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Accessible data curation and analytics for international-scale citizen science datasets

The Covid Symptom Study, a smartphone-based surveillance study on COVID-19 symptoms in the population, is an exemplar of big data citizen science. As of May 23rd, 2021, over 5 million participants have collectively logged over 360 million self-assessment reports since its introduction in March 2020. The success of the Covid Symptom Study creates significant technical challenges around effective da

Naturvetarnas arbetsliv - resultat, utvärdering och slutsatser från alumnenkät 2019

För att öka kunskapen om var studenter med examen i naturvetenskap frånLunds universitet får jobb och hur användbara deras utbildningar är i arbetslivethar vi genomfört en alumnenkät. Alumnenkäten har fokus på interaktionenmellan utbildning och arbetsliv och rör arbete i nära tid efter studierna. Enkätenskickades ut till kandidatalumnerna som tagit ut examen mellan september2017 och september 2018

Foraminiferal Mn/Ca as Bottom-Water Hypoxia Proxy: An Assessment of Nonionella stella in the Santa Barbara Basin, USA

Hypoxia is of increasing concern in marine areas, calling for a better understanding of mechanisms leading to decreasing dissolved oxygen concentrations ([O2]). Much can be learned about the processes and implications of deoxygenation for marine ecosystems using proxy records from low-oxygen sites, provided proxies, such as the manganese (Mn) to calcium (Ca) ratio in benthic foraminiferal calcite,

Experiences of using a continuous glucose monitoring system in children—a descriptive study with parents in the republic of Georgia

The benefits of medical devices are often multifaceted and may have an important impact on patients’ and relatives’ physical, mental and/or social well-being. Diabetes is a metabolic disorder and a continuous subcutaneous glucose monitoring sensor can suggest increasing treatment satisfaction. The purpose of this study was to describe parents’ experiences during their daily lives and support needs

Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis

Background: Osteoporosis is an underdiagnosed and undertreated disease worldwide. Recent studies have highlighted the use of simple vertebral trabecular attenuation values for opportunistic osteoporosis screening. Meanwhile, machine learning has been used to accurately segment large parts of the human skeleton. Purpose: To evaluate a fully automated deep learning-based method for lumbar vertebral

End-to-End Estimation of Hand- and Wrist Forces From Raw Intramuscular EMG Signals Using LSTM Networks

Processing myoelectrical activity in the forearm has for long been considered a promising framework to allow transradial amputees to control motorized prostheses. In spite of expectations, contemporary muscle-computer interfaces built for this purpose typically fail to satisfy one or more important desiderata, such as accuracy, robustness, and/or naturalness of control, in part due to difficulties

Is There Any Role for Opioids in the Management of Knee and Hip Osteoarthritis? A Systematic Review and Meta-Analysis

Objective: Opioids have long been prescribed for chronic pain conditions, including osteoarthritis (OA). However, there is little information about their temporal efficacy, or differences in efficacy and safety between opioids with strong versus weak/intermediate μ opioid receptor–binding affinity. To explore these research questions, we conducted a systematic review and meta-analyses of randomize

Double Nanowires for Hybrid Quantum Devices

Parallel 1D semiconductor channels connected by a superconducting strip constitute the core platform in several recent quantum device proposals that rely, for example, on Andreev processes or topological effects. In order to realize these proposals, the actual material systems must have high crystalline purity, and the coupling between the different elements should be controllable in terms of thei

Fusion imaging in brain structure measurements on a fetus phantom, combining real-time ultrasound with magnetic resonance imaging

Objectives: To assess synchronisation of MRI and US in measuring foetus phantom head structures; inter-method, intra- and inter-observer differences on biparietal diameter (BPD), head diameter, anterio-posterior head diameter (HAP) and lateral ventricle structures (VS). Methods: Fusion Imaging (FI) has been performed by combining MRI and US simultaneously. Axial scans of 1.5 Tesla MRI on a foetus

Conditional Cube Attack on Reduced-Round Keccak Sponge Function

The security analysis of Keccak, the winner of SHA-3, has attracted considerable interest. Recently, some attention has been paid to the analysis of keyed modes of Keccak sponge function. As a notable example, the most efficient key recovery attacks on Keccak-MAC and Keyak were reported at EUROCRYPT’15 where cube attacks and cube-attack-like cryptanalysis have been applied. In this paper, we devel

Unleashing the barriers to CSR implementation in the sme sector of a developing economy : A thematic analysis approach

The notion of corporate social responsibility (CSR) from the perspective of sustainability has been a part of the academic discussion in recent years. Different studies have also highlighted the inability of the SME sector to implement a CSR plan to achieve sustainability objectives. How-ever, why this sector is unable to adopt CSR is something that has not been properly attended by contemporary s

Detection of structural variations in densely-labelled optical DNA barcodes : A hidden Markov model approach

Large-scale genomic alterations play an important role in disease, gene expression, and chromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensity profiles (DNA barcodes) along single DNA molecules and is a technique well-suited for detecting such alterations. For sparsely-labelled barco

Using a linear discriminant analysis (LDA)-based nomenclature system and self-organizing maps (SOM) for spatiotemporal assessment of groundwater quality in a coastal aquifer

In this study, a linear discriminant analysis (LDA) - based nomenclature system have been used for the classification of groundwater samples in a coastal aquifer. The capability of three models (7 hlr, 7 M conc, and Greater molar conc) in determining the water types has been investigated. The results show that Ca-HCO3, Na-Cl, and Na-HCO3; and Ca-HCO3, Na-HCO3, and Na-Cl are the three dominant wate

Developing augmented reality business models for SMEs in tourism

Augmented reality (AR) is disrupting the business landscape. Small and medium-sized enterprises (SMEs) often face challenges capitalising on the potential presented by cutting-edge technologies, such as AR. Business models (BMs) are widely regarded as effective management tools, which help increase competitiveness. This paper aims to develop an augmented reality business model (ARBM), using a case

Gaia -ESO survey : Lithium abundances in open cluster Red Clump stars

Context. It has recently been suggested that all giant stars with masses below 2 M? suffer an episode of surface lithium enrichment between the tip of the red giant branch (RGB) and the red clump (RC). Aims. We test if the above result can be confirmed in a sample of RC and RGB stars that are members of open clusters. Methods. We discuss Li abundances in six open clusters with ages between 1.5 and