bluuebunny/crossref_metadata_2025_split huggingface dataset:
Layer-by-layer modification of cellulose aerogels to optimize capillary spreading rates and liquid holding capacity
Authors: Zou Fangxin , Östmans Rebecca , Wågberg Lars 
Published: February 2025

Abstract
Due to their excellent wetting and liquid-spreading properties, cellulose-based aerogels have shown great potential as absorbent materials in many applications. However, there is still a very limited understanding of how the aerogels should be tailored to optimize liquid spreading and liquid storage properties. The present work focuses on characterizing liquid spreading at short contact times and tailoring the surfaces within the aerogel to increase the spreading properties. Aerogels from periodate oxidized cellulose nano fibrils (CNFs) were freeze-linked to attain wet stability. Subsequently, they were modified with the layer-by-layer (LbL) assembly method using poly(diallyldimethylammonium chloride) (PDADMAC) and well-defined SiO2 nanoparticles to change their surface properties. The morphology of the untreated and treated aerogels, as determined from SEM images, indicates a complete surface coverage of PDADMAC/SiO2 bilayers on the inner surfaces of CNF aerogels, showing that the LbL-treatment can be used to tailor the aerogel, i.e. to increase the specific surface area of the aerogel, by changing the number of bilayers. It has also been shown that the horizontal liquid spreading rate increases significantly after surface modification. In addition, a theoretical analysis of the spreading results indicates that this is due to the increase in the specific surface area of the surface-modified aerogels. Moreover, the spreading rate can be gradually tailored by changing the number of bilayers and the dimensions of the nanoparticles. Furthermore, we provide a new method to calculate the specific surface area of aerogel materials by combining the experimentally determined liquid spreading rate and a version of the well-known Kozeny–Carman equation.
Review on climate change impacts on the Water-Energy-Food-Ecosystems (WEFE) Nexus in the North-Eastern Italian Alps
Authors: Napoli Anna , Matiu Michael , Laiti Lavinia , Barbiero Roberto , Bellin Alberto , Zardi Dino , Majone Bruno 
Published: February 2025

Abstract
Mountains, such as the Trentino region in the North-Eastern Italian Alps, are highly vulnerable to climate change. Their intricate topography amplifies the interaction between local atmospheric processes and regional-scale dynamics, adding complexity to the assessment of climate impacts. To devise effective adaptation strategies, it is crucial to thoroughly understand the environmental and socio-economic sectors most affected in these distinctive mountain landscapes. This study explores the most significant documented impacts of climate change on the sectors within the Water-Energy-Food-Ecosystems (WEFE) Nexus in Trentino. It highlights their interconnections and the critical knowledge gaps that must be addressed to comprehensively understand the Nexus. The main aim is to provide a solid scientific basis for identifying high-priority climate risks in the region and to craft the most appropriate adaptation strategies. Our findings reveal that regarding individual sectors in Trentino, most studies focus on Ecosystems, followed by Water and Food. The least studied sector is Energy. Regarding the NEXUS, the Water Sector exhibits the majority of interconnections with other components. While the impacts of climate change on individual sectors have been analyzed to varying degrees, the strong interconnections between these sectors remain largely unexplored with important missing interconnections mainly between Energy and Food, and Energy and Ecosystems, as well as a comprehensive consideration of the impacts of energy on water and food on ecosystems.
Overcoming Bias in ECSE by Incorporating Funds of Knowledge in Teacher Preparation
Authors: Bhattashali Ankita , Cheatham Gregory A. , Lickvar-Armstrong Chavis , Oh Jisun R. , Kim Gospel 
Published: February 2025

Abstract
Child developmental milestones are deeply rooted in Western developmental theory and, therefore, cannot be assumed to generalize to culturally and racially minoritized (CRM) children and families, including those who are from international backgrounds. When developmental milestones are exclusively used to assess children’s development and make decisions about child goals, Early Childhood Education (ECE) and Early Childhood Special Education (ECSE) practitioners may perpetuate unconscious bias by favoring Western expectations of child development. This can have negative consequences for children and families who are CRM. For example, children can be misdiagnosed with delays and continuing disproportionality in ECSE. To address this problem, we propose strategies to prepare ECE/ECSE preservice teachers to counter biases towards children from CRM backgrounds. In this conceptual paper with an emphasis on practical strategies, we provide an overarching framework of Funds of Knowledge [FoK; Esteban-Guitart and Moll, Cult Psychol 20(1):31–48, 2014] that can be incorporated into a preservice teacher preparation program. Next, we propose the following practical strategies aligned with FoK, which can be included in preservice teacher education: (1) assigning mentor families from CRM backgrounds to support preservice teachers learning about developing meaningful partnerships with families and (2) embedding opportunities for social identity mapping (Jacobson and Mustafa, Int J Qual Methods 18:1–12, 2019), a practice that prompts preservice teachers to reflect on their assumptions and biases.
Laboratory study of bed shear stress in gradually varied flow over a sudden change in bed roughness
Authors: Jamil Muhammad Farrukh , Ting Francis C. K. , Kafle Monika 
Published: February 2025

Abstract
The evolution of bed shear stress in open-channel flow due to a sudden change in bed roughness was investigated experimentally for rough-to-smooth (RTS) and smooth-to-rough (STR) transitions. The velocity field was measured in the longitudinal-vertical plane from upstream to downstream using a Particle Image Velocimetry system. The bed shear stress was determined from the measured velocity profile and water depth using various methods. It was found that the variation of bed shear stress in gradually varied flow through a roughness transition was influenced by both flow depth and bottom roughness. In both RTS and STR transitions, the bed shear stress adjusted to the new bed condition almost immediately even though the velocity profile away from the bed was still evolving, but unlike external and close-conduit flows the bed shear stress in open-channel flows continued to evolve until the flow depth was uniform. It is shown that the evolution of bed shear stress in a STR transition is dependent on the choice of the displacement height on the rough bed, which affects the mixing length used to derive the logarithmic velocity profile and equivalent roughness. Bed shear stress variation consistent with published data was obtained when the

$${k}_{s}/{d}_{90}$$

k
s

/

d
90

ratio was determined as a function of the

$$h/{d}_{90}$$

h
/

d
90

ratio, where

$${k}_{s}$$

k
s

is the equivalent roughness height,

$$h$$

h

is the flow depth, and

$${d}_{90}$$

d
90

is the grain diameter with 90% of finer particles.
Thin-Slice Accuracy Depends on the Wisdom of Crowds: Aggregate Judgments Outperform Individual Judgments when Inferring Athletic Performance Based on Nonverbal Behavior
Authors: Furley Philip , Wunderlich Fabian , Großhaus Laura , Schweizer Geoffrey 
Published: February 2025

Abstract
The present paper aims to resolve ambiguous findings on the accuracy or inaccuracy of human judgments based on sparse information by arguing that accurate thin-slice judgments can be understood as driven by the wisdom of the crowd. To test this hypothesis, participants estimated the performance of track and field athletes in different competitions based on thin slices of pre- and post-performance nonverbal behavior. Results suggest that averaged judgments based on thin slices of athletes’ nonverbal behavior (NVB) are correlated with actual performance and that averaged judgments are better than individual judgments, thus validating the wisdom of the crowd hypothesis. Taken together, the present paper suggests that understanding thin-slice judgments from a wisdom of the crowd perspective has the potential to resolve the apparent contradiction regarding the accuracy or inaccuracy of human judgments. Furthermore, the paper highlights the potential of averaged thin-slice judgments of naturally occurring NVB as an addition to resource consuming coding procedures.
Persons, Unique Value and Avatars
Authors: Sweeney Paula 
Published: February 2025

Abstract
An individual human has value partly in virtue of their uniqueness. Personal avatar technology—technology which creates a digital replication of a real person—appears to have the potential to undermine that value. Here I explore if and how avatars might make humans less valuable by undermining the value that a human gains from being unique. Ultimately, I conclude that, while avatars cannot make humans no longer unique, they could significantly undermine the value that we place on human uniqueness. First, I argue that a qualitative model of uniqueness cannot account for the unique value that a person has. This leads to the significant and surprising claim that necessarily unique properties of humans cannot accommodate the value arising from human uniqueness: humans have unique value in virtue of being contingently irreplaceable. I explore how the use of personal avatars might undermine or even destroy that value. Finally, I consider further applications of the theory of unique human value, including how it might explain and accommodate our attachment to personal avatars themselves.
Prevalence of the Cladosporium cladosporioides Species Complex in the Mycelia-Like Skin Crusts of Migratory Yellow-Throated Buntings (Emberiza elegans) in Korea
Authors: Lee Seung-Kyung , Park Se-Young , Kang Hwa-Yeon , Han Se-Jeong , Nam Hyun-Young , Choi Chang-Yong , Yamamoto Naomichi 
Published: February 2025

Abstract
Understanding the ecological characteristics and environmental factors of migratory songbirds is essential for their conservation as well as pathogen management that may cross ecological and political boundaries. In this study, we conducted a bird trapping and banding survey and report on fungal DNA detected from birds with putative fungal skin infections. We analyzed the mycobiome of mycelia-like skin crusts of the yellow-throated bunting (Emberiza elegans), a common migratory songbird with declining population in Korea, using DNA metabarcoding targeting the internal transcribed spacer 1 (ITS1) region, the actin (ACT) gene, and the translation elongation factor 1 − α (TEF) gene. Our analysis revealed that Cladosporium was the predominant genus (~ 60% sequence reads) in fungal mycelia-like tissues on the skins of yellow-throated buntings and detected a large number of DNA sequences similar to those of species belonging to the Cladosporium cladosporioides species complex. This is the first study to report possible infection in buntings by Cladosporium, including species known to infect humans and other animals. Further research on the causal relationship between birds and fungi is needed for pathogen management and conservation of Asian songbirds along the migration flyway.
Artificial Intelligence Tools in Misinformation Management during Natural Disasters
Authors: Komendantova Nadejda , Erokhin Dmitry 
Published: February 2025

Abstract
Ensuring accurate information during natural disasters is vital for effective emergency response and public safety. Disasters like earthquakes and hurricanes often trigger misinformation, complicating response efforts and endangering lives. Historical events, such as Hurricane Katrina and the COVID-19 pandemic, illustrate the harmful impact of false information. Artificial intelligence (AI), with technologies like natural language processing and machine learning, offers promising solutions for detecting and mitigating misinformation. This paper explores AI’s role in managing misinformation during disasters, highlighting its potential to improve disaster response, enhance public trust, and strengthen community resilience.
Realistic Evaluation of Deep Active Learning for Image Classification and Semantic Segmentation
Authors: Mittal Sudhanshu , Niemeijer Joshua , Çiçek Özgün , Tatarchenko Maxim , Ehrhardt Jan , Schäfer Jörg P. , Handels Heinz , Brox Thomas 
Published: February 2025

Abstract
Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Recently, deep active learning has shown success on various tasks. However, the conventional evaluation schemes are either incomplete or below par. This study critically assesses various active learning approaches, identifying key factors essential for choosing the most effective active learning method. It includes a comprehensive guide to obtain the best performance for each case, in image classification and semantic segmentation. For image classification, the AL methods improve by a large-margin when integrated with data augmentation and semi-supervised learning, but barely perform better than the random baseline. In this work, we evaluate them under more realistic settings and propose a more suitable evaluation protocol. For semantic segmentation, previous academic studies focused on diverse datasets with substantial annotation resources. In contrast, data collected in many driving scenarios is highly redundant, and most medical applications are subject to very constrained annotation budgets. The study evaluates active learning techniques under various conditions including data redundancy, the use of semi-supervised learning, and differing annotation budgets. As an outcome of our study, we provide a comprehensive usage guide to obtain the best performance for each case.
Trust and Motivation in High-Risk Volunteering: An Empirical Study of Norwegian Search-and-Rescue Volunteers
Authors: Wollebæk Dag 
Published: February 2025

Abstract
Volunteering in emergency situations can involve the risk of injury. Overcoming such risks may motivate some volunteers, but may also deter those who are risk-averse. This presents a challenge, as recruiting and engaging volunteers with different risk attitudes is important to ensure response capacity and a balanced organizational culture. This cross-sectional study uses data from online surveys of search-and-rescue (SAR) volunteers (n = 1,659) and the general population (n = 3,185) in Norway to examine whether trust moderates a negative relationship between risk aversion and motivation in high-risk volunteering. Results from OLS regressions show that SAR volunteers have higher levels of risk propensity (B = 0.25, p < 0.001), trust (B = 1.47, p < 0.001) and felt trust (B = 1.36, p < 0.001) than other volunteers. Risk-averse volunteers report lower motivation and participation, but trust mitigates much of the negative impact (interaction term B = −0.10, p < 0.01). These findings underline the importance of strong cultures of trust within SAR volunteer teams.
Spatial distribution of nicotine concentrations in Berlin’s surface waters and their potential sources
Authors: Venohr Markus , Beusch Christine , Goldhammer Tobias , Nguyen Hanh Hong , Podschun Simone , Schmalsch Claudia , Wolter Christian 
Published: February 2025

Abstract
Nicotine is a ubiquitous emergent pollutant that primarily enters the environment through inappropriate disposal of cigarette butts. In a 7-week monitoring program, we collected 56 water samples from 14 lakes, 9 ponds, 9 rivers, 8 canals, and 2 canalized brooks in Berlin. Nicotine was detected in all investigated surface waters. Observed concentrations ranged between 7 ng/l and 1469 ng/l (mean 73 ng/l, median 28 ng/l). Rainy weather conditions generally led to an increase in nicotine concentrations, particularly in canals where concentrations were up to 16 times higher after rain events. For water bodies receiving sewer discharge, mean nicotine concentrations were positively related to population density, while concentrations in surface waters without sewer connections were more related to the presence of public transport stops or recreational areas. Our results highlight the high spatiotemporal variability of nicotine concentrations in urban surface waters. We recommend a temporary systematic daily or event-based monitoring of nicotine concentrations to support our findings and to better understand and quantify emission sources and concentration decay phases. This would improve our still incomplete knowledge about ecological impacts arising from long-term below-lethal nicotine concentrations in urban surface waters.
Weighted embedding and outlier detection of metric space data
Authors: Heinonen Lauri , Nyberg Henri , Virta Joni 
Published: February 2025

Abstract
This work discusses weighted kernel point projection (WKPP), a new method for embedding metric space or kernel data. WKPP is based on an iteratively weighted generalization of multidimensional scaling and kernel principal component analysis, and one of its main uses is outlier detection. After a detailed derivation of the method and its algorithm, we give theoretical guarantees regarding its convergence and outlier detection capabilities. Additionally, as one of our mathematical contributions, we give a novel characterization of kernelizability, connecting it also to the classical kernel literature. In our empirical examples, WKPP is benchmarked with respect to several competing outlier detection methods, using various different datasets. The obtained results show that WKPP is computationally fast, while simultaneously achieving performance comparable to state-of-the-art methods.
Flow cytometry and cytological studies reveal consecutive rounds of strict partial genome duplications and endomitosis in cellular nuclei from vegetative organs of seeded Dactylorhiza majalis (subfamily Orchidoideae)
Authors: Schubert Roland , Hohlfeld Heike , Brugger Markus 
Published: February 2025

Abstract
During the analysis of suspensions of PI-stained nuclei from stem, adventitious roots, and leaves of in vitro germinated juvenile D. majalis plants, a range of one to three consecutive rounds of strict partial genome duplications could be discovered. Repeated cycles of under-replications were found again when axenically grown material was moved from solid nutrient media to potting soil, where it further maturated within and outside the laboratory. On average, 83–84% of the 2C DNA content participated in partial genome duplication processes while the remaining 16–17% were untouched. Different frequency distributions were detected for the affected nuclei, depending on the individual, the plant organ, and the ontogenetic stage. The above data were in line with the signs of endomitosis, as shown by acetocarmine-stained smear preparations from the lower epidermis of leaves and from adventitious roots sampled at some distance above the meristematic tip. Endomitosis is one known pathway of endoreplications, which leads to an increased DNA content in non-dividing somatic nuclei. Using a collection of young anthers in the microspore stage, where the regular haplophasic number of 1n = 2x = 40 chromosomes could be counted, foliar cells of the related vegetative plant body were considered to contain the whole set of 2n = 4x = 80 chromosomes that contributed to a mean mass of 14.71 pg DNA per nucleus at the 2C genome level. The diverse biological source materials and investigated ontogenetic stages as well as the different nuclear DNA amount calculations assessed in this study are of instructional value to avoid erroneous estimations of the present nuclear DNA amount per weight using flow cytometry. This is important with respect to the orchid genus Dactylorhiza, for example, when trying to achieve a full understanding of genome size variation in established polyploids and when searching for nascent polyploids in the future.
Entrepreneurship in the context of permanent crisis: the role of community support
Authors: Audretsch David B. , Kariv Dafna 
Published: February 2025

Abstract
In an era of persistent crises, the determinants of technological performance are undergoing a radical transformation. Existing research primarily addresses technological performance under stable conditions, offering insights that fall short during continual crises. To enhance technological performance amid uncertainty, our study of 489 Israeli tech-founders reveals that psychological capital and a strong sense of community belonging are pivotal. These entrepreneurial factors catalyze ecosystem support and opportunities, converting conventional drivers into potent engines of growth. Through mixed methods, advanced Natural Language Processing, and robust statistical analysis, we reveal how entrepreneurial strengths optimize resource utilization. Through interviews, we extract topics and sentiments associated with these factors during crises, showing that a sense of belonging acts as a positive anchor. Questionnaire results further reveal the mediating effects of these internal factors. Our methodology bridges conceptual and empirical gaps, offering new insights to decode technological success in uncertain times. The implications extend beyond theory, providing actionable strategies for tech leaders, policymakers, and innovation ecosystems facing ongoing instability.
Decoding the dark sides of family business: a synthesis, and future research agenda
Authors: Anand Amitabh , Wieszt Attila , Vajda Éva 
Published: February 2025

Abstract
Numerous contributions to family business recognize its positive impact on economic and social development. However, literature often overlooks the harmful aspects. To fill this void, we conduct a multidisciplinary systematic literature review to analyze the current state of the different dimensions of the dark sides of family business (FB) literature and synthesize the findings into a holistic framework. Our study employs a qualitative synthesis approach to propose a new unified definition of the dark side of FB, identify the antecedents, and analyze the consequences. Subsequently, we identify areas that require greater attention and outline a promising future agenda for advancing the literature on dark side of FB.
Leptin and Leptin Signaling in Multiple Sclerosis: A Narrative Review
Authors: Flores-Cordero Juan Antonio , Aranaz-Murillo Amalia , Vilariño-García Teresa , Pérez-Pérez Antonio , Izquierdo Guillermo , Flores-Campos Rocío , Hontecillas-Prieto Lourdes , García-Domínguez Daniel J. , Sánchez-Margalet Víctor 
Published: February 2025

Abstract
Obesity, a pandemic health problem, is now considered as a chronic inflammatory state, related to many autoimmune diseases, such as multiple sclerosis. Thus, adipokines, inflammatory mediators secreted by adipose tissue, play an important role modulating the immune response. In this context, obesity, especially during adolescent age, seems to be a key factor for the development of multiple sclerosis. Leptin, the main pro-inflammatory adipokine secreted by the adipose tissue, has been found increased in patients with multiple sclerosis and is able to regulate the immune system promoting a pro-inflammatory response. Leptin signaling in both innate and adaptative immune cells might have immunomodulatory effects in the context of multiple sclerosis. In this way, leptin has been found to produce a Th1 and Th17 response, increasing M1 macrophages and decreasing regulatory T cells and Th2 response. Moreover, circulating inflammatory adipokines, such as leptin, have been found in people with multiple sclerosis. In the present work, we are reviewing literature to update the body of knowledge regarding the role of obesity and leptin in multiple sclerosis.