bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fast and Memory-Efficient Approximate Minimum Spanning Tree Generation for Large Datasets
Authors: Almansoori Mahmood K. M. , Meszaros Andras , Telek Miklos 
Published: June 2024

AbstractConventional minimum spanning tree (MST) algorithms typically start by creating a distance matrix of the $$n(n-1)/2$$

n
(
n
-
1
)
/
2

pairs of data points, leading to a time complexity of $$O(n^2)$$

O
(

n
2

)

. This initial step poses a computational bottleneck. To overcome this limitation, we present a novel method that constructs an initial random k-neighbor graph and optimizes this graph by employing a crawling technique to efficiently approximate the k Nearest Neighbors (kNN) graph. This crawling approach allows us to approximate the closest neighbors of each node. Subsequently, the approximate kNN graph is utilized to build an initial approximate MST and iteratively refine it by the same crawling process. Using this approach, an approximate MST can be obtained for a data set of size n with empirical cost around $$O(n^{1.07})$$

O
(

n

1.07

)

and a minimal O(n) memory consumption. In contrast to spatial tree-based approaches, the presented method also scales well to high dimensional data. We have shown that the proposed approach achieves such a level of performance with only a marginal accuracy reduction between 0.5% and 6%. These qualities make it an excellent candidate for approximate MST calculation for high-dimensional, large data sets.
Positioning the notion of group in children’s learning: an Australian study
Authors: Guo Karen , Nolan Andrea , Lanting Carole 
Published: June 2024

Abstract
Current research and literature emphasize the crucial role of group experiences in children’s learning during early childhood. However, despite the frequent use of the term ‘group’, little attention has been paid to its position in children’s learning and the diverse perspectives that inform it. This study addressed this gap by applying a tri-partite lens, considering the perspectives of young children, parents and teachers in three preschools in Australia. We defined group broadly as any social context within preschool environments. Data were collected through focus group discussions with 24 children, individual interviews with six teachers and questionnaires completed by 48 parents in the preschools. The findings have conceptualised group as a complex interweaving of various elements, involving the dynamic tensions and relationships between children’s needs and adults’ expectations and practices. Central to this is the exploration of self and others, and an understanding of how children's desires for togetherness and belonging could stimulate thinking about what it means to be learning in groups.
A Lifetime of Work on Defect Modelling for Luminescence
Authors: Townsend Peter D. , Wang Yafang 
Published: June 2024

AbstractTo fully appreciate the contributions of Professor Watanabe to studies of luminescence, it is important to recall how, during his lifetime, not only have experimental facilities changed dramatically, but also there have been (and still are) many conflicting models as to the relevant lattice sites. This current overview summarises some of these factors. Indeed, several powerful early techniques have gone into abeyance, but there is a real potential benefit in resurrecting them. Equally, early key experiments on the existence of long-range interactions are frequently ignored, to the detriment of many models of lattice sites related to luminescence. Despite difficulties with defect site models and understanding luminescence processes, empirical data have nevertheless been effective in many applications from archaeological dating, luminescence dosimetry, and the development of modern phosphors for use across a wide range of modern applications. Improved models that include long-range features will inevitably add to this empirical progress.
Navigating Postpartum Weight Loss: Evidence and Interventions
Authors: Dellapiana Gabriela , Nguyen Quy Tu , Naqvi Mariam 
Published: June 2024

Abstract
Purpose of Review
Postpartum weight retention increases the risk for adverse obstetric outcomes in subsequent pregnancies, childhood obesity, and long-term metabolic and cardiovascular disease for the birthing person. This review examines recent evidence for the efficacy of various weight loss interventions to address this issue.

Recent Findings
Combining exercise with caloric restriction is more effective to reduce weight after childbirth than either intervention alone. Weight loss medications like GLP-1 agonists, while becoming more widely prescribed, require continuous use for optimal results and should be discontinued before attempting pregnancy. In 2022, indications for metabolic and bariatric surgery were updated to include BMI ≥ 35 kg/m2 and BMI 30–34.9 kg/m2 with metabolic disease that is refractory to medical interventions for weight loss.

Summary
A multimodal approach is recommended to support postpartum weight loss including, but not limited to, nutrition counseling and physical activity interventions. Weight loss medications and bariatric surgery are recommended adjuncts for patients who are otherwise unable to meet their weight loss goals.
Transplantation of Neural Progenitor Cells Derived from Stem Cells from Apical Papilla Through Small-Molecule Induction in a Rat Model of Sciatic Nerve Injury
Authors: Koh Junhao , Liu Junqing , Poon Chi Him , Kang Jun , Basabrain Mohammed S. , Lim Lee Wei , Zhang Chengfei 
Published: June 2024

Abstract
Background:
Stem cell-based transplantation therapy holds promise for peripheral nerve injury treatment, but adult availability is limited. A cell culture protocol utilizing a small-molecule cocktail effectively reprogrammed stem cells from apical papilla (SCAPs) into neural progenitor cells, subsequently differentiating into neuron-like cells. This study aims to evaluate neural-induced SCAPs, with and without small-molecule cocktail, for sciatic nerve repair potential.

Methods:
A scaffold-free cell sheet technique was used to construct a three-dimensional cell sheet. Subsequently, this cell sheet was carefully rolled into a tube and seamlessly inserted into a collagen conduit, which was then transplanted into a 5 mm sciatic nerve injury rat model. Functional sciatic nerve regeneration was evaluated via toe spread test, walking track analysis and gastrocnemius muscle weight. Additionally, degree of sciatic nerve regeneration was determined based on total amount of myelinated fibers.

Results:
Small-molecule cocktail induced SCAPs enhanced motor function recovery, evident in improved sciatic function index and gastrocnemius muscle retention. We also observed better host myelinated fiber retention than undifferentiated SCAPs or neural-induced SCAPs without small-molecule cocktail. However, clusters of neuron-like cell bodies (surrounded by sparse myelinated fibers) were found in all cell sheet-implanted groups in the implantation region. This suggests that while the implanted cells likely survived transplantation, integration was poor and would likely hinder long-term recovery by occupying the space needed for host nerve fibers to project through.

Conclusion:
Neural-induced SCAPs with small-molecule cocktail demonstrated promising benefits for nerve repair; further research is needed to improve its integration and optimize its potential for long-term recovery.
The Menstrual Health Manager (MHM): A Resource to Reduce Discrepancies Between Science and Practice in Sport and Exercise
Authors: Badenhorst Claire E. 
Published: June 2024

AbstractInadequate research on female health and performance; the complexity of the research; low menstrual health literacy of athletes, coaches, and support staff; and ethical and cultural sensitivities are all recognized as barriers to effective health monitoring for females in sports. Frameworks have been developed for academics to follow to help improve the quality of female-specific research. However, a similar resource that enables correct terminology, and use of health monitoring techniques has not been provided for sporting organizations, coaches, support staff or athletes. Therefore, this critical commentary presents a new resource, the Menstrual Health Manager. This resource may be used to determine the level of menstrual health monitoring detail that may be used by organisations, coaches or athletes, and specifies what reproductive health details the data will provide. This resource aims to provide organizations and coaches with a means of understanding the data that inform their decisions for female athletes. Utilization of this resource may aid in the consistent use of terminology and methods for female-specific health monitoring in both sports and research.
The Environmental Costs of Artificial Intelligence for Healthcare
Authors: Katirai Amelia 
Published: June 2024

AbstractHealthcare has emerged as a key setting where expectations are rising for the potential benefits of artificial intelligence (AI), encompassing a range of technologies of varying utility and benefit. This paper argues that, even as the development of AI for healthcare has been pushed forward by a range of public and private actors, insufficient attention has been paid to a key contradiction at the center of AI for healthcare: that its pursuit to improve health is necessarily accompanied by environmental costs which pose risks to human and environmental health—costs which are not necessarily directly borne by those benefiting from the technologies. This perspective paper begins by examining the purported promise of AI in healthcare, contrasting this with the environmental costs which arise across the AI lifecycle, to highlight this contradiction inherent in the pursuit of AI. Its advancement—including in healthcare—is often described through deterministic language that presents it as inevitable. Yet, this paper argues that there is need for recognition of the environmental harm which this pursuit can lead to. Given recent initiatives to incorporate stakeholder involvement into decision-making around AI, the paper closes with a call for an expanded conception of stakeholders in AI for healthcare, to include consideration of those who may be indirectly affected by its development and deployment.
Moving beyond Technical Issues to Stakeholder Involvement: Key Areas for Consideration in the Development of Human-Centred and Trusted AI in Healthcare
Authors: Kaye Jane , Shah Nisha , Kogetsu Atsushi , Coy Sarah , Katirai Amelia , Kuroda Machie , Li Yan , Kato Kazuto , Yamamoto Beverley Anne 
Published: June 2024

AbstractDiscussion around the increasing use of AI in healthcare tends to focus on the technical aspects of the technology rather than the socio-technical issues associated with implementation. In this paper, we argue for the development of a sustained societal dialogue between stakeholders around the use of AI in healthcare. We contend that a more human-centred approach to AI implementation in healthcare is needed which is inclusive of the views of a range of stakeholders. We identify four key areas to support stakeholder involvement that would enhance the development, implementation, and evaluation of AI in healthcare leading to greater levels of trust. These are as follows: (1) aligning AI development practices with social values, (2) appropriate and proportionate involvement of stakeholders, (3) understanding the importance of building trust in AI, (4) embedding stakeholder-driven governance to support these activities.
Power and Personal Experience in Online Anonymous Communities: A Corpus-Driven Exploration
Authors: Busso Lucia 
Published: June 2024

AbstractThe paper presents an innovative corpus study on Personal Experience as a pragmatic-discursive resource to express power in anonymous online interactions. Specifically, we explore a corpus-driven methodology to extract lexico grammatical features typical of Personal Experience in representative samples (around 160,000 words) of 3 online fora. The method is rooted in Part of Speech and semantic domain keyness (Rayson in Int J Corpus Linguist 13(4):519–549, 2008), which we combine in Corpus Language Queries to extract statistically relevant patterns in the data. Results show that the 3 datasets share a “core” set of key lexico-grammatical features. Furthermore, our findings align with the scientific literature exploring personal experiences and narratives in many different genres. This strongly supports the idea that our inductive protocol can be reliably used to break down the discursive textual function of Personal Experience into lower-level, scalable features. In other words, we suggest that our method can be used to extract “form” (i.e. lexical, grammatical, and syntactical units) from “function” (i.e. pragmatic and discursive annotations). Findings are discussed in the context of language and power in online interactions and in the context of building automatic feature detectors for the analysis of larger cross-genre corpora.
Enhancing mechanical properties of aluminium 6063 with crab shell particle reinforcement
Authors: Owa Adebayo Felix , Olubambi Peter Apata 
Published: June 2024

AbstractThe versatility and beneficial properties of aluminium 6063 make it an excellent material for various applications, but limited in engineering production where strength is a major material selection factor. The utilization of natural resources in material science has gained prominence due to the quest for sustainable and innovative materials. This work explores the development and characterization of an aluminium matrix composite reinforced with crab shell particles (CSPs). The CSPs are produced via the milling process for 72 h and the CSPs are incorporated in varying percentages (0–20 wt%) into the aluminium matrix using a stir casting technique, the mechanical properties (tensile strength, compressive strength, % elongation, and impact energy) of the composites are determined using an Instron universal testing machine (UTM) and a Charpy impact testing machine, respectively. A scanning electron microscope (SEM) is used to examine the microstructure of the composite fracture surfaces and Gywddion 2.65 software is used to view the SEM images of the fracture surfaces in three dimensions (3D). The results revealed that tensile strength, compressive strength, % elongation, and impact energy are enhanced by adding varying percentages of CSPs on the aluminium 6063 composites.
Young Adult Mental Health Problem Incidence Varies by Specific Combinations of Adverse Childhood Experiences
Authors: Agrawal Juhee , Lei Yvonne , Shah Vivek , Bui Anthony L. , Halfon Neal , Schickedanz Adam 
Published: June 2024

Abstract
Adverse childhood experiences (ACEs) have been shown to impact mental health. Risk associated with ACEs is commonly estimated based on counts from the conventional ACE types, but ACEs may not all carry the same health risk, either individually or in combination. Evidence is needed to understand the health impact of different ACE types and combinations of ACE types. We aimed to assess variation in risk of mental illness diagnosis and severe psychological distress in young adulthood based on differences in exposure to individual ACEs and combinations of ACEs, which can improve precision of ACE-based risk assessment. We used data from six waves of the Transition to Adulthood Supplement (2007–2017; n = 1832 young adults ages 18–28) of the Panel Study of Income Dynamics. We used logistic regression with cluster-robust variation estimation to test associations between each ACE, pairwise combinations of ACEs, and outcomes including new or existing mental illness diagnoses and severe psychological distress. Individual ACEs associated with greatest risk for new or existing mental illness diagnoses and severe psychological distress were parental mental illness and sexual abuse. Combinations of ACEs associated with greatest risk were parental mental illness-plus-sexual abuse and parental mental illness-plus-emotional neglect. ACEs associated with the lowest risk were parental substance use, physical abuse, and household violence. In this nationally representative longitudinal study of mental health outcomes in young adults, different individual and combinations of ACEs were associated with varying levels of mental health risk. This carries implications for risk assessment and ACE intervention prioritization.
Clinical and Imaging Characteristics of Herlyn-Werner-Wunderlich Syndrome: a Comprehensive Analysis
Authors: Qi Jiani , Zhou Ping , Peng Hong , Deng Jin , Shao Yang , Ye Lingjuan , Luo Shengjuan 
Published: June 2024

Abstract
Purpose
To describe the clinical and imaging characteristics of Herlyn-Werner-Wunderlich syndrome (HWWS).

Methods
This study presented an observational case series involving consecutive patients diagnosed with HWWS, whose medical records were retrospectively reviewed. From June 2012 to December 2022, there were a total of 85 patients with HWWS enrolled in our study. We obtained the medical history, including demographic characteristics, clinical presentation, treatment, complications, and radiologic examinations performed. Patients > 18 years of age (n = 58) were recontacted.

Result
In our analysis, 27 patients were categorised as having complete obstruction, and 58 were categorised as having incomplete obstruction. The mean age at the onset of symptoms and diagnosis of complete obstruction was significantly younger than incomplete obstruction (P < 0.05). For complete obstruction, the median time between menarche and the onset of symptoms was 2.1 years, while for incomplete obstruction, it was 5.3 years. There was a significantly lower incidence of intermittent mucopurulent discharge, irregular vaginal haemorrhage, and occasional examination findings of complete obstruction than incomplete obstruction (P < 0.05). Complete obstruction was significantly associated with dysmenorrhea and pelvic endometriosis compared with incomplete obstruction (P < 0.05).

Conclusions
There are distinct clinical differences between patients with complete obstruction of the hemivagina and those with incomplete obstruction. HWWS can manifest as various combinations of uterine anomalies, communications anomalies, and renal anomalies. Early recognition and treatment can avoid complications and preserve fertility.

Keyswords
Herlyn-Werner-Wunderlich syndrome (HWWS); complete obstruction; incomplete obstruction; obstructed hemivagina; congenital malformation.
Initial Professional Education for Youth and Community Workers: Exploring Academic’s Experiences
Authors: Norris Pat 
Published: June 2024

AbstractThis paper reflects on a small-scale piece of research into the experience of academics involved in the initial professional education of youth and community workers in England during the period 2015–2016, when multiple factors were affecting degree-qualifying youth and community worker education. Interviews with six academics identify the influences of funding issues, changing contexts for fieldwork settings, varied perceptions of professional youth work to ongoing pressures within higher education which inform their experience. This research draws on Bourdieu’s thinking tools of habitus and illusio as a theoretical lens to explore academics’ ongoing commitment to professional youth and community worker education. The actions and messages from the research participants offer an insight into the varied situations academics are navigating at this point in time, and resonate with a contemporary, post-pandemic context. The paper concludes with areas for further research into the ongoing development of initial professional youth and community worker education.
Upregulation of YPEL3 expression and induction of human breast cancer cell death by microRNAs
Authors: Lee Boyoung , Kwon Yeo-Jung , Shin Sangyun , Kwon Tae-Uk , Park Hyemin , Lee Hyein , Kwak Ji-Heung , Chun Young-Jin 
Published: June 2024

AbstractMicroRNAs (miRNAs), molecules comprising 18–22 nucleotides, regulate expression of genes post-transcriptionally at the 3′ untranslated region of target mRNAs. However, the biological roles and mechanisms of action of miRNAs in breast cancer remain unelucidated. Thus, in this study, we aimed to investigate the functions and possible mechanisms of action of miRNAs in breast cancer to suppress carcinogenesis. Using miRNA databases, we selected miR-34a and miR-605-5p to downregulate MDM4 and MDM2, respectively, because these ubiquitin E3 ligases degrade p53 and promote carcinogenesis. Results showed that miR-34a and miR-605-5p suppressed MDM4 and MDM2 expression, respectively. Moreover, they reduced the expression of yes‑associated protein 1 (YAP1), a well-known oncogene involved in Hippo signaling, but upregulated the mRNA and protein expression of yippee-like 3 (YPEL3). To elucidate whether these miRNAs promote cellular senescence and death through YPEL3 upregulation, we examined their effects on cellular proliferation, SA-β-gal activity, and mitochondrial activity in human breast cancer MCF-7 cells. Given their upregulating effect on YPEL3 expression, miR-34a and miR-605-5p increased the number of β-galactosidase-positive cells and depolarized live cells (by 10%–12%). These data suggest that miR-34a and miR-605-5p promote cellular senescence and cell death. Thus, they may act as tumor suppressors by inducing Hippo signaling and may serve as novel therapeutic agents in breast cancer treatment.
Multi-domain fusion for cargo UAV fault diagnosis knowledge graph construction
Authors: Xiao Ao , Yan Wei , Zhang Xumei , Liu Ying , Zhang Hua , Liu Qi 
Published: June 2024

AbstractThe fault diagnosis of cargo UAVs (Unmanned Aerial Vehicles) is crucial to ensure the safety of logistics distribution. In the context of smart logistics, the new trend of utilizing knowledge graph (KG) for fault diagnosis is gradually emerging, bringing new opportunities to improve the efficiency and accuracy of fault diagnosis in the era of Industry 4.0. The operating environment of cargo UAVs is complex, and their faults are typically closely related to it. However, the available data only considers faults and maintenance data, making it difficult to diagnose faults accurately. Moreover, the existing KG suffers from the problem of confusing entity boundaries during the extraction process, which leads to lower extraction efficiency. Therefore, a fault diagnosis knowledge graph (FDKG) for cargo UAVs constructed based on multi-domain fusion and incorporating an attention mechanism is proposed. Firstly, the multi-domain ontology modeling is realized based on the multi-domain fault diagnosis concept analysis expression model and multi-dimensional similarity calculation method for cargo UAVs. Secondly, a multi-head attention mechanism is added to the BERT-BILSTM-CRF network model for entity extraction, relationship extraction is performed through ERNIE, and the extracted triples are stored in the Neo4j graph database. Finally, the DJI cargo UAV failure is taken as an example for validation, and the results show that the new model based on multi-domain fusion data is better than the traditional model, and the precision rate, recall rate, and F1 value can reach 87.52%, 90.47%, and 88.97%, respectively.