bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes
Authors: Meneses Juan Pablo , Arrieta Cristobal , della Maggiora Gabriel , Besa Cecilia , Urbina Jesús , Arrese Marco , Gana Juan Cristóbal , Galgani Jose E. , Tejos Cristian , Uribe Sergio 
Published: April 2023

Abstract
Objective
To accurately estimate liver PDFF from chemical shift-encoded (CSE) MRI using a deep learning (DL)-based Multi-Decoder Water-Fat separation Network (MDWF-Net), that operates over complex-valued CSE-MR images with only 3 echoes.

Methods

The proposed MDWF-Net and a U-Net model were independently trained using the first 3 echoes of MRI data from 134 subjects, acquired with conventional 6-echoes abdomen protocol at 1.5 T. Resulting models were then evaluated using unseen CSE-MR images obtained from 14 subjects that were acquired with a 3-echoes CSE-MR pulse sequence with a shorter duration compared to the standard protocol. Resulting PDFF maps were qualitatively assessed by two radiologists, and quantitatively assessed at two corresponding liver ROIs, using Bland Altman and regression analysis for mean values, and ANOVA testing for standard deviation (STD) (significance level: .05). A 6-echo graph cut was considered ground truth.

Results
Assessment of radiologists demonstrated that, unlike U-Net, MDWF-Net had a similar quality to the ground truth, despite it considered half of the information. Regarding PDFF mean values at ROIs, MDWF-Net showed a better agreement with ground truth (regression slope = 0.94, R2 = 0.97) than U-Net (regression slope = 0.86, R2 = 0.93). Moreover, ANOVA post hoc analysis of STDs showed a statistical difference between graph cuts and U-Net (p < .05), unlike MDWF-Net (p = .53).

Conclusion
MDWF-Net showed a liver PDFF accuracy comparable to the reference graph cut method, using only 3 echoes and thus allowing a reduction in the acquisition times.

Clinical relevance statement
We have prospectively validated that the use of a multi-decoder convolutional neural network to estimate liver proton density fat fraction allows a significant reduction in MR scan time by reducing the number of echoes required by 50%.

Key Points
• Novel water-fat separation neural network allows for liver PDFF estimation by using multi-echo MR images with a reduced number of echoes.
• Prospective single-center validation demonstrated that echo reduction leads to a significant shortening of the scan time, compared to standard 6-echo acquisition.
• Qualitative and quantitative performance of the proposed method showed no significant differences in PDFF estimation with respect to the reference technique.
Thermoresponsive and co-nonsolvency behavior of poly(N-vinyl isobutyramide) and poly(N-isopropyl methacrylamide) as poly(N-isopropyl acrylamide) analogs in aqueous media
Authors: Henschel Cristiane , Schanzenbach Dirk , Laschewsky André , Ko Chia-Hsin , Papadakis Christine M. , Müller-Buschbaum Peter 
Published: April 2023

Abstract
Sets of the nonionic polymers poly(N-vinyl isobutyramide) (pNVIBAm) and poly(N-isopropyl methacrylamide) (pNIPMAm) are synthesized by radical polymerization covering the molar mass range from about 20,000 to 150,000 kg mol−1, and their thermoresponsive and solvent-responsive behaviors in aqueous solution are studied. Both polymers feature a lower critical solution temperature (LCST) apparently of the rare so-called type II, as characteristic for their well-studied analogue poly(N-isopropyl acrylamide) (pNIPAm). Moreover, in analogy to pNIPAm, both polymers exhibit co-nonsolvency behavior in mixtures of water with several co-solvents, including short-chain alcohols as well as a range of polar aprotic solvents. While the cloud points of the aqueous solutions are a few degrees higher than those for pNIPAm and increase in the order pNIPAm < pNVIBAm < pNIPMAm, the co-nonsolvency behavior becomes less pronounced in the order pNIPAm > pNVIBAm > pNIPMAm. Exceptionally, pNIPMAm does not show co-nonsolvency in mixtures of water and N,N-dimethylformamide.
Graphical Abstract
Fluorescence-based super-resolution-microscopy strategies for chromatin studies
Authors: Burgers Thomas C. Q. , Vlijm Rifka 
Published: April 2023

AbstractSuper-resolution microscopy (SRM) is a prime tool to study chromatin organisation at near biomolecular resolution in the native cellular environment. With fluorescent labels DNA, chromatin-associated proteins and specific epigenetic states can be identified with high molecular specificity. The aim of this review is to introduce the field of diffraction-unlimited SRM to enable an informed selection of the most suitable SRM method for a specific chromatin-related research question. We will explain both diffraction-unlimited approaches (coordinate-targeted and stochastic-localisation-based) and list their characteristic spatio-temporal resolutions, live-cell compatibility, image-processing, and ability for multi-colour imaging. As the increase in resolution, compared to, e.g. confocal microscopy, leads to a central role of the sample quality, important considerations for sample preparation and concrete examples of labelling strategies applicable to chromatin research are discussed. To illustrate how SRM-based methods can significantly improve our understanding of chromatin functioning, and to serve as an inspiring starting point for future work, we conclude with examples of recent applications of SRM in chromatin research.
Atrial cardiomyopathy and incident ischemic stroke risk: a systematic review and meta-analysis
Authors: Guo Jiahuan , Wang Dandan , Jia Jiaokun , Zhang Jia , Peng Fei , Lu Jingjing , Zhao Xingquan , Liu Yanfang 
Published: April 2023

Abstract
Background and purpose
Growing evidence suggests that atrial cardiomyopathy may play an essential role in thrombosis and ischemic stroke. The aim of this systematic review and meta-analysis was to quantify the values of cardiomyopathy markers for predicting ischemic stroke risk.

Methods
PubMed, Embase, and the Cochrane Library were searched for longitudinal cohort studies evaluating the association between cardiomyopathy markers and incident ischemic stroke risk.

Results
We included 25 cohort studies examining electrocardiographic, structural, functional, and serum biomarkers of atrial cardiomyopathy involving 262,504 individuals. P-terminal force in the precordial lead V1 (PTFV1) was found to be an independent predictor of ischemic stroke as both a categorical variable (HR 1.29, CI 1.06–1.57) and a continuous variable (HR 1.14, CI 1.00–1.30). Increased maximum P-wave area (HR 1.14, CI 1.06–1.21) and mean P-wave area (HR 1.12, CI 1.04–1.21) were also associated with an increased risk of ischemic stroke. Left atrial (LA) diameter was independently associated with ischemic stroke as both a categorical variable (HR 1.39, CI 1.06–1.82) and a continuous variable (HR 1.20, CI 1.06–1.35). LA reservoir strain independently predicted the risk of incident ischemic stroke (HR 0.88, CI 0.84–0.93). N-terminal pro-brain natriuretic peptide (NT-proBNP) was also associated with incident ischemic stroke risk, both as a categorical variable (HR 2.37, CI 1.61–3.50) and continuous variable (HR 1.42, CI 1.19–1.70).

Conclusion
Atrial cardiomyopathy markers, including electrocardiographic markers, serum markers, LA structural and functional markers, can be used to stratify the risk of incident ischemic stroke.
General bilinear forms in the Jacobi symbol over hyperbolic regions
Authors: Wilson Cameron 
Published: April 2023

AbstractWe study averages involving the Jacobi quadratic symbol $$(\frac{n}{m})$$

(

n
m

)

in regions where the product mn is bounded by a large parameter. We show that these averages exhibit cancellation whenever the summation is restricted to square-free integers bounded away from the axes.
Evaluation of an artificial intelligence–based algorithm for automated localization of craniofacial landmarks
Authors: Blum Friederike Maria Sophie , Möhlhenrich Stephan Christian , Raith Stefan , Pankert Tobias , Peters Florian , Wolf Michael , Hölzle Frank , Modabber Ali 
Published: April 2023

Abstract
Objectives
Due to advancing digitalisation, it is of interest to develop standardised and reproducible fully automated analysis methods of cranial structures in order to reduce the workload in diagnosis and treatment planning and to generate objectifiable data. The aim of this study was to train and evaluate an algorithm based on deep learning methods for fully automated detection of craniofacial landmarks in cone-beam computed tomography (CBCT) in terms of accuracy, speed, and reproducibility.

Materials and methods
A total of 931 CBCTs were used to train the algorithm. To test the algorithm, 35 landmarks were located manually by three experts and automatically by the algorithm in 114 CBCTs. The time and distance between the measured values and the ground truth previously determined by an orthodontist were analyzed. Intraindividual variations in manual localization of landmarks were determined using 50 CBCTs analyzed twice.

Results
The results showed no statistically significant difference between the two measurement methods. Overall, with a mean error of 2.73 mm, the AI was 2.12% better and 95% faster than the experts. In the area of bilateral cranial structures, the AI was able to achieve better results than the experts on average.

Conclusion
The achieved accuracy of automatic landmark detection was in a clinically acceptable range, is comparable in precision to manual landmark determination, and requires less time.

Clinical relevance
Further enlargement of the database and continued development and optimization of the algorithm may lead to ubiquitous fully automated localization and analysis of CBCT datasets in future routine clinical practice.
Synergies and trade-offs in drought resilience within a multi-level UK food supply chain
Authors: Vicario Dolores Rey , Holman Ian , Sutcliffe Chloe , Hess Tim 
Published: April 2023

AbstractWeather extremes are the biggest challenge for supply chains worldwide, with food supply chains particularly exposed due to agriculture’s sensitivity to weather conditions. Whilst attention has been paid to farm-level impacts from, and adaptation to, weather extremes, there remains a need to better understand how different actors along the supply chain suffer, react and adapt to these natural hazards and how their resilience-building strategies affect other actors’ and the whole system’s resilience. Taking the UK potato supply chain as a case study, this paper analyses the synergies and trade-offs in drought resilience in a multi-level food supply chain. Data from an online survey (87) and interviews with key informants (27) representing potato supply-chain actors (growers, packers, processors, retailers) were used to analyse drought risk perceptions, impacts and coping strategies, long-term resilience measures and further actions to build system resilience. Results suggest that the potato supply chain has increased its resilience to weather extremes due to retailers and packers having a wider geographical spread of supply, an increasing reliance on forward contracts and favouring growers with water security. However, a conceptual framework of resilience-building strategies adopted by supply chain actors shows that these measures are largely designed to reduce their own risk without considering implications for other parts of the chain and the system as a whole. A more integrated approach to promote drought resilience in complex food supply chains that enables improved vertical collaboration and trust between actors is therefore needed.
Which is the Digital Competence of Each Member of Educational Community to Use the Computer? Which Predictors Have a Greater Influence?
Authors: Guillén-Gámez Francisco D. , Colomo-Magaña Ernesto , Cívico-Ariza Andrea , Linde-Valenzuela Teresa 
Published: April 2023

AbstractSince the COVID-19 pandemic, the use of digital resources and virtual platforms is even more essential to continue the educational process, either in person or online, affecting all the members involved in the teaching–learning process of the students. Therefore, this study is aimed: (1) to know and compare the digital competence of the agents that are the main integrators of the educational community (parents, teachers, students) about the use of the computers, according to gender and educational stage (Pre-school, Primary and Secondary Education stages); and (2) to identify significant predictors that affect the acquisition of this competence. An ex-post-facto design was used with a sample of 786 participants from Andalusia (Spain). Research methods such as contrasts of means and multiple linear regression analysis were used. The results showed high average levels of basic digital competences for all the agents involved. A gender gap was found between mothers and fathers of students, with higher scores for the latter group. In addition, the use of videogames, the parents' academic background and the use of digital tablets or Google+ are the most significant predictors that affect the acquisition of this competence.
NRF2 and STAT3: friends or foes in carcinogenesis?
Authors: Arena Andrea , Romeo Maria Anele , Benedetti Rossella , Gilardini Montani Maria Saveria , Santarelli Roberta , Gonnella Roberta , D’Orazi Gabriella , Cirone Mara 
Published: April 2023

AbstractNRF2 is a transcription factor that plays a pivotal role in carcinogenesis, also through the interaction with several pro-survival pathways. NRF2 controls the transcription of detoxification enzymes and a variety of other molecules impinging in several key biological processes. This perspective will focus on the complex interplay of NRF2 with STAT3, another transcription factor often aberrantly activated in cancer and driving tumorigenesis as well as immune suppression. Both NRF2 and STAT3 can be regulated by ER stress/UPR activation and their cross-talk influences and is influenced by autophagy and cytokines, contributing to shape the microenvironment, and both control the execution of DDR, also by regulating the expression of HSPs. Given the importance of these transcription factors, more investigations aimed at better elucidating the outcome of their networking could help to discover new and more efficacious strategies to fight cancer.
Potential applicability of Jatropha curcas leaves in bioethanol production and their composites with polymer in wastewater treatment
Authors: Madian Hekmat R. , Abdelhamid Ahmed E. , Hassan H. M. , Labena Ahmed 
Published: April 2023

AbstractAmong the biggest issues facing the world now are fuel shortages and water contamination. Therefore, the goal of the current study was directed to produce bioethanol from Jatropha curcas leaves and use the residual wastes in the form of composite sheets for crystal violet (CV) removal. The leaves were collected from Jatropha curcas, irrigated by various irrigation sources; sewage-water (A), sewage-water-sludge (B), and tap water (C). The acid hydrolysis (4% H2SO4) of these leaves demonstrated that the hydrolysis of the Jatropha curcas leaves (A) produced higher values of total reducing sugars (≈ 21 g/l) than other leaves (B &C). Moreover, the bioethanol concentrations obtained from the fermentation of this hydrolysate (A) at the bioreactor scale using Candida tropicalis and Saccharomyces cerevisiae (≈10 and 7 ml/l, respectively) were relatively increased compared to the flask level (≈7 and 5 ml/l, respectively). Afterwards, the unhydrolyzed wastes were dried, grinded, and embedded in polyvinyl chloride (PVC) polymer forming sheets. The sheets were characterized using FT-IR, SEM, swelling, and porosity. The highest CV removal percent of 95.39%, after optimization, was achieved at 100 ppm crystal violet concentration using 2.5 g/l from PVC-A composite sheet after 180-min contact time.
Protective effect and mechanism insight of purified Antarctic krill phospholipids against mice ulcerative colitis combined with bioinformatics
Authors: Huang Rong , Yao Jiaxu , Zhou Li , Li Xiang , Zhu Jinrui , Hu Yueqi , Liu Jikai 
Published: April 2023

AbstractAntarctic krill oil is functional oil and has a complex phospholipids composition that poses difficulties in elucidating its effect mechanism on ulcerative colitis (UC). The mechanism of UC action was studied by bioinformatics, and the therapeutic effect of Antarctic krill phospholipids (APL) on dextran sulfate sodium (DSS)-induced colitis mice was verified. GO functional enrichment analysis uncovered an enrichment of these genes in the regulation of cell–cell adhesion, membrane region, signaling receptor activator activity, and cytokine activity. Meanwhile, the KEGG results revealed the genes were enriched in the TNF signaling pathway, pathogenic Escherichia coli infection, inflammatory bowel disease and tight junction. Animal experiments showed that APL treatment alleviated the UC symptoms and reduced inflammatory damage. Meanwhile, the expressions of the tight junction (TJ) proteins, ZO-1 and occludin, were restored, and the levels of IL-6 and TNF-α were reduced. Moreover, Firmicutes/Bacteroidetes ratio in the intestinal microbiota was regulated, and the contents of short-chain fatty acids metabolites were raised. These findings would provide an insight for the beneficial effects of APL and dietary therapy strategies for UC.
Tribological properties of PTFE-based fabric composites at cryogenic temperature
Authors: Xu Mingkun , Wang Zidan , Guo Lihe , Tao Liming , Ma Tianbao , Wang Tingmei , Wang Qihua 
Published: April 2023

AbstractFabric composites are widely employed in self-lubricating bearing liners as solid lubrication materials. Although the tribological behaviors of fabric composites have been extensively studied, the cryogenic tribological properties and mechanisms have been scarcely reported and are largely unclear to instruct material design for aerospace and other high-tech applications. Herein, the tribological properties of polytetrafluoroethylene (PTFE)-based hybrid-fabric composites were investigated at cryogenic and ambient temperatures in the form of pin-on-disk friction under heavy loads. The results suggest that the friction coefficients of the hybrid-fabric composites obviously increase with a decrease in wear when the temperature drops from 25 to −150 °C. Moreover, thermoplastic polyetherimide (PEI), as an adhesive for fabric composites, has better cryogenic lubrication performance than thermosetting phenol formaldehyde (PF) resin, which can be attributed to the flexible chemical structure of PEI. The excellent lubrication performance of hybrid-fabric composites is attributed to the transfer film formed by PTFE fibers on the surface of fabrics.
COCO: an annotated Twitter dataset of COVID-19 conspiracy theories
Authors: Langguth Johannes , Schroeder Daniel Thilo , Filkuková Petra , Brenner Stefan , Phillips Jesper , Pogorelov Konstantin 
Published: April 2023

AbstractThe COVID-19 pandemic has been accompanied by a surge of misinformation on social media which covered a wide range of different topics and contained many competing narratives, including conspiracy theories. To study such conspiracy theories, we created a dataset of 3495 tweets with manual labeling of the stance of each tweet w.r.t. 12 different conspiracy topics. The dataset thus contains almost 42,000 labels, each of which determined by majority among three expert annotators. The dataset was selected from COVID-19 related Twitter data spanning from January 2020 to June 2021 using a list of 54 keywords. The dataset can be used to train machine learning based classifiers for both stance and topic detection, either individually or simultaneously. BERT was used successfully for the combined task. The dataset can also be used to further study the prevalence of different conspiracy narratives. To this end we qualitatively analyze the tweets, discussing the structure of conspiracy narratives that are frequently found in the dataset. Furthermore, we illustrate the interconnection between the conspiracy categories as well as the keywords.
Thermochemical recycling of waste disposable facemasks in a non-electrically powered system
Authors: Iwuozor Kingsley O. , Emenike Ebuka Chizitere , Stephen Agbana Abiodun , Kevin Otoikhian Shegun , Adeleke Joy , Adeniyi Adewale George 
Published: April 2023

AbstractThe COVID-19 pandemic encouraged the use of plastic-based personal protective equipment (PPE), which aided greatly in its management. However, the increased production and usage of these PPEs put a strain on the environment, especially in developing and underdeveloped countries. This has led various researchers to study low-cost and effective technologies for the recycling of these materials. One such material is disposable facemasks. However, previous studies have only been able to engage electrically powered reactors for their thermochemical conversion, which is a challenge as these reactors cannot be used in regions with an insufficient supply of electricity. In this study, the authors utilized a biomass-powered reactor for the conversion of waste disposable facemasks and almond leaves into hybrid biochar. The reactor, which is relatively cheap, simple to use, environmentally friendly, and modified for biochar production, is biomass-powered. The co-carbonization process, which lasted 100 min, produced a 46% biochar yield, which is higher than previously obtained biochar yields by other researchers. The biochar thus obtained was characterized to determine its properties. FTIR analysis showed that the biochar contained functional groups such as alkenes, alkynes, hydroxyls, amines, and carbonyls. The EDX analysis revealed that the biochar was primarily made of carbon, tellurium, oxygen, and calcium in the ratios of 57%, 19%, 9%, and 7%, respectively. The inclusion of the facemask decreased the surface area and porosity of the biochar material, as evidenced by its surface area and pore characteristics.
A 3‐D Shape Reconstruction Strategy for Small Solar System Bodies With Single Flyby Spaceborne Radar
Authors: Hu Chaoran , Wei Mingchuan , Huang Jiahe , Zhao Yuhao , Cao Xibin 
Published: April 2023

AbstractThis article presents a novel 3‐D shape reconstruction strategy for small solar system bodies using spaceborne radar which is applied in flyby trajectories to characterize multiple targets in one mission to save time and cost. In this study, we establish a measurement geometry for rapidly spinning small solar system bodies that combines the motion properties of synthetic aperture radar and circular synthetic aperture radar techniques. We also propose a modified imaging algorithm, which is processed using Cardano's formula and the modified polar format algorithm, to improve the imaging quality. Finally, we present simulated results of point‐scattering and 3D shape models. Our analysis shows that the shape reconstruction errors of the algorithm are less than 1.5 m as indicated by the standard deviation.