bluuebunny/crossref_metadata_2025_split huggingface dataset:
Message in a bottle: Forecasting wine prices
Authors: Algieri Bernardina , Iania Leonardo , Leccadito Arturo , Meloni Giulia 
Published: May 2024

AbstractCan we predict fine wine and alcohol prices? Yes, but it depends on the forecasting horizon. We make this point by considering the Liv-ex Fine Wine 100 and 50 Indices, the retail and wholesale alcohol prices in the United States for the period going from January 1992 to March 2022. We use rich and diverse datasets of economic, survey, and financial variables as potential price drivers and adopt several combination/dimension reduction techniques to extract the most relevant determinants. We build a comprehensive set of models and compare forecast performances across different selling levels and alcohol categories. We show that it is possible to predict fine wine prices for the 2-year horizon and retail/wholesale alcohol prices at horizons ranging from 1 month to 2 years. Our findings stress the importance of including consumer survey data and macroeconomic factors, such as international economic factors and developed markets equity risk factors, to enhance the precision of predictions of retail/wholesale (fine wine) prices.
Entrepreneurial Philanthropy at Cromford, Quarry Bank, and Saltaire Mills during the Industrial Revolution
Authors: Yates David 
Published: May 2024

AbstractThis article offers a spatial examination of entrepreneurial philanthropy at Cromford, Quarry Bank, and Saltaire mills during the industrial revolution. It argues that entrepreneurial philanthropy at these mills, with its new social relations, was influenced by both market competition and philanthropy, to the extent that active welfare provision was dependent on profitable enterprise and creation of wealth. It demonstrates that the extent and nature of philanthropy intended, implemented, and experienced at each of these entrepreneurial projects was determined by site-specific factors with unique effects in space and time. The article builds on existing research into the socially transformative impact of the industrial revolution by developing the concept of philanthropic space to enable a fresh assessment of the relationship between capital and welfare. It suggests that, within these communities, the development of philanthropic space addressed some of the causes and effects of discontent of the working classes associated with the ‘condition-of-England question’. In particular, the discipline of education became an increasingly important component of both enhanced philanthropic development by owners and the experience of workers, offering opportunities for self-improvement. At the same time, discipline and control were ostensibly paradoxical within, yet established and essential features of, philanthropic space.
Assessing two methods of webcam-based eye-tracking for child language research
Authors: Kandel Margaret , Snedeker Jesse 
Published: May 2024

Abstract
We assess the feasibility of conducting web-based eye-tracking experiments with children using two methods of webcam-based eye-tracking: automatic gaze estimation with the WebGazer.js algorithm and hand annotation of gaze direction from recorded webcam videos. Experiment 1 directly compares the two methods in a visual-world language task with five to six year-old children. Experiment 2 more precisely investigates WebGazer.js’ spatiotemporal resolution with four to twelve year-old children in a visual-fixation task. We find that it is possible to conduct web-based eye-tracking experiments with children in both supervised (Experiment 1) and unsupervised (Experiment 2) settings – however, the webcam eye-tracking methods differ in their sensitivity and accuracy. Webcam video annotation is well-suited to detecting fine-grained looking effects relevant to child language researchers. In contrast, WebGazer.js gaze estimates appear noisier and less temporally precise. We discuss the advantages and disadvantages of each method and provide recommendations for researchers conducting child eye-tracking studies online.
Early childhood trauma exposure and neurocognitive and emotional processes: Associations in young children in a partial hospital program
Authors: Huffhines Lindsay , Parade Stephanie H. , Martin Sarah E. , Gottipaty Anjali , Kavanaugh Brian , Spirito Anthony , Boekamp John R. 
Published: May 2024

Abstract
Early childhood trauma has been linked to neurocognitive and emotional processing deficits in older children, yet much less is known about these associations in young children. Early childhood is an important developmental period in which to examine relations between trauma and executive functioning/emotion reactivity, given that these capacities are rapidly developing and are potential transdiagnostic factors implicated in the development of psychopathology. This cross-sectional study examined associations between cumulative trauma, interpersonal trauma, and components of executive functioning, episodic memory, and emotion reactivity, conceptualized using the RDoC framework and assessed with observational and performance-based measures, in a sample of 90 children (ages 4–7) admitted to a partial hospital program. Children who had experienced two or more categories of trauma had lower scores in episodic memory, global cognition, and inhibitory control as measured in a relational (but not computerized) task, when compared to children with less or no trauma. Interpersonal trauma was similarly associated with global cognition and relational inhibitory control. Family contextual factors did not moderate associations. Findings support examining inhibitory control in both relationally significant and decontextualized paradigms in early childhood, and underscore the importance of investigating multiple neurocognitive and emotional processes simultaneously to identify potential targets for early intervention.
GNET Derived Mass Balance and Glacial Isostatic Adjustment Constraints for Greenland
Authors: Barletta Valentina R. , Bordoni Andrea , Khan Shfaqat Abbas 
Published: May 2024

AbstractMonitoring the Greenland mass balance (GMB) is crucial in the context of global sea level rise. Currently, three main methods are used to measure GMB, with the primary source of uncertainty arising from the glacial isostatic adjustment (GIA) contribution. Here, we propose a novel approach based on a simple methodology that uses the entire Greenland GNSS network (GNET) as an instrument to monitor the present‐day mass changes. Our method is validated against GRACE‐derived GMB, and we find a very good agreement. This leads to an independent methodology for estimating present‐day mass changes from GNSS, bridging the gap between GRACE and GRACE‐FO in GMB estimates. Through a combined analysis of GMB from GRACE and GNET, we identify a consistency relation between the gravity and uplift signature of GIA, providing a new robust constraint for GIA models.
Magnetosheath Ion Field‐Aligned Asymmetry and Implications for Ion Leakage to the Foreshock
Authors: Liu Terry Zixu , Angelopoulos Vassilis , Zhang Hui , Vu Andrew , Raeder Joachim 
Published: May 2024

AbstractThe ion foreshock is highly dynamic, disturbing the bow shock and the magnetosphere‐ionosphere system. To forecast foreshock‐driven space weather effects, it is necessary to model foreshock ions as a function of upstream shock parameters. Case studies in the accompanying paper show that magnetosheath ions sometimes exhibit strong field‐aligned asymmetry toward the upstream direction, which may be responsible for enhancing magnetosheath leakage and therefore foreshock ion density. To understand the conditions leading to such asymmetry and the potential for enhanced leakage, we perform case studies and a statistical study of magnetosheath and foreshock region data surrounding ∼500 Time History of Events and Macroscale Interactions during Substorms mission bow shock crossings. We quantify the asymmetry using the heat flux along the field‐aligned direction. We show that the strong field‐aligned heat flux persists across the entire magnetosheath from the magnetopause to the bow shock. Ion distribution functions reveal that the strong heat flux is caused by a secondary thermal population. We find that stronger asymmetry events exhibit heat flux preferentially toward the upstream direction near the bow shock and occur under larger IMF strength and larger solar wind dynamic pressure and/or energy flux. Additionally, we show that near the bow shock, magnetosheath leakage is a significant contributor to foreshock ions, and through enhancing the leakage the magnetosheath ion asymmetry can modulate the foreshock ion velocity and density. Our results imply that likely due to field line draping and compression against the magnetopause that leads to a directional mirror force, modeling the foreshock ions necessitates a more global accounting of downstream conditions.
Biophysical Drivers of Seasonal Hysteresis of Urban Heat Islands Across Climates and Urban Landscapes
Authors: Li Congyuan , Zhang Ning , Ren Kaijun , Zhao Wenjing , Wu Jianping , Sun Yong 
Published: May 2024

AbstractThe phenomenon of seasonal hysteresis between urban heat islands (UHIs) and background surface temperature was reported in many studies, but a unifying explanation for the causes of its magnitude, shape and looping direction remained less clear, and the impacts of urban landscapes and background climate on such hysteresis were also the subject of enquiry. Here we performed a systematic study based on a long‐term offline simulation for surface energy budgets, surface air and skin temperature of the urban‐biosphere system in East China. It was carried out with an up‐to‐date land surface model — the CLM5‐LCZs (the Community Land Model version 5 (CLM5) coupled with a newly developed urban canopy model representing diverse urban landscapes with the local climate zones classification scheme). To isolate the causes of UHIs hysteresis, a simplified framework was constructed by combining a mathematical representation of grid/subgrid model outputs, the two‐resistance mechanism method and the time‐lagged cross correlation analysis. The results exhibited distinct hysteresis patterns of UHIs such as twisted, concave‐down, concave‐up and convex‐up curve across diverse background climates and urban landscapes. The basic shapes of hysteresis depict a gradual transition from concave/convex‐up to concave/convex‐down by characterized by a larger winter UHIs from a wetter and warmer climate to a drier and colder climate. Magnitude and seasonality of surface UHIs are separately dominated by the urban‐rural contrast of evapotranspiration and heat storage at daytime and nighttime, whereas across‐climate variations of daytime and nighttime surface UHIs hysteresis are regulated by the phase shift of convection efficiency and anthropogenic heat. Urban landscapes affect the hysteresis mainly by altering the amplitude rather than the shape of looping curves. Our work could provide a fuller picture of how to mitigate urban warming considering inter‐seasonal tradeoffs over a broader region.
Generative Adversarial Network for Real‐Time Flash Drought Monitoring: A Deep Learning Study
Authors: Foroumandi Ehsan , Gavahi Keyhan , Moradkhani Hamid 
Published: May 2024

AbstractDroughts are among the most devastating natural hazards, occurring in all regions with different climate conditions. The impacts of droughts result in significant damages annually around the world. While drought is generally described as a slow‐developing hazardous event, a rapidly developing type of drought, the so‐called flash drought has been revealed by recent studies. The rapid onset and strong intensity of flash droughts require accurate real‐time monitoring. Addressing this issue, a Generative Adversarial Network (GAN) is developed in this study to monitor flash droughts over the Contiguous United States (CONUS). GAN contains two models: (a) discriminator and (b) generator. The developed architecture in this study employs a Markovian discriminator, which emphasizes the spatial dependencies, with a modified U‐Net generator, tuned for optimal performance. To determine the best loss function for the generator, four different networks are developed with different loss functions, including Mean Absolute Error (MAE), adversarial loss, a combination of adversarial loss with Mean Square Error (MSE), and a combination of adversarial loss with MAE. Utilizing daily datasets collected from NLDAS‐2 and Standardized Soil Moisture Index (SSI) maps, the network is trained for real‐time daily SSI monitoring. Comparative assessments reveal the proposed GAN's superior ability to replicate SSI values over U‐Net and Naïve models. Evaluation metrics further underscore that the developed GAN successfully identifies both fine‐ and coarse‐scale spatial drought patterns and abrupt changes in the SSI temporal patterns that is important for flash drought identification.
Microtomographic Measurements of Total Air‐Water Interfacial Areas for Soils
Authors: Brusseau Mark L. , Araujo Juliana B. , Narter Matt , Marble Justin C. , Bigler Matt 
Published: May 2024

AbstractSynchrotron X‐ray microtomography (XMT) was used to measure total air‐water interfacial areas (Aaw) as a function of water saturation (Sw) for several soils that comprise a range of physical and geochemical properties. Measurements were also conducted for glass beads and quartz sands for comparison. Apparent near‐linear Aaw‐Sw relationships are observed for the three sands and the three sandy soils. In contrast, the measured interfacial areas for two soils that contain greater proportions of silt and clay are strongly nonlinear functions of water saturation. The greater degree of nonlinearity observed for these two soils is due to their much greater particle‐size distributions (i.e., uniformity coefficients) and their concomitant greater range in pore sizes. Interfacial areas determined with the thermodynamic method were used to benchmark the XMT measurements. XMT‐measured interfacial areas compare well to the thermodynamic‐determined values for the sands and sandy soils. In contrast, the XMT‐measured interfacial areas for the two soils with larger particle‐size distributions are not fully congruent with the thermodynamic‐determined values. Both of these soils have large fractions of pore space comprising nominal pore diameters smaller than the resolution of the XMT imaging. These results suggest that air‐water interfacial area may not always be fully characterized by standard XMT for soils with large particle‐size distributions.
A head-mounted photoacoustic fiberscope for hemodynamic imaging in mobile mice
Authors: Zheng Xiaoyan , Na Shuai 
Published: May 2024

AbstractA miniaturized photoacoustic fiberscope has been developed, featuring a lateral resolution of 9 microns and a lightweight design at 4.5 grams. Engineered to capture hemodynamic processes at single-blood-vessel resolution at a rate of 0.2 Hz, this device represents an advancement in head-mounted tools for exploring intricate brain activities in mobile animals.
Mechanisms of ligand recognition and activation of melanin-concentrating hormone receptors
Authors: He Qian , Yuan Qingning , Shan Hong , Wu Canrong , Gu Yimin , Wu Kai , Hu Wen , Zhang Yumu , He Xinheng , Xu H. Eric , Zhao Li-Hua 
Published: May 2024

AbstractMelanin-concentrating hormone (MCH) is a cyclic neuropeptide that regulates food intake, energy balance, and other physiological functions by stimulating MCHR1 and MCHR2 receptors, both of which are class A G protein-coupled receptors. MCHR1 predominately couples to inhibitory G protein, Gi/o, and MCHR2 can only couple to Gq/11. Here we present cryo-electron microscopy structures of MCH-activated MCHR1 with Gi and MCH-activated MCHR2 with Gq at the global resolutions of 3.01 Å and 2.40 Å, respectively. These structures reveal that MCH adopts a consistent cysteine-mediated hairpin loop configuration when bound to both receptors. A central arginine from the LGRVY core motif between the two cysteines of MCH penetrates deeply into the transmembrane pocket, triggering receptor activation. Integrated with mutational and functional insights, our findings elucidate the molecular underpinnings of ligand recognition and MCH receptor activation and offer a structural foundation for targeted drug design.
Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set
Authors: Owen Cameron J. , Torrisi Steven B. , Xie Yu , Batzner Simon , Bystrom Kyle , Coulter Jennifer , Musaelian Albert , Sun Lixin , Kozinsky Boris 
Published: May 2024

AbstractThis work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.
Pretraining of attention-based deep learning potential model for molecular simulation
Authors: Zhang Duo , Bi Hangrui , Dai Fu-Zhi , Jiang Wanrun , Liu Xinzijian , Zhang Linfeng , Wang Han 
Published: May 2024

AbstractMachine learning-assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a model that can be pretrained on all available data and finetuned on downstream tasks with a small additional effort would bring the field to a new stage. Here we propose DPA-1, a Deep Potential model with a gated attention mechanism, which is highly effective for representing the conformation and chemical spaces of atomic systems and learning the PES. We tested DPA-1 on a number of systems and observed superior performance compared with existing benchmarks. When pretrained on large-scale datasets containing 56 elements, DPA-1 can be successfully applied to various downstream tasks with a great improvement of sample efficiency. Surprisingly, for different elements, the learned type embedding parameters form a spiral in the latent space and have a natural correspondence with their positions on the periodic table, showing interesting interpretability of the pretrained DPA-1 model.
Compositional design and phase formation capability of high-entropy rare-earth disilicates from machine learning and decision fusion
Authors: Fan Yun , Bai Yuelei , Li Qian , Lu Zhiyao , Chen Dong , Liu Yuchen , Li Wenxian , Liu Bin 
Published: May 2024

AbstractA key strategy for designing environmental barrier coatings is to incorporate multiple rare-earth (RE) components into β- and γ-RE2Si2O7 to achieve multifunctional performance optimization. However, the polymorphic phase presents significant challenges for the design of multicomponent RE disilicates. Here, employing decision fusion, a machine learning (ML) method is crafted to identify multicomponent RE disilicates, showcasing notable accuracy in prediction. The well-trained ML models evaluated the phase formation capability of 117 (RE10.25RE20.25Yb0.25Lu0.25)2Si2O7 and (RE11/6RE21/6RE31/6Gd1/6Yb1/6Lu1/6)2Si2O7, which are unreported in experiments and validated by first-principles calculations. Utilizing model visualization, essential factors governing the formation of (RE10.25RE20.25Yb0.25Lu0.25)2Si2O7 are pinpointed, including the average radius of RE3+ and variations in different RE3+ combinations. On the other hand, (RE11/6RE21/6RE31/6Gd1/6Yb1/6Lu1/6)2Si2O7 must take into account the average mass and the electronegativity deviation of RE3+. This work combines material-oriented ML methods with formation mechanisms of multicomponent RE disilicates, enabling the efficient design of superior materials with exceptional properties for the application of environmental barrier coatings.
Genetic variation and pesticide exposure influence blood DNA methylation signatures in females with early-stage Parkinson’s disease
Authors: Schaffner S. L. , Casazza W. , Artaud F. , Konwar C. , Merrill S. M. , Domenighetti C. , Schulze-Hentrich J. M. , Lesage S. , Brice A. , Corvol J. C. , Mostafavi S. , Dennis J. K. , Elbaz A. , Kobor M. S. ,   DIGPD Study Group
Published: May 2024

AbstractAlthough sex, genetics, and exposures can individually influence risk for sporadic Parkinson’s disease (PD), the joint contributions of these factors to the epigenetic etiology of PD have not been comprehensively assessed. Here, we profiled sex-stratified genome-wide blood DNAm patterns, SNP genotype, and pesticide exposure in agricultural workers (71 early-stage PD cases, 147 controls) and explored replication in three independent samples of varying demographics (n = 218, 222, and 872). Using a region-based approach, we found more associations of blood DNAm with PD in females (69 regions) than in males (2 regions, Δβadj| ≥0.03, padj ≤ 0.05). For 48 regions in females, models including genotype or genotype and pesticide exposure substantially improved in explaining interindividual variation in DNAm (padj ≤ 0.05), and accounting for these variables decreased the estimated effect of PD on DNAm. The results suggested that genotype, and to a lesser degree, genotype-exposure interactions contributed to variation in PD-associated DNAm. Our findings should be further explored in larger study populations and in experimental systems, preferably with precise measures of exposure.