bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silver as a capturing material for iodine released from lead–bismuth eutectic in various conditions
Authors: Karlsson Erik , Neuhausen Jörg , Eichler Robert , Danilov Ivan I. , Vögele Alexander , Türler Andreas 
Published: April 2021

AbstractThe usage of silver as a filtering material for removal of iodine from the gas phase of a lead–bismuth eutectic based nuclear reactor was investigated in various atmospheres representing normal operation as well as accident conditions. Thermochromatography experiments were performed to quantify the retention experienced on a silver surface by iodine species evaporated from a lead–bismuth eutectic sample. Measured adsorption enthalpies ranged from −171 to − 208 kJ mol−1 with observed differences attributed to various surface effects rather than a change in iodine speciation. The postulated adsorption mechanism is chemisorption of iodine atoms on the silver surface. Metallic silver fulfills the desired criteria for a capturing material in water-free filtering systems to be used as an alternative to traditional alkaline scrubbers commonly used in LWR systems.
Thermochromatographic behavior of iodine in 316L stainless steel columns when evaporated from lead–bismuth eutectic
Authors: Karlsson Erik , Neuhausen Jörg , Eichler Robert , Danilov Ivan I. , Vögele Alexander , Türler Andreas 
Published: April 2021

AbstractIodine evaporated from lead–bismuth eutectic (LBE) has been examined with respect to its adsorption behavior on stainless steel in various gases to establish a base for safety evaluations on LBE based nuclear reactors. In inert conditions the iodine forms a single species with an adsorption enthalpy between − 97 and − 106 kJ/mol. The adsorbed species is tentatively identified as bismuth monoiodide, BiI. Addition of moisture to the inert gas has no substantial influence on the adsorption behaviour. For the reducing hydrogen carrier gas depositions with adsorption enthalpies ranging from − 87 to − 134 kJ/mol were observed in dry and water saturated conditions. The larger variation of adsorption enthalpies compared to analogous experiments in helium likely result from surface effects induced by the reactive gas. Formation of highly volatile species such as hydrogen iodide HI was not observed. In oxidizing conditions multiple iodine species with adsorption enthalpies ranging from − 67 to − 83 kJ/mol were observed, with the exception of one experiment where only a lower limit of –ΔHads < 64 kJ/mol could be determined due to high volatility. The species occurring in oxidizing atmosphere are most likely monatomic iodine, iodine oxides and hydroxides. While oxygen as a carrier gas changes the speciation of iodine to more volatile compounds, it also introduces a retentive effect on the evaporation of iodine from the LBE sample. These results provide important information that establish a better understanding of safety related aspects pertaining to iodine transport in an LBE reactor. The determined thermodynamic data can be used for safety assessments of LBE-based nuclear facilities in normal operation conditions as well as for accident scenarios.
Proposed definition of competencies for surgical neuro-oncology training
Authors: Kamp Marcel A. , Malzkorn Bastian , von Sass Christiane , DiMeco Francesco , Hadjipanayis Constantinos G. , Senft Christian , Rapp Marion , Gepfner-Tuma Irina , Fountas Konstantinos , Krieg Sandro M. , Neukirchen Martin , Florian Ioan Ștefan , Schnell Oliver , Mijderwijk Hendrik-Jan , Perin Alessandro , Baumgarten Peter , van Lieshout Jasper H. , Thon Niklas , Renovanz Miriam , Kahlert Ulf , Spoor Jochem K. H. , Hänggi Daniel , McLean Aaron Lawson , Mäurer Matthias , Sarrubbo Silvio , Freyschlag Christian F. , Schmidt Nils O. , Vergani Francesco , Jungk Christine , Stein Marco , Forster Marie-Therese , Weinberg Jeffrey S. , Sinclair John , Belykh Evgenii , Bello Lorenzo , Mandonnet Emmanuel , Moiyadi Aliasgar , Sabel Michael 
Published: April 2021

Abstract
Objective
The aim of this work is to define competencies and entrustable professional activities (EPAs) to be imparted within the framework of surgical neuro-oncological residency and fellowship training as well as the education of medical students. Improved and specific training in surgical neuro-oncology promotes neuro-oncological expertise, quality of surgical neuro-oncological treatment and may also contribute to further development of neuro-oncological techniques and treatment protocols. Specific curricula for a surgical neuro-oncologic education have not yet been established.

Methods
We used a consensus-building approach to propose skills, competencies and EPAs to be imparted within the framework of surgical neuro-oncological training. We developed competencies and EPAs suitable for training in surgical neuro-oncology.

Result
In total, 70 competencies and 8 EPAs for training in surgical neuro-oncology were proposed. EPAs were defined for the management of the deteriorating patient, the management of patients with the diagnosis of a brain tumour, tumour-based resections, function-based surgical resections of brain tumours, the postoperative management of patients, the collaboration as a member of an interdisciplinary and/or -professional team and finally for the care of palliative and dying patients and their families.

Conclusions and Relevance
The present work should subsequently initiate a discussion about the proposed competencies and EPAs and, together with the following discussion, contribute to the creation of new training concepts in surgical neuro-oncology.
Solid bitumen in shales from the Middle to Upper Jurassic Sargelu and Naokelekan Formations of northernmost Iraq: implication for reservoir characterization
Authors: Omar Nagham , McCann Tom , Al-Juboury Ali I. , Suárez-Ruiz Isabel 
Published: April 2021

AbstractPetrographic, organic, and inorganic geochemical analysis of the solid bitumen and host shales from the Middle and Late Jurassic-age Sargelu and Naokelekan Formations of the Banik section, northernmost Iraq, was undertaken. The aim was to understand their derivation and preservation, as well as examine the carbon and oxygen isotopes, and paleoredox proxies under which the solid bitumen and host sediments were deposited. Petrographic analysis of both formations revealed the presence of solid bitumen high reflectance (first phase) and solid bitumen low reflectance (second phase). The equivalent vitrinite reflectance indicates that the solid bitumen of the two formations probably accumulated within the shale reservoirs following oil migration from source rocks located within the same formations. Mineralogical study (XRD and SEM - EDX) revealed that the shales hosting the solid bitumen also contain clay minerals (illite, rectorite, chlorite, montmorillonite, and kaolinite) as well as carbonate minerals, quartz, alkali feldspar, and pyrite. Carbon and oxygen isotope data along with paleoredox indicators suggest that both the solid bitumen sources and host shales in both formations formed within a shallow-marine setting, most probably under anoxic conditions where water circulation was restricted.
An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning
Authors: Chowdhury Muhammad E. H. , Rahman Tawsifur , Khandakar Amith , Al-Madeed Somaya , Zughaier Susu M. , Doi Suhail A. R. , Hassen Hanadi , Islam Mohammad T. 
Published: April 2021

AbstractCOVID-19 pandemic has created an extreme pressure on the global healthcare services. Fast, reliable, and early clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. In order to study the important blood biomarkers for predicting disease mortality, a retrospective study was conducted on a dataset made public by Yan et al. in [1] of 375 COVID-19 positive patients admitted to Tongji Hospital (China) from January 10 to February 18, 2020. Demographic and clinical characteristics and patient outcomes were investigated using machine learning tools to identify key biomarkers to predict the mortality of individual patient. A nomogram was developed for predicting the mortality risk among COVID-19 patients. Lactate dehydrogenase, neutrophils (%), lymphocyte (%), high-sensitivity C-reactive protein, and age (LNLCA)—acquired at hospital admission—were identified as key predictors of death by multi-tree XGBoost model. The area under curve (AUC) of the nomogram for the derivation and validation cohort were 0.961 and 0.991, respectively. An integrated score (LNLCA) was calculated with the corresponding death probability. COVID-19 patients were divided into three subgroups: low-, moderate-, and high-risk groups using LNLCA cutoff values of 10.4 and 12.65 with the death probability less than 5%, 5–50%, and above 50%, respectively. The prognostic model, nomogram, and LNLCA score can help in early detection of high mortality risk of COVID-19 patients, which will help doctors to improve the management of patient stratification.
Contradictions and Interventions in Health IS
Authors: Weeger Andy , Wagner Heinz-Theo , Gewald Heiko , Weitzel Tim 
Published: April 2021

AbstractThe study analyzes data collected in two case studies in the healthcare industry, which is characterized by a variety of social and technical elements forming an activity system where all elements interact with each other. The findings indicate that many problems emerging during the implementation of a health information system can be traced back to contradictions between elements of the activity systems that are created or amplified by the new IS. The authors find that some contradictions are latent and become salient when introducing a new IS, while other contradictions are (unintentionally) newly created. Also, the study shows that contradictions are more complex than hitherto assumed and often concern more than two elements of a healthcare activity system. In a similar vein, effective interventions geared toward countering these contradictions are found to account for additional complexity while not always achieving their goal. Drawing on activity theory, the authors develop a framework to coherently synthesize the findings. The study can help increase the understanding of the IS’s role within an activity system and help guide IS implementation projects aimed at avoiding unintended consequences.
Prioritizing studies of COVID-19 and lessons learned
Authors: Jayaweera Dushyantha , Flume Patrick A. , Singer Nora G. , Cohen Myron S. , Lachiewicz Anne M. , Cameron Amanda , Kumar Naresh , Thompson Joel , Cabrera Alyssa , Daudelin Denise , Shaker Reza , Bauer Philippe R 
Published: April 2021

Abstract

Introduction:
COVID-19 altered research in Clinical and Translational Science Award (CTSA) hubs in an unprecedented manner, leading to adjustments for COVID-19 research.

Methods:
CTSA members volunteered to conduct a review on the impact of CTSA network on COVID-19 pandemic with the assistance from NIH survey team in October 2020. The survey questions included the involvement of CTSAs in decision-making concerning the prioritization of COVID-19 studies. Descriptive and statistical analyses were conducted to analyze the survey data.

Results:
60 of the 64 CTSAs completed the survey. Most CTSAs lacked preparedness but promptly responded to the pandemic. Early disruption of research triggered, enhanced CTSA engagement, creation of dedicated research areas and triage for prioritization of COVID-19 studies. CTSAs involvement in decision-making were 16.75 times more likely to create dedicated diagnostic laboratories (95% confidence interval [CI] = 2.17–129.39; P < 0.01). Likewise, institutions with internal funding were 3.88 times more likely to establish COVID-19 dedicated research (95% CI = 1.12–13.40; P < 0.05). CTSAs were instrumental in securing funds and facilitating establishment of laboratory/clinical spaces for COVID-19 research. Workflow was modified to support contracting and IRB review at most institutions with CTSAs. To mitigate chaos generated by competing clinical trials, central feasibility committees were often formed for orderly review/prioritization.

Conclusions:
The lessons learned from the COVID-19 pandemic emphasize the pivotal role of CTSAs in prioritizing studies and establishing the necessary research infrastructure, and the importance of prompt and flexible research leadership with decision-making capacity to manage future pandemics.
Treatment of ice-shelf evolution combining flow and flexure
Authors: MacAyeal Douglas R. , Sergienko Olga V. , Banwell Alison F. , Macdonald Grant J. , Willis Ian C. , Stevens Laura A. 
Published: April 2021

AbstractWe develop a two-dimensional, plan-view formulation of ice-shelf flow and viscoelastic ice-shelf flexure. This formulation combines, for the first time, the shallow-shelf approximation for horizontal ice-shelf flow (and shallow-stream approximation for flow on lubricated beds such as where ice rises and rumples form), with the treatment of a thin-plate flexure. We demonstrate the treatment by performing two finite-element simulations: one of the relict pedestalled lake features that exist on some debris-covered ice shelves due to strong heterogeneity in surface ablation, and the other of ice rumpling in the grounding zone of an ice rise. The proposed treatment opens new venues to investigate physical processes that require coupling between the longitudinal deformation and vertical flexure, for instance, the effects of surface melting and supraglacial lakes on ice shelves, interactions with the sea swell, and many others.
Genetics of substance use disorders: a review
Authors: Deak Joseph D. , Johnson Emma C. 
Published: April 2021

AbstractSubstance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2= ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g.ADH1BandALDH2) affecting alcohol-related traits, and loci within theCHRNA5-CHRNA3-CHRNB4gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.
A self-learning finite element extraction system based on reinforcement learning
Authors: Pan Jie , Huang Jingwei , Wang Yunli , Cheng Gengdong , Zeng Yong 
Published: April 2021

AbstractAutomatic generation of high-quality meshes is a base of CAD/CAE systems. The element extraction is a major mesh generation method for its capabilities to generate high-quality meshes around the domain boundary and to control local mesh densities. However, its widespread applications have been inhibited by the difficulties in generating satisfactory meshes in the interior of a domain or even in generating a complete mesh. The element extraction method's primary challenge is to define element extraction rules for achieving high-quality meshes in both the boundary and the interior of a geometric domain with complex shapes. This paper presents a self-learning element extraction system, FreeMesh-S, that can automatically acquire robust and high-quality element extraction rules. Two central components enable the FreeMesh-S: (1) three primitive structures of element extraction rules, which are constructed according to boundary patterns of any geometric boundary shapes; (2) a novel self-learning schema, which is used to automatically define and refine the relationships between the parameters included in the element extraction rules, by combining an Advantage Actor-Critic (A2C) reinforcement learning network and a Feedforward Neural Network (FNN). The A2C network learns the mesh generation process through random mesh element extraction actions using element quality as a reward signal and produces high-quality elements over time. The FNN takes the mesh generated from the A2C as samples to train itself for the fast generation of high-quality elements. FreeMesh-S is demonstrated by its application to two-dimensional quad mesh generation. The meshing performance of FreeMesh-S is compared with three existing popular approaches on ten pre-defined domain boundaries. The experimental results show that even with much less domain knowledge required to develop the algorithm, FreeMesh-S outperforms those three approaches in essential indices. FreeMesh-S significantly reduces the time and expertise needed to create high-quality mesh generation algorithms.
Making space for resistance: the spatiality of popular protest in the late medieval Southern Low Countries
Authors: Serneels Hannah 
Published: April 2021

AbstractUsing several cities in the late medieval Southern Low Countries as a case-study, this article deals with the relation between urban space and different forms of political protest. Urban commoners were aware of the powerful symbolism of certain places in the late medieval city and used that to their advantage during large-scale revolts. Yet the use of space was not limited to the dramatic occupations during these revolts. This article uncovers a wide range of strategies and tactics that common people used to act within given spaces to make their resistance possible. A spatial analysis of several instances of large- and smaller-scale resistance shows that space was intrinsically connected with how and when any form of resistance developed in late medieval cities. As such, the article aims to contribute to the literature on the importance of space in late medieval urban politics, in which attention to smaller-scale practices has been very limited.
Myotendinous Junction Components of Different Skeletal Muscles Present Morphological Changes in Obese Rats
Authors: Grillo Bruna Aléxia Cristofoletti , Rocha Lara C. , Martinez Giovana Z. , Pimentel Neto Jurandyr , Jacob Carolina dos Santos , Watanabe Ii-sei , Ciena Adriano P. 
Published: April 2021

Abstract
A Model for Buoyant Tephra Plumes Coupled to Lava Fountains With an Application to the 29th of August 2011 Paroxysmal Eruption at Mount Etna, Italy
Authors: Snee E. , Degruyter W. , Bonadonna C. , Scollo S. , Rossi E. , Freret‐Lorgeril V. 
Published: April 2021

AbstractExplosive basaltic eruptions pose significant threats to local communities, regional infrastructures and international airspace. They produce tephra plumes that are often associated with a lava fountain, complicating their dynamics. Consequently, source parameters cannot be easily constrained using traditional formulations. Particularly, mass flow rates (MFRs) derived from height observations frequently differ from field deposit‐derived MFRs. Here, we investigate this discrepancy using a novel integral plume model that explicitly accounts for a lava fountain, which is represented as a hot, coarse‐grained inner plume co‐flowing with a finer‐grained outer plume. The new model shows that a plume associated with a lava fountain has higher variability in rise height than a standard plume for the same initial MFR depending on initial conditions. The initial grain‐size distribution and the relative size of the lava fountain compared to the surrounding plume are primary controls on the final plume height as they determine the strength of coupling between the two plumes. We apply the new model to the August 29, 2011 paroxysmal eruption of Mount Etna, Italy. The modeled MFR profile indicates that the field‐derived MFR does not correspond to that at the vent, but rather the MFR just above the lava fountain top. High fallout from the lava fountain results in much of the erupted solid material not reaching the top of the plume. This material deposits to form the proximal cone rather than dispersing in the atmosphere. With our novel model, discrepancies between the two types of observation‐derived MFR can be investigated and understood.
Simultaneous Calibration of Hydrologic Model Structure and Parameters Using a Blended Model
Authors: Chlumsky Robert , Mai Juliane , Craig James R. , Tolson Bryan A. 
Published: April 2021

AbstractThe advent of hydrological modeling frameworks that support multiple model structures using the same software enables both model structure and model parameters to be calibrated and assessed. To date, the identification of optimal model structure has typically been performed manually. Here, a continuous (rather than discrete) treatment of model structure is used, which enables simultaneous automatic calibration of model structure and parameters using a conventional real‐valued decision variable optimization algorithm (the dynamically dimensioned search algorithm, DDS). The method, referred to herein as blended model structure calibration (BMSC), relies upon the calculation of each hydrologic flux (e.g., for infiltration) as a weighted average of fluxes generated from multiple process algorithm options. This method is applied to 12 lumped MOPEX catchment models and compared to the calibration of 108 fixed model structures, representing all possible permutations of fixed model structures with the given process options in this study. The BMSC method consistently identified near‐optimal model structure (as evaluated using average model rank performance) at significantly lower computational cost than calibrating the collective of fixed structure models. The BMSC method also provides a useful tool in identifying dominant processes and model structures in catchments.