bluuebunny/crossref_metadata_2025_split huggingface dataset:
Matching Tabular Data to Knowledge Graph with Effective Core Column Set Discovery.
Authors: Qiu Jingyi , Song Aibo , Jin Jiahui , Chen Jiaoyan , Zhang Xinyu , Fang Xiaolin , Zhang Tianbo 
Published: September 2024

Matching tabular data to a knowledge graph (KG) is critical for understanding the semantic column types, column relationships, and entities of a table. Existing matching approaches rely heavily on core columns that represent primary subject entities on which other columns in the table depend. However, discovering these core columns before understanding the table’s semantics is challenging. Most prior works use heuristic rules, such as the leftmost column, to discover a single core column, while an insightful discovery of the core column set that accurately captures the dependencies between columns is often overlooked. To address these challenges, we introduce Dependency-aware Core Column Set Discovery (
DaCo
), an iterative method that uses a novel rough matching strategy to identify both inter-column dependencies and the core column set. Additionally,
DaCo
can be seamlessly integrated with pre-trained language models, as proposed in the optimization module. Unlike other methods,
DaCo
does not require labeled data or contextual information, making it suitable for real-world scenarios. In addition, it can identify multiple core columns within a table, which is common in real-world tables. We conduct experiments on six datasets, including five datasets with single core columns and one dataset with multiple core columns. Our experimental results show that
DaCo
outperforms existing core column set detection methods, further improving the effectiveness of table understanding tasks.
Hepatocellular Carcinoma Etiology Drives Survival Outcomes: A Population-Based Analysis
Authors: Cranford Hannah M. , Jones Patricia D. , Wong Robert J. , Liu Qinran , Kobetz Erin N. , Reis Isildinha M. , Koru-Sengul Tulay , Pinheiro Paulo S. 
Published: September 2024

Abstract

Background:
Previous survival studies on hepatocellular carcinoma (HCC) by etiology are limited to hospital-based series, restricted cohorts, and monolithic etiologic categories. We studied population-based survival by seven mutually exclusive HCC etiologic groups—standalone hepatitis-C virus (HCV), hepatitis-B virus (HBV), alcohol-related liver disease (ALD), nonalcoholic fatty liver disease (NAFLD), and dual etiology HCV–HBV, HCV–ALD, and HBV–ALD—accounting for clinical and sociodemographic characteristics.

Methods:
All HCC cases diagnosed during 2005 to 2018 from the Florida Cancer Registry were linked for etiology using statewide discharge and viral hepatitis data. We performed a cause-specific survival analysis including Cox regression for the matched 15,616 cases by HCC etiology.

Results:
The leading etiology was HCV only (n = 4,983; 31.9%); the leading dual etiology was HCV–ALD (n = 2,552; 16.3%). The five-year adjusted survival was low—17.6% overall and &lt;22% across all HCC etiologies. ALD-related etiologies [ALD only (14.4%; 95% confidence interval (CI), 12.7–16.0), HCV–ALD (10.2%; 95% CI, 8.7–11.7), and HBV–ALD (8.2%; 95% CI, 2.2–14.1)] showed lower survival than non-ALD causes—HCV only, HBV only, and NAFLD only. After adjustment for clinical and sociodemographic covariates, ALD and HBV–ALD HCC had 1.20 (95% CI, 1.13–1.27) and 1.28 (95% CI, 1.06–1.54) times higher risk of death compared with those with HCV-only HCC.

Conclusions:
ALD only and dual etiologies involving ALD show worse prognosis for HCC compared with viral etiology alone. To increase survival, improved screening and treatment are needed for patients with multiple HCC risk factors.

Impact:
Understanding US disparities in HCC survival by etiology can help guide the identification of etiologically specific biomarkers and potential therapeutic targets and inform public health measures.
Charting the brain networks of impulsivity: Meta-analytic synthesis, functional connectivity modelling, and neurotransmitter associations
Authors: Gell Martin , Langner Robert , Küppers Vincent , Cieslik Edna C. , Satterthwaite Theodore D. , Eickhoff Simon B. , Müller Veronika I. 
Published: September 2024

Abstract
Impulsivity is a multi-dimensional construct that plays a crucial role in human behaviour and is believed to be a transdiagnostic marker of several psychiatric disorders. However, given its multi-faceted nature, investigations of its neural correlates are challenging and systematic comparisons across dimensions are lacking. In this study, we used a comprehensive multi-modal approach to investigate the functional network organisation of two dimensions in which impulsivity manifests: decision-making and response inhibition. Activation likelihood estimation (ALE) meta-analyses of task-based fMRI studies within each dimension identified two distinct and non-overlapping functional systems. One located in the default-mode network, associated with value-based judgements and goal-directed decision-making, and the other distributed across higher-order networks associated with cognitive control. Resting-state functional connectivity revealed the two systems were organised into four specialised communities of default-mode, cingulo-insular, fronto-parietal, and temporal regions. Finally, given the widespread use of neurotransmitter-acting medication to treat conditions with impulsive symptoms, we investigated the association between this organisation and neurochemistry and found that integration across communities was associated with PET-derived serotonin receptor density. Our findings reinforce insights from previous behavioural research and provide substantial evidence for the multi-dimensional nature of impulsivity on the neural level. This highlights the necessity for a comprehensive dimensional ontology on all levels of investigation to address impulsivity in a transdiagnostic manner.
Online functional connectivity analysis of large all-to-all networks in MNE Scan
Authors: Esch Lorenz , Dong Jinlong , Hämäläinen Matti , Baumgarten Daniel , Haueisen Jens , Vorwerk Johannes 
Published: September 2024

Abstract
The analysis of electroencephalography (EEG)/magnetoencephalography (MEG) functional connectivity has become an important tool in neuroscience. Especially the high time resolution of EEG/MEG enables important insight into the functioning of the human brain. To date, functional connectivity is commonly estimated offline, that is, after the conclusion of the experiment. However, online computation of functional connectivity has the potential to enable unique experimental paradigms. For example, changes of functional connectivity due to learning processes could be tracked in real time and the experiment be adjusted based on these observations. Furthermore, the connectivity estimates can be used for neurofeedback applications or the instantaneous inspection of measurement results. In this study, we present the implementation and evaluation of online sensor and source space functional connectivity estimation in the open-source software MNE Scan. Online capable implementations of several functional connectivity metrics were established in the Connectivity library within MNE-CPP and made available as a plugin in MNE Scan. Online capability was achieved by enforcing multithreading and high efficiency for all computations, so that repeated computations were avoided wherever possible, which allows for a major speed-up in the case of overlapping intervals. We present comprehensive performance evaluations of these implementations proving the online capability for the computation of large all-to-all functional connectivity networks. As a proof of principle, we demonstrate the feasibility of online functional connectivity estimation in the evaluation of somatosensory evoked brain activity
“By Turff and Twigg”: Seeing, Reading, and Hearing in the Performance of Legal Ritual in Seventeenth Century Maine
Authors: Bottino Daniel 
Published: September 2024

Abstract
This essay analyzes orality and literacy in seventeenth-century Maine. As most of Maine's English colonists were not fully literate, legal instruments such as land deeds existed simultaneously as oral, material, and textual representations of the authority of the law, integrally supported by the use of ritual.
Social Media and Emergence of Neo-Traditional Protests: Exploring Communicative Ecology of Oromo Protests in Ethiopia
Authors: Gutu Urgessa Deressa , Mulugeta Mercy Fekadu 
Published: September 2024

Abstract
Entanglements of rituals and networks of the past with the present have not been sufficiently appreciated by studies of contemporary protest movements; instead, most emphasis the contrast between protest movements mobilized online and traditional offline platforms. This article adopts the holistic lens of communicative ecology to analyze the entanglements between the novel (online) and traditional (offline) communication repertoires and actors during the Oromo Protests in Ethiopia (2014–2018). We collected data from key Oromo Protests actors in five cities in Oromia, focusing on their engagement with social media and how that impacted the movement. This study reveals that traditional platforms and actors in the Oromo Protests were critically aided by online platforms; giving rise to a new dynamic of protests that can be characterized as ‘neo-traditional’ protests; protests in which majority of the activities and platforms are offline but complemented by online channels or platforms and activists.
Navigating the Future of Education: Harnessing Data Mining to Illuminate Pathways to Success
Authors: Kada Becharef , Amel Belhamiti , Abderrezzaq Bouziani , El Batoul Ammour 
Published: September 2024

Abstract
This study aims to enhance educational assessment tools in Algerian middle schools by utilizing Educational Data Mining (EDM) techniques to predict student performance in the Middle School Certificate Examination. Recognizing a gap in the Algerian education system’s use of abundant student data for improving learning outcomes and decision-making, this research applies advanced data analytics to overcome the limitations of traditional evaluation methods. Using a dataset of 541,760 student records from the Ministry of National Education, the study employs regression models including CatBoost, Ridge, and linear regression, to analyze and forecast student examination performance. Findings indicate that EDM can effectively predict student outcomes, offering educators and policymakers a valuable resource for crafting targeted educational interventions and enhancing student success rates. This research underscores the significance of bridging the gap between available data and data-driven decision-making, advocating for the integration of EDM to modernize and improve educational efficacy in Algeria.
Body Composition in Primary Hyperparathyroidism: A Potential Contributor to Weakness and Fatigue
Authors: Bunch Paul M. , Johansson Erik D. , Rigdon Joseph , Tan Josh , Lenchik Leon , Randle Reese W. 
Published: September 2024

Background Primary hyperparathyroidism (PHPT) patients commonly report weakness and fatigue, though the underlying mechanisms are uncertain. Our purpose is to determine whether CT-derived muscle and adipose tissue metrics are associated with weakness and fatigue in PHPT patients. Methods For this retrospective study, cross-sectional muscle and adipose tissue metrics were derived from CTs in PHPT patients undergoing preoperative imaging within 1 year of parathyroid surgery. Skeletal muscle index (SMI) and visceral adipose tissue (VAT)/subcutaneous adipose tissue (SAT) ratio were calculated based on a single CT image at the level of the L3 vertebra. Established sex-specific SMI thresholds were used to define sarcopenia. Demographic and clinical data were collected from the electronic health record. When available, postoperative CT images were analyzed to assess for changes in body composition pre- and post-parathyroidectomy. Results The cohort comprised 53 PHPT patients (38 females, 15 males, mean age 61.4 years), of whom 24 (45%) reported weakness, 43 (81%) reported fatigue, and 31 (58%) met CT-based criteria for sarcopenia. Lower SMI was significantly associated with preoperative weakness in females but not males. For both weakness and fatigue, VAT/SAT ratios were higher in symptomatic females and lower in symptomatic males than their asymptomatic counterparts, though these differences were not statistically significant. In patients with postoperative CTs (n = 23), no significant changes in CT metrics were observed after parathyroidectomy. Discussion In females but not males with PHPT, subjective preoperative weakness was significantly associated with lower SMI. Effects of parathyroid hormone on skeletal muscle and visceral adiposity may differ by sex.
Exploring arteriovenous malformations patient sentiments through 1401 social media posts
Authors: Gajjar Avi A , Sioutas Georgios S , Corral-Tarbay Antonio , Salem Mohamed M , Patel Saarang , Srinivasan Visish M , Jankowitz Brian T , Burkhardt Jan-Karl 
Published: September 2024

Introduction Social media has allowed patients with rare diseases to connect and discuss their experiences with others online. This study analyzed various social media platforms to better understand the patient's perception of arteriovenous malformation. Methods Twitter, Instagram, and TikTok were searched to find posts about patients' experiences with arteriovenous malformations (AVM). Posts unrelated to the patient’s experience were excluded. Posts were coded for the relevant themes related to their experience with the disease, as well as engagement, and gender. Results The most common theme was raising awareness about the condition (87.0%). Recounting symptoms (50.2%), spreading positivity (17.5%), and survival (8.3%) were other common themes. Other prevalent themes were pain (5.2%) and fear of a rare disease (3.5%). Approximately half of AVM-related Instagram (47.93%) and TikTok (52.94%) posts raised awareness about the condition. Most Instagram (67.75%) and TikTok (89.71%) posts focused on recovery and rehabilitation. Most TikTok posts discussed “survival” or “death” (57.35%), while the majority focused on spreading positivity (79.41%). Most posts were made by women (69.6%). Females were more likely than males to post about the scientific explanation of AVMs ( p = 0.003). Conclusion Social media allows patients across the country and the globe to discuss their experiences with uncommon diseases and connect with others. It also allows AVM patients to share their experiences with other patients and the public.
Reforming Medical Physics and Radiopharmaceutical Science Training Through a Programmatic Approach to Assessment
Authors: Osborne Kristy C. , Barbagallo Cathryn , Aldaoud Ammar , Guille Jennifer , Campbell Andrew , Anderson Megan , Pearce Jacob 
Published: September 2024

OBJECTIVES Programmatic assessment approaches can be extended to the design of allied health professions training, to enhance the learning of trainees. The Australasian College of Physical Scientists and Engineers in Medicine worked with assessment specialists at the Australian Council for Educational Research and Amplexa Consulting, to revise their medical physics and radiopharmaceutical science training programs. One of the central aims of the revisions was to produce a training program that provides standardized training support to their registrars throughout the 3 years, better supporting their registrars to successfully complete the program in the time frame through providing timely and constructive feedback on the registrar's progression. METHODS We used the principles of programmatic assessment to revise the assessment methods and progression decisions in the three training programs. RESULTS We revised the 3-year training programs for diagnostic imaging medical physics, radiation oncology medical physics and radiopharmaceutical science in Australia and New Zealand, incorporating clear stages of training and associated progression points. CONCLUSIONS We discuss the advantages and difficulties that have arisen with this implementation. We found 5 key elements necessary for implementing programmatic assessment in these specialized contexts: embracing blurred boundaries between assessment of and for learning, adapting the approach to each specialized context, change management, engaging subject matter experts, and clear communication to registrars/trainees.
Mouse embryo CoCoPUTs: novel murine transcriptomic-weighted usage website featuring multiple strains, tissues, and stages
Authors: Fumagalli Sarah E. , Smith Sean , Ghazanchyan Tigran , Meyer Douglas , Paul Rahul , Campbell Collin , Santana-Quintero Luis , Golikov Anton , Ibla Juan , Bar Haim , Komar Anton A. , Hunt Ryan C. , Lin Brian , DiCuccio Michael , Kimchi-Sarfaty Chava 
Published: September 2024

AbstractMouse (Mus musculus) models have been heavily utilized in developmental biology research to understand mammalian embryonic development, as mice share many genetic, physiological, and developmental characteristics with humans. New explorations into the integration of temporal (stage-specific) and transcriptional (tissue-specific) data have expanded our knowledge of mouse embryo tissue-specific gene functions. To better understand the substantial impact of synonymous mutational variations in the cell-state-specific transcriptome on a tissue’s codon and codon pair usage landscape, we have established a novel resource—Mouse Embryo Codon and Codon Pair Usage Tables (Mouse Embryo CoCoPUTs). This webpage not only offers codon and codon pair usage, but also GC, dinucleotide, and junction dinucleotide usage, encompassing four strains, 15 murine embryonic tissue groups, 18 Theiler stages, and 26 embryonic days. Here, we leverage Mouse Embryo CoCoPUTs and employ the use of heatmaps to depict usage changes over time and a comparison to human usage for each strain and embryonic time point, highlighting unique differences and similarities. The usage similarities found between mouse and human central nervous system data highlight the translation for projects leveraging mouse models. Data for this analysis can be directly retrieved from Mouse Embryo CoCoPUTs. This cutting-edge resource plays a crucial role in deciphering the complex interplay between usage patterns and embryonic development, offering valuable insights into variation across diverse tissues, strains, and stages. Its applications extend across multiple domains, with notable advantages for biotherapeutic development, where optimizing codon usage can enhance protein expression; one can compare strains, tissues, and mouse embryonic stages in one query. Additionally, Mouse Embryo CoCoPUTs holds great potential in the field of tissue-specific genetic engineering, providing insights for tailoring gene expression to specific tissues for targeted interventions. Furthermore, this resource may enhance our understanding of the nuanced connections between usage biases and tissue-specific gene function, contributing to the development of more accurate predictive models for genetic disorders.
Genome-wide analysis of the passion fruit invertase gene family reveals involvement of PeCWINV5 in hexose accumulation
Authors: Huang Dongmei , Wu Bin , Chen Ge , Xing Wenting , Xu Yi , Ma Funing , Li Hongli , Hu Wenbin , Huang Haijie , Yang Liu , Song Shun 
Published: September 2024

Abstract
Background
Invertases (INVs) are key enzymes in sugar metabolism, cleaving sucrose into glucose and fructose and playing an important role in plant development and the stress response, however, the INV gene family in passion fruit has not been systematically reported.

Results
In this study, a total of 16 PeINV genes were identified from the passion fruit genome and named according to their subcellular location and chromosome position. These include six cell wall invertase (CWINV) genes, two vacuolar invertase (VINV) genes, and eight neutral/alkaline invertase (N/AINV) genes. The gene structures, phylogenetic tree, and cis-acting elements of PeINV gene family were predicted using bioinformatics methods. Results showed that the upstream promoter region of the PeINV genes contained various response elements; particularly, PeVINV2, PeN/AINV3, PeN/AINV5, PeN/AINV6, PeN/AINV7, and PeN/AINV8 had more response elements. Additionally, the expression profiles of PeINV genes under different abiotic stresses (drought, salt, cold temperature, and high temperature) indicated that PeCWINV5, PeCWINV6, PeVINV1, PeVINV2, PeN/AINV2, PeN/AINV3, PeN/AINV6, and PeN/AINV7 responded significantly to these abiotic stresses, which was consistent with cis-acting element prediction results. Sucrose, glucose, and fructose are main soluble components in passion fruit pulp. The contents of total soluble sugar, hexoses, and sweetness index increased significantly at early stages during fruit ripening. Transcriptome data showed that with an increase in fruit development and maturity, the expression levels of PeCWINV2, PeCWINV5, and PeN/AINV3 exhibited an up-regulated trend, especially for PeCWINV5 which showed highest abundance, this correlated with the accumulation of soluble sugar and sweetness index. Transient overexpression results demonstrated that the contents of fructose, glucose and sucrose increased in the pulp of PeCWINV5 overexpressing fruit. It is speculated that this cell wall invertase gene, PeCWINV5, may play an important role in sucrose unloading and hexose accumulation.

Conclusion
In this study, we systematically identified INV genes in passion fruit for the first time and further investigated their physicochemical properties, evolution, and expression patterns. Furthermore, we screened out a key candidate gene involved in hexose accumulation. This study lays a foundation for further study on INV genes and will be beneficial on the genetic improvement of passion fruit breeding.