bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonlinear convection stagnation point flow of Oldroyd-B nanofluid with non-Fourier heat and non-Fick’s mass flux over a spinning sphere
Authors: Kenea Gadisa , Ibrahim Wubshet 
Published: January 2024

AbstractThe current paper concerned with a non-linear convection flow of the Oldroyd-B nanofluid at a point of stagnation across a rotating sphere under the influence of convective heat and passive control conditions. The analysis of energy and concentration transition has been scrutinized based on the Cattaneo–Christov diffusion model. The formulated coupled mathematical problem involving boundary requirements can be alerted to a set of highly nonlinear ordinary differential equations by employing similarity analysis. The numerical solution for the governing problem was computed by utilizing bvp4c solver method. The performance of velocity fields, skin friction drag, energy, heat transfer rate, and concentration for various control parameters has been analyzed using diagrams and tables. The findings stipulated that velocity, temperature, and nanoparticle are enhanced for the relaxation time constant while they decay for the retardation time parameter. The upshots also confirmed that enlarging magnetic parameters leads to improve both linear velocity and coefficient of skin friction. The velocity profiles are enhanced as a function of the rotation constant. But, normal velocity declines for buoyancy force ratio, and the same trend is being noted for magnetic and relaxation time parameters on angular velocity. The fluid temperature declines for the Prandtl number and augments for thermal convective parameter. The coefficient of skin friction decreases for larger thermal relaxation and rotation parameters, whereas an analogous effect is being noticed for Brownian parameter on the concentration field. Further, the thermophoresis parameter displays an enhancing tendency on temperature as well as concentration profile while bringing down the Nusselt number. The Lewis number and solutal relaxation parameter filter the concentration field. The graph of the streamline is sketched for identical values of the magnetic parameter and noticed that the contour lines increased as magnified. Confirmation of the current outcomes with former studies is presented.
Nuts, vegetables, fruits, and protein dietary pattern during pregnancy is inversely associated with risk of childhood allergies: a case–control study
Authors: Adineh Parisa , Amini Shirin , Abolnezhadian Farhad , Jafari Fatemeh , Ebrahimian Niayesh 
Published: January 2024

AbstractAllergic diseases are prevalent chronic conditions among children and can lead to significant health and economic issues. It is hypothesized that healthy and high quality diet during pregnancy can prevent the onset of allergic diseases in offspring. This study aimed to investigate the potential relationship between major dietary patterns during pregnancy and allergies in children under one year of age. This case–control study was conducted involving 244 participants (122 mothers of allergic children and 122 healthy controls) who visited pediatricians and allergy outpatient clinics in Khuzestan Province, Iran, between June 2022 and March 2023. Demographic information was recorded using a socio-demographic questionnaire. A food frequency questionnaire was used to identify the foods consumed during pregnancy. Major dietary patterns were extracted using principal component analysis, and the potential relationship between these patterns and childhood allergies was investigated using multivariable logistic regression models. The crude odds ratio (OR) analysis showed that the fourth quartile of "Nut, vegetables, fruits, and protein" dietary pattern was associated with lower occurrence of childhood allergies (OR: 0.214, 95% CI = 0.068–0.679; P trend = 0.211). After adjusting for cofactors in Model 3, this association was still observed in the fourth quartile (OR = 0.108, 95% CI = 0.019–0.613; P trend, 0.001). However, no significant association was observed between "Carbohydrate and cereals" and "Salty" dietary patterns and childhood allergies. The study findings suggest that a maternal dietary pattern rich in nuts, vegetables, and fruits during pregnancy may reduce the risk of allergic diseases in offspring.
New perspective on first-trimester serum uric acid level in predicting the risk of gestational diabetes mellitus
Authors: Li Xiaojing , Niu Ziru , Bai Liwei , Lu Qiang 
Published: January 2024

AbstractThis study aimed to investigate the correlation between serum uric acid (UA) and gestational diabetes mellitus (GDM) during the first trimester and provide a new perspective for the prevention and treatment of GDM. Based on the diagnostic criteria of gestational diabetes of the International Association of Diabetes and Pregnancy Study Groups, 1744 and 4256 patients were enrolled in the GDM and normal glucose tolerance (NGT) groups. Four groups were constituted based on the quartile of first-trimester serum UA (UA) level, and the differences in each indicator between groups were compared. Logistic regression was used to analyze the effects of UA level on GDM risk. The rate of GDM in the UA quartile changed from low to high. Significant differences were also observed in fasting plasma glucose level, 1 h post glucose and 2 h post glucose levels, in all the groups (P < 0.05), which increased with the UA level. UA level were independent risk factors for GDM. The best threshold of GDM predicted by the first-trimester UA level was 226.55 μmol/L. The first-trimester UA level in patients with GDM was relatively higher and was an independent risk factor for GDM.
A monthly temperature prediction based on the CEEMDAN–BO–BiLSTM coupled model
Authors: Zhang Xianqi , Ren He , Liu Jiawen , Zhang Yuehan , Cheng Wanhui 
Published: January 2024

AbstractTemperature as an important indicator of climate change, accurate temperature prediction has important guidance and application value for agricultural production, energy management and disaster warning. Based on the advantages of CEEMDAN model in effectively extracting the time–frequency characteristics of nonlinear and nonsmooth signals, BO algorithm in optimizing the objective function within a limited number of iterations, and BiLSTM model in revealing the connection between the current data, the previous data and the future data, a monthly average temperature prediction model based on CEEMDAN–BO–BiLSTM is established. A CEEMDAN–BO–BiLSTM-based monthly average temperature prediction model is developed and applied to the prediction of monthly average temperature in Jinan City, Shandong Province. The results show that the constructed monthly mean temperature prediction model based on CEEMDAN–BO–BiLSTM is feasible; the constructed CEEMDAN–BO–BiLSTM model has an average absolute error of 1.17, a root mean square error of 1.43, an average absolute percentage error of 0.31%, which is better than CEEMDAN–BiLSTM, EMD–BiLSTM, and BiLSTM models in terms of prediction accuracy and shows better adaptability; the constructed CEEMDAN–BO–BiLSTM model illustrates that the model is not over-modeled and adds complexity using Friedman’s test and performance comparisons between model run speeds. The model provides insights for effective forecasting of monthly mean temperatures.
Deep learning reveals moisture as the primary predictability source of MJO
Authors: Shin Na-Yeon , Kim Daehyun , Kang Daehyun , Kim Hyemi , Kug Jong-Seong 
Published: January 2024

AbstractThe Madden-Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability that interacts with many other Earth system phenomena. The prediction skill of the MJO in many operational models is lower than its potential predictability, partly due to our limited understanding of its predictability source. Here, we investigate the source of MJO predictability by combining machine learning (ML) with a 1200-year-long Community Earth System Model version 2 (CESM2) simulation. A Convolutional Neural Network (CNN) for MJO prediction is first trained using the CESM2 simulation and then fine-tuned using observations via transfer learning. The source of MJO predictability in the CNN is examined via eXplainable Artificial Intelligence (XAI) methods that quantify the relative importance of the input variables. Our CNN exhibits an enhanced prediction skill over previous ML models, achieving a skill level of about 25 days. This level of performance is slightly superior or comparable to most operational models participating in the S2S project, although a few dynamical models surpass it. The XAI methods highlight precipitable water anomalies over the Indo-Pacific warm pool as the primary precursors of the subsequent MJO development for 1–3 weeks forecast lead times. Our results suggest that realistic representation of moisture dynamics is crucial for accurate MJO prediction.
Breaking the fast: first report of dives and ingestion events in molting southern elephant seals
Authors: Charlanne Laura M. , Chaise Laureline , Sornette Damien , Piot Erwan , McCafferty Dominic J. , Ancel André , Gilbert Caroline 
Published: January 2024

AbstractSouthern elephant seals (SES) experience a ‘catastrophic molt’, a costly event characterized by the renewal of both hair and epidermis that requires high peripheral vascular circulation. Molting animals are therefore constrained by high metabolic heat loss and are thought to fast and remain on land. To examine the ability of individuals to balance the energetic constraints of molting on land we investigate the stomach temperature and movement patterns of molting female SES. We find that 79% of females swam and 61% ingested water or prey items, despite the cost of cold-water exposure while molting. This behavior was related to periods of warm and low wind conditions, and females that dived and ingested more often, lost less body mass. We conclude that the paradigm of fasting during the molt in this species, and the fitness consequences of this behavior should be reconsidered, especially in the context of a changing climate.
Single-cell transcriptomic analyses of tumor microenvironment and molecular reprograming landscape of metastatic laryngeal squamous cell carcinoma
Authors: Sun Yuanyuan , Chen Sheng , Lu Yongping , Xu Zhenming , Fu Weineng , Yan Wei 
Published: January 2024

AbstractLaryngeal squamous cell carcinoma (LSCC) is a malignant tumor with a high probability of metastasis. The tumor microenvironment (TME) plays a critical role in cancer metastasis. To gain insights into the TME of LSCC, we conducted single-cell RNA-seq (scRNA-seq) on samples collected from LSCC patients with or without lymphatic metastasis. The stem and immune cell signatures in LSCC suggest their roles in tumor invasion and metastasis. Infiltration of a large number of regulatory T cells, dysplastic plasma cells, and macrophages that are at the early development stage in the cancerous tissue indicates an immunosuppressive state. Abundant neutrophils detected at the cancer margins reflect the inflammatory microenvironment. In addition to dynamic ligand-receptor interactions between the stromal and myeloid cells, the enhanced autophagy in endothelial cells and fibroblasts implies a role in nutrient supply. Taken together, the comprehensive atlas of LSCC obtained allowed us to identify a complex yet unique TME of LSCC, which may help identify potential diagnostic biomarkers and therapeutic targets for LSCC.
Beyond acceptable limits: intrinsic contamination in commercial 15N2 impedes reliable N2 reduction experiments
Authors: De Ras Michiel , Hollevoet Lander , Martens Johan. A. , Liu Tianxi , Nicolai Bart M. , Hertog Maarten L. A. T. M. , Hofkens Johan , Roeffaers Maarten B. J. 
Published: January 2024

The validity of N2 reduction experiments relies on control experiments with isotopically labelled 15N2. Commercially obtained 15N2 contains high amounts of 15NH3 and other activated nitrogen species which are readily reduced to 15NH3.
Light‐field image super‐resolution with depth feature by multiple‐decouple and fusion module
Authors: Chan Ka‐Hou , Im Sio‐Kei 
Published: January 2024

AbstractLight‐field (LF) images offer the potential to improve feature capture in live scenes from multiple perspectives, and also generate additional normal vectors for performing super‐resolution (SR) image processing. With the benefit of machine learning, established AI‐based deep CNN models for LF image SR often individualize the models for various resolutions. However, the rigidity of these approaches for actual LF applications stems from the considerable diversity in angular resolution among LF instruments. Therefore, an advanced neural network proposal is required to utilize a CNN‐based model for super‐resolving LF images with different resolutions obtained from provided features. In this work, a preprocessing to calculate the depth channel from given LF information is first presented, and then a multiple‐decouple and fusion module is introduced to integrate the VGGreNet for the LF image SR, which collects global‐to‐local information according to the CNN kernel size and dynamically constructs each view through a global view module. Besides, the generated features are transformed to a uniform space to perform final fusion, achieving global alignment for precise extraction of angular information. Experimental results show that the proposed method can handle benchmark LF datasets with various angular and different resolutions, reporting the effectiveness and potential performance of the method.
Three-dimensional time-dependent convection model for asteroseismology
Authors: Lizin S. , Dupret M.-A. , Salmon S. J. A. J. , Ludwig H.-G. 
Published: January 2024

Context. Due to an ill-depicting model of the convective layers below the photosphere in 1D stellar models (structural contribution) and/or a misrepresentation of the coupling between convection and oscillations (modal contribution), a well-known deviation appears between observed and theoretical frequencies, which grows towards high frequencies; the so-called surface effects. While satisfying solutions have been found regarding the structural contribution, the accurate modeling of the modal effect still represents a challenge. Alongside the frequency, the interaction between convection and oscillations also impacts the damping rate of the modes and forms an important part of the driving mechanism behind the stellar oscillations of low-mass stars. With increasing observational capabilities at our disposal with Kepler and TESS, shortcomings in modeling constitute the main limitation to accurate seismic probing of solar-like and red giant stars.
Aims. We present the formalism of an approach that changes the current paradigm by addressing three-dimensional space. This new formalism consists in an original nonadiabatic 3D time-dependent convection model for asteroseismology.
Methods. We aim to keep the entire 3D structure of the astrophysical flow in these superficial layers in order to fully account for the nature of turbulence in our model via the use of advanced hydrodynamic simulation. We use the perturbative approach and introduce a spectral decomposition approach that results in an entirely new formalism describing standing waves in 3D. This formalism is set to solve the quasi-radial global nonadiabatic oscillation equations in a full 3D framework.
Results. Based on physical assumptions, we establish an eigenvalue problem describing the 3D quasi-radial global nonadiabatic stellar oscillation. We also provide a prescription for its numerical resolution alongside a proposed iteration method for our formalism. Finally, we derive the peculiar 3D work integral and establish the expression of the damping rate. We show how our formalism offers the possibility to probe the complex structure of stars and is able to precisely locate regions of the driving and damping of the modes as well as their physical origin.
Cepheid Metallicity in the Leavitt Law (C-MetaLL) survey
Authors: Bhardwaj A. , Ripepi V. , Testa V. , Molinaro R. , Marconi M. , De Somma G. , Trentin E. , Musella I. , Storm J. , Sicignano T. , Catanzaro G. 
Published: January 2024

Context. The highly debated effect of metallicity on the absolute magnitudes of classical Cepheid variables needs to be properly quantified for determining accurate and precise distances based on their Leavitt Law.
Aims. Our goal is to obtain homogeneous optical and near-infrared light curves of Milky Way Cepheid variables complementing their already collected high-resolution spectroscopic metallicities as part of the C-MetaLL survey. Together with Gaia parallaxes, we investigate period-luminosity-metallicity relations for Cepheid variables at multiple wavelengths.
Methods. We present homogeneous multiband (grizJHKs) time-series observations of 78 Cepheids including 49 fundamental mode variables and 29 first-overtone mode variables. These observations were collected simultaneously using the ROS2 and REMIR instruments at the Rapid Eye Mount telescope. Multiwavelength photometric data were used to investigate pulsation properties of Cepheid variables and derive their period–luminosity (PL) and period–Wesenheit (PW) relations.
Results. The Cepheid sample covers a large range of distances (0.5 − 19.7 kpc) with varying precision of parallaxes, and thus astrometry-based luminosity fits were used to derive PL and PW relations in optical Sloan (griz) and near-infrared (JHKs) filters. These empirically calibrated relations exhibit large scatter primarily due to larger uncertainties in parallaxes of distant Cepheids, but their slopes agree well with those previously determined in the literature. Using homogeneous high-resolution spectroscopic metallicities of 61 Cepheids covering −1.1 < [Fe/H] < 0.6 dex, we quantified the metallicity dependence of PL and PW relations which varies between −0.30 ± 0.11 (in Ks) and −0.55 ± 0.12 (in z) mag dex−1 in grizJHKs bands. However, the metallicity dependence in the residuals of the PL and PW relations is predominantly seen for metal-poor stars ([Fe/H] < −0.3 dex), which also have larger parallax uncertainties. The modest sample size precludes us from separating the contribution to the residuals due to parallax uncertainties, metallicity effects, and reddening errors. While this Cepheid sample is not optimal for calibrating the Leavitt law, upcoming photometric and spectroscopic datasets of the C-MetaLL survey will allow the accurate derivation of PL and PW relations in the Sloan and near-infrared bandpasses, which will be useful for the distance measurements in the era of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time and upcoming extremely large telescopes.
Subcutaneous and Visceral Fat: Relation with Brown Adipose Tissue
Activation in Women
Authors: Da Rosa Samir Ezequiel , Neves Eduardo Borba , Martinez Eduardo Camilo , Marson Runer Augusto , Reis Victor Machado 
Published: January 2024

AbstractBrown adipose tissue (BAT) helps control body weight and is inversely correlated
with body fat, but it is unclear whether it is subcutaneous adipose tissue (SAT)
or visceral adipose tissue (VAT) that is related to BAT activation. The
presented study aimed to verify the relation of SAT and VAT on BAT activation
through infrared thermography (IRT) and cold stimulation in adult women. Forty
women were evaluated in body composition and skin temperature (Tskin)
acquisition by IRT. Student’s independent t-test, Pearson’s
correlation, and two-way repeated measures ANOVA with Tukey post-hoc were
applied. Women with low amounts of SAT and VAT had a significant increase in
supraclavicular Tskin (SCVT). Medium negative degrees of linear variation were
found before and after cold stimulation between SCVT, SAT and VAT. A significant
effect of the moment factor and the group factor on the SCVT between subjects
divided into the groups were pointed out. No difference was found in the
relation between SAT, VAT, and BAT in adult women, pointing out that both types
of fat are equally related. These results can help clinical practice understand
clearly, through IRT, that the high accumulation of SAT and VAT can impair the
activation of BAT and hinder the loss of weight in women.
Validation of Echocardiographic Measurements in Patients with Pulmonary Embolism in the RIETE Registry
Authors: Lyhne Mads Dam , Bikdeli Behnood , Dudzinski David M. , Muriel-García Alfonso , Kabrhel Christopher , Sancho-Bueso Teresa , Pérez-David Esther , Lobo José Luis , Alonso-Gómez Ángel , Jiménez David , Monreal Manuel ,   the RIETE Investigators
Published: January 2024

Abstract
Background In acute pulmonary embolism (PE), echocardiographic identification of right ventricular (RV) dysfunction will inform prognostication and clinical decision-making. Registro Informatizado Enfermedad TromboEmbolica (RIETE) is the world's largest registry of patients with objectively confirmed PE. The reliability of site-reported RV echocardiographic measurements is unknown. We aimed to validate site-reported key RV echocardiographic measurements in the RIETE registry.
Methods Fifty-one randomly chosen patients in RIETE who had transthoracic echocardiogram (TTE) performed for acute PE were included. TTEs were de-identified and analyzed by a core laboratory of two independent observers blinded to site-reported data. To investigate reliability, intraclass correlation coefficients (ICCs) and Bland–Altman plots between the two observers, and between an average of the two observers and the RIETE site-reported data were obtained.
Results Core laboratory interobserver variations were very limited with correlation coefficients >0.8 for all TTE parameters. Agreement was substantial between core laboratory observers and site-reported data for key parameters including tricuspid annular plane systolic excursion (ICC 0.728; 95% confidence interval [CI], 0.594–0.862) and pulmonary arterial systolic pressure (ICC 0.726; 95% CI, 0.601–0.852). Agreement on right-to-left ventricular diameter ratio (ICC 0.739; 95% CI, 0.443–1.000) was validated, although missing data limited the precision of the estimates. Bland–Altman plots showed differences close to zero.
Conclusion We showed substantial reliability of key RV site-reported measurements in the RIETE registry. Ascertaining the validity of such data adds confidence and reliability for subsequent investigations.
Designing for possibility in public space: affordance, assemblage, and ANT
Authors: Stevens Quentin , Daly Jonathan , Dovey Kim 
Published: January 2024

AbstractThe design of urban public space is inherently problematic because the range of its possible uses and meanings is broad and unpredictable. This paper engages this problematic through the lens of Gibson’s theory of ‘affordances’—the ways the material world affords for human desires. We first explore some conceptual and methodological problems of the theory of affordances and its application in understanding and designing public space. These dimensions of affordance theory are then reconceived using the relational thinking of assemblage and actor-network theory (ANT). A key contribution of the paper is an expanded typology of affordances which includes improvised and serendipitous affordances that extend beyond the intentions of designers and users. This opens new ways of thinking about the design of urban public space as a space of possibility where outcomes are open, multiple, and unpredictable. The paper suggests how urban spaces can be shaped to better support rich cultural diversity and social inclusion.