bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing machine learning to predict unplanned cesarean delivery
Authors: Meyer Raanan , Weisz Boaz , Eilenberg Roni , Tsadok Meytal Avgil , Uziel Moshe , Sivan Eyal , Mazaki‐Tovi Shali , Tsur Abraham 
Published: September 2022

AbstractObjectiveTo develop a comprehensive machine learning (ML) model predicting unplanned cesarean delivery (uCD) among singleton pregnancies based on features available at admission to labor.MethodsA retrospective cohort study from a tertiary medical center. Women with singleton vertex pregnancy of 34 weeks or more admitted for vaginal delivery between March 2011 and May 2019 were included. The cohort was divided into training (80%) and validation (20%) data sets. A separate cohort between June 2019 and April 2021 served as a test data set. Features selection was performed using a Random Forest ML algorithm.ResultsThe study population included 73 667 women, of which 4125 (6.33%) underwent uCD. The final model consisted of 13 features, based on prediction importance. The XGBoost model performed best with areas under the curve for the training, validation, and test data sets of 0.874, 0.839, and 0.840, respectively. The model showed a 65% positive predictive value for uCD among women in the 100th centile group, and a 99% or more negative predictive value in the less than 50th centile group. Positive and negative predictive values remained high among subgroups with high pretest probability of uCD.ConclusionAn ML model for the prediction of uCD provides clinically useful risk stratification that remains accurate across gestational weeks 34–42 and among clinical risk groups. The model may be clinically useful for physicians and women admitted for labor.SynopsisA machine learning model predicts unplanned cesarean delivery and can inform women's individualized decision making.
Automatic cervical cancer segmentation in multimodal magnetic resonance imaging using an EfficientNet encoder in UNet++ architecture
Authors: Jin Shan , Xu Hongming , Dong Yue , Hao Xinyu , Qin Fengying , Xu Qi , Zhu Yong , Cong Fengyu 
Published: September 2022

AbstractAutomatic cervical cancer segmentation in multimodal magnetic resonance imaging (MRI) is essential because tumor location and delineation can support patients' diagnosis and treatment planning. To meet this clinical demand, we present an encoder–decoder deep learning architecture which employs an EfficientNet encoder in the UNet++ architecture (E‐UNet++). EfficientNet helps in effectively encoding multiscale image features. The nested decoders with skip connections aggregate multiscale features from low‐level to high‐level, which helps in detecting fine‐grained details. A cohort of 228 cervical cancer patients with multimodal MRI sequences, including T2‐weighted imaging, diffusion‐weighted imaging, apparent diffusion coefficient imaging, contrast enhancement T1‐weighted imaging, and dynamic contrast‐enhanced imaging (DCE), has been explored. Evaluations are performed by considering either single or multimodal MRI with standard segmentation quantitative metrics: dice similarity coefficient (DSC), intersection over union (IOU), and 95% Hausdorff distance (HD). Our results show that the E‐UNet++ model can achieve DSC values of 0.681–0.786, IOU values of 0.558–0.678, and 95% HD values of 3.779–7.411 pixels in different single sequences. Meanwhile, it provides DSC values of 0.644 and 0.687 on three DCE subsequences and all MRI sequences together. Our designed model is superior to other comparative models, which shows the potential to be used as an artificial intelligence tool for cervical cancer segmentation in multimodal MRI.
Conformational energies of microsolvated Na+ clusters with protic and aprotic solvents from GFNn‐xTB methods
Authors: Otlyotov Arseniy A. , Minenkov Yury 
Published: September 2022

AbstractPerformance of contemporary tight‐binding semiempirical GFNn‐xTB methods for the conformational energies of singly charged sodium clusters Na+(S)n (n = 4–8) with 3 protic and 8 aprotic solvents is examined against the reference RI‐MP2/CBS method. The median Pearson correlation coefficients of ρ = 0.84 (GFN2‐xTB) and ρ = 0.82 (GFN1‐xTB) do not give the clear preference to any tested approach. GFN1‐xTB method demonstrates more stable performance than its GFN2‐xTB successor with the average mean absolute errors (MAEs)/mean signed errors (MSEs) of 1.2/0.2 and 2.3/1.6 kcal mol−1, respectively. Conformational energies produced by the computationally efficient DFT functional PBE and double‐ζ basis set complemented with –D3(BJ) dispersion correction are suitable for the preliminary sampling (median ρ = 0.93), but should be used with a caution for the calculations of the average ensemble properties (MAE/MSE = 1.7/1.1 kcal mol−1). Higher‐ranking PBE0‐D3(BJ) and ωB97M‐V with triple‐ζ basis sets yield significantly lower MAEs/MSEs of 0.55/0.20 and 0.51/0.23 kcal mol−1, respectively.
Dental hygiene educators’ knowledge and implementation of objective structured clinical examination in United States dental hygiene programs
Authors: Aboalsaud Khulood M. , Nieto Valerie K. , Eagle Iwonka T. , Rulli Danielle 
Published: September 2022

AbstractPurposeIn 2021, the American Dental Association (ADA) announced the intention to develop a standardized dental hygiene licensure objective structured clinical examination (DHLOSCE). The purpose of this study was to measure the United States (US) dental hygiene (DH) educators’ foundational knowledge of OSCE development and delivery in light of the impending development of the DHLOSCE by the ADA's Testing Services.MethodsThe study was determined to be exempt from Institutional Review Board oversight. A 21‐question survey was developed, pilot tested, and electronically disseminated through Qualtrics. The survey recruitment was emailed to the directors of all entry‐level DH education programs in the US (n = 328), asking them to participate in the survey and to forward it to the clinical faculty in their institutions. Descriptive and inferential statistics were utilized to analyze the data.ResultsThere were 143 study participants, for a completion rate of 45%. Over two‐thirds of respondents (64%) were unaware of the plans to develop the DHLOSCE, while 13% reported utilizing OSCEs to meet accreditation standards. Only 3% reported receiving a formal education in OSCE development compared to 29% who learned through a colleague or peer. Nearly half reported a lack of faculty experience as a barrier to OSCE implementation. Over three‐quarters, 76% reported a lack of OCSE development committees within their program and only 14% had experience developing an OSCE station.ConclusionThe study results suggest an urgent need for the development of OSCE training resources specific to DH education, as programs across the US prepare for the impending DHLOSCE.
Development of entrustable professional activities for post‐doctorate pediatric dentistry education
Authors: Cully Jennifer L. , Schwartz Scott B. , Quinonez Rocio , Martini Abigail , Klein Melissa , Schumacher Daniel J. 
Published: September 2022

AbstractPurposeTo identify the core components of pediatric dentistry defining entrustable professional activities (EPAs) representing the profession.MethodsPotential core components of pediatric dentistry and corresponding domains were identified through review of literature and existing pediatric dentistry standards. A modified Delphi technique was utilized to rate these candidate EPAs to achieve consensus around prioritized EPAs.ResultsEleven participants participated in all three rounds of the Delphi. After three rounds, 16 candidate EPAs reached consensus for pediatric dentistry. Each EPA fell into one of four domains: “assessment and planning,” “provision of care,” “behavior guidance,” and “professional development.” An original candidate EPA focused on non‐pharmacological behavior guidance was deemed too broad by the Delphi. This EPA was subsequently developed into three separate components on nitrous oxide analgesia, moderate sedation, and general anesthesia.ConclusionsPrioritized EPAs will help define the essential activities of the profession and provide a framework for creating assessments to ensure that graduating pediatric residents are ready for unsupervised practice.
Effect of COVID‐19 inpatients with cognitive decline on discharge after the quarantine period: A retrospective cohort study
Authors: Yoshida Shuhei , Miyamori Daisuke , Ikeda Kotaro , Ohge Hiroki , Ito Masanori 
Published: September 2022

AbstractBackgroundA new SARS‐CoV‐2 variant, Omicron, was reported on November 14, 2021, and it altered the COVID‐19 epidemic with a different peak timing by region in Japan. Residents in the Hiroshima prefecture, especially the vulnerable elderly, were threatened by this wave in advance of many other prefectures. We evaluated the effect of cognitive decline on discharge extension after the quarantine period.MethodsParticipants of this retrospective cohort study were patients who were admitted to the care unit for COVID‐19 treatment at Hiroshima University Hospital between January 1, 2022, and March 1, 2022 (60 days). Our primary outcome was the extended length of stay (LOS) in the hospital after the quarantine period (10 days after onset). A negative binomial regression analysis was performed to assess the extended LOS of patients with cognitive decline, adjusting for age classification, gender, and severity of COVID‐19.ResultsThe total number of participants was 74. Per the level of cognitive function, there were 56 independent participants, 5 mild declines, and 13 severe declines. For the negative binomial regression analysis, the exponentiated coefficient of mild cognitive decline was 3.05 (95% confidential interval [CI]: 1.43–6.49) and that of severe cognitive decline was 1.95 (95% CI: 1.09–3.53).ConclusionsMild cognitive decline and severe cognitive decline elevated the risk of extended LOS after COVID‐19 patients finished the quarantine period.
A brief history of Romanian psychology
Authors: David Daniel , Ștefan Simona , Nechita Diana , Dobrean Anca 
Published: September 2022

AbstractThe evolution of Romanian psychology followed several stages, similarly to other countries in Eastern Europe, yet with its own particularities. The first psychology institutes were introduced by former students of Wilhelm Wundt, and the field saw a rapid development, with distinguished scholars making relevant scientific contributions. However, after the communist regime was enforced, psychology stagnated somewhat due to ideological, financial, and political reasons, and, in 1977, it was even removed from academia. After 1989, psychology revived in academia and research, and as a profession as well. This article summarizes the evolution of Romanian psychology through these stages, focusing on its postcommunist revival.
A Novel Grading System for Supraglottic Stenosis Based on Morphology and Functional Status
Authors: Aziz Steven , O'Dell Karla , Johns Michael , Schindler Josh , Merati Al , Alanazi Abdullah , Watts Stephanie , Garber David , Nelson Rebecca , Bensoussan Yael 
Published: September 2022

ObjectiveCurrently, no classification system exists to grade the severity of supraglottic stenosis. The aim of this investigation was to (1) develop a novel grading system for supraglottic stenosis that can both enhance communication between providers and relay information about patient functional status and (2) determine the reliability of the grading system.MethodsA retrospective analysis of patients with supraglottic stenosis at three institutions from 2010–2021 was conducted. After demographic data were collected, two focus group meetings of five laryngologists were held to develop a grading system based on functional status and morphology of stenosis seen on laryngoscopy. Three laryngologists then used the grading system to rate 20 case examples of supraglottic stenosis. Quadratic‐weighted kappa coefficients were calculated to assess inter‐rater and intra‐rater reliabilities of the novel grading system.ResultsTwenty‐eight patients were included. Epiglottic and arytenoid fixation were morphological features associated with worse functional outcomes such as requiring a G‐tube or a tracheostomy, respectively. Inter‐rater reliability was substantial to almost perfect (Kw = 0.79–0.81) and intra‐rater reliability was almost perfect for all raters (0.88–1.0) when using the novel grading system.ConclusionA grading system for supraglottic stenosis has been proposed with strong inter‐rater and intra‐rater reliabilities. The proposed system has the advantage of being descriptive of both patient functionality and morphology of the stenosis.Level of Evidence3—According to the Oxford Center for Evidence‐Based Medicine 2011 level of evidence guidelines, this non‐randomized retrospective cohort study is classified as level 3 evidence Laryngoscope, 133:1442–1447, 2023
Assessing the Downstream Contamination of Chemically Recycled Ethylene Feed Streams on the Kinetic Behavior of Ziegler‐Natta Catalysts and Microstructural Properties of HDPE and LLDPE
Authors: Pernusch Daniel Christian , Paulik Christian , Mastalir Matthias , Hofer Wolfgang 
Published: September 2022

AbstractThe sustainability of consumer materials, such as plastics, belongs to the most important aspect of eco‐efficiency analyses. Besides mechanical recycling, chemical recycling represents an interesting waste management pathway. In theory, this technique does not rely on single‐grade feedstock to maintain product quality. However, cross‐contamination of feedstocks potentially leads to above‐specification impurities in obtained pyrolysis oils. This study investigates the potential downstream poisoning of a fourth‐generation Ziegler‐Natta catalyst, using selected model poisons at high (worst‐case) concentrations. With experimental and computational analysis, economic feasibility factors such as catalyst activity and microstructural properties are evaluated during the synthesis of high‐density polyethylene (HDPE) and linear low‐density polyethylene (LLDPE). Noticeable effects on the catalyst activity can be observed when the poison interacts with the co‐catalyst, whereas a lower impact is observed for interactions with the activated catalyst‐co‐catalyst complex. Molecular weight distribution (MWD) and comonomer composition distribution (CCD) modeling highlighted marginal to no polymer property changes caused by contaminants. Combined with the applicability of pyrolysis post‐treatments, these observations show that chemical recycling can be a promising technique for post‐consumer plastic waste treatment.
Effect of wood flour and nano‐SiO2 on stimulus response, mechanical, and thermal behavior of 3D printed polylactic acid composites
Authors: Kumar Shiv Ranjan 
Published: September 2022

AbstractThe present study focuses on development and characterization of nano‐SiO2 reinforced wood flour reinforced polylactic acid (PLA) composite. The detail characterization involves the physical characterization such as stimulus response behavior, mechanical characterization such as hardness, tensile strength, flexural strength, impact strength, and so forth, and thermal characterization such as thermal stability and thermal conductivity. The finding of results indicates that the shape memory recovery rate and recovery ratio are increased with the increase in temperature. On adding 2 wt% of nano‐SiO2, micro‐hardness, flexural strength, impact strength are increased by 35%, 25.4%, 32.6% respectively. Whereas, on adding 5 wt% of wood flour, micro‐hardness, flexural strength are increased by 17%, 4.4%, 15% respectively. On the other hand, tensile strength is decreased with the addition of wood flour and nano‐SiO2. In addition, increase in wood flour increases the shape recovery rate whereas increase in nano‐SiO2 decreases the shape recovery rate. In thermal analysis, increase in wood flour and nano‐SiO2 content improves the thermal degradation temperature. On the other hand, addition of wood flour and nano‐SiO2 decreases the thermal conductivity of PLA composite.
Subtypes of Chinese Shidu parents' (parents who have lost their only child) depressive symptoms and their relationships with resilience and coping styles
Authors: Zhao Xian , Wang Anni , Chen Jianshi , Zhang Jingping , Li Zhihua 
Published: September 2022

AbstractWe aimed to examine the subtype classification characteristics of depressive symptoms in Shidu parents (SDPs, parents who have lost their only child) and their associations with resilience and coping styles. The sample comprised 182 SDPs (Mean age = 59.93 ± 7.41 years, 61.5% females). Latent profile analysis and logistic regression analysis were used to analyze the data. Three subgroups of depressive symptoms in SDPs were identified: the depression and pessimism group (38.4%), the low depression symptoms group (30.8%), and the well‐adapted group (30.8%). The low depression symptoms group had a lower education level and higher family monthly income than the depression and pessimism group. The low depression symptoms group and the well‐adapted group scored significantly higher in resilience, and lower in negative coping style than the depression and pessimism group. The results highlighted that target intervention is needed for SDPs with high education levels, low family monthly income, high negative coping style, and low resilience in the depression and pessimism group.
Sequential Measurements, Topological Quantum Field Theories, and Topological Quantum Neural Networks
Authors: Fields Chris , Glazebrook James F. , Marcianò Antonino 
Published: September 2022

AbstractWe introduce novel methods for implementing generic quantum information within a scale‐free architecture. For a given observable system, we show how observational outcomes are taken to be finite bit strings induced by measurement operators derived from a holographic screen bounding the system. In this framework, measurements of identified systems with respect to defined reference frames are represented by semantically‐regulated information flows through distributed systems of finite sets of binary‐valued Barwise‐Seligman classifiers. Specifically, we construct a functor from the category of cone‐cocone diagrams (CCCDs) over finite sets of classifiers, to the category of finite cobordisms of Hilbert spaces. We show that finite CCCDs provide a generic representation of finite quantum reference frames (QRFs). Hence the constructed functor shows how sequential finite measurements can induce TQFTs. The only requirement is that each measurement in a sequence, by itself, satisfies Bayesian coherence, hence that the probabilities it assigns satisfy the Kolmogorov axioms. We extend the analysis too develop topological quantum neural networks (TQNNs), which enable machine learning with functorial evolution of quantum neural 2‐complexes (TQN2Cs) governed by TQFTs amplitudes, and resort to the Atiyah‐Singer theorems in order to classify topological data processed by TQN2Cs. We then comment about the quiver representation of CCCDs and generalized spin‐networks, a basis of the Hilbert spaces of both TQNNs and TQFTs. We finally review potential implementations of this framework in solid state physics and suggest applications to quantum simulation and biological information processing.
Recent Progress of Advanced Conductive Metal–Organic Frameworks: Precise Synthesis, Electrochemical Energy Storage Applications, and Future Challenges
Authors: Xu Guiying , Zhu Chengyao , Gao Guo 
Published: September 2022

AbstractMetal–organic frameworks (MOFs) with diverse composition, tunable structure, and unique physicochemical properties have emerged as promising materials in various fields. The tunable pore structure, abundant active sites, and ultrahigh specific surface area can facilitate mass transport and provide outstanding capacity, making MOFs an ideal active material for electrochemical energy storage and conversion. However, the poor electrical conductivity of pristine MOFs severely limits their applications in electrochemistry. Developing conductive MOFs has proved to be an effective solution to this problem. This review focuses on the design and synthesis of conductive MOF composites with judiciously chosen conducting materials, pristine MOFs, and assembly methods, as well as the preparation of intrinsically conductive MOFs based on building 2D π‐conjugated structures, introducing mixed‐valence metal ions/redox‐active ligands, designing π–π stacked pathways, and constructing infinite metal–sulfur chains (–M–S–)∞. Furthermore, recent progress and challenges of conductive MOFs for energy storage and conversion (supercapacitors, Li‐ion batteries, Li–S batteries, and electrochemical water splitting) are summarized.
Intermediate Valence Ion‐Mediated Electrodeposition Process
Authors: Hu Teng , Wang Yanling , Zhao Liyan , Yang Shikuan 
Published: September 2022

AbstractThe assembly of biomolecules and ions (e.g., biomineralization process) generates many intricate structures in nature. However, human beings’ control over the assembly processes of ions is in its infant stage compared with nature. Here, it is reported that the intermediate valence metal ions in the electrolyte can influence the growth speed of certain crystal facets and in turn adjust the shape of the electrodeposits created by anodic electrodeposition. This is because the intermediate valence metal ions (e.g., Pb2+, Mn2+, etc.) can be oxidized by the electrochemically oxidized high valence ions (e.g., Ag2+ and Ag3+). Therefore, the concentration of the electrochemically oxidized high valence ions can be controlled by the intermediate valence ions, affecting the growth kinetics of the electrodeposits. Taking the anodic electrodeposition of Ag7O8NO3 as an example, the role of intermediate valence ions in tailoring the shape of the Ag7O8NO3 electrodeposits is demonstrated. Moreover, the growth location of the second‐order structure can be controlled by the intermediate valence metal ions. Additionally, the designed complex microarchitectures starting from certain crystal facets to form hollow nanoframes can be selectively etched. The control capability over the electrochemical assembly process of metal ions is significantly strengthened by introducing intermediate valence ions into the electrolyte.
Sumanene Monolayer of Pure Carbon: A Two‐Dimensional Kagome‐Analogy Lattice with Desirable Band Gap, Ultrahigh Carrier Mobility, and Strong Exciton Binding Energy
Authors: Shi Xiaoran , Gao Weiwei , Liu Hongsheng , Fu Zhen‐Guo , Zhang Gang , Zhang Yong‐Wei , Liu Tao , Zhao Jijun , Gao Junfeng 
Published: September 2022

AbstractThe design and synthesis of novel two‐dimensional (2D) materials that possess robust structural stability and unusual physical properties may open up enormous opportunities for device and engineering applications. Herein, a 2D sumanene lattice that can be regarded as a derivative of the conventional Kagome lattice is proposed. The tight‐binding analysis demonstrates sumanene lattice contains two sets of Dirac cones and two sets of flat bands near the Fermi surface, distinctively different from the Kagome lattice. Using first‐principles calculations, two possible routines for the realization of stable 2D sumanene monolayers (named α phase and β phase) are theoretically suggested, and an α‐sumanene monolayer can be experimentally synthesized with chemical vapor deposition using C21H12 as a precursor. Small binding energies on Au(111) surface (e.g., −37.86 eV Å−2 for α phase) signify the possibility of their peel‐off after growing on the noble metal substrate. Importantly, the GW plus Bethe–Salpeter equation calculations demonstrate both monolayers have moderate band gaps (1.94 eV for α) and ultrahigh carrier mobilities (3.4 × 104 cm2 V−1 s−1 for α). In particular, the α‐sumanene monolayer possesses a strong exciton binding energy of 0.73 eV, suggesting potential applications in optics.