bluuebunny/crossref_metadata_2025_split huggingface dataset:
A decision support system for primary headache developed through machine learning
Authors: Liu Fangfang , Bao Guanshui , Yan Mengxia , Lin Guiming 
Published: January 2022

Background
Primary headache is a disorder with a high incidence and low diagnostic accuracy; the incidence of migraine and tension-type headache ranks first among primary headaches. Artificial intelligence (AI) decision support systems have shown great potential in the medical field. Therefore, we attempt to use machine learning to build a clinical decision-making system for primary headaches.

Methods
The demographic data and headache characteristics of 173 patients were collected by questionnaires. Decision tree, random forest, gradient boosting algorithm and support vector machine (SVM) models were used to construct a discriminant model and a confusion matrix was used to calculate the evaluation indicators of the models. Furthermore, we have carried out feature selection through univariate statistical analysis and machine learning.

Results
In the models, the accuracy, F1 score were calculated through the confusion matrix. The logistic regression model has the best discrimination effect, with the accuracy reaching 0.84 and the area under the ROC curve also being the largest at 0.90. Furthermore, we identified the most important factors for distinguishing the two disorders through statistical analysis and machine learning: nausea/vomiting and photophobia/phonophobia. These two factors represent potential independent factors for the identification of migraines and tension-type headaches, with the accuracy reaching 0.74 and the area under the ROC curve being at 0.74.

Conclusions
Applying machine learning to the decision-making system for primary headaches can achieve a high diagnostic accuracy. Among them, the discrimination effect obtained by the integrated algorithm is significantly better than that of a single learner. Second, nausea/vomiting, photophobia/phonophobia may be the most important factors for distinguishing migraine from tension-type headaches.
Rheumatoid Arthritis Synovial Inflammation Quantification Using Computer Vision
Authors: Guan Steven , Mehta Bella , Slater David , Thompson James R. , DiCarlo Edward , Pannellini Tania , Pearce‐Fisher Diyu , Zhang Fan , Raychaudhuri Soumya , Hale Caryn , Jiang Caroline S. , Goodman Susan , Orange Dana E. 
Published: January 2022

ObjectiveWe quantified inflammatory burden in rheumatoid arthritis (RA) synovial tissue by using computer vision to automate the process of counting individual nuclei in hematoxylin and eosin images.MethodsWe adapted and applied computer vision algorithms to quantify nuclei density (count of nuclei per unit area of tissue) on synovial tissue from arthroplasty samples. A pathologist validated algorithm results by labeling nuclei in synovial images that were mislabeled or missed by the algorithm. Nuclei density was compared with other measures of RA inflammation such as semiquantitative histology scores, gene‐expression data, and clinical measures of disease activity.ResultsThe algorithm detected a median of 112,657 (range 8,160‐821,717) nuclei per synovial sample. Based on pathologist‐validated results, the sensitivity and specificity of the algorithm was 97% and 100%, respectively. The mean nuclei density calculated by the algorithm was significantly higher (P < 0.05) in synovium with increased histology scores for lymphocytic inflammation, plasma cells, and lining hyperplasia. Analysis of RNA sequencing identified 915 significantly differentially expressed genes in correlation with nuclei density (false discovery rate is less than 0.05). Mean nuclei density was significantly higher (P < 0.05) in patients with elevated levels of C‐reactive protein, erythrocyte sedimentation rate, rheumatoid factor, and cyclized citrullinated protein antibody.ConclusionNuclei density is a robust measurement of inflammatory burden in RA and correlates with multiple orthogonal measurements of inflammation.
Palladium‐Catalyzed Stereoselective Intramolecular Heck Dearomative Silylation of Indoles
Authors: Wang Gang , Wei Mingzhu , Liu Tianxiang , Jin Weiwei , Zhang Yonghong , Wang Bin , Xia Yu , Liu Chenjiang 
Published: January 2022

AbstractA palladium‐catalyzed stereoselective intramolecular Heck dearomative of indoles with silyl termination has been developed. A type of tetracyclic indoline derivatives containing silicon were prepared, involving N‐(2‐bromobenzoyl)indoles and silylboronates. This protocol not only led to a broad substrate scope in acceptable yields but also could be scaled up to gram quantities as well as further synthetic transformation.magnified image
Topological Quantum Cathode Materials for Fast Charging Li‐Ion Battery Identified by Machine Learning and First Principles Calculation
Authors: Wu Wei , Wang Shuo , Sun Qiang 
Published: January 2022

AbstractFast charging electrode materials require excellent ion conductivity as well as high and stable electrical conductivity. However, the main commercial cathode materials are semiconducting transition metal oxides suffering from low electrical conductivity, so cathode materials with good electrical conductivity are highly desirable. It is well‐known that topological quantum materials (TQMs) can exhibit robust electrical conductivity, thus providing a promising solution to this problem. The key question becomes which TQMs can have high ionic conductivity. Herein, such topological quantum cathode materials for fast charging Li‐ion battery are identified by using machine learning combined with first‐principle calculation, where the supervised regression models are trained for diffusion energy barrier prediction. Among 7385 TQMs, 20 materials are found to have a diffusion energy barrier less than 1.0 eV. Especially, LiMnAs exhibits a reversible capacity of 195.9 mAh g−1, higher than that of commercial cathodes while with comparable diffusion energy barrier. Furthermore, LiMnAs shows high interface stability with selected solid lithium metal oxides electrolytes. This study not only opens a new path to developing novel cathode materials, but also expands the applications of TQMs.
Bubble‐scale observations of polyurethane foam expansion
Authors: Roberts Christine , Mondy Lisa , Soehnel Grant , Brady Casper , Shelden Bion , Soehnel Melissa , Garcia Robert , Ortiz Weston , Rao Rekha 
Published: January 2022

AbstractWe describe experiments designed to inform computational models of the dynamic filling process of chemically blown, polyurethane foams, especially subgrid models to predict bubble size affecting foam properties. Three experimental methods are used to observe the evolution of bubble sizes during blowing. Magnified views of bubbles at a transparent wall of a channel are recorded during the foaming. The bubble sizes in the final frame after the expansion has stopped are compared to scanning electron microscope images of the interior of the cured samples to determine wall effects. In addition, diffusing wave spectroscopy is used to determine the average bubble sizes across the width of a similar channel during foam expansion. We conclude that the bubble size distribution is dependent on the formulation of foam being tested, temperature, the height in the foam bar, the proximity to a wall, and the degree of overpacking.
Association of clonal hematopoiesis mutations with clinical outcomes: A systematic review and meta‐analysis
Authors: Nowakowska Malgorzata K. , Kim Taebeom , Thompson Mikayla T. , Bolton Kelly L. , Deswal Anita , Lin Steven H. , Scheet Paul , Wehner Mackenzie R. , Nead Kevin T. 
Published: January 2022

AbstractClonal hematopoiesis (CH) mutations are common among individuals without known hematologic disease. CH mutations have been associated with numerous adverse clinical outcomes across many different studies. We systematically reviewed the available literature for clinical outcomes associated with CH mutations in patients without hematologic disease. We searched PubMed, EMBASE, and Scopus for eligible studies. Three investigators independently extracted the data, and each study was verified by a second author. Risk of bias was assessed using the Newcastle‐Ottawa Scale. We identified 32 studies with 56 cohorts that examine the association between CH mutations and clinical outcomes. We conducted meta‐analyses comparing outcomes among individuals with and without detectable CH mutations. We conducted meta‐analyses for cardiovascular diseases (nine studies; HR = 1.61, 95% CI = 1.26–2.07, p = .0002), hematologic malignancies (seven studies; HR = 5.59, 95% CI = 3.31–9.45, p < .0001), therapy‐related myeloid neoplasms (four studies; HR = 7.55, 95% CI = 4.3–13.57, p < .001), and death (nine studies; HR = 1.34, 95% CI = 1.2–1.5, p < .0001). The cardiovascular disease analysis was further stratified by variant allele fraction (VAF) and gene, which showed a statistically significant association only with a VAF of ≥ 10% (HR = 1.42, 95% CI = 1.24–1.62, p < .0001), as well as statistically significant associations for each gene examined with the largest magnitude of effect found for CH mutations in JAK2 (HR = 3.5, 95% CI = 1.84–6.68, p < .0001). Analysis of the association of CH mutations with hematologic malignancy demonstrated a numeric stepwise increase in risk with increasing VAF thresholds. This analysis strongly supports the association of CH mutations with a clinically meaningful increased risk of adverse clinical outcomes among individuals without hematologic disease, particularly with increasing VAF thresholds.
Homogeneously Large Polarons in Aromatic Passivators Improves Charge Transport between Perovskite Grains for >24 % Efficiency in Photovoltaics
Authors: Zhao Jia‐Hui , Mu Xijiao , Wang Luyao , Fang Zihan , Zou Xiaoxin , Cao Jing 
Published: January 2022

AbstractAromatic passivators, such as porphyrin, with large π‐backbones have attracted considerable attention to boost the charge carrier in polycrystalline perovskite films, thus enabling the fabrication of efficient and stable perovskite solar cells (PSCs). However, they often self‐assemble into supramolecules that probably influence the charge‐transfer process in the perovskite grain boundary. Here, by doping a monoamine Cu porphyrin into perovskite films, two porphyrin‐based self‐assembled supramolecules were successfully prepared between perovskite grains. Crystal structures and theoretical analyses reveal the presence of a stronger interaction between the amine units and the central Cu ions of neighbouring porphyrins in one of the supramolecules. This has a modified effect on the dipole direction of the porphyrins to be quantized as homogeneously large polarons (HLPs) in a periodic lattice. The porphyrin supramolecules can stabilize perovskite grain boundaries to greatly improve the stability of PSCs, while the HLPs‐featured supramolecule facilitates hole transport across perovskite grains to remarkably increase the cell performance to as high as 24.2 %. This work proves that the modulation of the intermolecular interaction of aromatic passivators to yield HLPs is crucial for the cascaded acceleration of charge transport between perovskite grains.
Transient Plasmonic Imaging of Ion Migration on Single Nanoparticles and Insight for Double Layer Dynamics
Authors: Wang Lu‐Xuan , Zhang Miao , Sun Chao , Yin Li‐Xin , Kang Bin , Xu Jing‐Juan , Chen Hong‐Yuan 
Published: January 2022

AbstractSingle‐nanoparticle electrochemistry offers electrochemical behaviors of individual entities beyond the ensemble system. An electric double layer (EDL) exists on any charged particle–liquid interface because of counter‐ion accumulation, while direct measuring of the interfacial ion migration remains a challenge. Herein, a plasmonic‐based transient microscopic method, with a temporal resolution of 1–2 μs, was demonstrated to directly track the ion migration dynamics on single charged nanoparticles. We found that the dynamics of EDL formation might deviate significantly from the prediction made by using the classical resistance–capacitance (RC) model under nanoscale and transient conditions. Under ultrafast charging, due to the limit migration rate of ions in the solution, the actual time scale of the EDL formation could be up to 5 times slower than the predicted value from the RC model. We then proposed a new theoretical model to describe the transient dynamics of EDL formation. These results may expand our current knowledge about nano‐electrochemistry and transient electrochemistry.
Topochemical Polymerization of a Diacetylene in a Chalcogen‐Bonded (ChB) Assembly
Authors: Dhaka Arun , Jeon Ie‐Rang , Jeannin Olivier , Aubert Emmanuel , Espinosa Enrique , Fourmigué Marc 
Published: January 2022

AbstractThe successful topochemical polymerization of bis(selenocyanatomethyl)butadyine 1 is achieved upon association in a 1 : 1 co‐crystal with 1,2‐bis(2‐pyridyl)ethylene (2‐bpen) through strong and linear (NC)−Se⋅⋅⋅NPy chalcogen bonding (ChB) interactions, allowing for an appropriate parallel alignment of the diacetylene moieties toward the solid‐state reaction. Co‐crystal 1⋅(2‐bpen) undergoes polymerization upon heating at 100 °C. The reaction progress was monitored by IR, DSC and PXRD. An enhancement of the polymer conductivity by 8 orders of magnitude is observed upon iodine doping. Strikingly, the course of polymerization is accompanied with sublimation of the ChB acceptor molecules 2‐bpen, providing the polymer in a pure form with full recovery of the co‐former, at variance with the usual hydrogen‐bonded co‐crystal strategies toward polydiacetylenes.
Adsorption of organic dyes on macroporous melamine sponge incorporating conducting polypyrrole nanotubes
Authors: Stejskal Jaroslav , Pekárek Michal , Trchová Miroslava , Kolská Zdeňka 
Published: January 2022

AbstractThe macropores of melamine sponge were coated with globular polypyrrole or polypyrrole nanotubes. The resulting materials have been tested for the adsorptive removal of organic dyes from aqueous medium. The nanotubes deposited on the sponge were able to remove Reactive Black 5 dye while the adsorption on analogous polypyrrole globules was marginal. For that reason, the macroporous open‐cell melamine sponge with embedded nanotubes was tested for the adsorption of five anionic and five cationic dyes. The anionic dyes were adsorbed efficiently in the contrast to cationic ones. This can be explained by the electrostatic interaction of anionic dyes with polypyrrole polycation. The fast‐starting adsorption occurred within a few minutes and was followed by a slower process extending for days. The nanotubes deposited on the sponge have always been more efficient adsorbents than free polypyrrole nanotubes or melamine sponge alone. Better organization of polymer chains in the polypyrrole nanotubes and especially those deposited on the melamine sponge is proposed to be responsible for this effect. Cationic dyes were adsorbed even by neat melamine sponge while the adsorption by polypyrrole was negligible. In this case, the indifferent role of polypyrrole can be assigned to the electrostatic repulsion of the dye.
Aggregation von Zustandsindikatoren aus Inspektions‐ und Monitoringdaten im Brückenbau
Authors: Herbrand Martin , Lazoglu Alex , Ullerich Christof , Marx Steffen , Zehetmaier Gerhard 
Published: January 2022

AbstractDie Bewertung des Bauwerkszustands von Brückenbauwerken erfolgt in Deutschland anhand der auf Grundlage regelmäßiger Bauwerksprüfungen ermittelten Bauwerksnote. Eine Methodik zur Einbindung von Monitoringdaten in die Bauwerksbewertung existiert dagegen derzeit noch nicht. Dabei kann ein Bauwerksmonitoring zur Unterstützung der klassischen Bauwerksprüfung genutzt werden, um das Auftreten oder die Entwicklung von Bauwerksschäden vorübergehend oder dauerhaft zu überwachen und so die von den Schäden ausgehenden Risiken zu mindern. Des Weiteren können in vielen Fällen rechnerische Standsicherheitsdefizite mittels gezielt eingesetzter Messmaßnahmen kompensiert werden. Herausforderungen hinsichtlich der integralen Zustandsbewertung ergeben sich aus der unterschiedlichen Bewertung von Bauwerksschäden (Benotung) und Standsicherheitsnachweisen (Ausnutzungsgrad). Dieser Beitrag stellt eine Methodik vor, die Monitoringdaten und Bauwerksschäden in einer Echtzeitbewertungskennzahl aggregiert, die auch für Nichtfachleute verständlich ist. Neben dem allgemeinen Bewertungsverfahren, das bekannte Elemente aus dem Bewertungsschema nach SIB‐Bauwerke einschließt, werden zwei konkrete Anwendungsfälle anhand des smartBRIDGE‐Konzepts an der Köhlbrandbrücke in Hamburg gezeigt. Dabei handelt es sich um zwei aktuelle rechnerische Standsicherheitsdefizite, die durch eine messtechnische Überwachung kompensiert werden.
Silicon‐Based Nanorod Anodes by Employing Bacterial Cellulose Derived Carbon Skeleton Towards Lithium‐Ion Batteries
Authors: Wang Jie , Gao Jiafeng , Zhang Jian , Jiang Qiwen , Yin Huanhuan , Wang Ziqi , Zuo Songlin 
Published: January 2022

AbstractHuge volume change and high cost of silicon (Si) during the lithium insertion/extraction processes are still major challenges in practical application of Li‐ion batteries (LIBs). Herein, for the first time, a scalable one‐dimensional (1D) robust Si/C nanorods are developed by using pyrolytic bacterial cellulose (pBC) as 1D carbon skeleton and introducing carbon dioxide (CO2) greenhouse gas into traditional magnesiothermic reduction reaction, to accelerate the commercial utilization of Si/C composite electrodes. pBC arrays are generated via a self‐assembled parallel arrangement process in the SiO2/pBC hybrids. Notably, pBC arrays as a strong structural support and CO2‐derived in‐situ generated amorphous carbon as an ideal encapsulation endow Si/C nanorods with high structure robustness and good electronic conductivity. In particular, Si‐based nanorods anodes with carbon component content of 11 wt % deliver high reversible specific capacity, good Coulombic efficiency and impressive cycling performance. Such excellent electrochemical performance is attributed to unique Si/C nanorod structure and its superior properties, which can provide good accommodation of volume changes, superior electrolyte wetting, and fast electrons and lithium ions transportation pathways during charging and discharging processes.
Using machine learning to predict engineering technology students’ success with computer‐aided design
Authors: Singh Jasmine , Perera Viranga , Magana Alejandra J. , Newell Brittany , Wei‐Kocsis Jin , Seah Ying Ying , Strimel Greg J. , Xie Charles 
Published: January 2022

AbstractComputer‐aided design (CAD) programs are essential to engineering as they allow for better designs through low‐cost iterations. While CAD programs are typically taught to undergraduate students as a job skill, such software can also help students learn engineering concepts. A current limitation of CAD programs (even those that are specifically designed for educational purposes) is that they are not capable of providing automated real‐time help to students. To encourage CAD programs to build in assistance to students, we used data generated from students using a free, open‐source CAD software called Aladdin to demonstrate how student data combined with machine learning techniques can predict how well a particular student will perform in a design task. We challenged students to design a house that consumed zero net energy as part of an introductory engineering technology undergraduate course. Using data from 128 students, along with the scikit‐learn Python machine learning library, we tested our models using both total counts of design actions and sequences of design actions as inputs. We found that our models using early design sequence actions are particularly valuable for prediction. Our logistic regression model achieved a >60% chance of predicting if a student would succeed in designing a zero net energy house. Our results suggest that it would be feasible for Aladdin to provide useful feedback to students when they are approximately halfway through their design. Further improvements to these models could lead to earlier predictions and thus provide students feedback sooner to enhance their learning.
Plasma‐assisted Engineering of MOF Electrocatalyst for Highly Efficient Oxygen Evolution Reaction
Authors: Pan Chengcheng , Dong Yinghao , Chen Xiangbin , Yu Bo , Huang Minghua , Liu Zhicheng 
Published: January 2022

AbstractMetal‐organic frameworks (MOFs) have been extensively investigated as promising oxygen evolution reaction (OER) electrocatalysts due to their highly ordered porous structure and abundant active sites. The reasonable engineering of the MOF materials is the key to highly efficient energy conversion technologies. Here, we present a facile Ar plasma treatment to introduce various defects in MOF nanosheets while maintaining their morphology. The generated coordinatively unsaturated metal sites with electron‐rich structure are conducive to improving intrinsic catalytic activity, and the formed mesopores are beneficial to mass transport during the catalytic process. Compared with the pristine MOF nanosheets grown on nickel foam, the plasma‐etched MOF nanosheets exhibits excellent OER performance with an ultralow overpotential of 213 mV at current density of 50 mA cm−2. This work could deepen our understanding of the structure‐property relationship of the plasma‐treated MOF electrocatalysts, and open up new prospects for the engineering of highly efficient MOF‐based electrocatalysts.
Porous palladium phosphide nanotubes for formic acid electrooxidation
Authors: Wang Tian‐Jiao , Jiang Yu‐Chuan , He Jia‐Wei , Li Fu‐Min , Ding Yu , Chen Pei , Chen Yu 
Published: January 2022

AbstractThe development of an efficient catalyst for formic acid electrocatalytic oxidation reaction (FAEOR) is of great significance to accelerate the commercial application of direct formic acid fuel cells (DFAFC). Herein, palladium phosphide (PdxPy) porous nanotubes (PNTs) with different phosphide content (i.e., Pd3P and Pd5P2) are prepared by combining the self‐template reduction method of dimethylglyoxime‐Pd(II) complex nanorods and succedent phosphating treatment. During the reduction process, the self‐removal of the template and the continual inside–outside Ostwald ripening phenomenon are responsible for the generation of the one‐dimensional hollow and porous architecture. On the basis of the unique synthetic procedure and structural advantages, Pd3P PNTs with optimized phosphide content show outstanding electroactivity and stability for FAEOR. Importantly, the strong electronic effect between Pd and P promotes the direct pathway of FAEOR and inhibits the occurrence of the formic acid decomposition reaction, which effectively enhances the FAEOR electroactivity of Pd3P PNTs. In view of the facial synthesis, excellent electroactivity, high stability, and unordinary selectivity, Pd3P PNTs have the potential to be an efficient anode electrocatalyst for DFAFC.