bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on cellular uptake of a hydrophobic near-infrared-absorbing diradical-platinum(II) complex solubilized by albumin using hyperspectral imaging, spectrophotometry, and spectrofluorimetry
Authors: Sawamura Ryota , Masuya-Suzuki Atsuko , Iki Nobuhiko 
Published: June 2024

AbstractOwing to its biopenetrability and minimal invasiveness, near-infrared (NIR) light in the region between 700–1100 nm has attracted attention in cancer diagnosis and therapy. Our group previously reported that the hydrophobic diradical-platinum(II) complex PtL2 is a promising agent for cancer photothermal therapy (L = 3,5-dibromo-1,2-diiminobenzosemiquinonate radical). Because PtL2 does not fluoresce, its intercellular uptake of PtL2 cannot be observed with a fluorescence microscope. In this study, we clarified the uptake and intracellular behavior of PtL2 solubilized by bovine serum albumin (BSA) using hyperspectral imaging enabling spectrophotometric analysis of the image. The spectral changes in the obtained images indicated that the internalization of PtL2 was followed by crystallization of the complex during the long incubation period (> 4 h). Additionally, the binding constant Kb = 5.91 × 104 M–1 could be estimated upon fluorescence quenching analysis of BSA upon binding of PtL2; Kb is two orders of magnitude smaller than that of albumin–common drugs. Considering the small Kb and low solubility of PtL2 in water, we ultimately proposed the internalization path and fate of PtL2 in the cell: release of PtL2 from BSA near cellular membranes and subsequent cellular uptake via membrane permeation followed by saturation, resulting in crystallization.
Graphical abstract
Growth-induced transformable surfaces realized by bending-active scissors grid
Authors: Ono Fuki , Kamijo Haruto , Kase Miwako , Nishimoto Seri , Sempuku Kotaro , Shigematsu Mizuki , Tachi Tomohiro 
Published: June 2024

AbstractRuffled surfaces that appear in biological forms, such as coral and lettuce, are a great source of inspiration for architectural and furniture design. This paper proposes a mechanism based on a bending-active scissors grid that effectively reproduces the process of differential growth. The structure can deploy from a linearly folded state with rotational symmetry to a complex ruffled surface without rotational symmetry. The deployed shape further exhibits a wave-like motion similar to the swimming gait of flatworms or cuttlefish. First, we propose a design method for the mechanism computed from the surface of constant negative Gaussian curvature. We then numerically analyze the symmetry-breaking process of deployment and zero-stiffness wave-like motion after deployment. We built two demonstrators to verify the deployment and the transformation. The first demonstrator with 1.5m diameter was fabricated to verify the symmetry-breaking deployment motion. The second demonstrator with 0.9m diameter was fabricated to demonstrate the wave-like motion by controlled pulling of the group of threads.
Healthcare spending in high-income and upper-middle-income countries: a cross-country analysis
Authors: Jayadevan C. M. , Trung Hoang Nam 
Published: June 2024

AbstractThis research investigates the determinants of government healthcare expenditure in high-income and upper-middle-income countries by exploring economic, demographic, and political influences. By analyzing data from 1990 to 2019 from 28 high-income and 42 upper-middle-income nations, this study employs Bayesian model averaging, the generalized method of moments, and regression discontinuity design. The results reveal that government healthcare spending positively correlates with the previous year's expenditure in both income groups. Additionally, the impact of education on spending differs, while it is positively significant in high-income countries, it is not significant in upper-middle-income countries. The proportion of elderly individuals positively influences healthcare spending in high-income countries but inconsistently influences healthcare spending in upper-middle-income countries. Urbanization significantly impacts spending in upper-middle-income nations. The positive association between industrial employment and spending suggests greater healthcare needs in such areas. Efforts to curb corruption positively affect spending differently for each income group. Out-of-pocket expenses negatively impact spending in both groups, though positively in high-income countries alone. The influence of the young population varies, being negative in high-income countries but positive in upper-middle-income countries. Logistic and probit regression models identify key determinants, including gross domestic product (GDP) per capita, elderly population proportion, out-of-pocket expenses, and corruption control measures in high-income countries. Policymakers can use these findings to tailor strategies, optimize healthcare spending, and ensure equitable access across income levels.
Sustainable approach to quality assurance in cement-improved soil: applications of handheld XRF for geotechnical solutions
Authors: Sindete Mathiro José , Usui Hirofumi , Some Donzala David , Hino Takenori 
Published: June 2024

AbstractTraditional methods for evaluating the quality of the Deep Mixing Method (DMM) in Japan, such as the phenolphthalein tracer method, present limitations in ensuring strength improvement. This study explores handheld X-ray fluorescence (XRF) as a sustainable alternative for quality assessment. The elemental composition of cement-treated soil was investigated, focusing on Calcium (Ca), Silicate (Si), and Sulfate (S), which play crucial roles in the formation of hydrated products, aiming to accurately determine their influence on the strength development of the improved soil. A controlled protocol was employed using commercial Kaolin clay and the needle penetration test for strength assessment. Our laboratory experiments, conducted with a cement-based binder (C) dosage of 110 kg/m3 and a water-cement (W/C) ratio of 1, furthered our understanding of the hydration process. Results indicate an apparent increase in Ca amount over time, correlating with improved strength, while the apparent amount of Si decreases, suggesting its integration into hydration products such as C-S–H gel. Strength assessment rose significantly between day 1 and 28, aligning with variations observed in Si, Ca, and S, underlining their role in strength evolution. This research underscores the potential of handheld XRF as a sustainable substitute for conventional methods in field-quality assurance, offering real-time data on the formation of possible hydrated products during the hydration process for improved soil in geotechnical engineering.
Quantifying Volumetric Scattering Bias in ICESat‐2 and Operation IceBridge Altimetry Over Greenland Firn and Aged Snow
Authors: Fair Zachary , Flanner Mark , Neumann Tom , Vuyovich Carrie , Smith Benjamin , Schneider Adam 
Published: June 2024

AbstractThe Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) mission has collected surface elevation measurements for over 5 years. ICESat‐2 carries an instrument that emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat‐2 acquisitions during the melting season. We performed two case studies over the Greenland Ice Sheet to quantify bias in ICESat‐2 signals over snow: one to validate Airborne Topographic Mapper (ATM) data against Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS‐NG) grain sizes, and a second to estimate ICESat‐2 bias relative to ATM. We used snow optical grain sizes derived from ATM and AVIRIS‐NG to attribute altimetry bias to snowpack properties. For the first case study, the mean and standard deviation of optical grain sizes were 340 ± 65 µm (AVIRIS‐NG) and 670 ± 420 µm (ATM). A mean altimetry bias of 4.81 ± 1.76 cm was found for ATM, with larger biases linked to increases in grain size. In the second case study, we found a mean grain size of 910 ± 381 µm and biases of 6.42 ± 1.77 cm (ICESat‐2) and 9.82 ± 0.97 cm (ATM). The grain sizes and densities needed to recreate biases with a model are uncommon in nature, so we propose that additional surface attributes must be considered to characterize ICESat‐2 bias over snow. The altimetry biases are within the accuracy requirements of the ICESat‐2 mission, but we cannot rule out more significant errors over coarse‐grained snow.
The Limited Effect of Reduced Typhoon Frequency on Stream Hydrochemistry in a Subtropical Forest Watershed
Authors: Chang Chung‐Te , Huang Jr‐Chuan , Wang Lixin , Wang Hsiang‐Hua , Lee Jun‐Yi , Lin Teng‐Chiu 
Published: June 2024

AbstractTropical cyclones are often accompanied by large amount of precipitation potentially impacting stream hydrochemistry. Global warming is altering typhoon disturbance regime. Little is known about how cyclone changes, especially cyclone‐frequency reduction may affect stream hydrochemistry. In this study, we compared water and nutrient input via precipitation and output via streamflow between a frequent‐typhoon period (2013–2017), with 1.2 typhoon yr−1, and a no‐typhoon period (2018–2022) at a long‐term monitoring site, the Fushan Experimental Forest of Taiwan. Precipitation and streamflow quantities were not different between the two periods because typhoons increased the fluctuation but not the mean of monthly precipitation in the major typhoon months (July–September). Inputs of Mg2+, NO3−, and SO42− via precipitation were greater in the frequent‐typhoon period than the no‐typhoon period while inputs of other ions were not different between the two periods. Only the output of Mg2+ was different between the two periods, greater in the frequent‐typhoon period. Output/input ratio of NO3− was greater in the no‐typhoon period than the frequent‐typhoon period despite the greater input in the frequent‐typhoon period, while no differences were found for others. Increases in mineralization rates due to warming is suggested to be the cause of the greater NO3− output/input ratio during the no‐typhoon period. Relationships between stream discharge and ion export were similar between the two periods both with and without removing typhoon events. The limited variation in hydrochemistry between periods of contrasting cyclone activities suggests high resilience of the undisturbed subtropical forests to changes in cyclone frequency at the decadal scale.
Prediction of Solar Wind Speed Through Machine Learning From Extrapolated Solar Coronal Magnetic Field
Authors: Lin Rong , Luo Zhekai , He Jiansen , Xie Lun , Hou Chuanpeng , Chen Shuwei 
Published: June 2024

AbstractAn accurate solar wind (SW) speed model is important for space weather predictions, catastrophic event warnings, and other issues concerning SW—magnetosphere interaction. In this work, we construct a model based on convolutional neural network (CNN) and Potential Field Source Surface (PFSS) magnetic field maps, considering a SW source surface of RSS = 2.5R⊙, aiming to predict the SW speed at the Lagrange‐1 (L1) point of the Sun‐Earth system. The input of our model consists of four PFSS magnetic field maps at RSS, which are three, four, five, and six days before the target epoch. Reduced maps are used to promote the model's efficiency. We use the Global Oscillation Network Group (GONG) photospheric magnetograms and the potential field extrapolation model to generate PFSS magnetic field maps at the source surface. The model provides predictions of the quasi‐continuous test data set, which is generated by randomly assigning 120 data segments that are individually continuous in time, with an averaged correlation coefficient (CC) of 0.53 ± 0.07 and a root mean square error (RMSE) of 80.8 ± 4.8 km/s in an eight‐fold validation training scheme with the time resolution of the data as small as one hour. The model also has the potential to forecast high speed streams of the SW, which can be quantified with a general threat score of 0.39.
Distribution‐Based Model Evaluation and Diagnostics: Elicitability, Propriety, and Scoring Rules for Hydrograph Functionals
Authors: Vrugt Jasper A. 
Published: June 2024

AbstractDistribution forecasts P over future quantities or events are routinely made in hydrology but usually traded for a (likelihood‐weighted) mean or median prediction to accommodate error measures or scoring functions such as the mean absolute error or mean squared error. Case in point is the so‐called KG efficiency (KGE) of Gupta et al. (2009, https://doi.org/10.1016/j.jhydrol.2009.08.003) and improvements thereof (Lamontagne et al., 2020, https://doi.org/10.1029/2020wr027101), which have rapidly gained popularity among hydrologists as alternative scoring functions to the commonly used Nash and Sutcliffe (1970, https://doi.org/10.1016/0022‐1694(70)90255‐6) efficiency, but are equally exclusive in how they quantify model performance using only single‐valued output of the quantities of interest. This point‐valued mapping necessarily implies a loss of information about model performance. This paper advocates the use of probabilistic watershed model training, evaluation and diagnostics. Distribution evaluation opens a mature literature on scoring rules whose strong statistical underpinning provides, as we will demonstrate, the theory, context and guidelines necessary for the development of robust information‐theoretically principled metrics for watershed signatures. These so‐called hydrograph functionals are scalar‐valued mappings of major behavioral watershed functions embodied in a strictly proper scoring rule. We discuss past developments that led to the current state‐of‐the‐art of distribution evaluation in hydrology and review scoring rules for dichotomous and categorical events, quantiles (intervals) and density forecasts. We are particularly concerned with elicitable functionals and scoring rule propriety, discuss the decomposition of scoring rules into a sharpness, reliability and entropy term and present diagnostically appealing strictly proper divergence scores of hydrograph functionals for flood frequency analysis, flow duration and recession curves. The usefulness and power of distribution‐based model evaluation and diagnostics by means of scoring rules is demonstrated on simple illustrative problems and discharge distributions simulated with watershed models using random sampling and Bayesian model averaging. The presented theory (a) enables a more complete evaluation of distribution forecasts, (b) offers a statistically principled means for watershed model training, evaluation, diagnostics and selection using hydrograph functionals and/or extreme events and (c) provides a universal framework for metric development of watershed signatures, promoting metric standardization and reproducibility.
In Situ Observations of Magnetic Reconnection Caused by the Interactions of Two Dipolarization Fronts
Authors: Jiang K. , Huang S. Y. , Wei Y. Y. , Yuan Z. G. , Xiong Q. Y. , Xu S. B. , Zhang J. 
Published: June 2024

AbstractUsing high‐resolution data from the Magnetospheric Multiscale mission, an electron‐only reconnection current sheet is found between two successive dipolarization fronts (DFs). The electron‐only reconnection occurs between the northward component of the magnetic field of the flux pileup region (FPR) of the first DF (DF1) and the southward component of the magnetic dip of the second DF (DF2). The faster DF2 compresses the FPR of DF1, which constitutes an anti‐parallel topology and reduces the thickness of the current sheet. Further analysis shows that the current sheet is unstable to the electron tearing instability, which may power the onset of the reconnection. Our results suggest that these two DFs may merge into one by the reconnection, which sheds light on the evolution of DFs during their earthward propagation.
A Multi‐Model Ensemble System for the Outer Heliosphere (MMESH): Solar Wind Conditions Near Jupiter
Authors: Rutala M. J. , Jackman C. M. , Owens M. J. , Tao C. , Fogg A. R. , Murray S. A. , Barnard L. 
Published: June 2024

AbstractHow the solar wind influences the magnetospheres of the outer planets is a fundamentally important question, but is difficult to answer in the absence of consistent, simultaneous monitoring of the upstream solar wind and the large‐scale dynamics internal to the magnetosphere. To compensate for the relative lack of in‐situ solar wind data, propagation models are often used to estimate the ambient solar wind conditions at the outer planets for comparison to remote observations or in‐situ measurements. This introduces another complication: the propagation of near‐Earth solar wind measurements introduces difficult‐to‐assess uncertainties. Here, we present the Multi‐Model Ensemble System for the outer Heliosphere (MMESH) to begin to address these issues, along with the resultant multi‐model ensemble (MME) of the solar wind conditions near Jupiter. MMESH accepts as input any number of solar wind models together with contemporaneous in‐situ spacecraft data. From these, the system characterizes typical uncertainties in model timing, quantifies how these uncertainties vary under different conditions, attempts to correct for systematic biases in the input model timing, and composes a MME with uncertainties from the results. For the Juno‐era (04/07/2016–04/07/2023) MME hindcast for Jupiter presented here, three solar wind propagation models were compared to in‐situ measurements from the near‐Jupiter spacecraft Ulysses and Juno spanning diverse geometries and phases of the solar cycle across >14,000 hr of data covering 2.5 decades. The MME gives the most‐probable near‐Jupiter solar wind conditions for times within the tested epoch, outperforming the input models and returning quantified estimates of uncertainty.
Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States
Authors: Huber Daniel E. , Kort Eric A. , Steiner Allison L. 
Published: June 2024

AbstractAgricultural soils containing nitrogen‐rich fertilizers are a substantial source of reactive nitrogen to the atmosphere with potential to impact air quality. One form of reactive nitrogen, nitrogen oxides (NOx = NO + NO2), are a harmful air pollutant and form secondary pollutants, including particulate matter (PM) and ozone (O3). Soil nitrogen oxide emissions (SNOx) are heavily influenced by environmental conditions, however the understanding of the influence of environmental drivers on the behavior of SNOx is limited. Here, we implement a modified soil moisture‐dependent SNOx parameterization into the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) and investigate the impact on regional air quality in the central U.S. Evaluating against TROPOspheric Monitoring Instrument (TROPOMI) column NO2 observations, WRF‐Chem columns better capture the TROPOMI column magnitudes earlier in the growing season when using the updated SNOx parametrization, with modeled column bias improved to −1.1% over the most heavily fertilized regions. Evaluating against Environmental Protection Agency (EPA) surface NO2 observations, the relationship between surface NO2 and soil moisture is better represented in agriculturally‐dominant regions when using the updated parameterization, with greatest surface NO2 concentrations at moderate soil moisture and lower concentrations at wetter or drier soil conditions. In simulations, these SNOx lead to increased O3 in select urban regions, with more than double the occurrences of O3 exceeding the EPA 8‐hr O3 standard of 70 ppb.
Modeling Salt‐Verde Watershed Winter Precipitation Using Convection‐Permitting WRF‐Simulations With Water Vapor Tracers
Authors: Salamanca‐Palou Francisco , Svoma Bohumil , Walter James , Insua‐Costa Damian , Miguez‐Macho Gonzalo , Karanja Joseph , Georgescu Matei 
Published: June 2024

AbstractThis study characterizes moisture source regions for wintertime precipitation across the Salt‐Verde watershed and Arizona (USA) through use of convection‐permitting numerical experiments. We dynamically downscale three four‐month‐long (i.e., December‐January‐February‐March, or DJFM) winter periods: a representative warm (DJFM 1997–1998), cold (DJFM 1999–2000), and neutral (DJFM 2016–2017) winter, as diagnosed by the mean Sea Surface Temperature (SST) across the El Niño 3.4 region compared to a 1995 to 2019 baseline. We utilize the Weather Research and Forecasting (WRF) model with water vapor tracers (WVTs) to distinguish moisture source contributions to total precipitation across Arizona, as originating from land evapotranspiration, sea evaporation, and external advection. Analysis of our numerical experiments demonstrates that WRF is able to capture the day‐to‐day precipitation events across the complex terrain that is characteristic of the Salt‐Verde watershed, but seasonal accumulated precipitation is consistently overestimated compared to individual station observations. The spatial distribution of wintertime monthly accumulated precipitation across Arizona is well captured by WRF, although the total amount of rainfall is overestimated in some confined areas across the highlands of Arizona. Our convection‐permitting WRF experiments also demonstrate that WVT contributions to total wintertime precipitation are apportioned roughly equally between sea evaporation (contributing 45.6%) across the North America west coast and external advection (contributing 48.1%), with land evapotranspiration playing a minimal role (i.e., the remaining 6.3%). We further conduct single‐domain WRF experiments at non‐convection‐permitting resolution and conclude that local sea evaporation, bounded by 140°W and 100°W, is the primary moisture source region to total wintertime precipitation across the Salt‐Verde watershed and Arizona independent of the remote tropical SST across the El Niño 3.4 region.
Inhibition abilities and functional brain connectivity in school-aged term-born and preterm-born children
Authors: Disselhoff Vera , Jakab Andras , Latal Beatrice , Schnider Barbara , Wehrle Flavia M. , Hagmann Cornelia F. ,   the EpoKids Research Group, Held Ulrike , O’Gorman Ruth Tuura , Fauchère Jean-Claude , Hüppi Petra 
Published: June 2024

Abstract

Background
Inhibition abilities are known to have impact on self-regulation, behavior, and academic success, and they are frequently impaired in children born preterm. We investigated the possible contributions of resting-state functional brain connectivity to inhibition following preterm birth.

Methods
Forty-four preterm and 59 term-born participants aged 8–13 years were administered two inhibition tasks and resting-state functional MRI was performed. Functional connectivity (FC) networks were compared between groups using network-based statistics. Associations of FCNs and inhibition abilities were investigated through multivariate linear regression models accounting for the interaction between birth status and inhibition.

Results
NBS revealed weaker FC in children born preterm compared to term-born peers in connections between motor and supplementary motor regions, frontal lobe, precuneus, and insula. Irrespective of birth status, connections between the cerebellum, frontal, and occipital lobes and inter-lobar, subcortical, intra-hemispheric long-range connections were positively correlated with one of the two inhibition tasks.

Conclusions
Preterm birth results in long-term alterations of FC at network level but these FCN alterations do not specifically account for inhibition problems in children born very preterm.

Impact

Irrespective of birth status, significant associations were found between the subdomain of response inhibition and functional connectivity in some subnetworks.

A group comparisons of functional brain connectivity measured by rsfMRI in school-aged children born very preterm and at term.

The investigation of network-level functional connectivity at rest does not appear adequate to explain differences in inhibition abilities between children born very preterm and at term, hence other imaging techniques might be more suited to explore the underlying neural mechanisms of inhibition abilities in school-aged children born very preterm.