bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perinatal Mortality Trend Associated with Maternal Obesity in United States between 2015 and 2020
Authors: Yao Ruofan , Rossi Jordan , Nguyen Hoang Yen , Vedhanayagam Kriti , Tritch Neville , Karageuzian Sergio , Gedestad Ilish , Contag Stephen 
Published: January 2025

Objective Obesity is associated with an increased risk of stillbirth and neonatal death. Since the publication of A Randomized Trial of Induction Versus Expectant Management (ARRIVE) in 2018, there was an increase in 39-week deliveries. The objective of this study was to evaluate the trends in perinatal mortality by body mass index (BMI) category from 2015 to 2020.
Study Design This was a retrospective cohort study of U.S. births between 2015 and 2020. The rates of stillbirths, infant deaths, and perinatal mortality were calculated for each BMI category. Logistic regression models were constructed based on specific outcome rates from 2015 to 2018 to predict the rates in 2019 and 2020. The predicted rates were compared with the actual rates to determine possible deviations due to policy and practice changes that occurred.
Results Between 2015 and 2018, the stillbirth rate increased for ascending BMI categories. Whereas the neonatal death rate decreased for all except the underweight group, the perinatal death rate increased in all except for those with category III obesity. In 2019 the perinatal mortality rate decreased for every BMI category except underweight group. In 2020, the rate of infant deaths increased for all BMI categories compared with the predicted rates. The results were similar after excluding common comorbidities.
Conclusion Perinatal mortality rates improved in 2019, reversing the increasing trend from 2015 to 2018. However, this trend did not persist for some BMI categories in 2020. These findings may suggest a beneficial effect of policy changes since the ARRIVE trial publication and the negative effects from the coronavirus disease 2019 pandemic.
Key Points
Cerebrospinal Fluid Composition of Infants with Ischemic Stroke
Authors: Daniel Katherine B. , Benjamin Daniel K. , Smith P. Brian , Cotten C. Michael , Clark Reese H. , Greenberg Rachel G. 
Published: January 2025

Objective This study aimed to characterize the cerebrospinal fluid (CSF) of infants with stroke and compare those findings to the CSF of infants with bacterial meningitis and neither condition in the first 14 postnatal days.
Study design Cohort study of 30,092 infants who received a lumbar puncture in the first 14 postnatal days discharged from >400 neonatal intensive care units from 1997 to 2020. CSF parameters were compared between infants with stroke and bacterial meningitis using non-parametric hypothesis testing and quantile regression.
Results Compared to infants with bacterial meningitis, infants with stroke had a significantly lower median protein concentration, higher median glucose concentration, higher median red blood cell count, and higher median monocyte count. Using quantile regression at the 75th percentile, infants with stroke had a significantly lower white blood cell count, segmented neutrophil count, and lymphocyte count than infants with bacterial meningitis.
Conclusion This study addresses the paucity of literature describing the CSF of infants with ischemic stroke. Knowledge of the differences in CSF parameters between infants with stroke and meningitis may allow for faster recognition and intervention before CSF culture results are available.
Key Points
Effects of Alternative Milk on Streptococcus Mutans Biofilm Formation and Enamel Demineralization in Human Primary Teeth
Authors: Srivoha Naruemon , Asvanund Yuwadee , Mitrakul Kemthong , Srisatjaluk Ratchapin 
Published: January 2025

Abstract
Objectives This study was conducted to investigate the effects of alternative milk on Streptococcus mutans biofilm formation and their ability to demineralize enamel in primary teeth.
Materials and Methods First, to evaluate the effects of cow milk, lactose-free cow milk, goat milk, unsweetened pistachio milk, and sweetened pistachio milk on S. mutans biofilm formation, biofilm assay was conducted. The optical density (OD) was measured to determine S. mutans biofilm. Second, to assess the enamel demineralization, enamel slabs were prepared from 50 primary incisor teeth and divided into three test groups, along with positive and negative control groups. Enamel slabs were immersed in each type of milk three times a day for 5 days. The percentage of surface hardness loss (%SHL) for enamel demineralization was measured. One enamel slab was randomly selected from each group to visualize the enamel opacity in demineralization area by using a light microscope. Another slab was randomly selected from each group to stain with fluorescence dye and to observe the biofilm structure by using a confocal microscope.
Results The OD ± SD (standard deviation) measurements for S. mutans biofilm formation in cow milk, lactose-free cow milk, goat milk, unsweetened pistachio milk, and sweetened pistachio milk were 0.082 (± 0.002), 0.086 (± 0.004), 0.083 (± 0.007), 0.0952 (± 0.010), and 0.342 (± 0.072), respectively. The sweetened pistachio milk exhibited significantly more biofilm formation than the other milk (p < 0.05). Since there was no significant difference in biofilm formation among cow milk, lactose-free cow milk, goat milk, and unsweetened pistachio milk, we tested the enamel demineralization only with cow milk, unsweetened pistachio milk, and sweetened pistachio milk. The %SHL (± SD) for cow milk, unsweetened pistachio milk, and sweetened pistachio milk were 20.01 (± 2.618), 22.088 (± 3.4), and 35.49 (± 2.069), respectively. The %SHL on the enamel in sweetened pistachio milk was higher (p < 0.001) than other tested milk. White spot lesion was directly visualized on slabs in sweetened pistachio milk under light microscope. Biofilm formed in sweetened pistachio milk demonstrated a mushroom-like structure, whereas cow milk and unsweetened pistachio milk had a flat biofilm structure.
Conclusion Sweetened pistachio milk increases the risk for primary incisor teeth caries formation greater than cow milk and unsweetened pistachio milk regarding S. mutans biofilm formation was higher in quantity and ability to demineralization in primary teeth.
Oral Cancer's New Enemy: Goniothalamus umbrosus Targets Oral Squamous Cell Carcinoma and Spare Human Gingival Fibroblast Cells
Authors: Aziz Nuraini Che , Alahmad Basma Ezzat Mustafa , Kashmoola Muhanad Ali , Lestari Widya , Rosdy Nik Mohd Mazuan Nik Mohd , Mokhtar Khairani Idah 
Published: January 2025

Abstract
Objective Oral squamous cell carcinoma (OSCC) is the prevailing type of oral cancer, representing poor prognosis and elevated mortality rates. Major risk factors for OSCC include the use of tobacco products, alcohol consumption, betel quid chewing, and genetic mutation. Goniothalamus umbrosus is traditionally consumed by cancer patients to fight against tumor growth. To date, research on the anticancer potential of G. umbrosus in oral cancer remains deficient. This study aimed to evaluate the anticancer potential of G. umbrosus in OSCC cell lines (SCC-15 and HSC-3) and compare its cytotoxic activity on human gingival fibroblast (HGF) cell lines.
Material and Methods Leaves of G. umbrosus were cleaned, air dried, ground, and soaked for 24 hours with methanol and hexane repeatedly three times, respectively. Pooled extracts of each solvent were then dried with a rotary evaporator. Anticancer potential of G. umbrosus extracts was evaluated on two OSCC cell lines (SCC-15 and HSC-3) and a normal HGF cell line incubated for 24, 48, and 72 hours by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The cytotoxicity of cisplatin was assessed as a positive control. Morphological changes of cells were observed under an inverted microscope.
Results MTT assay revealed that G. umbrosus methanol extract (GUME) displayed moderate anticancer activity on SCC-15, HSC-3, and HGF cell lines with IC50 values of 126.67, 90.5, and 87.33 µg/mL following 72 hours' incubation times, respectively. G. umbrosus hexane extract (GUHE) exerted moderate anticancer activity against SCC-15 and HSC-3 cell lines with IC50 values of 171 and 174 µg/mL, respectively, but weak cytotoxicity against the HGF cell line with IC50 value of 343.5 µg/mL. Cisplatin exerted a strong cytotoxic impact on both OSCC and HGF cell lines. Morphological observation revealed the characteristics of cells undergoing apoptosis.
Conclusion The findings show that GUHE was more selective in inhibiting the proliferation of oral cancer cells than GUME by exerting moderate cytotoxicity on OSCC cell lines and weak cytotoxicity in HGF cells, while GUME exerted moderate cytotoxicity on both. These findings suggest a more targeted anticancer effect by GUHE as compared with cisplatin, which exerted nonselective cytotoxic activity. These findings provide a groundwork for the development of more targeted plant-based treatment for oral cancer.
Exploring young Chilean learners’ ‘thick’ voices about English language learning
Authors: Tabali Pía , Pinter Annamaria 
Published: January 2025

Abstract
This paper aims to explore the perspectives of Chilean primary school children about their English education. A
hermeneutic approach was adopted in this longitudinal study to foreground the voices of children. Altogether 9 children (between
the ages of 7–9) from two underprivileged schools in Santiago, Chile, participated in the study. The first author spent eight
months in the field teaching and researching at the same time. The research question in this paper aims to address the views of
children about their English learning experiences, and based on these insights, some pedagogical implications are drawn for the
context and beyond. Participatory methods for data collection such as conversations wrapped around information gap activities,
role-play games, drawing tasks and reflection tasks were employed to allow the children to express themselves in a relaxed,
trusting and comfortable environment. The findings reveal that young children are articulate and capable of reflecting on what
they enjoy in their English learning and why. This study highlights the importance of incorporating children’s voices into
pedagogical decisions in English language teaching and learning.
Processing costs in Cantonese-Latin script-mixing
Authors: Tam Janessa Pui Ling , Monahan Philip J. , Helms-Park Rena 
Published: January 2025

Abstract
An emerging trend among young Cantonese speakers is to script-mix morphographic Chinese characters with Latin
graphemes in social media exchanges, uncommon in traditional Chinese contexts. Results of a self-paced reading experiment with
Cantonese speakers are reported to determine whether script-mixing incurs processing costs, and if so, whether these can be
attributed to Inhibitory Control of one of the two scripts or to Dual Activation of both scripts but with slower lexical access
within the non-dominant script. Sentences were presented either entirely in Chinese characters or had one region presented in
Latin graphemes. Processing costs arose only at the switch from Latin graphemes back to Chinese characters, pointing to the
involvement of Inhibitory Control. Further, these costs only appeared in a subset of grammatical categories, potentially
coinciding with parsing uncertainties. As such, a combination of script-mixing and parsing complexities could be seen to result in
processing costs in certain sentential positions.
Adaptive Nesterov momentum method for solving ill-posed inverse problems
Authors: Jin Qinian 
Published: January 2025

Abstract
Nesterov’s acceleration strategy is renowned in speeding up the convergence of gradient-based optimization algorithms and has been crucial in developing fast first order methods for well-posed convex optimization problems. Although Nesterov’s accelerated gradient method has been adapted as an iterative regularization method for solving ill-posed inverse problems, no general convergence theory is available except for some special instances. In this paper, we develop an adaptive Nesterov momentum method for solving ill-posed inverse problems in Banach spaces, where the step-sizes and momentum coefficients are chosen through adaptive procedures with explicit formulas. Additionally, uniform convex regularization functions are incorporated to detect the features of sought solutions. Under standard conditions, we establish the regularization property of our method when terminated by the discrepancy principle. Various numerical experiments demonstrate that our method outperforms the Landweber-type method in terms of the required number of iterations and the computational time.
Emergence and tunability of Fermi-pocket and electronic instabilities in layered Nickelates
Authors: Sheth Alpesh , Lacroix Claudine , Burdin Sébastien 
Published: January 2025

Abstract
Layered Nickelates have gained intensive attention as potential high-temperature superconductors, showing similarities and subtle differences to well-known Cuprates. This study introduces a modelling framework to analyze the tunability of electronic structures by focusing on effective orbitals and additional Fermi pockets, mimicking doping or external pressure qualitatively. It investigates the role of the

3

d

z
2

orbital in interlayer hybridization, which leads to the formation of a second pocket in the Fermi surface. The resulting effective model also predicts specific charge and spin susceptibility in the form of Lindhard susceptibility at wave vector

q

0

=
(
π
,
π
)

, which can be tuned by doping or pressure. These results provide valuable insights into tunable orbital contributions and their influence on potential ordering and electronic instabilities in Layered Nickelates.
Platanus occidentalis L. fruit-derived carbon materials for electrochemical potassium storage
Authors: Hao Jiaxing , Ye Mingyuan , Vijaya Kumar Saroja Ajay Piriya , Liu Liying , Wu Yuhan , Hao Xiaorui , Liu Feng , Fang Yingjiao , Dong Xuejun , Li Laishi , Wu Yusheng , Xu Yang 
Published: January 2025

Abstract
In the post-lithium-ion battery era, potassium-ion batteries (PIBs) have been considered as a promising candidate because of their electrochemical and economic characteristics. However, as an emerging electrochemical storage technology, it is urgent to develop capable anode materials that can be produced at low cost and on a large scale to promote its practical application. Biomass-derived carbon materials as anodes of PIBs exhibit strong competitiveness by their merits of low weight, high stability, non-toxicity, and wide availability. In this work, we employed Platanus occidentalis L. fruits as a precursor to prepare a series of biomass-derived carbon materials by simply adjusting carbonization temperature, and we explored their electrochemical potassium storage capability as anode materials. The optimized sample (annealed at 800 °C) delivered good potassium storage capability (193.3 mAh g−1 at 100 mA g−1 after 100 cycles), cycling stability (80.4 mAh g−1 after 300 cycles at 300 mA g−1), and rate performance (51.2 mAh g−1 at 1000 mA g−1). This work demonstrates a feasible way to utilize biomass waste disposal for emerging sustainable energy storage technologies.
Investigation of trochoidal paths in physics lessons
Authors: Kämpf Lydia , Bauer Jan , Stallmach Frank 
Published: January 2025

Abstract
Using the example of trochoids it is shown how Bruner’s cognitive-psychological model of modes of representations is used to introduce the kinematics and its mathematical description of a complex motion in the introductory phase of physics studies. Enactive (experimental), iconic (simulation) and symbolic (equation) representations of the rolling motion of a wheel are combined to address the different types of learning to gradually introduce the formal description of trochoids.
The joint recognition of multi-MHD instabilities on HL-2A
Authors: Zhu Xiaobo , Yang Zongyu , Xia Fan , He Muwen , Shi Peiwan , Yu Liming , Zhang Yi , Deng Wei , Chen Zhengwei , Xu Zhaohe , Dong Yunbo , Zhong Wulyu 
Published: January 2025

Abstract
In tokamak plasmas, various Magnetohydrodynamic (MHD) instabilities could be driven by free energy, which enhance the plasma’s transportation, leading to a reduction in critical fusion parameters such as temperature and density, and in severe cases, can even cause major plasma disruptions. Accurate identification and active control of MHD is an important technology for maintaining stable operation and improving the parameter performance of fusion reactors in the future, but it is difficult to balance the accuracy, robustness and standard uniformity by traditional methods to recognize MHD instability. This study employs deep learning techniques to learn from 1000 shots manually labeled as three types of MHD instabilities: fishbone mode, long-lived mode, and TM mode, enabling real-time automated recognition of the instabilities. High accuracies of 97.83%, 95.32%, 94.84% are obtained on 200 testing shots, which are measured by area under the receiver-operator characteristic curve (AUC). Data processing methods that conform to the intuition of physics experts, such as short time Fourier transform (STFT), have been retained, and advanced artificial intelligence algorithms such as Resnet have been combined to achieve a high accuracy rate. It also demonstrated the robustness in fully automatic detections over thousands of discharges. Furthermore, this study explores multitask learning techniques. Instead of using three individual neural network to recognize the different instabilities, a joint recognition algorithm is proposed. The joint algorithm shares the encoder of the three networks and use separate decoder branches to output the result of different instabilities. An inspiring outcome is found that the joint algorithm outperforms the individual ones on all of the instability recognition tasks. Implementing multiple MHD recognition tasks jointly can comprehensively improve the model’s performance on each task by sharing related information between intrinsically related tasks. This means that in the future, the model can further develop as more tasks are added, revealing a possible technique routine to build an accurate and comprehensive large-scale model for fusion applications. The method realizes high accuracy, robustness and computational efficiency of MHD instability recognition at the same time, providing a powerful means to support the real-time control of MHD instability in future fusion reactors.
Error field correction in reversed field pinch with feedback stabilization of resistive wall mode
Authors: Saad E A , Brunsell P R 
Published: January 2025

Abstract
A recently developed, model-based linear-quadratic optimal resistive wall mode (RWM) control algorithm is extended in this work to include error field (EF) correction. The EF correction is based on a scheme known in control engineering as disturbance estimation and rejection. The new control algorithm performs real-time EF estimation and feedforward EF compensation in parallel with feedback stabilization. The new RWM control algorithm is implemented and tested in reversed field pinch (RFP) plasma experiments on the EXTRAP T2R device. The EF correction leads to improved performance of the RFP plasma, indicated by lower plasma resistance and sustained, less perturbed intrinsic tearing mode rotation, visible as a reduction of the temporal fluctuations in the mode rotation frequency. The estimated spatial and temporal structure of the EF provides useful information for identification of the EF sources in the EXTRAP T2R device.
Ultra-sensitive flexible piezoresistive pressure sensor for biopressure and tiny force measurements based on tilted micropillar array microstructures
Authors: Su Yue , Chang Yukuan , Xiao Mingke , Wu Jiatao , Zhang Xu , Chen Hongda 
Published: January 2025

Abstract
Flexible pressure sensor can acquire important information during contact with the human body and the external environment, thus shining in various fields such as rehabilitative monitoring, artificial intelligence and touch-on displays. With the development of the fifth generation (5 G) mobile communication technology and the Internet of Things, flexible sensing devices need to be used more in ultra-precision fields, such as biopressure and tiny force detection, which require devices to have higher sensitivity. In this work, an ultra-sensitive flexible piezoresistive pressure sensor is created by embedding multi-walled carbon nanotubes onto a polydimethylsiloxane layer with tilted micropillar array microstructures on its surface. Based on the sensing mechanism of microstructure bending deformation rather than compression deformation, the fabricated device exhibits fascinating properties in terms of ultrahigh sensitivity (1.74 kPa−1), fast response time (<100 ms), low detection limit (5.8 Pa) and excellent cyclic stability. Furthermore, the prepared sensors can meet the sensing needs in a variety of dynamic environments, including real-time artery pulse, airflow, acoustic vibrations, and finger bending, indicating that the sensing devices have enormous potential in human health assessment and diagnosis, and robotic tactile perception. This work provides an innovative approach for the development of highly sensitive sensors required in practical applications.
Observing kinematic anisotropies of the stochastic background with LISA
Authors: Heisenberg Lavinia , Inchauspé Henri , Maibach David 
Published: January 2025

Abstract
We propose a diagnostic tool for future analyses of stochastic gravitational wave
background signals of extra-galactic origin in LISA data. Next-generation gravitational wave
detectors hold the capability to track unresolved gravitational waves bundled into a stochastic
background. This composite background contains cosmological and astrophysical contributions, the
exploration of which offers promising avenues for groundbreaking new insights into very early
universe cosmology as well as late-time structure formation. In this article, we develop a full
end-to-end pipeline for the extraction of extra-galactic signals, based on kinematic anisotropies
arising from the galactic motion, via full-time-domain simulations of LISA's response to the
gravitational wave anisotropic sky. Employing a Markov-Chain-Monte-Carlo map-making scheme,
multipoles up to ℓ=2 are recovered for scale-free spectra in the case of a high
signal-to-noise ratio. We demonstrate that our analysis is consistently beating sample variance
and is robust against statistical and systematic errors. The impact of instrumental noise on the
extraction of kinematic anisotropies is investigated, and we establish a detection threshold of
Ω
GW
≳ 5 × 10-8 in the presence of instrument-induced noise. Potential
avenues for improvement in our methodology are highlighted.
Imprints of PeV cosmic-ray sources on the diffuse gamma-ray emission
Authors: Kaci Samy , Giacinti Gwenael 
Published: January 2025

Abstract
We present our new model for the description of the very high energy Galactic gamma-ray
emission based on a discrete injection of cosmic rays by individual sources. We investigate the
morphology of the very high energy gamma-ray sky, the detectability of cosmic-ray sources and the
clumpiness of the diffuse gamma-ray flux, assuming two different scenarios for cosmic-ray
propagation. Namely, a standard isotropic and homogeneous diffusion process and an isotropic and
inhomogeneous diffusion process. We notably formulate a possible explanation to the small number
of hadronic PeVatrons recently detected by LHAASO. In the case of the inhomogeneous diffusion
process, we constrain the number of hadronic PeVatrons to be small. Finally, we give an argument
that may explain the discrepancy between the interstellar gas density distribution and the very
high energy diffuse gamma-ray flux.