bluuebunny/crossref_metadata_2025_split huggingface dataset:
Free-breathing radial magnetic resonance elastography of the liver in children at 3 T: a pilot study
Authors: Kafali Sevgi Gokce , Armstrong Tess , Shih Shu-Fu , Kim Grace J. , Holtrop Joseph L. , Venick Robert S. , Ghahremani Shahnaz , Bolster Bradley D. , Hillenbrand Claudia M. , Calkins Kara L. , Wu Holden H. 
Published: April 2022

Abstract
Background
Magnetic resonance (MR) elastography of the liver measures hepatic stiffness, which correlates with the histopathological staging of liver fibrosis. Conventional Cartesian gradient-echo (GRE) MR elastography requires breath-holding, which is challenging for children. Non-Cartesian radial free-breathing MR elastography is a potential solution to this problem.

Objective
To investigate radial free-breathing MR elastography for measuring hepatic stiffness in children.

Materials and methods
In this prospective pilot study, 14 healthy children and 9 children with liver disease were scanned at 3 T using 2-D Cartesian GRE breath-hold MR elastography (22 s/slice) and 2-D radial GRE free-breathing MR elastography (163 s/slice). Each sequence was acquired twice. Agreement in the stiffness measurements was evaluated using Lin’s concordance correlation coefficient (CCC) and within-subject mean difference. The repeatability was assessed using the within-subject coefficient of variation and intraclass correlation coefficient (ICC).

Results
Fourteen healthy children and seven children with liver disease completed the study. Median (±interquartile range) normalized measurable liver areas were 62.6% (±26.4%) and 44.1% (±39.6%) for scan 1, and 60.3% (±21.8%) and 43.9% (±44.2%) for scan 2, for Cartesian and radial techniques, respectively. Hepatic stiffness from the Cartesian and radial techniques had close agreement with CCC of 0.89 and 0.94, and mean difference of 0.03 kPa and −0.01 kPa, for scans 1 and 2. Cartesian and radial techniques achieved similar repeatability with within-subject coefficient of variation=1.9% and 3.4%, and ICC=0.93 and 0.92, respectively.

Conclusion
In this pilot study, radial free-breathing MR elastography was repeatable and in agreement with Cartesian breath-hold MR elastography in children.
Microscopical Justification of Solid-State Wetting and Dewetting
Authors: Piovano Paolo , Velčić Igor 
Published: April 2022

AbstractThe continuum model related to theWinterbottom problem, i.e., the problem of determining the equilibrium shape of crystalline drops resting on a substrate, is derived in dimension two by means of a rigorous discrete-to-continuum passage by$$\Gamma $$Γ-convergence of atomistic models taking into consideration the atomic interactions of the drop particles both among themselves and with the fixed substrate atoms. As a byproduct of the analysis, effective expressions for the drop surface anisotropy and the drop/substrate adhesion parameter appearing in the continuum model are characterized in terms of the atomistic potentials, which are chosen of Heitmann–Radin sticky-disk type. Furthermore, a threshold condition only depending on such potentials is determined distinguishing the wetting regime, where discrete minimizers are explicitly characterized as configurations contained in an infinitesimally thick layer, i.e., the wetting layer, on the substrate, from the dewetting regime. In the latter regime, also in view of a proven conservation of mass in the limit as the number of atoms tends to infinity, proper scalings of the minimizers of the atomistic models converge (up to extracting a subsequence and performing translations on the substrate surface) to a bounded minimizer of the Winterbottom continuum model satisfying the volume constraint.
Observation-driven generation of texture maps depicting dust accumulation over time
Authors: Santos Rebecca L C , Baranoski Gladimir V G 
Published: April 2022

AbstractThe perception of realism in computer-generated images can be significantly enhanced by subtle visual cues. Among those, one can highlight the presence of dust on synthetic objects, which is often subject to temporal variations in real settings. In this paper, we present a framework for the generation of textures representing the accumulation of this ubiquitous material over time in indoor settings. It employs a physically inspired approach to portray the effects of different levels of accumulated dust roughness on the appearance of substrate surfaces and to modulate these effects according to the different illumination and viewing geometries. The development of its core algorithms was guided by empirical insights and data obtained from observational experiments which are also described. To illustrate its applicability to the rendering of visually plausible depictions of time-dependent changes in dusty scenes, we provide sequences of images obtained considering distinct dust accumulation scenarios.
Unintentional response priming from verbal action–effect instructions
Authors: Damanskyy Yevhen , Martiny-Huenger Torsten , Parks-Stamm Elizabeth J. 
Published: April 2022

AbstractAction–effect learning is based on a theoretical concept that actions are associated with their perceivable consequences through bidirectional associations. Past research has mostly investigated how these bidirectional associations are formed through actual behavior and perception of the consequences. The present research expands this idea by investigating how verbally formulated action–effect instructions contribute to action–effect learning. In two online experiments (Exp. 1, N = 41, student sample; Exp. 2, N = 349, non-student sample), participants memorized a specific action–effect instruction before completing a speeded categorization task. We assessed the consequences of the instructions by presenting the instructed effect as an irrelevant stimulus in the classification task and compared response errors and response times for instruction-compatible and instruction-incompatible responses. Overall, we found evidence that verbal action–effect instructions led to associations between an action and perception (effect) that are automatically activated upon encountering the previously verbally presented effect. In addition, we discuss preliminary evidence suggesting that the order of the action–effect components plays a role; only instructions in a perception–action order showed the expected effect. The present research contributes evidence to the idea that action–effect learning is not exclusively related to actual behavior but also achievable through verbally formulated instructions, thereby providing a flexible learning mechanism that does not rely on specific actual experiences.
Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique
Authors: Weng Chi-Hung , Huang Yu-Jui , Fu Chen-Ju , Yeh Yu-Cheng , Yeh Chao-Yuan , Tsai Tsung-Ting 
Published: April 2022

Abstract
Purpose
Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimation of various spinopelvic parameters. The locations of inflection points (IPs) and apices (APs) in whole-spine lateral radiographs could be mathematically determined by a fully automatic spinal sagittal curvature analysis system.

Methods
We developed a DL model for automatic spinal curvature analysis of whole-spine lateral plain radiographs by using 1800 annotated images of various spinal disease etiologies. The DL model comprised a landmark localizer to detect 25 vertebral landmarks and a numerical algorithm for the generation of an individualized spinal sagittal curvature. The characteristics of the spinal curvature, including the IPs, APs, and curvature angle, could thus be analyzed using mathematical definitions. The localization error of each landmark was calculated from the predictions of 300 test images to evaluate the performance of the landmark localizer. The interrater reliability among a senior orthopedic surgeon, a radiologist, and the DL model was assessed using the intraclass correlation coefficient (ICC).

Results
The accuracy of the landmark localizer was within an acceptable range (median error: 1.7–4.1 mm), and the interrater reliabilities between the proposed DL model and each expert were good to excellent (all ICCs > 0.85) for the measurement of spinal curvature characteristics.

Conclusion
The interrater reliability between the proposed DL model and human experts was good to excellent in predicting the locations of IPs, APs, and curvature angles. Future applications should be explored to validate this system and improve its clinical efficiency.
Electrochemical sensors based on metal nanoparticles with biocatalytic activity
Authors: Białas Katarzyna , Moschou Despina , Marken Frank , Estrela Pedro 
Published: April 2022

AbstractBiosensors have attracted a great deal of attention, as they allow for the translation of the standard laboratory-based methods into small, portable devices. The field of biosensors has been growing, introducing innovations into their design to improve their sensing characteristics and reduce sample volume and user intervention. Enzymes are commonly used for determination purposes providing a high selectivity and sensitivity; however, their poor shelf-life is a limiting factor. Researchers have been studying the possibility of substituting enzymes with other materials with an enzyme-like activity and improved long-term stability and suitability for point-of-care biosensors. Extra attention is paid to metal and metal oxide nanoparticles, which are essential components of numerous enzyme-less catalytic sensors. The bottleneck of utilising metal-containing nanoparticles in sensing devices is achieving high selectivity and sensitivity. This review demonstrates similarities and differences between numerous metal nanoparticle-based sensors described in the literature to pinpoint the crucial factors determining their catalytic performance. Unlike other reviews, sensors are categorised by the type of metal to study their catalytic activity dependency on the environmental conditions. The results are based on studies on nanoparticle properties to narrow the gap between fundamental and applied research. The analysis shows that the catalytic activity of nanozymes is strongly dependent on their intrinsic properties (e.g. composition, size, shape) and external conditions (e.g. pH, type of electrolyte, and its chemical composition). Understanding the mechanisms behind the metal catalytic activity and how it can be improved helps designing a nanozyme-based sensor with the performance matching those of an enzyme-based device.Graphical abstract
The sexual and reproductive health of women with mental illness: a primary care registry study
Authors: Hope Holly , Pierce Matthias , Johnstone Edward D. , Myers Jenny , Abel Kathryn M. 
Published: April 2022

AbstractThe purpose of this study is to characterise the sexual and reproductive health risks associated with mental illness among women. This was a retrospective cohort study of 2,680,149 women aged 14 to 45 years in the Clinical Practice Research Datalink, a UK primary care register, linked to 1,702,211 pregnancies that ended between the 1st January 1990 and 31st December 2017. Mental illness was identified in primary care and categorised into the following: common mental illness (depression/anxiety); addiction (alcohol/drug misuse); serious mental illness (affective/non-affective psychosis); other mental illness (eating/personality disorders). Logistic regression estimated the association between mental illness and subsequent risk of recurrent miscarriage and termination. Cox proportional hazards estimated the association between mental illness and time to gynaecological diseases, sexually transmitted infections, reproductive cancers, cervical screen, contraception and emergency contraception. Models were adjusted for calendar year, year of birth, smoking status and ethnicity, region and index of socioeconomic status. Compared to women without mental illness, exposed women were more likely to experience recurrent miscarriage (adjOR = 1.50, 95%CI 1.41 to 1.60), termination (adjOR = 1.48, 95%CI 1.45 to 1.50), gynaecological diseases (adjHR = 1.39, 95%CI 1.37 to 1.40), sexually transmitted infections (adjHR = 1.47, 95%CI 1.43 to 1.51), reproductive cancers (adjHR = 1.10, 95%CI 1.02 to 1.19), contraception (adjHR = 1.28 95%CI 1.26 to 1.29) and emergency contraception (adjHR = 2.30, 95%CI 2.26 to 2.34), and less likely to attend for cervical screening (adjHR = 0.91, 95%CI 0.90 to 0.92). Currently, the sexual and reproductive health needs of women with mental illness are unmet representing significant health inequalities. Clinicians must create opportunities to engage with women in primary care and mental health services to address this gap.
An embodied conversational agent coach to support societal participation learning by low-literate users
Authors: Schouten Dylan G. M. , Deneka Agnes A. , Theune Mariët , Neerincx Mark A. , Cremers Anita H. M. 
Published: April 2022

AbstractPeople of low literacy could benefit from automated support when learning about societal participation. We design an Embodied Conversational Agent (ECA) ‘coach’ that can provide effective learning support to low-literate learners, develop a prototype virtual learning environment, and evaluate this prototype with low-literate end users. First, we inventory the learning support benefits of ECA coaching. Second, we update existing requirements to better specify functional demands for the coach ECA. Third, we write use cases and develop the prototype. Finally, we evaluate the prototype with low-literate users in a mixed-method within-subjects experiment. Results show that the coach influences the subjective learning experience: Participants report higher positive affect, higher user-system engagement, and increased self-efficacy regarding online banking. These results particularly apply to the domain of challenging information skills exercises. Caveats apply: One of four exercises was significantly more difficult than the other three; and coach support rules were not clearly formalized.
Bayesian active learning for parameter calibration of landslide run-out models
Authors: Zhao Hu , Kowalski Julia 
Published: April 2022

AbstractLandslide run-out modeling is a powerful model-based decision support tool for landslide hazard assessment and mitigation. Most landslide run-out models contain parameters that cannot be directly measured but rely on back-analysis of past landslide events. As field data on past landslide events come with a certain measurement error, the community developed probabilistic calibration techniques. However, probabilistic parameter calibration of landslide run-out models is often hindered by high computational costs resulting from the long run time of a single simulation and the large number of required model runs. To address this computational challenge, this work proposes an efficient probabilistic parameter calibration method by integrating landslide run-out modeling, Bayesian inference, Gaussian process emulation, and active learning. Here, we present an extensive synthetic case study. The results show that our new method can reduce the number of necessary simulation runs from thousands to a few hundreds owing to Gaussian process emulation and active learning. It is therefore expected to advance the current practice of parameter calibration of landslide run-out models.
A density estimation approach for detecting and explaining exceptional values in categorical data
Authors: Angiulli Fabrizio , Fassetti Fabio , Palopoli Luigi , Serrao Cristina 
Published: April 2022

AbstractIn this work we deal with the problem of detecting and explaining anomalous values in categorical datasets. We take the perspective of perceiving an attribute value as anomalous if its frequency is exceptional within the overall distribution of frequencies. As a first main contribution, we provide the notion offrequency occurrence. This measure can be thought of as a form of Kernel Density Estimation applied to the domain of frequency values. As a second contribution, we define anoutliernessmeasure for categorical values that leverages the cumulated frequency distribution of the frequency occurrence distribution. This measure is able to identify two kinds of anomalies, calledlower outliersandupper outliers, corresponding to exceptionally low or high frequent values. Moreover, we provide interpretableexplanationsfor anomalous data values. We point out that providing interpretable explanations for the knowledge mined is a desirable feature of any knowledge discovery technique, though most of the traditional outlier detection methods do not provide explanations. Considering that when dealing with explanations the user could be overwhelmed by a huge amount of redundant information, as a third main contribution, we define a mechanism that allows us to single outoutstanding explanations. The proposed technique isknowledge-centric, since we focus on explanation-property pairs and anomalous objects are a by-product of the mined knowledge. This clearly differentiates the proposed approach from traditional outlier detection approaches which instead areobject-centric. The experiments highlight that the method is scalable and also able to identify anomalies of a different nature from those detected by traditional techniques.
Darwin’s empirical claim and the janiform character of fitness proxies
Authors: Krohs Ulrich 
Published: April 2022

AbstractDarwin’s claim about natural selection is reconstructed as an empirical claim about a causal connection leading from the match of the physiology of an individual and its environment to leaving surviving progeny. Variations in this match, Darwin claims, cause differences in the survival of the progeny. Modern concepts of fitness focus the survival side of this chain. Therefore, the assumption that evolutionary theory wants to explain reproductive success in terms of a modern concept of fitness has given rise to the so-called tautology problem. It is shown that the tautology problem reappears in the treatment of fitness proxies in today’s experimental evolutionary biology when these proxies are considered to indicate fitness only. Taking Darwin’s empirical claim seriously suggests, by contrast, that fitness proxies are first of all measures of the match between organism and environment, which I call the organism’s ‘fittedness’. At the same time, they are indeed related to reproductive success. Thus looking in both directions, at fitness and at fittedness, they are janiform. Acknowledging this situation not only allows for rejection of the tautology objection, but also for integration of Darwin’s argument into current evolutionary biology. It is suggested that this helps reframe and alleviate the dispute between the Modern Synthesis and the Extended Evolutionary Synthesis.
Fluvial levees in compound channels: a review on formation processes and the impact of bedforms and vegetation
Authors: Branß Till , Núñez-González Francisco , Aberle Jochen 
Published: April 2022

AbstractNatural levees are wedge-shaped morphological features developing along the boundaries of mass flows. When they form in fluvial landscapes, they can have multiple implications for river management of trained inland rivers. This paper summarizes the present knowledge in regard to the formation and evolution of so-called fluvial levees of trained inland river sections and provides novel hypotheses in regard to the significance of bedforms and vegetation strips along the floodplain on levee formation, evolution, and characteristics. The hypotheses that (i) bedforms contribute to levee formation by altering the interface hydraulics between the main channel and the floodplain and enhancing entrainment of sediment into suspension and (ii) vegetation stripes along the floodplain additionally affect the interface hydraulics resulting in a changed levee geometry are supported by combining existing knowledge on bedform dynamics and flow-vegetation-sediment interaction with results reported in recent flume studies.
A genome-wide assessment of the genetic diversity, evolution and relationships with allied species of the clonally propagated crop Vanilla planifolia Jacks. ex Andrews
Authors: Favre Félicien , Jourda Cyril , Grisoni Michel , Piet Quentin , Rivallan Ronan , Dijoux Jean-Bernard , Hascoat Jérémy , Lepers-Andrzejewski Sandra , Besse Pascale , Charron Carine 
Published: April 2022

AbstractThe Vanilla genus is a complex taxonomic group characterized by a vegetative reproduction mode combined with intra- and inter-specific hybridizations, and polyploidy events. These factors strongly impact the diversification of the genus and complicate the delimitation of taxa. Among the hundred Vanilla species, Vanilla planifolia Jacks. ex Andrews and Vanilla × tahitensis J. W. Moore are the main cultivated aromatic species. We applied Genotyping-by-Sequencing to explore the genetic diversity of these two cultivated vanilla species, seven closely related species and nineteen interspecific hybrids. The inter- and intra-specific relationships of 133 vanilla accessions were examined based on 2004 filtered SNPs. Our results showed a strong genetic structuring between the nine species studied, with wild species showing much lower heterozygosity levels than cultivated ones. Moreover, using Bayesian clustering analyses, the kinship of several hybrids could be verified. We evidenced in particular that Vanilla sotoarenasii and Vanilla odorata C.Presl may be the parental species of V. x tahitensis. The analysis of 1129 SNPs for 84 V. planifolia accessions showed a clear genetic demarcation between the vegetatively propagated traditional vanilla cultivars compared to the accessions derived from sexual reproduction, and a higher genetic diversity and lower heterozygosity of the latter (Ho = 0.206) compared to the former (Ho = 0.362). Our data are consistent with a single-step domestication for V. planifolia in accordance with the recent history of its cultivation. It also opens avenues to breed new V. planifolia varieties adapted to biotic and abiotic constraints and to reduce mutational load induced by clonal propagation.
Silymarin constrains diacetyl-prompted oxidative stress and neuroinflammation in rats: involvements of Dyn/GDNF and MAPK signaling pathway
Authors: Tabaa Manar Mohammed El , Aboalazm Hamdi M. , Shaalan Mohamed , Khedr Naglaa Fathy 
Published: April 2022

AbstractNeuroinflammation, a major component of many CNS disorders, has been suggested to be associated with diacetyl (DA) exposure. DA is commonly used as a food flavoring additive and condiment. Lately, silymarin (Sily) has shown protective and therapeutic effects on neuronal inflammation. The study aimed to explore the role of Sily in protecting and/or treating DA-induced neuroinflammation. Neuroinflammation was induced in rats by administering DA (25 mg/kg) orally. Results revealed that Sily (50 mg/kg) obviously maintained cognitive and behavioral functions, alleviated brain antioxidant status, and inhibited microglial activation. Sily enhanced IL-10, GDNF and Dyn levels, reduced IFN-γ, TNFα, and IL-1β levels, and down-regulated the MAPK pathway. Immunohistochemical investigation of EGFR and GFAP declared that Sily could conserve neurons from inflammatory damage. However, with continuing DA exposure during Sily treatment, oxidative stress and neuroinflammation were less mitigated. These findings point to a novel mechanism involving the Dyn/GDNF and MAPK pathway through which Sily might prevent and treat DA-induced neuroinflammation.