bluuebunny/crossref_metadata_2025_split huggingface dataset:
Jogos e Geometria no Ensino Médio: um Mapeamento Sistemático
Authors: Nipo Daniel , Lopes Andiara , Silva Deleon 
Published: December 2024

O conhecimento e as habilidades desenvolvidas pela geometria gráfica são essenciais para a resolução de problemas, sendo cruciais na formação de profissionais em diversas áreas. Para que o ensino de geometria seja efetivo, é fundamental o uso de recursos didáticos que facilitem a compreensão dos conteúdos. Nesse contexto, destacamos a utilização de jogos como uma estratégia capaz de promover a aprendizagem pelo lúdico. Este artigo apresenta um mapeamento sistemático com o objetivo de compreender o estado da arte das investigações que relacionam a Aprendizagem Baseada em Jogos com o Ensino de Geometria no Ensino Médio. Os resultados da pesquisa revelaram lacunas e direções para apoiar pesquisas futuras, incluindo os principais conteúdos de geometria explorados em jogos, os diferentes tipos de jogos utilizados, e os métodos predominantes de coleta de dados em atividades com jogos.

Palavras-chave: Aprendizagem baseada em jogos. Geometria. Ensino médio.
Analysis of approaches to solving a forward problem based on a comparison of the results of two seismic tomography algorithms
Authors: Potapova K. Yu. , Abramenkov S. S. , Chernyshov G. S. , Dergach P. A. , Medved I. V. , Stupina T. A. 
Published: December 2024

The seismic ray tomography method provides a way to construct models of velocity anomalies in the geological medium to provide hypotheses about structure beneath. In the tomographic inversion process the chosen approach and quality of the forward problem solution significantly affects final result which may vary for the same dataset. The aim of this paper is to study the influence of the choice in forward problem solving method on the inversion result using two algorithms as an example: PROFIT (ray-bending technique) and ST3D (tracing via eikonal equation solution), using field data (Beltir, Altai Republic, 2021).
УПОРЕДНА АНАЛИЗА САТИВНИХ ГЛАГОЛА У СРПСКОМ И РУСКОМ ЈЕЗИКУ (НА КОРПУСУ САВРЕМЕНИХ КЊИЖЕВНИХ ДЕЛА)
Authors: Балек Тијана 
Published: December 2024

У раду су представљени првенствено глаголи са сативном компонентом која је изражена граматички, одређеним префиксима, и то упоредо у два сродна словенска језика – српском и руском. Сагледана је и могућност реализације ове факултативне глаголске категорије у датом контексту. Сативност се посматра пре свега са функционално-семантичког аспекта, тако да су најпре утврђени типични и мање типични начини творбе и реализације дате значењске компоненте код глагола. На основу тога су одређени центар и периферија проучаване категорије у поређеним језицима, те утврђене разлике у погледу њене реализације на творбеном и лексичком плану у српском и руском језику.
Association of lipids in lipoprotein subfractions with liver fibrosis in a mouse model of metabolic dysfunction–associated steatohepatitis
Authors: Nakahara Honoka , Ichimura-Shimizu Mayuko , Tachibana Shotaro , Jargalsaikhan Orgil , Qinyi Cai , Yuko Miyakami , Ogawa Hirohisa , Matsuda Satoru , Tsuneyama Koichi 
Published: December 2024

Abstract

Background
Metabolic dysfunction–associated steatohepatitis (MASH) exhibits inflammation and fibrosis in addition to lipid accumulation in the liver, which may progress to cirrhosis and liver failure. Liver biopsy is the only method currently available to differentiate between MASH and simple steatosis.
Aims
This study investigated whether the serum lipoprotein subfraction reflects fibrosis severity in a MASH mouse model.
Methods
Nine-week-old male A/J and C57BL6/J mice were fed a high-fat/cholesterol/cholate-based (iHFC) diet to induce fibrotic MASH. To generate fibrosis of varying severity, mice were fed two diets with different cholesterol concentrations (1.25% and 2.5%). After 9 weeks of feeding, serum cholesterol and triglyceride levels of each lipoprotein were comprehensively analyzed, including chylomicron, very-large low-density lipoprotein, low-density lipoprotein (LDL), and high-density lipoprotein (HDL), with 20 subclasses according to particle size.
Results
Among 20 lipoprotein subfractions, serum levels of very-large HDL-cholesterol, very-small HDL-cholesterol, very-small HDL-triglycerides, and very-small LDL-cholesterol were significantly higher in the stage 2 fibrosis group than the stage 1 fibrosis group. Serum very-small LDL-cholesterol levels were correlated with histological severity of MASH, which reportedly increases with the progression of MASH in humans.
Conclusion
The serum lipoprotein subfraction reflects liver fibrosis severity even in early phase, independent of the severity of other MASH lesions in MASH model mice. Fractionating HDL, which have been measured in clinical practice, may help establish noninvasive markers of liver fibrosis.
Origins of the fastest stars from merger-disruption of He-CO white dwarfs
Authors: Perets Hagai , Glanz Hila , Bhat Aakash , Pakmor Rüdiger 
Published: December 2024

Abstract

Hypervelocity white dwarfs (HVWDs) are stellar remnants moving at speeds exceeding the Milky Way's escape velocity1-6. The origins of the fastest HVWDs are enigmatic, with proposed formation scenarios facing challenges explaining both their extreme velocities and observed properties7-8. Here we report a three-dimensional hydrodynamic simulation of a merger between two hybrid helium-carbon-oxygen white dwarfs (HeCO WDs with masses of 0.68 and 0.62 M_sun). We find that the merger leads to a partial disruption of the secondary WD, coupled with a double-detonation explosion of the primary WD. This launches the remnant core of the secondary WD at a speed of ~2000 km s-1, consistent with observed HVWDs. The low mass of the ejected remnant and its heating from the primary WD's ejecta explain the observed luminosities and temperatures of hot HVWDs, which are otherwise difficult to reconcile with previous models. This discovery establishes a new formation channel for HVWDs and points to a previously unrecognized pathway for producing peculiar Type Ia supernovae and faint explosive transients.
WITHDRAWN: Unveiling the continuum of acute-on-chronic liver failure: phenotypic insights into severity and outcomes
Authors: Zhang Qian , Hu Jiaxuan , Qiu Shaotian , Bian Jiale , Gao Aimin , Liu Fang , Zhao Caiyan , Zhang Liaoyun , Ren Wanhua , Xin Shaojie , Chen Yu , Duan Zhongping , Han Tao 
Published: December 2024

Abstract

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
parenting concerns in cancer patients with minor children: a scoping review
Authors: Gu Sai-nan , ZHU Ai-yong , Sun Shan-shan , Shen Ling-ling , Zhao Fang 
Published: December 2024

Abstract

Background: Parenting problems are prevalent in cancer patients, and breast cancer patients themselves are more prone to depression, anxiety, fear of illness and other negative emotions, and the role of motherhood requires female cancer patients to be treated while raising their children, and patients must balance managing their illness with caring for their minor children. Therefore, the group of young and middle-aged cancer deserves more attention from society, medical treatment, and nursing.
Objectives：to summarise the influencing factors of rearing anxiety of young and middle-aged cancer patients with minor children.
Design:Scoping review
Data sources:the scope review report framework of Arksey and O'Malley was used to search China Knowledge Network (CNKI),China Biomedical Literature Database (CBM),Wanfang database,PubMed,Web of Science, Embase and Cochrane Library From the establishment of the database to July 20,2024,the included literatures were screened and analysed.
Results: A total of 13 articles were included. the results showed that the level of parenting anxiety of cancer patients at home and abroad was higher, which was mostly affected by personal characteristics, disease characteristics and psychosocial characteristics.
Conclusion: Cancer patients are affected by many factors in the process of disease and parenting,and face the challenge of parenting,which leads to a high level of parenting anxiety. Therefore,future medical workers should pay close attention to the parenting concerns of cancer patients and regard them as the core part of psychological care.
Joint Optimization of Collaborative Delivery Routes and Charging Station Locations for Electric Vehicles and Drones
Authors: Guan Tian , Gao Mingren , Wang Shu , Han Yi , Jiang JiaXin 
Published: December 2024

Abstract

In the current context of achieving carbon neutrality, energy transition has become imperative. For the automotive sector, replacing traditional fuel-powered vehicles with electric vehicles (EVs) offers the most effective solution. In logistics, deploying EVs for delivery can significantly reduce costs. This paper proposes a novel model to address the problem of collaborative delivery using drones and electric vehicles based on a genetic algorithm (GA). Furthermore, it incorporates the siting of charging stations as part of the model. A new logic for the deployment and retrieval of drones is developed and implemented in the algorithm. Unlike previous models constrained by fixed charging requirements, this model enables EVs to proactively decide whether to recharge at charging stations when visiting specific customer nodes, ensuring that the remaining range of EVs never falls below zero within the mathematical framework.
Enhancing Security Operations Center Efficiency throughMulti-Model Integration of Large Language Models and SIEMSystems
Authors: Singh Yuvraj , Patel ND , Shandilya Shishir Kumar 
Published: December 2024

Abstract

The rising rates of cyberattacks necessitate advanced solutions within Security Operations Centers (SOCs). This research explores the integration of Large Language Models (LLMs) with Security Information and Event Management (SIEM) systems to enhance the triage processes of Tier 1 SOC analysts. We evaluate five LLMs—GPT-4, GPT-3.5, LLaMA 3, Mixtral 8x22B, and OpenHermes 2.5 Mistral 7B—on their ability to classify alerts as 'interesting' or 'not interesting'. Our proposed framework, consisting of an alert generation module, an LLM agent, and a reporting module, was tested using Wazuh SIEM integrated with CALDERA for adversary emulation. The results demonstrate that GPT-4 achieved the highest accuracy with a precision of 94\%, recall of 92\%, and an F1-score of 93\%, significantly outperforming the other models. The integration of LLMs accelerated preliminary triage by reducing the average processing time per alert by 40\% and decreased the cognitive load on analysts by automating up to 60\% repetitive tasks. However, challenges such as hallucinations—occurring in approximately 5\% of cases—integration complexities and privacy risks associated with handling sensitive data were observed. To address these issues, we propose a hybrid approach where LLMs act as co-pilots alongside analysts, incorporating strategies for model transparency, bias detection, and compliance with data privacy regulations. These findings offer practical insights for enhancing SOC efficiency and resilience against evolving cyber threats, emphasizing the importance of prompt optimization, continuous learning, and industry collaboration for large-scale alert training in future studies.
An Artificial Intelligence Approach to Predicting Processing Parameters for Liquid Composite Molded (LCM) Carbon Fibre-Reinforced Plastics (CFRPs)
Authors: Sears Jennifer L , Johrendt Jennifer 
Published: December 2024

Abstract

This study developed a comparative machine learning (ML) framework to predict optimal processing parameters and mechanical properties for automotive-grade carbon fibre-reinforced plastics (CFRPs) produced via Liquid Composite Molding (LCM). Multi-linear- (MLR), support vector- (SVR), random forest- (RFR), and gradient boosting regression (GBR) algorithms were coupled with artificial neural network (ANNs) using multi-layer perceptron (MLP), and single and dual-path functional application programming interface (FAPIs) models to increase the prediction outcomes. The models developed herein can be tailored to the case-specific needs of the application. The results demonstrated that the RFR model, enhanced with hyperparameter tuning, achieved the highest predictive accuracy, explaining 45% of the variability in the data for the linear regression case. The FAPI model using Keras® and Tensorflow® exhibited superior performance for the non-linear case, with test predictions of 78.20% for flexural strength, 73.8% for flexural modulus and 99.97% for binder use. Additionally, thermal and demolding analysis expanded the complexity of the predictions by enhancing the correlation to part quality, ultimately accelerating product development and providing industry with accurate predictive modelling tools.
Active Grade Estimator on Short Answer Assessment
Authors: Iqbal Mohammad , Nugraha Tsamara Rana , Pao Hsing-Kuo 
Published: December 2024

Abstract

When introducing machine learning to automated grading systems, active learning is advantageous by helping teachers provide as little guidance as possible to offer proper automatic grading results in the end. However, given a high variety of Q/A nature, one has to pay attention to a diverse set ofpossible correct answers to offer suitable grading. Moreover, students who lack self-confidence in replying to exam questionsusually put long-winded or formless answers which jeopardizes the automatic gradingto reach its reliable performance. All aforementioned factors prohibit applying the conventional keyword-matching approaches to solve the problem. To deal with the difficulty, we propose a novel two-stage query strategy based on large language models (LLMs).In the first stage, we match a student's answer to a key answer from a prepared answer set. Afterward, the student's answer shall be summarized through LLMs to a well-structured answer. The proposed LLM-based approach is considered a prototype-based learning method. We also attempt to reduce the possibility of bias labeling by having multiple graders as oracles to join the proposed active learning framework. The proposed approach has been demonstrated on two publicly automated short answer grading datasets with different grading tasks. Overall, the proposed model exhibits outstanding performance compared to state-of-the-art methods focusing on similar topics in terms of effectiveness and efficiency.
Accelerated Sky Region Segmentation Using Hybrid Deep CNNs and Lattice Boltzmann Level-Set Model
Authors: Albalooshi Fatema A. , Qader M. R. , Ismail Yasser , Elmedany Wael , Al-Ammal Hesham , Rajarajan Muttukrishnan , Asari Vijayan k. 
Published: December 2024

Abstract

In this paper, we present a novel hybrid method for accelerated sky region segmentation that integrates Convolutional Neural Networks (CNNs) with the Lattice Boltzmann Level-Set (LBLS) model. By leveraging DeepLabV3+, Fully Convolutional Network (FCN), and SegNet, our approach guides the active contour and extracts regions of interest. We employ a local image fitting level-set function to characterize the region-based active contour model and utilize the Lattice Boltzmann Method (LBM) to achieve rapid convergence. This deep LBLS segmentation method not only preserves precise details of the sky region but also demonstrates improved robustness and computational efficiency. Experimental results on the CamVid dataset show that our proposed method outperforms state-of-the-art techniques, achieving a mean recall value improvement of up to 14.45%. Our method contributes to advancements in sky region segmentation, essential for applications such as object detection, augmented reality, and virtual reality.
Model breeding and ecotoxicity study of Eprinomectin on the reproductive performance of Onthophagus hircus (Coleoptera: Scarabaeidae)
Authors: Bianchinotti Vernadet , González-Vainer Patricia , Suárez Gonzalo 
Published: December 2024

Abstract

This study developed a laboratory rearing model for the dung beetle Onthophagus hircus to evaluate the ecotoxicological effects of eprinomectin (EPM) on its survival and reproductive performance. Adult O. hircus were exposed to increasing EPM concentrations (0-50 ppm) in bovine feces. Survival was significantly reduced at 50 ppm EPM. A reproductive per-formance experiment compared control and 0.05 ppm EPM treatment groups. While adult fecundity was not significantly affected, the EPM treatment resulted in complete failure of progeny development, with no adult emergence. The study demonstrates that environmentally relevant EPM concentrations can negatively impact O. hircus populations through larvi-cidal effects, even when adult survival and reproduction appear unaffected. This highlights the importance of considering long-term impacts when assessing the environmental risks of antiparasitic drugs on beneficial dung fauna. The laboratory rearing model developed provides a valuable tool for further ecotoxicological research on dung beetles.
Regulatory effects of Poria cocos polysaccharides on gut microbiota and metabolites: Evaluation of prebiotic potential
Authors: Zhou Xu , Li Yangyou , Yang Yuhan , Wei Li , Wang Chen , Xu Jiahui , Song Jiajia , Liu Shijian , Bai Junying , Suo Huayi 
Published: December 2024

Abstract

Dietary polysaccharides have the function of regulating gut microbiota and metabolites, and can serve as an important source of functional foods. This study aimed to analyze the regulation of poria cocos polysaccharides on the structure and metabolism of human gut microbiota through an in vitro fecal fermentation model. The results showed that Poria cocos polysaccharides can be utilized by gut microbiota, resulting in a significant decrease in pH and a significant increase in the concentration of short-chain fatty acids. Additionally, the relative abundance of beneficial bacteria such as Lactobacillus, Bifidobacterium increased, while the relative abundance of harmful bacteria such as Escherichia-Shigella, Bilophila decreased. Furthermore, Poria cocos polysaccharides had a positive effect on microbial metabolites, significantly up-regulating metabolites such as L-cystine, and etelcalcetide. These results highlight the beneficial role of Poria cocos polysaccharides in maintaining intestinal health and indicate their potential prebiotics in the functional food industry.
Blocking copper transporter protein-dependent drug efflux with albumin-encapsulated Pt(IV) for synergistically enhanced chemo-immunotherapy
Authors: Fang Man , Cao Lei , Zhang Zhao , Yu Zhen , Shen Yue , Chen Jieqi , Chen Juan , Liu Zhaoqian , Meng Yingcai , Xiao Haihua , Qu Qiang , Yin Ji-Ye , Li Xiang-Ping 
Published: December 2024

Abstract

Non-small cell lung cancer (NSCLC) represents the most prevalent form of lung cancer, exerting a substantial impact on global health. Cisplatin-based chemotherapy is the standard treatment for NSCLC, but resistance and severe side effects present significant clinical challenges. Recently, novel tetravalent platinum compounds have attracted significant interest. While numerous studies concentrate on their functional modifications and targeted delivery, tumor-induced platinum resistance is frequently overlooked. Previous tetravalent platinum compound demonstrated antitumor activity, yet proved ineffective against cells exhibiting resistance to cisplatin. In order to enhance the efficacy and potential applications of tetravalent platinum in NSCLC, a glutathione (GSH)-responsive albumin nanoquadrivalent platinum (HSA@Pt) have been constructed. In light of previous research into drug conjugation, this study was to develop a combined chemo-immunotherapy approach. The HSA@Pt demonstrated high efficacy and low toxicity, with targeted tumor accumulation. Furthermore, tetrathiomolybdate (TM) has been demonstrated to exert a synergistic inhibitory effect on Cu2+ Transporting Beta Polypeptide (ATP7B) and Programmed Death Ligand 1 (PD-L1), impede platinum efflux, induce cellular stress, and activate antitumor immunity. The findings suggest HSA@Pt's potential for clinical use and a novel chemo-immunotherapy strategy for NSCLC, enhancing the utility of established drugs through synergistic sensitization.
Shallow groundwater salinization risks under climate change: FEFLOW model application in Cebala Borj-Touil irrigation zone, northern Tunisia
Authors: Rzigui Houda , Bogacki Wolfgang , Hörmann Georg , Hachicha Mohamed 
Published: December 2024

ABSTRACT

The Cebala Borj-Touil irrigation perimeter in the low valley of the Medjerda River is marked by a shallow saline groundwater rise. The seasonal water salinity shows a high spatial and temporal variation. This study introduces a novel methodological approach dealing with the data scarcity problem in a complex deltaic area, using only available data and numerical models. The numerical model FEFLOW was used to simulate the shallow groundwater flow and salt transfer. Several simulations were run to explore future trends of groundwater salinity under different climate change (CC) conditions. The results show a significant increase in water salinity under all the climatic scenarios. A 15% decrease in precipitation leads to an average increase in salinity of 10–15 g/l. The significant rise in sea level also affects the salinization process. The intrusion of seawater results in concentrations of salinity between 16 and 20 g/l. In addition, the quality of irrigation water has a marked impact, contributing to a significant increase in salinity, reaching a maximum of 15 g/l. These concerning results are to be expected, as the coastal study area is characterized by a semi-arid climate and is increasingly influenced by anthropogenic factors, including irrigation practices and drainage deficiency.
Microbial–physicochemical interplay in Iko River estuary, unraveling the hidden mystery in bioremediation of petroleum hydrocarbons
Authors: Unimke Augustine , Okezie Onyemaechi , Agbo Bassey E. , Ugwu Joy C. , Ukeye Andrew A. , Ibiene Abiye A. , Okerentugba Phillip O. 
Published: December 2024

ABSTRACT
The aquatic microbial communities are relatively complex with a high level of prokaryotic diversities. Standard and novel microbiological, analytical, and statistical techniques were employed in the collection, analysis, and comprehensive study of the samples. From the study, the mean values of total heterotrophic bacteria were determined to be 1.35 ± 0.18 (×107), 1.59 ± 0.64 (×107), and 1.56 ± 0.52 (×107) for upstream, midstream, and downstream, respectively, while the mean values for crude oil-utilizing bacteria were 1.08 ± 0.12 (×106), 1.28 ± 0.58 (×106), and 1.24 ± 0.44 (×106) for upstream, midstream, and downstream, respectively. The mean concentrations of physicochemical parameters and heavy metals obtained in the benthic sediment were significantly higher than the mean concentrations in the water samples (tidal and intertidal) (p &lt; 0.02). The result of the component analysis of total petroleum hydrocarbons (including polycyclic aromatic hydrocarbon and benzene, toluene, ethylbenzene, and xylene) revealed significantly higher levels in the sediment than tidal and intertidal water. Structural metagenomics revealed seven top phyla, namely, Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Planctomycetes, Fusobacteria, and Chloroflexi. The significantly (p &lt; 0.05) high levels of hydrocarbon-utilizing microorganisms in Iko River estuary can be taken as a sensitive index of environmental exposure to hydrocarbon pollutants in the estuary. This research revealed the response patterns of microorganisms to natural and anthropogenic gradients toward sustainability in Iko River estuary.