bluuebunny/crossref_metadata_2025_split huggingface dataset:
Addressing cyber security skills: the spectrum, not the silo
Authors: Furnell Steven , Bishop Matt 
Published: February 2020

With cyber security gaining ever-greater recognition as a key concern in today's organisations, there is an accompanying appreciation that specialist skills are required to support it. However, this has created challenges for employers in recruiting the associated talent, not least because skilled staff are in short supply. With cyber security becoming a key concern in today's organisations, there is an accompanying appreciation that specialist skills are required to support it. As Steven Furnell of the University of Plymouth and Matt Bishop of the University of California at Davis explain, it is important to recognise the breadth of skills needed. The natural way to do this is to recruit talent with suitable qualifications, but for this to work we need to understand what they cover and whether they match what organisations need.
The business benefits of cyber security for SMEs
Authors: Lloyd Guy 
Published: February 2020

Cyber security is often discussed in terms of data breaches, regulatory fines and business disruption. The advantages are seldom highlighted. For example, effective cyber security makes it possible for companies to innovate and this drives revenue, profit and growth. Defending against cybercrime can deliver genuine benefits for small and medium-size enterprises (SMEs) and result in more valuable organisations. Cyber security is often discussed in terms of data breaches, regulatory fines and business disruption. However, the advantages are seldom highlighted. Effective cyber security makes it possible for companies to innovate and this drives revenue, profit and growth. Defending against cybercrime can deliver genuine benefits for small and medium-size enterprises. And as organisations of all sizes move towards driving efficiency through digitising processes, it's important for business leaders to redefine how they think about security, argues Guy Lloyd of CySure.
Rationality, uncertainty, and unanimity: an epistemic critique of contractarianism
Authors: Schaefer Alexander 
Published: February 2020

AbstractThis paper considers contractarianism as a method of justification. The analysis accepts the key tenets of contractarianism: expected utility maximization, unanimity as the criteria of acceptance, and social-scientific uncertainty of modelled agents. In addition to these three features, however, the analysis introduces a fourth feature: a criteria of rational belief formation, viz. Bayesian belief updating. Using a formal model, this paper identifies a decisive objection to contractarian justification. Insofar as contractarian projects approximate the Agreement Model, therefore, they fail to justify their conclusions. Insofar as they fail to approximate the Agreement Model, they must explain which modelling assumption they reject.
The effects of pre-task planning on EFL learners’ oral performance in a 3D multi-user virtual environment
Authors: Chen Julian ChengChiang 
Published: February 2020

AbstractPrior research on pre-task planning examines its effects on the quality of second language (L2) learners’ planned output. Planning mitigates the cognitive overload placed upon L2 learners’ oral performance, thus improving language production. Despite the pedagogical benefits, studies on pre-task planning on L2 learners’ oral output are conducted mostly in a lab or class setting. Whether or not similar effects of pre-task planning can be evidenced in three-dimensional (3D) multi-user virtual environments (MUVEs), such as Second Life (SL), is still less explored. Hence, this study investigates whether pre-task planning could enhance the quality and quantity of English as a foreign language (EFL) learners’ task-oriented, voice-based outcomes in SL. Nine EFL learners worldwide participated in this 10-session virtual class. Data were collected through students’ oral presentations in performing real-life simulated tasks related to their home cultures and interests. Yuan and Ellis’s (2003) framework of T-units measures was adopted to analyze their linguistic performance measured by complexity and accuracy. Results indicated that EFL learners showed statistically significant improvement on grammatical complexity on the levels of syntactic complexity and variety (but not on lexical variety) and on linguistic accuracy across all measured levels (error-free clauses/T-units/verb forms). It is suggested that pre-task planning can be seeded in task-based instruction either in a classroom-based or 3D MUVE setting to optimize the quality of learners’ linguistic performance. Tasks that are real-world oriented and targeting learners’ cultural repertoires and world knowledge also positively impact their virtual learning experiences. These significant implications add new research and pedagogical dimensions to the field of computer-assisted language learning.
Quality of life assessment in children before and after a successful ablation for supraventricular tachycardia
Authors: Gonzalez Corcia M Cecilia , Peters Laura , Sluysmans Thierry , Moniotte Stephane , Carbonez Karlien , Barrea Catherine , Vo Christophe , Vanhoutte Laetitia , Scavee Christophe 
Published: February 2020

ABSTRACTBackground and Objectives:Young patients suffering from rhythm disorders have a negative impact in their quality of life. In recent years, ablation has become the first-line therapy for supraventricular arrhythmias in children. In the light of the current expertise and advancement in the field, we decided to evaluate the quality of life in young patients with supraventricular arrhythmias before and after a percutaneous ablation procedure.Methods:The prospective cohort consisted of patients <18 years with structurally normal hearts and non-pre-excited supraventricular arrhythmias, who had an ablation in our centre from 2013 to 2018. The cohort was evaluated with the PedsQL™ 4.0 Generic Core Scales self-questionnaire prior to and post-ablation.Results:The final cohort included 88 patients consisted of 52 males (59%), with a mean age at ablation of 12.5 ± 3.3 years. Forty-two patients (48%) had a retrograde-only accessory pathway mediating the tachycardia, 38 (43%) had atrio-ventricular nodal re-entrant tachycardia, 7 (8%) had ectopic atrial tachycardia, and 1 (1%) had atrial flutter. The main reason for an ablation was the patient’s choice in 53%. There were no severe complications. Comparison between the baseline and post-ablation assessments showed that patients reported significant improvement in the scores for physical health, emotional and social functioning, as well as in the total scores.Conclusions:The present study demonstrates that the successful treatment of supraventricular arrhythmias by means of an ablation results in a significant improvement in the quality of self-reported life scores in young patients.
Domain-general inhibition ability predicts the intensity of inhibition on non-target language in bilingual word production: An ERP study
Authors: Kang Chunyan , Ma Fengyang , Li Shuhua , Kroll Judith F. , Guo Taomei 
Published: February 2020

AbstractThis study investigated the predictive effects of executive functions on bilingual language control processes. We used a flanker task, a switching task and an n-back task to investigate inhibition, shifting, and updating, respectively. We adopted a cued language switching task to investigate the language control processes during bilingual word production. Results of linear mixed effects models showed that picture naming in switch trials was significantly slower and elicited larger stimulus-locked N2 and N400-like components. The results further showed that the flanker effect alone robustly predicted the variability of the N2 but not N400-like switch effects. These findings suggest that domain-general inhibition appears to predict the intensity of inhibition exerted on the lexical items in the non-target language during bilingual word production, but bilingual language control only partially overlaps with executive functions.
Constraining Interseismic Deformation of the Cascadia Subduction Zone: New Insights From Estimates of Vertical Land Motion Over Different Timescales
Authors: Yousefi Maryam , Milne Glenn , Li Shaoyang , Wang Kelin , Bartholet Alan 
Published: February 2020

AbstractWe determine late Holocene (past 4 kyr) vertical land motion (VLM) rates from relative sea level observations along the coastline of western North America and compare these to contemporary (decadal‐scale) rates inferred from Global Positioning System data. The residual rates (contemporary minus late Holocene) indicate uplift at most locations, which likely reflects short‐term signals associated with the Cascadia subduction earthquake cycle and processes that were recently activated. Regarding the latter, we model and remove the signals associated with ground water extraction and twentieth‐century glacier retreat, which have a significant influence in, respectively, California and southern British Columbia. We interpret the remaining signal as being dominated by interseismic deformation associated with the locking of the Cascadia megathrust. A preliminary comparison of this signal with output from a model of interseismic deformation indicates good agreement at most locations within a range of key model parameter values. This agreement is particularly encouraging as the locking model is based on the inversion of only horizontal land motion observations. Considering the data‐model fit at all locations, preference was found for models featuring nearly full locking to a relatively shallow depth (<30 km), although the locking state preference is variable along the coast and not strong. The best fitting parameter set varies considerably from site to site, and no set of parameter values was able to capture the residual VLM rates in northwestern Vancouver Island. Our study indicates that the residual VLM data provide useful constraints for megathrust locking models of Cascadia subduction.
Wave‐Driven Mean Flow Dynamics in Submerged Canopies
Authors: van Rooijen Arnold , Lowe Ryan , Rijnsdorp Dirk P. , Ghisalberti Marco , Jacobsen Niels G. , McCall Robert 
Published: February 2020

AbstractThe physical roughness (canopies) formed by organisms within aquatic ecosystems (e.g., seagrass, kelp, and mangroves) modifies the local wave‐driven hydrodynamics within coastal and estuarine regions. In wave‐dominated environments, an understanding of the mean wave‐driven flows generated within and above canopies is important, as it governs material transport (e.g., of nutrients, sediment, and biota). However, until recently the effect of submerged canopies on wave‐current interactions and the resulting mean (wave‐averaged) flow dynamics has received relatively little attention. In this study, a combination of wave flume experiments and numerical modeling is used to investigate the wave‐induced mean flow profiles in the presence of a submerged canopy. The measured velocities and vegetation forces were used to derive bulk drag and inertia coefficients, and to validate a nonhydrostatic 2DV wave‐flow model. The numerical model results were used to conduct an in‐depth analysis of the mean horizontal momentum terms responsible for driving the mean (horizontal) flow within and above the submerged canopies. We show that the mean canopy hydrodynamics are driven by vertical gradients in wave and turbulent Reynolds stresses, balanced by the mean canopy drag forces. The wave Reynolds stress gradient is the dominant force driving the in‐canopy mean flow and is directly related to the vorticity that is generated when the wave orbital motions become rotational near the canopy interface. This study provides new insight in the mechanisms responsible for wave‐driven mean flows within submerged canopies and guidance for how these hydrodynamics can be predicted in coastal wave‐circulation models.
Buffered, Incomplete, and Shredded: The Challenges of Reading an Imperfect Stratigraphic Record
Authors: Straub Kyle M. , Duller Robert A. , Foreman Brady Z. , Hajek Elizabeth A. 
Published: February 2020

AbstractClimate, tectonics, and life influence the flux and caliber of sediment transported across Earth's surface. These environmental conditions can leave behind imprints in the Earth's sedimentary archive, but signals of climate, tectonic, and biologic change are not always present in the stratigraphic record. Deterministic and stochastic surface dynamics collectively act as a stratigraphic filter, impeding the burial and preservation of environmental signals in sedimentary deposits. Such impediments form a central challenge to accurately reconstructing environmental conditions through Earth's history. Emergent and self‐organized length and timescales in landscapes, which are themselves influenced by regional environmental conditions, define spatial and temporal sedimentation patterns in basins and fundamentally control the likelihood of environmental signal preservation in sedimentary deposits. Properly characterizing these scales provides a key avenue for incorporating the known “imperfections” of the stratigraphic record into paleoenvironmental reconstructions. These insights are necessary for answering both basic and applied science questions, including our ability to reconstruct the Earth system response to prior episodes of climate, tectonic, or land cover change.
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model
Authors: Gagne David John , Christensen Hannah M. , Subramanian Aneesh C. , Monahan Adam H. 
Published: February 2020

AbstractStochastic parameterizations account for uncertainty in the representation of unresolved subgrid processes by sampling from the distribution of possible subgrid forcings. Some existing stochastic parameterizations utilize data‐driven approaches to characterize uncertainty, but these approaches require significant structural assumptions that can limit their scalability. Machine learning models, including neural networks, are able to represent a wide range of distributions and build optimized mappings between a large number of inputs and subgrid forcings. Recent research on machine learning parameterizations has focused only on deterministic parameterizations. In this study, we develop a stochastic parameterization using the generative adversarial network (GAN) machine learning framework. The GAN stochastic parameterization is trained and evaluated on output from the Lorenz '96 model, which is a common baseline model for evaluating both parameterization and data assimilation techniques. We evaluate different ways of characterizing the input noise for the model and perform model runs with the GAN parameterization at weather and climate time scales. Some of the GAN configurations perform better than a baseline bespoke parameterization at both time scales, and the networks closely reproduce the spatiotemporal correlations and regimes of the Lorenz '96 system. We also find that, in general, those models which produce skillful forecasts are also associated with the best climate simulations.
Low-frequency parietal repetitive transcranial magnetic stimulation reduces fear and anxiety
Authors: Balderston Nicholas L. , Beydler Emily M. , Goodwin Madeline , Deng Zhi-De , Radman Thomas , Luber Bruce , Lisanby Sarah H. , Ernst Monique , Grillon Christian 
Published: February 2020

AbstractAnxiety disorders are the most prevalent mental disorders, with few effective neuropharmacological treatments, making treatments development critical. While noninvasive neuromodulation can successfully treat depression, few treatment targets have been identified specifically for anxiety disorders. Previously, we showed that shock threat increases excitability and connectivity of the intraparietal sulcus (IPS). Here we tested the hypothesis that inhibitory repetitive transcranial magnetic stimulation (rTMS) targeting this region would reduce induced anxiety. Subjects were exposed to neutral, predictable, and unpredictable shock threat, while receiving double-blinded, 1 Hz active or sham IPS rTMS. We used global brain connectivity and electric-field modelling to define the single-subject targets. We assessed subjective anxiety with online ratings and physiological arousal with the startle reflex. Startle stimuli (103 dB white noise) probed fear and anxiety during the predictable (fear-potentiated startle, FPS) and unpredictable (anxiety-potentiated startle, APS) conditions. Active rTMS reduced both FPS and APS relative to both the sham and no stimulation conditions. However, the online anxiety ratings showed no difference between the stimulation conditions. These results were not dependent on the laterality of the stimulation, or the subjects’ perception of the stimulation (i.e. active vs. sham). Results suggest that reducing IPS excitability during shock threat is sufficient to reduce physiological arousal related to both fear and anxiety, and are consistent with our previous research showing hyperexcitability in this region during threat. By extension, these results suggest that 1 Hz parietal stimulation may be an effective treatment for clinical anxiety, warranting future work in anxiety patients.
Melatonin alleviates intervertebral disc degeneration by disrupting the IL-1β/NF-κB-NLRP3 inflammasome positive feedback loop
Authors: Chen Fan , Jiang Guowei , Liu Hui , Li Zemin , Pei Yuxin , Wang Hua , Pan Hehai , Cui Haowen , Long Jun , Wang Jianru , Zheng Zhaomin 
Published: February 2020

AbstractThe inflammatory response is induced by the overexpression of inflammatory cytokines, mainly interleukin (IL)-1β, and is one of the main causes of intervertebral disc degeneration (IVDD). NLR pyrin domain containing 3 (NLRP3) inflammasome activation is an important source of IL-1β. As an anti-inflammatory neuroendocrine hormone, melatonin plays various roles in different pathophysiological conditions. However, its roles in IVDD are still not well understood and require more examination. First, we demonstrated that melatonin delayed the progression of IVDD and relieved IVDD-related low back pain in a rat needle puncture IVDD model; moreover, NLRP3 inflammasome activation (NLRP3, p20, and IL-1β levels) was significantly upregulated in severely degenerated human discs and a rat IVDD model. Subsequently, an IL-1β/NF-κB-NLRP3 inflammasome activation positive feedback loop was found in nucleus pulposus (NP) cells that were treated with IL-1β. In these cells, expression of NLRP3 and p20 was significantly increased, NF-κB signaling was involved in this regulation, and mitochondrial reactive oxygen species (mtROS) production increased. Furthermore, we found that melatonin disrupted the IL-1β/NF-κB-NLRP3 inflammasome activation positive feedback loop in vitro and in vivo. Melatonin treatment decreased NLRP3, p20, and IL-1β levels by inhibiting NF-κB signaling and downregulating mtROS production. Finally, we showed that melatonin mediated the disruption of the positive feedback loop of IL-1β in vivo. In this study, we showed for the first time that IL-1β promotes its own expression by upregulating NLRP3 inflammasome activation. Furthermore, melatonin disrupts the IL-1β positive feedback loop and may be a potential therapeutic agent for IVDD.
Integrating DNA methylation measures to improve clinical risk assessment: are we there yet? The case of BRCA1 methylation marks to improve clinical risk assessment of breast cancer
Authors: Wong Ee Ming , Southey Melissa C. , Terry Mary Beth 
Published: February 2020

AbstractCurrent risk prediction models estimate the probability of developing breast cancer over a defined period based on information such as family history, non-genetic breast cancer risk factors, genetic information from high and moderate risk breast cancer susceptibility genes and, over the past several years, polygenic risk scores (PRS) from more than 300 common variants. The inclusion of additional data such as PRS improves risk stratification, but it is anticipated that the inclusion of epigenetic marks could further improve model performance accuracy. Here, we present the case for including information on DNA methylation marks to improve the accuracy of these risk prediction models, and consider how this approach contrasts genetic information, as identifying DNA methylation marks associated with breast cancer risk differs inherently according to the source of DNA, approaches to the measurement of DNA methylation, and the timing of measurement. We highlight several DNA-methylation-specific challenges that should be considered when incorporating information on DNA methylation marks into risk prediction models, using BRCA1, a highly penetrant breast cancer susceptibility gene, as an example. Only after careful consideration of study design and DNA methylation measurement will prospective performance of the incorporation of information regarding DNA methylation marks into risk prediction models be valid.
NR1D1 modulates synovial inflammation and bone destruction in rheumatoid arthritis
Authors: Liu Hui , Zhu Yuanli , Gao Yutong , Qi Dahu , Zhao Liming , Zhao Libo , Liu Changyu , Tao Tenghui , Zhou Chuankun , Sun Xuying , Guo Fengjing , Xiao Jun 
Published: February 2020

AbstractRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial hyperplasia, pannus formation, and cartilage and bone destruction. Nuclear receptor subfamily 1 group D member 1 (NR1D1) functions as a transcriptional repressor and plays a vital role in inflammatory reactions. However, whether NR1D1 is involved in synovial inflammation and joint destruction during the pathogenesis of RA is unknown. In this study, we found that NR1D1 expression was increased in synovial tissues from patients with RA and decreased in RA Fibroblast-like synoviocytes (FLSs) stimulated with IL-1β in vitro. We showed that NR1D1 activation decreased the expression of proinflammatory cytokines and matrix metalloproteinases (MMPs), while NR1D1 silencing exerted the opposite effect. Furthermore, NR1D1 activation reduced reactive oxygen species (ROS) generation and increased the production of nuclear transcription factor E2-related factor 2 (Nrf2)-associated enzymes. Mitogen-activated protein kinase (MAPK) and nuclear factor κB (NF-κB) pathways were blocked by the NR1D1 agonist SR9009 but activated by NR1D1 silencing. NR1D1 activation also inhibited M1 macrophage polarization and suppressed osteoclastogenesis and osteoclast-related genes expression. Treatment with NR1D1 agonist SR9009 in collagen-induced arthritis (CIA) mouse significantly suppressed the hyperplasia of synovial, infiltration of inflammatory cell and destruction of cartilage and bone. Our findings demonstrate an important role for NR1D1 in RA and suggest its therapeutic potential.