bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial Intelligence in Predicting Postpartum Hemorrhage in Twin Pregnancies Undergoing Cesarean Section
Authors: Dogru Sukran , Ezveci Huriye , Akkus Fatih , Bahçeci Pelin , Karanfil Yaman Fikriye , Acar Ali 
Published: January 2025

Abstract
This study aimed to create a risk prediction model with artificial intelligence (AI) to identify patients at higher risk of postpartum hemorrhage using perinatal characteristics that may be associated with later postpartum hemorrhage (PPH) in twin pregnancies that underwent cesarean section. The study was planned as a retrospective cohort study at University Hospital. All twin cesarean deliveries were categorized into two groups: those with and without PPH. Using the perinatal characteristics of the cases, four different machine learning classifiers were created: Logistic regression (LR), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP). LR, RF, and SVM models were created a second time by including class weights to manage the underlying imbalances in the data. A total of 615 twin pregnancies were included in the study. There were 150 twin pregnancies with PPH and 465 without PPH. Dichorionity, PAS, and placenta previa were significantly higher in the PPH-positive group (p = .045, p = .004, p = .001 respectively). In our model, LR with class weight was the best model with the highest negative predictive value. The AUC in our LR with class weight model was %75.12 with an accuracy of 70.73%, a PPV of 47.92%, and an NPV of 85.33% in our data. Although the application of machine learning to create predictive models using clinical risk factors and our model’s 70% accuracy rate are encouraging, it is not sufficient. Machine learning modeling needs further study and validation before being incorporated into clinical use.
Impact of Spring Snow Cover Anomaly Over the Russian Far East on the Early Summer Precipitation Variability in Northeast China
Authors: Zhang Taotao , Wang Xiaoyi , Song Yaoming , Chen Haishan 
Published: January 2025

AbstractThe summer precipitation in Northeast China (NEC) exerts vital effects on the local crop yield and food security of our country, however, the prediction skill of it is still limited as yet. This study investigated the impact of snow cover anomaly over the Russian Far East during spring (March–April) on the succeeding early summer (May–June) precipitation variability in NEC as well as the underlying physical mechanisms during the years 1961–2020 based on diagnostic analyses and model simulation. The results showed that, on the interannual timescale, the decreased (increased) spring snow cover over the Russian Far East is conducive to the increased (decreased) NEC early summer precipitation. Further analyses indicated that the negative anomaly of spring snow cover can persist into early summer, which then enhances the diabatic heating and thereby warms the overlying atmosphere via the snow‐albedo effect. The warming atmosphere favors the intensified Okhotsk High and an associated prominent anticyclonic circulation over northeast Asia. The anomalous southeast winds on the southwest flank of the anticyclone could bring abundant water vapor to the NEC, induce moisture convergence and ascending motion, and eventually contribute to the above‐than‐normal precipitation. These physical processes operate in the opposite manner in the case of the positive anomaly of spring snow cover. Our findings are beneficial to further improve the understanding and prediction ability of the summer precipitation variability over NEC.
Multiple Elevation‐Dependent Climate Signals From Quantitative Wood Anatomical Measurements of Rocky Mountain Bristlecone Pine
Authors: Edwards Julie , Tintor Will L. , Nolin Alexandre F. , Woodhouse Connie A. , von Arx Georg , Anchukaitis Kevin J. 
Published: January 2025

AbstractSouthwestern North America has experienced significant temperature increases over the last century, leading to intensified droughts that significantly affect montane forests. Although tree‐ring data have provided long‐term context for this recent drought severity, the varying physiological responses of trees to climate variability make it challenging to disentangle the combined influence of temperature and soil moisture. Here we investigate complex climate‐growth relationships in Rocky Mountain bristlecone pine (Pinus aristata) at a low‐elevation and a high‐elevation site using quantitative wood anatomy (QWA). Significant correlations with climate were found for low‐elevation tree‐ring width (TRW) and earlywood chronologies, including positive correlations with spring and early summer precipitation and drought indices and negative correlations with spring and early summer maximum temperatures. At high elevations, TRW and earlywood chronologies show positive responses to summer moisture, whereas latewood chronologies correlate positively with August and September maximum temperatures and negatively with August precipitation. We leverage this differing seasonality of moisture and temperature signals and compare the QWA data to known droughts. The earlywood lumen area is found to be highly responsive to drought because of its physiological reliance on water availability for maintaining turgor pressure during cell enlargement. We also observed a decline in temperature sensitivity at the high elevation site, suggesting shifts in the dominance of limiting factors. Integrating QWA with traditional dendrochronology improves interpretations of tree‐ring data for use in climate reconstruction, offering detailed insights into tree physiological responses and the mix of environmental and developmental controls on cell growth.
Single-cell analysis identifies the CNP/GC-B/cGMP axis as marker and regulator of modulated VSMCs in atherosclerosis
Authors: Lehners Moritz , Schmidt Hannes , Zaldivia Maria T. K. , Stehle Daniel , Krämer Michael , Peter Andreas , Adler Julia , Lukowski Robert , Feil Susanne , Feil Robert 
Published: January 2025

Abstract
A balanced activity of cGMP signaling contributes to the maintenance of cardiovascular homeostasis. Vascular smooth muscle cells (VSMCs) can generate cGMP via three ligand-activated guanylyl cyclases, the NO-sensitive guanylyl cyclase, the atrial natriuretic peptide (ANP)-activated GC-A, and the C-type natriuretic peptide (CNP)-stimulated GC-B. Here, we study natriuretic peptide signaling in murine VSMCs and atherosclerotic lesions. Correlative profiling of pathway activity and VSMC phenotype at the single-cell level shows that phenotypic modulation of contractile VSMCs to chondrocyte-like plaque cells during atherogenesis is associated with a switch from ANP/GC‑A to CNP/GC‑B signaling. Silencing of the CNP/GC-B axis in VSMCs results in an increase of chondrocyte-like plaque cells. These findings indicate that the CNP/GC-B/cGMP pathway is a marker and atheroprotective regulator of modulated VSMCs, limiting their transition to chondrocyte-like cells. Overall, this study highlights the plasticity of cGMP signaling in VSMCs and suggests analogies between CNP-dependent remodeling of bone and blood vessels.
Bilayer nanographene reveals halide permeation through a benzene hole
Authors: Niyas M. A. , Shoyama Kazutaka , Grüne Matthias , Würthner Frank 
Published: January 2025

Abstract
Graphene is a single-layered sp
2-hybridized carbon allotrope, which is impermeable to all atomic entities other than hydrogen1,2. The introduction of defects allows selective gas permeation3–5; efforts have been made to control the size of these defects for higher selectivity6–9. Permeation of entities other than gases, such as ions10,11, is of fundamental scientific interest because of its potential application in desalination, detection and purification12–16. However, a precise experimental observation of halide permeation has so far remained unknown11,15–18. Here we show halide permeation through a single benzene-sized defect in a molecular nanographene. Using supramolecular principles of self-aggregation, we created a stable bilayer of the nanographene19–23. As the cavity in the bilayer nanographene could be accessed only by two angstrom-sized windows, any halide that gets trapped inside the cavity has to permeate through the single benzene hole. Our experiments reveal the permeability of fluoride, chloride and bromide through a single benzene hole, whereas iodide is impermeable. Evidence for high permeation of chloride across single-layer nanographene and selective halide binding in a bilayer nanographene provides promise for the use of single benzene defects in graphene for artificial halide receptors24,25, as filtration membranes26 and further to create multilayer artificial chloride channels.
Specification of claustro-amygdalar and palaeocortical neurons and circuits
Authors: Kaur Navjot , Kovner Rothem , Gulden Forrest O. , Pletikos Mihovil , Andrijevic David , Zhu Tianjia , Silbereis John , Shibata Mikihito , Shibata Akemi , Liu Yuting , Ma Shaojie , Salla Nikkita , de Martin Xabier , Klarić Thomas S. , Burke Megan , Franjic Daniel , Cho Hyesun , Yuen Matthew , Chatterjee Ipsita , Soric Paula , Esakkimuthu Devippriya , Moser Markus , Santpere Gabriel , Mineur Yann S. , Pattabiraman Kartik , Picciotto Marina R. , Huang Hao , Sestan Nenad 
Published: January 2025

Abstract
The ventrolateral pallial (VLp) excitatory neurons in the claustro-amygdalar complex and piriform cortex (PIR; which forms part of the palaeocortex) form reciprocal connections with the prefrontal cortex (PFC), integrating cognitive and sensory information that results in adaptive behaviours1–5. Early-life disruptions in these circuits are linked to neuropsychiatric disorders4–8, highlighting the importance of understanding their development. Here we reveal that the transcription factors SOX4, SOX11 and TFAP2D have a pivotal role in the development, identity and PFC connectivity of these excitatory neurons. The absence of SOX4 and SOX11 in post-mitotic excitatory neurons results in a marked reduction in the size of the basolateral amygdala complex (BLC), claustrum (CLA) and PIR. These transcription factors control BLC formation through direct regulation of Tfap2d expression. Cross-species analyses, including in humans, identified conserved Tfap2d expression in developing excitatory neurons of BLC, CLA, PIR and the associated transitional areas of the frontal, insular and temporal cortex. Although the loss and haploinsufficiency of Tfap2d yield similar alterations in learned threat-response behaviours, differences emerge in the phenotypes at different Tfap2d dosages, particularly in terms of changes observed in BLC size and BLC–PFC connectivity. This underscores the importance of Tfap2d dosage in orchestrating developmental shifts in BLC–PFC connectivity and behavioural modifications that resemble symptoms of neuropsychiatric disorders. Together, these findings reveal key elements of a conserved gene regulatory network that shapes the development and function of crucial VLp excitatory neurons and their PFC connectivity and offer insights into their evolution and alterations in neuropsychiatric disorders.
Highly Efficient and achromatic mid-infrared silicon nitride meta-lenses
Authors: Maher Abdullah , Swillam Mohamed A. 
Published: January 2025

Abstract
Inverse design with topology optimization considers a promising methodology for discovering new optimized photonic structure that enables to break the limitations of the forward or the traditional design especially for the meta-structure. This work presents a high efficiency mid infra-red imaging photonics element along mid infra-red wavelengths band starts from 2 to 5 µm based on silicon nitride optimized material structures. The first two designs are broadband focusing and reflective meta-lens under very high numerical aperture condition (NA = 0.9). The two designs are modeled by inverse design with topology optimization problem with Kreisselmeier–Steinhauser (k–s) aggregation objective function, while the final design is depended on novel inverse design optimization problem with double aggregation objective function that can target bifocal points along the wavelength band producing high efficiency achromatic broadband multi-focal meta-lens under very high numerical apertures (
$$N{A}_{1} = 0.9, \, N{A}_{2}=0.88$$
).
Positive association between chronic hepatitis B virus infection and anemia in pregnancy in Southern China
Authors: Huang Renliang , Lu Zhe , Li Xinze , Zhou Duo , Xu Jing , Lin Dan , Fu Yunxue , Liang Yan , Li Xuexia , Petersen Frank , Zhou Qiaomiao , Yu Xinhua 
Published: January 2025

Abstract
This observational investigation aimed to explore potential risk factors for anemia in pregnancy. Firstly, a cross-sectional study was conducted, encompassing a review of clinical data of 43,201 pregnant women admitted to the Hainan Women and Children’s Medical Center between January 2017 and December 2020. Comparison between women with and without anemia in pregnancy revealed significant differences between the two groups concerning age, gestational diabetes, hypothyroidism, hyperthyroidism, chronic hepatitis B virus infection, syphilis infection, and human immunodeficiency virus infection. Multivariable logistic regression analysis showed that chronic hepatitis B virus infection was significantly associated with anemia during pregnancy (AOR   2.97, 95% CI 2.57–3.44, p < 0.0001). Subsequently, a retrospective cohort comprising 86 cases with chronic hepatitis B virus infection and 129 control subjects recruited from the Hainan Women and Children’s Medical Center from November 2021 and January 2023 was examined. Results of the examination revealed a corroborative association between chronic hepatitis B virus infection and anemia in pregnancy (OR  2.13, 95% CI 1.20–3.79, p = 0.0092), particularly manifesting in the third trimester of gestation. Further analysis unveiled distinctive hematological alterations among cases with chronic hepatitis B virus infection, characterized by diminished erythrocyte size and reduced levels of corpuscular hemoglobin. Collectively, these findings underscore a positive association of chronic hepatitis B virus infection with anemia during pregnancy.
Use of data mining algorithms in prediction of eggshell thickness from egg quality traits of Potchefstroom Koekoek layers
Authors: Molabe Kagisho Madikadike , Tyasi Thobela Louis , Mbazima Vusi Gordon 
Published: January 2025

Abstract
Egg quality is affected by lot of factors. Study was conducted to compare performance of data mining algorithms; Classification and regression tree (CART), Chi-square automatic interaction detection (CHAID), Exhaustive chi-square automatic interaction detection (Ex-CHAID) and Multivariate adaptive regression spline (MARS) in prediction of Potchefstroom Koekoek’s eggshell thickness from egg quality traits. 350 eggs were collected at 31st to 39th week to examine the egg quality traits. MARS with R2(0.86) revealed yolk ratio, shell weight, egg shape index, yolk ratio, shell ratio, albumen weight and albumen ratio as explanatory variables predicting eggshell thickness. CART with R2 (0.37), yolk/albumen ratio was noted to be influential predictor of eggshell thickness. CHAID and Ex-CHAID (R2= 0.35) discovered egg weight as the best predictor of eggshell thickness. MARS with R2(0.86) revealed yolk ratio, shell weight, egg shape index, yolk ratio, shell ratio, albumen weight and albumen ratio as explanatory variables predicting eggshell thickness. MARS had high r (0.925), R2 (0.856) and lower RMSE (0.129) and AIC (-975.331) compared to CHAID, Ex-CHAID and CART leading MARS to be the best data mining algorithm when predicting the eggshell thickness using egg quality traits.
Causal chambers as a real-world physical testbed for AI methodology
Authors: Gamella Juan L. , Peters Jonas , Bühlmann Peter 
Published: January 2025

Abstract
In some fields of artificial intelligence, machine learning and statistics, the validation of new methods and algorithms is often hindered by the scarcity of suitable real-world datasets. Researchers must often turn to simulated data, which yields limited information about the applicability of the proposed methods to real problems. As a step forward, we have constructed two devices that allow us to quickly and inexpensively produce large datasets from non-trivial but well-understood physical systems. The devices, which we call causal chambers, are computer-controlled laboratories that allow us to manipulate and measure an array of variables from these physical systems, providing a rich testbed for algorithms from a variety of fields. We illustrate potential applications through a series of case studies in fields such as causal discovery, out-of-distribution generalization, change point detection, independent component analysis and symbolic regression. For applications to causal inference, the chambers allow us to carefully perform interventions. We also provide and empirically validate a causal model of each chamber, which can be used as ground truth for different tasks. The hardware and software are made open source, and the datasets are publicly available at causalchamber.org or through the Python package causalchamber.
Speech Technology for Automatic Recognition and Assessment of Dysarthric Speech: An Overview
Authors: Bhat Chitralekha , Strik Helmer 
Published: January 2025

Purpose:
In this review article, we present an extensive overview of recent developments in the area of dysarthric speech research. One of the key objectives of speech technology research is to improve the quality of life of its users, as evidenced by the focus of current research trends on creating inclusive conversational interfaces that cater to pathological speech, out of which dysarthric speech is an important example. Applications of speech technology research for dysarthric speech demand a clear understanding of the acoustics of dysarthric speech as well as of speech technologies, including machine learning and deep neural networks for speech processing.

Method:
We review studies pertaining to speech technology and dysarthric speech. Specifically, we discuss dysarthric speech corpora, acoustic analysis, intelligibility assessment, and automatic speech recognition. We also delve into deep learning approaches for automatic assessment and recognition of dysarthric speech. Ethics committee or institutional review board did not apply to this study.

Conclusions:
Overcoming the challenge of limited data and exploring new avenues in data collection, artificial intelligence–powered analysis and teletherapy hold immense potential for significant advancements in dysarthria research. To make longer and faster strides, researchers typically rely on existing research and data on a global scale. Therefore, it is imperative to consolidate the existing research and present it in a form that can serve as a basis for future work. In this review article, we have reviewed the contributions of speech technologists to the area of dysarthric speech with a focus on acoustic analysis, speech features, and techniques used. By focusing on the existing research and future directions, researchers can develop more effective tools and interventions to improve communication, quality of life, and overall well-being for people with dysarthria.
iSurgARy: A mobile augmented reality solution for ventriculostomy in resource‐limited settings
Authors: Asadi Zahra , Castillo Joshua Pardillo , Asadi Mehrdad , Sinclair David S. , Kersten‐Oertel Marta 
Published: January 2025

AbstractGlobal disparities in neurosurgical care necessitate innovations addressing affordability and accuracy, particularly for critical procedures like ventriculostomy. This intervention, vital for managing life‐threatening intracranial pressure increases, is associated with catheter misplacement rates exceeding 30% when using a freehand technique. Such misplacements hold severe consequences including haemorrhage, infection, prolonged hospital stays, and even morbidity and mortality. To address this issue, a novel, stand‐alone mobile‐based augmented reality system (iSurgARy) aimed at significantly improving ventriculostomy accuracy, particularly in resource‐limited settings such as those in low‐ and middle‐income countries is presented. iSurgARy uses landmark based registration by taking advantage of light detection and ranging to allow for accurate surgical guidance. To evaluate iSurgARy, a two‐phase user study is conducted. Initially, the usability and learnability is assessed with novice participants using the system usability scale (SUS), incorporating their feedback to refine the application. In the second phase, human‐computer interaction and clinical domain experts are engaged to evaluate this application, measuring root mean square error, SUS and NASA task load index metrics to assess accuracy usability, and cognitive workload, respectively.
Integrated DC arc model and DC arc detection approach based on K‐line diagram and spectrum integral difference
Authors: Xiong Qing , Zhang Junyi , Li Jianghan , Tang Yijie , Zhuang Yi , Cui Yanjie , Li Rui , Ji Shengchang 
Published: January 2025

AbstractIn the low voltage direct current (LVDC) systems, the occurrence of DC series arc faults poses a significant threat to the safe operation of the system. This paper develops an accurate arc model for the arc fault simulation. The proposed arc model consists the steady‐state impedance, high frequency characteristics, and dynamic characteristics of the arc. Additionally, this paper proposes an arc detection algorithm combining the K‐line diagram and the spectrum integral difference of the arc current in the LVDC systems. This algorithm can identify four circuit states: normal operation, arc fault, switching action, and load mutation, which addresses the challenge of arc fault detection in complex working conditions. The STM32F407 microcontroller is utilized to design a DC series arc fault detector. Online detection tests demonstrate that the arc faults can be accurately detected and isolated within 37 ms, meeting the requirement of the UL1699B standard, with an accuracy rate of 99.33%. These achievements not only enhance the safety of the LVDC systems but also provide valuable references for the development of arc fault detection technology.
Voltage support strength analysis and stability control strategy for grid‐forming wind power transmission system
Authors: Zhang Xiangyu , Wu Jiahui , Fu Yuan 
Published: January 2025

AbstractIncreasing the short‐circuit ratio (SCR) of the power transmission system is crucial to ensuring voltage stability when the system has a high‐penetration of wind energy resources. This paper first analyses the weak nodes in the power system and quantifies the SCR requirements of these nodes under voltage safety constraints. Based on this analysis, a third‐order dynamic model of a virtual synchronous generator is established, and a design method for virtual transient reactance is proposed to meet the system's SCR requirements. Finally, a power system simulation with high‐penetration of wind energy is constructed, validating that under the proposed voltage stability support control strategy, grid‐forming wind turbines can meet the system's SCR requirements by optimizing the design of transient reactance, thereby improving the voltage stability of the system.