by the same teacher and partly thesame students, were studied at upper secondary school. Both lectures coveredordinary differential equations. The main aim of the present paper was to investigate the teacher’s different and similar ways to handle related mathematicalcontent in the two school subjects. The findings show a structural use of mathematics wi

In this paper, we describe the extraction of all the location entries from a prominent Swedish encyclopedia from the early 20th century, the Nordisk Familjebok 'Nordic Family Book.' We focused on the second edition called Uggleupplagan, which comprises 38 volumes and over 182,000 articles. This makes it one of the most extensive Swedish encyclopedias. Using a classifier, we first determined the ca

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

The short-time iterative adaptive approach is a spectral estimation alternative to the short-time Fourier transform for non-stationary vibration analysis. This technique offers a reduction in leakage effects and a higher resolution in exchange for a higher computational complexity. The short-time iterative adaptive approach can be summarized as a high-resolution data-dependent approach which has b

Heart transplantation (HT) is a life saving procedure, but a limited donor supply forces the surgeons to prioritize the recipients. The understanding of factors that predict mortality could help the doctors with this task. The objective of this study is to find locally optimal feature sets to predict survival of HT patients for different time periods. To this end, we applied logistic regression to