bluuebunny/crossref_metadata_2025_split huggingface dataset:
The growth rate of multicolor Ramsey numbers of 3-graphs
Authors: Bradač Domagoj , Fox Jacob , Sudakov Benny 
Published: July 2024

AbstractThe q-color Ramsey number of a k-uniform hypergraph G, denoted r(G; q), is the minimum integer N such that any coloring of the edges of the complete k-uniform hypergraph on N vertices contains a monochromatic copy of G. The study of these numbers is one of the most central topics in combinatorics. One natural question, which for triangles goes back to the work of Schur in 1916, is to determine the behavior of r(G; q) for fixed G and q tending to infinity. In this paper, we study this problem for 3-uniform hypergraphs and determine the tower height of r(G; q) as a function of q. More precisely, given a hypergraph G, we determine when r(G; q) behaves polynomially, exponentially or double exponentially in q. This answers a question of Axenovich, Gyárfás, Liu and Mubayi.
Exploration of a new AlCoCrNiNb high-entropy alloy: in situ alloying of a CoCrMo, M247, and Nb powder mixture via laser powder bed fusion
Authors: Tsai Meng-Hsiu , Cheng Chia-Ping , Fu Ho-Chung , Chiba Akihiko , Yamanaka Kenta 
Published: July 2024

Abstract
High-entropy alloys (HEAs) have compelling advantages, such as high strength and corrosion resistance, but they remain underexplored owing to the limited availability of certain prealloyed and elemental powders. In this study, an AlCoCrNiNb HEA was fabricated in situ via laser powder bed fusion (LPBF) using a powder mixture of commercial CoCrMo, Mar M247, and Nb elemental powders. The powder mixture was blended for 24 h using a horizontal blending machine, to obtain similar chemical compositions in the middle and top layers of the blended powder. However, local Nb aggregation was observed in the bottom layer owing to the particle-size effect. X-ray diffraction and chemical composition analyses revealed that the in situ alloyed AlCoCrNiNb HEA specimen obtained via LPBF was a homogeneous solid solution with a face-centered cubic structure. HEA exhibits a fine-grained morphology, and its maximum microhardness is approximately 970 HV. These characteristics are typical of rapid solidification and sluggish diffusion. These results underscore the effectiveness of using commercial prealloyed and elemental powders for fabricating AlCoCrNiNb HEAs through LPBF-based in situ alloying, thus advancing the development of HEAs. Thermodynamic calculations were performed to support these outcomes.
Two-sample testing with local community depth
Authors: Evans Ciaran , Berenhaut Kenneth S. 
Published: July 2024

AbstractIn this paper, we investigate nonparametric two-sample hypothesis testing with local community depth, a measure of data depth calculated from pairwise distances between observations. Unlike many common “center-outwards” measures of data depth, local community depth captures local features of a distribution such as multimodality and can adapt to modes with different scales. This gives local community depth greater power to detect scale changes in multimodal distributions, and importantly the method is parameter-free. The local depth employed supplements existing adaptations of depth to local regions and is computationally cheaper in high dimensions than many classic depths such as halfspace depth, regression depth, simplicial depth, and Mahalanobis depth. We test hypotheses by using local community depth in the Liu–Singh test and give conditions under which our method is consistent against fixed alternatives (and has a limiting null distribution). In simulations and an application to diagnosing dengue fever, we show that local community depth outperforms other depths when the underlying distribution is multimodal or asymmetric, and is comparable to other methods when the data is unimodal and symmetric.
A bridge between influence models and control methods
Authors: Sadaf Abida , Mathieson Luke , Bródka Piotr , Musial Katarzyna 
Published: July 2024

AbstractUnderstanding how influence is seeded and spreads through social networks is an increasingly important study area. While there are many methods to identify seed nodes that are used to initialize a spread of influence, the idea of using methods for selecting driver nodes from the control field in the context of seed selection has not been explored yet. In this work, we present the first study of using control approaches as seed selection methods. We employ a Minimum Dominating Set to develop a candidate set of driver nodes. We propose methods based upon driver nodes (i.e. Driver-Random, Driver-Degree, Driver-Closeness, Driver-Betweenness, Driver-Degree-Closeness-Betweenness, Driver-Kempe, Driver-Ranked) for selecting seeds from this set. These methods make use of centrality measures to rank the driver nodes in terms of their potential as seed nodes. We compare proposed methods to existing approaches using the Linear Threshold model on both real and synthetic networks. Our experiment results show that the proposed methods consistently outperform the benchmarks. We conclude that using driver nodes as seeds in the influence spread results in faster and thus more effective spread than when applying traditional methods.
AU3-GAN: A Method for Extracting Roads from Historical Maps Based on an Attention Generative Adversarial Network
Authors: Zhao Yao , Wang Guangxia , Yang Jian , Li Tingting , Li Ziwei 
Published: July 2024

AbstractIn recent years, the integration of deep learning technology based on convolutional neural networks with historical maps has made it possible to automatically extract roads from these maps, which is highly important for studying the evolution of transportation networks. However, the similarity between roads and other features (such as contours, water systems, and administrative boundaries) poses a significant challenge to the feature extraction capabilities of convolutional neural networks (CNN). Additionally, CNN require a large quantity of labelled data for training, which can be a complex issue for historical maps. To address these limitations, we propose a method for extracting roads from historical maps based on an attention generative adversarial network. This approach leverages the unique architecture and training methodology of the generative adversarial network to augment datasets by generating data that closely resembles real samples. Meanwhile, we introduce an attention mechanism to enhance UNet3 + and achieve accurate historical map road segmentation images. We validate our method using the Third Military Mapping Survey of Austria-Hungary and compare it with a typical U-shaped network. The experimental results show that our proposed method outperforms the direct use of the U-shaped network, achieving at least an 18.26% increase in F1 and a 7.62% increase in the MIoU, demonstrating its strong ability to extract roads from historical maps and provide a valuable reference for road extraction from other types of historical maps.
Behavior Based Group Recommendation from Social Media Dataset by Using Deep Learning and Topic Modeling
Authors: Mukta Md. Saddam Hossain , Ahmed Jubaer , Raiaan Mohaimenul Azam Khan , Fahad Nur Mohammad , Islam Muhammad Nazrul , Imtiaz Nafiz , Islam Md. Adnanul , Ali Mohammed Eunus , Azam Sami 
Published: July 2024

AbstractIn this digital era, users frequently share their thoughts, preferences, and ideas through social media, which reflect their Basic Human Values. Basic Human Values (aka values) are the fundamental aspects of human behavior, which define what we consider important, and worth having and pursue them. Existing studies identify the values of individuals from different social network usages such as Facebook and Reddit. However, discovering the similarity (or diversity) of value priorities among the members in a group is important since we can reveal many interesting insights such as finding a set of target customers, identifying the chain of misdeed groups, searching for similar acquaintances in workplaces, etc. In this paper, a graph dataset is compiled using the strongest correlation among the features and then we apply a graph clustering technique to identify a suitable hedonist group (i.e., one dimension of values) for users’ recommendations. Then, we also propose a behavior based (i.e., value ) group recommendation technique by analyzing users’ contextual and psychological attributes. Finally, we validate those group members in real life by introducing two hypotheses. In particular, we analyze the tweets of a total of 1140 users collected from Twitter. We obtain a substantial intra-cluster correlation coefficient (ICC) and silhouette clustering coefficient (SCC) scores of 65% and 76%, respectively, among the members in our discovered group.
Inference and prioritization of tissue-specific regulons in Arabidopsis and Oryza
Authors: Dai Honggang , Fan Yaxin , Mei Yichao , Chen Ling-Ling , Gao Junxiang 
Published: July 2024

AbstractA regulon refers to a group of genes regulated by a transcription factor binding to regulatory motifs to achieve specific biological functions. To infer tissue-specific gene regulons in Arabidopsis, we developed a novel pipeline named InferReg. InferReg utilizes a gene expression matrix that includes 3400 Arabidopsis transcriptomes to make initial predictions about the regulatory relationships between transcription factors (TFs) and target genes (TGs) using co-expression patterns. It further improves these anticipated interactions by integrating TF binding site enrichment analysis to eliminate false positives that are only supported by expression data. InferReg further trained a graph convolutional network with 133 transcription factors, supported by ChIP-seq, as positive samples, to learn the regulatory logic between TFs and TGs to improve the accuracy of the regulatory network. To evaluate the functionality of InferReg, we utilized it to discover tissue-specific regulons in 5 Arabidopsis tissues: flower, leaf, root, seed, and seedling. We ranked the activities of regulons for each tissue based on reliability using Borda ranking and compared them with existing databases. The results demonstrated that InferReg not only identified known tissue-specific regulons but also discovered new ones. By applying InferReg to rice expression data, we were able to identify rice tissue-specific regulons, showing that our approach can be applied more broadly. We used InferReg to successfully identify important regulons in various tissues of Arabidopsis and Oryza, which has improved our understanding of tissue-specific regulations and the roles of regulons in tissue differentiation and development.
Iron administered in the neonatal period changed memory, brain monoamine levels, and BDNF mRNA expression in adult Sprague–Dawley rats
Authors: Rogóż Zofia , Kamińska Kinga , Lorenc-Koci Elżbieta , Wąsik Agnieszka 
Published: July 2024

Abstract
Background
Iron is one of the key microelements in the mammalian body and is the most abundant metal in the brain. Iron, a very important chemical element in the body of mammals, is the most abundant metal in the brain. It participates in many chemical reactions taking place in the central nervous system acting as a cofactor in key enzymatic reactions involved in neurotransmitter synthesis and degradation, dendritic arborization, and myelination. Moreover, iron accumulation in the brain has been implicated in the pathogenesis of neurogenerative disorders.

Material and methods
The aim of our study was to assess the influence of iron administered orally (30 mg/kg) to rats in the neonatal period (p12-p14) by testing the performance of rats in the open field and social interaction tests, and by evaluating the recognition memory, monoamine levels in some brain structures, and BDNF mRNA expression. The behavioral and biochemical tests were performed in adult p88-p92 rats.

Results
Iron administered to rats in the neonatal period induced long-term deficits in behavioral tests in adult rats. It reduced the exploratory activity in the open field test. In the social interaction test, it induced deficits in the parameters studied, and decreased memory retention. Moreover, iron changed the brain monoamine levels in some studied brain structures and decreased the expression of BDNF mRNA in the hippocampus.

Conclusions
All earlier and our present results indicated that iron administered to rats in the neonatal period induced an increase in oxidative stress which resulted in a change in the brain monoamine levels and decreased BDNF mRNA expression which may play a role in iron-induced memory impairment in adult rats.
Energy-absorbing limitations of hard hat safety helmets in mitigating trauma from falling objects
Authors: Ptak Mariusz , Dymek Mateusz , Wdowicz Daniel , Szumiejko Adrianna , Kwiatkowski Artur 
Published: July 2024

AbstractThe aim of the study was to analyze the effectiveness of hard hat helmets in mitigating head injuries from high-energy falling objects through a real-world case study, advanced numerical simulations and an uncertainty study. The study aims to answer the following research questions: (a) to what extent would the use of the protective helmet limit the kinetic energy of the falling construction prop, (b) whether the hard hat helmet would be damaged, and if so, to what extent, according to the helmet standards? A fatal construction accident involving a falling prop impact on the victim’s head was reconstructed using multi-body dynamics simulations and finite element analysis (FEA) based on uncertainty-based determination of initial conditions. The study quantified the impact energy, helmet damage and its energy-absorbing capabilities, and potential injury reduction compared to scenarios without a helmet. While the helmet absorbed significant energy (245% of the standard requirement) and reduced the Head Injury Criterion by 8–11%, the high impact energy ultimately proved fatal. This study highlights the limitations of hard hat helmets in extreme scenarios with high kinetic energy impacts. While helmets offer valuable protection, unrealistic expectations should not be placed on their ability to prevent all head injuries. The study not only enhances our understanding of the biomechanics of head injuries in such incidents but also provides practical implications for safety protocols and regulations.
A Māori data governance assessment of the NZ COVID Tracer app
Authors: Sterling Rogena , Kukutai Tahu , Chambers Tim , Chen Andrew Tzer-Yeu 
Published: July 2024

AbstractPurposeDuring the COVID-19 pandemic, the NZ COVID Tracer App (NZCTA) was released as a digital intervention to support contact tracing processes in Aotearoa New Zealand. This paper examines whether NZCTA met the data governance requirements of the Indigenous Māori people. Māori are an interesting case study as they have unique Treaty and data sovereignty rights, and a higher risk of COVID-related mortality.MethodsThe NZCTA was assessed against 24 criteria drawn from the Māori Data Governance Model. The assessment drew on documentary sources and the authors’ knowledge of NZCTA and contact tracing process. Each criteria was assessed as ‘met’, ‘partially met’ or ‘not met’.ResultsOur retrospective assessment showed a mixed performance against the Māori Data Governance Model, with NZCTA only fulfilling seven of the 24 model criteria and failing to meet nine.ConclusionThere is significant room for improvement in future digital health interventions for Māori. Much work remains to be done in the Aotearoa public sector to uphold Māori data sovereignty and address systemic barriers to genuine partnership with Māori.
Teaching responsible creativity: a path to ethical innovation
Authors: Rebecchi Kevin , Todd Lubart , Hagège Hélène 
Published: July 2024

AbstractEducation today is evolving to foster essential psychosocial skills like creativity, critical thinking, and responsibility, equipping students for 21st-century challenges. However, it is crucial to examine the motivations driving these changes and their alignment with broader societal goals beyond merely economic interests.This article explores the ethical dimensions of creativity, recognizing its potential for both positive innovation and harm. It emphasizes the neutrality of creativity and the importance of evaluating the intentions and consequences behind creative acts, not just their outcomes. We introduce and define the concept of ‘‘responsible creativity,’’ characterized by the ability to generate original ideas, behaviors, or objects while considering the moral and legal repercussions of one's actions, both in the present and future. This concept is anchored in the ethics of conviction and responsibility, promoting a fundamental commitment to avoid harm and enhance well-being. Our model of responsible creativity incorporates qualities such as benevolence, flexibility, positivity, reliability, accountability, reflexivity, and wisdom. We advocate for nurturing this type of creativity in educational settings through innovative approaches such as board and video games, philosophy workshops, wisdom education, and mindfulness meditation. These pedagogical methods aim to cultivate future leaders who are ethically aware and capable of using their creativity to positively impact society and the environment. By navigating the interplay of creativity and ethics, this article provides valuable insights and practical guidance for educators and policymakers striving to create a more ethically conscious and innovative educational landscape.
Analysis of the socio-environmental impacts of an environmental disaster caused by a minining company in the city of Maceió, Brazil
Authors: de Lima Filho Walter Araujo , de Almeida Levino Natallya , Guarnieri Patrícia 
Published: July 2024

AbstractIn mid-2018, several neighbourhoods in Maceió, Brazil, were affected by soil subsidence in the region. Since then, unprecedented developments and consequences have been observed in the affected areas. Against this backdrop, the study aims to analyses the socio-environmental impacts suffered by the five neighbourhoods affected by subsidence from rock salt extraction in the municipality of Maceió, Alagoas, Brazil. We collected secondary data from documents (Geological Survey studies, information made available by the Federal Public Prosecutor's Office, Compensation Plan, Terms of Agreement, Socio-urban Action Plan, Environmental Impact Study, Study of the Economic Impact of the Disaster) to assess the socio-environmental impacts caused by the socio-environmental disaster. These data were analysed using Checklist, Interaction Matrix, and Delphi. The results highlight the complexity of the effects since they were observed from a multidisciplinary approach. In addition, it is clear that these impacts were relevant and important from the specialists' point of view and, when analysed quantitatively and qualitatively,such as impacts on identity and cultural aspects, change in standard of living, and overload in the provision of public facilities, which had a high degree of impact when evaluated in this study. The study also concluded that it is pertinent to take measures to mitigate the impacts indicated as possible through integration between public authorities and the mining company. Upon its completion, a technical product in the form of a document containing the identified mitigation measures was submitted to the competent authorities. These results can be relevant for practitioners and policymakers involved in decisions related to mining operations.
Physical Mechanisms Sustaining Silica Production Following the Demise of the Diatom Phase of the North Atlantic Spring Phytoplankton Bloom During EXPORTS
Authors: Brzezinski Mark A. , Johnson Leah , Estapa Margaret , Clevenger Samantha , Roca‐Martí Montserrat , Romanelli Elisa , Buck Kristen N. , Jenkins Bethany D. , Jones Janice L. 
Published: July 2024

AbstractEach spring, the North Atlantic experiences one of the largest open‐ocean phytoplankton blooms in the global ocean. Diatoms often dominate the initial phase of the bloom with succession driven by exhaustion of silicic acid. The North Atlantic was sampled over 3.5 weeks in spring 2021 following the demise of the main diatom bloom, allowing mechanisms that sustain continued diatom contributions to be examined. Diatom biomass was initially relatively high with biogenic silica concentrations up to 2.25 μmol Si L−1. A low initial silicic acid concentration of 0.1–0.3 μM imposed severe Si limitation of silica production and likely limited the diatom growth rate. Four storms over the next 3.5 weeks entrained silicic acid into the mixed layer, relieving growth limitation, but uptake limitation persisted. Silica production was modest and dominated by the >5.0 μm size fraction although specific rates were highest in the 0.6–5.0 μm size fraction over most of the cruise. Silica dissolution averaged 68% of silica production. The resupply of silicic acid via storm entrainment and silica dissolution supported a cumulative post‐bloom silica production that was 32% of that estimated during the main bloom event. Diatoms contributed significantly to new and to primary production after the initial bloom, possibly dominating both. Diatom contribution to organic‐carbon export was also significant at 40%–70%. Thus, diatoms can significantly contribute to regional biogeochemistry following initial silicic acid depletion, but that contribution relies on physical processes that resupply the nutrient to surface waters.
Rift to Post‐Rift Tectonostratigraphy of the Sverdrup Basin in Relation to Onset of the High Arctic Large Igneous Province (HALIP) in the Early Cretaceous, Arctic Canada
Authors: Hadlari T. 
Published: July 2024

AbstractA summary of the Jurassic‐Cretaceous rift to breakup tectonostratigraphy of the onshore Sverdrup Basin is correlated to the offshore Amerasia Basin in order to reconstruct a tectonic setting for the High Arctic Large Igneous Province (HALIP). The rift climax from the Canadian rifted margin is correlated with hyper‐extension of the continent‐ocean‐transition zone. Hyper‐extension of the continental lithosphere can accommodate plate motions of Arctic Alaska‐Chukotka away from the Canadian Arctic Islands and Lomonosov Ridge between ∼155 Ma and 135–133 Ma. After lithospheric breakup at ∼135–133 Ma, correlation of the post‐rift stage to the seafloor spreading anomalies M10n to M4n that are associated with oceanic crustal domains can accommodate plate motions from 135–133 Ma to 128 Ma. The uncertainties associated with the earliest magmas of HALIP overlap with the uncertainties on the timing of the latest seafloor spreading. The first main pulse of HALIP in the Aptian at 124–120 Ma post‐dates seafloor spreading and so HALIP was emplaced in a tectonic setting that closely resembles the present state of the south and eastern Amerasia Basin. At the paleogeographic center of the HALIP, the Alpha Ridge complex is consistent with the magmatic character and history of similar Cretaceous oceanic plateau in terms of volume and duration.