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The effect of external pressure on intramuscular blood flow at rest and after running

Local blood flow in the thigh was measured with 133Xe clearance technique in eight male distance runners after compression with a foam rubber compress and a standard elastic bandage. Two degrees of compression were tested, and an initial experiment with rested subjects was followed by a similar experiment immediately after running. Maximum compression exerted a cutaneous pressure of 85 (+/- 8) mm

Exploring networks of care in the end-of-life context through eco maps: : feminist perspectives on caregiving in between family, community, and professionals in Sweden

More complex understanding of relationality in care networks around patients with life-limiting illness and their significant others is needed. This is the case not only because care is distributed unequally along gendered lines, but also because of the changing landscape of care in welfare states where families and communities are made more self-responsible. This study examines everyday experienc

Mapping the Past : Geographically Linking an Early 20th Century Swedish Encyclopedia with Wikidata

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

Deep Learning for Breast Cancer Detection in Ultrasound Imaging : Classification, Managing Data Scarcity and Detecting Out-of-Distribution Samples

Breast cancer has a profound affect on society. The survival for women in low- and middle-income countries (LMICs) is poor compared to in high-income countries (HICs). The lack of timely diagnosis is one of the main factors contributing to the poor outcomes for women in LMICs. Point-of-care ultrasound (POCUS) combined with a deep learning (DL) classification network could potentially be a suitable

A New Sieving-style Information-set Decoding Algorithm

The problem of decoding random codes is a fundamental problem for code-based cryptography, including recent code-based candidates in the NIST post-quantum standardization process. In this paper, we present a novel Sieving-style Information-set Decoding algorithm, addressing the task of solving the syndrome decoding problem. Our approach involves maintaining a list of weight-2p solution vectors to

A Key-Recovery Attack on the LCMQ Authentication Protocol

We present a simple key-recovery attack on the LCMQ Authentication Protocol, an RFID authentication protocol proposed by Li, Gong, and Qin in 2013. We show that a successful attack is performed by solving a Learning Parity with Noise instance in a not-too-large dimension. For the proposed LCMQ parameters, the attack requires only a few invocations with the tag under attack. When there is no restri

Critical needs to close monitoring gaps in pan-tropical wetland CH4 emissions

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 Perils of Limited Key Reuse: Adaptive and Parallel Mismatch Attacks with Post-processing Against Kyber

The Module Learning With Errors (MLWE)-based Key Encapsulation Mechanism (KEM) Kyber is NIST's new standard scheme for post-quantum encryption. As a building block, Kyber uses a Chosen Plaintext Attack (CPA)-secure Public Key Encryption (PKE) scheme, referred to as Kyber.CPAPKE. In this paper we study the robustness of Kyber.CPAPKE against key mismatch attacks.We demonstrate that Kyber's security

A combined neural ODE-Bayesian optimization approach to resolve dynamics and estimate parameters for a modified SIR model with immune memory

We propose a novel hybrid approach that integrates Neural Ordinary Differential Equations (NODEs) with Bayesian optimization to address the dynamics and parameter estimation of a modified time-delay-type Susceptible-Infected-Removed (SIR) model incorporating immune memory. This approach leverages a neural network to produce continuous multi-wave infection profiles by learning from both data and th

The short-time iterative adaptive approach : an effective analysis tool for complex non-stationary vibrations

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

Real-World Applications of Anomaly Detection : Detecting the Unexpected Through Distributional Modelling

In many machine learning tasks, the premise is designed around predetermined targets and clear expectations of model behaviour. In such cases, there is a direct definition of the optimal mappings between inputs and outputs, which can be learned given sufficiently sized datasets and models. However, in many real-world scenarios, tasks are often not as well-posed and instead defined around detecting

The Poem as Concert. Lidner, Oxenstierna and the Unity of the Long Poem

This article adresses the problem of literary unity as is is posed by two late eighteenth century long poems, "Året 1783" by Bengt Lidner and Skördarne by Johan Gabriel Oxenstierna. By investigating the relations between poetry, poetics and practical criticism it seeks to document a situation in which new poems failed to achieve the kind of unity found in the traditional long poem, i.e. the epic.

Langforia: Language pipelines for annotating large collections of documents.

In this paper, we describe Langforia, a multilingual processing pipeline to annotate texts with multiple layers: formatting, parts of speech, named entities, dependencies, semantic roles, and entity links. Langforia works as a web service, where the server hosts the language processing components and the client, the input and result visualization. To annotate a text or a Wikipedia page, the user c