bluuebunny/crossref_metadata_2025_split huggingface dataset:
Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
Authors: Lima Pedro , Steger Stefan , Glade Thomas , Murillo-García Franny G. 
Published: June 2022

AbstractIn recent decades, data-driven landslide susceptibility models (DdLSM), which are based on statistical or machine learning approaches, have become popular to estimate the relative spatial probability of landslide occurrence. The available literature is composed of a wealth of published studies and that has identified a large variety of challenges and innovations in this field. This review presents a comprehensive up-to-date overview focusing on the topic of DdLSM. This research begins with an introduction of the theoretical aspects of DdLSM research and is followed by an in-depth bibliometric analysis of 2585 publications. This analysis is based on the Web of Science, Clarivate Analytics database and provides insights into the transient characteristics and research trends within published spatial landslide assessments. Following the bibliometric analysis, a more detailed review of the most recent publications from 1985 to 2020 is given. A variety of different criteria are explored in detail, including research design, study area extent, inventory characteristics, classification algorithms, predictors utilized, and validation technique performed. This section, dealing with a quantitative-oriented review expands the time-frame of the review publication done by Reichenbach et al. in 2018 by also accounting for the four years, 2017–2020. The originality of this research is acknowledged by combining together: (a) a recap of important theoretical aspects of DdLSM; (b) a bibliometric analysis on the topic; (c) a quantitative-oriented review of relevant publications; and (d) a systematic summary of the findings, indicating important aspects and potential developments related to the DdLSM research topic. The results show that DdLSM are used within a wide range of applications with study area extents ranging from a few kilometers to national and even continental scales. In more than 70% of publications, a combination of the predictors, slope angle, aspect and geology are used. Simple classifiers, such as, logistic regression or approaches based on frequency ratio are still popular, despite the upcoming trend of applying machine learning algorithms. When analyzing validation techniques, 38% of the publications were not clear about the validation method used. Within the studies that included validation techniques, the AUROC was the most popular validation metric, being used accounting for 44% of the studies. Finally, it can be concluded that the application of new classification techniques is often cited as a main research scope, even though the most relevant innovation could also lie in tackling data-quality issues and research designs adaptations to fit the input data particularities in order to improve prediction quality.
Is it time to consider population screening for fracture risk in postmenopausal women? A position paper from the International Osteoporosis Foundation Epidemiology/Quality of Life Working Group
Authors: Chotiyarnwong P. , McCloskey E. V. , Harvey N. C. , Lorentzon M. , Prieto-Alhambra D. , Abrahamsen B. , Adachi J. D. , Borgström F. , Bruyere O. , Carey J. J. , Clark P. , Cooper C. , Curtis E. M. , Dennison E. , Diaz-Curiel M. , Dimai H. P. , Grigorie D. , Hiligsmann M. , Khashayar P. , Lewiecki E. M. , Lips P. , Lorenc R. S. , Ortolani S. , Papaioannou A. , Silverman S. , Sosa M. , Szulc P. , Ward K. A. , Yoshimura N. , Kanis J. A. 
Published: June 2022

Abstract

Summary

The IOF Epidemiology and Quality of Life Working Group has reviewed the potential role of population screening for high hip fracture risk against well-established criteria. The report concludes that such an approach should strongly be considered in many health care systems to reduce the burden of hip fractures.

Introduction
The burden of long-term osteoporosis management falls on primary care in most healthcare systems. However, a wide and stable treatment gap exists in many such settings; most of which appears to be secondary to a lack of awareness of fracture risk. Screening is a public health measure for the purpose of identifying individuals who are likely to benefit from further investigations and/or treatment to reduce the risk of a disease or its complications. The purpose of this report was to review the evidence for a potential screening programme to identify postmenopausal women at increased risk of hip fracture.

Methods
The approach took well-established criteria for the development of a screening program, adapted by the UK National Screening Committee, and sought the opinion of 20 members of the International Osteoporosis Foundation’s Working Group on Epidemiology and Quality of Life as to whether each criterion was met (yes, partial or no). For each criterion, the evidence base was then reviewed and summarized.

Results and Conclusion
The report concludes that evidence supports the proposal that screening for high fracture risk in primary care should strongly be considered for incorporation into many health care systems to reduce the burden of fractures, particularly hip fractures. The key remaining hurdles to overcome are engagement with primary care healthcare professionals, and the implementation of systems that facilitate and maintain the screening program.
An update on adrenocortical cell lines of human origin
Authors: Sigala Sandra , Rossini Elisa , Abate Andrea , Tamburello Mariangela , Bornstein Stefan R. , Hantel Constanze 
Published: June 2022

AbstractAdrenocortical carcinoma (ACC) is a rare, heterogenous and highly malignant disease. Management of ACC is dependent on disease stage with complete surgical resection as the only potentially curative option. However, advanced, un-resectable, metastatic stages and also recurrences often require systemic treatments, which are unfortunately nowadays still unsatisfactory. The scarcity of preclinical models reflecting patient heterogeneities and furthermore drug-resistant phenotypes, has hampered the progress and development of new therapies in recent years. In this review, we provide an overview on the classical models and substantial progress which has been made over the last years in context of this aggressive disease.
‘If you don’t feel respect then morally, it just takes a lot out of everything you’re doing”: learning in a pedagogical approach inspired by Reggio Emilia middle years school settings
Authors: Rouse Elizabeth 
Published: June 2022

AbstractPractice and pedagogy, influenced and informed by the approaches used in the preschool programs of Reggio Emilia is widespread across many early childhood settings in Australia, however, is less commonly used in Australian primary and secondary schools. Little research exists which focuses on the experiences of students in schools where this pedagogical approach is adopted. This paper draws from the findings of a 2019 study undertaken across three Australian schools implementing a pedagogical approach inspired by Reggio Emilia. The voices of students from one of these schools will be used to shed light on their perceived learner identity. The study found that the expressed learner identities were multifaceted. On one hand the students considered themselves to be informed, confident and passionate learners, shaping their world as democratic citizens. However, they also positioned themselves as citizens of the future, sharing perceptions regarding their capacity to compete as successful productive members of an economic society.
Publishing in the academy: An arts-based, metaphorical reflection towards self-care
Authors: Barton Georgina , Brömdal Annette , Burke Katie , Fanshawe Melissa , Farwell Vicki , Larsen Ellen , Pillay Yosheen 
Published: June 2022

AbstractPublishing in the academy is a high-stakes activity often used to measure academic staff progress and inform promotion. Many universities have increased pressure on academics, even at the earliest stages of their careers, to publish in high-ranking journals resulting in increased stress and uncertainty. The authors of this paper are members of a writing group in an Australian regional university, established to support each other towards success in quality research and publishing. Over the 2020–2021 summer semester, six members of the group decided to reflect on their experiences, emotions and outcomes throughout the writing process by participating in four reflective arts-based activities. Theoretical frameworks of reflection and metaphor were used to share findings. Strong evidence of having to grapple with meeting university expectations in tension with personal goals and passions was ever-present. The importance of drawing on both personal resources and significant others to manage these tensions through self-care practices was also evident. Implications resulting from this research include recognising the pressures placed on academics to publish only in specifically ranked journals. Overall, the arts-based reflection was critical in uncovering deeper feelings about the pressures of publishing and supporting higher education employees’ well-being and self-care during the writing process.
Emerging technologies for the production of biojet fuels from wood—can greenhouse gas emission reductions meet policy requirements?
Authors: Björnsson Lovisa , Ericsson Karin 
Published: June 2022

AbstractThe transition from fossil jet fuel to biojet fuel is an important step towards reducing greenhouse gas (GHG) emissions from aviation. To enable such a fuel shift, the Swedish Government introduced a GHG emission reduction mandate of 27% by 2030 for aviation fuel sold in Sweden, forcing fuel suppliers to blend in biojet fuel in fossil jet fuel. A similar policy instrument is being discussed within the EU. Biojet fuels with life cycle GHG emissions 90% lower than those for fossil jet fuel are projected to be available by 2025, which by far exceeds the requirement of 65% lower emissions in the EU Renewable Energy Directive. The purpose of this study was to carry out life cycle assessments for a number of wood-fuel-based production chains near commercialization and to determine whether they meet the Swedish projection and the EU requirement. The study illustrates what can be achieved in a region with high availability of wood fuels and access to heat and power with low GHG emissions. The production chains studied include the production of hydrocarbon intermediates via (i) fast pyrolysis, (ii) hydrothermal liquefaction, (iii) thermal gasification followed by Fischer–Tropsch-synthesis, and (iv) cellulosic ethanol fermentation followed by upgrading of these four intermediates to biojet fuel and other liquid biofuels. The results show that all the production chains studied can deliver biojet fuels with 89–91% lower GHG emissions than fossil jet fuels. Non-fossil hydrogen is required to achieve low emissions in the upgrading of intermediates from fast pyrolysis and hydrothermal liquefaction.
Glioblastoma, from disease understanding towards optimal cell-based in vitro models
Authors: Boccellato Chiara , Rehm Markus 
Published: June 2022

Abstract
Background
Glioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and treatment options initially can be evaluated pre-clinically. Here, we provide a concise overview of glioblastoma epidemiology, disease classification, the challenges faced in the treatment of glioblastoma and current novel treatment strategies. From this, we lead into a description and assessment of advanced cell-based models that aim to narrow the gap between pre-clinical and clinical studies. Such invitro models are required to deliver reliable and meaningful data for the development and pre-validation of novel therapeutics and treatments.

Conclusions
The toolbox for GBM cell-based models has expanded substantially, with the possibility of 3D printing tumour tissues and thereby replicating invivo tissue architectures now looming on the horizon. A comparison of experimental cell-based model systems and techniques highlights advantages and drawbacks of the various tools available, based on which cell-based models and experimental approaches best suited to address a diversity of research questions in the glioblastoma research field can be selected.
Free Movement of Audiovisual Content for Benefit of European Consumers of Culture
Authors: Mylly Ulla-Maija , Herrero Mónica 
Published: June 2022

AbstractOne of the EU’s founding premises was the establishment of the internal market, in which the free movement of goods, persons, services and capital is ensured. However, in the present online era, the internal market remains far from frictionless. To address this failure, the EU launched the Digital Market Strategy in 2015. One component of this strategy is the removal of barriers for the flow of online content across borders. This article highlights the fact that free movement of audiovisual online content is of paramount importance for European end users, and an important component for the free movement of persons in the EU. Free movement of audiovisual content would enable Europeans who have migrated to another European country to access content from their home country. In addition, the free flow of audiovisual online content would serve the interests of various language minorities. Serving the end users of audiovisual content in this manner would be in line with important objectives of the EU, such as the protection of European cultural diversity and the public sphere. This article notes that when the EU has regulated digital audiovisual markets, the emphasis has been on the protection of copyright-related interests. This has meant that other stakeholder interests linked to cultural diversity and non-discrimination have been undervalued and played only a limited role. The article posits that, with regard to audiovisual content, more weight than before should be given to the free movement of persons and to minority language rights. This would also align with achieving a digital single market in audiovisual online services.
An agent-based modeling framework for the design of a dynamic closed-loop supply chain network
Authors: Bozdoğan Ayşegül , Görkemli Aykut Latife , Demirel Neslihan 
Published: June 2022

AbstractThe supply chain is a dynamic and uncertain system consisting of material, information, and fund flows between different organizations, from the acquisition of the raw materials to the delivery of the finished products to the end customers. Closed-loop supply chains do not end with the delivery of the finished products to the end customers, the process continues until economic value is obtained from the returned products or they are disposed properly in landfills. Incorporating reverse flows in supply chains increases the uncertainty and complexity, as well as complicating the management of supply chains that are already composed of different actors and have a dynamic structure. Since agent-based modeling and simulation is a more efficient method of handling the dynamic and complex nature of supply chains than the traditional analytical methods, in this study agent-based modeling methodology has been used to model a generic closed-loop supply chain network design problem with the aims of integrating customer behavior into the network, coping with the dynamism, and obtaining a more realistic structure by eliminating the required assumptions for solving the model with analytical methods. The actors in the CLSC network have been defined as agents with goals, properties and behaviors. In the proposed model dynamic customer arrivals, the changing aspects of customers' purchasing preferences for new and refurbished products and the time, quantity and quality uncertainties of returns have been handled via the proposed agent-based architecture. To observe the behavior of the supply chain in several conditions various scenarios have been developed according to different parameter settings for the supplier capacities, the rate of customers being affected by advertising, the market incentive threshold values, and the environmental awareness of customers. From the scenarios, it has been concluded that the system should be fed in the right amounts for the new and refurbished products to increase the effectiveness of factors such as advertising, incentives, and environmental awareness for achieving the desired sales amounts and cost targets.
A distributed gradient algorithm based on randomized block-coordinate and projection-free over networks
Authors: Zhu Junlong , Wang Xin , Zhang Mingchuan , Liu Muhua , Wu Qingtao 
Published: June 2022

AbstractThe computational bottleneck in distributed optimization methods, which is based on projected gradient descent, is due to the computation of a full gradient vector and projection step. This is a particular problem for large datasets. To reduce the computational complexity of existing methods, we combine the randomized block-coordinate descent and the Frank–Wolfe techniques, and then propose a distributed randomized block-coordinate projection-free algorithm over networks, where each agent randomly chooses a subset of the coordinates of its gradient vector and the projection step is eschewed in favor of a much simpler linear optimization step. Moreover, the convergence performance of the proposed algorithm is also theoretically analyzed. Specifically, we rigorously prove that the proposed algorithm can converge to optimal point at rate of $${\mathcal {O}}(1/t)$$

O
(
1
/
t
)

under convexity and $${\mathcal {O}}(1/t^2)$$

O
(
1
/

t
2

)

under strong convexity, respectively. Here, t is the number of iterations. Furthermore, the proposed algorithm can converge to a stationary point, where the “Frank-Wolfe” gap is equal to zero, at a rate $${\mathcal {O}}(1/\sqrt{t})$$

O
(
1
/

t

)

under non-convexity. To evaluate the computational benefit of the proposed algorithm, we use the proposed algorithm to solve the multiclass classification problems by simulation experiments on two datasets, i.e., aloi and news20. The results shows that the proposed algorithm is faster than the existing distributed optimization algorithms due to its lower computation per iteration. Furthermore, the results also show that well-connected graphs or smaller graphs leads to faster convergence rate, which can confirm the theoretical results.
A robust target tracking algorithm based on spatial regularization and adaptive updating model
Authors: Chen Kansong , Guo Xiang , Xu Lijun , Zhou Tian , Li Ran 
Published: June 2022

AbstractThe correlation filtering-based target tracking method has impressive tracking performance and computational efficiency. Nevertheless, a few issues limit the accuracy of the correlation filter-based tracking methods including the object deformation, boundary effects, scale variations, and the target occlusion. This article proposes a robust target tracking algorithm to solve these issues. First, a feature fusion method is used to enhance feature response discrimination between the target and others. Second, a spatial weight function is introduced to penalize the magnitude of filter coefficients and an ADMM algorithm is employed to reduce the iteration of filter coefficients when tracking. Third, an adaptive scale filter is designed to make the algorithm adaptable to the scale variations. Finally, the correlation peak average difference ratio is applied to realize the adaptive updating and improve the stability. The experiment’s result demonstrates the proposed algorithm improved tracking results compared to the state-of-the-art correlation filtering-based target tracking method.
On Existence and Admissibility of Singular Solutions for Systems of Conservation Laws
Authors: Kalisch Henrik , Mitrovic Darko 
Published: June 2022

AbstractA weak notion of solution for systems of conservation laws in one dimension is put forward. In the framework introduced here, it can be shown that the Cauchy problem for any$$n\times n$$n×nsystem of conservation laws has a solution. The solution concept is an extension of the notion of singular$$\delta $$δ-shocks which have been used to provide solutions for Riemann problems in various systems, for example in cases where strict hyperbolicity or the genuine-nonlinearity condition are not satisfied, or in cases where initial conditions have large variation. We also introduce admissibility conditions which eliminate a wide range of unreasonable solutions. Finally, we provide an example from the shallow water system which justifies introduction of$$\delta $$δ-distributions as a part of solutions to systems of conservation laws.
Broken Promises – The Probable Futurity of the Laboring Class (Re-Assessed)
Authors: Aßländer Michael S. 
Published: June 2022

AbstractOver the past two decades, work relations have changed dramatically. New phenomena like “gig-economy” or “crowd work” not only constitute precarious working conditions but also contradict with our social esteem of work resulting from the social theories of the classical economy of the eighteenth and nineteenth centuries. The central focus of classical economists on building an educated and disciplined workforce provided not only the base for the upcoming industrial society but also resulted in a work-based society where “being employed” became the precondition for social security and social participation. It is the aim of this contribution to show how our positive attitudes towards work, established by the political economic theories of the eighteenth and nineteenth centuries, are jeopardized by the social changes in post-industrialized societies, due to the effects of globalized economies, digitalization and changed industrial relations. This has also far-reaching consequences for managerial theories based on conceptions like meaningful work or discussions about social responsibilities vis-à-vis employees as primary stakeholder groups.
Exploring the impact of air pollution on COVID-19 admitted cases
Authors: Alsaber Ahmad R. , Setiya Parul , Al-Sultan Ahmad T. , Pan Jiazhu 
Published: June 2022

AbstractIn urban areas, air pollution is one of the most serious global environmental issues. Using time-series approaches, this study looked into the validity of the relationship between air pollution and COVID-19 hospitalization. This time series research was carried out in the state of Kuwait; stationarity test, cointegration test, Granger causality and stability test, and test on multivariate time-series using the Vector Error Correction Model (VECM) technique. The findings reveal that the concentration rate of air pollutants ($$\hbox {O}_3$$

O
3

, $$\hbox {SO}_2$$

SO
2

, $$\hbox {NO}_2$$

NO
2

, $$\hbox {CO}$$
CO
, and $$\hbox {PM}_{10}$$

PM
10

) has an effect on COVID-19 admitted cases via Granger-cause. The Granger causation test shows that the concentration rate of air pollutants ($$\hbox {O}_3$$

O
3

, $$\hbox {PM}_{10}$$

PM
10

, $$\hbox {NO}_2$$

NO
2

, temperature and wind speed) influences and predicts the COVID-19 admitted cases. The findings suggest that sulfur dioxide ($$\hbox {SO}_2$$

SO
2

), $$\hbox {NO}_2$$

NO
2

, temperature, and wind speed induce an increase in COVID-19 admitted cases in the short term according to VECM analysis. The evidence of a positive long-run association between COVID-19 admitted cases and environmental air pollution might be shown in the cointegration test and the VECM. There is an affirmation that the usage of air pollutants ($$\hbox {O}_3$$

O
3

, $$\hbox {SO}_2$$

SO
2

, $$\hbox {NO}_2$$

NO
2

, $$\hbox {CO}$$
CO
, and $$\hbox {PM}_{10}$$

PM
10

) has a significant impact on COVID-19-admitted cases’ prediction and its explained about 24% of increasing COVID-19 admitted cases in Kuwait.