bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing
Authors: Liu Fang , Wang Xiaojing , Hancock Roeland , Chen Ming-Hui 
Published: March 2022

AbstractComputerized assessment provides rich multidimensional data including trial-by-trial accuracy and response time (RT) measures. A key question in modeling this type of data is how to incorporate RT data, for example, in aid of ability estimation in item response theory (IRT) models. To address this, we propose a joint model consisting of a two-parameter IRT model for the dichotomous item response data, a log-normal model for the continuous RT data, and a normal model for corresponding paper-and-pencil scores. Then, we reformulate and reparameterize the model to capture the relationship between the model parameters, to facilitate the prior specification, and to make the Bayesian computation more efficient. Further, we propose several new model assessment criteria based on the decomposition of deviance information criterion (DIC) the logarithm of the pseudo-marginal likelihood (LPML). The proposed criteria can quantify the improvement in the fit of one part of the multidimensional data given the other parts. Finally, we have conducted several simulation studies to examine the empirical performance of the proposed model assessment criteria and have illustrated the application of these criteria using a real dataset from a computerized educational assessment program.
Deep convolutional neural network for multi-level non-invasive tunnel lining assessment
Authors: Chiaia Bernardino , Marasco Giulia , Aiello Salvatore 
Published: March 2022

AbstractIn recent years, great attention has focused on the development of automated procedures for infrastructures control. Many efforts have aimed at greater speed and reliability compared to traditional methods of assessing structural conditions. The paper proposes a multi-level strategy, designed and implemented on the basis of periodic structural monitoring oriented to a cost- and time-efficient tunnel control plan. Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential critical situations. In a supervised learning framework, Ground Penetrating Radar (GPR) profiles and the revealed structural phenomena have been used as input and output to train and test such networks. Image-based analysis and integrative investigations involving video-endoscopy, core drilling, jacking and pull-out testing have been exploited to define the structural conditions linked to GPR profiles and to create the database. The degree of detail and accuracy achieved in identifying a structural condition is high. As a result, this strategy appears of value to infrastructure managers who need to reduce the amount and invasiveness of testing, and thus also to reduce the time and costs associated with inspections made by highly specialized technicians.
Uncertainties in estimating global potential yields and their impacts for long-term modeling
Authors: Ollenburger Mary , Kyle Page , Zhang Xin 
Published: March 2022

AbstractEstimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.
Understanding drivers of stunting reduction in Nigeria from 2003 to 2018: a regression analysis
Authors: Adeyemi Olutayo , Toure Mariama , Covic Namukolo , van den Bold Mara , Nisbett Nicholas , Headey Derek 
Published: March 2022

AbstractNigeria is a high burden country for stunting. Stunting reduction has been slow and characterized by unequal progress across the 36 states and federal capital territory of the country. This study aimed to assess the changes in prevalence of stunting and growth determinants from 2003 to 2018, identify factors that predicted the change in stunting, and project future stunting prevalence if these predicted determinants improve. Trend and linear decomposition analyses of growth outcomes and determinants were conducted using 2003, 2008, 2013, and 2018 Nigeria Demographic and Health Survey data. Pooled data included 57,507 children 0 to 59 months old. Findings show that stunting and severe stunting significantly reduced from 43 to 37% and 23% to 17%, respectively (p < 0.001), between 2003 and 2018. Disturbingly, height-for-age z-scores at birth significantly decreased, indicating risks of potential future stunting increase. Improvements in nine stunting determinants (maternal body mass index, maternal height, ≥ 4 antenatal care visits, health facility delivery, reduced child illnesses, asset index, maternal education, paternal education, and preceding birth interval) predicted stunting reductions in children 0–59 months. Few of these nine determinants improved in subpopulations with limited stunting progress. Intra-sectoral and multisectoral coordination were potentially inadequate; 12% of children had received all of three selected health sector interventions along a continuum of care and 6% had received all of six selected multisector interventions. Forward looking projections suggest that increased efforts to improve the nine predictors of stunting change can reduce under-five stunting in Nigeria to ≤ 27% in the short term.
Environmental and health impact of current uranium mining activities in southwestern Sinai, Egypt
Authors: Ramadan Randa S. , Dawood Yehia H. , Yehia Mohamed M. , Gad Ahmed 
Published: March 2022

AbstractStream sediments and groundwater samples were collected from the vicinity of El Allouga uranium mine in southwestern Sinai and analyzed for their radionuclides to explore the geochemical dispersion and environmental impact. The radioactivity measurements were performed using γ-ray spectrometry and UV-photometry. Most stream sediments samples have eU concentrations more than the background level. The significant correlations between eU, clay, and organic matter contents reflect possible adsorption of U to the surface of clay and organic matter. The high radionuclide concentrations in the stream sediment are mainly due to contamination from the mining process, and, in some locations, due to rock outcrops weathering. The measured concentrations of U in groundwater samples exceed the Maximum Contamination Level of groundwater U (30 ppb). The lack of correspondence of U concentrations in the country rocks and associated groundwater indicates the high mobility of U and reflects absence of a simple rock/water equilibration. Water resources in the study area have 234U/238U activity ratios with obvious deviations from secular equilibrium. The U isotopic data support that uranium ore body could be locally forming within the rock aquifer at El Allouga area. The calculated external hazard parameter values are higher than the worldwide average in 30% of the studied stream sediment samples; this indicates that people who are exposed to that level of radiation for a lifetime would have an elevated cancer risk. The Annual Effective Dose resulting from U activity concentrations in the studied drinking water is significantly higher than the recommended limit for children and adults. Therefore, the available water resources in the study area are considered unsafe for human consumption.
A numerical verification method to specify homoclinic orbits as application of local Lyapunov functions
Authors: Nitta Koki , Yamamoto Nobito , Matsue Kaname 
Published: March 2022

AbstractWe propose a verification method for specification of homoclinic orbits as application of our previous work for constructing local Lyapunov functions by verified numerics. Our goal is to specify parameters appeared in the given systems of ordinary differential equations (ODEs) which admit homoclinic orbits to equilibria. Here we restrict ourselves to cases that each equilibrium is independent of parameters. The feature of our methods consists of Lyapunov functions, integration of ODEs by verified numerics, and Brouwer’s coincidence theorem on continuous mappings. Several techniques for constructing continuous mappings from a domain of parameter vectors to a region of the phase space are shown. We present numerical examples for problems in 3 and 4-dimensional cases.
Ricci solitons on four-dimensional Lorentzian Lie groups
Authors: Ferreiro-Subrido M. , García-Río E. , Vázquez-Lorenzo R. 
Published: March 2022

AbstractWe determine all non-Einstein Ricci solitons on four-dimensional Lorentzian Lie groups whose soliton vector field is left-invariant. In addition to pp-wave and plane wave Lie groups, there are four families of Lorentzian metrics on semi-direct extensions $$\mathbb {R}^3\rtimes \mathbb {R}$$

R

3

⋊
R

and $$E(1,1)\rtimes \mathbb {R}$$

E
(
1
,
1
)
⋊
R

. We show that some of these Ricci solitons are conformally Einstein and they may be expanding, steady or shrinking.
Domain-adapted Gaussian mixture models for population-based structural health monitoring
Authors: Gardner Paul , Bull Lawrence A. , Dervilis Nikolaos , Worden Keith 
Published: March 2022

AbstractTransfer learning, in the form of domain adaptation, seeks to overcome challenges associated with a lack of available health-state data for a structure, which severely limits the effectiveness of conventional machine learning approaches to structural health monitoring (SHM). These technologies utilise labelled information across a population of structures (and physics-based models), such that inferences are improved, either for the complete population, or for particular target structures — enabling a population-based view of SHM. The aim of these methods is to infer a mapping between each member of the population’s feature space (called a domain) in which a classifier trained on one member of the population will generalise to the remaining structures. This paper introduces the domain-adapted Gaussian mixture model (DA-GMM) for population-based SHM (PBSHM) scenarios. The DA-GMM, infers a linear mapping that transforms target data from one structure onto a Gaussian mixture model that has been inferred from source data (from another structure). The proposed model is solved via an expectation maximisation technique. The method is demonstrated on three case studies: an artificial dataset demonstrating the approach’s effectiveness when the target domain differs by two-dimensional rotations; a population of two numerical shear-building structures; and a heterogeneous population of two bridges, the Z24 and KW51 bridges. In each case study, the method is shown to provide informative results, outperforming other conventional forms of GMM (where no target labelled data are assumed available), and provide mappings that allow the effective exchange of labelled information from source to target datasets.
The genesis, development and implementation of an interdisciplinary university Cross-School Research Group
Authors: Brandenburg Robyn , Smith Jeremy , Higgins Angela , Courvisanos Jerry 
Published: March 2022

AbstractThis article examines the genesis, development and implementation of an interdisciplinary university cross-school research group (three individual schools) at Federation University in Australia. This CSRG is a consequence of both local and national calls for interdisciplinarity in university research and a direct response to the revised Strategic Goals and Policy document at Federation University. Using a conceptual framework based on a treatise by Jürgen Habermas (The theory of communicative action, Beacon Press, 1987) incorporating three socio-political levels (Lifeworld, Steering Media and Systems), we examined the ideals, processes and challenges in setting up an interdisciplinary research group within a traditional disciplinary-based university environment. Drawing on multiple data sets composed of member survey responses and interviews, email communication, online meetings, policy documents and co-leader feedback, we identified key resonant themes focussing on academic aspiration and motivation, the role of policy and practice, influence of grants and grant development across schools, mentoring and publishing. Using Habermas’ conceptual framework and his overarching notion of Lifeworld with qualitative methods of data analysis, this article explores establishment of the CSRG, deeper academic aspirations and engagement for interdisciplinarity informing the group’s formation and effectiveness of the processes used in this specific case. The impact on systems and policy is addressed together with the processes adopted to bring about interdisciplinary university collaboration. Evaluating the formation of the CSRG, the authors found that researchers placed a high value on opportunities to creatively collaborate in a cross-school and interdisciplinary environment, whereas obtaining grants and publishing research were seen by staff as indirect and less immediate benefits of collaboration. This article contributes to the growing body of research on interdisciplinary collaboration by applying a distinct theoretical and analytical framework to emphasise the potential of grassroots collaboration and the role of power and influence on research within universities.
Metallurgical infrastructure and technology criticality: the link between photovoltaics, sustainability, and the metals industry
Authors: Bartie Neill , Cobos-Becerra Lucero , Fröhling Magnus , Schlatmann Rutger , Reuter Markus 
Published: March 2022

Abstract
Various high-purity metals endow renewable energy technologies with specific functionalities. These become heavily intertwined in products, complicating end-of-life treatment. To counteract downcycling and resource depletion, maximising both quantities and qualities of materials recovered during production and recycling processes should be prioritised in the pursuit of sustainable circular economy. To do this well requires metallurgical infrastructure systems that maximise resource efficiency.To illustrate the concept, digital twins of two photovoltaic (PV) module technologies were created using process simulation. The models comprise integrated metallurgical systems that produce, among others, cadmium, tellurium, zinc, copper, and silicon, all of which are required for PV modules. System-wide resource efficiency, environmental impacts, and technoeconomic performance were assessed using exergy analysis, life cycle assessment, and cost models, respectively. High-detail simulation of complete life cycles allows for the system-wide effects of various production, recycling, and residue exchange scenarios to be evaluated to maximise overall sustainability and simplify the distribution of impacts in multiple-output production systems. This paper expands on previous studies and demonstrates the key importance of metallurgy in achieving Circular Economy, not only by means of reactors, but via systems and complete supply chains—not only the criticality of elements, but also the criticality of available metallurgical processing and other infrastructure in the supply chain should be addressed. The important role of energy grid compositions, and the resulting location-based variations in supply chain footprints, in maximising energy output per unit of embodied carbon footprint for complete systems is highlighted.
A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models
Authors: Azhari Fatemeh , Davids William , Chen Hansheng , Ringer Simon P. , Wallbrink Chris , Sterjovski Zoran , Crawford Bruce R. , Agius Dylan , Wang Chun H. , Schaffer Graham 
Published: March 2022

AbstractTwo methods used to construct a microstructural representative volume element (RVE) were evaluated for their accuracy when used in a crystal plasticity-based finite element (CP-FE) model. The RVE-based CP-FE model has been shown to accurately predict the complete tensile stress–strain response of a Ti–6Al–4V alloy manufactured by laser powder bed fusion. Each method utilized a different image-based technique to create a three-dimensional (3D) RVE from electron backscatter diffraction (EBSD) images. The first method, referred to as the realistic RVE (R-RVE), reconstructed a physical 3D microstructure of the alloy from a series of parallel EBSD images obtained using serial-sectioning (or slicing). The second method captures key information from three orthogonal EBSD images to create a statistically equivalent microstructural RVE (SERVE). Based on the R-RVEs and SERVEs, the CP-FE model was then used to predict the complete tensile stress–strain response of the alloy, including the post-necking damage progression. The accuracy of the predicted stress–strain responses using the R-RVEs and SERVEs was assessed, including the effects of each microstructure descriptor. The results show that the R-RVE and the SERVE offer comparable accuracy for the CP-FE purposes of this study.
Bibliometric Analysis of the Structure and Evolution of Research on Assisted Migration
Authors: Benomar Lahcen , Elferjani Raed , Hamilton Jill , O’Neill Greg A. , Echchakoui Said , Bergeron Yves , Lamara Mebarek 
Published: March 2022

AbstractPurpose of ReviewAssisted migration is increasingly proposed as a proactive management strategy to mitigate the consequences of maladaptation predicted under climate change. Exploring the social and academic structure of the field, its research gaps, and future research directions can help further the understanding and facilitate the implementation of assisted migration strategies. Here we used bibliometric analysis to examine the intellectual, social, and conceptual structures of assisted migration research to identify gaps and opportunities for future research. Bibliometric data based on publications on assisted migration were collected from Scopus and Web of Science databases using assisted migration and climate change or their synonyms as queries. Metadata were merged, processed and several networks were constructed.Recent FindingsCo-citation and keyword co-occurrence networks identified three major clusters focused on (i) theory and risk of assisted migration of threatened and endangered species, (ii) impact of climate change on realized and fundamental climate and geographic niches, and (iii) assisted population migration. Collaboration network analysis identified three social core hubs: North America, Europe, and Australia, with the USA and Canada being the most productive and the most collaborative countries.SummaryWe conclude that future research is expected to concern mainly the assessment of physiological response of species and populations to extreme climate events such as drought and frost, and the contribution of non-climatic factors and biotic interactions in local adaptation and population performance under climate change. Social core hubs distinguished in this work can be used to identify potential international research and training collaborators necessary to address gaps and challenges underlying assisted migration implementation.
Challenges in Adopting Recovery-oriented Practices in Specialized Mental Health Care: “How Far Should Self-Determination Go; Should One be Allowed to Perish?”
Authors: Ørjasæter Kristin B. , Almvik Arve 
Published: March 2022

AbstractMental health services need to transform from a primary focus on symptom reduction to a recovery-oriented delivery. Research on recovery-oriented practices is mainly based in community mental health settings, while research on specialized mental health care remains scarce. In this article, we aim to identify and explore the experiences faced by professionals working in specialized mental health care units that aim to be recovery-oriented. Data were collected during seven focus group interviews with 45 professionals from four psychiatric hospitals and district psychiatric centers in Norway. We used reflexive thematic analysis to interpret the data. Three main themes emerged from the analysis: (a) disease-oriented structures, (b) negotiating roles and (c) risk management. This study identified the many tensions professionals face as they try to shift specialized mental health care toward a recovery-oriented paradigm. Specifically, professionals must balance managing risks and promoting self-determination. To succeed, it is not sufficient to implement practices that are characterized as recovery-oriented without also changing existing systems, structures, and frameworks. We suggest approaching recovery orientation through shared decision-making. This could contribute to the promotion of self-determination and increased inpatient safety in specialized mental health care.
Highly Flexible and Broad-Range Mechanically Tunable All-Wood Hydrogels with Nanoscale Channels via the Hofmeister Effect for Human Motion Monitoring
Authors: Yan Guihua , He Shuaiming , Chen Gaofeng , Ma Sen , Zeng Anqi , Chen Binglin , Yang Shuliang , Tang Xing , Sun Yong , Xu Feng , Lin Lu , Zeng Xianhai 
Published: March 2022

AbstractWood-based hydrogel with a unique anisotropic structure is an attractive soft material, but the presence of rigid crystalline cellulose in natural wood makes the hydrogel less flexible. In this study, an all-wood hydrogel was constructed by cross-linking cellulose fibers, polyvinyl alcohol (PVA) chains, and lignin molecules through the Hofmeister effect. The all-wood hydrogel shows a high tensile strength of 36.5 MPa and a strain up to ~ 438% in the longitudinal direction, which is much higher than its tensile strength (~ 2.6 MPa) and strain (~ 198%) in the radial direction, respectively. The high mechanical strength of all-wood hydrogels is mainly attributed to the strong hydrogen bonding, physical entanglement, and van der Waals forces between lignin molecules, cellulose nanofibers, and PVA chains. Thanks to its excellent flexibility, good conductivity, and sensitivity, the all-wood hydrogel can accurately distinguish diverse macroscale or subtle human movements, including finger flexion, pulse, and swallowing behavior. In particular, when “An Qi” was called four times within 15 s, two variations of the pronunciation could be identified. With recyclable, biodegradable, and adjustable mechanical properties, the all-wood hydrogel is a multifunctional soft material with promising applications, such as human motion monitoring, tissue engineering, and robotics materials.