bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical modeling of the funnel multiphysical flow of fresh self-compacting concrete considering proportionate heterogeneity of aggregates
Authors: Onyelowe Kennedy C. , Kontoni Denise-Penelope N. 
Published: January 2024

AbstractFilling ability is one of the prominent rheological properties of the self-compacting concrete (SCC), which has been studied in this research work deploying the functional behavior of the concrete through the studied funnel apparatus using the coupled ANSYS-SPH interface. Seven (7) model cases were studied and optimized. The aim of this numerical study is to propose a more sustainable mix of coarse and fine aggregates proportion that allows for most minimum flow time to enhance a more efficient filling of forms during concreting. The maximum size of the coarse aggregates considered is 20 mm and that of the fine aggregates is below 4 mm. The Bingham model properties for the multiphysics (SPH)-ANSYS models’ simulation are; viscosity = 20 ≤ μ ≤ 100 and the yield stress = 50 $$\le {\tau }_{0}\le 200$$

≤

τ
0

≤
200

, standard flow time, t (s) ranges; 6 ≤ t ≤ 25 and the funnel volume is 12 L. The minimum boundary flow time, which represents the time it takes for the SCC to completely flow through a specified distance, typically measured in seconds was modeled for in the seven (7) model cases. The second case with 40% coarse mixed with 60% fine completely flowed out in 16 s, thus fulfilling the minimum flow time. This minimum flow time was considered alongside other relevant parameters and tests, such as slump flow, passing ability, segregation resistance, and rheological properties (stresses), to comprehensively assess the filling ability of SCC in this model. By considering these factors and the optimized mix (40%C + 60%F:16s), engineers and researchers can optimize the SCC mix design to achieve the desired flowability and filling performance for their specific construction applications. The multiphase optimized mix was further simulated using the coupled interface of the ANSYS-SPH platform operating with the CFX command at air temperature of 25 °C. The results show energy reduction jump at the optimized flow time. Ideally, the mix, 40%C + 60%F:16s has been proposed as the mix with the most efficient flow to achieve the filling ability for sustainable structural concrete construction.
Microbial cement grout anchoring steel reinforcement pull-out test
Authors: Jia Qiang , Zhang Tianjian 
Published: January 2024

AbstractMicrobial cement, known for its superior fluidity, stable crystal formation, and strong bond with concrete, is an effective solution in fixing defects such as voids that appear due to insufficient grouting in the joints of precast concrete components. To evaluate the mechanical properties of rebar anchored with microbial cement grout, three pull-out tests were designed, taking into account parameters such as calcium source concentration, the filler in borehole voids, and the shape of the rebar. The results indicate that specimens with a higher concentration of calcium source require fewer grouting cycles, but the pull-out bearing capacity of the anchored rebar is lower. However, the introduction of quartz sand as a filler in the borehole voids results in a significant increase in the pull-out bearing capacity of the rebar compared to specimens without filler. Among these, the specimens with a medium particle size of 0.5 ~ 1 mm (1/4δ ~ 1/2δ, the gap of δ = 2 mm between the steel bars and hole wall) have the highest pull-out bearing capacity. In comparing rebar shapes, ribbed rebar slightly outperforms smooth round rebar in terms of pull-out bearing capacity. Based on the experimental results analysis, the anchoring mechanism of microbial cement grouting on reinforcement has been elucidated.
New marker for chronic kidney disease progression and mortality in medical-word virtual space
Authors: Kanda Eiichiro , Epureanu Bogdan I. , Adachi Taiji , Sasaki Tamaki , Kashihara Naoki 
Published: January 2024

AbstractA new marker reflecting the pathophysiology of chronic kidney disease (CKD) has been desired for its therapy. In this study, we developed a virtual space where data in medical words and those of actual CKD patients were unified by natural language processing and category theory. A virtual space of medical words was constructed from the CKD-related literature (n = 165,271) using Word2Vec, in which 106,612 words composed a network. The network satisfied vector calculations, and retained the meanings of medical words. The data of CKD patients of a cohort study for 3 years (n = 26,433) were transformed into the network as medical-word vectors. We let the relationship between vectors of patient data and the outcome (dialysis or death) be a marker (inner product). Then, the inner product accurately predicted the outcomes: C-statistics of 0.911 (95% CI 0.897, 0.924). Cox proportional hazards models showed that the risk of the outcomes in the high-inner-product group was 21.92 (95% CI 14.77, 32.51) times higher than that in the low-inner-product group. This study showed that CKD patients can be treated as a network of medical words that reflect the pathophysiological condition of CKD and the risks of CKD progression and mortality.
Stable isotopes in the shell organic matrix for (paleo)environmental reconstructions
Authors: Paleček Dragana , Milano Stefania , Gutiérrez-Zugasti Igor , Talamo Sahra 
Published: January 2024

AbstractStable isotope ratios of mollusc shell carbonates have long been used to reconstruct past environmental conditions. Although shells also contain organics, they are seldom used in (paleo)climatic studies. Here, we extract the acid-soluble and insoluble fractions of the organic matrix of modern Mytilus galloprovincialis shells from three sites along a coast–to-upper-estuary environmental gradient to measure their hydrogen (δ2H) and oxygen (δ18O) isotope compositions. Both organic fractions showed isotopic signatures significantly different from those of carbonate and water at each site, indicating the involvement of different fractionation mechanisms. The soluble fraction showed gradual differences in isotope values along the gradient, while the insoluble fraction showed δ2H-δ18O correlation regressions subparallel to the Global and Local Meteoric Water Lines. These results showed the great potential of the shell organic matrix stable isotopes as possible (paleo)environmental proxies, stimulating further research to better define the fractionation mechanisms involved.
Elucidating the impact of oxygen functional groups on the catalytic activity of M–N4–C catalysts for the oxygen reduction reaction: a density functional theory and machine learning approach
Authors: Xie Liang , Zhou Wei , Huang Yuming , Qu Zhibin , Li Longhao , Yang Chaowei , Ding Yani , Li Junfeng , Meng Xiaoxiao , Sun Fei , Gao Jihui , Zhao Guangbo , Qin Yukun 
Published: January 2024

While current experimental and computational studies often concentrate on introducing external structures or idealized MN4 models, we emphasize the often-overlooked impact of inherent OGs within the carbon structure of MN4 materials, presenting a new perspective on their catalytic activity origin.
Interview completed: the application of survival analysis to detect factors influencing response rates in online surveys
Authors: Münnich Ákos , Kocsis Mátyás , Mainwaring Mark C. , Fónagy István , Nagy Jenő 
Published: January 2024

AbstractMarketing interviews are widely used to acquire information on the behaviour, satisfaction, and/or needs of customers. Although online surveys are broadly available, one of the major challenges is to collect high-quality data, which is fundamental for marketing. Since online surveys are mostly unsupervised, the possibility of providing false answers is high, and large numbers of participants do not finish interviews, yet our understanding of the reasons behind this pattern remains unclear. Here, we examined the possible factors influencing response rates and aimed to investigate the impact of technical and demographic information on the probability of interview completion rates of multiple surveys. We applied survival analysis and proportional hazards models to statistically evaluate the associations between the probability of survey completion and the technical and demographic information of the respondents. More complex surveys had lower completion probabilities, although survey completion was increased when respondents used desktop computers and not mobile devices, and when surveys were translated to their native language. Meanwhile, age and gender did not influence completion rates, but the pool of respondents invited to complete the survey did affect completion rates. These findings can be used to improve online surveys to achieve higher completion rates and collect more accurate data.
Fraudsters target the elderly: Behavioural evidence from randomised controlled scam-baiting experiments
Authors: Robinson Jemima , Edwards Matthew 
Published: January 2024

AbstractEmail-based fraud is a lucrative market for cybercriminals to scam a wide range of potential victims. Yet there is a sometimes conflicted literature on who these victims are, complicated by low and possibly confounded reporting rates. We make use of an experimental automated scam-baiting platform to test hypotheses about the characteristics online fraudsters find more attractive, gathering behavioural evidence directly from the fraudsters themselves (n = 296). In our comparison of four instrumented ‘personalities’ designed based on traits highlighted in the literature and in a small public perception survey, we find that a script adopting the personality of an elderly woman attracts significantly more engagement from scammers than our control measure. We discuss our approach and the possible interpretations and implications of our findings.
A study on identification of youth identity through a gender lens in network buzzwords: A critical discourse analysis
Authors: Tan Huawei , Yu Yating 
Published: January 2024

AbstractAs an emerging form of discourse in the Internet era, network buzzwords serve as an indicator of the mentality of the youth, reflecting their identity. However, research on the implementation of network buzzwords in the context of gender formations has been limited. This study fills this research gap by using critical discourse analysis to analyse the use of 11 gender-specific buzzwords listed in the annual list of top-ten network buzzwords published by the magazine Yaowen Jiaozi from 2012 to 2021 on the social media platform, Weibo. It discusses how the gender network buzzwords shape the identity of young groups, what kind of identities were formed, and how young people use gender buzzwords to construct both gender-conforming and patriarchal discourse, as well as gender-nonconforming discourse, from the perspectives of conformity and nonconformity. Additionally, it discusses the cultural significance of network buzzwords and their potential impact on contemporary society.
Generation of spatial combs digitized by orbital angular momentum
Authors: Shahar Daniel I. , Kabagöz Havva Begüm , Ramachandran Siddharth 
Published: January 2024

Shaping the transverse spatial domain of light has been experiencing recent growth in attention for its applications in optical tweezing, microscopy, communications, and quantum information sciences. The orbital angular momentum (OAM) of light is a transverse physical property that functions as a viable basis for many of such applications. While fields containing a single OAM mode order have extensively been used, fields containing a broad, discrete, and equally spaced OAM spectrum—an OAM comb—has largely been unexplored due to a lack of viable creation methods. Much like how frequency combs enabled myriad applications, it is conceivable that OAM combs would likewise enable further opportunities or expand upon single-OAM applications. For instance, an OAM comb may pave the way for more sophisticated particle manipulation, object detection, and pump shaping for high-dimensional spatial-mode entanglement. Here, we create four OAM combs with rectangular, sinusoidal, sinc, and Gaussian OAM spectral distributions using multiplane light conversion, which only involves phase modulations (hence is inherently lossless) and allows for improved tailoring of the spatial shape. The verification of such combs is done qualitatively by analyzing their propagation evolutions and quantitatively by employing a mode sorting technique—both exhibiting good agreement with user specifications and simulations. The scattering losses of all four combs were measured to be minimal, ranging from 0.66 to 1.04 dB.
Electromagnetohydrodynamic flow through a periodically grooved channel
Authors: Dewangan Mainendra Kumar , Persoons Tim 
Published: January 2024

Abstract
This paper harnesses the spectral approach to study electromagnetohydrodynamics (EMHD) flow through an undulating 2D microchannel for a Newtonian fluid. The present study aims to investigate EMHD flow through a periodically patterned channel for large values of corrugation amplitude (surface roughness) relative to the channel height, Hartmann number and a wide range of wavelengths. A mathematical model is developed for the hydraulic permeability and the velocity field using the Fourier approach. By imposing a small pattern amplitude constraint, asymptotic analysis was employed to investigate the model presented in the literature. In the present study, hydraulic permeability is shown to strongly depend on the Hartmann number, pattern amplitude and wavelength. The spectral method predicts a monotonic decrease in hydraulic permeability irrespective of pattern amplitude at a small dimensionless wavelength (λ = 1) and Hartmann number (Ha < 1). At large wavelengths (λ > 3), the hydraulic permeability demonstrates an augmentation corresponding to the pattern amplitude. At intermediate wavelength (

2.5
<
λ
<
3

), the permeability of the channel firstly decreases and then increases with pattern amplitude. For large Hartmann numbers

(
H
a
≫
1
)

, the prediction from the spectral model exhibits a similar trend as a function of wavelength. Across a range of wavelengths, the spectral model captured the permeability minima for various large Hartmann number values. The spectral model is significantly faster than the finite-element-based numerical simulation, with computational efficiency ranging from 150 to 250 times higher. The existence of a limited pattern amplitude and Hartmann number for small-large wavelength patterns, at which the permeability of the channel is minimized, is one example of a prediction from the spectral model that is beyond the resolution of currently accessible asymptotic theories.
Digital twins for metrology; metrology for digital twins
Authors: Wright Louise , Davidson Stuart 
Published: January 2024

Abstract
Digital twinning is a rapidly growing area of research. Digital twins combine models and data to provide up-to-date information about the state of a system. They support reliable decision-making in fields such as structural monitoring and advanced manufacturing. The use of metrology data to update models in this way offers benefits in many areas, including metrology itself. The recent activities in digitalisation of metrology offer a great opportunity to make metrology data ‘twin-friendly’ and to incorporate digital twins into metrological processes. This paper discusses key features of digital twins that will inform their use in metrology and measurement, highlights the links between digital twins and virtual metrology, outlines what use metrology can make of digital twins and how metrology and measured data can support the use of digital twins, and suggests potential future developments that will maximise the benefits achieved.
Virtual dosimetry study with three cone-beam breast computed tomography scanners using a fast GPU-based Monte Carlo code
Authors: Mettivier Giovanni , Lai Youfang , Jia Xun , Russo Paolo 
Published: January 2024

Abstract

Objective. To compare the dosimetric performance of three cone-beam breast computed tomography (BCT) scanners, using real-time Monte Carlo-based dose estimates obtained with the virtual clinical trials (VCT)-BREAST graphical processing unit (GPU)-accelerated platform dedicated to VCT in breast imaging. Approach. A GPU-based Monte Carlo (MC) code was developed for replicating in silico the geometric, x-ray spectra and detector setups adopted, respectively, in two research scanners and one commercial BCT scanner, adopting 80 kV, 60 kV and 49 kV tube voltage, respectively. Our cohort of virtual breasts included 16 anthropomorphic voxelized breast phantoms from a publicly available dataset. For each virtual patient, we simulated exams on the three scanners, up to a nominal simulated mean glandular dose of 5 mGy (primary photons launched, in the order of 1011–1012 per scan). Simulated 3D dose maps (recorded for skin, adipose and glandular tissues) were compared for the same phantom, on the three scanners. MC simulations were implemented on a single NVIDIA GeForce RTX 3090 graphics card. Main results. Using the spread of the dose distribution as a figure of merit, we showed that, in the investigated phantoms, the glandular dose is more uniform within less dense breasts, and it is more uniformly distributed for scans at 80 kV and 60 kV, than at 49 kV. A realistic virtual study of each breast phantom was completed in about 3.0 h with less than 1% statistical uncertainty, with 109 primary photons processed in 3.6 s computing time. Significance. We reported the first dosimetric study of the VCT-BREAST platform, a fast MC simulation tool for real-time virtual dosimetry and imaging trials in BCT, investigating the dose delivery performance of three clinical BCT scanners. This tool can be adopted to investigate also the effects on the 3D dose distribution produced by changes in the geometrical and spectrum characteristics of a cone-beam BCT scanner.
Utility of realistic microscopy-based cell models in simulation studies of nanoparticle-enhanced photon radiotherapy
Authors: Antunes Joana , Pinto Catarina I G , Campello Maria Paula Cabral , Santos Pedro , Mendes Filipa , Paulo António , Sampaio Jorge M 
Published: January 2024

Abstract
To enhance the effect of radiation on the tumor without increasing the dose to the patient, the combination of high-Z nanoparticles with radiotherapy has been proposed. In this work, we investigate the effects of the physical parameters of nanoparticles (NPs) on the Dose Enhancement Factor (DEF), and on the Sensitive Enhancement Ratio (SER) by applying a version of the Linear Quadratic Model. A method for constructing voxelized realistic cell geometries in Monte Carlo simulations from confocal microscopy images was developed and applied to Gliobastoma Multiforme cell lines (U87 and U373). The comparison of simulations with realistic geometry and spherical geometry shows that there is significant impact on the survival curves obtained for the same irradiation conditions. Using this model, the DEF and the SER are determined as a function of the concentration, size and distribution of gold nanoparticles within the cell. For small NPs, d
AuNP = 10 nm, no clear trend in the DEF and SER was observed when the number of NPs within the cell increases. Experimentally, the variable number of NPs measured inside the U373 cells (ranging between 1.48 × 105 and 1.19 × 106) also did not influence much the observed cell survival upon irradiation of the cells with a Co-60 source. The same lack of trend is obtained when the Au content in the cell is kept constant, 0.897 mg/g, but the size of the NPs is changed. However, if the number of NPs is kept constant (7.91 × 105) and the size changes, there is a critical diameter above which the dose effect increases significantly. Using the realistic geometries, it was verified that the key parameter for the DEF and the SER enhancement is the volume fraction of Au in the cell, with NP size being a more important parameter than the number of NPs.
Evaluating weather impact on vehicles: a systematic review of perceived precipitation dynamics and testing methodologies
Authors: Pao Wing Yi , Carvalho Mateus , Hosseinnouri Farimah , Li Long , Rouaix Clement , Agelin-Chaab Martin , Hangan Horia , Gultepe Ismail , Komar John 
Published: January 2024

Abstract
The performance of road vehicles degrades when driving in adverse weather conditions. Weather testing for vehicles is important to understand the impacts of precipitation on vehicle performance, such as driver visibility, autonomous sensor signal, tire traction, and structural integrity due to corrosion, to ensure safety. This tutorial summarizes the essential elements for performing realistic testing by applying physical and meteorological rationale to vehicle applications. Three major topics are identified as crucial steps for precise quantitative studies, including understanding the natural precipitation characteristics, estimating the perceived precipitation experienced by a moving vehicle, and selecting data collection strategies. The methods used in current practices to investigate the effects of rain and snow on road vehicles at common facilities of outdoor test tracks, drive-through weather chambers, and climatic wind tunnels are summarized. The testing techniques and relevant instrumentations are also discussed, with considerations of factors that influence the measured data, such as particle size distribution, precipitation intensity, wind-induced droplet dynamic events, accumulation behaviour, etc. The goals of this paper are to provide a tutorial with guidelines on designing weather testing experiments for road vehicles and to promote the idea of establishing standardized methodologies for realistic vehicle testing that facilitates accurate prediction of vehicle performance in adverse weather conditions.
Analysis of heat generation during friction stir welding of aluminum alloy 2024-T4 and its impact on joint characteristics
Authors: Kumar Deepak , Sinha A N 
Published: January 2024

Abstract
Friction stir welding (FSW) is a successful welding technique for joining of aluminium and many other materials with the required joint configurations. During this welding process, large amount of heat is generated, which influences the integrity, performance, and microstructure of the weld joints. In this study, both experimental and numerical approaches are adopted to analyse the influence of heat generation on the metallurgical and mechanical properties of friction stir-welded joints of AA2024-T4. A computational fluid dynamics (CFD) model is constructed for quantitative analysis of heat flux, heat generation, temperature distribution, strain rate and viscosity. The model is validated by experimentally measured temperature data, and both agree well. The results showed that both heat flux and strain rate are more or less symmetric about the tool axis whereas plastic material flow is asymmetric. Heat flux affects the grain size and mechanical properties of the joint.