bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Macroeconomic Imbalance Procedure at the Heart of EU Economic Governance Reform
Authors: Koll Willi , Watt Andrew 
Published: February 2022

AbstractWhile the euro officially came into being in 1999, it was the introduction of euro notes and coins 20 years ago in January 2002 that made the common currency a tangible reality for European citizens. The circle of member states has since grown from 11 to 19, and a growing section of the population no longer has any personal experience with a “national” currency, yet the debate on the legal and institutional framework underpinning the common currency has never gone away.
Iterative multilevel assimilation of inverted seismic data
Authors: Nezhadali Mohammad , Bhakta Tuhin , Fossum Kristian , Mannseth Trond 
Published: February 2022

AbstractIn ensemble-based data assimilation (DA), the ensemble size is usually limited to around one hundred. Straightforward application of ensemble-based DA can therefore result in significant Monte Carlo errors, often manifesting themselves as severe underestimation of parameter uncertainties. Localization is the conventional remedy for this problem. Assimilation of large amounts of simultaneous data enhances the negative effects of Monte Carlo errors. Use of lower-fidelity models reduces the computational cost per ensemble member and therefore renders the possibility to reduce Monte Carlo errors by increasing the ensemble size, but it also adds to the modeling error. Multilevel data assimilation (MLDA) uses a selection of models forming hierarchies of both computational cost and computational accuracy, and tries to balance between Monte Carlo errors and modeling errors. In this work, we assess a recently developed MLDA algorithm, the Multilevel Hybrid Ensemble Smoother (MLHES), and introduce and assess an iterative version of this algorithm, the Iterative Multilevel Hybrid Ensemble Smoother (IMLHES). In our assessments, we compare these algorithms with conventional single-level DA algorithms with localization. To this end, a typical example of large amount of spatially distributed data, i.e. inverted seismic data, is considered and three data sets of this kind are assimilated in three different petroleum reservoir models. Qualitatively evaluating the DA outcomes, it is found that multilevel algorithms outperform their conventional single-level counterparts in obtaining the posterior statistics of both uncertain parameters and model forecasts. Additionally, it is observed that IMLHES performs better than MLHES in the same regard, and also successfully converges to the proximity of solution in a case where the considered iterative single-level algorithm did not converge to the global optimum.
Multi-objective optimisation of ultrasonically welded dissimilar joints through machine learning
Authors: Mongan Patrick G. , Modi Vedant , McLaughlin John W. , Hinchy Eoin P. , O’Higgins Ronan M. , O’Dowd Noel P. , McCarthy Conor T. 
Published: February 2022

AbstractThe use of composite materials is increasing in industry sectors such as renewable energy generation and storage, transport (including automotive, aerospace and agri-machinery) and construction. This is a result of the various advantages of composite materials over their monolithic counterparts, such as high strength-to-weight ratio, corrosion resistance, and superior fatigue performance. However, there is a lack of detailed knowledge in relation to fusion joining techniques for composite materials. In this work, ultrasonic welding is carried out on a carbon fibre/PEKK composite material bonded to carbon fibre/epoxy composite to investigate the influence of weld process parameters on the joint’s lap shear strength (LSS), the process repeatability, and the process induced defects. A 33 parametric study is carried out and a robust machine learning model is developed using a hybrid genetic algorithm–artificial neural network (GA–ANN) trained on the experimental data. Bayesian optimisation is employed to determine the most suitable GA–ANN hyperparameters and the resulting GA–ANN surrogate model is exploited to optimise the welding process, where the process performance metrics are LSS, repeatability and joint visual quality. The prediction for the optimal LSS was subsequently validated through a further set of experiments, which resulted in a prediction error of just 3%.
The Limit Empirical Spectral Distribution of Gaussian Monic Complex Matrix Polynomials
Authors: Barbarino Giovanni , Noferini Vanni 
Published: February 2022

AbstractWe define the empirical spectral distribution (ESD) of a random matrix polynomial with invertible leading coefficient, and we study it for complex $$n \times n$$

n
×
n

Gaussian monic matrix polynomials of degree k. We obtain exact formulae for the almost sure limit of the ESD in two distinct scenarios: (1) $$n \rightarrow \infty $$

n
→
∞

with k constant and (2) $$k \rightarrow \infty $$

k
→
∞

with n constant. The main tool for our approach is the replacement principle by Tao, Vu and Krishnapur. Along the way, we also develop some auxiliary results of potential independent interest: We slightly extend a result by Bürgisser and Cucker on the tail bound for the norm of the pseudoinverse of a nonzero mean matrix, and we obtain several estimates on the singular values of certain structured random matrices.
Understanding Conceptual Impact of Scientific Knowledge on Policy: The Role of Policymaking Conditions
Authors: Edler Jakob , Karaulova Maria , Barker Katharine 
Published: February 2022

AbstractThis paper presents a framework to understand the impact of scientific knowledge on the policy-making process, focusing on the conceptual impact. We note the continuing dissatisfaction with the quality and effects of science-policy interactions in both theory and practice. We critique the current literature’s emphasis on the efforts of scientists to generate policy impact, because it neglects the role of ‘user’ policymaking organisations. The framework offered in the paper develops an argument about the essential role of institutional conditions of policy ‘users’ for scientific knowledge to achieve impact. The framework is informed by the reflexive institutionalist and the neo-institutionalist theoretical approaches. Its main contribution is in outlining the intra- and inter-organisational conditions of policymaking organisations, along with personal characteristics of individual policy officials that influence the likelihood of scientific knowledge to generate conceptual impact. We also offer an operationalisation of the framework. The wider relevance of the paper is in moving the focus from the activities of scientists and the incentive structure in scientific organisations to the policy user side.
Volume change response and fabric evolution of granular MX80 bentonite along different hydro-mechanical stress paths
Authors: Ferrari Alessio , Bosch Jose A. , Baryla Patrycja , Rosone Marco 
Published: February 2022

AbstractDespite the increasing understanding of bentonite behaviour, there is still missing evidence on how different hydro-mechanical loadings, including sequences of hydration and compression, affect the fabric and the volume change behaviour of the material. It is generally assumed that the interplay between the behaviour of clay assemblages and the overall fabric of the material is the reason of having final states that are dependent on the stress path followed. Here the results of an experimental campaign aiming to study these factors are reported and discussed. Free swelling and swelling pressure tests were performed, both followed by compression to a relatively high stress. The experimental program involved various samples that were dismantled at intermediate states in order to perform microstructural observations by means of mercury intrusion porosimetry and electronic scanning microscopy. It was observed that while the void ratio at a given stress level depends on the stress path, subsequent compression led to a unique virgin compression line. The data obtained at the microscale gave further insight for an interpretation of the volume change behaviour observed at the macroscale, showing that at high stress the material tends to recover the same fabric regardless of the path to saturation.
Learning in a Pandemic: Primary School children’s Emotional Engagement with Remote Schooling during the spring 2020 Covid-19 Lockdown in Ireland
Authors: Chzhen Yekaterina , Symonds Jennifer , Devine Dympna , Mikolai Júlia , Harkness Susan , Sloan Seaneen , Martinez Sainz Gabriela 
Published: February 2022

AbstractThe COVID-19 pandemic resulted in the greatest disruption to children’s schooling in generations. This study analyses primary school children’s emotional engagement with remote schooling during the Spring 2020 lockdown in the Republic of Ireland, which involved one of the longest school closures among rich countries at the time. It investigates whether children’s engagement with their remote schooling varied by personal and family characteristics, using data from the Children’s School Lives (CSL) surveys. CSL is a nationally representative study of primary schools in Ireland, which collected information from children aged 8–9 years in May – August 2019 and in May – July 2020. Linear regression estimates with school fixed effects are based on the analytic sample of nearly 400 children (from across 71 schools) who took part in both waves and have complete data on all the key variables. Emotional engagement with schooling is measured using child-reported items on satisfaction with schooling. Everything else being equal, children who reported higher engagement with schooling before the pandemic were more engaged with remote schooling during the lockdown. Although there were no significant differences by family affluence, children with greater resources for home schooling reported higher levels of engagement. This includes having a computer or a laptop for schoolwork, having someone to help with schoolwork if the child is worried about falling behind, and having schoolwork checked by a teacher. This points to the paramount importance of adequate digital technologies in the home as well as the availability of help during periods of remote schooling.
Crested porcupine (Hystrix cristata) abundance estimation using Bayesian methods: first data from a highly agricultural environment in central Italy
Authors: Franchini Marcello , Viviano Andrea , Frangini Lorenzo , Filacorda Stefano , Mori Emiliano 
Published: February 2022

AbstractWildlife abundance estimation is one of the key components in conservation biology. Bayesian frameworks are widely used to adjust the potential biases derived by data collected in the field, as they can increase the precision of model parameter as a consequence of the combination of previous pieces of knowledge (priors) combined with data collected in the field to produce an a-posteriori distribution. Capture-recapture is one of the most common techniques used to assess animal abundance. However, the implementation with camera traps requires that animals present unique phenotypic traits for individual-based recognition. The crested porcupine Hystrix cristata is a semi-fossorial rodent with a continuous, but patchily distribution across Italy. Despite the species does not present evident individual-specific phenotypic traits, the information gathered using presence-only data obtained from camera traps, opportunistic observations, and road-killing events could be used to provide a rough estimate of the species abundance within an area. The main purpose of the present research was hence to provide the first preliminary estimate of the abundance of the crested porcupine in central Italy using presence-only data obtained from the above different monitoring methods. The results obtained estimated an average minimum number of 1803 individuals (SD = 26.89, CI 95% = 1750–1855) within an area covering about 17,111 km2. Since the porcupine is considered as “potentially problematic” because of damages to croplands and riverbanks, assessing its abundance is even more important to delineate adequate conservation and management actions to limit the potential trade-off effects over human activities.
Vijf jaar regionalisatie van de behandeling erectieprothese bij therapieresistente erectiele disfunctie in Nederland, de eerste uitkomsten en ervaringen
Authors: Broers Eveline , Beck Jack , Dinkelman-Smit Marij , Dohle Gert , Elzevier Henk , D’Hauwers Kathleen , Levens Wim , Meijer Boaz , Pigot Garry , Ronkes Brechje , van Uhm Janneke , Verkerk-Geelhoed Jeannette , Glas Afina 
Published: February 2022

SamenvattingSinds 2016 is de implantatie van een erectieprothese opgenomen in het basispakket voor patiënten die voldoen aan de indicatie en kwaliteitsvoorwaarden die zijn beschreven in het NVU-Standpunt. In dit artikel van de Nederlandse implanteurs zijn de data gebundeld van die eerste vijf jaar erectieprothese-implantatie. De patiënttevredenheid is met 82 % groter dan vóór 2016 en 86 % maakt daadwerkelijk gebruik van de erectieprothese. Deze getallen liggen hoger in de primaire groep dan in de re-implantatiegroep. Het risico op een ernstige complicatie is respectievelijk 5,8 en 7,5 %. Introductie van een gevalideerde PROM en intensievere samenwerking met seksuologen kunnen de patiënttevredenheid en het complicatierisico optimaliseren. Ook zal er een optimalisatie van volumes moeten komen.
A Preliminary Study of the Eye-Gaze Patterns and Reading Comprehension Skill of Students on the Autism Spectrum
Authors: Drysdale Bradley M. , Furlonger Brett E. , Anderson Angelika , Moore Dennis W. 
Published: February 2022

Abstract
Objectives

To identify, using eye-tracking technology, if readers on the autism spectrum (AS) would exhibit longer mean fixation times during question-answering but similar levels of comprehension accuracy to typically developing (TD) individuals.

Methods
The eye-gaze behavior of two school-aged autistic children and two TD children with similar reading abilities, age, gender, and grade level, was tracked while they read age-appropriate passages and answered related comprehension questions.

Results
Both participants on the AS displayed longer mean fixations than TD participants during question-answering. Despite the longer fixations during question-answering, the accuracy of the participants on the AS was equal to or superior to those of the TD participants.

Conclusions
Longer mean fixation durations during question-answering did not result in lower reading comprehension scores.
Environmental Sustainability Framework for Plastic Waste Management—a Case Study of Bubble Tea Industry in Malaysia
Authors: Lee Chie Jian , Chang Lam , Tan Jully 
Published: February 2022

Abstract
Economic growth and rapid industrialisation have led to enormous increase in municipal solid waste (MSW). Lack of waste management alternatives and ineffective waste policy implementation are the major challenges for government to materialise a sustainable solid waste management framework, especially for plastic waste. Booming of the food and beverage (F&B) industry has aggravated the situation by generating more plastic waste with no economic values. Hence, this study aims to evaluate the overall environmental performance of existing and alternative waste management technologies that are available in Malaysia based on net greenhouse gas (GHG) emission in terms of carbon dioxide equivalent (kg CO2-eq) per tonne of plastic waste that are analysed through life cycle assessment (LCA) methodology. LCA result has proven that Scenario B (waste to energy (WTE) incineration) is more environmentally preferable as it had a negative net GHG emission of − 573.80 kg CO2-eq as compared to GHG emission of existing Scenario A (sanitary landfill) of 566.15 kg CO2-eq. Negative net GHG emission in WTE incineration was mainly due to higher GHG saving achieved through cleaner electricity generation as compared to conventional power production. This alternative technology was proven to have the potential to reduce the dependence on landfills and is served as the basis of environmental sustainability framework development for plastic waste management based on case study in Malaysia. This framework can be served as the baseline for the local authorities or policy makers for other plastic waste generation hotspots other than bubble tea industry to improve plastic waste management via WTE incineration.
Biochar applications influence soil physical and chemical properties, microbial diversity, and crop productivity: a meta-analysis
Authors: Singh Hardeep , Northup Brian K. , Rice Charles W. , Prasad P. V. Vara 
Published: February 2022

AbstractBiochar is a widely known soil amendment. Here we synthesize the available information on influence of biochar application on different soil properties and crop productivity using meta-analysis. Global data on influence of biochar applications on different soil physical, chemical, microbial properties, and crop productivity were extracted from literature and statistically analyzed. Based on selection criteria, 59 studies from the literature published between 2012 and 2021 were selected for the meta-analysis. Correlations were developed between effect size of biochar application on different soil properties and crop productivity. Application of biochar increased soil pH, cation exchange capacity, and organic carbon by 46%, 20%, and 27%, respectively, with greater effects in coarse and fine-textured soils. Effects on chemical properties were variable among biochar prepared from different feedstocks. Among physical properties, biochar application reduced bulk densities by 29% and increased porosity by 59%. Biochar prepared at higher pyrolytic temperatures (> 500 ℃) improved bulk density and porosity to greater extents (31% and 66%, respectively). Biochar prepared at lower pyrolytic temperatures (< 500 ℃) had a greater effect on microbial diversity (both bacterial and fungal), with more diverse bacterial populations in medium and coarse textured soils, while fungal diversity increased in fine textured soils. Biochar applications increased crop productivity only in fine and coarse textured soil. The effect size of biochar application on crop productivity was correlated with responses to physical properties of soils. The meta-analysis highlighted the need to conduct long-term field experiments to provide better explanations for changes in biochar properties as it undergoes aging, its longer-term effects on soil properties, and timing of re-application of different biochars.
Investigation of the HelioVital filter foil revealed protective effects against UVA1 irradiation-induced DNA damage and against UVA1-induced expression of matrixmetalloproteinases (MMP) MMP1, MMP2, MMP3 and MMP15
Authors: Ivanova I. , Kurz B. , Lang K. , Maisch T. , Berneburg M. , Kamenisch Y. 
Published: February 2022

AbstractThe damaging effects of solar ultraviolet (UV) radiation exposure to human skin are well known and can reach from accelerated skin aging (photoaging) to skin cancer. Much of the damaging effects of solar UVA (320–400 nm) radiation is associated with the induction of reactive oxygen species (ROS), which are capable to cause oxidative damage to DNA like the oxidized guanosine 8-hydroxy-2' -deoxyguanosine (8-OHdG). Therefore, new UV protective strategies, have to be tested for their efficiency to shield against UV induced damage. We investigated the protective effects of HelioVital sun protection filter foil against UVA1 irradiation in skin cells. It could be shown, that HelioVital sun protection filter foil has protective effects against UVA1 irradiation induced changes in matrix metalloproteinase (MMP) expression. Furthermore a UVA1-dependant regulation of MMP15 in human fibroblasts could be shown for the first time in this context. In addition, this study demonstrated the protective effect of the HelioVital filter film against UVA1-induced ROS production and DNA damage. These results could pave the way for clinical studies with HelioVital filter foil shielding against the damaging effects of phototherapy and other forms of irradiation therapy, thereby increasing the safety and treatment opportunities of these forms of therapy.
Graphical abstract
Kirchhoff’s theorem for Prym varieties
Authors: Len Yoav , Zakharov Dmitry 
Published: February 2022

Abstract
We prove an analogue of Kirchhoff’s matrix tree theorem for computing the volume of the tropical Prym variety for double covers of metric graphs. We interpret the formula in terms of a semi-canonical decomposition of the tropical Prym variety, via a careful study of the tropical Abel–Prym map. In particular, we show that the map is harmonic, determine its degree at every cell of the decomposition and prove that its global degree is

$2^{g-1}$

. Along the way, we use the Ihara zeta function to provide a new proof of the analogous result for finite graphs. As a counterpart, the appendix by Sebastian Casalaina-Martin shows that the degree of the algebraic Abel–Prym map is

$2^{g-1}$

as well.
Marine Target Extraction Based on Adjoint Covariance Correction Model
Authors: Lin Liu , Jixian Zhang , Wanwu Li , Qiaoli Sui 
Published: February 2022

AbstractConstant False‐Alarm Rate (CFAR) algorithm is a mature method in marine target detection at present, the key of which is the choice of probability model. The most classical probability model is Gaussian distribution, which is suitable for modeling the calm ocean surface. Complex ocean conditions generally do not obey to Gaussian distribution, which limits the performance of CFAR algorithm. Therefore, we propose Adjoint Covariance Correction Model (ACCM) to improve the performance of CFAR marine target detection. Analyzing the distribution characteristic of ocean clutter under complex ocean conditions based on experiments, we find that it has long‐tail characteristic. Aiming at this characteristic, we have conducted fitting experiment on 23 kinds of probability density functions (PDFs) and find Loglogistic distribution has a better fitting effect on long‐tail characteristic, therefore, we use it to model ocean clutter under complex ocean conditions for the first time. In order to further improve the fitting goodness, we add a variance correction term to the Loglogistic model to construct ACCM for marine target extraction. The experiment result shows that ACCM effectively fits the long‐tail characteristic caused by Synthetic Aperture Radar backscatter under complex ocean conditions. The goodness of fit improves by 50% compared with Loglogistic model, and the amount of false alarms is 81.42% of that of Loglogistic model. The extraction accuracy of marine target characteristic parameter based on ACCM is 11.58% higher than that of Loglogistic model, and 12.18% higher than that of two‐parameter CFAR model based on standard error function (named SEF‐CFAR).
Large South Equatorial Current Meander in the Southeastern Tropical Indian Ocean Captured by Surface Drifters Deployed in 2019
Authors: Wu Wei , Du Yan , Qian Yu‐Kun , Chen Ju , Jiang Xingwei 
Published: February 2022

AbstractTo investigate the South Equatorial Current (SEC) in the Indian Ocean, 18 drifters were deployed off Sumatra‐Java during boreal spring 2019. These drifter observations revealed a large SEC meander that swung southward about 1,100 km during 40 days along ∼100°E. The southward motion occurred on the eastern edge of the Seychelles‐Chagos thermocline ridge, accompanied by an anticyclonic eddy/Rossby wave from the east, indicated by the geostrophic velocity induced by the zonal pressure gradient. Meanwhile, the ageostrophic velocity induced by the southeasterly wind also contributes to this southward motion. This is verified by a Lagrangian Trajectory Model in which drifter trajectories are well reproduced using Chinese‐French Oceanic SATellite winds products. Further analysis of the historical drifters with similar trajectories reveals that the geostrophic and ageostrophic currents jointly drive drifters to move southward. Ageostrophic component could contribute up to 45% of the southward movement of the SEC meander.