bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incremental high average-utility itemset mining: survey and challenges
Authors: Chen Jing , Yang Shengyi , Ding Weiping , Li Peng , Liu Aijun , Zhang Hongjun , Li Tian 
Published: April 2024

AbstractThe High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases. However, practical applications like market basket analysis and business decision-making necessitate regular updates of the database with new transactions. As a result, researchers have developed incremental HAUIM (iHAUIM) algorithms to identify HAUIs in a dynamically updated database. Contrary to conventional methods that begin from scratch, the iHAUIM algorithm facilitates incremental changes and outputs, thereby reducing the cost of discovery. This paper provides a comprehensive review of the state-of-the-art iHAUIM algorithms, analyzing their unique characteristics and advantages. First, we explain the concept of iHAUIM, providing formulas and real-world examples for a more in-depth understanding. Subsequently, we categorize and discuss the key technologies used by varying types of iHAUIM algorithms, encompassing Apriori-based, Tree-based, and Utility-list-based techniques. Moreover, we conduct a critical analysis of each mining method's advantages and disadvantages. In conclusion, we explore potential future directions, research opportunities, and various extensions of the iHAUIM algorithm.
Pan-cancer analysis reveals correlation between RAB3B expression and tumor heterogeneity, immune microenvironment, and prognosis in multiple cancers
Authors: Liu Xu-Sheng , Chen Ya-Lan , Chen Yu-Xuan , Wu Rui-Min , Tan Fan , Wang Ya-Lan , Liu Zi-Yue , Gao Yan , Pei Zhi-Jun 
Published: April 2024

AbstractRAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B’s involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.
Segmentation of liver CT images based on weighted medical transformer model
Authors: Gu Qun , Zhang Hai , Cai Rui , Sui Si Yi , Wang Rui 
Published: April 2024

AbstractDeep convolutional neural networks have made significant strides in the field of medical image segmentation. Although existing convolutional structures enhance performance by leveraging local image information, they often lose the interdependence information between contexts. Therefore, the article utilizes the multi-attention mechanism of the Transformer structure to more comprehensively express relationships between contexts and introduced the Transformer network architecture into the field of medical image segmentation. Most models based on this Transformer structure typically require large datasets for training. However, in the medical field, the limited size of datasets makes training models with the Transformer structure challenging. To address this, the article propose a Weighted Medical Transformer (WMT) model that imposes low requirements on dataset quantity. The weighting mechanism in the WMT model aims to improve the issue of inaccurate relative positional coding when dealing with small medical datasets. Additionally, a coarse-grained and fine-grained segmentation mechanism is introduced, focusing on both the detailed aspects within image blocks and the boundary information connecting blocks. Experimental results on a liver dataset demonstrate that the model achieves F1 and IoU scores of 88.48% and 79.41%, respectively. Results on the MoNuSeg dataset show comparable high F1 and IoU scores of 79.58% and 66.19%, respectively. The model’s accuracy surpasses that of U-Net++ and U-Net models. Compared to other models, this approach is applicable to scenarios with limited datasets, exhibiting high execution efficiency and accuracy.
Tomato domestication rather than subsequent breeding events reduces microbial associations related to phosphorus recovery
Authors: Dixon Mary M. , Afkairin Antisar , Davis Jessica G. , Chitwood-Brown Jessica , Buchanan Cassidy M. , Ippolito James A. , Manter Daniel K. , Vivanco Jorge M. 
Published: April 2024

AbstractLegacy phosphorus (P) is a reservoir of sparingly available P, and its recovery could enhance sustainable use of nonrenewable mineral fertilizers. Domestication has affected P acquisition, but it is unknown if subsequent breeding efforts, like the Green Revolution (GR), had a similar effect. We examined how domestication and breeding events altered P acquisition by growing wild, traditional (pre-GR), and modern (post-GR) tomato in soil with legacy P but low bioavailable P. Wild tomatoes, particularly accession LA0716 (Solanum pennellii), heavily cultured rhizosphere P solubilizers, suggesting reliance on microbial associations to acquire P. Wild tomato also had a greater abundance of other putatively beneficial bacteria, including those that produce chelating agents and antibiotic compounds. Although wild tomatoes had a high abundance of these P solubilizers, they had lower relative biomass and greater P stress factor than traditional or modern tomato. Compared to wild tomato, domesticated tomato was more tolerant to P deficiency, and both cultivated groups had a similar rhizosphere bacterial community composition. Ultimately, this study suggests that while domestication changed tomato P recovery by reducing microbial associations, subsequent breeding processes have not further impacted microbial P acquisition mechanisms. Selecting microbial P-related traits that diminished with domestication may therefore increase legacy P solubilization.
Longitudinal study investigating the influence of COMT gene polymorphism on cortical thickness changes in Parkinson's disease over four years
Authors: Tajerian Amin 
Published: April 2024

AbstractParkinson's disease (PD) is a progressive neurodegenerative disorder affecting over 3% of those over 65. It's caused by reduced dopaminergic neurons and Lewy bodies, leading to motor and non-motor symptoms. The relationship between COMT gene polymorphisms and PD is complex and not fully elucidated. Some studies have reported associations between certain COMT gene variants and PD risk, while others have not found significant associations. This study investigates how COMT gene variations impact cortical thickness changes in PD patients over time, aiming to link genetic factors, especially COMT gene variations, with PD progression. This study analyzed data from 44 PD patients with complete 4-year imaging follow-up from the Parkinson Progression Marker Initiative (PPMI) database. Magnetic resonance imaging (MRI) scans were acquired using consistent methods across 9 different MRI scanners. COMT single-nucleotide polymorphisms (SNPs) were assessed based on whole genome sequencing data. Longitudinal image analysis was conducted using FreeSurfer's processing pipeline. Linear mixed-effect models were employed to examine the interaction effect of genetic variations and time on cortical thickness, while controlling for covariates and subject-specific variations. The rs165599 SNP stands out as a potential contributor to alterations in cortical thickness, showing a significant reduction in overall mean cortical thickness in both hemispheres in homozygotes (Left: P = 0.023, Right: P = 0.028). The supramarginal, precentral, and superior frontal regions demonstrated significant bilateral alterations linked to rs165599. Our findings suggest that the rs165599 variant leads to earlier manifestation of cortical thinning during the course of the disease. However, it does not result in more severe cortical thinning outcomes over time. There is a need for larger cohorts and control groups to validate these findings and consider genetic variant interactions and clinical features to elucidate the specific mechanisms underlying COMT-related neurodegenerative processes in PD.
New cyanido-bridged iron(ii) spin crossover coordination polymers with an unusual ladder-like topology: an alternative to Hofmann clathrates
Authors: Visinescu Diana , Shylin Sergii I. , Shova Sergiu , Novitchi Ghenadie , Popescu Delia-Laura , Alexandru Maria-Gabriela 
Published: April 2024

The newly reported cyanido-bridged {FeIIMII} coordination polymers, with rare ladder-like topologies, show gradual HS-to-LS SCO on cooling due to the flexible N6 surrounding of FeII metal ions from one pincer and three CN- ligands (M = Pd, Pt).
Active noise control by means of high frequency injection in electric motors
Authors: Skoulaxinos Stefanos , Wheeler Pat , Vakil Gaurang 
Published: April 2024

AbstractMachine acoustics is an important area of research impacting the quality and comfort of human life. With increased levels of electrification and the wider use of electric motors, the contribution of motor drives towards quieter acoustic systems becomes increasingly important. This paper presents a novel acoustic improvement method involving the use of acoustic waves generated from High Frequency Injection to perform Active Noise Control. Although High Frequency Injection has been used widely in the domain of sensorless motor control, its acoustic generation process has been so far perceived as a negative by‐product. This paper presents the analysis and experimental results from the application of the proposed method to the Helicopter Electro‐Mechanical Actuation System. Considering the extensive use of motor drives in a number of industries, the proposed practice of High Frequency Injection Active Noise Control can have a significant impact to future applications.
Green synthesis and characterization of Ag nanoparticles using fresh and dry Portulaca Oleracea leaf extracts: Enhancing light reflectivity properties of ITO glass
Authors: Barzinjy Azeez A. , Haji Banaz Sh. 
Published: April 2024

AbstractSilver (Ag) nanoparticles (NPs) are perceiving remarkable progress during the past few periods due to its exclusive properties in many applications. Recently, green synthesis method of NPs is racing against traditional chemical and physical methods by avoiding the use of many toxic chemicals, and expensive devices. Accordingly, in this study, dry and fresh Portulaca‐oleracea L. leaf extract has been employed for producing AgNPs as a reducing, capping and stabilizing agents. This process is simple, eco‐friendly and green. UV–vis spectra showed the formation of AgNPs represented by the change of a colorless liquid to brownish solution. The crystallinity of the AgNPs, was confirmed by X‐ray diffraction (XRD). The contribution of the available functional groups of the leaf extract in the reduction and capping process of NPs was demonstrated using Fourier transform infrared spectroscopy (FTIR). This study showed that fresh Portulaca‐oleracea L. leaf extract provides better NPs in terms of stability, purity, degree of crystallinity and spherical shape. The biosynthesized AgNPs from both procedures were coated on the indium tin oxide (ITO) glass substrates to enhance the reflectivity property. It has been shown that the utilized AgNPs, from fresh Portulaca‐oleracea L. extract, has smaller size and negligeable agglomeration, consequently lower light transmittance.
Power prediction of regional distributed photovoltaic clusters with incomplete information based on improved weighted fusion and transfer learning
Authors: Zheng Wanting , Xiao Hao , Zhou Hai , Zhang Heng , Gao Wei , Pei Wei 
Published: April 2024

AbstractThe rapid expansion of low‐voltage distributed photovoltaic (PV) systems with decentralized layouts poses significant data collection challenges. The scarcity of data amplifies prediction complexities, affecting the operational security and stability of distribution networks. To enhance predictive accuracy for distributed regional PV power generation, including unmonitored low‐voltage systems, this paper proposes a novel prediction approach that combines weight optimization and transfer learning. Firstly, to more accurately extrapolate from neighbouring monitored PV to estimate unmonitored PV outputs, a novel SSA‐MLP‐XGBoost model is proposed for monitored PV power plants, in which the hyperparameters of multilayer perceptron (MLP) and (extreme gradient boosting) XGBoost models are fine‐tuned using the sparrow search algorithm (SSA), and the optimized models are synergistically integrated to heighten prediction precision for monitored plants. Secondly, based on the predicted power curves of monitored PV power plants, a weight optimization model is presented to optimize the combined weights between unmonitored and monitored power stations. Furthermore, the power generation model from monitored facilities is transplanted to unmonitored plants for power generation estimation. Ultimately, the authors combine the weight optimization and transfer learning model to get more accurate and robust model. Validation across three regional distributed photovoltaic clusters demonstrates a noteworthy improvement in prediction accuracy—20%, 7.5%, and 25% for the respective clusters compared to the existing methods.
Galaxy archaeology for wet mergers: Globular cluster age distributions in the Milky Way and nearby galaxies
Authors: Valenzuela Lucas M. , Remus Rhea-Silvia , McKenzie Madeleine , Forbes Duncan A. 
Published: April 2024

Context.Identifying past wet merger activity in galaxies has been a longstanding issue in extragalactic formation history studies.Gaia’s 6D kinematic measurements in our Milky Way (MW) have vastly extended the possibilities for Galactic archaeology, leading to the discovery of a multitude of early mergers in the MW’s past. As recent work has established a link between younger globular clusters (GCs; less than about 10–11 Gyr old) and wet galaxy merger events, the MW provides an ideal laboratory for testing which GC properties can be used to trace extragalactic galaxy formation histories.Aims.To test the hypothesis that GCs trace wet mergers, we relate the measured GC age distributions of the MW and three nearby galaxies, M 31, NGC 1407, and NGC 3115, to their merger histories and interpret the connection with wet mergers through an empirical model for GC formation.Methods.The GC ages of observed galaxies are taken from a variety of studies to analyze their age distributions side-by-side with the model. For the MW, we additionally cross-match the GCs with their associated progenitor host galaxies to disentangle the connection to the GC age distribution. For the modeled GCs, we take galaxies with similar GC age distributions as observed to compare their accretion histories with those inferred through observations.Results.We find that the MW GC age distribution is bimodal, mainly caused by younger GCs (10–11 Gyr old associated with Gaia-Sausage/Enceladus (GSE) and in part by unassociated high-energy GCs. The GSE GC age distribution also appears to be bimodal. We propose that the older GSE GCs (12–13 Gyr old) were accreted together with GSE, while the younger ones formed as a result of the merger. For the nearby galaxies, we find that clear peaks in the GC age distributions coincide with active early gas-rich merger phases. Even small signatures in the GC age distributions agree well with the expected wet formation histories of the galaxies inferred through other observed tracers. From the models, we predict that the involved cold gas mass can be estimated from the number of GCs found in the formation burst.Conclusions.Multimodal GC age distributions can trace massive wet mergers as a result of GCs being formed through them. From the laboratory of our own MW and nearby galaxies we conclude that the ages of younger GC populations of galaxies can be used to infer the wet merger history of a galaxy.
X-Shooting ULLYSES: Massive stars at low metallicity
Authors: Martins F. , Bouret J.-C. , Hillier D. J. , Brands S. A. , Crowther P. A. , Herrero A. , Najarro F. , Pauli D. , Puls J. , Ramachandran V. , Sander A. A. C. , Vink J. S. ,   the XShootU Collaboration
Published: April 2024

Context. Massive stars rotate faster, on average, than lower mass stars. Stellar rotation triggers hydrodynamical instabilities which transport angular momentum and chemical species from the core to the surface. Models of high-mass stars that include these processes predict that chemical mixing is stronger at lower metallicity.
Aims. We aim to test this prediction by comparing the surface abundances of massive stars at different metallicities.
Methods. We performed a spectroscopic analysis of single O stars in the Magellanic Clouds (MCs) based on the ULLYSES and XShootU surveys. We determined the fundamental parameters and helium, carbon, nitrogen, and oxygen surface abundances of 17 LMC and 17 SMC non-supergiant O6–9.5 stars. We complemented these determinations by literature results for additional MCs and also Galactic stars to increase the sample size and metallicity coverage. We investigated the differences in the surface chemical enrichment at different metallicities and compared them with predictions of three sets of evolutionary models.
Results. Surface abundances are consistent with CNO-cycle nucleosynthesis. The maximum surface nitrogen enrichment is stronger in MC stars than in Galactic stars. Nitrogen enrichment is also observed in stars with higher surface gravities in the SMC than in the Galaxy. This trend is predicted by models that incorporate chemical transport caused by stellar rotation. The distributions of projected rotational velocities in our samples are likely biased towards slow rotators.
Conclusions. A metallicity dependence of surface abundances is demonstrated. The analysis of larger samples with an unbiased distribution of projected rotational velocities is required to better constrain the treatment of chemical mixing and angular momentum transport in massive single and binary stars.
The Ongoing Debate: Longevity of Biological Valves in Pulmonary Position
Authors: Müller Marlene , Biermann Daniel , Righa Miriam Mkanyika , Carstens Henning , Kozlik-Feldmann Rainer Gerhard , Hübler Michael , Sachweh Jörg Siegmar 
Published: April 2024

Abstract
Background In patients with tetralogy of Fallot (ToF) or ToF-like anatomy, factors possibly impacting the longevity of biological valves in the pulmonary position were investigated.
Method Between 1997 and 2017, 79 consecutive hospital survivors with a median age of 8.7 years (range: 0.2–56.1 years; interquartile range [IQR]: 14.8 years) with ToF or ToF-like anatomy underwent surgical implantation of Contegra (n = 34), Hancock (n = 23), Perimount (n = 9), pulmonary homograft (n = 9), and miscellaneous (n = 4) conduits. The median internal graft diameter was 19 mm (range: 11–29 mm; IQR: 8 mm) which refers to a median z-score of 0.6 standard deviation (SD) (range: −1.8 to 4.0 SD; IQR: 2.1 SD).
Results The median time of follow-up was 9.4 years (range: 1.1–18.8 years; IQR: 6.0 years). Thirty-nine patients (49%) underwent surgical (n = 32) or interventional (n = 7) pulmonary valve re-replacement. Univariate Cox regression revealed patient age (p = 0.018), body surface area (p = 0.004), internal valve diameter (p = 0.005), and prosthesis z-score (p = 0.018) to impact valve longevity. Multivariate Cox regression analysis, however, did not show any significant effect (likely related to multicollinearity). Subgroup analysis showed that valve-revised patients have a higher average z-score (p = 0.003) and younger average age (p = 0.007).
Conclusion A decreased longevity of biological valves in the pulmonary position is related to younger age, lower valve diameter, and higher z-score. Because valve size (diameter and z-score) can be predicted by age, patient age is the crucial parameter influencing graft longevity.
Large for Gestational Age and Adverse Outcomes: Stratified By Diabetes Status
Authors: Nazeer Sarah A. , Chen Han-Yang , Cornthwaite Joycelyn Ashby , Chauhan Suneet P. , Sibai Baha , Wagner Stephen , Bartal Michal F. 
Published: April 2024

Objective To examine the association of adverse outcomes among parturients with large for gestational age (LGA; birth weight ≥ 90th) newborns, stratified by diabetes status. Additionally, we described the temporal trends of adverse outcomes among LGA neonates.
Study Design This retrospective cohort study used the U.S. Vital Statistics dataset between 2014 and 2020. The inclusion criteria were singleton, nonanomalous LGA live births who labored and delivered at 24 to 41 weeks with known diabetes status. The coprimary outcomes were composite neonatal adverse outcomes of the following: Apgar score < 5 at 5 minutes, assisted ventilation > 6 hours, seizure, or neonatal or infant mortality, and maternal adverse outcomes of the following: maternal transfusion, ruptured uterus, unplanned hysterectomy, admission to intensive care unit, or unplanned procedure. Multivariable Poisson regression models were used to estimate adjusted relative risks (aRR) and 95% confidence intervals (CI). Average annual percent change (AAPC) was calculated to assess changes in rates of LGA and morbidity over time.
Results Of 27 million births in 7 years, 1,843,467 (6.8%) met the inclusion criteria. While 1,656,888 (89.9%) did not have diabetes, 186,579 (10.1%) were with diabetes. Composite neonatal adverse outcomes (aRR = 1.48, 95% CI = 1.43, 1.52) and composite maternal adverse outcomes (aRR = 1.37, 95% CI = 1.36, 1.38) were significantly higher among individuals with diabetes, compared with those without diabetes. From 2014 to 2020, the LGA rate was stable among people without diabetes. However, there was a downward trend of LGA in people with diabetes (AAPC = − 2.4, 95% CI = − 3.5, −1.4).
Conclusion In pregnancies with LGA newborns, composite neonatal and maternal morbidities were higher in those with diabetes, compared with those without diabetes.
Key Points