bluuebunny/crossref_metadata_2025_split huggingface dataset:
PB-Raft: A Byzantine fault tolerance consensus algorithm based on weighted PageRank and BLS threshold signature
Authors: Shi Haoran , Chen Zehua , Cheng Yongqiang , Liu Xiaofeng , Wang Qianqian 
Published: August 2024

Abstract

Addressing the challenge of balancing consensus efficiency and Byzantine fault tolerance in prevalent consensus algorithms within consortium blockchains, this paper proposes an improved Raft algorithm——PB-Raft, based on the weighted PageRank algorithm and BLS threshold signature. First, it improves the leader election process through the weighted PageRank algorithm, constructing a weighted directed graph among nodes, computing the PageRank values of each node, and reducing the election timeout for node with the highest PageRank values to improve leader election efficiency and thereby enhance algorithm's consensus efficiency. Then, it improves the log replication process through BLS threshold signature, transforming the log replication process into a threshold signature verification process, achieving Byzantine fault tolerance during the log replication process, and hence improving the algorithm's security. Finally, the PB-Raft algorithm was simulated in Go language on Hyperledger Fabric, and through multiple tests using Caliper, it was shown that compared to the Raft algorithm, PB-Raft's leader election efficiency increases by approximately 30$\%$, and it has Byzantine fault tolerance capability, increases throughput by about 10$\%$, and reduces consensus delay by about 30$\%$. These results demonstrate that the PB-Raft algorithm not only possesses Byzantine fault tolerance capability but also enhances consensus efficiency, offering new insights and viable solutions for the design of consortium blockchain consensus algorithms.
Groundwater Modeling in Agricultural Arid Area under Different Scenarios, East Nile Delta, Egypt
Authors: Abdulaziz Abdulaziz M. , Abdelghany Osman , Ahmed Alaa 
Published: August 2024

Abstract

The East Nile Delta represents the natural extension of the Nile Delta that recently showed significant changes in groundwater system related to both agricultural and urbanization land development. The current study presents a GIS-based 3D groundwater flow model to outline a safe framework for pumping stress management to the upper 100 m of Quaternary aquifer located North of Ismaelia Canal. Model construction comprised 93 borehole data to model a 19-layer grid of the fluvial Quaternary deposits. The finite difference MODFLOW 2000 accomplished simulation to predict groundwater head distribution across the aquifer system in both steady and transient states. Steady state model is calibrated to the 1991-groundwater hydrogeological map of Egypt, and subsequently provided the initial conditions for the 1991–2005 transient simulation. The transient model is considered calibrated as the calculated head matches the field observations of 2004–2005. Using severe aquifer stress strategy, three scenarios are proposed to manage the reported local rise in groundwater head and evaluate the potential aquifer production during drought. This involved using several infiltration rates from irrigation return and pumping stress to model predictions extending to the year 2030. Results showed pumping controls to the rising groundwater head especially towards the North where confinement conditions prevail with two subregions, northern and southern, requiring different schemes of management. Optimum pumping and infiltration rate are determined for these subregions and for the unconfined parts of the Quaternary aquifer. During drought, a maximum of 500 million m3/yr are producible from the unconfined aquifer with standard discharge of 5000 m3/d that may induce drawdown less than 0.5 m. The water budget of modeled aquifer indicated that pumping stress is predominantly balanced by seepage from Ismaelia canal and Damietta branch with slight contributions from irrigation canals and drains. Details of water budget and changes in groundwater head to pumping stresses across the modeled area are presented and discussed in detail. The model results provide a scientific platform to delineate efficient and sustainable management to the East Nile Delta Quaternary aquifer associating active dynamic land development.
Mechanical properties and durability of asphalt–concrete mixture modified with recycled concrete and porcelain aggregates
Authors: Hamad Waleed A. , Khoshnaw Ganjeena J. 
Published: August 2024

Abstract

Asphalt–concrete mixtures have various applications in engineering construction projects, with their performance influenced by external, internal, and environmental factors. Several studies have focused on modifying their required properties and performance. Researchers have utilized recycled concrete as an additive or replacement for natural aggregate in asphalt and cement concrete mixtures, yielding acceptable results. This research introduces another waste construction material, porcelain waste, as aggregates replacing recycled concrete aggregates in different proportions to modify the mechanical properties and durability of a binder–asphalt concrete mixture. This is an additional effort to save the environment from different waste construction materials. Following the Marshall requirements, the properties of the samples with optimized quantities were investigated using wheel trucks and Bohme abrasion tests. The modified mixture exhibited an increase in bulk specific gravity by 6% to 2.24, enhanced the Marshall flow from 3.5 to 4.6 mm, and an increase in the stability by 5%, yielding the highest value of 33 kN. Subsequently, the mechanical properties and durability of the mixtures were affected with an increase in the rutting resistance. The highest abrasion resistance and service life were obtained when 25% porcelain replaced the recycled concrete aggregates, but the mixture became more temperature susceptable. Therefore, this study achieved economical, environmentally-friendly, and safe pavements.
Role of Proximate Determinants on the Fertility Rate Among Currently Married Women in Somalia via Bongaart’s Model: Findings From 2018-19 Sdhs Data
Authors: Mohamud Liban Ali , Nasir Jamal Abdul 
Published: August 2024

Abstract

Background
High fertility leads overpopulation and underdevelopment. All continents, including Africa, undertaken fertility decline. Somalia has a high fertility rate of over 6 births per woman. However, no national or sub-national studies have explored fertility determinants in Somalia. This study seeks to address this gap by examining intermediate fertility variables' impact on fertility in Somalia.
Methods
The study utilized secondary data from the Somalia Health Demographic Survey (SDHS) conducted between 2018 and 2019, employing Classical Bongaart's Aggregate and Disaggregate models.
Findings:
At the national level, postpartum infecundity caused a 51.14% reduction in Somalia's fertility rate, while marriage contributed to a decline of 48.01%. Contraception had a minimal effect, lowering the rate by only 0.79%. Sub-group analysis showed employed individuals contributed most to the Marriage Index (72.05%), with primary or higher education having a significant impact (65.77%). Unemployed individuals with no education had the highest contribution to the Postpartum Infecundability Index (75.48% and 59.48%, respectively). The Contraception Index had relatively low contributions, with urban areas and individuals with primary and higher education contributing the most (1.09% and 1.64%, respectively).
Conclusion
The study found nationally, longer breastfeeding and delayed marriage reduced fertility. In sub-groups, education and employment reduced fertility through the Marriage Index, while residence and employment decreased fertility through the Postpartum Infecundability Index. The Contraception Index had a smaller impact, but higher contributions in urban areas and among those with higher education.
The King Saud bin Abdulaziz University for Health Sciences Learner Corpus: A Longitudinal Resource for Researching the Development of Academic Writing Proficiency in EFL Learners
Authors: Nafjan Eman Al , Alfelaij Alaa , Binsuwadan Nouf Ali , Alfawaz Norah , Althowaini Banan Mohammed , Mohammed Sarah , Jawhar Sabria 
Published: August 2024

Abstract

The King Saud bin Abdulaziz University for Health Sciences (KSAUHS) Learner Corpus is a new longitudinal corpus of English as a Foreign Language (EFL) academic writing at the university level that complies with the FAIR principles. Collection began in 2022, the corpus captures writing development during a period of emerging language technologies. The corpus currently contains over a million words from 158 learners across four proficiency levels (CEFR A1-B2). Texts span four trimesters and multiple academic genres, including paragraphs and essays in rhetorical modes like cause-effect, argumentation, and summarization. Metadata includes learners' parents’ first language background, other foreign languages, academic focus, and reference tool preferences. The corpus enables research into multiple dimensions of second language writing development to inform EAP pedagogy and assessment. Avenues for investigation include: lexico-grammatical development, cross-linguistic influence, individual differences, instructional interventions, impacts of task conditions and language technologies, and longitudinal trajectories. Ongoing corpus expansion aims to expand size, representation, and accessibility. This unique resource promises data-driven insights into the textual features and factors that characterize and facilitate intermediate and advanced EFL writing proficiency in university contexts.
Development of an Investment Recommender System Using Factor Analysis, ANFIS, and MMNN
Authors: Asemi Asefeh , Asemi Adeleh , Ko Andrea 
Published: August 2024

Abstract

The main goal is to present two investment recommender systems (IRS), by combining clustering, factor analysis, Adaptive Neuro Fuzzy Inference System (ANFIS), and Multimodal Neural Network (MNN). The aim is to merge each method with advanced techniques to improve the precision and efficiency of investment recommendations. To develop and implement the IRS, clustering and factor analysis are initially used to detect patterns and connections among variables aiding in grouping individuals into several categories. Then ANFIS is developed in MATLAB using data derived from factor analysis to prove rules for recommending clusters of investment types. Furthermore, MNN was created using Python making use of TensorFlow and Keras libraries using same data for ANFIS. This network is pre-trained with data to predict investment types. The performance of both models is assessed by metrics RMSE and MSE on test data to gauge their accuracy of recommendations. An assessment of the IRSs illustrates its effectiveness in offering investment recommendations. Both models highlight promising performance as shown by the error rates on the test data. By combining clustering, factor analysis, ANFIS and MNN a holistic strategy appears for tailoring investment advice. This approach effectively merged methods with innovative machine learning (ML) and deep learning (DL) techniques. This paper proposes the personalized IRSs that are useful for investment advice. By integrating clustering, factor analysis, ANFIS, and MNN, IRS provides a unique approach with using Explainable artificial intelligence (XAI) to increase the accuracy of investment recommendations. These systems use the strengths of each method in combining them.
A Novel Non-Rodent Animal Model of Hydrochloric Acid-Induced acute and chronic lung injury.
Authors: Solopov Pavel A. , Biancatelli Ruben Manuel Luciano Colunga , Day Tierney , Dimitropoulou Christiana , Catravas John D 
Published: August 2024

Abstract

Hydrochloric acid is one of the most prevalent and dangerous chemicals. Accidental spills occur in industrial plants or during transportation. Exposure to HCl can induce severe health impairment, including acute and chronic pulmonary diseases. We have previously described the molecular, structural, and functional aspects of the development of chronic lung injury and pulmonary fibrosis caused by intratracheal instillation of HCl in mice. Although mouse models of human disease have many advantages, rodents are evolutionary far from human and exhibit significant anatomical and physiological differences. Genetic and anatomic similarities between rabbits and humans are significantly higher. Rabbit models of HCl-induced lung injury have been used sparsely to evaluate acute lung injury. In this study, for the first time, we utilized rabbits as a model of HCl-induced pulmonary fibrosis and chronic lung injury. We present molecular, histological, and functional evidence that demonstrate the utility of using this model for studying new pharmaceutics against pulmonary fibrosis.
Effect of N-acyl homoserine lactone on biofilm characteristics and formation in a Poly-hydroxybutyrate-hydroxyvalerate-supported solid phase denitrification system
Authors: Zhang Shusong , Zhou Simeng , Shen Wenting , Xu Peng , Fan Yueting 
Published: August 2024

Abstract

Quorum sensing (QS) plays an important role in biofilm formation, and its involvement in biofilm formation during heterotrophic denitrification has remained underexplored. This study investigated the impact of N-acyl homoserine lactone (AHLs) on biofilm characteristics and formation in a Poly(3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV)-supported SPD system. The effects of AHLs from SPD system on biofilm formation were conducted by batch experiments. The results revealed that exogenous addition of N-(3-Oxotetradecanoyl)-L-homoserine lactone (3-oxo-C14-HSL) resulted in the highest concentration of TB-EPS, reaching 254.2 mg/L. 3-oxo-C14-HSL has a more pronounced effect on TB-PN synthesis. However, exogenous addition of 3-oxo-C12-HSL increased the negatively charged LB-EPS content, resulting in the electrostatic exclusion and reduced cell attachment capacity and a lower degree of microbial adhesion. Furthermore, the presence of exogenous 3-oxo-C14-HSL AHLs promoted the formation of tryptophan-like proteins and humic acids. The biofilm thickness and adhesion force in EPS were 47.75 uM and 4.0 uN, respectively, when adding 3-oxo-C14-HSL. Confocal laser scanning microscopy (CLSM) studies demonstrated that the 3-oxo-C14-HSL-mediated QS system enhanced the formation of bioaggregates and increased biofilm thickness in biological denitrification. These findings confirm the involvement of AHLs-mediated QS in the regulation of biofilm characteristics and formation in SPD systems. The insights gained from this study contribute to the theoretical understanding of QS and provide practical guidance for biofilm acclimation in SPD systems.
Towards Smart Home Automation Based on Containerization
Authors: tarhouni mounira , ALOUI ibrahim 
Published: August 2024

Abstract

This article describes an advanced container-based smart home automation system that is optimized for the administration of IoT devices and sensors. Using Docker and Docker Compose on a Raspberry Pi, the system provides streamlined and efficient operations. A Dockerized Django backend handles data processing and authentication with high efficiency. Integrated AI programs improve the system’s capabilities such as text classification.A Flutter-based mobile application facilitates user engagement and provides a variety of features such as facial recognition login, complete weather management, voice commands and advanced smart surveillance. The containerized architecture improves the system's efficiency while simultaneously ensuring scalability, making it an effective option for modern home automation demands.
Job preferences of Master Public Health candidates in Northeast China based on discrete choice experiments
Authors: Cheng Huaizhi , Tian Ruotong , Chen Dongquan , Shang Jiesen , Gao Lingxiao , Dong Xiaoyu , Guo Bin , Liu Guoxiang 
Published: August 2024

Abstract

Background
The shortage of health workers in rural and remote areas is a key issue for global health systems, including China. Public health undertakings in Northeast China face the risk of a talent gap. In September 2023, the National Development and Reform Commission (NDRC) held a symposium on promoting the comprehensive revitalization of Northeast China in the New Era, proposing to support the comprehensive revitalization of Northeast China with high-quality population development, strengthen the development and utilization of human resources, and increase policy support for the revitalization of talent.
Methods
The questionnaire was designed by discrete choice experiments, and 1208 public health master’s candidates from six universities in Northeast China were investigated online via the Powercx system network survey platform in April 2024. The mixed logit model was used to analyze the job preferences of public health master candidates.
Results
All 7 attributes included in the study had statistically significant effects on the job preferences of public health master’s degree candidates (P < 0.05). They tended to choose jobs with higher monthly income (12,000 CNY/month), located in cities with good working environments and with bianzhi when seeking jobs. There is heterogeneity in job preference, and different preference characteristics are displayed in different subgroups.
Conclusion
This study revealed that public health master’s degree candidates in Northeast China were more willing to choose jobs with higher monthly incomes, working places in cities and better working environments. The way to formulate a combination of policy packages is more attractive than improving a single aspect alone. Since the preferences of each subgroup are different, the preference characteristics of the target population should also be considered when formulating the policy package to meet the challenges of talent attraction and retention.
Investigating practices and difficulties in communicating with patients about COVID-19 vaccination among healthcare workers in Italy
Authors: Polla Giorgia Della , Giudice Grazia Miraglia , Cirillo Raffaele , Sansone Vincenza , Napolitano Francesco 
Published: August 2024

Abstract

The aims of this cross-sectional study were to understand the healthcare workers’ (HCWs) practices and difficulties in communicating with patients about COVID-19 vaccinations, to investigate the factors associated, and to identify targets to improve the efficacy of the COVID-19 immunization strategy. Questionnaires were administered between November 2021 and March 2022 in three immunization centers in Italy. More than half of HCWs (56.8%) reported to often/always recommend COVID-19 vaccination to their patients, and the recommendations for other vaccinations were provided by 50.4% of the participants. Physicians/medical residents, males, and those who recommended other vaccinations to their patients were more likely to often/always recommend COVID-19 vaccination. The participants’ perception of difficulties in communicating with patients about COVID-19 vaccination and the impact of sources of information on patients’ knowledge about vaccination, explored using a ten-point Likert-type scale, resulted in a mean value of 6.3 and 7.9, respectively. A higher level of perception regarding difficulties in communicating with patients was more likely to be found among nurses/midwives and younger HCWs. It is important to reduce HCWs’ perceived gap regarding difficulties in communicating with patients, supporting them through health policy to recommend vaccinations, and engaging them in increasing uptake rates.
Incidence of Depression, Anxiety and Stress among Final- Year Medical Students versus Internship Graduates of Faculty of Medicine, Sana'a University 2023
Authors: Al-Haddad KM , Raja'a YA , Al-Nuzaili AF , Al-Hakimi AA , Zayed AA , Al-Yosefi MA , Al-Madhfari RH , Khaled AR , AY Raja'a , Al-Garbani GA , Al-Yazidi NA , Al-Selmi SF 
Published: August 2024

Abstract

Background: Depression, anxiety, and stress among medical students are significant health issues due to their impact in the challenging journey in medicine.
Objective: To assess the relief in depression, anxiety, and stress attributed to graduation of final year medical students of Faculty of Medicine and Health science, Sana'a University, Yemen in 2023.
Methodology: Cohort design was employed. Volunteers were 408 with a response rate of 99.8%. They were contacted electronically through faculty registries. The Final year respondents were 212 and the interns were 197. The data were collected by using questionnaire that including socio-demographic characteristics and a validated self-administered questionnaire DASS-21 to assess depression, anxiety and stress. The collected data were analyzed by using (SPSS) version 26. Ethical Clearence Cetrificate was taken from The Faculty of Medicine, Sana'a University.
Results: Final year medical students had incidence rates of 74.1% depression, 66 % anxiety and 62.7 % stress. While, internship graduates 63.96% were depressed, 56.9% anxious and 45% were stressed. The relief were significant from depression (p=0.032) and stress (p<0.0001), whereas not significant P=0.067 for anxiety.
Conclusion: The rates of depression, anxiety and stress are high among both cohorts. The relief attributed to graduation was significant for depression and stress.
Modeling studies on the Interactions of Endocrine Disruptive Compound BPA and its Analogs with dsDNA
Authors: Shukla Anamika , Pandey Anwesh , Kumar Devesh 
Published: August 2024

Abstract

BPA and its derivatives have been used heavily in the manufacture of epoxy resins and polycarbonate plastics. They are mainly used in food packaging materials, dental sealants and thermal receipts. Human beings are subjected to the exposure of BPA through their diet via consumption of packed food materials. Previous studies have revealed diverse disadvantages of BPA and its halogen derivatives on plants growth and also on human body. Present work is dedicated to the detailed study of interaction between DNA and BPA derivatives through computational tools. Five different BPA derivatives namely BPA, BPAF, BPS, TBBPA and TCBPA were selected as ligands for the study whereas 5 DNA sequences with PDB ID 1BNA, 1DSC, 1RMX, 2ROU and 195D were taken as macromolecular targets. Firstly, geometry optimization of the ligands was performed and then they were subjected to three computational analysis methods, Molecular Docking, Molecular Dynamics and Quantum Mechanical/Molecular Mechanical (QM/MM) respectively. Such investigations would aid in better understanding of the toxic mechanism of BPA and bring about new scientiﬁc insights about other Bisphenol A analogues.
Comparative Analysis of Finetuning Strategies and Automated Evaluation Metrics for Large Language Models in Customer Service Chatbots
Authors: Ilse Benjamin , Blackwood Frederick 
Published: August 2024

Abstract

Customer service chatbots have become integral to the efficient operation of many businesses, offering scalable solutions to handle vast volumes of customer interactions. However, ensuring that these chatbots generate accurate, contextually appropriate, and coherent responses remains a significant challenge, particularly as the complexity of customer queries increases. The research presented introduces a novel approach to optimizing chatbot performance through an in-depth comparison of various finetuning strategies and evaluation metrics, demonstrating that Domain-Adaptive Pretraining (DAPT) provides superior accuracy, robustness, and relevance in customer service scenarios. A comprehensive experimental analysis was conducted across three distinct large language models, revealing that while DAPT excels in producing high-quality, resilient responses, parameter-efficient finetuning methods offer a resource-efficient alternative suitable for environments with limited computational capabilities. The study’s findings have critical implications for the development and deployment of customer service chatbots, emphasizing the need for careful selection of finetuning strategies aligned with specific operational requirements.