bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longer Interpregnancy Interval Is Associated with Gestational Diabetes Mellitus Recurrence
Authors: Peled Tzuria , Federmesser Daniella , Mazaki Eyal , Sela Hen Y. , Grisaru-Granovsky Sorina , Rottenstreich Misgav 
Published: November 2024

Objective This study aimed to evaluate the effect of interpregnancy interval (IPI) on the gestational diabetes mellitus (GDM) recurrence rate in the subsequent pregnancies following an initial pregnancy complicated by GDM.
Study Design A multicenter, retrospective cohort study was conducted. The study included women diagnosed with GDM during their index pregnancy who subsequently delivered between 26 and 42 weeks of gestation from 2005 to 2021. The study population was categorized into eight groups according to their IPIs: up to 3, 3–5, 6–11, 12–17, 18–23, 24–35, 36–47, and over 48 months. We examined the recurrence rate of GDM in the different groups while comparing it to the 18–23-month group that was defined as the reference group. Statistical analyses included univariate analyses and multiple logistic regression.
Results Out of 3,532 women who were included in the study, 1,776 (50.3%) experienced GDM recurrence in subsequent pregnancy. The recurrence rate was 44.6% for women IPI <6 months, 42.6% for women IPI of 6–11 months, 48.0% for women IPI of 12–17 months, 49.7% for women IPI of 18–23 months, 58.0% for women IPI of 24–47 months, and 62.6% for women IPI above 48 months. Multivariable logistic regression revealed that IPIs of 24–47 months and over 48 months were significantly associated with higher recurrence rates as compared with the 18–23-month reference group (adjusted odds ratio [aOR], 95% confidence interval [CI]: 1.66 [1.04–2.64] and 3.15 [1.07–9.29], respectively). This analysis also revealed other independent risk factors for GDM recurrence, including medication-controlled GDM in the index pregnancy, obesity, maternal age, parity, and gravidity.
Conclusion Longer IPIs (over 24 months) are associated with an increased risk of GDM recurrence in subsequent pregnancies. These findings suggest that clinicians should consider IPI while managing postpartum care and planning future pregnancies for women with a history of GDM.
Key Points
The Impact of Silver Diamine Fluoride and Potassium Iodide Treatment on Microtensile Bonds Strength of Composite Restoration for Carious Dentin in Primary and Permanent Teeth and Its Potential Color Changes: An In Vitro Study
Authors: Shaheen Sarah D. , Esmaeil Doaa A. M. , Ghobar Somaia 
Published: November 2024

Abstract
Objectives This study aims to examine the effects of silver diamine fluoride and potassium iodide (SDF/KI) treatment on the possible color changes and the microtensile bond strength of composite restorations to carious dentin in different dentitions.
Material and Methods A total of 48 sound human teeth were utilized in this study. Twenty-four primary molar teeth were divided into two groups. Each group has 12 teeth; group 1 received no pretreatment, while group 2 received SDF/KI treatment. Also, 24 permanent premolar teeth were divided into two groups. Group 3 received no pretreatment, and group 4 received SDF/KI treatment. For 7 days at 25 °C, every sample was submerged in a demineralizing solution. Following the manufacturer's guidelines for SDF/KI treatments, exposed dentin surfaces were promptly preserved in artificial saliva (pH 7.4) for 14 days. On the prepared teeth surfaces of the nontreated groups, deionized water was administered rather than SDF/KI. A self-etching bonding agent was used, and a 4-mm-thick composite restoration was constructed. Evaluations were conducted on color measurement, microtensile bond strength, and mode of failure.
Statistical Analysis The groups were compared using a one-way analysis of variance test, and a post hoc test was used for pairwise comparisons.
Result Regarding color measurement, in deciduous dentition, there were no statistically significant differences between the groups. Additionally, there is no discernible variation in ΔE values among various pretreatment groups in the permanent dentition. Microtensile bond strength did not differ significantly between permanent and deciduous teeth.
Conclusion A 14-day delay in the application of composite restoration can successfully conceal the color of SDF/KI without compromising the microtensile bond strength.
Classifying Three-Wall Intrabony Defects from Intraoral Radiographs Using Deep Learning–Based Convolutional Neural Network Models
Authors: Piroonsan Kanteera , Pimolbutr Kununya , Tansriratanawong Kallapat 
Published: November 2024

Abstract
Objective Intraoral radiographs are used in periodontal therapy to understand interdental bony health and defects. However, identifying three-wall bony defects is challenging due to their variations. Therefore, this study aimed to classify three-wall intrabony defects using deep learning–based convolutional neural network (CNN) models to distinguish between three-wall and non-three-wall bony defects via intraoral radiographs.
Materials and Methods A total of 1,369 radiographs were obtained from 556 patients who had undergone periodontal surgery. These radiographs, each featuring at least one area of intrabony defect, were categorized into 15 datasets based on the presence of three-wall or non-three-wall intrabony defects. We then trained six CNN models—InceptionV3, InceptionResNetV2, ResNet50V2, MobileNetV3Large, EfficientNetV2B1, and VGG19—using these datasets. Model performance was assessed based on the area under curve (AUC), with an AUC value ≥ 0.7 considered acceptable. Various metrics were thoroughly examined, including accuracy, precision, recall, specificity, negative predictive value (NPV), and F1 score.
Results In datasets excluding circumferential defects from bitewing radiographs, InceptionResNetV2, ResNet50V2, MobileNetV3Large, and VGG19 achieved AUC values of 0.70, 0.73, 0.77, and 0.75, respectively. Among these models, the VGG19 model exhibited the best performance, with an accuracy of 0.75, precision of 0.78, recall of 0.82, specificity of 0.67, NPV of 0.88, and an F1 score of 0.75.
Conclusion The CNN models used in the study showed an AUC value of 0.7 to 0.77 for classifying three-wall intrabony defects. These values demonstrate the potential clinical application of this approach for periodontal examination, diagnosis, and treatment planning for periodontal surgery.
Innovative Approaches to Digital Health in Ovulation Detection: A Review of Current Methods and Emerging Technologies
Authors: Shkodzik Katerina 
Published: November 2024

AbstractOvulation is a vital sign, as significant as body temperature, heart rate, respiratory rate, and blood pressure, in assessing overall health and identifying potential health issues. Ovulation is a key event of the menstrual cycle that provides insights into the hormonal and reproductive health aspects. Affected by the orchestra of hormones, namely thyroid, prolactin, and androgens, disruptions in ovulation can indicate endocrinological conditions and lead to gynecological problems, such as heavy menstrual bleeding, irregular periods, amenorrhea, dysmenorrhea, and difficulties in getting pregnant. Monitoring ovulation and detecting disruptions can aid in the early detection of health issues, extending beyond reproductive health concerns. It can help identify underlying causes of symptoms like excessive fatigue and abnormal hair growth. The integration of digital health technologies, such as mobile apps using machine learning algorithms, wearables tracking temperature, heart rate, breath rate, and sleep patterns, and devices measuring reproductive hormones in urine or saliva samples, offers a wealth of opportunities in family planning, early health issue diagnosis, treatment adjustment, and tracking menstrual cycles during assisted reproductive techniques. These advancements provide a comprehensive approach to health monitoring, addressing both reproductive and overall health concerns.
Reducing Vancomycin Dosage in Children on ECMO with Renal Impairment
Authors: Bobrowski Alexej , Höhn René , Kubicki Rouven , Fleck Thilo , Zürn Christoph , Maier Sven , Kari Fabian Alexander , Kroll Johannes , Stiller Brigitte 
Published: November 2024

Abstract
Background Extracorporeal membrane oxygenation (ECMO) can influence pharmacokinetics. We investigated the vancomycin dosage in children on ECMO compared to critically ill children to determine the necessary dosage adjustment on ECMO.
Methods Eight-year, single-center, retrospective cohort study at a tertiary heart center's pediatric cardiac intensive care unit (ICU) of children undergoing ECMO support. Our control group (non-ECMO) was critically ill children with delayed sternal closure after cardiac surgery. We included consecutively all children undergoing vancomycin administration. The starting dose was 10 to 15 mg/kg BW per dose, every 8 to 12 hours depending on age. The vancomycin trough level was maintained in the 10 to 20 μg/ml range.
Results 85 total courses on ECMO and 99 non-ECMO courses were included. The ECMO group's daily vancomycin dose was significantly lower than non-ECMO's at a median of 33.3 and 38.5 mg/kg/d, respectively (p < 0.001). Vancomycin serum trough levels were similar between groups and within the target range. The ECMO group's daily vancomycin dose dropped faster over time, with a dose on day 3 of 28.7 and 33.7 mg/kg/d, respectively. The impact of renal function on vancomycin dosing was more apparent in the ECMO group. If the renal function was reduced at the start of treatment, the vancomycin dose was lower in the ECMO group compared to the non-ECMO group with renal impairment (22.5 vs. 42.1 mg/kg/d; p < 0.001). When renal function was normal, the doses were similar between groups.
Conclusion In children on ECMO with impaired renal function at treatment initiation, lower vancomycin doses were necessary. Early therapeutic drug monitoring, even before reaching a steady state, should be considered.
All we need is a Silicon Valley: tech place as a strategic branding tool
Authors: Mashiah Itzhak 
Published: November 2024

AbstractDoes every country need its own “Silicon Valley”? This article delves into this question by examining the importance of place and image management. Globally, countries, cities, and regions strive to establish technology hubs, motivated by economic, marketing, and diplomatic factors. This current paper suggests that creating a new localized version of “Silicon Valley” within a country can serve as a powerful marketing tool, both on a domestic and international level. Nations can develop a technological identity and brand by adopting the Silicon Valley (SV) model and strategically projecting tech symbols to maintain this image for stakeholders. Such strategic branding of a tech hub can strengthen a nation’s reputation as a leader in innovation and technology, driving economic growth, fostering global partnerships, attracting investors, and promoting tourism.
Enhanced decoupling of conductivity relaxation from structural relaxation in non-stoichiometric protic ionic liquids involving triflic acid and 2-aminoethyl hydrogen sulfate
Authors: You Jinhai , Mangialetto Jessica , Li Bing-Yu , Jia Xu , Wei Runhong , Niu Li , De Borggraeve Wim , Wübbenhorst Michael 
Published: November 2024

The glass transition dynamics and conductivity relaxation are studied for a series of non-stoichiometric protic ionic liquids (PILs) based on 2-aminoethyl hydrogen sulfate and triflic acid with varying molar ratios (denoted as AT-55, AT-46, AT-37, AT-28, and AT-19) by broadband dielectric spectroscopy in a wide frequency (10−1–107 Hz) and temperature range (173–353 K). The results indicate that the addition of acid lowers the glass transition temperature, as confirmed by the activation energy fine structure analysis and a crossover in the conductivity relaxation time. Notably, samples with higher acid content deliver markedly increased conductivity. In addition, detailed analysis of the permittivity and modulus spectra reveals enhanced decoupling between the structural (α-process) and conductivity relaxation in samples with a higher acid content. Remarkably, nano-phase separation in AT-28 and AT-19 samples is observed, resulting in a second glass transition temperature indicating a more mobile phase. Based on the above-mentioned findings, we infer that increased acid content disrupts strong ionic interactions within the IL fraction, resulting in a decrease in the glass transition temperature and leading to nano-phase separation into distinct acid-rich and IL-rich phases with varying Tg values. This phase separation alters the long-range ionic pathways, shifting from being solely governed by IL cluster dynamics to a scenario where charge transport becomes largely decoupled from the dynamics of IL-rich clusters. Hence, modulating the stoichiometry of PILs appears a promising approach to enhance the conductivity together with widening the usable temperature range for applications.
Multifrequency electrical impedance tomography system based on undersampling combined with a fast digital demodulation algorithm
Authors: Liu Jinzhen , Zhou Yapeng , Xiong Hui , Li Xiaobin , Shi Fangming 
Published: November 2024

Multifrequency electrical impedance tomography (MFEIT) has shown great application prospects in the field of biomedical imaging. To realize high-precision multifrequency electrical impedance information acquisition, a high-precision MFEIT system with undersampling combined with a fast digital demodulation algorithm is proposed. The system is integrated with 16 electrodes, and semi-parallel acquisition is used. In addition, a novel multifrequency digital demodulation algorithm is applied to enhance the accuracy of multifrequency excitation signal demodulation and achieve rapid demodulation. This improvement is achieved by analyzing the process of the multifrequency digital demodulation algorithm and combining undersampling with a fast digital demodulation technique. To evaluate the proposed method, a systematic comparative experiment is conducted. The experimental results demonstrate that the demodulation error using the undersampling method is less than 0.7% within the frequency range of 5–500 kHz. In addition, the system achieves a maximum signal-to-noise ratio of 62.92 dB, an average blur radius of 0.953, and an average position error percentage of 9.3%. The results indicate that the MFEIT system constructed based on the above research has good performance and a high signal-to-noise ratio.
Electron cyclotron emission quasi-optical transmission system on the HL-3 tokamak
Authors: Yu X. , Shi Z. B. , Yang Z. C. , Jiang M. , Chen W. , Yu G. Y. , Zhu Y. L. , Deng W. C. , Zhou Y. , Shen Y. Q. , Wen J. , Shi P. W. , Han K. X. 
Published: November 2024

A new quasi-optical (QO) Electron Cyclotron Emission (ECE) transmission system has been established on the HL-3 tokamak, which includes a focusing QO mirror combination and a long-distance transmission line. This system was developed to meet the requirements for poloidal spatial resolution and the high signal-to-noise ratio needed for magnetohydrodynamic (MHD) instability studies using ECE on the HL-3. The QO mirror combination was installed inside the vacuum chamber for focusing. Laboratory test results, theoretical calculations, and synthetic ECE simulation results indicate that the Gaussian beam can meet the spatial resolution requirements for the accurate measurement of the MHD instability on the q = 1/2/3 surfaces, corresponding to the poloidal mode numbers m = 3/6/9. This includes good diagnostic poloidal spatial resolution for the important 2/1 and 3/2 modes. At the front end of the transmission line, a high-efficiency mode converter was designed to transition the TE10 mode to the HE11 mode for input into the transmission line, with an insertion loss of less than 1.5 dB. A 30 m long-distance corrugated oversized waveguide was constructed, with transmission losses ranging from 6 to 10 dB in the 60–120 GHz range. Polarization adjustment results show that the polarization offset and geometric spatial polarization angle change consistently, which can provide a reference for polarization adjustment in other complex structured transmission lines. The newly established ECE QO transmission system will provide strong support for future physics research involving ECE on the HL-3.
Production of prominence by Mandarin‑speaking EFL
learners
Authors: Hua Congchao 
Published: November 2024

Abstract
This study investigated Mandarin-speaking
English-as-a-foreign-language (EFL) learners’ prominence production in relation
to prominence position, focus type, and proficiency. Eighty Mandarin-speaking
EFL learners and 20 native English speakers read 12 question-answer pairs in
English, with the questions eliciting different prominence patterns (end vs.
non-end) for different focus types (broad vs. narrow). The results revealed that
the phonological aspect (prominence assignment) was influenced by prominence
position, focus type, and proficiency, but the phonetic aspect (phonetic
realization of prominence) was affected only by prominence position.
Phonologically, the learners achieved more native-like performance on end than
non-end prominence, on broad than narrow focus, and their performance improved
with proficiency. Phonetically, they achieved more native-like performance on
end than non-end prominence and produced native-like F0 and intensity, but not
duration. Drawing on these patterns, in teaching priorities should be given to
prominence assignment over phonetic realization, non-end over end prominence,
and narrow over broad focus.
Lateral size dependence of photoconductivity in TMD networks
Authors: Olaya-Cortes D , Ramos L , Rubio T , Pabon J P , Hernandez Y 
Published: November 2024

Abstract
Photoconductivity is an important feature of semiconductors that finds major attention in the fields of solar cells, hydrogen and oxygen evolution reactions, and photodetectors. This feature involves a change of density of charge carriers induced by light, which is dependent on the generation of light-induced carriers and the recombination of excitons. This phenomenon has been observed in transition metal dichalcogenides (TMDs) since 2010; however, when printing such materials on flexible substrates, they form networks that would exhibit distinct transport characteristics compared to isolated TMDs crystals. In this work, TMD nanosheets are printed by vacuum filtering and their photoconductivity was measured by using a xenon lamp inside an obscure chamber. Molybdenum disulfide-based devices show higher responsivity as compared with tungsten disulfide devices, which is attributed to an increased light absorption and hydroxyl groups attached to the surface of the MoS2 networks that enhance the photoconductivity by increasing the carrier lifetimes. Furthermore, the responsivity of the devices behaves similarly to the conductivity, which is modeled as networks of pairs of nanosheets and junctions through percolative paths. Finally, this is the first report that shows that the response time of the devices increases with lateral size.
MSDFNet: multi-scale detail feature fusion encoder–decoder network for self-supervised monocular thermal image depth estimation
Authors: Kong Lingjun , Zheng Qianhui , Wang Wenju 
Published: November 2024

Abstract
Currently available thermal image depth estimation methods are difficult to efficiently extract fine multi-scale feature information from thermal images and suffer from the problem of blurring details at the edges of the estimated depth map. To address these challenges, this paper proposes MSDFNet, a multi-scale detail feature fusion encoder–decoder network, for self-supervised monocular thermal image depth estimation. The model is based on a channel expansion hourglass residual lightweight feature encoder, which can capture rich and fine-grained multi-scale feature information with low computational effort. MSDFNet utilizes a detail feature weight evaluation decoder to fuse cross-scale features and reevaluate the importance of each feature, thereby emphasizing critical edge information at multiple scales. Additionally, MSDFNet incorporates a depth consistency loss function, which provides self-supervised signals for the detailed features of thermal images and improves the optimization of network performance. The method is applied to the ViViD++ and MS2 datasets and achieves state-of-the-art depth estimation performance compared to existing state-of-the-art algorithms. In the Indoor Dark scenario of the ViViD++ dataset, the Abs Rel, Sq Rel, RMSE, and RMSE log error metric values of MSDFNet are reduced by 6.71%, 11.92%, 9.09%, and 5.73%, respectively, while the accuracy metric values

δ
<

1.25
i

,
i
=
1
,
2
,
3

were improved by 4.18%, 1.13%, and 0.2%, respectively. In addition, MSDFNet proves its excellent generalization ability on the MS2 dataset. The Abs Rel and RMSE error values in the night scene are reduced by 45.6% and 30.09%, respectively, and the accuracy

δ
<

1.25
i

,
i
=
1
,
3

is improved by 20.95% and 1.33%, respectively. The Abs Rel and RMSE values in the rainy day scenario are reduced by 1.33% and 1.21%, respectively, and the accuracy

δ
<

1.25
i

,
i
=
1
,
3

is improved by 0.24% and 0.83%, respectively.
Research on belt deviation diagnosis of belt conveyors based on deep learning
Authors: Wu Lei , Wang Yahu , Zhang Wei , Huang Shuai , Li Junxia 
Published: November 2024

Abstract
Due to the slow detection speed, low accuracy, and small detection range of existing methods for detecting belt deviation in belt conveyors, this paper introduces an enhanced ultra-fast lane detection (UFLD) algorithm that leverages deep learning for the detection of belt deviation. Based on the UFLD algorithm, a variable step-size row anchor division method is proposed, and the simple parameter-free attention module is added to the network to enhance the network model’s focus on edge information of conveyor belts. Furthermore, improvements are made to the convolution operations in the ResNet-18 Stem and the downsampling operations in the residual modules, thereby enhancing the network’s ability to recognize the edges of conveyor belts. Based on the established experimental platform, a high-definition camera equipped with a track-type inspection robot was used to inspect the entire belt conveyor, covering the whole of the transmission line. The conveyor belt operation datasets collected under various working conditions were used to train and comparatively study the Hough Transform, DHT, YOLOv5, YOLOv8, LaneNet, SAD, and UFLD algorithms. The experimental outcomes demonstrate that the algorithm introduced in this article outperforms the other algorithms, achieving an F1-measure of 90.31%, an accuracy rate of 94.19 %, and a detection speed of 71 frames per second, meeting the real-time diagnostic needs for belt misalignment in the coal mining industry.