bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of protected areas for a colonial-breeding waterbird in a fragmented landscape throughout its annual cycle
Authors: Ferreira Hugo R. S. , Alves José A. , Jiguet Frédéric , Duriez Olivier , Blanchon Thomas , Lok Tamar , Champagnon Jocelyn 
Published: December 2024

Abstract

Context
Throughout their annual cycle and life stages, animals depend on a variety of habitats to meet their vital needs. However, habitat loss, degradation, and fragmentation are making it increasingly difficult for mobile species such as birds to find suitable habitats. Wetlands are highly productive systems of great importance to many animals, but their continued degradation threatens their capacity to support different species, including waterbirds. In this context, waterbirds are likely to benefit not only from the creation and management of protected wetlands, but also from the existence of anthropogenic wetlands, managed for economic or recreational activities.

Objectives
We investigated the habitat use of Eurasian spoonbills within an extensive and heterogeneous area in Southern France, and how it varies across the annual cycle and for different age classes.

Methods
We tracked 91 spoonbills of different ages throughout their annual cycle and tested for overall differences in the use of strongly protected areas in Camargue between periods and age classes. Additionally, we identified the main sites used and their management practices.

Results
Our study shows that privately managed wetland areas play a complementary role to strongly protected areas: they may provide spoonbills (and other waterbirds) with suitable foraging habitat at certain periods of the year when these are less available in strongly protected areas.

Conclusions
This study illustrates how the spoonbill, a moderately specialized species, is benefiting from current global changes due to its ability to use suitable habitats, natural and artificial, in fragmented landscapes. Nevertheless, reliance on privately managed wetland areas may have serious consequences for species that are highly dependent on them, and thus, habitat management promoting natural conditions may be crucial to maintain species resilience. It is therefore essential to understand how specific management actions may affect waterbird presence and habitat use, not only to enhance the effectiveness of conservation efforts, but also to promote wetland connectivity and species resilience, particularly in fragmented landscapes.
Trends in Income and Well-Being Inequality During the COVID-19 Pandemic in Japan
Authors: Ishii Kayoko , Yamamoto Isamu 
Published: December 2024

AbstractAlthough the COVID-19 pandemic could have caused both monetary and non-monetary distributional changes, existing studies have only investigated its immediate monetary impacts. This study examines the pandemic’s medium-term impacts on income and well-being inequality using individual longitudinal data from the Japan Household Panel Survey. Gini coefficients and income mobility before and after the pandemic are calculated to analyze income inequality. Various well-being measures such as mental health and life satisfaction are used to analyze well-being inequality. The findings reveal no increase in income inequality. Progressive income growth ensured stable inequality throughout the pandemic. Conversely, on average, well-being worsened, and well-being inequality increased. Furthermore, we find an association between income and well-being inequality. The random-effects and fixed-effects models indicate that the well-being of the high-income group tended to improve, whereas that of the low-income group tended to deteriorate after the outbreak of the pandemic. Additionally, the causal mediation analysis shows that the adoption of remote work served as a factor for the increase in the well-being of people in the high-income group. Remote work became disproportionately prevalent during the pandemic, especially among people in the higher income group. This group experienced various benefits of remote work, which contributed to an improvement in their well-being and an increase in well-being inequality.
Pore-space partitioning in geological porous media using the curvature of the distance map
Authors: Ben-Noah Ilan , Hidalgo Juan J. , Dentz Marco 
Published: December 2024

Abstract
Media classification and the construction of pore network models from binary images of porous media hinges on accurately characterizing the pore space. We present a new method for (i) locating critical points, that is, pore body and throat centers, and (ii) partitioning of the pore space using information on the curvature of the distance map (DM) of the binary image. Specifically, we use the local maxima and minima of the determinant map of the Hessian matrix of the DM to locate the center of pore bodies and throats. The locating step provides structural information on the pore system, such as pore body and throat size distributions and the mean coordination number. The partitioning step is based on the eigenvalues of the Hessian, rather than the DM, to characterize the pore space using either watershed or medial-axis transforms. This strategy eliminates the common problem of saddle-induced over-partitioning shared by all traditional marker-based watershed methods and represents an alternative method to determine the skeleton of the pore space without the need for morphological reconstruction.
Coenzyme Q10 Attenuates Kidney Injury Induced by Titanium Dioxide Nanoparticles and Cadmium Co-exposure in Rats
Authors: Abd-Elhakim Yasmina M. , Hashem Mohamed M. M. , Abo-EL-Sooud Khaled , El-metawally Abeer E. , Hassan Bayan A. 
Published: December 2024

AbstractThis study examined the possible defensive role of coenzyme Q10 (CQ10) against the impact of cadmium (Cd) and titanium dioxide nanoparticle (TNP) exposure on rat kidneys. Distilled water (1 mL/rat), corn oil (1 mL/rat), 10 mg CQ10/kg b.wt, 50 mg TNP/kg b.wt, 5 mg Cd/kg b.wt, TNP + Cd, or TNP + Cd + CQ10 was administered orally to seven groups of 70 male Sprague Dawley rats for 60 days. The findings demonstrated that TNP and/or Cd exposure considerably raised serum levels of several renal damage products, disturbed electrolyte balance including sodium, potassium, and calcium, decreased antioxidant enzyme concentration in the kidneys, and elevated malondialdehyde. In addition, rats exposed to TNP and/or Cd had significantly higher levels of renal titanium and Cd. In addition, rats exposed to TNP and/or Cd showed significant histopathological lesions and collagen deposition as revealed by H and E and Masson trichrome staining, respectively. The kidneys were severely damaged by the combined effects of TNP and Cd, although CQ10 greatly mitigated these effects. According to the study, exposure to TNP and Cd can damage the kidneys’ function and structure, especially when combined. However, CQ10 can protect against TNP and Cd’s nephrotoxic effects.
Low-cost predictive models of dementia risk using machine learning and exposome predictors
Authors: Camacho Marina , Atehortúa Angélica , Wilkinson Tim , Gkontra Polyxeni , Lekadir Karim 
Published: December 2024

Abstract
Purpose
Diagnosing dementia, affecting over 55 million people globally, is challenging and costly, often leading to late-stage diagnoses. This study aims to develop early, accurate, and cost-effective dementia screening methods using exposome predictors and machine learning. We investigate whether low-cost exposome predictors combined with machine learning models can reliably identify individuals at risk of dementia.

Methods
We analyzed data from 500,000 UK Biobank participants, selecting 1523 diagnosed with dementia and an equal number of healthy controls, matched by age and sex. A total of 3046 participants were included: 2740 for internal validation and 306 for external validation. We used 128 low-cost exposome factors from baseline visits, imputed missing data, and assessed two predictive models: a classical logistic regression and a machine learning ensemble classifier (XGBoost). Feature importance was estimated within the predictive models.

Results
The XGBoost model outperformed the logistic regression model, achieving a mean AUC of 0.88 in external validation. We identified novel exposome factors that might be combined as potential markers for dementia, such as facial aging, the frequency of use of sun/ultraviolet light protection, and the length of mobile phone use.

Conclusions
Machine learning models utilizing exposome data can reliably identify individuals at risk of dementia, with XGBoost showing superior performance. This approach highlights the potential of low-cost, readily available exposome factors as markers for dementia. Future studies should validate these findings in diverse populations and explore the integration of additional exposome factors to enhance prediction accuracy.
Rayleigh-based crack monitoring with distributed fiber optic sensors: experimental study on the interaction of spatial resolution and sensor type
Authors: Herbers Max , Richter Bertram , Marx Steffen 
Published: December 2024

AbstractCracks can negatively affect the durability of concrete structures, making effective crack monitoring crucial for maintenance. Utilizing coherent optical frequency domain reflectometry, it is possible to accurately localize cracks and measure their widths. However, long distributed fiber optic sensors (DFOS) lengths, required for structural health monitoring applications, are accompanied by a reduced spatial resolution due to technical limitations of the interrogator. This study investigates the impact of spatial resolution on signal quality in areas with large strain gradients and demonstrates its implications for crack monitoring. First, tensile tests were conducted on a calibration rig to determine the measurable strain gradient for different gage pitches (gps) and further influencing parameters. Subsequently, four types of DFOS – categorized as robust and filigree – were installed on a 4 m long reinforced concrete beam subjected to a 4-point bending test. Crack widths up to 0.5 mm were measured with varying gps to assess how spatial resolution affects crack width calculations. The results indicate that a reduced spatial resolution impairs the ability to accurately record regions with large strain gradients, leading to diminished signal quality and reduced measurable crack widths. While strain gradients of approximately $$1500\,\upmu \varepsilon$$

1500

μ
ε

/mm could be measured with the finest gp of 0.65 mm, this threshold dropped to about $$60\,\upmu \varepsilon$$

60

μ
ε

/mm for a gp of 5.20 mm. For the DFOS/adhesive combinations tested, and at the highest spatial resolution available for sensor lengths greater than 50 m (gp = 2.60 mm), reliable crack monitoring of crack widths larger than 0.2 mm was not possible. This limitation poses challenges for practical applications. A method for determining the required gp based on the expected crack width and the DFOS/adhesive combination used is proposed to ensure reliable crack monitoring.
Particle Current in Double-Path Josephson Junction under Rashba Interaction Connected to Bose-Einstein Condensate Reservoirs
Authors: Kawaguchi Satoshi 
Published: December 2024

AbstractWe investigate the properties of a double-path Josephson junction connected to Bose-Einstein condensate reservoirs. By comparing the current in the proposed setup with that in a similar system connected to superconductors, we elucidate the key differences between the two systems. The systems are influenced by the Aharonov-Bohm effect, Rashba spin-orbit interaction, and phase difference of order parameters between left and right leads. Utilizing the Keldysh formalism, it turns out that, in the system connected to Bose-Einstein condensate reservoirs, the Josephson current includes higher frequency components of the phase difference between left and right reservoirs. Additionally, the dependence of critical current on energy level does not show the complete symmetric resonance but the Fano-type resonance with single or double peaks. These differences result from the bosonic statistics of reservoirs.
Impact of climate change on water resources in the Yarmouk River Basin of Jordan
Authors: Bashabsheh Abdelaziz Q. , Alzboon Kamel K. 
Published: December 2024

AbstractUnderstanding the impact of climate change on water resources is important for developing regional adaptive water management strategies. This study investigated the impact of climate change on water resources in the Yarmouk River Basin (YRB) of Jordan by analyzing the historical trends and future projections of temperature, precipitation, and streamflow. Simple linear regression was used to analyze temperature and precipitation trends from 1989 to 2017 at Irbid, Mafraq, and Samar stations. The Statistical Downscaling Model (SDSM) was applied to predict changes in temperature and precipitation from 2018 to 2100 under three Representative Concentration Pathway (RCP) scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5), and the Soil and Water Assessment Tool (SWAT) was utilized to estimate their potential impact on streamflow at Addasiyia station. Analysis of data from 1989 to 2017 revealed that mean maximum and minimum temperatures increased at all stations, with average rises of 1.62°C and 1.39°C, respectively. The precipitation trends varied across all stations, showing a significant increase at Mafraq station, an insignificant increase at Irbid station, and an insignificant decrease at Samar station. Historical analysis of streamflow data revealed a decreasing trend with a slope of −0.168. Significant increases in both mean minimum and mean maximum temperatures across all stations suggested that evaporation is the dominant process within the basin, leading to reduced streamflow. Under the RCP scenarios, projections indicated that mean maximum temperatures will increase by 0.32°C to 1.52°C, while precipitation will decrease by 8.5% to 43.0% throughout the 21st century. Future streamflow projections indicated reductions in streamflow ranging from 8.7% to 84.8% over the same period. The mathematical model results showed a 39.4% reduction in streamflow by 2050, nearly double the SWAT model’s estimate under RCP8.5 scenario. This research provides novel insights into the regional impact of climate change on water resources, emphasizing the urgent need to address these environmental challenges to ensure a sustainable water supply in Jordan.
A note on surfaces with constant angle intersection in Riemannian manifolds
Authors: Meléndez Josué , Rodríguez-Romero Eduardo 
Published: December 2024

AbstractWe study ruled surfaces that intersect with constant angle a surface M in a Riemannian manifold $$\bar{M}^3$$

M

¯

3

, thus extending some results recently given in (Meléndez and Rodríguez-Romero in Differ Geom Appl 91:102063, 2023). We also deal with normal and tangent submanifolds of arbitrary dimension, giving some properties about them.
Critical policy analysis of Indigenous knowledges and perspectives within health and physical education: moving beyond the past
Authors: Bonato Graeme 
Published: December 2024

AbstractThe ideology of a national curriculum is to facilitate and nurture a nation’s aspirations for future generations. The curriculum must provide a balance between recognition of cultural history and global contexts for 21st century learners. However, what constitutes effective policy reform to achieve future goals is always open to debate. Over the past decade, the Australian Professional Teacher Standards have increasingly emphasised the requirement for educators to demonstrate enhanced knowledge and understanding of Aboriginal and Torres Strait Islander peoples, their histories, and cultures. As such, there has been a renewed focus to ensure that Indigenous knowledges and perspectives are embedded and ultimately enacted within the Australian Curriculum: Health and Physical Education (AC: HPE). A critical policy analysis was undertaken to investigate the evolution of the effectiveness and representation of Indigenous knowledges and perspectives within the AC: HPE Version 9 and to explore tensions arising from an Indigenous standpoint. The findings revealed evidence of cultural inclusiveness and reconciliation discourse across the curriculum context (within the content elaborations), albeit with varying degrees of prominence in each and with particular emphasis of specific contexts. Examination of the curricula yielded three primary tensions: (i) Disruption of Western ideologies; (ii) Indigenous self-determination; and (iii) Power dynamics. A positive contribution to the field, revealing a lack of substantive progress with embedding Indigenous knowledges and perspectives within HPE, the results of this study provide direction for policy makers and curriculum developers when further incorporating Indigenous knowledges and perspectives within the AC: HPE.
K-hyperparameter tuning in high-dimensional genomics using joint optimization of deep differential evolutionary algorithm and unsupervised transfer learning from intelligent GenoUMAP embeddings
Authors: Gikera Rufus , Maina Elizaphan , Mambo Shadrack Maina , Mwaura Jonathan 
Published: December 2024

AbstractK-hyperparameter optimization in high-dimensional genomics remains a critical challenge, impacting the quality of clustering. Improved quality of clustering can enhance models for predicting patient outcomes and identifying personalized treatment plans. Subsequently, these enhanced models can facilitate the discovery of biomarkers, which can be essential for early diagnosis, prognosis, and treatment response in cancer research. Our paper addresses this challenge through a four-fold approach. Firstly, we empirically evaluate the k-hyperparameter optimization algorithms in genomics analysis using a correlation based feature selection method and a stratified k-fold cross-validation strategy. Secondly, we evaluate the performance of the best optimization algorithm in the first step using a variety of the dimensionality reduction methods applied for reducing the hyperparameter search spaces in genomics. Building on the two, we propose a novel algorithm for this optimization problem in the third step, employing a joint optimization of Deep-Differential-Evolutionary Algorithm and Unsupervised Transfer Learning from Intelligent GenoUMAP (Uniform Manifold Approximation and Projection). Finally, we compare it with the existing algorithms and validate its effectiveness. Our approach leverages UMAP pre-trained special autoencoder and integrates a deep-differential-evolutionary algorithm in tuning k. These choices are based on empirical analysis results. The novel algorithm balances population size for exploration and exploitation, helping to find diverse solutions and the global optimum. The learning rate balances iterations and convergence speed, leading to stable convergence towards the global optimum. UMAP’s superior performance, demonstrated by short whiskers and higher median values in the comparative analysis, informs its choice for training the special autoencoder in the new algorithm. The algorithm enhances clustering by balancing reconstruction accuracy, local structure preservation, and cluster compactness. The comprehensive loss function optimizes clustering quality, promotes hyperparameter diversity, and facilitates effective knowledge transfer. This algorithm’s multi-objective joint optimization makes it effective in genomics data analysis. The validation on this algorithm on three genomic datasets demonstrates superior clustering scores. Additionally, the convergence plots indicate relatively smoother curves and an excellent fitness landscape. These findings hold significant promise for advancing cancer research and computational genomics at large.
The Effect of Concrete and Virtual Manipulative Blended Instruction on Mathematical Achievement for Elementary School Students
Authors: Siller Hans-Stefan , Ahmad Sagheer 
Published: December 2024

AbstractMathematics has been crucial to learning and extending the frontiers of knowledge in all academic areas. At the elementary level, several teaching approaches have been implemented to improve students’ mathematical achievement. However, compared to traditional teaching exposition techniques, the teaching with the use of math manipulatives has been found useful to enhance mathematical achievement. The current quasi-experimental study was carried out with Pakistani students, and aimed to explore the blended effect of concrete and virtual manipulatives on fifth-graders’ mathematical achievement. Different mathematical concepts such as whole number, decimals and percentages, fraction, unitary method, perimeter, area, and geometry from a grade 5 textbook were targeted for the intervention period. Following randomization, one section from a public school was chosen as a control group and the other section classified as an experimental group. The mathematical achievement of fifth graders was measured through mathematics achievement test (MAT), developed, and piloted for this particular study, in a pre–posttest design. The data were analysed using one-way ANCOVA and mixed between-within ANOVA test to examine the significant differences, if any exist, in pretest/posttest scores between and within the groups over the period of intervention. The results revealed blended use of concrete and virtual manipulatives significantly enhances students’ mathematical achievement as compared to the results achieved from traditional instruction. This study offers information for teachers and students to incorporate concrete and virtual manipulatives simultaneously in mathematics lessons.
Decolonizing AI ethics in Africa’s healthcare: An ethical perspective
Authors: Grancia Mugalula Kalule 
Published: December 2024

AbstractOwing to the ethical tension between the ethics frameworks developed in the Global North and the African understanding of ethics, health, and care, decolonization can be a useful tool through which Artificial Intelligence (AI) ethics is understood and applied in Africa. While existing AI ethics frameworks often reflect Western values and perspectives like individuality, the African setting is still largely communalist. Thus, the current frameworks, developed in the Global North, need to be interpreted in the African context to represent the values of people in Africa. It is then that they will be suitable for addressing the healthcare challenges in Africa today. Challenges like resource constraints, coloniality and the paternalism of the Global North toward the Global South have put Africa at the periphery of the AI Ethics debate. This article discusses the need to “decolonize” AI ethics to ensure just, equitable, and inclusive AI in healthcare in Africa. It critiques the current ethical frameworks largely developed from the Global North in shaping ethical AI development in Africa, calling for the decolonization of ethical principles. The paper discusses key considerations for a decolonized approach in healthcare and proposes key principles that can ensure an approach rooted in African contexts and values.