bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Generalization of Genetic Programming for High-Dimensional Symbolic Regression with Shapley Value Based Feature Selection
Authors: Wang Chunyu , Chen Qi , Xue Bing , Zhang Mengjie 
Published: December 2024

AbstractSymbolic Regression (SR) on high-dimensional datasets often encounters significant challenges, resulting in models with poor generalization capabilities. While feature selection has the potential to enhance the generalization and learning performance in general, its application in Genetic Programming (GP) for high-dimensional SR remains a complex problem. Originating from game theory, the Shapley value is applied to additive feature attribution approaches where it distributes the difference between a model output and a baseline average across input variables. By providing an accurate assessment of each feature importance, the Shapley value offers a robust approach to select features. In this paper, we propose a novel feature selection method leveraging the Shapley value to identify and select important features in GP for high-dimensional SR. Through a series of experiments conducted on ten high-dimensional regression datasets, the results indicate that our algorithm surpasses standard GP and other GP-based feature selection methods in terms of learning and generalization performance on most datasets. Further analysis reveals that our algorithm generates more compact models, focusing on the inclusion of important features.
Beyond Juul: The New Face of Underage Nicotine Addiction - A Survey of College Students
Authors: Riggs Griffin , Church Terry David 
Published: December 2024

Abstract
Background
Youth nicotine addiction is a major public health concern in the United States. Disposable Electronic Nicotine Delivery Systems (ENDS), or disposable vapes, are commonly sought out by youth despite not having received premarket authorization from the FDA. The objective of this study was to identify factors contributing to underage consumption of disposable ENDS.

Methods
An anonymous survey was deployed to college students to understand young adults’ perceptions and patterns of use of disposable ENDS.

Results
Disposable ENDS are very popular among youth. The results of this study revealed the popular brands, flavors, modes of access, and attractive aspects of disposable ENDS. Survey results combined with information from the literature reveal that disposable ENDS gained popularity in the years following the decline in the popularity of pod-based ENDS, such as JUUL, following strict regulatory action from the FDA.

Conclusion
To ultimately address underage nicotine addiction, the FDA must hold disposable ENDS to the same regulatory standards as other tobacco products and produce regulations specifically targeted at disposable ENDS. The results of this study emphasize the importance of making effective regulatory reform and functional educational resources to prevent young people from initiating the use of disposable ENDS.
Prolonged Storage of Bound Organic Carbon in Wetland but Not Upland Soils: A 13C and 14C Perspective
Authors: Ma Tian , Wang Yiyun , Dai Guohua , Jia Juan , Liu Zongguang , Jia Yufu , Wang Simin , Zhu Erxiong , Zhang Xinying , Haghipour Negar , Wacker Lukas , Jia Bingrui , He Jin‐Sheng , Zhang Hailong , Zhao Meixun , Eglinton Timothy I. , Feng Xiaojuan 
Published: December 2024

AbstractProtection by metal (hydr) oxides is one of the key mechanisms for the long‐term stabilization of soil organic carbon (SOC). However, the source and turnover of (metal‐) bound organic carbon (OC) in soils are poorly constrained. Here we present the first large‐scale study on the 13C and 14C characteristics of bound OC in 15 wetland and upland soil profiles. We find that bound OC has similar δ13C as SOC, suggesting no preference for plant‐ or microbe‐derived carbon. However, bound OC Δ14C is more negative than SOC in wetland but not upland mineral soils, and decreases with increasing reactive minerals. Hence, in contrast to the conventional assumption, bound OC is better preserved relative to SOC in wetlands with high contents of reactive metals. Our finding highlights the dynamic exchange of bound OC with SOC in upland soils and calls for a better recognition of reactive metals in stabilizing OC in wetlands.
Higher‐Order Gravity Waves and Traveling Ionospheric Disturbances From the Polar Vortex Jet on 11–15 January 2016: Modeling With HIAMCM‐SAMI3 and Comparison With Observations in the Thermosphere and Ionosphere
Authors: Vadas Sharon L. , Themens David R. , Huba Joseph D. , Becker Erich , Bossert Katrina , Goncharenko Larisa , Maguire Sophie J. , Figueiredo Cosme A. O. B. , Xu Shuang , Harvey V. Lynn , Frissell Nathaniel A. , Molzen Michael J. , Pisano Thomas J. , Nykiel Grzegorz 
Published: December 2024

AbstractIn Vadas et al. (2024, https://doi.org/10.1029/2024ja032521), we modeled the atmospheric gravity waves (GWs) during 11–14 January 2016 using the HIAMCM, and found that the polar vortex jet generates medium to large‐scale, higher‐order GWs in the thermosphere. In this paper, we model the traveling ionospheric disturbances (TIDs) generated by these GWs using the HIAMCM‐SAMI3 and compare with ionospheric observations from ground‐based Global Navigation Satellite System (GNSS) receivers, Incoherent Scatter Radars (ISR) and the Super Dual Auroral Radar Network (SuperDARN). We find that medium to large‐scale TIDs are generated worldwide by the higher‐order GWs from this event. Many of the TIDs over Europe and Asia have concentric ring/arc‐like structure, and most of those over North/South America have planar wave structure and occur during the daytime. Those over North/South America propagate southward and are generated by higher‐order GWs from Europe/Asia which propagate over the Arctic. These latter TIDs can be misidentified as arising from geomagnetic forcing. We find that the higher‐order GWs that propagate to Africa and Brazil from Europe may aid in the formation of equatorial plasma bubbles (EPBs) there. We find that the simulated GWs, TIDs and EPBs agree with EISCAT, PFISR, GNSS, and SuperDARN measurements. We find that the higher‐order GWs are concentrated at N at 200 km, in agreement with GOCE and CHAMP data. Thus the polar vortex jet is important for generating TIDs in the northern winter ionosphere via multi‐step vertical coupling through GWs.
Extracting Site Effects From P‐wave spectra: Application of Cluster‐Event Method 2 (CEM2) in the Tohoku Region, Japan
Authors: Jian Pei‐Ru , Kuo Ban‐Yuan 
Published: December 2024

AbstractTheories related to the Earth's attenuation effect and earthquake source properties predict a similar spectral falloff of body waves, creating severe trade‐off problems when determining these two processes from waveform spectra. Previous efforts attempted to suppress this trade‐off by either applying an empirical Green's function or conducting linear inversion with a specially designed event–station configuration. However, both approaches encounter difficulties when dealing with large datasets or site effect contamination. In this study, we modify a previously used cluster‐event method (CEM), combining both the spectral amplitude and the spectral ratio of the P‐waves for the clustering of events (CEM2); we then apply CEM2 to the High‐Sensitivity Seismograph Network data in the Tohoku region of Japan. An initial inversion with CEM2 yields the first estimates of the source and path parameters, that is, the corner frequency (fc) and the quality factor (Q). The residuals of this inversion demonstrate distinct spectral characteristics that are well correlated with vertical‐to‐horizontal (V/H) spectral ratios of the P‐coda waves at each station, suggesting that they represent a form of site response unaccounted for by theoretical predictions of Q and fc. After removing this particular site response, the second inversion yields an improved determination of Q. We hypothesize that this site effect is dominated by P to SV conversion upon P‐wave arrival and develops and amplifies toward the coda waves. Furthermore, the site effect demonstrates systematic regional characteristics, some of which correlate well with those derived from the V/H spectral ratios of the P‐coda waves.
Operational Capability of Drone‐Based Meteorological Profiling in an Urban Area
Authors: Inoue Jun , Seko Hiromu , Sato Kazutoshi , Sakai Tetsu 
Published: December 2024

AbstractDuring the Uncrewed Aircraft Systems Demonstration Campaign (UAS‐DC), led by the World Meteorological Organization (WMO), twice‐daily meteorological profiling was conducted for 2 months at the Meteorological Research Institute in Tsukuba City (Japan), which is identified as a densely inhabited district. This campaign was instigated to assess the feasibility of obtaining continuous daily measurements for the long term (over a period of more than 1 month), to distribute the data in a format designated for numerical weather prediction, and to evaluate data quality compared to conventional meteorological data. Three types of uncrewed aircraft systems were utilized, that is, a meteorological medium‐sized hexacopter and medium‐ and small‐sized commercial drones with meteorological sensors attached. The maximum flight height was limited to 900 m above ground level owing to airspace regulations around the observation site. Compared with routine radiosonde data, the bias of air temperature, relative humidity, and wind speed measurements was less than 0.3 K, 1.5%, and 0.6 m , respectively, thereby meeting WMO requirements. Moreover, data transfer to the WMO‐prepared repository was completed within 30 min after measurement acquisition. Based on user experience, several aspects regarding the UAS‐DC campaign were discussed from the perspective of sustainable operation and atmospheric boundary layer research.
Oblique Impact Adjacent to Chang'E−5 Sampling Site: Fine‐Scale Analysis and Implication on the Provenance of Returned Samples
Authors: Wu Wenhui , Ren Xin , Chen Zhaopeng , Zhang Peng , Liu Dawei , Zeng Xingguo , Chen Yuan , Chen Wangli , Yan Wei , Liu Bin , Zhang Xiaoxia , Liu Jianjun 
Published: December 2024

AbstractImpact ejecta is a major source of lunar regolith. Symmetric ejecta thickness models are widely used to estimate ejecta distribution. However, they cannot accurately describe the asymmetric distributions from oblique impacts. Here, the Xu Guangqi crater provides an example for the study of oblique impacts. High‐resolution data from this crater, acquired during the Chang'E−5 mission, has facilitated studies of a potential oblique impact, the development of a correction model for asymmetric ejecta distribution, and a detailed analysis of regolith provenance at the sampling site. The results show that the Chang'E−5 returned samples mainly originate from the Xu Guangqi crater formed by an oblique impact at 25°–45°, and its corrected ejecta thickness at the sampling site is about 80 cm, an increase of about 30% over the estimate from the original symmetric ejecta thickness model. Within the uppermost 5 cm, the Chang'E−5 returned regolith is modeled to consist mainly of Xu Guangqi ejecta (∼99%) and a small number of local materials (∼1%), but both are similar in composition composed of local mare basalts. Although small quantities (∼0.7%) of nonlocal mare components from Sharp B, Copernicus, Harpalus, and Aristarchus occur at the bottom of the drilled samples (80–90 cm), the samples are still dominated by Xu Guangqi ejecta (∼88%) and local materials (∼11%). Our study demonstrates the possible effect of an oblique impact to be considered when discussing the sample provenance for a lunar sample returning mission.
Ratio of River Channel Bar to Bank Height Sets Bank Erosion Rate
Authors: Inoue Takuya , Hiramatsu Yuki , Johnson Joel P. L. , Dempo Junya , Mishra Jagriti 
Published: December 2024

AbstractRiver channel changes during floods, including bank erosion and bar deposition, are difficult to predict but important for infrastructure, river management, and riparian zone health. Upstream dams can also drive disequilibrium changes to channel morphology, potentially changing bar and bank susceptibility to flooding. To understand feedback between bar morphology, flood flow, bank erosion and channel cross‐sectional evolution, we (a) evaluate how bank erosion during natural floods in six gravel‐bed rivers with alternate and/or mid‐channel bars varied with bar and bank height, and (b) conduct laboratory experiments scaled to the Chubetsu River in Japan, a pseudo‐meandering gravel‐bed river that has experienced bank erosion influenced by alternate bars. The field data show a strong correlation between bank erosion during floods and the bar to bank height ratio measured before the respective floods. We also find that rivers with upstream dams tend to have higher bar to bank height ratios. In the experiments, we systematically vary flood discharge, initial bar height, and initial bank height, and measure bank erosion and bar evolution. We experimentally find that bank erosion initially increases with bar height and flood discharge. As bar height evolves, bank erosion rates tend to converge under different initial conditions. Bank erosion rate increases with decreasing bank height. Because bars in natural rivers tend to not be adjusted to the largest floods, our experimental results and field data suggest that surveyed ratios of bar height to bank height could be used to infer relative bank erosion risks prior to large floods.
Deep Learning‐Based Approach for Enhancing Streamflow Prediction in Watersheds With Aggregated and Intermittent Observations
Authors: Mangukiya Nikunj K. , Sharma Ashutosh 
Published: December 2024

AbstractAccurate daily streamflow estimates are crucial for water resources management. Yet, many regions lack high‐temporal‐resolution data due to limited monitoring infrastructure, often relying on monthly aggregates or intermittent observations. Predicting streamflow in these sparsely sampled watersheds remains challenging. This study proposes a deep learning‐based approach using Long Short‐Term Memory, leveraging its inherent advantages in learning long‐term dependencies within hydrological variables and processes to enhance streamflow predictions in sparsely sampled watersheds. The approach was evaluated for simulating daily flow patterns from monthly aggregated and monthly or weekly intermittent observations in two contrasting hydrological settings: near‐natural and human‐influenced watersheds. Results showed that the proposed approach reliably predicts daily flows from monthly aggregates with a median Nash‐Sutcliffe efficiency (NSE) of 0.61 for near‐natural and 0.48 for human‐influenced watersheds. The proposed approach performed even better for daily flow predictions from monthly or weekly intermittent observation, achieving a median NSE of 0.70 and 0.55 for near‐natural and human‐influenced watersheds, respectively. The proposed approach remained robust across different seasons and hydrological regimes, with a median percentage bias of ±5%, except in arid regions. Moreover, data sensitivity analysis indicated that data from wet seasons were crucial for improving model predictions and that weekly data could yield results comparable to daily observations. Overall, this study demonstrates that the deep learning‐based approach offers a robust and accurate representation of daily streamflow patterns from aggregated or intermittent observations, providing valuable hydrological insights and promising solutions for improving water resource management in regions with limited monitoring infrastructures.
Modelling Infiltration Based on Source‐Responsive Method for Improving Simulation of Rapid Subsurface Stormflow
Authors: Shen Xuhui , Liu Jintao , Han Xiaole , Yang Hai , Liu Hu , Ni Feiyu 
Published: December 2024

AbstractIn humid hilly regions, macropore preferential flow in soils dominates the distribution of event water, thereby influencing the generation and development of runoff. However, the mechanism of how soil functions on macropore drainage and matrix absorption remains poorly understood due to complex soil water dynamics in a multi‐porosity subsurface network. In this study, based on the source‐responsive method that divides the soil into source‐responsive and diffusive domains, the allocation ratio of infiltrated water in macropores recharging the matrix were derived and it was coupled with PIHM (Penn State Integrated Hydrologic Model) as PIHM‐SRM (PS). By simulating the soil moisture process at profile scale and the runoff process at catchment scale, it was found that the PS overcame the difficulty of most hydrologic models in describing the process of replenishing moisture in dry soil. This leads to more satisfactory performance for flood peaks at the outlet (CCC > 0.84) and soil moisture peaks at three profiles (CCC = 0.97) compared to original PIHM models. Moreover, the separate channel of film flow in the PS further improves the simulation accuracy of peak response speed in subsurface floods under rainstorms (TP > 40 mm). Additionally, sensitivity analysis shows that the storage‐discharge capacity of soil profiles dominates torrential flood forecasting in humid headwaters when considering the influence of macropores. Finally, considering the parameter‐predictive property in the PS, field‐based parameterized strategies are vital for distributed catchment modeling. This will enable the PS to improve flash torrent predictions in headwaters and be applied at catchment scales.
Developing Storylines of Plausible Future Streamflow and Generating a New Warming‐Driven Declining Streamflow Ensemble: Colorado River Case Study
Authors: Salehabadi Homa , Tarboton David G. , Wheeler Kevin , Prairie James , Smith Rebecca , Baker Sarah 
Published: December 2024

AbstractPlausible future streamflow time series are essential for evaluating policies and management strategies in river basins and testing the operation of water resource systems. Relying solely on stationary historical data is not sufficient in a changing climate. However, uncertainty in the range of streamflow projections from General Circulation Models calls into question their direct use in water resources planning. An intermediate approach is needed to identify ensembles of streamflow time series based on well‐defined assumptions that represent plausible future hydrologic conditions. This paper suggests multiple quantitative storylines of plausible future conditions, each matched with a representative streamflow ensemble to serve as inputs for planning models where, to account for uncertainty, plans or policies that are robust to a range of plausible futures are developed. Applying this approach in the Colorado River Basin we found that, while three storylines were well matched with existing ensembles, there was no suitable ensemble representing increasing variability around a declining mean. To address this gap, we developed a general method to create new streamflow ensembles that account for future changes by combining observed and paleo‐reconstructed flows and adjusting the marginal distribution of the streamflow time series to incorporate the estimated decline in, and increasing variability of, future flow. The results are a set of quantitative storylines that justify a range of plausible future conditions, and a new warming‐driven declining streamflow ensemble for use in Colorado River Basin scenario evaluation and decision‐making representing the plausible increasing variability around a declining mean storyline.
Parameter-efficient fine-tuning of large language models using semantic knowledge tuning
Authors: Prottasha Nusrat Jahan , Mahmud Asif , Sobuj Md. Shohanur Islam , Bhat Prakash , Kowsher Md , Yousefi Niloofar , Garibay Ozlem Ozmen 
Published: December 2024

AbstractLarge Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning and require extensive training for best performance, often falling short. In this context, we propose a novel method called Semantic Knowledge Tuning (SK-Tuning) for prompt and prefix tuning that employs meaningful words instead of random tokens. This method involves using a fixed LLM to understand and process the semantic content of the prompt through zero-shot capabilities. Following this, it integrates the processed prompt with the input text to improve the model’s performance on particular tasks. Our experimental results show that SK-Tuning exhibits faster training times, fewer parameters, and superior performance on tasks such as text classification and understanding compared to other tuning methods. This approach offers a promising method for optimizing the efficiency and effectiveness of LLMs in processing language tasks.
Effect of bed clay on surface water-wave reconstruction from ripples
Authors: Malarkey Jonathan , Pollard Ellen M. , Fernández Roberto , Wu Xuxu , Baas Jaco H. , Parsons Daniel R. 
Published: December 2024

AbstractWave ripples can provide valuable information on their formative hydrodynamic conditions in past subaqueous environments by inverting dimension predictors. However, these inversions do not usually take the mixed non-cohesive/cohesive nature of sediment beds into account. Recent experiments involving sand–kaolinite mixtures have demonstrated that wave-ripple dimensions and the threshold of motion are affected by bed clay content. Here, a clean-sand method to determine wave climate from orbital ripple wavelength has been adapted to include the effect of clay and a consistent shear-stress threshold parameterisation. From present-day examples with known wave conditions, the results show that the largest clay effect occurs for coarse sand with median grain diameters over 0.45 mm. For a 7.4% volumetric clay concentration, the range of possible water-surface wavelengths and water depths can be reduced significantly, by factors of three and four compared to clean sand, indicating that neglecting clay when present will underestimate the wave climate.
Outdoor nitrogen dioxide exposure and longitudinal health status trajectory in the Canadian National Population Health Survey
Authors: Stieb David M. , Chen Li , Hystad Perry , Rittmaster Robyn , Lavigne Eric 
Published: December 2024

AbstractFew studies have examined the association between air pollution and the trajectory of global health status measures related to the functional impacts of chronic disease. To address this gap, we examined the trajectory of the Health Utilities Index (HUI) over 17 years of follow-up among Canadian National Population Health Survey (NPHS) participants. Annual average nitrogen dioxide (NO2) exposures from a national land use regression surface were mapped to 15,631 NPHS participants at their place of residence provided at each follow-up. We modelled HUI trajectory as a cubic polynomial function of age in relation to air pollution and selected covariates using random growth curve models to account for longitudinal repeated measures. Adjusting for covariates selected based on a directed acyclic graph, we found that NO2 exposure exhibited a significant negative association with HUI in females. It also exhibited a significant positive interaction with the linear age term, and a significant negative interaction with the quadratic age term, resulting in a small non-significant decrease in quality adjusted life years lived after age 20 among females. Our analysis provides a proof of concept for examining the influence of built environment variables on the trajectory of health related quality of life in Canada.