bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Fluid Flow‐Based Deep Learning (FFDL) Architecture for Subsurface Flow Systems With Application to Geologic CO2 Storage
Authors: Qin Zhen , Liu Yingxiang , Zheng Fangning , Jafarpour Behnam 
Published: January 2025

AbstractPrediction of the spatial‐temporal dynamics of the fluid flow in complex subsurface systems, such as geologic storage, is typically performed using advanced numerical simulation methods that solve the underlying governing physical equations. However, numerical simulation is computationally demanding and can limit the implementation of standard field management workflows, such as model calibration and optimization. Standard deep learning models, such as RUNET, have recently been proposed to alleviate the computational burden of physics‐based simulation models. Despite their powerful learning capabilities and computational appeal, deep learning models have important limitations, including lack of interpretability, extensive data needs, weak extrapolation capacity, and physical inconsistency that can affect their adoption in practical applications. We develop a Fluid Flow‐based Deep Learning (FFDL) architecture for spatial‐temporal prediction of important state variables in subsurface flow systems. The new architecture consists of a physics‐based encoder to construct physically meaningful latent variables, and a residual‐based processor to predict the evolution of the state variables. It uses physical operators that serve as nonlinear activation functions and imposes the general structure of the fluid flow equations to facilitate its training with data pertaining to the specific subsurface flow application of interest. A comprehensive investigation of FFDL, based on a field‐scale geologic storage model, is used to demonstrate the superior performance of FFDL compared to RUNET as a standard deep learning model. The results show that FFDL outperforms RUNET in terms of prediction accuracy, extrapolation power, and training data needs.
Semi-mechanistic efficacy model for PARP + ATR inhibitors—application to rucaparib and talazoparib in combination with gartisertib in breast cancer PDXs
Authors: Villette Claire C. , Dupuy Nathalie , Brightman Frances A. , Zimmermann Astrid , Lignet Floriane , Zenke Frank T. , Terranova Nadia , Bolleddula Jayaprakasam , El Bawab Samer , Chassagnole Christophe 
Published: January 2025

Abstract

Background
Promising cancer treatments, such as DDR inhibitors, are often challenged by the heterogeneity of responses in clinical trials. The present work aimed to build a computational framework to address those challenges.

Methods
A semi-mechanistic pharmacokinetic-pharmacodynamic model of tumour growth inhibition was developed to investigate the efficacy of PARP and ATR inhibitors as monotherapies, and in combination. Key features of the DNA damage response were incorporated into the model to allow the emergence of synthetic lethality, including redundant DNA repair pathways that may be impaired due to genetic mutations, and due to PARP and ATR inhibition. Model parameters were calibrated using preclinical in vivo data for PARP inhibitors rucaparib and talazoparib and the ATR inhibitor gartisertib.

Results
The model successfully captured the monotherapy efficacies of rucaparib and talazoparib, as well as the combination efficacy with gartisertib. The model was evaluated against multiple tumour xenografts with diverse genetic backgrounds and was able to capture the observed heterogeneity of response profiles.

Conclusions
By enabling simulation of in vivo tumour growth inhibition with PARP and ATR inhibitors for specific tumour types, the model provides a rational approach to support the optimisation of dosing regimens to stratified populations.
Nucleophilicity at copper(-I) in a compound with a Cu–Mg bond
Authors: Jackson Ross A. , Evans Nicholas J. , Babula Dawid J. , Horsley Downie Thomas M. , Charman Rex S. C. , Neale Samuel E. , Mahon Mary F. , Liptrot David J. 
Published: January 2025

Abstract
Copper is ubiquitous as a structural material, and as a reagent in (bio)chemical transformations. A vast number of chemical reactions rely on the near-inevitable preference of copper for positive oxidation states to make useful compounds. Here we show this electronic paradigm can be subverted in a stable compound with a copper-magnesium bond, which conforms to the formal oxidation state of Cu(-I). The Cu-Mg bond is synthesized by the reaction of an N-heterocyclic carbene (NHC) ligated copper alkoxide with a dimeric magnesium(I) compound. Its identity is confirmed by single-crystal X-ray structural analysis and NMR spectroscopy, and computational investigations provide data consistent with a high charge density at copper. The Cu-Mg bond acts as a source of the cupride anion, transferring the NHC-copper fragment to electrophilic s-, p-, and d-block atoms to make known and new copper-containing compounds.
Ferromagnetic Fe-TiO2 spin catalysts for enhanced ammonia electrosynthesis
Authors: Wang Jingnan , Zhao Kaiheng , Yao Yongbin , Xue Fan , Lu Fei , Yan Wensheng , Yuan Fangli , Wang Xi 
Published: January 2025

Abstract
Magnetic field effects (MFE) of ferromagnetic spin electrocatalysts have attracted significant attention due to their potential to enhance catalytic activity under an external magnetic field. However, no ferromagnetic spin catalysts have demonstrated MFE in the electrocatalytic reduction of nitrate for ammonia (NO3RR), a pioneering approach towards NH3 production involving the conversion from diamagnetic NO3
− to paramagnetic NO. Here, we report the ferromagnetic Fe-TiO2 to investigate MFE on NO3RR. Fe-TiO2 possesses a high density of atomically dispersed Fe sites and exhibits an intermediate-spin state, resulting in magnetic ordering through ferromagnetism. Assisted by a magnetic field, Fe-TiO2 achieves a Faradaic efficiency (FE) of up to 97% and an NH3 yield of 24.69 mg mgcat
−
1 at −0.5 V versus reversible hydrogen electrode. Compared to conditions without an external magnetic field, the FE and NH3 yield for Fe-TiO2 under an external magnetic field is increased by ~21.8% and ~ 3.1 times, respectively. In-situ characterization and theoretical calculations show that spin polarization enhances the critical step of NO hydrogenation to NOH by optimizing electron transfer pathways between Fe and NO, significantly boosting NO3RR activity.
A travelable area boundary dataset for visual navigation of field robots
Authors: Zhang Kai , Yuan Xia , Xu Jiachen , Wang Kaiyang , Wu Shiwei , Zhao Chunxia 
Published: January 2025

Abstract
Travelable area boundaries not only constrain the movement of field robots but also indicate alternative guiding routes for dynamic objects. Publicly available road boundary datasets have outlined boundaries by binary segmentation labels. However, hard post-processes have to be done to extract from detected boundaries further semantics including the shapes of the boundaries and guiding routes, which poses challenges to a real-time visual navigation system without detailed prior maps. In addition, boundary detectors suffer from insufficient data collected from complex roads with severe occlusion and of different shapes. In this paper, a travelable area boundary dataset is semi-automatically built. 82.05% of the data is collected from bends, crossroads, T-shape roads and other irregular roads. Novel guiding semantics labels, shape labels and scene complexity labels are assigned to boundaries. With the support of the new dataset, travelable area boundary detectors could be trained, evaluated and fairly compared. The dataset can also be used to train, evaluate or test detectors for the road boundary detection task.
Dataset for developing deep learning models to assess crack width and self-healing progress in concrete
Authors: Jakubowski Jacek , Tomczak Kamil 
Published: January 2025

Abstract
The presented dataset comes from an experimental study on the autogenous self-healing of high-strength concrete and the development of deep learning metasensor for crack width assessment and self-healing evaluation. Concrete specimens were prepared, matured, cracked, and exposed to self-healing. High-resolution scanning of the specimen surface and scale-invariant image processing were performed, multiple grid lines crossing cracks were established, and brightness degree profiles along grid lines were extracted. Then, reference measurements of the crack widths were obtained by an operator. The dataset comprises 19,098 records of brightness profiles, reference measurements, and benchmark measurements by deep learning and analytic models. The source images, stacked and marked with grid lines, are provided. The considerable number of brightness profiles coupled with manual reference measurements make the dataset well suited for developing an image-based deep CNN models or analytic algorithms for assessing crack widths in concrete. The technical validation study explored three factors that affect crack measurement: the specimen position in relation to the scanner, the surface moisture level, and the operator performing manual measurements.
Greater residential greenness is associated with reduced epigenetic aging in adults
Authors: Egorov Andrey I. , Griffin Shannon M. , Klein Jo , Guo Wei , Styles Jennifer N. , Kobylanski Jason , Murphy Mark S. , Sams Elizabeth , Hudgens Edward E. , Wade Timothy J. 
Published: January 2025

Abstract
Potential pathways linking urban green spaces to improved health include relaxation, stress alleviation, and improved immune system functioning. Epigenetic age acceleration (EAA) is a composite biomarker of biological aging based on DNA methylation measurements; it is predictive of morbidity and mortality. This cross-sectional study of 116 adult residents of a metropolitan area in central North Carolina investigated associations between exposure to residential green spaces and EAA using four previously developed epigenetic age formulas. DNA methylation tests of white blood cells were conducted using Illumina MethylationEPIC v1.0 assays. EAA values were calculated as residuals from the linear regression model of epigenetic age on chronological age. Residential greenness was characterized using tree cover, total vegetated land cover, and normalized difference vegetation index (NDVI) data. An interquartile range (IQR) increase in distance-to-residence weighted average greenness within 500 m of residence was consistently associated with a reduced EAA adjusted for sociodemographic covariates, smoking status, white blood cell fractions, and the two-dimensional spline function of geographic coordinates. The reduction in the EAA estimates for the four EAA measures ranged from − 1.0 to − 1.6 years for tree cover, from − 1.2 to − 1.5 years for vegetated land cover, and from − 0.9 to − 1.3 years for the NDVI; 11 of the 12 associations were statistically significant (p < 0.05). This study produced new evidence linking reduced epigenetic aging to greater greenness near residences.
Hypertensive load predicts recovery of renal function for patients undergoing revascularisation for renal artery stenosis
Authors: Edgar Ben , Pearson Rob , Jackson Andrew , Stove Callum , Kasthuri Ram , Hussey Keith , Delles Christian , Geddes Colin , Mark Patrick , Roditi Giles , McCallum Linsay , Kingsmore David B. 
Published: January 2025

Abstract
Renal ischaemia due to renal artery stenosis produces two differing responses - a juxtaglomerular hypertensive response and cortical renal dysfunction. The reversibility of renal impairment is not predictable, and thus renal revascularisation is controversial. This study aims to test the hypothesis that the hypertensive response to renal ischaemia reflects viable renal parenchyma, and thus could be used to predict the recovery in renal function. A retrospective analysis was performed of all patients who had renal revascularisation for renal impairment in a defined geographical area (West of Scotland, population 2.4 million) between 2008 and 2024. Clinical records were used to determine the pre-intervention blood pressure, anti-hypertensive medication load and renal function, and post-intervention outcomes. The Hypertensive Index (HTi), a combined measure of systolic blood pressure and antihypertensive drug load, was used as a measure of pre-intervention hypertensive response. 75 patients had intervention for renal impairment over 15 years (68 endovascular, 7 open). Mean pre-intervention serum creatinine of 323 µmol/L was reduced to 191 umol/L at discharge and 182 µmol/L at 6-month follow-up. Refractory hypertension (HTi > 120) was associated with a significant benefit from revascularisation with improved renal function (p = 0.003) and reduced risk of future dialysis (p = 0.001). Renal impairment with no hypertensive response was highly predictive of the need for future dialysis. The hypertensive index is a good predictor of the impact of renal revascularisation on improving renal function with good outcomes in selected patients, and the absence of this is an indicator of chronic non-reversible renal dysfunction.
Beta oscillations predict the envelope sharpness in a rhythmic beat sequence
Authors: Leske Sabine , Endestad Tor , Volehaugen Vegard , Foldal Maja D. , Blenkmann Alejandro O. , Solbakk Anne-Kristin , Danielsen Anne 
Published: January 2025

Abstract
Periodic sensory inputs entrain oscillatory brain activity, reflecting a neural mechanism that might be fundamental to temporal prediction and perception. Most environmental rhythms and patterns in human behavior, such as walking, dancing, and speech do not, however, display strict isochrony but are instead quasi-periodic. Research has shown that neural tracking of speech is driven by modulations of the amplitude envelope, especially via sharp acoustic edges, which serve as prominent temporal landmarks. In the same vein, research on rhythm processing in music supports the notion that perceptual timing precision varies systematically with the sharpness of acoustic onset edges, conceptualized in the beat bin hypothesis. Increased envelope sharpness induces increased precision in localizing a sound in time. Despite this tight relationship between envelope shape and temporal processing, it is currently unknown how the brain uses predictive information about envelope features to optimize temporal perception. With the current EEG study, we show that the predicted sharpness of the amplitude envelope is encoded by pre-target neural activity in the beta band (15–25 Hz), and has an impact on the temporal perception of target sounds. We used probabilistic sound cues in a timing judgment task to inform participants about the sharpness of the amplitude envelope of an upcoming target sound embedded in a beat sequence. The predictive information about the envelope shape modulated task performance and pre-target beta power. Interestingly, these conditional beta-power modulations correlated positively with behavioral performance in the timing judgment task and with perceptual temporal precision in a click-alignment task. This study provides new insight into the neural processes underlying prediction of the sharpness of the amplitude envelope during beat perception, which modulate the temporal perception of sounds. This finding could reflect a process that is involved in temporal prediction, exerting top-down control on neural entrainment via the prediction of acoustic edges in the auditory stream.
A pediatric emergency prediction model using natural language process in the pediatric emergency department
Authors: Choi Arum , Kim Chohee , Ryoo Jisu , Jeon Jangyeong , Cho Sangyeon , Lee Dongjoon , Kim Junyeong , Lee Changhee , Bae Woori 
Published: January 2025

Abstract
This study developed a predictive model using deep learning (DL) and natural language processing (NLP) to identify emergency cases in pediatric emergency departments. It analyzed 87,759 pediatric cases from a South Korean tertiary hospital (2012–2021) using electronic medical records. Various NLP models, including four machine learning (ML) models with Term Frequency-Inverse Document Frequency (TF-IDF) and two DL models based on the KM-BERT framework, were trained to differentiate emergency cases using clinician transcripts. Gradient Boosting, among the ML models, performed best with an AUROC of 0.715, AUPRC of 0.778, and F1-score of 0.677. DL models, especially the fine-tuned KM-BERT model, showed superior performance, achieving an AUROC of 0.839, AUPRC of 0.879, and F1-score of 0.773. Shapley-based explanations provided insights into model predictions, underlining the potential of these technologies in medical decision-making. This study demonstrates the potential of advanced DL techniques for NLP in emergency medical settings, offering a more precise and efficient approach to managing healthcare resources and improving patient outcomes.
The degree of cross-linking of polyacrylic acid affects the fibrogenicity in rat lungs
Authors: Tomonaga Taisuke , Izumi Hiroto , Nishida Chinatsu , Sato Kazuma , Nakamura Yuiko , Morimoto Toshiki , Higashi Yasuyuki , Wang Ke-Yong , Higashi Hidenori , Kojima Takuma , Sakurai Kazuo , Takeshita Jun-ichi , Moriyama Akihiro , Yamasaki Kei , Yatera Kazuhiro , Morimoto Yasuo 
Published: January 2025

Abstract
Polyacrylic acid (PAA) with different concentrations of cross-linker was instilled into the trachea of rats to examine the effect of PAA crosslink density on lung disorders. Methods: F344 rats were intratracheally exposed to low and high doses of PAA with cross-linker concentrations of 0.1, 1.0, and 5.0% (CL0.1%, CL1.0%, and CL5.0%, respectively). Rats were sacrificed at 3 days, 1 week, 1 month, 3 months, and 6 months after exposure. PAA with different cross-linker concentrations caused an increase in neutrophil influx, cytokine-induced neutrophils, and chemotactic factor (CINC) in bronchoalveolar lavage fluid (BALF) from 3 days to 1 week after instillation. Lactate dehydrogenase (LDH) activity in BALF and heme oxygenase-1 (HO-1) release in lung tissue were higher in the CL0.1% exposure group during the acute phase. Lung histopathological findings also showed that severe fibrotic changes induced by CL0.1% were greater than those observed in CL1.0% and CL5.0% exposure during the observation period. CL0.1% was associated with more severe lung fibrosis, and a decrease in lung fibrosis was observed with increasing cross-linker concentrations, suggesting that the cross-link density of PAA is a physicochemical feature that affects lung disorders.
Extracellular vesicles in seminal plasma of Sahiwal cattle bulls carry a differential abundance of sperm fertility-associated proteins for augmenting the functional quality of low-fertile bull spermatozoa
Authors: Pal Ankit , Karanwal Seema , Habib Mir Ahmad , Josan Fanny , Gaur Vikrant , Patel Aditya , Garg Muskaan , Bhakat Mukesh , Datta Tirtha K. , Kumar Rakesh 
Published: January 2025

Abstract
Poor male fertility significantly affects dairy production, primarily due to low conception rates (CR) in bulls, even when cows are inseminated with morphologically normal sperm. Seminal plasma is a key factor in evaluating the fertilizing ability of bull semen. The extracellular vesicles (EVs) in seminal plasma contain fertility-associated proteins like SPAM1, ADAM7, and SP10, which influence sperm function and fertilizing potential. This study aimed to assess EV-associated fertility proteins in bulls with varying fertility levels and to investigate the effects of seminal plasma EVs (SPEVs) from high-fertility (HF) bulls on the spermatozoa of low-fertility (LF) Sahiwal bulls. Seminal plasma was isolated from the fresh semen of Sahiwal bulls, with four bulls classified as high fertility and three as low fertility. Fertility-associated proteins such as SP10, ADAM7, and SPAM 1 were highly expressed in SPEVs of high-fertility (HF) bulls. PKH26 dye-labeled SPEVs demonstrated significant uptake by spermatozoa at pH 6.8 with ≥ 4 h of co-incubation. Exposure of HF SPEVs to low-fertility (LF) spermatozoa reduced acrosome response, capacitation, and reactive oxygen species (ROS) formation. Our findings suggest that protein repertoires in SPEVs influence sperm activities such as motility, acrosome response, and ROS production. Supplementing LF spermatozoa with HF SPEVs could enhance their functional characteristics, highlighting these proteins as potential resources to modulate cattle bull sperm fertilizing ability.
Cognitive reserve is associated with education, social determinants, and cognitive outcomes among older American Indians in the Strong Heart Study
Authors: Suchy-Dicey Astrid M. , Longstreth W. T. , Buchwald Dedra S. , Rhoads Kristoffer , Grabowski Thomas J. 
Published: January 2025

Abstract
Cognitive reserve, a component of resilience, may be conceptualized as the ability to overcome accumulating neuropathology and maintain healthy aging and function. However, research measuring and evaluating it in American Indians is needed. We recruited American Indians from 3 regional centers for longitudinal examinations (2010-13, n = 818; 2017-19, n = 403) including MRI, cognitive, clinical, and questionnaire data. We defined cognitive reserve by measuring the residual from individual regressions of cognitive tests over imaged brain volumes, adjusted for age and sex. Analyses examined three different metrics of cognitive reserve against sociodemographic, clinical, and longitudinal cognitive data in causal mediation models. Better cognitive reserve was significantly associated with more education, higher income, lower prevalence of depression, lower prevalence of diabetes, and lower prevalence of kidney disease, but we found no statistically significant evidence for an association with plasma biomarkers for Alzheimer’s disease and related dementias, APOE e4 carrier status, alcohol use, body mass, or hypertension. Better cognitive reserve was associated with better cognitive function over mean 6.7 years follow-up (range 4-9 years); and the association for education with cognition over time was mediated in part (15-24%) by cognitive reserve. Cognitive reserve, although challenging to measure, appears important for understanding the range of cognitive aging in American Indians.