bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mitigating Class Imbalance in Pump-and-Dump Detection: A Comparative Analysis of Imbalance-Aware Algorithms
Authors: Bogutsky Denis , Mironov Mikhail 
Published: December 2024

Abstract

The cryptocurrency market has been subject to various forms of exploitation, with pump-and-dump schemes being a persistent problem that can lead to significant price volatility and financial losses. Prior studies have focused on predicting attack targets using machine learning approaches; however, these methods are often compromised by class imbalance and biases inherent in historical data. To address this limitation, we present a novel framework for manipulation targets prediction.
We employ two-step bias-minimizing data normalization techniques to mitigate the effects of class imbalance and temporal heterogeneity. We also propose several innovative machine learning approaches including imbalance-aware hyperparameters optimization and ranking algorithms.
Our evaluation reveals that the proposed framework outperforms existing methods, achieving an accuracy rate of 5\% and a top-10 accuracy rate of 45\% on a highly imbalanced dataset of historical P\&Ds events(imbalance ratio $\approx$ 270).
For further validation, we construct a portfolio strategy based on predicted target class probabilities to assess the practical application of our constructed models.
Enhanced biological nitrogen fixation in alfalfa through the synergistic interactions between Sinorhizobium meliloti and Priestia aryabhattai
Authors: Liu Rui , Li Chang , Zhang Yunjun , Liu Chunli , Zheng Yanning , Xue Jinai 
Published: December 2024

Abstract

Nitrogen fertilizer is crucial for agricultural output. However, prolonged overuse has resulted in nitrate leaching, and potential soil acidification. Research on microbial fertilizers has become essential to enhance soil conditions and minimize nitrogen fertilizer usage. In alfalfa cultivation, research on efficient compound microbial agents remains limited, therefore, this study concentrates on the investigation of dual microbial combinations. In the screening process, black soil was utilized with alfalfa plants as samples to identify a strain of rhizobacteria, Sinorhizobium meliloti LMGL3-1, exhibiting nitrogen-fixing capabilities, and Priestia aryabhattai (Bacillus aryabhattai) YJHT21, demonstrating phosphorus-solubilizing abilities. The S. meliloti strain demonstrated the ability to symbiotically associate with the alfalfa variety Longmu 806, resulting in the formation of effective nodules containing leghemoglobin, thereby enabling the plants to thrive in the absence of nitrogen fertilizer application. Here, we discovered that the addition of phosphorus-solubilizing P. aryabhattai enhanced plant growth and increased nitrogenase activity of S. meliloti. Moreover, the incorporation of P. aryabhattai resulted in a significant increase in flavonoid production within the root system of alfalfa plants. Consequently, under the influence of the inducer extracted from the root system of quantitatively analyzed plants, the rhizobacteria exhibited enhanced production of metabolites associated with the Nod factor cluster. The current experiment demonstrated that the interaction between the two bacteria significantly enhanced nitrogen fixation, effectively substituting nitrogen fertilizer in alfalfa cultivation with improved efficiency and offered theoretical support for the eco-friendly advancement of microbial compound fertilizers as a substitute for chemical fertilizers.
Association between ribosomal protein gene dysregulation and tumor biodiversity of hepatocellular carcinoma
Authors: Lu Zhimin , Xu Sicong , Zhao Guofeng , Niu Ziyi , Hou Guoxin 
Published: December 2024

Abstract

Background
Tumor cells are characterized by a higher production of ribosomes, which are necessary for maintaining enhanced cell growth and subsequent cell division. An increase in ribosome production is associated with aberrant ribosome biogenesis homeostasis; these elements represent specific hallmarks of cancer cells. However, its association with the hepatocellular carcinoma (HCC) microenvironment remains poorly understood.
Methods
Using single-sample gene set enrichment analysis (ssGSEA), we constructed an RPLscore to estimate the dysregulation of ribosomal protein large (RPL) genes. The expression of RPL genes and their association with clinical outcomes and the tumor microenvironment (TME) were systematically investigated using bulk-seq and single-cell RNA-seq (scRNA-seq).
Results
We observed that HCC with high expression levels of RPL was associated with poorer overall survival (OS) (P < 0.001). We developed an RPL score to evaluate the RPL gene and verified its independent prognostic value for both OS and relapse-free survival (P = 0.0074 and P < 0.001, respectively). TME analysis indicated that RPL gene dysregulation was closely associated with T cell exhaustion, myeloid-derived suppressor cell (MDSC) infiltration, and vascular dysplasia may be promoted by arginine deficiency (P = 7.6 × 10–10). The scRNA-seq data concerning HCC suggested that the RPL score was positively and significantly associated with the tumor biodiversity score (ITH score).
Conclusion
The present study highlights the prognostic value of the RPL score and its potential role in mediating immune evasion of HCC, which may provide an impetus for the development of new targets for the treatment of HCC.
Assessing Biodegradation and Flame retardation in Bio- Fiber Reinforced Polymer Composites for Advanced Material Applications
Authors: Ghanem Asmaa Mohamed 
Published: December 2024

Abstract

Background: The demand for sustainable materials has driven interest in biodegradable polymer composites reinforced with natural fibers as eco-friendly alternatives to synthetic materials. These composites combine biodegradability with enhanced mechanical performance, using fibers like jute and hemp to strengthen polymer matrices while reducing environmental impact. Challenges such as water absorption and limited durability are mitigated through surface treatments and compatibilizers. Biopolymers like polylactic acid (PLA) and polyhydroxyalkanoates (PHA) naturally degrade under various conditions, making them suitable for biomedical and industrial applications. This study explores the potential of bio-fiber composites to balance environmental sustainability with high-performance requirements. My study aims to determine their suitability for sustainable engineering and industrial applications, in keeping with the global demand for ecologically responsible material advances.
Results: This experimental laboratory-based study with analytical and comparative elements, conducted at Alexandria University's Department of Materials Science. Results show enhanced tensile strength (up to 201 kg/cm²) and flame retardancy (Limiting Oxygen Index of 31) with increased bio-fiber content, achieving improved thermal stability and reduced toxic gas emissions. Thermal analyses highlight significant char formation that protects the composite at high temperatures, while water absorption tests confirm improved hydrophobicity due to fiber treatment. Biodegradability tests reveal progressive weight loss over 14 days, validating eco-friendliness. The findings demonstrate the composite's suitability for biomedical and industrial applications, balancing environmental sustainability with performance demands.
Conclusions: The study assesses biodegradation and water resistance of bio-fiber reinforced polymer composites, revealing their potential for advanced applications, including fire and antibacterial testing, enhancing tensile strength and thermal stability.
Unsupervised multi-scale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes
Authors: Song Won-Min , Ming Chen , Forst Christian V. , Zhang Bin 
Published: December 2024

Abstract

Cell clustering is an essential step in uncovering cellular architectures in single cell RNA-sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. Here, we develop a multi-scale clustering (MSC) approach to construct sparse cell-cell correlation network for identifying de novo cell types and subtypes at multiscale resolution in an unsupervised manner. Based upon simulated, silver and gold standard data as well as real scRNA-seq data in diseases, MSC showed much improved performance in comparison to established benchmark methods, and identified biologically meaningful cell hierarchy to facilitate the discovery of novel disease associated cell subtypes and mechanisms.
Stress-Tolerant Bacillus Strains for Enhancing Tomato Growth and Biocontrol of Fusarium oxysporum under Saline Conditions: Functional and Genomic Characterization
Authors: Valencia-Marin María F. , Chávez-Avila Salvador , Sepúlveda Edgardo , Delgado-Ramírez Carmen S. , Meza-Contreras Jenny J. , Orozco-Mosqueda Ma del Carmen , Santos-Villalobos Sergio , Babalola Olubukola Oluranti , Hernández-Martinez Rufina , Santoyo Gustavo 
Published: December 2024

Abstract

Soil salinity is a major limiting factor for agricultural crops, which increases their susceptibility to pathogenic attacks. This is particularly relevant for tomato (Solanum lycopersicum), a salt-sensitive crop. Fusarium wilt, caused by Fusarium oxysporum f. sp. lycopersici, is a significant threat to tomato production in both greenhouse and field environments. This study evaluated the salinity tolerance, biocontrol, and plant growth-promoting properties of Bacillus velezensis AF12 and Bacillus halotolerans AF23, isolated from soil affected by underground fires and selected for their resistance to saline conditions (up to 1000 mM NaCl). In vitro assays confirmed that both strains produced siderophores, indole-3-acetic acid (IAA), and proteases, and exhibited phosphate solubilization under saline stress (100–200 mM NaCl). AF23 exhibited synergistic interactions with AF12, and inoculation with either strain individually or in combination significantly improved the growth of the Bonny Best tomato cultivar under 200 mM saline stress, leading to increased shoot and root weight, enhanced chlorophyll content, and higher total biomass. The biocontrol potential of AF12 and AF23 was evaluated in tomato plants infected with F. oxysporum. Both strains, individually or combined, increased shoot and root weight, chlorophyll content, and total biomass under non-saline conditions, promoting growth and reducing infection rates under saline stress (100 mM NaCl). Genomic analysis revealed that both strains harbored genes related to salt stress tolerance, biocontrol, and plant growth promotion. In conclusion, Bacillus AF23 and AF12 demonstrated strong potential as bioinoculants for enhancing tomato growth and providing protection against F. oxysporum in saline-affected soils.
Unveiling Face Recognition Challenges and Awareness in Autism Spectrum Disorder: Insights from the Italian Famous Face Test (IT-FFT)
Authors: Ventura Martina , Manippa Valerio , Caffò Alessandro Oronzo , Cicinelli Giovanni , Nobile Emanuela , Keller Roberto , Rivolta Davide 
Published: December 2024

Abstract

Accurate face recognition is crucial for navigating social interactions. While neurotypical individuals generally show no issues with face processing, persons with Autism Spectrum Disorder (PwASD) often exhibit impairments in this area. This study explores the extent of these face recognition deficits in autistic adults, focusing on their ability to identify famous faces, along with the awareness (metacognition) of their face recognition skills. Using the Italian Famous Face Test (IT-FFT) and the Prosopagnosia Index-20 (PI-20), to compare face recognition performance and self-awareness of face recognition abilities between 50 neurotypical individuals (NTs) and 49 PwASD. Our results showed that PwASD had significantly lower face identification scores and greater difficulties recognizing famous faces than NT participants. Additionally, PwASD reported more face recognition challenges on the PI-20, highlighting their awareness of these deficits. These findings suggest that face recognition impairments in PwASD extend to famous faces and underscore the importance of further research to explore targeted interventions aimed at improving different aspects of face recognition processes in ASD.
Iatrogenic Budd-chiari Syndrome from Misplacement of Right Internal Jugular Central Vein Catheter: A Case Report
Authors: Garmpis Nikolaos , Prevezanos Dionysios , Belivanis Michail , Psilopatis Iason , Papoutsas Dimitrios , Garmpi Anna , Dimitroulis Dimitrios , Damaskos Christos 
Published: December 2024

ntroduction/Background:
Budd-Chiari syndrome is a rare entity that is caused by an obstruction of the flow in the hepatic veins or inferior vena cava.

Case Presentation:
Herein, we report a rare case of iatrogenic Budd-Chiari syndrome. A 52-year-old woman with chronic renal failure under hemodialysis, presented
to our hospital for dyspnea caused by a large pleural effusion. After the placement of the central right jugular vein catheter, she suffered from right
upper quadrant acute abdominal pain along with elevation of liver function enzymes in blood tests. An abdominal computed tomography with
contrast revealed obstruction of the right hepatic vein by the catheter tip with concomitant thrombosis, thus the diagnosis of Budd-Chiari syndrome
was confirmed. Removal of the catheter and anticoagulant therapy were successfully utilized to treat the patient.

Conclusion:
Knowledge of the full spectrum of adverse effects of such a procedure is crucial for their early identification and treatment, often with a
multidisciplinary approach.
Eco-Apps for Change? Evaluating Mobile Apps to Promote and Support Sustainable Lifestyle Changes
Authors: Hynes Mike , Fahy Frances 
Published: December 2024

Introduction:
Mobile digital devices have developed mainly from voice communications
to always-on internet-accessing, mini-computers used universally across the generations. As
the consumption and use of smartphones and digital devices and services grow exponentially,
their pervasive acceptance has coincided with an increasing demand for mobile software applications.
Faced with the evidence of the deepening climate crisis, can mobile digital apps be better
deployed in support of critical lifestyle and behavioral changes required to tackle the impacts of
climate change? Applying a review of the existing literature on mobile apps and combining this
with original data from new eco-app users affords us deeper insights into the effectiveness (or
otherwise) and utility of apps in promoting lifestyle changes allowing us to better design, develop,
and deploy these digital tools for environmental good.

Methods:
A comprehensive review of the literature on behavioural change and its links to digital
ICTs is undertaken. This is followed by an analysis of quantitative data collected from just under
100 novel eco-app users to explore what they found useful, what they found troublesome, and
what forced them to reject and uninstall such apps.

Results:
Findings identified an overcrowded marketplace as a barrier to success. Attrition is also
an issue of concern in encouraging digital intervention lifestyle change, with some revealing they
would uninstall apps if they affected the operation and running of their device, or if the services
on offer were irrelevant to their needs at a particular time.

Conclusion:
The study concludes by outlining recommendations and guidelines for best practices
in future digital interventions for promoting sustainable behavioural change specifically using
mobile digital apps.
The Use of “Cancer Ratio” in Differentiating Malignant and Tuberculous Pleural Effusions: Protocol for a Prospective Observational Study
Authors: Chalamalasetty Sai Pooja , Acharya Preetam , Antony Thomas , Ramakrishna Anand , Kotian Himani 
Published: December 2024

Background
Differentiating between tuberculosis and malignancy as the cause of an exudative lymphocyte predominant pleural effusion is difficult due to similarities in the cellular and biochemical characteristics of the pleural fluid in both conditions. Microbiological tests in tubercular pleural effusions have a poor diagnostic yield, and the long turnaround time for results prevents an early diagnosis. The diagnosis of malignant pleural effusion (MPE) is hampered by a variable yield of pleural fluid cytology and closed pleural biopsy and the fact that thoracoscopy may not be readily available or feasible in each patient. A key gap in the existing knowledge is the performance of the serum lactate dehydrogenase to pleural adenosine deaminase ratio (ie, “cancer ratio”; CR) in differentiating between tuberculous and MPE in a high tuberculosis prevalence country like India, although its use has been well established in Western literature. The CR may find a practical application in the community health care settings in low-income countries without ready access to biopsy.

Objective
This study aimed to evaluate the CR as a test to differentiate tubercular and malignant etiology in patients with an exudative lymphocyte predominant pleural effusion. Secondary objectives to be assessed include a comparison of CR to pleural fluid carcinoembryonic antigen in MPE and the association of histologic type of lung carcinoma to the CR positivity.

Methods
This hospital-based, prospective, observational study will include patients admitted with pleural effusion whose pleural fluid reports indicate a lymphocyte-predominant exudate. The ability of the CR to discriminate between tuberculous and MPE will be evaluated as a primary objective of this study. The performance of CR and pleural fluid carcinoembryonic antigen in the diagnosis of MPE will be compared using the receiver operating characteristics and area under the curve for both tests as a secondary objective. The association between a positive CR and histologic type of lung cancer will be analyzed as well.

Results
Data collection began in June 2022. As of March 24, 2024, we have recruited 22 patients. Outcomes of the study are expected at the end of 2024.

Conclusions
The results of this study will provide an objective basis for the use of CR in differentiating between tuberculosis and malignancy as the cause of an exudative lymphocyte predominant pleural effusion.

International Registered Report Identifier (IRRID)
DERR1-10.2196/56592
Identifying the Relative Importance of Factors Influencing Medication Compliance in General Patients Using Regularized Logistic Regression and LightGBM: Web-Based Survey Analysis
Authors: Iino Haru , Kizaki Hayato , Imai Shungo , Hori Satoko 
Published: December 2024

Background
Medication compliance, which refers to the extent to which patients correctly adhere to prescribed regimens, is influenced by various psychological, behavioral, and demographic factors. When analyzing these factors, challenges such as multicollinearity and variable selection often arise, complicating the interpretation of results. To address the issue of multicollinearity and better analyze the importance of each factor, machine learning methods are considered to be useful.

Objective
This study aimed to identify key factors influencing medication compliance by applying regularized logistic regression and LightGBM.

Methods
A questionnaire survey was conducted among 638 adult patients in Japan who had been continuously taking medications for at least 3 months. The survey collected data on demographics, medication habits, psychological adherence factors, and compliance. Logistic regression with regularization was used to handle multicollinearity, while LightGBM was used to calculate feature importance.

Results
The regularized logistic regression model identified significant predictors, including “using the drug at approximately the same time each day” (coefficient 0.479; P=.02), “taking meals at approximately the same time each day” (coefficient 0.407; P=.02), and “I would like to have my medication reduced” (coefficient –0.410; P=.01). The top 5 variables with the highest feature importance scores in the LightGBM results were “Age” (feature importance 179.1), “Using the drug at approximately the same time each day” (feature importance 148.4), “Taking meals at approximately the same time each day” (feature importance 109.0), “I would like to have my medication reduced” (feature importance 77.48), and “I think I want to take my medicine” (feature importance 70.85). Additionally, the feature importance scores for the groups of medication adherence–related factors were 77.92 for lifestyle-related items, 52.04 for awareness of medication, 20.30 for relationships with health care professionals, and 5.05 for others.

Conclusions
The most significant factors for medication compliance were the consistency of medication and meal timing (mean of feature importance), followed by the number of medications and patient attitudes toward their treatment. This study is the first to use a machine learning model to calculate and compare the relative importance of factors affecting medication adherence. Our findings demonstrate that, in terms of relative importance, lifestyle habits are the most significant contributors to medication compliance among the general patient population. The findings suggest that regularization and machine learning methods, such as LightGBM, are useful for better understanding the numerous adherence factors affected by multicollinearity.
Comparative Assessment on the Use of Videogrammetry and Photogrammetry for Rapid and Low-Cost Three-Dimensional Modeling
Authors: Nuha Muhammad Ulin , Pramudya Alif Farhan , Laia Bonifasius Efraim , Husain Rainaldy , Setiaji Danang , Isnaini Een Lujainatul , Perdana Redho Surya , Atmojo Aulia Try , Jatmiko Retnadi Heru 
Published: December 2024

The current activities in photogrammetry technology such as the permission to apply non-metric cameras, development of Structure from Motion (SfM), and potential usage of videogrammetry are part of the answers to the need for low-cost camera-based mapping. Therefore, this study aimed to test and compare the accuracy of photogrammetry and videogrammetry methods for three-dimensional (3D) modeling obtained using a non-metric camera with SfM processing. Terrestrial Laser Scanner (TLS) was used to obtain comparative data and the results showed a degradation of photo resolution in videogrammetry method, causing a reduction in the number of point clouds produced compared to photogrammetry. Moreover, the point cloud test showed that the surface variation results for both methods were identical to 3D modeling with a higher point density recorded in photogrammetry and the relative distance was different by 0.125 meters. The average difference in point cloud between photogrammetry and TLS was 0.062 meters while videogrammetry and TLS had 0.106 meters. The absolute test produced an RMSE value of 0.022 meters for photogrammetry and 0.032 meters for videogrammetry at a 95% confidence interval, indicating the two methods produced similar data quality. The results led to the conclusion that videogrammetry had satisfactory values and could be used as an alternative in 3D modeling but was not considered better than photogrammetry. Received: 2023-08-13 Revised: 2024-05-27 Accepted: 2024-09-20 Published: 2024-10-10