bluuebunny/crossref_metadata_2025_split huggingface dataset:
Roma university students in Spain and Central and Eastern Europe: Exploring participation and identity in contrasting international contexts
Authors: Hinton‐Smith Tamsin , Padilla‐Carmona Maria Teresa 
Published: June 2021

AbstractRoma are Europe's largest, most marginalised minority, with a long history of racism and exclusion informing complex inequalities. Roma higher education participation remains under addressed, and paucity of research hinders understanding. While there is variation between countries, the proportion of Roma accessing higher education compared to the general population is extremely small in all countries. Spain has the largest Roma population outside Central and Eastern Europe, and relatively high levels of Roma participation in higher education. As part of an international project on Internalisation and Mobility, here we discuss insights from eleven qualitative interviews carried out with Roma students and recent graduates in Central and Eastern Europe and Spain. Findings from a thematic analysis of interviews highlight identity and inclusion and how experience intersects with distinct national approaches. We focus in particular on competing pulls of ethnic invisibility versus coming out, and related onus on a responsibility to give back. The participation of Roma in higher education remains an important social justice issue in Europe. Our research shows that proactive efforts by higher education institutions in Europe are needed to challenge persistent assumptions that fail to value the contribution and potential of Roma students within higher education.
Strategies to improve the accuracy and reduce costs of genomic prediction in aquaculture species
Authors: Song Hailiang , Hu Hongxia 
Published: June 2021

AbstractGenomic selection (GS) has great potential to increase genetic gain in aquaculture breeding; however, its implementation is hindered owing to high genotyping cost and the large number of individuals to genotype. This study investigated the efficiency of genomic prediction in four aquaculture species. In total, 749 to 1481 individuals with records for disease resistance and growth traits were genotyped using SNP arrays ranging from 12K to 40K. We compared the prediction accuracies and bias of breeding values obtained from BLUP, genomic BLUP (GBLUP), Bayesian mixture (BayesR), weighted GBLUP (WGBLUP), and genomic feature BLUP (GFBLUP). For GFBLUP, the genomic feature matrix was constructed based on prior information from genome‐wide association studies. Fivefold cross‐validation was performed with 20 replicates. Moreover, to reduce the cost of GS, we reduced the SNP density based on linkage disequilibrium as well as the reference population size. The results showed that the methods with marker information produced more accurate predictions than the pedigree‐based BLUP method. For the genomic model, BayesR performed prediction with a similar or higher accuracy compared to GBLUP. For the four traits, WGBLUP yielded an average of 1.5% higher accuracy than GBLUP. However, the accuracy of genomic prediction decreased by an average of 6.2% for GFBLUP compared to GBLUP. When the density of SNP panels was reduced to 3K, which was sufficient to obtain accuracies similar to those using the whole dataset in the four species, the cost of GS was estimated to be 50% lower than that of genotyping all animals with high‐density panels. In addition, when the reference population size was reduced by 10%, evenly from full‐sib family, the accuracy of genomic prediction was almost unchanged, and the cost reduction was 8% in the four populations. Our results have important implications for translating the benefits of GS to most aquaculture species.
Meta‐analysis: Congruence of genomic and phenotypic differentiation across diverse natural study systems
Authors: Wood Zachary T. , Wiegardt Andrew K. , Barton Kayla L. , Clark Jonathan D. , Homola Jared J. , Olsen Brian J. , King Benjamin L. , Kovach Adrienne I. , Kinnison Michael T. 
Published: June 2021

AbstractLinking genotype to phenotype is a primary goal for understanding the genomic underpinnings of evolution. However, little work has explored whether patterns of linked genomic and phenotypic differentiation are congruent across natural study systems and traits. Here, we investigate such patterns with a meta‐analysis of studies examining population‐level differentiation at subsets of loci and traits putatively responding to divergent selection. We show that across the 31 studies (88 natural population‐level comparisons) we examined, there was a moderate (R2 = 0.39) relationship between genomic differentiation (FST) and phenotypic differentiation (PST) for loci and traits putatively under selection. This quantitative relationship between PST and FST for loci under selection in diverse taxa provides broad context and cross‐system predictions for genomic and phenotypic adaptation by natural selection in natural populations. This context may eventually allow for more precise ideas of what constitutes “strong” differentiation, predictions about the effect size of loci, comparisons of taxa evolving in nonparallel ways, and more. On the other hand, links between PST and FST within studies were very weak, suggesting that much work remains in linking genomic differentiation to phenotypic differentiation at specific phenotypes. We suggest that linking genotypes to specific phenotypes can be improved by correlating genomic and phenotypic differentiation across a spectrum of diverging populations within a taxon and including wide coverage of both genomes and phenomes.
Equine parvovirus hepatitis
Authors: Ramsauer Anna Sophie , Badenhorst Marcha , Cavalleri Jessika‐M. V. 
Published: June 2021

AbstractEquine parvovirus hepatitis (EqPV‐H) was first described in 2018 in a fatal case of Theiler's disease which followed the administration of an equine‐origin biological product. The virus has since been frequently identified in serum and liver tissue of horses affected by Theiler's disease—an acute, severe hepatitis characterised by fulminant hepatic necrosis with a fatal outcome in most cases. EqPV‐H is hepatotropic, appears to be associated with subclinical to severe hepatitis in horses, and is a likely cause of Theiler's disease. Although this disease is most frequently reported following the administration of equine‐origin biological products, it can also occur among in‐contact horses. Horizontal transmission may be iatrogenic, via contaminated equine‐origin biological products such as equine serum, botulism or tetanus antitoxin, and mesenchymal stem cells or by means of the oral route of infection. Other horizontal transmission routes, for example, arthropod vectors, warrant further investigation. A worldwide prevalence of EqPV‐H antibodies and DNA has been reported in asymptomatic horses. EqPV‐H‐positive horses suffering from acute, severe hepatitis have reportedly developed clinical signs including icterus, lethargy, inappetence, and neurological abnormalities and have had increased liver‐associated biochemistry parameters recorded. The most common histopathological abnormalities of the liver have been hepatocellular necrosis, collapse of the lobular architecture, and lymphocytic infiltration. Most horses infected experimentally with EqPV‐H have developed subclinical hepatitis, and close temporal associations between peak viraemia, seroconversion, and the onset of hepatitis have been observed. Based on strong evidence indicating that EqPV‐H causes hepatitis in horses, veterinarians should consider this virus an important differential diagnosis in such cases. Potential risks associated with the administration of equine‐origin biological products must be emphasised.
Business analytics in Industry 4.0: A systematic review
Authors: Silva António João , Cortez Paulo , Pereira Carlos , Pilastri André 
Published: June 2021

AbstractRecently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet‐of‐Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data‐based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.
Deep ensemble learning approach for lower extremity activities recognition using wearable sensors
Authors: Jain Rahul , Semwal Vijay Bhaskar , Kaushik Praveen 
Published: June 2021

AbstractHuman walking is a very challenging task and always requires rigorous practice. It is a learning process that involves the complex coordination of the brain and lower limbs. The bipedal robots that mimic the human morphological structure to produce human similar walking, are not capable of producing an efficient walk. Due to walking challenges and structural differences, a robot cannot walk like a human being. In this research, to achieve the aforementioned objective to produce a human similar walk, human lower extremity activities are considered to understand walking behaviour. The experiment involves different walking styles on different terrains. To capture the learning process of bipedal robot locomotion, a deep learning‐based ensemble classifier is introduced for human lower activities recognition. To understand the learning process seven different walking activities are considered for analysis purposes. An Inertial measurement unit (IMU) is used as a wearable device due to its small form factor and unobtrusive nature to capture the walking movement of different lower limbs joints. Three public datasets viz. mHealth, OU‐ISIR similar action and HAPT inertial sensor data sets are considered for this study. To classify the activities, 2 different deep learning models namely convolutional neural network (CNN) and long short‐term memory (LSTM) are used. To generalize the results, an ensemble of different classifiers is implemented. The Classifier has reported accuracy of 99.25%, 88.48% and 97.44%, respectively, on the aforementioned data sets. This work can be utilized for elderly subjects' postural stability, rehabilitation of patients post‐stroke and trauma, generation of robot walk trajectories in cluttered environment and reconstruction of impaired walking.
Evolution and connectivity influence the persistence and recovery of coral reefs under climate change in the Caribbean, Southwest Pacific, and Coral Triangle
Authors: McManus Lisa C. , Forrest Daniel L. , Tekwa Edward W. , Schindler Daniel E. , Colton Madhavi A. , Webster Michael M. , Essington Timothy E. , Palumbi Stephen R. , Mumby Peter J. , Pinsky Malin L. 
Published: June 2021

AbstractCorals are experiencing unprecedented decline from climate change‐induced mass bleaching events. Dispersal not only contributes to coral reef persistence through demographic rescue but can also hinder or facilitate evolutionary adaptation. Locations of reefs that are likely to survive future warming therefore remain largely unknown, particularly within the context of both ecological and evolutionary processes across complex seascapes that differ in temperature range, strength of connectivity, network size, and other characteristics. Here, we used eco‐evolutionary simulations to examine coral adaptation to warming across reef networks in the Caribbean, the Southwest Pacific, and the Coral Triangle. We assessed the factors associated with coral persistence in multiple reef systems to understand which results are general and which are sensitive to particular geographic contexts. We found that evolution can be critical in preventing extinction and facilitating the long‐term recovery of coral communities in all regions. Furthermore, the strength of immigration to a reef (destination strength) and current sea surface temperature robustly predicted reef persistence across all reef networks and across temperature projections. However, we found higher initial coral cover, slower recovery, and more evolutionary lag in the Coral Triangle, which has a greater number of reefs and more larval settlement than the other regions. We also found the lowest projected future coral cover in the Caribbean. These findings suggest that coral reef persistence depends on ecology, evolution, and habitat network characteristics, and that, under an emissions stabilization scenario (RCP 4.5), recovery may be possible over multiple centuries.
Spatiotemporal variability of fire effects on soil carbon and nitrogen: A global meta‐analysis
Authors: Li Jinquan , Pei Junmin , Liu Jiajia , Wu Jihua , Li Bo , Fang Changming , Nie Ming 
Published: June 2021

AbstractA consensus about the fire‐related soil carbon (C) and nitrogen (N) impacts that determine soil health and ecosystem services at the global scale remains elusive. Here, we conducted a global meta‐analysis of 3173 observations with 1444, 1334, 228, and 167 observations for soil C, N, pyrogenic C (PyC), and the percent of PyC to total organic C (PyC/TOC) from 296 field studies. Results showed that fire significantly decreased soil C (−15.2%) and N (−14.6%) but increased soil PyC (40.6%) and PyC/TOC (30.3%). Stronger negative fire impacts on soil C and N were found in tropical and temperate climates than in Mediterranean and subtropical climates; stronger effects were found in forest ecosystems than in non‐forest ecosystems. Wildfire and high‐severity fire led to greater soil C and N losses than prescribed and low‐severity fires, respectively, while they promoted greater increases in soil PyC and PyC/TOC than prescribed and low‐severity fires, respectively. However, soil C and N recovered to control levels approximately 10 years after fire, which is a shorter period than previously determined. These results suggest that fire‐induced PyC production should be accounted for in the C budget under global change. These results will improve our knowledge of the spatiotemporal variability of fire effects on soil C and N storage and have implications for fire management and ecosystem recovery.
Biologically meaningful distribution models highlight the benefits of the Paris Agreement for demersal fishing targets in the North Atlantic Ocean
Authors: Ramos Martins Manuel , Assis Jorge , Abecasis David 
Published: June 2021

AbstractAimWith climate change challenging marine biodiversity and resource management, it is crucial to anticipate future latitudinal and depth shifts under contrasting global change scenarios to support policy‐relevant biodiversity impact assessments [e.g., Intergovernmental Panel on Climate Change (IPCC)]. We aim to demonstrate the benefits of complying with the Paris Agreement (United Nations Framework Convention on Climate Change) and limiting environmental changes, by assessing future distributional shifts of 10 commercially important demersal fish species.LocationNorthern Atlantic Ocean.Time periodAnalyses of distributional shifts compared near present‐day conditions (2000–2017) with two Representative Concentration Pathway (RCP) scenarios of future climate changes (2090–2100): one following the Paris Agreement climate forcing (RCP2.6) and another without stringent mitigation measures (RCP8.5).Major taxa studiedDemersal fish.MethodsWe use machine learning distribution models coupled with biologically meaningful predictors to project future latitudinal and depth shifts. Structuring projections with information beyond temperature‐based predictors allowed us to encompass the physiological limitations of species better.ResultsOur models highlighted the additional roles of temperature, primary productivity and dissolved oxygen in shaping fish distributions (average relative contribution to the models of 32.12 ± 10.24, 15.6 ± 7.5 and 12.1 ± 6.1%, respectively). We anticipated a generalized trend of poleward shifts in both future scenarios, with aggravated changes in suitable area with RCP8.5 (average area loss with RCP2.6 = 13.3 ± 4.1%; RCP8.5 = 40.9 ± 13.3%). Shifts to deeper waters were also predicted to be of greater magnitude with RCP8.5 (average depth gain = 25.4 ± 21.5 m) than with RCP2.6 (average depth gain = 10.4 ± 7.9 m). Habitat losses were projected mostly in the Mediterranean, Celtic and Irish Seas, the southern areas of the North Sea and along the NE coast of North America.Main conclusionsInclusion of biologically meaningful predictors beyond temperature in species distribution modelling can improve predictive performances. Limiting future climate changes by complying with the Paris Agreement can translate into reduced distributional shifts, supporting biodiversity conservation and resource management.
Asymmetric responses of terrestrial C:N:P stoichiometry to precipitation change
Authors: Sun Yuan , Wang Cuiting , Chen Han Y. H. , Luo Xuesong , Qiu Nianwei , Ruan Honghua 
Published: June 2021

AbstractAimThe aim was to test whether the responses of C:N:P stoichiometry in plant–soil–microorganism systems to precipitation changes support the prediction of the double asymmetry model, which predicts ecological processes (i.e. aboveground productivity, soil microbial community, and soil respiration) are more sensitive to increased precipitation (R+) than decreased precipitation (R−) under normal precipitation changes, whereas more sensitive to R− than R+ under extreme precipitation changes.LocationGlobal.Time period1999–2020.Major taxa studiedPlants, soils, and soil microorganisms.MethodsWe performed a global meta‐analysis of 848 observations (587 R− and 261 R+ manipulations) from 160 studies, which tested the effects of precipitation changes on C:N:P across plants, soils, and soil microorganisms. The data encompassed broad variations in ecosystems, climate, precipitation intensity, and experimental duration.ResultsWe revealed that the C:N and C:P ratios of different ecosystem compartments were more sensitive to moderate R+ rather than moderate R−, whereas they exhibited a higher response to extreme R− rather than extreme R+, which supported the prediction of the double asymmetry model. Moreover, such responses were more pronounced under higher precipitation intensities and longer experimental duration. The effects of precipitation changes on the C:N:P stoichiometry of plants, soils, and soil microorganisms were consistent across ecosystem types (i.e. forests and grasslands) and associated background climates (i.e. mean annual temperature and precipitation).Main conclusionsOur findings provide the first evidence of the asymmetric responses of C:N:P stoichiometry in above‐ and belowground systems to precipitation change. These results extend the double asymmetric model and improve our understanding of C and N cycling, as well as facilitate the prediction of ecosystem responses to precipitation changes.
Indomethacin‐responsive headaches—A narrative review
Authors: Villar‐Martínez Maria Dolores , Moreno‐Ajona David , Chan Calvin , Goadsby Peter J. 
Published: June 2021

AbstractBackgroundIndomethacin is a nonsteroidal anti‐inflammatory drug whose mechanism of action in certain types of headache disorders remains unknown. The so‐called indomethacin‐responsive headache disorders consist of a group of conditions with a very different presentation that have a particularly good response to indomethacin. The response is so distinct as to be used in the definition of two: hemicrania continua and paroxysmal hemicrania.MethodsThis is a narrative literature review. PubMed and the Cochrane databases were used for the literature search.ResultsWe review the main pharmacokinetic and pharmacodynamics properties of indomethacin useful for daily practice. The proposed mechanisms of action of indomethacin in the responsive headache disorders, including its effect on cerebral blood flow and intracranial pressure, with special attention to nitrergic mechanisms, are covered. The current evidence for its use in primary headache disorders, such as some trigeminal autonomic cephalalgias, cough, hypnic, exertional or sexual headache, and migraine will be covered, as well as its indication for secondary headaches, such as those of posttraumatic origin.ConclusionIncreasing understanding of the mechanism(s) of action of indomethacin will enhance our understanding of the complex pathophysiology that might be shared by indomethacin‐sensitive headache disorders.
Awareness of diagnosis, treatment and risk of late effects in Chinese survivors of childhood cancer in Hong Kong
Authors: Yang Lok Sum , Ma Chung Tin , Chan Chun Him , Luk Mei Shum , Woo Hoi Kei , Lee Vivian Wai‐yan , Leung Alex Wing Kwan , Lee Samantha Lai‐ka , Yeung Nelson Chun‐yiu , Li Chi‐kong , Cheung Yin Ting 
Published: June 2021

AbstractBackgroundFor survivors of childhood cancer, awareness of personal health risks is a critical component of long‐term health management.ObjectiveTo evaluate the awareness of the diagnosis, treatment and risk of late effects among survivors of childhood cancer in Hong Kong.MethodsBetween June 2019 and March 2020, this cross‐sectional study recruited 155 adult survivors (mean age = 26.9, standard deviation [SD] = 6.4 years) and 45 parents of paediatric survivors (mean age = 11.1, SD = 3.6 years) from a long‐term follow‐up clinic. At >10 years post‐treatment (mean = 13.4, SD = 7.6 years), they completed a structured questionnaire to report their cancer‐specific knowledge. Multiple linear regression analysis was conducted to identify clinical, socioeconomic and behavioural factors associated with poor awareness.ResultsThe majority of participants accurately recalled their diagnoses (73.5%) and major treatment modalities (chemotherapy 92.4%, radiation 82.9% and surgery 88.2%). However, less than half (45%) of the participants recognized more than 25% of the total late effects for which they were at risk. The highest levels of awareness were reported for endocrine problems (49%), neurocognitive impairment (44%) and secondary cancers (43%), and the lowest for peripheral neuropathy (21%) and vision problems (23%). Compared with survivors of haematological malignancies, those of central nervous system (CNS) tumours (standardized estimate [B] = −9.33, 95% confidence interval [95% CI]: −13.41 to −5.26) and non‐CNS solid tumours (B = −8.47, 95% CI: −12.39 to −4.94) had less knowledge about their diagnosis. Retaining medical records (P < .0001) and better medical information‐seeking habits (P = .048) were associated with better awareness.ConclusionsSurvivors of childhood cancer in Hong Kong have deficient awareness of their personal health risks. They may benefit from the provision of a survivorship care plan and personalized education regarding treatment‐related late effects.Patient ContributionPatients contributed in designing the study tools. Results were presented at a non‐governmental organization.