bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlates of Insulin Selection as a First-Line Pharmacological Treatment for Gestational Diabetes
Authors: Palatnik Anna , Harrison Rachel K. , Thakkar Madhuli Y. , Walker Rebekah J. , Egede Leonard E. 
Published: November 2021

Objective The aim of this study was to investigate prenatal factors associated with insulin prescription as a first-line pharmacotherapy for gestational diabetes mellitus (GDM; compared with oral antidiabetic medication) after failed medical nutrition therapy.
Study Design This is a retrospective cohort study of 437 women with a singleton pregnancy and diagnosis of A2GDM (GDM requiring pharmacotherapy), delivering in a university hospital between 2015 and 2019. Maternal sociodemographic and clinical characteristics, as well as GDM-related factors, including provider type that manages GDM, were compared between women who received insulin versus oral antidiabetic medication (metformin or glyburide) as the first-line pharmacotherapy using univariable and multivariable analyses.
Results In univariable analysis, maternal age, race and ethnicity, insurance, chronic hypertension, gestational age at GDM diagnosis, glucose level after 50-g glucose loading test, and provider type were associated with insulin prescription. In multivariable analysis, after adjusting for sociodemographic and clinical maternal factors, GDM characteristics and provider type, Hispanic ethnicity (0.26, 95% confidence interval [CI]: 0.09–0.73), and lack of insurance (0.34, 95% CI: 0.13–0.89) remained associated with lower odds of insulin prescription, whereas endocrinology management of GDM (compared with obstetrics and gynecology [OBGYN]) (8.07, 95% CI: 3.27–19.90) remained associated with higher odds of insulin prescription.
Conclusion Women of Hispanic ethnicity and women with no insurance were less likely to receive insulin and more likely to receive oral antidiabetic medication for GDM pharmacotherapy, while management by endocrinology was associated with higher odds of insulin prescription.This finding deserves more investigation to understand if differences are due to patient choice or a health disparity in the choice of pharmacologic agent for A2GDM.
Key Points
Design of pulsed power supply for repetitive pulsed high magnetic field for water electrolysis
Authors: Jiang Shan , Hu Heng , Wang Shuang , Li Liang , Peng Tao 
Published: November 2021

A system based on a novel scheme for generating the repetitive pulsed high magnetic field (RPHMF) is developed and applied to enhance the performance of the NdFeB electrocatalyst in alkaline water electrolysis for the first time. In this system, the scheme for generating continuously high-frequency pulses depends on the cooperation of multiple power modules with a new structure. Multiple power modules are connected in parallel to energize the pulsed magnet, and each module is composed of two capacitor banks and a pulse transformer, which is used to realize the conversion of the energy between the two capacitor banks. As the residual energy in one capacitor is transferred to another, the energy required to be replenished for the next pulse reduces substantially. Then, the high repetition rate of the RPHMF can be achieved by discharging the capacitor banks of each module in sequence. The scheme has been validated by the experiment of a 2.4 T/12 Hz prototype with only one power module. Simulation shows that the frequency of the RPHMF can be improved to 12*N Hz with N power modules, and a higher repetition rate of the RPHMF may bring new opportunities to the water electrolysis.
Translating official documents from French to English in Uganda
Authors: Sebuyungo Enoch 
Published: November 2021

AbstractAlthough underexplored in Africa, the translation of official documents presents a revelatory context for examining translation practice and theory. Through a sociolinguistic and pragmatic lens, this study explores how translating official documents by focusing on linguistic equivalences without taking into account national institutional systems can be misleading. The argument is made that sociolinguistic variables and Grice’s pragmatic maxims are essential in enhancing translation effectiveness. A sample of 151 pairs of source and target documents dating from 2011–2017 was purposively selected. This corpus from nineteen Francophone countries covers three broad categories: Education, Legal, and General Administrative Correspondence. Nineteen translators and fourteen end-users were also interviewed regarding the translation effectiveness of corpus examples. Data is analyzed using sociolinguistic and pragmatic criteria. Finally, the analysis is positioned within the broader scholarship on translation studies to demonstrate how this approach expands our knowledge regarding effective translation.
The role of linguistic structure in the perceptions of vernacular speech
Authors: Davydova Julia , Hazen Kirk 
Published: November 2021

AbstractThis study explores the role of linguistic structure in speakers’ perceptions of vernacular English, i.e. speech used in informal interactions. In so doing, it tests the assumptions of the Interface Principle (Labov 1993) and its major claim that semantic and discourse-pragmatic features will elicit a greater degree of social awareness than morphosyntactic variants (Levon and Buchstaller 2015). Relying on data obtained from 372 respondents, we explore the social perceptions of two discourse-pragmatic and two morphosyntactic variables. We show that the morphosyntactic features investigated here are generally available to the sociolinguistic monitor of L1 speakers as well as highly advanced learners of English as a Foreign Language. However, these morphosyntactic features are less salient than the semantic/discourse pragmatic variants, and their social indexation is, for this reason, more pliable. We argue for the weaker version of the Interface Principle and propose that the differences in the recognisability of vernacular features is gradient. We additionally propose that juxtaposing different types of speaker data is instrumental in discerning those differences.
The ideological debate on Naijá and its use in education
Authors: Mazzoli Maria 
Published: November 2021

Abstract
Naijá (also known as Nigerian Pidgin) is an extended pidgin with millions of speakers in Nigeria, and it is also a creole since some communities use it as a first language (Faraclas 2013; Mazzoli 2017). It is a common lingua franca in former English colonies in West Africa and has potential for transnational use. Notwithstanding its importance at multiple levels, Naijá is not mentioned in language-related policies in Nigeria, and its use in education is limited and stigmatized. This is due to aggressive ideologies that identify Naijá as an inferior language, especially with respect to English in Nigeria. In this paper, based on fieldwork data collected in southern Nigeria, I outline positive and negative ideologies related to Naijá, and argue that innovative ideologies have emerged among Naijá native speakers, which constitute a base for elaborating endoglossic policies and introducing Naijá into the classroom.
Data-driven learning, theories of learning and second language acquisition
Authors: O’Keeffe Anne 
Published: November 2021

Abstract
This chapter focuses on the need to address both theories of learning and theories of language acquisition in data-driven learning (DDL) research. While it recognises that there has been so much worthwhile research work on DDL which has shed so much light on the value of DDL, it is still not a mainstream methodology. The chapter argues that by understanding better the variations in pedagogical underpinnings and ontologies, DDL research can better pinpoint what works within specified variables. Additionally, the paper argues strongly for engagement with ongoing research in second language acquisition (SLA), especially from a usage-based perspective because there are so many resonances for DDL in terms of the centrality of the role of frequently experienced syntactic regularities in learning.
Physical determinants, intercorrelations, and relevance of movement speed components in elite junior tennis players
Authors: Vuong Jo‐Lâm , Fett Janina , Ulbricht Alexander , Ferrauti Alexander 
Published: November 2021

ABSTRACTMovement speed is considered essential for success in elite tennis. The aim of the present study was to develop a model of movement speed components and quantify their age – and gender‐related relevance for tennis performance. Physical testing data obtained from 1,434 nationally ranked junior squad tennis players were divided according to the age at peak height velocity (YPHV) into two age groups (pre‐PHV: n=103 girls, 11.7 ± 0.6 yrs.; n=466 boys, 12.7 ± 1.0 yrs.; post‐PHV: n=524 girls, 14.2 ± 1.4 yrs.; n=344 boys, 15.3 ± 1.2 yrs.). After assessing anthropometrics and maturity status, all players passed a series of standardized physical tests on an indoor hard court. All data were z‐standardized, filtered and sorted by gender, maturity level, and ranking position. The structuring of the speed‐related performance parameters resulted in four factors (“Elementary Speed”, “Jumping Power”, “Linear Speed”, and “COD Speed”), which were then confirmed by factor analysis. The correlation of these factors to the national ranking position was mostly significant but rather low, with “Linear Speed” reaching the lowest (r=0.10–0.18) and “COD Speed” the highest correlation (r=0.22–0.34). Path analytic models revealed “COD Speed” as the most important factor, which is strongly influenced by “Jumping Power” and “Linear Speed,” with medium effect sizes, while “Elementary Speed” affects this factor only slightly. It can be concluded that the relationship between movement speed and junior players’ tennis ranking is lower than expected. The development of “COD Speed” should be prioritized during testing, training, and talent identification, independent of age group and gender.Highlights
Performance parameters for 1,434 junior players with national rankings were analyzed and assigned to four superior factors.
The impact of the factors on the ranking position, as well as the internal causal relationships, were investigated via path analysis.
“COD Speed” was the most impactful factor for tennis performance and was strongly influenced by “Linear Speed” and “Jumping Power.”
Basic concepts of biological microparticles isolation by inertia spiral microchannels in simple terms: a review
Authors: Tabatabaei Seyed Ali , Zabetian Targhi Mohammad , Javaherchian Javane , Yaghoubi Marzieh 
Published: November 2021

Abstract
The microfluidics separation has absorbed wide-ranging attention in recent years due to its outstanding advantages in biological, medical, clinical, and diagnostical cell studies. While conventional separation methods failed to render the acceptable performance, microfluidics sorting methods offer many privileges such as high throughput, user-friendliness, minimizing sample volumes, cost-efficiency, non-invasive procedures, high precision, improved portability, quick processing, etc. Among the inertial microfluidics approaches such as the straight and curved microchannels, although the spiral microchannels, which are the sorts of passive separations, are complicated in concepts and geometries, they have demonstrated auspicious benefits for this purpose. Thus, numerous studies have strived to explain the principle of particle migrating and forces in these complex microchannels. However, a comprehensive understanding is still necessary. On the other side, it is manifest that the diagnosis and separation of circulating tumor cells (CTCs) from the blood are significant for targeted treatments of this detrimental disease. Therefore, this study aims to review the previous investigations and developments for understanding the CTC separation using the spiral microchannels straightforwardly and profoundly. After elucidating the inertial microfluidics and their governing physics in simple terms, we provide insights about spiral microchannels’ mechanism and concepts, the secondary flow, the cross-section effects on the separation processes, the investigation about CTCs in the spiral microchannels specifically, and finally, the future applications and challenges of this kind of inertial microfluidics. The analyses reveal that new approaches should be conducted to use spiral microchannels with combined cross-sections. These kinds of microchannels with optimum size and shape of cross-sections can improve performance efficiently.
Efficient approach for optical and morphological characterization of hybrid perovskite films based on reflectance and transmittance measurements
Authors: Caram Jorge , Senno Maximiliano , Cencha Luisa , Tinte Silvia , Urteaga Raúl , Arce Roberto D 
Published: November 2021

Abstract
Organo-inorganic perovskites (OIPs) have been intensively studied due to their potential application in low-cost, high-efficiency energy conversion in solar cells. Despite the great improvement in the quality of OIP films, wide dispersion in the same batch of perovskite-based devices remains an obstacle to obtaining highly reproducible results. For that reason, new and efficient strategies for testing deposition results is essential. Here we present a simple and efficient procedure for characterizing optical and morphological properties based on simultaneous reflectance and transmittance measurements under normal incidence over a methylammonium lead iodide film. The proposed method provides qualitative and quantitative morphological information associated with the film roughness as well as information about the position of the optical gap and possible contributions to optical dispersion in the structure that can be used as a simple diagnostic tool to optimize film deposition. Results are compared and validated with electronic and atomic force microscopy, as well as first-principles calculations.
Practical health indicator construction methodology for bearing ensemble remaining useful life prediction with ISOMAP-DE and ELM-WPHM
Authors: Gu Yingkui , Bi Qingpeng , Qiu Guangqi 
Published: November 2021

Abstract
To improve the accuracy of our previous bearing ensemble remaining useful life (RUL) prediction model using the genetic algorithm (GA), support vector regression, and the Weibull proportional hazard model (WPHM) (see Qiu et al (2020 Measurement
150 107097)), we proposed a more practical health indicator (HI) construction methodology for bearing ensemble RUL prediction. A weighted coefficient determination method for four prognostic metrics-monotonicity, robustness, trendability, and consistency-was proposed to select sensitive health features accurately using the analytic hierarchy process. The selected sensitive health features were fused through isometric feature mapping (ISOMAP), and differential evolution (DE) was employed to replace GA for computing the optimal weight coefficients of each input fused feature. One-dimensional HI was constructed by multiplying each input fused feature with the corresponding optimal weight coefficient, and RUL prediction was implemented through an extreme learning machine (ELM) and WPHM. The accuracy and effectiveness of the proposed method were validated by a bearing experiment. The results show that HI construction with ISOMAP-DE has achieved the best performance, and the proposed ELM-WPHM model is compared with BP-WPHM, SVM-WPHM, LSTM-WPHM, and DLSTM-WPHM in terms of RMSE criteria. The minimum error and training time appear in ELM-WPHM, indicating the superiority of the proposed bearing ensemble RUL prediction model.
A real time detection method for abnormal strapping of steel coil based on CCD active imaging
Authors: Ye Chuan , Zhao Liming , Wang Qiyan , Pan Bo , Xie Youchun , Wang Chao , Hu Yuanyao 
Published: November 2021

Abstract
In order to accurately detect the abnormal looseness of strapping in the process of steel coil hoisting, an accurate detection method of strapping abnormality based on CCD structured light active imaging is proposed. Firstly, a maximum entropy laser stripe automatic segmentation model integrating multi-scale saliency features is constructed. With the help of saliency detection model, the purpose is to reduce the interference of the environment to the laser stripe and highlight the distinguishability between the stripe and the background. Then, the maximum entropy is used to segment the fused saliency features and accurately extract the stripe contour. Finally, the stripe normal field is obtained by calculating the stripe gradient vector, the stripe center line is extracted based on the stripe distribution normal direction, and the abnormal strapping is recognized online according to the stripe center. Experiments show that the proposed method is effective in terms of detection accuracy and time efficiency, and has certain engineering application value.
Nanofibrous drug delivery systems for breast cancer: a review
Authors: Hussain Tanveer , Ramakrishna Seeram , Abid Sharjeel 
Published: November 2021

AbstractBreast cancer is the most common type of cancer among women. Breast-conserving surgery (BCS) is one of the preferred approaches for treating non-invasive or early-stage breast cancers. However, local-regional recurrence (LRR) is one of the critical risk factors after BCS. As many as 10%–20% of BCS cases may show LRR within 5 years and almost 50% within 10 years after surgery. Radiation therapy is one of the preferred treatments used to prevent LRR after BCS. However, because of possible side-effects of radiation therapy, targeted drug delivery systems (DDS) based on nanofibers loaded with anti-cancer drugs have been explored in recent years to control LRR. This paper aims to review different polymers and anti-cancer drugs used for developing nanofibrous DDS against various breast cancer cell lines for their efficacy and advantages. It was observed that the utilization of nanofibers scaffolds after mastectomy could decrease the recurrence of breast cancer cells to a great extent as these nanofibrous scaffolds release drugs in a sustained manner for a prolonged time eliminating the need for radiations. Besides, the side effects of chemotherapy or other aggressive anticancer treatment on healthy cells could also be avoided.
How should we model and evaluate breathing interplay effects in IMPT?
Authors: Pastor-Serrano Oscar , Habraken Steven , Lathouwers Danny , Hoogeman Mischa , Schaart Dennis , Perkó Zoltán 
Published: November 2021

Abstract
Breathing interplay effects in Intensity Modulated Proton Therapy (IMPT) arise from the interaction between target motion and the scanning beam. Assessing the detrimental effect of interplay and the clinical robustness of several mitigation techniques requires statistical evaluation procedures that take into account the variability of breathing during dose delivery. In this study, we present such a statistical method to model intra-fraction respiratory motion based on breathing signals and assess clinical relevant aspects related to the practical evaluation of interplay in IMPT such as how to model irregular breathing, how small breathing changes affect the final dose distribution, and what is the statistical power (number of different scenarios) required for trustworthy quantification of interplay effects. First, two data-driven methodologies to generate artificial patient-specific breathing signals are compared: a simple sinusoidal model, and a precise probabilistic deep learning model generating very realistic samples of patient breathing. Second, we investigate the highly fluctuating relationship between interplay doses and breathing parameters, showing that small changes in breathing period result in large local variations in the dose. Our results indicate that using a limited number of samples to calculate interplay statistics introduces a bigger error than using simple sinusoidal models based on patient parameters or disregarding breathing hysteresis during the evaluation. We illustrate the power of the presented statistical method by analyzing interplay robustness of 4DCT and Internal Target Volume (ITV) treatment plans for a 8 lung cancer patients, showing that, unlike 4DCT plans, even 33 fraction ITV plans systematically fail to fulfill robustness requirements.
Design and modeling of a Laue lens for radiation therapy with hard x-ray photons
Authors: Girou David , Ford Eric , Wade Colin , van Aarle Casper , Uliyanov Alexei , Hanlon Lorraine , Tomsick John A , Zoglauer Andreas , Collon Maximilien J , Beijersbergen Marco W , Barrière Nicolas M 
Published: November 2021

Abstract
We have designed and modeled a novel optical system composed of a Laue lens coupled to an x-ray tube that produces a focused beam in an energy range near 100 keV (λ = 12.4 picometer). One application of this system is radiation therapy where it could enable treatment units that are considerably simpler and lower in cost than present technologies relying on linear accelerators. The Laue lens is made of Silicon Laue components which exploit the silicon pore optics technology. The lens concentrates photons to a small region thus allowing high dose rates at the focal area with very much lower dose rates at the skin and superficial regions. Monte Carlo simulations with Geant4 indicate a dose deposition rate of 0.2 Gy min−1 in a cylindrical volume of 0.7 mm diameter and 10 mm length, and a dose ratio of 72 at the surface (skin) compared to the focus placed 10 cm within a water phantom. Work is ongoing to newer generation crystal technologies to increase dose rate.
Convex optimization algorithms in medical image reconstruction—in the age of AI
Authors: Xu Jingyan , Noo Frédéric 
Published: November 2021

Abstract
The past decade has seen the rapid growth of model based image reconstruction (MBIR) algorithms, which are often applications or adaptations of convex optimization algorithms from the optimization community. We review some state-of-the-art algorithms that have enjoyed wide popularity in medical image reconstruction, emphasize known connections between different algorithms, and discuss practical issues such as computation and memory cost. More recently, deep learning (DL) has forayed into medical imaging, where the latest development tries to exploit the synergy between DL and MBIR to elevate the MBIR's performance. We present existing approaches and emerging trends in DL-enhanced MBIR methods, with particular attention to the underlying role of convexity and convex algorithms on network architecture. We also discuss how convexity can be employed to improve the generalizability and representation power of DL networks in general.
Microstructure analysis and crack nucleation in TWIP steel tube at expansive deformation
Authors: Liu ChunYuan , Song KaiHong , Wu Wei , Jiang Ping , Jiang YanFei , Xia XingChuan , Liao Bo 
Published: November 2021

Abstract
The expansion test of twinning induced plastic (TWIP) steel tube was carried out at room temperature. Cracks appeared inside the tube edge when TWIP steel tube expands by 15.6%. The microstructure evolution, deformation mechanism and crack generation of TWIP steel after expansion were investigated by XDR OM TEM and EBSD. The results show that TWIP steel tube still austenite phase after expansion at room temperature; a great deal of dislocations are gathered around the grain boundaries and twin boundaries, the integral number of twins is high, and the mechanism of expansion deformation is the joint action of dislocations slip and deformation twins; Twins produce a large number of finer secondary or even multiple twins, intersecting each other; After expansion, the silk texture with direction of 〈111〉∥X0 dominated by rotating brass texture {110} 〈111〉 is gradually produced through grain deformation and rotation; The proportion of small angle grain boundaries increased greatly; It is deduced that the criterion of crack nucleation is based on the difference between the dislocation pile-up energy (DPE) and the crack nucleation energy (CNE), and the expansion deformation process of TWIP steel satisfies the condition of crack nucleation.