bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of chemical characteristics of engine‐oil‐based Prandtl hybrid nanofluid flow
Authors: Awan Aziz Ullah , Qayyum Sidra , Nadeem Sohail , Ahammad N. Ameer , Gepreel Khaled A. , Alharthi Mohammed , Alosaimi Moataz 
Published: July 2024

AbstractThe literature showed that an empirical experiment creates another part of exploration that has been made in the field of thermal science, such that today, modern researchers are more directed to utilize hybrid types of nanoparticles due to their efficient thermal conductivity compared to single nanoparticles. The study of the hybrid flow of nanofluid is essential in many scientific and industrial arguments, such as power generation, medical equipment, oil refineries, and so forth. Furthermore, it has distinctive features to advance the expertise of their energy sources and cooling methodologies. Incentives by this research postulation: The significant objective of this investigation is to design a mathematical model of Prandtl hybrid nano liquid flow over a Riga plate when nanoparticles of aluminum alloys (AA7072 and AA7075) are suspended in engine oil. Mixed convection, activation energy, and heat radiation are also considered. The nanomaterial is modeled using a modified Buongiorno model that considers the functional qualities of hybrid nanofluids. The simulated PDEs are converted into a collection of nonlinear ODEs with appropriate and relevant similarity transformations, which are numerically addressed using finite‐difference‐oriented bvp4c procedure in MATLAB. Graphs and tables are used to evaluate and show the impacts of different factors on velocity, temperature, concentration fields, skin friction number, and Nusselt number. The velocity profile develops with the enhancement of Prandtl fluid parameters. With the increment in the magnetic parameter, both temperature and concentration profiles improve, but in the case of the Brownian motion parameter, the concentration profile declines. In terms of heat transfer, hybrid nanofluids outperform ordinary nanofluids. The current results provide an equitable contrast against the results that already exist.
Empires of the Mind
Authors: Lopes Carlos 
Published: July 2024

AbstractThe colonial experience has profoundly marked both Europe and Africa, the coloniser and the colonised. From the start of the scramble for Africa in the fifteenth century, African culture, language, identity, and agency have been systematically minimised and discounted while European supremacy has been amplified. This has set a tone that has persisted as the two struggle to achieve an equitable partnership. To this day, the language used by African and European leaders, writers, and influencers reflects that many are trapped in an outdated worldview that masks the true colonial legacy.It takes conscious work to do away with the heavy presence of colonial narratives and perceptions. This chapter reviews the works of many scholars who have attempted to do just this. From seminal books such as Born in Blackness (French, Born in Blackness: Africa, Africans, and the Making of the Modern World, 1471 to the Second World War, 2021), African Europeans (Otele, African European: An Untold History, 2020), and The EU and Africa (Adebajo & Whiteman, 2012) to others that frame the discussion in terms of the historical reasons for continuity in the stigmatisation of Africa, this chapter seeks to capture some of the critical insights of those who can help us construct a new narrative. Frantz Fanon’s and Amilcar Cabral’s theories on decolonising minds are also mentioned. Additionally, references to the current post-colonial academic debates are included.
A Survey of Mathematical Modeling of Hormonal Contraception and the Menstrual Cycle
Authors: Zhao Lihong , Kim Ruby , Oremland Lucy S. , Chowkwale Mukti , Pillis Lisette G. de , Brooks Heather Z. 
Published: July 2024

AbstractIn this survey, we review the current state of the art in mathematical modeling of the menstrual cycle. We compare and contrast different modeling choices and the benefits and limitations of various models. We investigate the sensitivity of these models to variations in parameter values, highlighting that these models display particular sensitivity to the growth rate of the reserve pool of follicular stimulating hormone. We also describe the incorporation of time delays in the model equations and discuss the ways in which these delays reflect the biological system and impact the dynamics. We explore the qualitative effects that introducing exogenous hormones into these models plays on inducing a contraceptive state. Through our comparative study of these models, we are able to highlight important areas of future work in the mathematical modeling of hormonal contraception and the menstrual cycle.
Deconstructing the Contributions of Heterogeneity to Combination Treatment of Hormone-Sensitive Breast Cancer
Authors: Linn Samantha , Moore-Ott Jenna A. , Shuttleworth Robyn , Zhang Wenjing , Craig Morgan , Jenner Adrianne L. 
Published: July 2024

AbstractCombination therapies are fundamental to cancer treatments, including in breast cancer, which is the most common invasive malignancy in women. Breast cancer treatment is determined based on molecular subtypes. Since 2016, combination palbociclib and fulvestrant has been used to treat hormone receptor-positive breast cancer. However, the impact of heterogeneity of the tumor landscape and tumor composition dynamics on scheduling decisions remains poorly understood. To elucidate the contributions of variability at multiple scales to treatment outcomes in hormone receptor-positive breast cancer, we developed a simple mathematical model of two unique estrogen receptor-positive (ER$$+$$
+
) breast cancer cell types and their responses to combination treatment with palbociclib and fulvestrant. We used this model to understand how the initial fraction of either cell type may impact the fraction remaining after treatment and examined how heterogeneity in pharmacokinetics and pharmacodynamics results in a large distribution of outcomes. Our results suggest that the pharmacokinetics and pharmacodynamics of fulvestrant were the major drivers of final tumor size and composition. We then leveraged our model to guide therapeutic scheduling of combination palbociclib and fulvestrant, demonstrating the use of mathematical modeling to improve our understanding of cancer biology and treatments.
Argumentation-Based Probabilistic Causal Reasoning
Authors: Bengel Lars , Blümel Lydia , Rienstra Tjitze , Thimm Matthias 
Published: July 2024

AbstractWe introduce an argumentation-based approach for conducting probabilistic causal reasoning. For that, we consider Pearl’s causal models where causal relations are modelled via structural equations and a probability distribution over background atoms. The probability that some causal statement holds is then computed by constructing a probabilistic argumentation framework and determining its extensions. This framework can then be used to generate argumentative explanations for the (non-)acceptance of the causal statement. Furthermore, we present an argumentation-based version of the twin network method for dealing with counterfactuals. Finally, we show that our approach yields the same results for causal and counterfactual queries as Pearl’s model.
From Networks to Narratives: Bayes Nets and the Problems of Argumentation
Authors: Keshmirian Anita , Fuchs Rafael , Cao Yuan , Hartmann Stephan , Hahn Ulrike 
Published: July 2024

AbstractBayesian Belief Networks (BBNs) are gaining traction in practical fields such as law and medicine. Given this growing relevance, it is imperative to make Bayesian methodologies accessible to professionals in these fields, many of whom might lack formal training in probability calculus. Argumentation offers a promising avenue to achieve this. It serves a dual purpose: (i) generating an explanation of the important reasoning steps that occur in Bayesian inference and (ii) exploring the structure of complex problems, which can help to elicit a BBN representation. Since Bayesian probabilistic inference also provides clear normative criteria for argument quality, there is a tight conceptual connection between the argumentative structure of a problem and its representation as a BBN. The primary challenge is representing the argumentative structure that renders BBN inference transparent to non-experts. Here, we examine algorithmic approaches to extract argument structures from BBNs. We critically review three algorithms - each distinguished by its unique methodology in extracting and evaluating arguments. We show why these algorithms still fall short when it comes to elucidating intricate features of BBNs, such as “explaining away” [44] or other complex interactions between variables. We conclude by diagnosing the core issue and offering a forward-looking suggestion for enhancing representation in future endeavors.
Enhancing Argument Generation Using Bayesian Networks
Authors: Cao Yuan , Fuchs Rafael , Keshmirian Anita 
Published: July 2024

AbstractIn this paper, we examine algorithms that utilize factor graphs from Bayesian Belief Networks to generate and evaluate arguments. We assess their strengths and weaknesses, which leads to the creation of our improved algorithm that rectifies the issues that we identified. Our approach includes applying the original and modified algorithms to previously known networks to pose challenges in generating robust arguments for humans and computers. Our findings reveal significant improvements in the creation of more robust arguments. Moreover, we delve into the dynamics of argument interaction, offering detailed insight into the algorithms’ practical efficacy.
Are Large Language Models Reliable Argument Quality Annotators?
Authors: Mirzakhmedova Nailia , Gohsen Marcel , Chang Chia Hao , Stein Benno 
Published: July 2024

AbstractEvaluating the quality of arguments is a crucial aspect of any system leveraging argument mining. However, it is a challenge to obtain reliable and consistent annotations regarding argument quality, as this usually requires domain-specific expertise of the annotators. Even among experts, the assessment of argument quality is often inconsistent due to the inherent subjectivity of this task. In this paper, we study the potential of using state-of-the-art large language models (LLMs) as proxies for argument quality annotators. To assess the capability of LLMs in this regard, we analyze the agreement between model, human expert, and human novice annotators based on an established taxonomy of argument quality dimensions. Our findings highlight that LLMs can produce consistent annotations, with a moderately high agreement with human experts across most of the quality dimensions. Moreover, we show that using LLMs as additional annotators can significantly improve the agreement between annotators. These results suggest that LLMs can serve as a valuable tool for automated argument quality assessment, thus streamlining and accelerating the evaluation of large argument datasets .
The Impact of Argument Arrangement on Essay Scoring
Authors: Knaebel René , Schaefer Robin , Stede Manfred 
Published: July 2024

AbstractWe study the question to what extent the task of predicting the quality of student essays can be supported with computing “flows” of semantic types of argumentative units. Specifically, we use tagsets for claim and premise types that were recently applied to the Argument Annotated Essays corpus (AAE; Stab/Gurevych 2017) by Schaefer et al (2023). We train argument component and semantic type classification models on AAE and then use them to label the essays in two corpora that have numeric essay ratings, viz. FEEDBACK/PERSUADE and ICLE. We train linear classification models on flow features and find that flows of our semantic types are a better predictor for essay quality (in a simplified, good/bad dichotomy) than flows of coarse argument components (major claim, claim, premise). Finally, we calculate feature impact and perform a qualitative inspection, which shows some tendencies for pattern occurrence in the two essay classes.
Incoherent diffractive dijet production and gluon Bose enhancement in the nuclear wave function
Authors: Kar Tiyasa , Kovner Alexander , Li Ming , Skokov Vladimir V. 
Published: July 2024

Abstract
We investigate the effect of gluon Bose enhancement in the nuclear wave function on the dijet production in incoherent diffractive processes in DIS and ultraperipheral collisions. We demonstrate that Bose enhancement leads to an enhancement of diffractive dijet production cross section when the transverse momenta of the two jets are aligned at zero relative angle. This enhancement is maximal when the magnitude of the transverse momenta of the two jets are equal, and disappears rather quickly as a function of the ratio of the two momenta. We study both the dilute limit and fully nonlinear dense regime where the nuclear wave function is evolved with the leading order JIMWLK equation. In both cases we observe a visible effect, with it being enhanced by the evolution due to the dynamical generation of the color neutralization scale.
Comparison of fatalities due to COVID-19 and other nonexternal causes during the first five pandemic waves
Authors: Buschner Andrea , Katz Katharina , Beyerlein Andreas 
Published: July 2024

Abstract
Background
Older age is a risk factor for a fatal course of SARS-CoV‑2 infection, possibly due to comorbidities whose exact role in this context, however, is not yet well understood. In this paper, the characteristics and comorbidities of persons who had died of COVID-19 in Bavaria by July 2022 are shown and compared with the characteristics of other fatalities during the pandemic.

Methods
Based on data from multiple cause of death statistics, odds ratios for dying from COVID-19 (compared to dying from other nonexternal causes of death) were calculated by using logistic regression models, stratified by age, sex, and pandemic waves.

Results
In Bavaria, a total of 24,479 persons (6.5% of all deaths) officially died from COVID-19 between March 2020 and July 2022. In addition to increasing age and male sex, preexisting diseases and comorbidities such as obesity, degenerative diseases of the nervous system, dementia, renal insufficiency, chronic lower respiratory diseases, and diabetes mellitus were significantly associated with COVID-19–related deaths. Dementia was mainly associated with increased COVID-19 mortality during the first and second waves, while obesity was strongly associated during the fourth wave.

Discussion
The frequency of specific comorbidities in COVID-19 deaths varied over the course of the pandemic. This suggests that wave-specific results also need to be interpreted against the background of circulating virus variants, changing immunisation levels, and nonpharmaceutical interventions in place at the time.
Time to bury the chisel: a continuous dorsal association tract system
Authors: van den Hoven Emiel , Reisert Marco , Musso Mariacristina , Glauche Volkmar , Rijntjes Michel , Weiller Cornelius 
Published: July 2024

AbstractThe arcuate fasciculus may be subdivided into a tract directly connecting frontal and temporal lobes and a pair of indirect subtracts in which the fronto-temporal connection is mediated by connections to the inferior parietal lobe. This tripartition has been advanced as an improvement over the centuries-old consensus that the lateral dorsal association fibers form a continuous system with no discernible discrete parts. Moreover, it has been used as the anatomical basis for functional hypotheses regarding linguistic abilities. Ex hypothesi, damage to the indirect subtracts leads to deficits in the repetition of multi-word sequences, whereas damage to the direct subtract leads to deficits in the immediate reproduction of single multisyllabic words. We argue that this partitioning of the dorsal association tract system enjoys no special anatomical status, and the search for the anatomical substrates of linguistic abilities should not be constrained by it. Instead, the merit of any postulated partitioning should primarily be judged on the basis of whether it enlightens or obfuscates our understanding of the behavior of patients in which individual subtracts are damaged.
Sex-related variability of white matter tracts in the whole HCP cohort
Authors: Herlin B. , Uszynski I. , Chauvel M. , Dupont S. , Poupon C. 
Published: July 2024

AbstractBehavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22–35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10–19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition.
New thermal insulating polyurethane biofoams based on cherry seed oil
Authors: Malewska Elżbieta , Pulit-Prociak Jolanta , Zielina Michał , Matyjasik Wiktoria , Hodacka Gabriela , Prociak Tomasz , Banach Marcin , Kurańska Maria , Prociak Aleksander 
Published: July 2024

AbstractCherry fruits were used in clean technologies for preparation of hydroxyl components applied in polyurethane foams. Polyphenols from cherry fruits helped to obtain a stable suspension of nanosilver particles dispersed in diethylene glycol, while cherry seeds constituted a renewable source of oil, which was transesterified into biopolyol. Such biocomponents containing nanosilver particles were applied to obtain open cell heat insulating polyurethane foams resistant to a fungus strain Candida albicans. The influence of nanosilver concentration in diethylene glycol, reaction temperature, and catalyst concentration on the biopolyols and the properties of the final foams were subjected to a statistical analysis. It was found that the following process conditions were crucial in obtaining the most desired foams (in terms of their physical and mechanical properties): the catalyst content—0.225%, the concentration of DEG with nanoAg—25%, temperature—188 °C. Such an approach allowed us to obtain open cell polyurethane foams in line with Green Chemistry rules.
Graphical abstract
Upgrading low-concentration oxygen-bearing coal bed methane by dual-reflux vacuum swing adsorption
Authors: Guo Yalou , Hu Guoping , Liu Liying , Wang Jian , Webley Paul A. , Li Gang Kevin 
Published: July 2024

AbstractFugitive methane (CH4) is a typical by-product of mining processes, which is commonly known as coal bed methane (CBM) or coal mine gas (CMG). The capture of these CH4 gases can simultaneously avoid greenhouse gas emissions and provide extra energy benefits. However, the explosion risk of low-concentration CBM (CH4 molar fraction ≤ 30%) requires strictly safe operating protocols to conduct the capture process. Dual reflux vacuum swing adsorption (DR-VSA) is a promising candidate with a vacuum operating condition which can lower the explosion risk and simultaneously reach CH4 enrichment and O2 removal targets in product and effluent streams. Herein, a low-concentration oxygen-bearing CBM (20% CH4, 16% O2 and 64% N2) can be upgraded to 69.7 mol% in the product gas while ensuring an effluent concentration of 2.5 mol% by the DR-VSA cycle using ionic liquidic zeolites (ILZ) as the adsorbents. A rigorous safety analysis has been conducted to investigate the explosion risk in the adsorption column and product tank, suggesting that the DR-VSA process is a safe technology for upgrading low-concentration oxygen-bearing methane.
Evolvability: filling the explanatory gap between adaptedness and the long-term mathematical conception of fitness
Authors: Bourrat Pierrick , Deaven Katie , Villegas Cristina 
Published: July 2024

AbstractThe new foundation for the propensity interpretation of fitness (PIF), developed by Pence and Ramsey (Br J Philos Sci 64:851–881, 2013), describes fitness as a probability distribution that encompasses all possible daughter populations to which the organism may give rise, including daughter populations in which traits might change and the possible environments that members of the daughter populations might encounter. This long-term definition of fitness is general enough to avoid counterexamples faced by previous mathematical conceptions of PIF. However, there seem to be downsides to its generality: the ecological role of fitness involves describing the degree of adaptedness between an organism and the specific environment it inhabits. When all possible changes in traits and all possible environments that a daughter population may encounter are included in the concept, it becomes difficult to see how fitness can fulfill this role. In this paper, we argue that this is a feature of Pence and Ramsey’s view rather than a bug: long-term fitness accommodates evolvability considerations, which concern the role that variation plays in evolutionary processes. Building on the foundations, we show that Pence and Ramsey’s fitness—F—can be partitioned into fourths: adaptedness, robustness of adaptedness, and two facets of evolvability. Conceptualizing these last three components forces us to consider the role played by grains of description of both organisms and the environment when thinking about long-term fitness. They track the possibility that there could be a change in type in a daughter population as a way of responding to environmental challenges, or that the type persists in the face of novel environments. We argue that these components are just as salient as adaptedness for long-term fitness. Together, this decomposition of F provides a more accurate picture of the factors involved in long-term evolutionary success.
Iconic origins of language? An essay review of Steven Mithen’s The Language Puzzle (2024)
Authors: van Mazijk Corijn 
Published: July 2024

AbstractThis essay review explores Steven Mithen’s interdisciplinary approach to the origins and evolution of language in The Language Puzzle (2024). It focuses mainly on what I call his iconic vocal origins hypothesis. Mithen challenges the prevalent gestural origins hypothesis, suggesting instead that early prehistoric languages were predominantly vocal and iconic, with conventionalization – as characteristic of symbol use – emerging later. The Language Puzzle draws on research from archaeology, philosophy, computer science, developmental psychology, and many other fields, thus assembling a wealth of insights from various disciplines. While intriguing, Mithen’s suggestion that prehistoric languages may have relied on iconicity instead of conventionalization faces substantial problems, which are discussed in this review essay. In the final section, I also briefly review the important conclusion chapter of Mithen’s book, which contains an imaginative outline of how language evolved from the last common ancestor up until modern H. sapiens. My criticisms of the iconic vocal origins hypothesis notwithstanding, The Language Puzzle is a valuable resource for anyone interested in language evolution, and once again showcases Mithen’s wide-ranging expertise and masterful writing.