bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Timing for Subsequent Water Flooding in Alkali-Surfactant- Polymer Flooding in Daqing Oilfield Based on Automated Machine Learning
Authors: Jiang Wenchao , Hou Zhaowei , Yao Shichun , Wu Xiaolin , Gai Jian , Nie Chunlin , Su Xu , Lu Shouliang , Wang Yunchao , Huang Bin , Dong Chi , Liu Di , Jiang Jiang , Yu Xiaodan , Wang Yane , Zhang Jifeng , Zhao Changjiu , Yang Erlong , He Xiaoru , Qi Guangming , Li Jingya 
Published: September 2024

Abstract

Whether the timing of subsequent water flooding in ASP flooding is reasonable or not directly determines the technical and economic benefit of the block. In order to carry out the research on the reasonable timing for subsequent water flooding, 8 evaluation parameters affecting the technical and economic benefits of ASP flooding blocks were selected, and the selection range of each evaluation parameter was determined according to the completed blocks and actual data. The optimized timing for subsequent water flooding was obtained based on the change of the cumulative net profit in the whole process of ASP flooding. On this basis, using machine learning technology, an optimization design model of reasonable timing for subsequent water flooding was established. The work efficiency was greatly improved, while the timeliness and reliability were guaranteed. The model was used to calculate the optimized timing for the subsequent water flooding of 6 blocks which were in the chemical flooding slug in Daqing oilfield. The injection scheme such as extending slug was adjusted according to the optimization results. The result shows that the cumulative net profit of these block increased by 224.9 million CNY than the original scheme, the predicted final increase will be 752.1 million CNY.
Stress perception and the developmental trajectory of smart phone addiction among college students:Based on Parallel Latent Variable Growth Modeling
Authors: Ye Zicong , Peng Ying , Huang Xiantao , Rao Wei , Yao Jie , Zhang Ting 
Published: September 2024

Abstract

Purpose In recent years, the problem of smart phone addiction among college students has become increasingly serious, which has aroused the attention of colleges and universities at home and abroad. Based on the general stress theory, this study explores the development of stress perception and smart phone addiction among college students over a semester, while further exploring the causal relationship between the two. Methods A longitudinal study was conducted utilizing a physical education classroom to administer questionnaires on students' stress perception and smart phone addiction levels. The test was administered three times at the beginning, middle, and end of the semester, resulting in 517 valid participants. Data were processed using SPSS and Mplus to explore trends in their stress perception and smart phone addiction using potential growth modeling, as well as causal relationships between the aforementioned variables using cross-lagged modeling. Results (1) The levels of college students' stress perception and smart phone addiction showed a linear trend of weakening over time; (2)There is a significant positive effect of the intercept of college student stress on the intercept of smart phone addiction and a significant negative effect on the slope of smart phone addiction;(3)The intercept of smart phone addiction among college students has a significant negative impact on the slope of stress perception;(4)The slope of smart phone addiction among college students has a significant positive impact on the slope of stress perception;(5) college students' stress perception and smart phone addiction were causally related to each other. Conclusion This study reveals the developmental trajectories of stress perception and smart phone addiction among college students over the course of a semester, and explores the causal relationship between the two. These findings may provide insight into how stress perception affects smart phone addictive behaviors, and provide a scientific basis for the development of effective preventive and intervention measures.
Determinants of Financial Stability: A Dynamic Panel Data Analysis
Authors: Tsegaye Adane Tilahun , Irena Obsa Teferi , Tesfaye Getahun Daribie 
Published: September 2024

Abstract

Financial soundness is crucial for the health of the financial sector and economic stability. The study examines the degree of financial stability and its drivers in commercial banks using dynamic panel data analysis. Arellano & Bover and Blundell & Bond a two-step system GMM model were applied to test the hypothesis. The 'Z-score' was used as a proxy for financial stability. The results indicate that the previous year's financial stability, profitability, and liquidity positively influenced financial stability, while bank size, credit risk, and bank concentration have negative impacts. External factors including the GDP growth rate positively affected financial stability, whereas real interest rates have a negative impact on the financial stability of the banks. The findings of this study will have implications for banks, bank regulators, policymakers, and the government in fostering a stable banking environment through targeted policies and strategic management of financial metrics.
Moderating effect of physical activity on stigma and psychological distress in children and adolescents with epilepsy: a multicenter cross-sectional study in China
Authors: Zhao Jing , Li Shuangzi , Zhang Ni , Zeng Junqi , Xie Yuan , Wang Ting , Xia Qing 
Published: September 2024

Abstract

Objective: Children and adolescents with epilepsy suffer from stigma. Stigma associated with epilepsy is closely related to poor physical activity (PA) and high levels of psychological distress. However, the internal relationships are not well understood in China. This study aims to investigate the mediating effect of PA to determine whether PA mediates the relationship between stigma and psychological distress among children and adolescents with epilepsy.
Methods: A multicenter cross-sectional design was used to study children and adolescents with epilepsy admitted to 9 tertiary hospitals in China. Data were collected using a questionnaire measuring the Kilifi Stigma Scale for Epilepsy, the Depression Anxiety and Stress Scale, and the Physical Activity Rating Scale. The PROCESS macro in SPSS was used to examine the mediation model.
Results: 226 children and adolescents with epilepsy participated in the study. Psychological distress increased considerably as stigma levels increased, while a decrease was observed with increasing levels of PA. The results showed PA mainly plays partial mediating roles in the relationship between stigma and depression (ab = 0.042, 95% CI: 0.016 to 0.068), anxiety (ab = 0.077, 95% CI: 0.054 to 0.099) and stress (ab = 0.092, 95% CI: 0.061 to 0.122) dimensions of psychological distress. Additionally, intensity (ab = 0.027, 95% CI: 0.007 to 0.048) and frequency (ab = 0.028, 95% CI: 0.010 to 0.049) respectively only intermediated the relationship between stigma and anxiety and stress; duration (ab = 0.023, 95% CI: 0.002 to 0.044; ab = 0.034, 95% CI: 0.015 to 0.055; ab = 0.037, 95% CI: 0.012 to 0.061) all mediated between stigma and the psychological distress dimensions.
Conclusion: Stigma could increase psychological distress by indirectly influencing PA and its components. Interventions to improve physical activity may prevent or reduce psychological distress among children and adolescents with epilepsy.
A Compact UWB-MIMO Antenna with Enhanced Isolation for Short distance V2X Communications
Authors: Kumari E. Kusuma , Szymański Jerzy R. , Żurek-Mortka Marta , Sathiyanarayanan Mithileysh 
Published: September 2024

Abstract

The main focus of this work is the design and parametric study of a compact Ultra Wide Band (UWB) Multiple Input Multiple Output (MIMO) antenna with three ports loaded with DGS and elliptical slots on the ground plane to enhance isolation and bandwidth. The dimensions of the proposed constructed antenna are 26 x 50 x 0.8 mm. The FR4 is used as a substrate, its dielectric constant is 4.4. The suggested Antenna was simulated using the HFSS Software tool and evolved over five steps. Based on simulation findings, it is noted that the antenna falls inside the Ultra Wide Band, ranging from 3.6 GHz to 10.06 GHz, and has an isolation of more than -43 dB. Even with the patches' modest end-to-end gap of 8 mm, it is apparent that the suggested antenna exhibits good isolation. Important factors that evaluate the effectiveness of the antenna are examined, including radiation pattern, diversity gain, surface current distribution, peak gain, Total Active Reflection Coefficient (TARC), and Envelope Correlation Coefficient (ECC) below 0.05. The measured Diversity Gain (DG) of the MIMO antenna is more than 9.98 dB, its TARC is observed as -10 dB, and its estimated ECC was less than 0.002. Using a computer-aided design (CAD) model of the vehicle, the antenna’s performance was examined to estimate the antenna's dependability in the presence of metallic bodies. The results show that due to its low profile and satisfactory functionality, the suggested antenna is well suited to high throughput compact UWB transceivers in Connected Vehicle Technology and V2V Communication applications.
Genome-Wide Association Study of Haploid Female Fertility (HFF) and Haploid Male Fertility (HMF) in BS39-Derived Doubled Haploid Lines
Authors: Fakude Mercy , Murithi Ann , Frei Ursula K. , Scott Paul M. , Lübberstedt Thomas 
Published: September 2024

Abstract

Doubled haploid (DH) breeding accelerates the development of elite inbred lines and facilitates the incorporation of exotic germplasm, offering a powerful tool for maize improvement. Traditional DH breeding relies on colchicine to induce haploid genome doubling. Colchicine is toxic, and its application is labour-intensive, with most genotypes recording low genome doubling rates (10% to 30%). This study investigates spontaneous haploid genome doubling (SHGD) as a safer and more efficient alternative to colchicine. We evaluated the effectiveness of SHGD in restoring haploid female fertility (HFF) and haploid male fertility (HMF) without colchicine. Using genome-wide association studies (GWAS), we identified genomic regions influencing HFF and HMF. The plant materials included the BS39-haploid isogenic lines (HILs) and BS39-SHGD-haploid isogenic lines (HILs). Our results revealed significant SNP associations for both traits, with candidate genes involved in cell cycle regulation, cytoskeletal organization, and hormonal signalling. Analysis of variance (ANOVA) revealed significant variation in HFF across haploids and two environments. Similarly, HMF showed substantial differences across haploids and between the two environments. Spearman correlation between HFF and HMF showed no correlation (r = -0.03) between the two traits. HFF showed high heritability (0.8), indicating strong genetic control, whereas HMF displayed moderate heritability (0.5), suggesting additional environmental influences. The findings underscore the potential of SHGD to enhance DH breeding efficiency and support the development of new maize varieties tailored to diverse agricultural needs.
Experimental study of the impact of deck-charge structure on blast-induced fragmentation
Authors: Hong Zhixian , Tao Ming , Feng Shurong , Liu Hao , Wu Wenhong , Li Xudong , Liu Shuai 
Published: September 2024

Abstract

The deck-charge structure, also referred to as axially decoupled charge structure, has found widespread application in open-pit rock excavation to enhance blasting performance. However, the relationships between blast-induced fragmentation and deck-charge structures remain unclear. This paper aims to experimentally investigate the influences of deck ratio, deck position and deck material on blast-induced fragmentation. Small-scale single-hole blasting experiments were conducted on concrete blocks (400×400×200 mm3). The dynamic evolution process of model fracturing under blast loading was captured using a high-speed camera. The displacement and strain fields were analyzed employing a 3D digital image correlation system (DIC), and the fragment size distribution (FSD) was determined through ImageJ, which is an advanced image-processing code. Meanwhile, the blasthole wall pressure (BWP) was monitored through the embedded gauges in the test block. The experimental results indicate that under a deck charge blasting, the host concrete experiences three phases, i.e., crushing phase, further crushing and fracturing phase, and radial crack developing phase. The fragmentation performance increases within a reasonable range of air-deck ratio, while an excessive deck ratio results in worse fragmentation compared to fully coupled charge blasting. The center deck charge yields the superior fragmentation, followed by the double-ends deck charge and top deck charge. Water-deck charge produces finer fragmentation than air-deck and PE-deck charges. EPS-deck charge is not conducive to fragmentation, but it may provide a solution for reducing vibration and controlling damage to the remaining rock mass. Based on the experiment results, production blasts with fully coupled charge, center air-deck charge and center water-deck charge were conducted in an open-pit mine, revealing that the proposed center deck charge blasting results in at least a 15% reduction in median fragment size, with center water-deck charge outperforming in rock fragmentation due to its ability to maximize the utilization of explosive energy for rock fracturing.
The burden of ambient air pollution on years of life lost from ischaemic heart disease in Pudong New Area, Shanghai
Authors: Zhong Xing , Chen Yichen , Sun Lianghong , Chen Hua , Qu Xiaobing , Hao Lipeng 
Published: September 2024

Abstract

Ischaemic heart disease (IHD) remains a major public health threat globally. The aim of this study was to evaluate the short-term burden of air pollution exposure on years of life lost (YLLs) from IHD in Pudong New Area, Shanghai. Data on air pollutants, meteorological factors, and daily IHD deaths were collected from 2013 to 2021. A distributed lag nonlinear model (DLNM) combined with linear (for YLLs) and quasi-Poisson (for mortality) regression models was applied to analyse the association between air pollution exposure and the IHD burden. A stratified analysis was conducted according to sex, age, and educational level. Each 10 µg/m³ increase in PM10, SO2, and NO2 exposure was associated with YLL increases of 0.40 (95% CI: -0.32, 1.11), 4.38 (95% CI: 0.83, 7.92), and 0.67 (95% CI: -0.71, 2.04) years, respectively, at lag0-3. The corresponding YLL increase due to PM2.5 exposure was 0.28 (95% CI: -0.24, 0.80) years at lag0-1. The impacts of air pollution exposure on YLLs and daily IHD deaths were greater for males than for females. Furthermore, the difference in SO2 exposure effects was statistically significant among sex-stratified groups. Air pollution exposure was positively associated with IHD-related YLL increases in Pudong New Area, Shanghai.
Pretrained Language Models for Semantics-Aware Data Harmonisation of Observational Clinical Studies in the Era of Big Data
Authors: Dylag Jakub J. , Zlatev Zlatko , Boniface Michael 
Published: September 2024

Abstract

Background:
In clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase the efficiency of healthcare delivery. However, realising these potential demands requires substantial efforts in harmonising source datasets and curating study data, which currently relies on costly, time-consuming and labour-intensive methods. We explore and assess the use of natural language processing (NLP) and unsupervised machine learning (ML) to address the challenges of big data semantic harmonisation and curation.
Methods:
Our aim is to establish an efficient and robust technological foundation for the development of automated tools supporting data curation of large clinical datasets. We propose two AI based pipelines for automated semantic harmonisation: a pipeline for semantics-aware search for domain relevant variables and a pipeline for clustering of semantically similar variables. We evaluate pipeline performance using 94,037 textual variable descriptions from the English Longitudinal Study of Ageing (ELSA) database.
Results:
We observe high accuracy of our Semantic Search pipeline, with an AUC of 0.899 (SD = 0.056). Our semantic clustering pipeline achieves a V-measure of 0.237 (SD = 0.157), which is on par with that of leading implementations in other relevant domains. Automation can significantly accelerate the process of dataset harmonisation. Manual labelling was performed at a speed of 2.1 descriptions per minute, with our automated labelling increasing speed to 245 descriptions per minute.
Conclusions:
Our study findings underscore the potential of AI technologies, such as NLP and unsupervised ML, in automating the harmonisation and curation of big data for clinical research. By establishing a robust technological foundation, we pave the way for the development of automated tools that streamline the process, enabling health data scientists to leverage big data more efficiently and effectively in their studies and accelerating insights from data for clinical benefit.
Experimental observation of gapped shear waves and liquid-like to gas-like dynamical crossover in active granular matter
Authors: Zhang Jie , Jiang Cunyuan , Zheng Zihan , Chen Yangrui , Baggioli Matteo 
Published: September 2024

Abstract

Unlike crystalline solids, liquids do not exhibit long-range order due to frequent structural rearrangements. When considering shorter time and length scales, molecular dynamics simulations and theoretical propositions suggest that collective shear excitations in liquids display a gap in wave-vector space, referred to as the k-gap. Above this gap, solid-like transverse waves re-emerge. However, direct experimental verification of this phenomenon in classical liquids remains elusive, with the only documented evidence from studies in two-dimensional dusty plasmas. Active granular systems provide a novel platform for exploring the emergence of collective dynamics and showcasing a rich interplay of complex phases and phenomena. Our study focuses on bi-disperse active Brownian vibrators. In this work, we demonstrate that this active system exhibits both gas-like and liquid-like phases, depending on the packing fraction, despite pure hard-disk-like repulsive interactions. Notably, within the granular liquid-like phase, we experimentally validate the existence of a k-gap in the dispersion of transverse excitations. Our results offer a direct experimental confirmation of the k-gap phenomenon, extending its relevance beyond classical thermal liquids to active granular systems, and reveal the existence of intriguing similarities between the physics of active granular matter and supercritical fluids.
Scalable Recurrence Graph Network for Stratifying RhoB Texture Dynamics in Rectal Cancer Biopsies
Authors: Pham Tuan 
Published: September 2024

Abstract

Background: RhoB plays a crucial role in cellular processes. Its expression, evaluated via immunohistochemistry (IHC), serves as a significant biomarker for predicting survival outcomes in cancer patients, particularly in response to radiotherapy (RT). However, the accuracy and reliability of RhoB expression assessments can be compromised by variability in staining techniques and tumor heterogeneity.

Methods: This study introduces the scalable recurrence graph network (SRGNet) to improve the accuracy and reliability of five-year survival predictions for patients with rectal cancer. SRGNet integrates principles of spatial statistics, nonlinear dynamics, graph theory, and graph convolutional networks (GCNs). Spatial statistics aims to capture the distribution of protein expression, while nonlinear dynamics can model complex temporal changes within tumor biopsies. Graph theory represents relationships between texture recurrences, and GCN architecture enables graph node classification.

Results: SRGNet outperformed 10 pre-trained convolutional neural networks. For biopsy samples with RT, SRGNet achieved an accuracy of 88%, predicting five-year survival with 100% accuracy. It demonstrated a precision of 100% and an F1 score of 0.80, with an AUC of 0.73. For biopsy samples without RT, SRGNet obtained an accuracy of 91%, predicting survival over five years with perfect precision (100%), an F1 score of 0.86, and an AUC of 0.82.

Conclusions: SRGNet can enhance the biopsy-based prediction of five-year survival outcomes for rectal cancer patients, offering a more precise and individualized assessment. Its integration of artificial intelligence and machine learning technologies addresses the challenges of variability and tumor heterogeneity in RhoB expression evaluation, leading to more reliable prognostic evaluations.
Research on Shape Memory Performance of TPI/PE Composite Materials
Authors: Zhang Tao , Ma Ruize , Xu Haohao , Xue Caihong , Liang Yurong 
Published: September 2024

Abstract

Triple shape memory materials have become a major research hotspot in recent years. Trans-1,4-polyisoprene (TPI) was mixed with inexpensive polyethylene (PE) in this work, and TPI/PE shape memory polymer composites (SMPCs) were vulcanized using the dynamic vulcanization process. PE can be divided into low-density polyethylene (LDPE) and high-density polyethylene (HDPE), both have the same structure but different molecular chain arrangement and density. Since the properties of SMPC are different due to the different ratios of TPI and PE components, choosing the right ratio is especially important for triple shape memory materials. We investigated the triple shape memory properties of composites of TPI with LDPE and TPI with HDPE at different ratios (8:2,7:3 and 6:4), respectively. The impact of the dynamic vulcanization system on the mechanical and shape memory characteristics of the TPI/PE hybrid SMPC was discovered through a sequence of studies. The results showed that when the ratio of TPI/PE was 8:2, the composites had the fastest vulcanization rate and the largest cross-linking degree with the highest tensile strength and mechanical properties. In addition, the test results show that the crystalline properties of HDPE-based composites are consistently higher than those of LDPE-based composites. The shape memory properties of TPI/HDPE composites are more excellent than those of TPI/LDPE composites at the same ratio. The best triple shape memory properties were obtained at a TPI/HDPE composite ratio of 8:2. We believe that the relevant findings of this study can provide a valuable design reference for the development of high-performance TPI shape memory materials.