bluuebunny/crossref_metadata_2025_split huggingface dataset:
How can relational, decolonial and feminist approaches inform the EU bioeconomy?
Authors: Ramcilovic-Suominen Sabaheta , Giuntoli Jacopo , Oliver Tom , Mehta Lyla 
Published: January 2025

Abstract
In this commentary we argue that, to transform the bioeconomy sectors towards ecologically less harmful and socially fairer outcomes, the bioeconomy policy project must be questioned, re-politicised and fundamentally reframed and reinvented. We firstly identify some of the main root causes for continuity of extractivism and injustices in the bioeconomy policy and, more broadly, in the green transition (“Root causes of today’s socioecological crises and why they matter for the EU bioeconomy project” section). Secondly, we outline the largely neglected ideas and concerns emerging from relational, feminist and decolonial approaches and perspectives (“Moving beyond growth while enabling marginalised voices, knowledges, and practices that nurture web of life and wellbeing for all” section). Finally, we compile a list of 11 actions and 47 suggestions for decisionmakers, practitioners and academics to contemplate on how to cocreate bioeconomies founded on ethics of care, relationality and socioecological justice. Ultimately, the aim is to reject socioecological domination, extractivism and exploitation and foster collective wellbeing for all beings, human and other-than-human.
Doping Engineering of Sodium Vanadium Fluorophosphates Cathodes for Sodium-Ion Batteries
Authors: Kim Rakyung , Hwang Minjun , Park Ho Seok 
Published: January 2025

Abstract
Sodium-ion batteries offer a promising alternative to lithium-ion batteries due to the abundance and low cost of sodium resources. Na3V2(PO4)2F3−y
O
y
(NVPFO
y
) stands out as a cathode material with high average operating potential (~ 3.9 V vs Na+/Na), fast Na⁺ transport, and strong structural stability (minimal volumetric strain of ~ 2%). This review addresses the structural characteristics and charge storage mechanisms of NVPFO
y
, focusing on charge compensation and Na⁺/vacancy ordering. It also discusses recent advances in lattice regulation and doping strategies to enhance electrochemical properties. Finally, we highlight challenges and future directions for practical applications, emphasizing the correlation between crystal structure and performance.
Structured mathematical modelling in an authentic scientific-engineering context
Authors: Kohen Zehavit 
Published: January 2025

Abstract
This study suggests the framing of structured mathematical modelling (MM) in an authentic scientific-engineering context. Taking a task design view, structure is maintained through inherent scaffolding for the dual purpose of preserving the authenticity of the extra-mathematical context and making the adaptations required to allow incorporation of the task into the duration of a regular lesson and within the full capacity of the curriculum. Participants were 23 secondary school novice mathematics teachers and two experts who possess extensive experience in MM task design. Research tools included a reflective diary filled in by the novice teachers throughout the design process, and a task design evaluation form that was filled in by the two expert designers. Both tools aimed at identifying MM task characteristics and the alignment of the designed structured MM tasks with the MM cycle phases. Findings show the presence of all the unique characteristics that underly a quality designed MM task, with relatively low presence of openness and high presence of accessibility and authenticity from the novice teachers’ point of view. The alignment with the MM cycle was further manifest in the designed tasks, with the validation phase as being less evident compared to the other MM phases. Theoretical and practical contributions are discussed in the paper, indicating the sequentially-oriented process by which the structured MM tasks scaffold students through the MM cycle.
Classroom data science: data and dataing for making sense of multivariate plant growth
Authors: Fry Kym 
Published: January 2025

Abstract
What is considered data and how it is communicated publicly is rapidly changing. Participation in society involves multiple opportunities to engage with complex statistical concepts in media, in personal health, and regarding climate change. Children also are engaging with evolving data types in social media interactions and in educational contexts where they are the data. Yet little time is spent in classrooms supporting children to explore and make their own data decisions about various data types. This study investigates the role that fourth graders’ use of graphing conventions played in supporting their conceptual development of: non-traditional data and dataing during one lesson. The author hopes to contribute a new perspective in conceptualising dataing as enculturating statistical practices around data that involves multiple features, to communicate key information, involving tools for engaging with statistics to communicate a story. In this case study, a video clip presented an entrance point in exploring multivariate data (multiple variables). Video observation and student graphs revealed insights into children’s data and dataing experiences and processes involved with multivariate data, supported by a classroom culture that valued statistical processes as a creative and meaningful, story-telling endeavour. When students were tasked with representing plant growth using a graph, displays included a wide range of variables such as patterns of leaf growth and qualitative stages of plant growth. Engaging with multivariate data in exploratory ways supported students in this study to play with graphing conventions, establishing local mathematical practices involving non-traditional data.
A scoping review of clinical decision support systems for child and adolescent mental health
Authors: Bertie Lizél-Antoinette , McDermott Emma A. , Quiroz Juan C. , Hudson Jennifer L. 
Published: January 2025

Abstract
This scoping review maps the literature on clinical decision support systems (CDSSs) that aid clinicians in treatment decision-making for youth mental health. The objectives were to identify CDSSs used in youth mental health services, as well as grade and evaluate these systems with regard to performance, usability, and clinical utility. Electronic databases were systematically searched for publications related to the development, implementation, or evaluation of clinical decision support systems. Identified CDSSs were grouped according to user setting (primary or mental health care) and three functional areas including screening and assessment, risk prediction, and treatment recommendation. We assessed and graded the systems based on phases of evaluation, as well as the level and direction of evidence. This review identified 10 CDSSs at various stages of development and implementation used across primary and mental health care settings. Of these, one CDSS is in development phase, four have been implemented, and five have evidence of post-implementation investigations. Outside of primary care settings, few CDSSs exist to support clinicians making clinical treatment decisions for youth mental health. Availability of CDSSs is limited and country-specific. In terms of functionality, successful implementation is evident in the functional area of screening and assessment, with more work required in the functional areas of risk prediction and treatment recommendation to assist clinicians in providing youth mental health care. There is potential for machine learning in developing these functional areas.
Early Detection of Alzheimer's Disease from MR Images Using Fine-Tuning Neighborhood Component Analysis and Convolutional Neural Networks
Authors: Özaltın Öznur 
Published: January 2025

Abstract
This study develops an automatic algorithm for detecting Alzheimer's disease (AD) using magnetic resonance imaging (MRI) through deep learning and feature selection techniques. It utilizes a dataset of 6400 MRI images from Kaggle, categorized into four classes. Initially, the study employs pretrained CNN architectures—DenseNet-201, MobileNet-v2, ResNet-18, ResNet-50, ResNet-101, and ShuffleNet—for classification using five fold cross-validation, with DenseNet-201 achieving the highest accuracy of 82.11%. Due to the dataset's size and imbalance, as well as the long training times, the study aims to create a more efficient algorithm. The CNNs are used as deep feature extractors from AD images, and the extracted features are reduced using a new fine-tuning neighborhood component analysis (FTNCA) algorithm, which minimizes loss and determines the optimal tolerance value. The essential features are then classified using various machine learning algorithms, including artificial neural network (ANN), K-nearest neighbor (KNN), Naïve Bayes, and support vector machine (SVM). Experimental results reveal that reducing the feature set from 2048 to 344 allows the ResNet-50-FTNCA-KNN model to achieve 100% accuracy, significantly enhancing AD detection. This approach will aid in the early diagnosis and treatment of AD patients.
The effect of caregiver mastery on the associations of depression, anxiety, caregiver burden, fear of disease progression with quality of life among children with solid tumors
Authors: Cheng Fangfang , Gao Rui , Zhu Huanhuan , Zhang Yu , Xiong Hui , Meng Yingtao 
Published: January 2025

Abstract

Objectives
Caring for children with solid tumors (STs) can impact caregiver’s physical and mental health. Caregiver mastery, which influences psychological well-being, is vital in improving outcomes for both caregivers and children. The study aimed to investigate the relationship between caregiver mastery, anxiety, depression, fear of disease progression (FoP), caregiver burden, and the quality of life (QOL) of children with ST.

Methods
This cross-sectional study was conducted from June 2022 to April 2023 at a Grade A tertiary hospital in Shandong. Family caregivers of children with ST completed several validated measures, including the Pediatric Quality of Life Inventory (PedsQL) 3.0 Cancer Module, the Fear of Progression Questionnaire-parent version (FoP-Q-SF/PR), the Zarit Burden Interview Scale (ZBI), the hospital anxiety and depression scale (HADS), and the Caregiver Mastery Scale. Multiple linear regression analyses assessed the relationships between FoP, caregiver burden, anxiety, depression, caregiver mastery, and children’s QOL. Results were expressed as β and 95% confidence intervals (CIs).

Results
A total of 454 caregivers participated. Caregiver mastery was positively correlated with children’s QOL (β = 0.80, 95% CI: 0.20 to 1.39). Depression (β = −0.64, 95% CI: −0.83 to −0.45), anxiety (β = −0.67, 95% CI: −0.85 to −0.49), caregiver burden (β = −1.20, 95% CI: −1.60 to −0.80), and FoP (β = −0.04, 95% CI: −0.05 to −0.03) were negatively related to children’s QOL. Caregiver mastery moderated the associations between depression, caregiver burden, FoP, and children’s QOL, while also improving the effect of mild anxiety on QOL.

Significance of results
The study underscores the importance of fostering caregiver mastery to mitigate the negative impact of caregiver distress on children’s QOL and improve outcomes for both caregivers and children with solid tumors.

Conclusion
Caregiver mastery moderates the effects of anxiety, depression, FoP, and caregiver burdenon children’s QOL. Supporting caregiver mastery can alleviate caregiver burden and enhance both caregiver and child well-being.
Exploring the Influence of Morphologic Heterogeneity and Discharge on Transient Storage in Stream Systems: 1. Insights From the Field
Authors: Gambill Ian , Marshall Anna , Benson David A. , McFadden Sawyer , Navarre‐Sitchler Alexis , Wohl Ellen , Singha Kamini 
Published: January 2025

AbstractHere, we explore how differences in morphologic heterogeneity due to logjams and secondary channels drive transient storage across discharge in two stream reaches within the Front Range of Colorado, USA. During three tracer tests conducted from baseflow to near‐peak snowmelt, we collected instream fluid conductivity measurements and conducted electrical resistivity surveys to characterize tracer movement in the surface and subsurface of the stream system. The reach with two logjams and an intermittent secondary channel exhibited greater heterogeneity in surface transient storage, driving heterogeneity in hyporheic exchange flows, compared to the reach with a single logjam and a perennial secondary channel. As discharge increased, (a) backwater pools created by logjams increased in size in both systems, (b) channel complexity increased as logjams forced flow into secondary channels, and (c) subsurface flowpath distribution increased. Various transient storage indices provide some insight on solute retention but compressing data from this system into simple values was unintuitive given the noise in breakthrough‐curve tails and secondary peaks in concentration. While subsurface exchange increases with discharge in both reaches, retention may not. Flushing of subsurface tracers is highest at medium discharge as interpreted from the electrical resistivity inversions in both reaches, perhaps because of a tradeoff between the increasing extent of subsurface flowpaths with discharge and larger pressure gradients for driving flow. This work is one of the first to explore controls on exchange and retention in stream systems with multiple logjams and evolving channel planform using geophysical data to constrain the subsurface movement of solutes.
Day‐To‐Day Variability of Ionospheric Electron Temperature Revealed by High‐Resolution SYISR Observations During April–May 2022
Authors: Wang Zhongqiu , Yue Xinan , Zhou Xu , Cai Yihui , Wang Junyi , Ding Feng , He Jianhui , Wang Yonghui , Zhang Ning , Luo Junhao , Li Mingyuan , Xu Su 
Published: January 2025

AbstractThis study investigated the day‐to‐day variability of ionospheric electron temperature (Te) over Sanya using the newly built Sanya Incoherent Scatter Radar (SYISR; 18.3°N, 109.6°E, dip latitude: 12.8°N). The 24 days of observations with transmitted beams encoded by the alternating code and directed toward the zenith provided Te profiles during April–May 2022. The spatial‐temporal resolution was as precise as 4.5 km and ∼120 s. The day‐to‐day variability of Te over Sanya thus revealed, which was strong in the sunrise Te peak region (above ∼260 km, duration increases from ∼0.5 to ∼3.5 hr with altitude) and the top of the 200–300 km Te bulge (∼260 to ∼300 km, lasting from ∼09:00 LT to ∼18:30 LT). The day‐to‐day variability of Te in the two regions could reach ∼26% and ∼16% of the average Te, respectively. Although the day‐to‐day variability of Te is negatively correlated with the variation of ionospheric electron densities (Ne) in general, a positive correlation still occurred during the daytime, especially at 400–480 km from ∼17:00 LT to ∼18:00 LT. Further Thermosphere Ionosphere Electrodynamics General Circulation Model simulations reproduced the positive correlation, which may result from the internal heat exchange between electrons, ions, and neutrals. The simulations suggested that the variation of solar radiation/geomagnetic activity contributes most to the daytime/sunrise day‐to‐day variability of Te over Sanya.
Development and Application of a New Convective Entrainment Rate Parameterization for Improving Precipitation Simulation Over the Tibetan Plateau and Its Surrounding Areas
Authors: Li Junjun , Lu Chunsong , Chen Jinghua , Li Jian , Yang Jing , Xu Xiaoqi , Zhu Lei , He Xin , Wu Shiying 
Published: January 2025

AbstractThe Tibetan Plateau (TP) significantly impacts the global climate. TP's unique geographical conditions make it one of the areas with the largest precipitation biases in numerical models. The overestimation and distribution biases of precipitation in models are closely related to the parameterization of convection processes over the TP. In light of this, a new deep convective entrainment rate parameterization suitable for the region is developed based on convection observational data and is applied to the Grell‐Freitas Ensemble Scheme of the Weather Research and Forecasting Model. The new scheme significantly reduces the overestimation of simulated precipitation over the TP, decreasing the overestimation from 29.4% in the default scheme to 11.8%. The physical mechanism behind the improved simulation results is as follows: first, the entrainment rate of convection in the new scheme is closer to the observed results. Second, in terms of cloud macrophysics, the new scheme increases the convective entrainment rate, reduces the cloud top height and depth of convective clouds, and decreases the number of grids with updrafts in the vertical layers and grids with convective precipitation on the surface. Third, in terms of cloud microphysics, the increased entrainment rate reduces the cloud water content and weakens the intensity of convective precipitation. All of these mechanisms ultimately reduce the accumulated convective precipitation amount, providing an optimized modeling tool for weather and climate research over TP, which also aids in better assessing the water cycle and water resource reserves of the “Asian Water Tower.”
Predicting Transient Anomalous Transport in Two‐Dimensional Discrete Fracture Networks With Dead‐End Fractures
Authors: Sun HongGuang , Lei Dawei , Zhang Yong , Qian Jiazhong , Yu Xiangnan 
Published: January 2025

AbstractPollutant transport in discrete fracture networks (DFNs) exhibits complex dynamics that challenge reliable model predictions, even with detailed fracture data. To address this issue, this study derives an upscaled integral‐differential equation to predict transient anomalous diffusion in two‐dimensional (2D) DFNs. The model includes both transmissive and dead‐end fractures (DEFs), where stagnant water zones in DEFs cause non‐uniform flow and transient sub‐diffusive transport, as shown by both literature and DFN flow and transport simulations using COMSOL. The upscaled model's main parameters are quantitatively linked to fracture properties, especially the probability density function of DEF lengths. Numerical experiments show the model's accuracy in predicting the full‐term evolution of conservative tracers in 2D DFNs with power‐law distributed fracture lengths and two orientation sets. Field applications indicate that while model parameters for transient sub‐diffusion can be predicted from observed DFN distributions, predicting parameters controlling solute displacement in transmissive fractures requires additional field work, such as tracer tests. Parameter sensitivity analysis further correlates late‐time solute transport dynamics with fracture properties, such as fracture density and average length. Potential extensions of the upscaled model are also discussed. This study, therefore, proves that transient anomalous transport in 2D DFNs with DEFs can be at least partially predicted, offering an initial step toward improving model predictions for pollutant transport in real‐world fractured aquifer systems.
Dual targeting PD-L1 and 4-1BB to overcome dendritic cell-mediated lenalidomide resistance in follicular lymphoma
Authors: Zheng Zhong , Wang Jian-Biao , Sun Rui , Wang Nan , Weng Xiang-Qin , Xu Tian-Yuan , Fu Di , Feng Yan , Xu Peng-Peng , Cheng Shu , Wang Li , Zhao Yan , Qu Bin , Huang Chuan-Xin , Zhao Wei-Li 
Published: January 2025

Abstract
Immunomodulatory agent lenalidomide is effective in treating follicular lymphoma (FL). We conducted the first trial of immunotherapy rituximab plus lenalidomide in newly diagnosed FL in China (NCT03715309). One-hundred and fifteen patients were enrolled and treated with rituximab 375 mg/m2 intravenously on day 0 and lenalidomide 25 mg orally on day 1–10 for 6 cycles of induction treatment, as well as lenalidomide for 6 cycles and rituximab for 8 cycles of maintenance treatment. We found that inferior progression-free survival of the patients was significantly associated with elevated serum β2m and lymph node >6 cm, linking to decreased lymphoma cell autophagy and dendritic cell infiltration within the tumor microenvironment. PU.1 transcriptionally downregulated PD-L1 (Programmed death ligand 1) expression and upregulated 4-1BBL (4-1BB ligand) expression, increased lymphoma cell autophagy and dendritic cell maturation via PD-1/PD-L1 and 4-1BB/4-1BBL interaction. In vitro in co-culture system and in vivo in murine xenograft model, knockdown of PU.1 induced lenalidomide resistance, but sensitized FL cells to bi-specific PD-L1/4-1BB antibody or combined treatment of PD-L1 inhibitor and 4-1BB agonist. Collectively, PU.1 is essential in immunomodulatory effect of FL through PD-1/PD-L1- and 4-1BB/4-1BBL-mediated microenvironmental modulation. Dual targeting PD-L1 and 4-1BB could be an alternative immunotherapeutic strategy in the chemo-free era of FL treatment.
Isoxazole-based molecules restore NK cell immune surveillance in hepatocarcinogenesis by targeting TM4SF5 and SLAMF7 linkage
Authors: Kim Ji Eon , Kim Hyun Su , Kim Wonsik , Lee Eun Hae , Kim Soyeon , Kim Taewoo , Shin Eun-Ae , Pyo Kyung-hee , Lee Haesong , Jin Seo Hee , Lee Jae-Ho , Byeon Soo-Min , Kim Dong Joo , Jeong Jinwook , Lee Jeongwon , Ohn Minjae , Lee Hyojung , Yu Su Jong , Shin Dongyun , Kim Semi , Yoo Jun Yeob , Lee Seung-Chul , Suh Young-Ger , Lee Jung Weon 
Published: January 2025

Abstract
Dynamic communication between hepatocytes and the environment is critical in hepatocellular carcinoma (HCC) development. Clinical immunotherapy against HCC is currently unsatisfactory and needs more systemic considerations, including the identification of new biomarkers and immune checkpoints. Transmembrane 4 L six family member 5 (TM4SF5) is known to promote HCC, but it remains unclear how cancerous hepatocytes avoid immune surveillance and whether avoidance can be blocked. We investigated how TM4SF5-mediated hepatic tumorigenesis avoids surveillance by natural killer (NK) cells, which are prevalent in the liver, and whether the avoidance can be blocked by anti-TM4SF5 agents. We used comprehensive structure activity relationship analysis to identify TM4SF5-specific isoxazole (TSI)-based small molecules that inhibit TM4SF5-mediated effects. TM4SF5 expressed by hepatocytes reduced NK cell cytotoxicity by downregulating stimulatory ligands/receptors, including signaling lymphocytic activation molecule family member 7 (SLAMF7). TM4SF5 bound SLAMF7 depending on N-glycosylation and caused intracellular trafficking of SLAMF7 from the plasma membrane to lysosomes for degradation. TSI treatments in cell lines and animal models of HCC blocked this binding, intracellular trafficking, and downregulation, resulting in higher levels of stimulatory NK cell ligands. In mouse xenograft models, TSI treatment abrogated HCC development by increasing the abundance and dispersion of Slamf7-positive cells in liver tissues, recapitulating the phenotype of Tm4sf5-knockout mice and indicating TSI-mediated restoration of NK cell surveillance. These findings suggest that TSIs can inhibit TM4SF5-mediated liver carcinogenesis by increasing NK cell surveillance.