bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic Evaluation of Susceptibility to Fluid Injection-Induced Seismicity Based on Statistics of Fracture Criticality
Authors: Cao Wenzhuo , Durucan Sevket , Cai Wu , Shi Ji-Quan , Korre Anna , Ratouis Thomas , Hjörleifsdóttir Vala , Sigfússon Bergur 
Published: October 2022

AbstractFault reactivation and associated microseismicity pose a potential threat to industrial processes involving fluid injection into the subsurface. In this research, fracture criticality, defined as the gradient of critical fluid pressure change to trigger seismicity (Δpc/h), is proposed as a novel reservoir depth-independent metric of fault slip susceptibility. Based on statistics of the fracture criticality, a probabilistic evaluation framework for susceptibility to injection-induced seismicity was developed by integrating seismic observations and hydrogeological modelling of fluid injection operations for faulted reservoirs. The proposed seismic susceptibility evaluation method considers the injection-driven fluid pressure increase, the variability of fracture criticality, and regional fracture density. Utilising this methodology, the probabilistic distribution of fracture criticality was obtained to evaluate the potential for injection-induced seismicity in both fault and off-fault zones at the Hellisheiði geothermal site, Iceland. It has been found that the fracture criticality within both fault and off-fault zones shows natural variability (mostly ranging between 0.001 and 2.0 bar/km), and that fault zones tend to be characterised by larger fracture criticality values than the off-faut zones. Fracture criticality values estimated within each zone roughly follow a Gaussian distribution. Fault zones around five geothermal fluid re-injection wells at the site were estimated to have relatively high probability of seismic event occurrence, and these regions experienced high levels of induced seismicity over the microseismic monitoring period. The seismotectonic state estimated for each zone is generally consistent with the forecasted susceptibility to seismicity based on statistics of fracture criticality.
Speed of convergence of Weyl sums over Kronecker sequences
Authors: Colzani Leonardo 
Published: October 2022

AbstractWe study the speed of convergence in the numerical integration with Weyl sums over Kronecker sequences in the torus, $$\begin{aligned} \dfrac{1}{N}\sum _{n=1}^{N}f\left( x+n\alpha \right) -\int _{\mathbb {T}^{d} }f(y)dy. \end{aligned}$$

1
N

∑

n
=
1

N

f

x
+
n
α

-

∫

T

d

f

(
y
)

d
y
.
Quantile regression for count data: jittering versus regression coefficients modelling in the analysis of credits earned by university students after remote teaching
Authors: Carcaiso Viviana , Grilli Leonardo 
Published: October 2022

AbstractThe extension of quantile regression to count data raises several issues. We compare the traditional approach, based on transforming the count variable using jittering, with a recently proposed approach in which the coefficients of quantile regression are modelled by parametric functions. We exploit both methods to analyse university students’ data to evaluate the effect of emergency remote teaching due to COVID-19 on the number of credits earned by the students. The coefficients modelling approach performs a smoothing that is especially convenient in the tails of the distribution, preventing abrupt changes in the point estimates and increasing precision. Nonetheless, model selection is challenging because of the wide range of options and the limited availability of diagnostic tools. Thus the jittering approach remains fundamental to guide the choice of the parametric functions.
Discovering a cohesive football team through players’ attributed collaboration networks
Authors: Yu Shenbao , Zeng Yifeng , Pan Yinghui , Chen Bilian 
Published: October 2022

AbstractThe process of team composition in multiplayer sports such as football has been a main area of interest within the field of the science of teamwork, which is important for improving competition results and game experience. Recent algorithms for the football team composition problem take into account the skill proficiency of players but not the interactions between players that contribute to winning the championship. To automate the composition of a cohesive team, we consider the internal collaborations among football players. Specifically, we propose a Team Composition based on the Football Players’ Attributed Collaboration Network (TC-FPACN) model, aiming to identify a cohesive football team by maximizing football players’ capabilities and their collaborations via three network metrics, namely, network ability, network density and network heterogeneity&homogeneity. Solving the optimization problem is NP-hard; we develop an approximation method based on greedy algorithms and then improve the method through pruning strategies given a budget limit. We conduct experiments on two popular football simulation platforms. The experimental results show that our proposed approach can form effective teams that dominate others in the majority of simulated competitions.
Physicochemical aspects of the tumour microenvironment as drivers of vasculogenic mimicry
Authors: Andreucci Elena , Peppicelli Silvia , Ruzzolini Jessica , Bianchini Francesca , Calorini Lido 
Published: October 2022

AbstractTumour vascularisation is vital for cancer sustainment representing not only the main source of nutrients and oxygen supply but also an escape route for single or clustered cancer cells that, once detached from the primary mass, enter the blood circulation and disseminate to distant organs. Among the mechanisms identified to contribute to tumour vascularisation, vasculogenic mimicry (VM) is gaining increasing interest in the scientific community representing an intriguing target for cancer treatment. VM indeed associates with highly aggressive tumour phenotypes and strongly impairs patient outcomes. Differently from vessels of healthy tissues, tumour vasculature is extremely heterogeneous and tortuous, impeding efficient chemotherapy delivery, and at the meantime hyperpermeable and thus extremely accessible to metastasising cancer cells. Moreover, tumour vessel disorganisation creates a self-reinforcing vicious circle fuelling cancer malignancy and progression. Because of the inefficient oxygen delivery and metabolic waste removal from tumour vessels, many cells within the tumour mass indeed experience hypoxia and acidosis, now considered hallmarks of cancer. Being strong inducers of vascularisation, therapy resistance, inflammation and metastasis, hypoxia and acidosis create a permissive microenvironment for cancer progression and dissemination. Along with these considerations, we decided to focus our attention on the relationship between hypoxia/acidosis and VM. Indeed, besides tumour angiogenesis, VM is strongly influenced by both hypoxia and acidosis, which could potentiate each other and fuel this vicious circle. Thus, targeting hypoxia and acidosis may represent a potential target to treat VM to impair tumour perfusion and cancer cell sustainment.
Cellulose nanocrystal-based enhancement of ultrasound microbubbles for increased tolerance of mechanical index values
Authors: Wang Yiwei , Li Na , Duan Shaobo , Zhang Ye , Wang Yuzhou , Zhang Beibei , Ren Shanshan , Zhang Lianzhong 
Published: October 2022

AbstractEnhancements in the echo intensity and mechanical index (MI) tolerance of ideal ultrasound contrast agents (UCAs) are urgently needed to realize precise clinical ultrasound (US). Solid cellulose nanocrystals (CNCs) have the advantages of imparting strong sound wave propagation and echo intensity when irradiated by US. This study aimed to fabricate improved UCAs via CNC-modified SonoVue ultrasound microbubbles (MBs), characterize the resulting SonoVue@CNC MBs, and evaluate the performance of the SonoVue@CNC MBs in US imaging in vitro and in vivo. SonoVue@CNC MBs were successfully prepared by incorporating CNCs into SonoVue MBs via self-assembly. The SonoVue@CNC MBs were spherical in shape with mean particle sizes of (5.50 ± 1.60) μm. The CNCs were mainly distributed on the polymeric shells of the SonoVue@CNC MBs. When the MI was 0.4, the echo intensity of the SonoVue@CNC MBs was 1.5-fold greater than that of the SonoVue MBs in vitro. The CNC concentration regulated the quality of SonoVue@CNC-promoted contrast-enhanced ultrasound (CEUS) images. Enhanced US images of both the livers and kidneys of Sprague–Dawley (SD) rats showed that the CNC-loaded UCA led to a higher echo intensity than SonoVue. In CCK-8 assays using MCF-10A cells, both SonoVue@CNC MBs and CNCs exhibited weak toxicities against MCF-10A cells. Ultimately, the spherical SonoVue@CNC MBs with a uniform particle size displayed an enhanced safety profile and improved the imaging quality of US in vivo and in vitro. Next, drugs and targeting moieties will be loaded onto the SonoVue@CNC MBs via the CNCs to develop UCA-based selective ultrasonic theranostic methods.
Graphical abstract
As shown in the graphical abstract, the white bubble in the left-middle position symbolized SonoVue microbubble (MB), the green rod-like particle signified CNC nanorod. The big white bubble decorated with green rod-like nanorod next to the mouse was SonoVue@CNC MB which was successfully prepared by incorporating CNCs into SonoVue MB via self-assembly. The purple square frame on the upper left displayed CNC, SonoVue MB, SonoVue@CNC MB and their relative diagrammatic drawings. Picture (I) displayed the transmission electron microscopy results for CNCs (a) and SonoVue@CNC MBs (b, c and d) of morphological study. Picture (II) displayed the in vitro ultrasound (US) imaging of SonoVue (a) MB and SonoVue@CNC (b, c and d) MBs with different CNCs concentrations. Picture (III and IV) displayed the in vivo US imaging of SonoVue (a) and SonoVue@CNC (b, c and d) MBs with different CNCs concentrations for SD mouse liver and kidney, respectively.
A large scale analysis of mHealth app user reviews
Authors: Haggag Omar , Grundy John , Abdelrazek Mohamed , Haggag Sherif 
Published: October 2022

AbstractThe global mHealth app market is rapidly expanding, especially since the COVID-19 pandemic. However, many of these mHealth apps have serious issues, as reported in their user reviews. Better understanding their key user concerns would help app developers improve their apps’ quality and uptake. While app reviews have been used to study user feedback in many prior studies, many are limited in scope, size and/or analysis. In this paper, we introduce a very large-scale study and analysis of mHealth app reviews. We extracted and translated over 5 million user reviews for 278 mHealth apps. These reviews were then classified into 14 different aspects/categories of issues reported. Several mHealth app subcategories were examined to reveal differences in significant areas of user concerns, and to investigate the impact of different aspects of mhealth apps on their ratings. Based on our findings, women’s health apps had the highest satisfaction ratings. Fitness activity tracking apps received the lowest and most unfavourable ratings from users. Over half of users who reported troubles leading them to uninstall mHealth apps gave a 1-star rating. Half of users gave the account and logging aspect only one star due to faults and issues encountered while registering or logging in. Over a third of users who expressed privacy concerns gave the app a 1-star rating. However, only 6% of users gave apps a one-star rating due to UI/UX concerns. 20% of users reported issues with handling of user requests and internationalisation concerns. We validated our findings by manually analysing a sample of 1,000 user reviews from each investigated aspect/category. We developed a list of recommendations for mHealth apps developers based on our user review analysis.
Can Algorithms be Embodied? A Phenomenological Perspective on the Relationship Between Algorithimic Thinking and the Life-World
Authors: Buongiorno Federica 
Published: October 2022

AbstractThis article investigates the possibility to question the difference between artificial and human intelligence by assuming that the latter can incorporate artificial, external components just as artificial intelligence can simulate human responses, and by exploring human embodiment in its technically and digitally augmented dimension. The idea that digital processes do not merely imply a detachment from the body, a dematerialization or disembodiment, is supported by many researchers, starting already from those who—back in the 1980s—reacted to cyberpunk narratives and their tendency to posit a new mind–body dualism. Yet, here I would like to frame this thesis not within the post-human context but in a phenomenological perspective, and in doing so I will employ specific conceptual tools. I will particularly (1) rely on Katherine Hayles’ distinction between incorporating and inscribing practices; (2) refer to Maturana and Varela’s notion of structural coupling; (3) analyze algorithmic thinking and its temporal structure.
An evidence-based study mapping the decline in freshwater ponds in the Severn Vale catchment in the UK between 1900 and 2019
Authors: Smith Lucy P. , Clarke Lucy E. , Weldon Laura , Robson Hannah J. 
Published: October 2022

AbstractFreshwater ponds have long been an overlooked biodiversity store and changing types of land use and the land management practices has led to a steady decline in pond numbers. Establishing the regional extent of pond loss is the first step in identifying key areas for conservation action. This study calculated pond loss in the Severn Vale catchment UK since 1900. Identification of pond location and surrounding land use on historic and contemporary maps enabled a comparison of total number, density and distance between present day and historic ponds. 57.7% of ponds present in 1900 were lost and pond density declined from 7.3 to 4.5 ponds km−2 between 1900 and 2019. This resulted in a 24.6 m increase in the average distance between contemporary ponds. Land use was an important factor in determining pond loss. Although in 2019 the highest density of ponds are in rural areas, 62.3% of ponds lost were from agricultural settings (arable or pasture). Our results highlight the significant pond loss experienced in the Severn Vale since 1900 and provide a valuable baseline for pondscape restoration. The methods described are widely applicable to other regions either with a history of ponds or an environment that could sustain them.
Changes in refraction after cataract phacoemulsification surgery
Authors: Lee Natalie Si-Yi , Ong Keith 
Published: October 2022

Abstract
Purpose
After cataract phacoemulsification surgery, spherical equivalent refraction (SER) may be affected by factors including corneal curvature, effective lens position and axial length. While refractive outcomes have been assessed in the immediate post-operative period, longer-term changes in refraction have not been reported. The purpose of this study was to investigate the timeline changes in refraction after cataract surgery over a period of 3 years.

Methods
This was a retrospective observational study that included 344 eyes of 204 patients who underwent cataract emulsification surgery between 1 January and 31 December 2018 at two private hospitals. Keratometry, anterior chamber depth (ACD), central corneal thickness (CCT) and axial length were measured at baseline and post-operatively at 1 month, 1 year, 2 years and 3 years. Changes in SER and ocular parameters were assessed at each post-operative timepoint.

Results
Between 1 month and 3 years post-operatively, an overall myopic shift (0.32 ± 0.21 D, p < 0.001) occurred in 33.6% of eyes and a hypermetropic shift in 45.2% of eyes (0.35 ± 0.22 D, p < 0.001). In 21.2% of eyes, there was no reported change in SER between 1 month and 3 years. Significant changes in ACD (p = 0.04) and CCT (p < 0.001) occurred during the first year after surgery.

Conclusion
The 3-year timeline changes in SER after cataract surgery were evaluated. As hypermetropic shift was the most common refractive change observed, it may be beneficial to aim for a more myopic post-operative refraction target. Patients should be advised of the potential for refractive changes after surgery.
Measurements of Spontaneous Communication Initiations in Children with Autism in Preschool through Third Grade Classrooms
Authors: Birkeneder Sandy Luong , Sparapani Nicole 
Published: October 2022

AbstractWe utilized classroom video observations to examine the frequency and function of spontaneous communication in 112 preschool–3rd grade children with autism within 57 classrooms. Children initiated 7.53 instances (SD = 9.42) of spontaneous communication on average within a 12-minute sample, a rate of 0.69 initiations per minute. Autism features, receptive and expressive language, and adaptive functioning were associated with communication rate. A 4-factor model of spontaneous communication functions exhibited the best relative and absolute fit to the data. Findings highlight, and begin to explain, variability in spontaneous communication children used in classrooms, link individual developmental characteristics to communicative initiations, and provide evidence for conceptualizing and measuring spontaneous communication in learners with autism across classroom activities. Implications and future directions are discussed.
Improving analysis of the vaginal microbiota of women undergoing assisted reproduction using nanopore sequencing
Authors: Lüth Theresa , Graspeuntner Simon , Neumann Kay , Kirchhoff Laura , Masuch Antonia , Schaake Susen , Lupatsii Mariia , Tse Ronnie , Griesinger Georg , Trinh Joanne , Rupp Jan 
Published: October 2022

Abstract
Purpose
Subclinical alterations of the vaginal microbiome have been described to be associated with female infertility and may serve as predictors for failure of in vitro fertilization treatment. While large prospective studies to delineate the role of microbial composition are warranted, integrating microbiome information into clinical management depends on economical and practical feasibility, specifically on a short duration from sampling to final results. The currently most used method for microbiota analysis is either metagenomics sequencing or amplicon-based microbiota analysis using second-generation methods such as sequencing-by-synthesis approaches (Illumina), which is both expensive and time-consuming. Thus, additional approaches are warranted to accelerate the usability of the microbiome as a marker in clinical praxis.

Methods
Herein, we used a set of ten selected vaginal swabs from women undergoing assisted reproduction, comparing and performing critical optimization of nanopore-based microbiota analysis with the results from MiSeq-based data as a quality reference.

Results
The analyzed samples carried varying community compositions, as shown by amplicon-based analysis of the V3V4 region of the bacterial 16S rRNA gene by MiSeq sequencing. Using a stepwise procedure to optimize adaptation, we show that a close approximation of the microbial composition can be achieved within a reduced time frame and at a minimum of costs using nanopore sequencing.

Conclusions
Our work highlights the potential of a nanopore-based methodical setup to support the feasibility of interventional studies and contribute to the development of microbiome-based clinical decision-making in assisted reproduction.
Machine learning in industrial control system (ICS) security: current landscape, opportunities and challenges
Authors: Koay Abigail M. Y. , Ko Ryan K. L , Hettema Hinne , Radke Kenneth 
Published: October 2022

AbstractThe advent of Industry 4.0 has led to a rapid increase in cyber attacks on industrial systems and processes, particularly on Industrial Control Systems (ICS). These systems are increasingly becoming prime targets for cyber criminals and nation-states looking to extort large ransoms or cause disruptions due to their ability to cause devastating impact whenever they cease working or malfunction. Although myriads of cyber attack detection systems have been proposed and developed, these detection systems still face many challenges that are typically not found in traditional detection systems. Motivated by the need to better understand these challenges to improve current approaches, this paper aims to (1) understand the current vulnerability landscape in ICS, (2) survey current advancements of Machine Learning (ML) based methods with respect to the usage of ML base classifiers (3) provide insights to benefits and limitations of recent advancement with respect to two performance vectors; detection accuracy and attack variety. Based on our findings, we present key open challenges which will represent exciting research opportunities for the research community.
Room temperature ferromagnetism and dielectric enhancement in nanocomposites ZnO doped with iron
Authors: Elsheikh Nora Y. , Battisha Inas K. , Abo Arais Ahmed , Shams M. S. 
Published: October 2022

AbstractPure and iron with different concentrations (0.2, 1, 5, 10, 15, 20, 25, 30, 35 and 40 Mol. %) doped zinc oxide, symbolic as Zn: (0.2, 1, 5, 10, 15, 20, 25, 30, 35 and 40 Fe Mol. %) were synthesized using the self-modified sol–gel technique in powder form. Structural and morphological properties of the samples were studied comparatively by (XRD), (XPS), (FESEM), and (HRTEM), which revealed that the used samples adapted the hexagonal wurtzite structure. Some structural parameters such as strain, crystalline size, and dislocation density, were calculated to have accurate investigation giving rise to the nanostructure phase. The Laser-based Raman micro-spectroscopy presents the homogenous distribution of the iron oxide. The sensing performance of the samples toward the effect of increasing the temperature (from 25 to 150 °C) on the dielectric high-frequency range between 1 MHz up and 1 GHz was investigated with the help of a network impedance analyser (KEYSIGHT-E4991B). The mentioned increase in temperature record ε′ increases values while, it decreases by increasing the frequency, indicating a Debye-type dielectric dispersion. Compared to pure zinc oxide, an enhancement in both (σac) and the impedance real part Z′ was observed in the nanocomposite Z0.2F sample at higher dielectric temperature up to 130 °C. In contrast to pure ZnO, the area of the hysteresis loop against iron concentration for the doped samples increases with an increase in iron concentration. This behavior enhances ferromagnetism in Fe-doped ZnO nanostructure material.