bluuebunny/crossref_metadata_2025_split huggingface dataset:
UAV‐Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest
Authors: Beyer Matthias , Iraheta Alberto , Gerchow Malkin , Kuehnhammer Kathrin , Callau‐Beyer Ana Claudia , Koeniger Paul , Dubbert David , Dubbert Maren , Sánchez‐Murillo Ricardo , Birkel Christian 
Published: February 2025

AbstractThe spatial variation of soil water isotopes (SWI)—representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques—has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between the spatial variability of soil water content and soil water isotope patterns with canopy status, represented in the form of VI. We carried out a spatial sampling of 10 SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm–5 m). Best relationships were used for generating soil water isoscapes for the entire study area. Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R2 of 0.66 for δ18O and 0.64 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU in tropical dry forest environments. Supporting spatial analyses of SWI with UAV‐based approaches might be a future avenue for improving the spatial representation and credibility of such studies.
Frequency and factors associated with the utilization (curative and preventive) of oral health care services among pregnant women in Kinshasa, Democratic Republic of Congo
Authors: Sekele Patrick Marob-Ndjock , Kamangu Erick Ntambwe , Kayembe Harry-César Ntumba , Chandad Fatiha , Bolenge Jacques Ileboso , Mbambi Stephanie Mikalo , Sekele Jean-Paul Isouradi-Bourley , Kalala Em Kazadi , Nyimi Fidele Bushabu , Akilimali Pierre Zalagile 
Published: February 2025

Abstract

Background
The Democratic Republic of Congo (DRC) has one of the highest maternal and neonatal mortality rates in Africa. There is a growing body of evidence about the relationship between poor oral health and adverse pregnancy outcomes. However, there is a lack of information about oral health status during pregnancy in the DRC. This study aimed to identify the factors related to the utilization of oral health care services among pregnant women.

Methods
A hospital-based cross-sectional study was conducted in four health facilities representing each administrative district of the city of Kinshasa, between March and May, 2021. The study population comprised pregnant women aged at least 18 or over attending antenatal care (ANC), selected using a simple random sampling technique. Data were collected using a structured questionnaire. Multivariable logistic regression was employed to identify factors associated with the outcome variable using the adjusted odds ratio (AOR) with its 95% confidence interval (95% CI) and p value  <  0.05.

Results
A total of 5% of the 500 pregnant women who participated in the study were identified as users of oral healthcare services. 15% of pregnant women were aware of the necessity of oral health care during pregnancy, while 58% indicated that dental visits for routine and/or treatment purposes were not a priority during pregnancy. Factors associated with its utilization were knowledge of the need for oral health care during pregnancy (AOR:3.62, 95% CI: 1.42–9.26), knowledge of the importance of routine visits or dental treatment for oral diseases during pregnancy (AOR: 4.94, 95% CI: 1.70–16.73), and having experience oral health problem during the current pregnancy (AOR: 3.13, 95% CI: 1.22–8.21).

Conclusion
The utilization of oral health care services during pregnancy is very low. Appropriate public health initiatives are urgently needed to facilitate collaboration between health professionals to integrate oral and dental consultations, oral health counseling, and check-ups as an essential component of routine ANC.
Endurance exercise remodels skeletal muscle by suppressing Ythdf1-mediated myostatin expression
Authors: Huang Xin , Xu Chenzhong , Zhang Jie , Wu Weiwei , Wang Zimei , Pang Qiuxiang , Liu Zuojun , Liu Baohua 
Published: February 2025

Abstract
Exercise can improve health via skeletal muscle remodeling. Elucidating the underlying mechanism may lead to new therapeutics for aging-related loss of skeletal muscle mass. Here, we show that endurance exercise suppresses expression of YT521-B homology domain family (Ythdf1) in skeletal muscle, which recognizes the N6-methyladenosine (m6A). Ythdf1 deletion phenocopies endurance exercise-induced muscle hypertrophy in mice increases muscle mitochondria content and type I fiber specification. At the molecular level, Ythdf1 recognizes and promotes the translation of m6A-modified Mstn mRNA, which encodes a muscle growth inhibitor, Myostatin. Loss of Ythdf1 leads to hyperactivation of skeletal muscle stem cells (MuSCs), also called satellite cells (SCs), enhancing muscle growth and injury-induced regeneration. Our data reveal Ythdf1 as a key regulator of skeletal muscle homeostasis, provide insights into the mechanism by which endurance exercise promotes skeletal muscle remodeling and highlight potential strategies to prevent aging-related muscle degeneration.
Dielectric constant of MgO tunnel barrier with epitaxial strain
Authors: Nozaki Tomohiro , Onoda Hiroshige , Tamaru Shingo , Nakayama Hiroyasu , Konoto Makoto , Nozaki Takayuki , Yuasa Shinji 
Published: February 2025

Abstract
MgO tunnel barrier is a key material in spintronics. MgO-based magnetic tunnel junctions (MTJs) are widely used in magnetic sensors and magnetoresistive random access memory (MRAM) applications. The MgO tunnel barrier also plays a central role in research on the voltage control of magnetic anisotropy (VCMA) effect, which enables an emerging magnetization control technique with ultralow power consumption. However, the value of the dielectric constant (ε
r), which is a basic physical quantity of the MgO tunnel barrier, has not been experimentally investigated due to the difficulty in measuring the ε
r of small and thin MgO tunnel barriers. In this study, we measured ε
r for a MgO tunnel barrier in epitaxial stacks and systematically investigated the relationships among ε
r, epitaxial strain, and the VCMA effect. We showed that the MgO tunnel barrier in the epitaxial stacks was subjected to ~1.5% compressive strain and exhibited an enhanced ε
r (>15), which is more than 50% greater than that of bulk MgO. Our results indicate that the compressive strain in the thin MgO tunnel barrier enhances ε
r and thus the VCMA coefficient. Such strain engineering makes simple rocksalt tunnel barriers more attractive for spintronics applications.
AlphaFold prediction of structural ensembles of disordered proteins
Authors: Brotzakis Z. Faidon , Zhang Shengyu , Murtada Mhd Hussein , Vendruscolo Michele 
Published: February 2025

Abstract
Deep learning methods of predicting protein structures have reached an accuracy comparable to that of high-resolution experimental methods. It is thus possible to generate accurate models of the native states of hundreds of millions of proteins. An open question, however, concerns whether these advances can be translated to disordered proteins, which should be represented as structural ensembles because of their heterogeneous and dynamical nature. To address this problem, we introduce the AlphaFold-Metainference method to use AlphaFold-derived distances as structural restraints in molecular dynamics simulations to construct structural ensembles of ordered and disordered proteins. The results obtained using AlphaFold-Metainference illustrate the possibility of making predictions of the conformational properties of disordered proteins using deep learning methods trained on the large structural databases available for folded proteins.
Postoperative outcomes and their risk factors in left pancreatectomy with and without multivisceral resection
Authors: Brunner Maximilian , Loeser Ilvie , Weber Georg F. , Grützmann Robert , Krautz Christian 
Published: February 2025

Abstract
The aim of the present study was to identify risk factors associated with postoperative morbidity and mortality in patients undergoing isolated left pancreatectomy and those undergoing left pancreatic resection as part of a multivisceral resection. We performed a retrospective analysis of 296 adult patients who underwent elective left pancreatectomy from 2005 to 2022 at the University Hospital Erlangen. Patient demographics, pre- and intraoperative findings, along with postoperative outcomes, were collected and tested as predictive factors for various short-term postoperative parameters. Isolated left pancreatectomy (LP) was performed in 173 patients, while 123 patients underwent left pancreatectomy as part of a multivisceral resection (multivisceral LP). Multivisceral LP was associated with a higher rate of major morbidity (27% vs. 17%, p = 0.043) and mortality (7% vs. 2%, p = 0.046) compared to LP. Independent risk factors for major morbidity included the need for intraoperative blood transfusion and oncological lymphadenectomy in the LP group and longer operative time in the multivisceral LP group. CR-POPF was associated with the indication for surgery in the LP group. Independent risk factors for re-surgery included intraoperative blood transfusion in the LP group and ASA III or IV in the multivisceral LP group. Cardiovascular diseases were associated with higher mortality in the LP group, while COPD was the only risk factor for mortality in the multivisceral LP group. Multivisceral left pancreatectomy is associated with worse outcomes compared to isolated left pancreatectomy. In both groups, relevant risk factors predict postoperative complications. Patients with these identified risk factors should receive close monitoring during the postoperative course to anticipate outcomes with an increased risk of complications.
Improving medical machine learning models with generative balancing for equity and excellence
Authors: Theodorou Brandon , Danek Benjamin , Tummala Venkat , Kumar Shivam Pankaj , Malin Bradley , Sun Jimeng 
Published: February 2025

Abstract
Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. Despite attempts, biases in predictions persist, driven by disparities in representation and exacerbated by the scarcity of positive labels, perpetuating health inequities. This paper introduces , a synthetic data generation approach leveraging large language models, to address these issues. enhances algorithmic performance and reduces bias by creating realistic, anonymous synthetic patient data that improves representation and augments dataset patterns while preserving privacy. Through experiments on multiple datasets, we demonstrate that boosts mortality prediction performance across diverse subgroups, achieving up to a 21% improvement in F1 Score without requiring additional data or altering downstream training pipelines. Furthermore, consistently reduces subgroup performance gaps, as shown by universal improvements in performance and fairness metrics across four experimental setups.
Chemical reactivity of RNA and its modifications with hydrazine
Authors: Yeşiltaç-Tosun Nur , Qi Yuyang , Li Chengkang , Stafflinger Helena , Hollnagel Katja , Rusling Leona , Wöhnert Jens , Kaiser Steffen , Kaiser Stefanie 
Published: February 2025

Abstract
RNA modifications are essential for the regulation of cellular processes and have a key role in diseases such as cancer and neurological disorders. A major challenge in the analysis of RNA modification is the differentiation between isomers, including methylated nucleosides as well as uridine and pseudouridine. A solution is their differential chemical reactivity which enables isomer discrimination by mass spectrometry (MS) or sequencing. In this study, we systematically determine the chemical reactivity of hydrazine with RNA and its native modifications in an aniline-free environment. We optimize the conditions to achieve nearly full conversion of all uridines while avoiding RNA cleavage. We apply the conditions to native tRNAPhe which allows discrimination of pseudouridine and uridine by MALDI-MS. Furthermore, we determine the identity of the reaction product of hydrazine with various modified nucleosides using high resolution mass spectrometry and quantify the reaction yield in native tRNA from E. coli and human cells under various hydrazine conditions. Most modified nucleosides react quantitatively at lower hydrazine concentration while uridines do not decompose under these conditions. Thus, this study paves the way to exploit aniline-free hydrazine reactions in the detection of RNA modifications through MS and potentially even long-read RNA sequencing.
SparkGrid: Blockchain Assisted Secure Query Scheduling and Dynamic Risk Assessment for Live Migration of Services in Apache Spark‐Based Grid Environment
Authors: Kiran Gangasandra Mahadevaiah , Nalini Narasimaiah 
Published: February 2025

ABSTRACTGrid computing is an emerging technology that enables the heterogeneous collection of data and provision of services to users. Due to the high amount of incoming heterogeneous requests, grid computing needs efficient scheduling to reduce execution time and satisfy service level agreement (SLA) and quality of service (QoS) requirements. For that purpose, we proposed the SprakGrid method to reduce execution time and satisfy SLA, and QoS requirements. The proposed work includes four consecutive phases which are explained as follows, in first we perform user authentication to ensure the legitimacy of the users using the elliptic curve‐based chaos theory algorithm which generates a secret key and stores it in the blockchain. In the second we perform query scheduling for resource discovery using the soft actor critic algorithm by considering 3P's parameters which is performed by spark environment that schedules optimal resources based on the service request. Third, we perform a risk assessment and request dropping, in which the risk nodes of workers are evaluated by the master node. To address the resource wastage by attackers, this research dynamically evaluates the risk value using Shannon entropy. Based on the risk assessment the requests are classified into two classes such as normal and malicious. Fourth we perform service live migration, in which the malicious requests are dropped and normal requests are migrated from the source node to the target node using multi‐constraints based emperor penguin optimization. Finally, simulation is performed by GridSim and the simulation results demonstrate that the proposed SparkGrid method achieves superior performance compared to other state‐of‐the‐art methods.
A distributed model‐free adaptive voltage control algorithm for distribution systems with extensive integration of photovoltaics
Authors: Tian Baoye , Guo Zhifei , Zhou Baorong , Fan Lijuan , Deng Zhuoming , Zhang Yongjie , You Zuowei , Lin Lingxue 
Published: February 2025

AbstractThe widespread integration of photovoltaics (PVs) presents significant challenges to the operation and control of distribution systems, particularly in maintaining voltage stability at nodes with PV connections. To address these challenges, this paper proposes a voltage control algorithm based on distributed model‐free adaptive control (MFAC). The control objective is to achieve real‐time reactive‐power‐voltage coordination under constraints including PV power output limitations, voltage safety ranges, and the communication network topology. The proposed method estimates dynamic linearization parameters that represent the voltage control characteristics of the distribution systems by utilizing real‐time data from distributed PVs and enabling communication between adjacent nodes. Rather than relying on a precise network model, the algorithm achieves robust voltage control by estimating these parameters from historical and real‐time sampling data, employing a data‐driven approach to iteratively update control strategies. Multi‐scenario simulations of a 32‐bus power system demonstrated the effectiveness and robustness of the algorithm across diverse operating conditions.
5G/6G wave efficient window glass utilising surface mount passive metasurface for enhancing microwave transmission
Authors: Zhang Nana , Geng Ziyang , Ni Yuanliang , Cheng Yangjie , Du Xupan , Shen Yan , Ryu Tominaga , Yin Xuefeng , Luo Yong 
Published: February 2025

AbstractEnergy efficiency is fundamentally concerned in 5G/6G communication systems. Window glass considers mainly thermal energy efficiency, and it does not consider microwave efficiency too much for wireless communications, particularly in the fixed wireless access scenario, where the window glass is the only non‐destructive microwave wireless propagation path between the transmitter outside the house and the signal receiver inside. Regular window glasses induce severe reflections and large penetration loss, resulting in low energy efficiency for 5G/6G communications. This paper provides a new paradigm to obtain the wave efficient window glass with designing the passive and transparent metasurface. Thanks to the glass‐metasurface adjoint model and the ABCD‐field adjoint analysis, it is not only appropriate for known glasses with detailed dimensions, materials etc, but also compatible with unknown pre‐existing glasses such as an encrypted glass model. Moreover, the metasurface design is quite applicable for pre‐existing glasses with surface mounting process, rather than the regular integrated manufacturing process in which new glasses and metasurfaces are designed and manufactured together. Spectral transmission enhancement induced by the proposed metasurface is measured, validating the effectiveness of the proposed method. In addition, surface mount process and the CPE (Customer Premises Equipment) location are discussed for a limited space. Due to the passive, and low carbon design of the metasurface, the wave efficient glass can be easily obtained, and is compatible with the CPE (Customer Premises Equipment) or RIS (Reconfigurable Intelligent Surface) for 5G/6G communications.
A hybrid optimization approach to evaluating load capacity in distribution networks with new energy and energy storage integration
Authors: Zhang Longtian , Wang Delin , Wang Jun , Mastoi Muhammad Shahid , He Zelin , Hassan Mannan 
Published: February 2025

AbstractNew energy can enhance the load capacity of the distribution networks, and the addition of energy storage can suppress the fluctuations caused by the uncertainty of new energy, promoting the stable load absorption of the distribution networks. This paper explored the impact of new energy and energy storage integration into distribution network load‐carrying capacity and proposed a method for evaluating the load‐carrying capacity of the distribution networks by improving GA‐BWO with voltage adaptive control. Under the premise of considering the integration of new energy and energy storage access to the distribution networks, the impact of load increase on the status of the distribution network is derived. Constructing a distribution network load‐carrying capacity evaluation indicator system with safety, flexibility, and economy, then calculating indicator weights using the AHP‐EWM method and building evaluation function. Building a distribution network load carrying capacity model based on objective function and constraint conditions on this basis, utilizing bus voltage to adaptively control the balance factor and development stage of the Beluga algorithm, and introducing the mutation process of the Genetic algorithm, realize the solution of load carrying capacity. Evaluate the distribution networks with new energy and energy storage, for example, prove the improvement effect of new energy and energy storage output characteristics on the load carrying capacity of the distribution networks and provide a theoretical basis for regional planning and construction.
Impact of Hepatic Steatosis, Psoas Muscle Mass, and Density on Outcomes in Patients with Moderately Severe and Severe Acute Pancreatitis: A Serial Computed Tomography-Based Retrospective Study
Authors: Jerath Akhil , Rewari Nishita , Gupta Pankaj , Jearth Vaneet , Singh Anupam , Shah Jimil , Samanta Jayanta , Mandavdhare Harshal , Sharma Vishal , Sinha Saroj K. , Dutta Usha 
Published: February 2025

Abstract
Background and Objective There is limited literature on the association of fatty liver and muscle mass with outcomes of acute pancreatitis (AP) in Indian patients. We aim to investigate the impact of these parameters on clinical outcomes in AP patients based on serial computed tomography (CT) scans.
Materials and Methods Consecutive patients of AP who had a baseline CT scan within 2 weeks of pain onset and a follow-up CT scan within 2 months of initial CT scan were included. Fatty liver, spleen to liver attenuation difference (AD), psoas muscle area (PMA), and psoas muscle attenuation (PMAt) were assessed on baseline and follow-up portal venous CT scans. Their association with the length of hospitalization, intensive care unit (ICU) admission, length of ICU stay, surgery, and mortality were assessed using univariate and multivariate analysis.
Results One hundred and ninety-eight patients (143 [72.2%] males, mean age 37.9 [ ± 12.4] years) were included. The mean interval between the two CT scans was 30 days (± 13.5 days). Twenty-four (12.1%) patients had fatty liver at baseline CT and 58 (29.3%) patients had fatty liver on follow-up CT (p < 0.001). The mean AD at the baseline scan was –10.2 (± 12.3) Hounsfield units (HU) and on follow up was –18.8 (± 21.7) HU (p < 0.001). PMA in baseline CT was 13.9 (± 5.5) mm2 and on follow-up was 11.2 (± 4.6) mm2 (p < 0.001). PMAt on baseline CT was 49.2 (± 8.2) HU and on follow-up was 47.1 (± 12.1) HU (p < 0.001). In multivariate analysis, the PMA and PMAt were significantly associated with the clinical outcomes. There was no association of fatty liver with clinical outcomes. The parameter with the highest area under the curve for predicting clinical outcomes was PMAt at follow-up CT.
Conclusion Psoas muscle-based assessment is associated with clinical outcomes in patients with AP.