bluuebunny/crossref_metadata_2025_split huggingface dataset:
The potential of algae as a source of cellulose and its derivatives for biomedical applications
Authors: Machado Bárbara , Costa Sofia M. , Costa Isabel , Fangueiro Raul , Ferreira Diana P. 
Published: March 2024

AbstractCellulose has been intensively investigated for biomedical applications, because of its excellent properties, like biodegradability, biocompatibility, abundant availability of renewable resources and cost-effectiveness. Among all sources of cellulose, marine macroalgae or seaweeds, are acquiring tremendous attention, due to their high availability around the world. Moreover, the atypical proliferation of some exotic macroalgae species represents a serious problem to the ecosystems, since their accumulation threatens native oceanic species and resources worldwide. Several studies already reported the successfully extraction of cellulose and its derivatives from brown, green and red macroalgae. The extracted cellulose properties vary according to the type of algae, their maturity and the used extraction methods. This review will cover the main methods used to extract cellulose from algae, focusing on more sustainable ones, as well as its further processing into the various cellulose derivatives. Electrospun nanofibers have revealed great potential for biomedical applications, such as delivery of therapeutic agents, tissue engineering, wound dressings and enzyme immobilization. Pure cellulose presents some drawbacks, such as limited solubility in organic solvents and its inability to fuse due to inter and intra-molecular hydrogen bonding. To overcome these limitations, cellulose derivatives, which includes microcrystalline cellulose, cellulose nanocrystals, cellulose nanofibers, cellulose acetate and carboxymethyl cellulose, have been extensively studied to generate electrospun fibers. Therefore, this review aims to explore the marine seaweeds as a promising source of cellulose and its derivatives, the extraction methodologies of these compounds, as well as to demonstrate the potential of nanofibers developed by electrospinning with algae-based cellulose for biomedical applications.
Humanoid robot-empowered language learning based on self-determination theory
Authors: Fung Ka Yan , Lee Lik Hang , Sin Kuen Fung , Song Shenghui , Qu Huamin 
Published: March 2024

AbstractWith the ability to provide feedback and assistance, humanoid educational robots have been proven effective in assisting students to overcome learning challenges and enhancing individual learning outcomes. However, the strength of humanoid robots in promoting social and emotional skills has not been well investigated. Socially supportive behaviour can contribute more to students’ learning engagement than knowledge transfer. This study focuses on the design of humanoid robots to engage students from functional and affective perspectives. To this end, a pilot test is conducted on 64 primary school students in Hong Kong, comprising a control group (N = 33) and an experimental group (N = 31). Questionnaires, observations, and language proficiency test are done to ensure the validity of the findings. The results show that the experimental group, which learned with the humanoid robots, significantly improved their behavioural engagement (+ 13.24%), emotional engagement (+ 13.14%), cognitive engagement (21.56%), and intrinsic motivation (12.07%). The impact of utilizing humanoid robots in education is elucidated through the lens of the self-determination theory (SDT), which pertains to students’ learning motivation and engagement. These findings can provide valuable insights into the development of more captivating humanoid robots for extensive learning purposes.
Understanding vessel noise across a network of marine protected areas
Authors: McKenna Megan F , Rowell Timothy J , Margolina Tetyana , Baumann-Pickering Simone , Solsona-Berga Alba , Adams Jeffrey D , Joseph John , Kim Ella B , Kok Annebelle CM , Kügler Anke , Lammers Marc O , Merkens Karlina , Reeves Lindsey Peavey , Southall Brandon L , Stimpert Alison K , Barkowski Jack , Thompson Michael A , Van Parijs Sofie , Wall Carrie C , Zang Eden J , Hatch Leila T 
Published: March 2024

AbstractProtected areas are typically managed as a network of sites exposed to varying anthropogenic conditions. Managing these networks benefits from monitoring of conditions across sites to help prioritize coordinated efforts. Monitoring marine vessel activity and related underwater radiated noise impacts across a network of protected areas, like the U.S. National Marine Sanctuary system, helps managers ensure the quality of habitats used by a wide range of marine species. Here, we use underwater acoustic detections of vessels to quantify different characteristics of vessel noise at 25 locations within eight marine sanctuaries including the Hawaiian Archipelago and the U.S. east and west coasts. Vessel noise metrics, including temporal presence and sound levels, were paired with Automatic Identification System (AIS) vessel tracking data to derive a suite of robust vessel noise indicators for use across the network of marine protected areas. Network-wide comparisons revealed a spectrum of vessel noise conditions that closely matched AIS vessel traffic composition. Shifts in vessel noise were correlated with the decrease in vessel activity early in the COVID-19 pandemic, and vessel speed reduction management initiatives. Improving our understanding of vessel noise conditions in these protected areas can help direct opportunities for reducing vessel noise, such as establishing and maintaining noise-free periods, enhancing port efficiency, engaging with regional and international vessel quieting initiatives, and leveraging co-benefits of management actions for reducing ocean noise.
Hypocrisy and Epistemic Injustice
Authors: Carey Brian 
Published: March 2024

AbstractIn this article I argue that we should understand some forms of hypocritical behaviour in terms of epistemic injustice; a type of injustice in which a person is wronged in their capacity as a knower. If each of us has an interest in knowing what morality requires of us, this can be undermined when hypocritical behaviour distorts our perception of the moral landscape by misrepresenting the demandingness of putative moral obligations. This suggests that a complete theory of the wrongness of hypocrisy must account for hypocrisy as epistemic injustice.
The influence of habitat heterogeneity on Nematoda communities in Posidonia oceanica meadows
Authors: García-Cobo Marta , González-Casarrubios Alberto , García-Gómez Guillermo , Pardos Fernando , Sánchez Nuria 
Published: March 2024

AbstractNematodes typically comprise the most abundant phylum in meiofaunal communities. We aim to characterize the specific ecological conditions that influence Nematoda communities inPosidonia oceanicagrasslands focusing on three habitats: leaves, matte, and unvegetated adjacent sediment. We hypothesized that the constant flux of nutrients under the canopy would result in a higher concentration of metazoans compared to the unvegetated sediment outside; however, the hypothesis was not confirmed by the obtained results. The habitat heterogeneity played an important role in shaping the community, yielding a greater richness in the matte. The resource specificity of the leaves (microepiphytes) was also expected to shape the community by favoring nematodes capable of exploiting this resource (epistratum feeders with scraping-like structures), such as the family Chromadoridae that dominated this habitat. In addition, the high light exposure of the leaves explains the higher concentration of ocellated nematodes in this habitat. Organic carbon and nitrogen contents had an impact on the Nematoda community composition, meanwhile average grain size only affected the abundance of nematodes with elongated/filiform tails.
Exploring the Effects of Technology-Related Informal Mathematics Learning Activities: A Structural Equation Modeling Analysis
Authors: Jiang Haozhe , Chugh Ritesh , Turnbull Darren , Wang Xiaoqin , Chen Suting 
Published: March 2024

AbstractDespite the burgeoning adoption of informal learning in people’s daily lives, the actual effects of informal learning activities, especially technology-related informal learning activities, are much less reported than those of formal learning. Furthermore, there is a notable lack of research on the effects of technology-related informal mathematics learning activities (TRLA). This study aims to propose and validate a new model which illustrates the effects of TRLA on four constructs: mathematics self-efficacy (MSE), mathematics interest (MI), self-regulation in mathematics learning (SR), and teacher-student relationship (TSR). Adopting a quantitative cross-sectional survey approach, 460 students were investigated. The data were analyzed employing two-step structural equation modeling. Our findings demonstrate the direct effects of TRLA on MI and SR as well as the indirect effects on MI, MSE, and TSR. This study advances the understanding of technology-enhanced informal learning, which is an emerging perspective of technology-enhanced learning.
Exploring Family Obligation as a Buffer Between Parental Differential Treatment and Sibling Hostility
Authors: McClellan Lucy S. , Fry Cassidy M. , Telzer Eva H. , Rogers Christy R. 
Published: March 2024

AbstractHigh levels of between-sibling parental differential treatment (PDT) have been associated with several negative outomes, including externalizing behavior, emotional maladjustment, and depressive symptoms, as well as with hostility in sibling relationships. In contrast, high levels of family obligation have been associated with positive adolescent adjustment and family dynamics. Given the substantial risks associated with PDT and the benefits of family obligation for emotional health and family relations, we investigated family obligation as a potential buffer against the negative effects of PDT on sibling relationships. We hypothesized that 1) younger and older siblings experiencing higher levels of PDT would demonstrate greater sibling hostility, and 2) family obligation would buffer against these associations. Adolescent younger siblings (Mage = 12.1; 24 females) and their adolescent older siblings (Mage = 14.5; 21 females) participated in a collaborative problem-solving task, which was coded for directional expressions of hostility. Siblings also independently completed questionnaires on PDT and family obligation. Greater PDT was associated with more hostility expressed from younger sibling to older sibling, and a greater sense of family obligation buffered against this association. Greater PDT was also associated with increased hostility from older sibling to younger sibling, but no significant interaction effect was found with family obligation. Findings highlight the potential of family obligation to improve sibling relationships in the context of PDT and can inform future sibling research and family intervention work; the import of these findings is limited due to the homogeneous nature of the sample and we recommend inclusion of more diverse populations.
Product of Gaussian Mixture Diffusion Models
Authors: Zach Martin , Kobler Erich , Chambolle Antonin , Pock Thomas 
Published: March 2024

AbstractIn this work, we tackle the problem of estimating the density$$ f_X $$fXof a random variable$$ X $$Xby successive smoothing, such that the smoothed random variable$$ Y $$Yfulfills the diffusion partial differential equation$$ (\partial _t - \Delta _1)f_Y(\,\cdot \,, t) = 0 $$(∂t-Δ1)fY(·,t)=0with initial condition$$ f_Y(\,\cdot \,, 0) = f_X $$fY(·,0)=fX. We propose a product-of-experts-type model utilizing Gaussian mixture experts and study configurations that admit an analytic expression for$$ f_Y (\,\cdot \,, t) $$fY(·,t). In particular, with a focus on image processing, we derive conditions for models acting on filter, wavelet, and shearlet responses. Our construction naturally allows the model to be trained simultaneously over the entire diffusion horizon using empirical Bayes. We show numerical results for image denoising where our models are competitive while being tractable, interpretable, and having only a small number of learnable parameters. As a by-product, our models can be used for reliable noise level estimation, allowing blind denoising of images corrupted by heteroscedastic noise.
Characteristics of Ce-doped phosphate inorganic glass scintillators for gamma- and X-ray detection
Authors: Nakabayashi Yusuke , Fujimoto Yutaka , Koshimizu Masanori , Kawamoto Hiroki , Asai Keisuke 
Published: March 2024

AbstractWe report on the structural, photoluminescence (PL), and scintillation properties of Ce-doped P2O5–Al2O3–Cs2O–BaO glass scintillators having different Ce concentrations (1.96, 3.85, 7.41, 10.7, and 13.8 mol%) for gamma- and X-ray detection. The highest density (3.57 g/cm3) was achieved with Ce concentration of 13.8 mol%. The PL emission and X-ray-induced radioluminescence spectra showed emission peaks corresponding to the allowed transition from the Ce3+ 5d excited state to the 4f ground states. The highest scintillation light yields (approximately 2200 photons/MeV) were achieved with Ce concentrations of 7.41, 10.7, and 13.8 mol%. These light yields are higher than those previously reported for glasses containing heavy elements, such as Eu-doped SiO2–Al2O3–HfO2 (630 photons/MeV), Ce-doped P2O5–Li2O–GdI3–Al2O3–CaCO3 (1600 photons/MeV), and Ce-doped SiO2–Al2O3–BaF2–Gd2O3 (2050 photons/MeV). For all glasses, short scintillation decay times (28.5–34.0 ns) corresponding to the transition from the Ce3+ 5d excited state to the 4f ground states were observed. These results indicate that the fabricated glass with an optimal Ce concentration of 13.8 mol% is suitable for gamma- and X-ray detection.
A Preliminary Trial of an Early Surveillance Program for Autism and Developmental Delays within General Practices
Authors: Karlov Lisa , Masi Anne , Diaz Antonia Mendoza , Khan Feroza , Winata Teresa , Gilbert Melissa , Nair Radhika , Dissanayake Cheryl , Barbaro Josephine , Eapen Valsamma ,   Autism Surveillance Study Team, Abdullahi Ifrah , Descallar Joseph , Eastwood John , Hasan Iqbal , Jalaludin Bin , Kohlhoff Jane , Liaw S. T. , Lingam Raghu , Ong Natalie , Tam Chun Wah Michael , Unwin Katy , Williams Katrina , Woolfenden Sue 
Published: March 2024

AbstractThere are inequities in engagement with established early childhood developmental surveillance programs, eclipsing disadvantaged families. The current study sought to address this by dovetailing developmental surveillance with immunization visits and other opportunistic contacts with children at general practices). While 53 General Practices were recruited, significant COVID-19 disruptions resulted in only 81 children being screened (both parent-administered and GP completed). Of the 81 children, 11 screened positive and all of them along with 5% of screen negatives (i.e. 4 children) received clinician-administered reference-standard assessment for autism and developmental delay (DD) using Autism Diagnostic Observation Schedule (ADOS), Autism Diagnostic Interview Schedule –Revised (ADI-R), and Mullen Scales of Early Learning (MSEL). All children found by reference-standard assessment to have probable autism and/or DD had screened positive during the screening process, and 90.9% of children who screened positive were found by reference-standard assessment to have probable DD or autism. The findings provide early evidence for the feasibility and usefulness of parent completed and GP administered developmental measures during opportunistic contacts with GPs as a promising method to facilitate early identification of DD or autism.
Numerical Modeling and Open-Source Implementation of Variational Partition-of-Unity Localizations of Space-Time Dual-Weighted Residual Estimators for Parabolic Problems
Authors: Thiele J. P. , Wick T. 
Published: March 2024

AbstractIn this work, we consider space-time goal-oriented a posteriori error estimation for parabolic problems. Temporal and spatial discretizations are based on Galerkin finite elements of continuous and discontinuous type. The main objectives are the development and analysis of space-time estimators, in which the localization is based on a weak form employing a partition-of-unity. The resulting error indicators are used for temporal and spatial adaptivity. Our developments are substantiated with several numerical examples.
Fast Dimension Spectrum for a Potential with a Logarithmic Singularity
Authors: Gohlke Philipp , Lamprinakis Georgios , Schmeling Jörg 
Published: March 2024

AbstractWe regard the classic Thue–Morse diffraction measure as an equilibrium measure for a potential function with a logarithmic singularity over the doubling map. Our focus is on unusually fast scaling of the Birkhoff sums (superlinear) and of the local measure decay (superpolynomial). For several scaling functions, we show that points with this behavior are abundant in the sense of full Hausdorff dimension. At the fastest possible scaling, the corresponding rates reveal several remarkable phenomena. There is a gap between level sets for dyadic rationals and non-dyadic points, and beyond dyadic rationals, non-zero accumulation points occur only within intervals of positive length. The dependence between the smallest and the largest accumulation point also manifests itself in a non-trivial joint dimension spectrum.
Pixels and Pedagogy: Examining Science Education Imagery by Generative Artificial Intelligence
Authors: Cooper Grant , Tang Kok-Sing 
Published: March 2024

AbstractThe proliferation of generative artificial intelligence (GenAI) means we are witnessing transformative change in education. While GenAI offers exciting possibilities for personalised learning and innovative teaching methodologies, its potential for reinforcing biases and perpetuating stereotypes poses ethical and pedagogical concerns. This article aims to critically examine the images produced by the integration of DALL-E 3 and ChatGPT, focusing on representations of science classrooms and educators. Applying a capital lens, we analyse how these images portray forms of culture (embodied, objectified and institutionalised) and explore if these depictions align with, or contest, stereotypical representations of science education. The science classroom imagery showcased a variety of settings, from what the GenAI described as vintage to contemporary. Our findings reveal the presence of stereotypical elements associated with science educators, including white-lab coats, goggles and beakers. While the images often align with stereotypical views, they also introduce elements of diversity. This article highlights the importance for ongoing vigilance about issues of equity, representation, bias and transparency in GenAI artefacts. This study contributes to broader discourses about the impact of GenAI in reinforcing or dismantling stereotypes associated with science education.
Influence of climate-smart technologies on the success of livestock donation programs for smallholder farmers in Rwanda
Authors: Kandulu John M. , Zuo Alec , Wheeler Sarah , Dusingizimana Theogene , Chagunda Mizeck G. G. 
Published: March 2024

AbstractClimate change threatens the livelihoods of Sub-Saharan African farmers through increased droughts. Livestock donation programs offer a potential solution, but their effectiveness under climate stress remains unclear. This study assesses the economic viability of integrating climate-smart technologies (cowsheds and biogas plants) into these programs in Rwanda. Using a stochastic benefit–cost analysis from the beneficiary perspective, we evaluate the net gains for households receiving heifers compared to the current program. Our findings reveal that integrating climate-smart technologies significantly enhances economic viability. Households with cows and climate-smart technologies can possibly realise net benefits 3.5 times higher than the current program, with benefit–cost ratios reaching 5:1. Beyond economic benefits, adopting biogas reduces deforestation, greenhouse gas emissions, and respiratory illness risks. This study demonstrates that integrating climate-smart technologies into livestock donation programs can generate positive economic, environmental, and health benefits, leading to more resilient and sustainable smallholder systems. However, overcoming implementation challenges requires tailored policy packages addressing local barriers.
Spontaneous self-affirmation predicts more meaning and less boredom
Authors: O’Dea Muireann K. , Igou Eric R. , van Tilburg Wijnand A. P. 
Published: March 2024

AbstractChronic boredom is associated with many negative psychological outcomes, including undermining perceived meaning in life. Meanwhile, emerging research suggests that spontaneous self-affirmation, that is, an inclination to self-affirm, is linked to greater well-being and buffers against psychological threats. We investigated the relationship between spontaneous self-affirmation, perceptions of meaning in life, and boredom proneness with four correlational studies. Study 1a (N = 166) demonstrated that people inclined to self-affirm experience greater perceptions of meaning in life. Study 1b (N = 170) confirmed that spontaneous self-affirmation is associated with lower levels of boredom proneness. Study 2a (N = 214) and Study 2b (N = 105) provided evidence for our central hypothesis, showing that spontaneous self-affirmation predicts lower levels of boredom proneness via greater perceptions of meaning in life. These findings confirm that elevating meaning in life through psychological resources, like spontaneous self-affirmation, may limit boredom. Our work extends the emerging well-being benefits of spontaneous self-affirmation, by demonstrating associations with higher meaning in life and lower boredom proneness.
Fixed points and attractors of additive reaction systems
Authors: Ascone Rocco , Bernardini Giulia , Manzoni Luca 
Published: March 2024

AbstractReaction systems are discrete dynamical systems that simulate biological processes within living cells through finite sets of reactants, inhibitors, and products. In this paper, we study the computational complexity of deciding on the existence of fixed points and attractors in the restricted class of additive reaction systems, in which each reaction involves at most one reactant and no inhibitors. We prove that all the considered problems, that are known to be hard for other classes of reaction systems, are polynomially solvable in additive systems. To arrive at these results, we provide several non-trivial reductions to problems on a polynomially computable graph representation of reaction systems that might prove useful for addressing other related problems in the future.
Multi-modal Domain Adaptation Method Based on Parameter Fusion and Two-Step Alignment
Authors: Wu Lan , Wang Han , Gong Lishuang , Yao Yuan , Guo Xin , Li Binquan 
Published: March 2024

AbstractDue to the well-known domain shift problem, directly deploying a trained multi-modal classifier to a new environment usually leads to poor performance. The existing multi-modal domain adaption methods not only lack the fine-grained information of cross-modal data distribution, but also lack the cross-modal correlation research. Therefore, this paper proposes a multi-modal domain adaption method based on parameter fusion and two-step alignment (PFTS) to solve the related problems. The consistency of network parameters is used to enhance the correlation among modalities, and a higher-order moment measurement is introduced to improve the alignment of data distribution at the fine-grained level. In addition, the weighting of each modality is further carried out to achieve focused transfer. Comprehensive experiments based on multi-modal datasets with different domain adaption settings have been conducted, the results show that the precision of PFTS is 5.38% higher than state-of-the-art multi-modal domain adaption methods.