bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinetic Models for Epidemic Dynamics in the Presence of Opinion Polarization
Authors: Zanella Mattia 
Published: March 2023

AbstractUnderstanding the impact of collective social phenomena in epidemic dynamics is a crucial task to effectively contain the disease spread. In this work, we build a mathematical description for assessing the interplay between opinion polarization and the evolution of a disease. The proposed kinetic approach describes the evolution of aggregate quantities characterizing the agents belonging to epidemiologically relevant states and will show that the spread of the disease is closely related to consensus dynamics distribution in which opinion polarization may emerge. In the present modelling framework, microscopic consensus formation dynamics can be linked to macroscopic epidemic trends to trigger the collective adherence to protective measures. We conduct numerical investigations which confirm the ability of the model to describe different phenomena related to the spread of an epidemic.
Effects of Age of In Vitro-Derived Potato Plantlets on Early Above- and Below-Ground Development After Planting in Different Cultivars
Authors: Lommen W. J. M. 
Published: March 2023

AbstractIn vitro-propagated potato plantlets are commonly used in potato seed tuber production. Four experiments were carried out to identify how the duration of the last in vitro phase (‘age’) before planting of in vitro-produced plantlets affects the early growth and development ex vitro, assessed 10–14 days after planting. Experiments included varying ranges in age of the in vitro plantlets at planting (10–40, 15–45, 14–28 and 14–56 days old at the moment of planting in the respective experiments) and different cultivars. Because in vitro plantlet size increases with age, the first experiment studied interactions between age and planting method. Planting ‘deep’ (the upper four visible leaves above the ground) seemed more robust than planting ‘shallow’ (all nodes/leaves above ground except the lowest two), and in later experiments, only deep planting was applied. Across experiments, plants grown from younger in vitro plantlets had smaller leaf areas 10–14 days after planting than those from older in vitro plantlets. The increase in leaf area levelled off with increasing age of the in vitro plantlets used, especially when plantlets were older than c. 28 days. Larger leaf areas 10–14 days after planting were related to the older in vitro plantlets having higher absolute growth rates after planting and a larger above-ground leaf area at planting, even though four leaves were kept above ground in all treatments. Below ground, plants from older in vitro plantlets had more stem nodes, initiated stolons earlier after planting and initiated more stolons per plant. Tuber initiation rarely occurred within 14 days after planting, but was observed in some plants from 42- and especially 56-day-old in vitro plantlets of the very early cultivar Gloria and a single plant from 56-day-old in vitro plantlets of the mid-early cultivar Bintje. The data show that planting older in vitro plantlets can enhance early leaf area growth. Plants from older in vitro plantlets also more readily initiate stolons below ground and may be more advanced in the tuber formation process, especially when from early cultivars.
Autoinflammatory diseases and the kidney
Authors: Hegazy Mohamed Tharwat , Fayed Ahmed , Nuzzolese Rossana , Sota Jurgen , Ragab Gaafar 
Published: March 2023

AbstractThe kidney represents an important target of systemic inflammation. Its involvement in monogenic and multifactorial autoinflammatory diseases (AIDs) vary from peculiar and relatively frequent manifestations to some rare but severe features that may end up requiring transplantation. The pathogenetic background is also very heterogeneous ranging from amyloidosis to non-amyloid related damage rooted in inflammasome activation. Kidney involvement in monogenic and polygenic AIDs may present as renal amyloidosis, IgA nephropathy, and more rarely as various forms of glomerulonephritis (GN), namely segmental glomerulosclerosis, collapsing glomerulopathy, fibrillar, or membranoproliferative GN. Vascular disorders such as thrombosis or renal aneurysms and pseudoaneurysms may be encountered in patients with Behcet’s disease. Patients with AIDs should be routinely assessed for renal involvement. Screening with urinalysis, serum creatinine, 24-h urinary protein, microhematuria, and imaging studies should be carried out for early diagnosis. Awareness of drug-induced nephrotoxicity, drug-drug interactions as well as addressing the issue of proper renal adjustment of drug doses deserve a special mention and should always be considered when dealing with patients affected by AIDs. Finally, we will explore the role of IL-1 inhibitors in AIDs patients with renal involvement. Targeting IL-1 may indeed have the potential to successfully manage kidney disease and improve long-term prognosis of AIDs patients.
The Fragile X Protein Family in Amyotrophic Lateral Sclerosis
Authors: Mueller Sarah , Decker Lorena , Menge Sonja , Ludolph Albert C. , Freischmidt Axel 
Published: March 2023

AbstractThe fragile X protein (FXP) family comprises the multifunctional RNA-binding proteins FMR1, FXR1, and FXR2 that play an important role in RNA metabolism and regulation of translation, but also in DNA damage and cellular stress responses, mitochondrial organization, and more. FMR1 is well known for its implication in neurodevelopmental diseases. Recent evidence suggests substantial contribution of this protein family to amyotrophic lateral sclerosis (ALS) pathogenesis. ALS is a highly heterogeneous neurodegenerative disease with multiple genetic and unclear environmental causes and very limited treatment options. The loss of motoneurons in ALS is still poorly understood, especially because pathogenic mechanisms are often restricted to patients with mutations in specific causative genes. Identification of converging disease mechanisms evident in most patients and suitable for therapeutic intervention is therefore of high importance. Recently, deregulation of the FXPs has been linked to pathogenic processes in different types of ALS. Strikingly, in many cases, available data points towards loss of expression and/or function of the FXPs early in the disease, or even at the presymptomatic state. In this review, we briefly introduce the FXPs and summarize available data about these proteins in ALS. This includes their relation to TDP-43, FUS, and ALS-related miRNAs, as well as their possible contribution to pathogenic protein aggregation and defective RNA editing. Furthermore, open questions that need to be addressed before definitively judging suitability of these proteins as novel therapeutic targets are discussed.
Improved prehospital triage for acute cardiac care: results from HART-c, a multicentre prospective study
Authors: de Koning Enrico R. , Beeres Saskia L. M. A. , Bosch Jan , Backus Barbra E. , Tietge Wouter J. , Alizadeh Dehnavi Reza , Groenwold Rolf H. H. , Silvius Allena M. , van Lierop Pepijn T. S. , Jukema J. Wouter , Schalij Martin J. , Boogers Mark J. 
Published: March 2023

Abstract
Background
Cardiac symptoms are one of the most prevalent reasons for emergency department visits. However, over 80% of patients with such symptoms are sent home after acute cardiovascular disease has been ruled out.

Objective
The Hollands-Midden Acute Regional Triage—cardiology (HART-c) study aimed to investigate whether a novel prehospital triage method, combining prehospital and hospital data with expert consultation, could increase the number of patients who could safely stay at home after emergency medical service (EMS) consultation.

Methods
The triage method combined prehospital EMS data, such as electrocardiographic and vital parameters in real time, and data from regional hospitals (including previous medical records and admission capacity) with expert consultation. During the 6‑month intervention and control periods 1536 and 1376 patients, respectively, were consulted by the EMS. The primary endpoint was the percentage change of patients who could stay at home after EMS consultation.

Results
The novel triage method led to a significant increase in patients who could safely stay at home, 11.8% in the intervention group versus 5.9% in the control group: odds ratio 2.31 (95% confidence interval (CI) 1.74–3.05). Of 181 patients staying at home, only 1 (< 1%) was later diagnosed with ACS; no patients died. Furthermore the number of interhospital transfers decreased: relative risk 0.81 (95% CI 0.67–0.97).

Conclusion
The HART‑c triage method led to a significant decrease in interhospital transfers and an increase in patients with cardiac symptoms who could safely stay at home. The presented method thereby reduced overcrowding and, if implemented throughout the country and for other medical specialties, could potentially reduce the number of cardiac and non-cardiac hospital visits even further.
The information-theoretic view of quantum mechanics and the measurement problem(s)
Authors: Laudisa Federico 
Published: March 2023

AbstractUntil recently Jeffrey Bub and Itamar Pitowsky, in the framework of an information-theoretic view of quantum mechanics, claimed first that to the measurement problem in its ordinary formulation there correspond in effect two measurement problems (simply called the big and the small measurement problems), with a different degree of relevance and, second, that the analysis of a quantum measurement is a problem only if other assumptions – taken by Pitowsky and Bub to be unnecessary ‘dogmas’ – are assumed. Here I critically discuss this unconventional stance on the measurement problem and argue that the Bub-Pitowsky arguments are inconclusive, mainly because they rely on an unwarranted extension to the quantum realm of a distinction concerning the foundations of special relativity which is in itself rather controversial.
Bias Mitigation for Capturing Potentially Illegal Hate Speech
Authors: Schäfer Johannes 
Published: March 2023

AbstractHate speech is a persistent issue in social media. Researchers have analyzed and developed detection methods for hate speech on the basis of example data, even though the phenomenon is only rather vaguely defined. This paper provides an approach to identify hate speech in terms of German laws, which are used as a basis for annotation guidelines applied to real world data. We annotate six labels in a corpus of 1,385 German short text messages: four subcategories of illegal hate speech, offensive language and a neutral class. We consider hate speech expressions as illegal if the linguistic content could be interpreted in a given context possibly violating a specific law. This interpretation and a check by lawyers would be the next step which is not yet included in our annotation. In this paper, I report on strategies to avoid certain biases in data for illegal hate speech. These strategies may serve as a model for building a larger dataset. In experiments, I investigate the capability of a Transformer-based neural network model to learn our classification. The results show that this multiclass classification is still difficult to learn, probably due to the small size of the dataset. I suggest that it is crucial to be aware of data biases and to apply bias mitigation techniques when training hate speech detection systems on such data. Data and scripts of the experiments are made publicly available.
Evolution, Investment, and Bargaining
Authors: Robles Jack 
Published: March 2023

AbstractWe present an evolutionary model which allows us to study the impact relationship-specific investment has on bargaining. Agents are matched to play an investment and bargaining game. During bargaining, agents have an outside option to form a new relationship, but in exercising this option loses their current investment. We find that the stochastically stable post-investment bargaining convention is dependent on the cost of investment. In particular, the larger the cost of investment, the lower is the share of gross surplus that is received. This stands in contrast with previous studies. In addition, we find that there is under-investment. We disentangle the forces which lead to these two results.
Strategies to improve swine manure hydrochar: HCl-assisted hydrothermal carbonization versus hydrochar washing
Authors: Ipiales Ricardo Paul , Sarrion Andres , Diaz Elena , Diaz-Portuondo Emiliano , Mohedano Angel F. , de la Rubia Angeles 
Published: March 2023

AbstractThe work focuses on the study of hydrochar upgrading from hydrothermal carbonization (HTC) of swine manure by HCl-assisted HTC or washing with HCl or acetone, as a post-treatment to conventional HTC. Conventional HTC of swine manure yields a low-quality hydrochar (C content ~ 38 wt.%, higher heating value (HHV) ~ 15 MJ kg−1, and ash content up to 32 wt.%). HCl-assisted HTC (0.5 M HCl at 230 ℃) substantially reduced the ash content up to ~10 wt.% in the hydrochar and increased the C content to 58 wt.%, reaching a HHV of 23 MJ kg−1. However, the N and S contents remained at values similar to those of the swine manure. Washing post-treatment of conventional hydrochars with HCl or acetone significantly improved the C content and the HHV in the range 47–58 wt.% and 19–25 MJ kg−1, respectively, as well as the ash removal with values 7-11 wt.%. Washing the hydrochar with acetone significantly reduced the N and S contents, obtaining a carbonaceous material with properties suitable for solid biofuel according to ISO/TS 17225–8, (N < 3 wt.%; S < 0.15 wt.%; HHV > 17 MJ kg−1; and ash < 10 wt.%). Hydrochars obtained by HCl-assisted HTC and HCl/acetone washing post-treatment yielded higher thermal stability, as well as better reactivity and low ash agglomeration indexes than compared to conventional hydrochars. Washing post-treatment with acetone proved to be the best strategy to obtain improved hydrochars from swine manure for industrial use as a solid biofuel.
Connecting Sunken Actors: Social Network Analysis in Maritime Archaeology
Authors: Aragon Enrique 
Published: March 2023

AbstractThe concept of a “social network” has become a popular term thanks to online tools such as Facebook or Twitter, allowing us to connect with everyone. Specific to archaeology, social network analysis (SNA) is well established as a method, but its theoretical application in maritime archaeology is an incipient initiative. This paper presents the use of SNA in maritime archaeology as a potential instrument to reinterpret underwater sites by integrating spatial and nonspatial patterns of cultural contact. The method implies an abstraction of an historical phenomenon in concepts of network analysis to be represented as network data. Using early Australian shipwrecks as examples, this paper shows how the application of SNA in maritime archaeological contexts can help to analyze and visualize flow of material goods, power, influence, and social control. As a result, it can be argued that exploring the structural position of actors in a network can reveal information about developing relationships in maritime contexts during the past.
Digitalisierung christlicher Verkündigungsformate während der Covid19-Pandemie: Empirische Befunde und theoretische Systematisierungen aus religionswissenschaftlicher Perspektive
Authors: Neumaier Anna 
Published: March 2023

ZusammenfassungMit den Kontaktbeschränkungen zu Beginn der Covid19-Pandemie mussten auch religiöse Institutionen geradezu über Nacht ihre bisherigen Angebote neu denken. Gerade für Gottesdienste sind dabei häufig digitale Alternativen entwickelt worden. Der Aufsatz beleuchtet dieses emergierende Feld der Digitalisierung christlicher Verkündigungsformate und die Anschlussstellen zu bestehender religionswissenschaftlicher Forschung zu Religion und digitalen Medien. Dafür wird zunächst ein empirisch orientierter Überblick über die Digitalisierungsbemühungen der christlichen Kirchen im deutschsprachigen Raum unter Corona-Bedingungen gegeben, insbesondere unter Rückgriff auf die bisher vorliegenden statistischen Erhebungen. Auf der Grundlage qualitativer Interviews wird dann der Blick auf die Rezipient*innenperspektive auf digitale Gottesdienste gerichtet. Diese empirischen Befunde werden schließlich in Verbindung gesetzt zu bestehenden systematischen Querschnittsthemen der Forschung zu Religion und Medien, insbesondere zu den Konsequenzen digitalisierter religiöser Kommunikation für Formen religiöser Vergemeinschaftung, Raum und Ritual sowie die Selbstermächtigung religiöser Lai*innen und den Wandel religiöser Autorität. Der Aufsatz will damit auf empirischer Grundlage eine Einordnung der gegenwärtigen, Corona-induzierten Entwicklungen in den bestehenden Forschungsstand anbieten und Anschlussüberlegungen aufzeigen.
Chinese GI Schizophrenia: Impacts of EU-US GI Contestations
Authors: Cheng Wenting 
Published: March 2023

AbstractGeographical Indications (GIs) have been a ‘must-have’ element for EU FTAs in the last decade. Contemporaneously, the USA has contested these EU GI provisions in its own FTAs often with the same countries. The impacts of the EU-US contestation on GIs on a third country are not sufficiently understood. China has been a long-standing example of the EU-US GI contestation. This article examines how the competing demands of EU-US GI contestation have contributed to the ‘Chinese GI Schizophrenia’, which features triplicate GI protection mechanisms coexisting simultaneously and independently. It discusses how the symptom has developed when China was navigating GI regulations bilaterally and multilaterally in the last four decades, how China has made efforts to manage this schizophrenia through institutional integration, and how recent agreements with the EU and the USA respectively further worsened the situation. Using the case of Chinese GI Schizophrenia, this article warns of similar consequences for any country signing bilateral GI agreements with both the EU and the USA: a compliance dilemma that can ultimately cast doubts on the legitimacy of GI rules and create rule complexity that can bring enormous uncertainty to agri-food producers and exporters.
The problem of varying annotations to identify abusive language in social media content
Authors: Seemann Nina , Lee Yeong Su , Höllig Julian , Geierhos Michaela 
Published: March 2023

AbstractWith the increase of user-generated content on social media, the detection of abusive language has become crucial and is therefore reflected in several shared tasks that have been performed in recent years. The development of automatic detection systems is desirable, and the classification of abusive social media content can be solved with the help of machine learning. The basis for successful development of machine learning models is the availability of consistently labeled training data. But a diversity of terms and definitions of abusive language is a crucial barrier. In this work, we analyze a total of nine datasets—five English and four German datasets—designed for detecting abusive online content. We provide a detailed description of the datasets, that is, for which tasks the dataset was created, how the data were collected, and its annotation guidelines. Our analysis shows that there is no standard definition of abusive language, which often leads to inconsistent annotations. As a consequence, it is difficult to draw cross-domain conclusions, share datasets, or use models for other abusive social media language tasks. Furthermore, our manual inspection of a random sample of each dataset revealed controversial examples. We highlight challenges in data annotation by discussing those examples, and present common problems in the annotation process, such as contradictory annotations and missing context information. Finally, to complement our theoretical work, we conduct generalization experiments on three German datasets.
Do 20-minute neighbourhoods moderate associations between work and commute hours with food consumption?
Authors: Oostenbach Laura Helena , Lamb Karen Elaine , Crawford David , Timperio Anna , Thornton Lukar Ezra 
Published: March 2023

AbstractObjective:To examine associations between work and commute hours with food consumption and test whether neighbourhood type (20-minute neighbourhood (20MN)/non-20MN) moderate associations.Design:Cross-sectional analysis of the Places and Locations for Activity and Nutrition study (ProjectPLAN). Exposures were work hours (not working (0 h), working up to full-time (1–38 h/week), working overtime (> 38 h/week)), and among those employed, combined weekly work and commute hours (continuous). Outcomes were usual consumption of fruit, vegetables, takeaway food, snacks and soft drinks, and number of discretionary food types (takeaway, snacks and soft drinks) consumed weekly. Generalised linear models were fitted to examine associations between each exposure and outcome. The moderating role of neighbourhood type was examined through interaction terms between each exposure and neighbourhood type (20MN/non-20MN).Setting:Melbourne and Adelaide, Australia, 2018–2019.Participants:Adults ≥ 18 years old (n 769).Results:Although all confidence intervals contained the null, overall, patterns suggested non-workers and overtime workers have less healthy food behaviours than up-to-full-time workers. Among those employed, analysis of continuous work and commute hours data suggested longer work and commute hours were positively associated with takeaway consumption (OR = 1·014, 95 % CI 0·999, 1·030, P-value = 0·066). Patterns of better behaviours were observed across most outcomes for those in 20MN than non-20MN. However, differences in associations between work and commute hours with food consumption across neighbourhood type were negligible.Conclusions:Longer work and commute hours may induce poorer food behaviours. There was weak evidence to suggest 20MN moderate associations between work and commute hours with food consumption, although behaviours appeared healthier for those in 20MN.
On Bayesian credibility mean for finite mixture distributions
Authors: Jahanbani Ehsan , Payandeh Najafabadi Amir T. , Masoumifard Khaled 
Published: March 2023

AbstractConsider the problem of determining the Bayesian credibility mean$E(X_{n+1}|X_1,\cdots, X_n),$whenever the random claims$X_1,\cdots, X_n,$given parameter vector$\boldsymbol{\Psi},$are sampled from the K-component mixture family of distributions, whose members are the union of different families of distributions. This article begins by deriving a recursive formula for such a Bayesian credibility mean. Moreover, under the assumption that using additional information$Z_{i,1},\cdots,Z_{i,m},$one may probabilistically determine a random claim$X_i$belongs to a given population (or a distribution), the above recursive formula simplifies to an exact Bayesian credibility mean whenever all components of the mixture distribution belong to the exponential families of distributions. For a situation where a 2-component mixture family of distributions is an appropriate choice for data modelling, using the logistic regression model, it shows that: how one may employ such additional information to derive the Bayesian credibility model, say Logistic Regression Credibility model, for a finite mixture of distributions. A comparison between the Logistic Regression Credibility (LRC) model and its competitor, the Regression Tree Credibility (RTC) model, has been given. More precisely, it shows that under the squared error loss function, it shows the LRC’s risk function dominates the RTC’s risk function at least in an interval which about$0.5.$Several examples have been given to illustrate the practical application of our findings.