bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing
Authors: Zhang Yaping , Liu Mingqian , Hu Shundong , Shen Yao , Lan Jun , Jiang Beibei , de Bock Geertruida H. , Vliegenthart Rozemarijn , Chen Xu , Xie Xueqian 
Published: October 2021

Abstract
Background
Artificial intelligence can assist in interpreting chest X-ray radiography (CXR) data, but large datasets require efficient image annotation. The purpose of this study is to extract CXR labels from diagnostic reports based on natural language processing, train convolutional neural networks (CNNs), and evaluate the classification performance of CNN using CXR data from multiple centers

Methods
We collected the CXR images and corresponding radiology reports of 74,082 subjects as the training dataset. The linguistic entities and relationships from unstructured radiology reports were extracted by the bidirectional encoder representations from transformers (BERT) model, and a knowledge graph was constructed to represent the association between image labels of abnormal signs and the report text of CXR. Then, a 25-label classification system were built to train and test the CNN models with weakly supervised labeling.

Results
In three external test cohorts of 5,996 symptomatic patients, 2,130 screening examinees, and 1,804 community clinic patients, the mean AUC of identifying 25 abnormal signs by CNN reaches 0.866 ± 0.110, 0.891 ± 0.147, and 0.796 ± 0.157, respectively. In symptomatic patients, CNN shows no significant difference with local radiologists in identifying 21 signs (p > 0.05), but is poorer for 4 signs (p < 0.05). In screening examinees, CNN shows no significant difference for 17 signs (p > 0.05), but is poorer at classifying nodules (p = 0.013). In community clinic patients, CNN shows no significant difference for 12 signs (p > 0.05), but performs better for 6 signs (p < 0.001).

Conclusion
We construct and validate an effective CXR interpretation system based on natural language processing.
Accelerating the transition of clinical science to translational medicine
Authors: Holgate Stephen T. 
Published: October 2021

Abstract
The SARS-CoV-2 pandemic has shown the importance of medical research in responding to the urgent prevention and health needs to combat the devastating disease, COVID-19, that this β-coronavirus unleashed. Equally, it has demonstrated the importance of interdisciplinary working to translate scientific discovery into public and patient benefit. As we come to adjust to live with this new virus, it is important to look back and see what lessons we have learnt in the way scientific medical discoveries can be more effectively and rapidly moved into public benefit. Clinical Science has had a long and distinguished history with this Journal bearing the same name and being an important contributor to the rapidly increasing use of human pathobiological data to gain mechanistic understanding of disease mechanisms leading to new diagnostic tests and treatments. The recognition that many complex diseases engage multiple causal pathways that may vary from patient to patient, and at different times across the lifecourse, has led to the emergence of stratified or precision medicine in which the right treatment is given to the right patient at the right time and, in doing so, minimise ‘non-responders’ and off-target side effects. Applications of omics technologies, the digitalisation of biology and the applications of machine learning and artificial intelligence (AI) are accelerating disease insights at pace with translation of discoveries into new diagnostic tests and treatments. The future of clinical science, as it morphs into translational medicine, is now creating unique possibilities where even the most intractable diseases are now open to being conquered.
Accent, Comprehensibility, and Confidence in Second and Third Languages of Adolescents: How Do They Relate to Language Proficiency and Language Interactions?
Authors: Elin Thordardottir  , Hávarðarson Guðlaugur 
Published: October 2021

Purpose:This study examines the degree to which adolescents in Iceland are judged by native Icelandic speakers to have a foreign accent both in Icelandic and in English, two languages that are learned under different conditions, as the community and school language, and through school and incidental exposure.Method:Fifty-eight adolescents, 27 with Icelandic as their first language (L1), 21 as their second language (L2), and 10 as one of two L1s read passages in Icelandic and English. Twelve untrained native speakers of Icelandic rated the degree of foreign accent, comprehensibility, and confidence level and selected from multiple-choice options what they thought was the L1 of the speakers.Results:Significant group differences were found in Icelandic but not in English. L2 speakers had a significantly greater foreign accent than the other groups in Icelandic; however, there was substantial overlap with some L2 speakers judged to be native and some L1 speakers judged as nonnative. All groups had a significantly greater accent in English than in Icelandic. Accent was judged more sternly than comprehensibility and confidence and related differently to vocabulary proficiency.Conclusions:Accent is typically not considered in studies of bilingual attainment in children for purposes of clinical assessment or educational placement but should be given closer attention. The study confirms previous findings that many young L2 learners have a detectable foreign accent. The overlap with L1 speakers also raises questions about the ideal of a native accent. More research is needed on how accent relates to bilingual and multilingual proficiency and on its impacts on comfort level, ease of communication, choice of language, and language exposure.
A fault location method of distribution network based on XGBoost and SVM algorithm
Authors: Liu Keyan , Kang Tianyuan , Ye Xueshun , Bai Muke , Fan Yaqian 
Published: October 2021

AbstractNowadays, the reliable supply of electric power is vital in all aspects of social life. With the development and participation of distributed generations, not only does an accurate fault location lets repair of a fault line as quickly as possible, but also it is of great significance to ensure the safe and stable economic operation of the power system. This study proposes a method to determine the fault location in distribution networks, which is a combination of Extreme Gradient Boosting and Support Vector Machine. The effectiveness of the proposed method is validated on an IEEE34‐bus distribution network under single‐phase‐to‐ground faults, using voltage measurements available at each node in the distribution network. The comparison in accuracy, precision, recall, F1‐score and time‐cost of the method in this study with K‐Nearest Neighbour and Multi‐Layer Perceptron demonstrates the feasibility of applying the proposed method in distribution system fault diagnosis.
The implementation of wideband 90° hybrids on non‐optimal substrates
Authors: du Toit Johan B. , Joubert Johan , Odendaal Johann W. 
Published: October 2021

AbstractA new technique to implement wideband 90° hybrid coupling profiles on non‐optimal substrate configurations is presented. The technique uses an impedance taper over the whole length of the hybrid to remove the restriction of a substrate defined maximum coupling coefficient at crossover, thus resulting in much more flexibility for the implementation of hybrids on integrated printed circuit boards. The choice of board thicknesses and material type no longer needs to be dominated by the hybrid, but can be optimized for other components or priorities. The flexibility provided by the technique is shown in the implementation of a 2–18 GHz hybrid on a large range of substrate thicknesses as well as on a non‐optimal substrate material, for which acceptable measured performance is still obtained.
Information sufficient segmentation and signal‐to‐noise ratio for 3D astigmatism stochastic optical localization nanoscopy
Authors: Sun Mingyan , Sun Yi 
Published: October 2021

AbstractIt is known that 80% power effective data segmentation with Airy and Gaussian point spread functions (PSFs) for 2D imaging achieves sufficient Fisher information and is appropriate to define signal‐to‐noise ratio (SNR) of a data frame. This letter investigates information‐sufficient data segmentation with an astigmatic PSF for 3D imaging. The SNR and the root mean square error (RMSE) of Fisher information for ρ‐power effective segmentation are derived. Numerical evaluations in various conditions of emitter axial locations and noise levels are carried out. It is found that the 80% power effective segmentation with the 3D astigmatic PSF also achieves sufficient Fisher information and is appropriate to define SNR. The results are applicable to data segmentation and SNR computation in experiments and simulations.
New alternative derivations of Cramér–Rao bound for equality‐constrained estimation
Authors: Li Xi , Liu Yi , Yang Le 
Published: October 2021

AbstractThis paper presents new alternative derivations of the well‐known constrained Cramr–Rao bound for estimating parameters that satisfy a set of deterministic and differentiable equality constraints. Specifically, for unbiased parameter estimation, the equality constraints are treated as pseudo‐measurements corrupted by independent zero‐mean Gaussian noise with infinitely small covariance. In this way, the desired constrained Cramr–Rao bound can be established via utilising the property that the Fisher information matrices for independent measurements are additive. This paper also provides a new simple way for deriving the constrained Cramr–Rao bound when the parameter estimate has a specified bias through exploring that the estimation error lies in the null space of the gradient matrix of the constraints and invoking the Cauchy–Schwarz inequality.
Study on the residual flux density measurement method for power transformer cores based on magnetising inductance
Authors: Huo Cailing , Wang Youhua , Liu Chengcheng , Lei Gang 
Published: October 2021

AbstractWhen a power transformer is reconnected to a power grid, if the residual flux in its iron core is large, significant inrush current may be generated and result in closing failure. Therefore, accurate residual flux measurement is necessary to avoid the harmful effects of inrush current. This work proposes a residual flux density measurement method for the power transformer core based on magnetising inductance. Firstly, when positive and negative DC voltages are applied along or opposite to the direction of the initial residual flux density, the measured positive magnetising inductance is smaller than the negative so that the direction of residual flux density can be determined by comparing their values. Secondly, the magnitude of residual flux density can calculated by analysing the empirical formula between residual flux density and positive magnetising inductance using the finite element method. Finally, this work takes the square iron core as the research object, establishes the corresponding empirical formula, and verifies its accuracy through experiments. The experimental results show that the proposed method has higher accuracy compared with the voltage integration method widely used in this field.
A compact triple‐band dipole array antenna for selected sub 1 GHz, 5G and WiFi access point applications
Authors: Yazdani Reza , Aliakbarian Hadi , Sahraei Amir , Vandenbosch Guy A. E. 
Published: October 2021

AbstractThis work aims at realizing an antenna with a stable radiation pattern for base station applications. A novel high‐efficiency shared‐aperture triple‐band dipole array antenna configuration is proposed in sub‐6 GHz microcell base stations in environments where bi‐directional radiation patterns are preferred. The radiators of the antenna are composed of double‐sided square dipole array structures and two novel long‐side monopoles. To verify the principle, the antenna with an overall size of 0.3λ0 × 0.33λ0 × 0.002λ0 (λ0 is the free‐space wavelength at 900 MHz) is fabricated and measured. The measurements confirm impedance bandwidths of 9.5% (840–924 MHz), 21.9% (3–3.74 GHz), and 12.2% (4.9–5.54 GHz), respectively. The second frequency band covers the 5G sub‐6 GHz NR frequency band n78, mainly used in China and some other countries, and the LTE 42/43 bands (3.4–3.6 GHz, 3.6–3.8 GHz). The first and the third bands are also suitable for GSM 900, 5 GHz WiFi and are potential candidates for future 5G developments. The boresight gain is greater than 1, 6, and 10 dBi in these bands, respectively. The measured results also demonstrate that the proposed configuration has stable radiation patterns across the three frequency bands.
Parallel‐plates‐based Dirac Leaky Wave Antennas
Authors: Rezaee Sina , Memarian Mohammad , Ahmadian Mohammad 
Published: October 2021

AbstractIn this work, the authors experimentally show Dirac Leaky Wave Antennas (DLWAs) at upper microwave frequencies. For the first time, DLWAs are implemented using simple Parallel plate waveguide (PPW) technology, while yielding desirable radiation features and continuous beam scanning through broadside, as well as extremely low profile, with significant ease of fabrication, making them well suited for Ku band applications such as satellite communication, radar and emerging fifth‐generation (5G). A planar Dirac photonic crystal in PPW is shown with a closed bandgap and linear dispersion around broadside. In this work, 1D and 2D PPDLWAs are designed that provide scannable fan and pencil beams, respectively, with a symmetric beamwidth. Phase and attenuation constants are controlled with unit cell dimensions to obtain a directive beam and scanning in a wide range of angles. For the 2D design, an appropriate wideband feeding network is designed that excites the antenna appropriately. The presented PPDLWAs operate with a peak gain of about 13 dB for the fan beam and 22 dB for the pencil beam, in the frequency range from 12 to 16 GHz.
A single‐stage bridgeless LLC resonant converter with constant frequency control based LED driver
Authors: Ma Jianguang , Sun Ying , Hu Liang 
Published: October 2021

AbstractIn this article, a single‐stage bridgeless LLC resonant converter with a constant frequency control method is proposed for a high‐brightness light‐emitting diode (LED) driver. LED strings require drivers with high power density and high efficiency. This article presents a novel LED driver circuit topology based on switch integration and the switching controlled capacitor (SCC) technique. By combining the merits of a totem‐pole bridgeless boost PFC unit and a high frequency SCC‐LLC half‐bridge resonant converter, the proposed topology can achieve high efficiency. Due to the SCC‐LLC circuit topology structure, constant frequency control of the LLC resonant converter is achieved by the regulation of the equivalent resonant capacitance. The proposed novel LED driver topology can automatically achieve soft‐switching characteristics and a high power factor. The operating principle of different operation modes and the characteristics of the proposed LED driver are analysed in detail. Finally, to demonstrate the feature of the proposed topology, a 100 W/70 V laboratory prototype is built. The satisfactory experimental results correspond with the theoretical analysis and parameter design.
Enhancing the distribution power system resilience against hurricane events using a bayesian network line outage prediction model
Authors: Omogoye Okeolu Samuel , Folly Komla Agbenyo , Awodele Kehinde Oladayo 
Published: October 2021

AbstractEnhancing the grid resilience against hurricane events proactively requires a pre‐disaster system optimization built on accurate system network line outage prediction. In the past, the statistical system level failure predictive model such as generalized linear model (GLM), generalized additive model (GAM), system tree‐based mining model (classification regression tree (CART), Bayesian additive regression model (BART), and the topology‐based system components’ fragility curve (FC)‐Monte Carlo simulation (MCS) model have been used to estimate the hurricane‐induced damage on the grid system. Although these models are suitable for a long term infrastructural planning, increased prediction approximation error with high computational time limit their applications as a components level predictive model that can be used for a short‐term proactive operational planning. To solve these problems, a dynamic bayesian network (BN) model is proposed. The investigation is performed on a standard IEEE 15‐bus system using hurricane events data. The proposed BN's system line outage prediction accuracy and efficiency are validated using the statistical system grid components’ FC‐MCS‐scenario reduction (SCENRED) predictive model. Therefore, creating a platform to develop a cost‐effective pre‐disaster system optimization for system network resilience enhancement against the predicted approaching hurricane events.
Research on vehicle adaptive cruise control based on BP neural network working condition recognition
Authors: Wang Yongwei , Guo Zhijun , Wu Jingbo , Fu Shenzhen 
Published: October 2021

AbstractTo solve the problems of the vehicle following model mismatch under different driving conditions and poor vehicle following performance, this paper proposes an adaptive cruise control system based on BP neural network to identify different driving conditions. Firstly, eight typical driving cycles are selected as samples, which are redivided into low‐speed mode and medium high‐speed mode. According to the selected characteristic parameters and re‐division of driving mode, a new BP neural network structure is designed. Secondly, the characteristic parameter values are calculated by using the characteristic parameters, and the characteristic parameters are normalized. The working condition recognition model is obtained by training the normalized data values. Finally, according to the classification of working conditions, the fuzzy control upper control algorithm and the MPC upper control algorithm for medium‐high speed conditions are designed respectively. Based on the above control algorithms, the joint simulation is carried out with Car‐Sim and MATLAB/Simulink. The simulation results show that the low‐speed fuzzy logic algorithm and the medium high‐speed MPC algorithm proposed in this paper can make the vehicle have a better following performance and comfort.
Selbstbestimmtes Wohnen mit Unterstützung – Entwicklung und Überprüfung der „Modelltreueskala Selbstbestimmtes Wohnen (MSSW)“ für Menschen mit psychischen Beeinträchtigungen
Authors: Richter Dirk , Adamus Christine , Mötteli Sonja , Myszor Franziska , Wienberg Günther , Steinhart Ingmar 
Published: October 2021

Zusammenfassung
Ziel der Studie In der psychiatrischen Versorgung fehlt bisher eine umfassende Beschreibung der Struktur- und Prozessmerkmale unterstützter Wohnformen im deutschsprachigen Raum. Die Entwicklung und Testung einer Modelltreueskala für selbstbestimmtes Wohnen wird dargestellt.
Methodik Im Rahmen einer länderübergreifenden Kooperation wurde eine Skala entwickelt und in Interviews mit Leitungspersonen in 87 Diensten und Einrichtungen in Deutschland und der Schweiz eingesetzt.
Ergebnisse Die Modelltreueskala umfasst 31 Items in 4 Bereichen. Unterstützungsdienste in der eigenen Wohnung wiesen eine leicht höhere Modelltreue gegenüber besonderen Wohnformen (stationäre Einrichtungen) auf. Dies galt insbesondere für die Bereiche Wohnbedingungen und Inklusionsorientierung. In den Bereichen Mitarbeitende/Team und Unterstützungsbedingungen wurden keine Unterschiede gemessen.
Schlussfolgerung Mit der Modelltreueskala steht erstmalig ein überprüfbarer Kriterienkatalog für das selbstbestimmte Wohnen in der psychiatrischen Versorgung zur Verfügung.
The Impact of Body Mass Index on Postpartum Infectious Morbidities and Wound Complications: A Study of Extremes
Authors: Sheikh Iqra , Fuller Kylie A. , Addae-Konadu Kateena , Dotters-Katz Sarah K. , Varvoutis Megan S. 
Published: October 2021

Objective As body mass index increases, the risk of postpartum infections has been shown to increase. However, most studies lump women with a body mass index (BMI) of above 40 kg/m2 together, making risk assessment for women in higher BMI categories challenging. The objective of this study was to evaluate the impact of extreme obesity on postpartum infectious morbidity and wound complications during the postpartum period.
Study Design The present study is a secondary analysis of women who underwent cesarean delivery and had BMI ≥ 40 kg/m2 in the Maternal-Fetal Medicine Units Cesarean Registry. The primary outcome was a composite of postpartum infectious morbidity including endometritis, wound infection, inpatient wound complication prior to discharge, and readmission due to wound complications. Appropriate statistics used to compare baseline demographics, pregnancy complications, and primary outcomes among women by increasing BMI groups (40–49.9, 50–59.9, 60–69.9, and >70 kg/m2).
Results Rates of postpartum infectious morbidity increased with BMI category (11.7% BMI: 50–59.9 kg/m2; 13.7% BMI: 60–69.9 kg/m2; and 21.9% BMI >70+ kg/m2; p = 0.001). Readmission for wound complications also increased with BMI (3.1% for BMI: 50–59.9 kg/m2; 6.2% for BMI: 60–69.9 kg/m2; and 9.4% for BMI >70+ kg/m2; p = 0.001). After adjusting for confounders, increased BMI of 70+ kg/m2 category remained the most significant predictor of postpartum infectious complications compared with women with BMI of 40 to 49.9 kg/m2 (adjusted odds ratio [aOR] = 6.38; 95% confidence interval [CI]: 1.37–29.7). The adjusted odds of readmission also increased with BMI (aOR = 2.33, 95% CI: 1.35–4.02 for BMI 50–59.9 kg/m2; aOR = 4.91, 95% CI: 2.07–11.7 for BMI of 60–69.9 kg/m2; and aOR = 36.2, 95% CI: 7.45–176 for BMI >70 kg/m2).
Conclusion Women with BMI 50 to 70+ kg/m2 are at an increased risk of postpartum wound infections and complications compared with women with BMI 40 to 49.9 kg/m2. These data provide increased guidance for counseling women with an extremely elevated BMI and highlight the importance of postpartum wound prevention bundles.
Key Points
Estudo radiográfico em pacientes submetidos à artroplastia total de joelho não cimentada: Segmento mínimo de 2 anos
Authors: Mainine Sérgio , Marinho José Antônio , Oliveira Bruna Gabriela Passarini de , Zanon Enrico Montorsi , Pereira Bruno Machado , Souza Rafael Fonseca Rodrigues de 
Published: October 2021

Resumo
Objetivo Avaliar radiograficamente a existência de sinais de soltura precoce das artroplastias totais de joelho não cimentadas Score (Amplitude Surgical SAS, Valence, France), verificadas com um tempo de seguimento que variou de 2 a 5,75 anos (média de 3,75 anos).
Métodos Investigação longitudinal descritiva de caráter observacional, não comparativa, realizada através de estudo radiográfico estático de controle anual, de uma série de casos, em um único centro, todos operados pelo mesmo cirurgião (S.M.). Foram incluídas todas as artroplastias não cimentadas que se enquadraram nos critérios de inclusão e exclusão realizadas no período de março de 2012 a outubro de 2014.
Resultados Dentre as 46 artroplastias de joelho não cimentadas avaliadas em 40 pacientes, não foram verificados sinais radiográficos de soltura precoce.
Conclusão A artroplastia não cimentada promove ótima osteointegração, não havendo soltura precoce, sendo fundamental que a técnica cirúrgica seja perfeitamente respeitada.