bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining the association between prenatal and perinatal adversity and the psychotic experiences in childhood
Authors: Staines Lorna , Dooley Niamh , Healy Colm , Kelleher Ian , Cotter David , Cannon Mary 
Published: March 2024

AbstractBackgroundPrenatal and perinatal complications are established risk factors for psychotic disorder, but far less is known about these measures and psychotic experiences (PEs). We investigated the longitudinal effect of prenatal risk factors (maternal behavior, medication complications) and perinatal risk factors (birth weight, medical complications) on frequency of PEs. We also examined the cumulative risk of prenatal/perinatal risk factors, and differences between transient PE, persistent PE, and controls.MethodsThe Adolescent Brain Cognitive Development study is a large child cohort (age 9–10 at baseline; n = 11 872 with PE data). PEs were measured longitudinally using the Prodromal Questionnaire-Brief, Child version, and included only if reported as distressing. Mixed-effects models were used for analysis, controlling for random effects, and a substantial number of fixed-effects covariates.ResultsUrinary tract infection (β = 0.11, 95% confidence interval [CI] 0.03–0.19) and severe anemia (β = 0.18, 95% CI 0.07–0.29) increased frequency of distressing PEs in childhood. Number of prenatal complications increased frequency of PEs (β = 0.03, 95% CI 0.01–0.06) and risk of persistent PEs (odds ratio [OR] = 1.08, 95% CI 1.01–1.15). Maternal smoking was associated with an increased frequency of PEs (β = 0.11, 95% CI 0.04–0.18) and persistent PEs (OR = 1.31, 95% CI 1.04–1.66). Maternal substance use was a risk factor for a 48% increased risk of persistent PEs (OR = 1.48, 95% CI 1.08–2.01). Perinatal complications showed no effect on PEs.ConclusionsThis study provides evidence that certain prenatal medical complications (severe nausea, severe anemia), cumulative number of prenatal medical complications, and maternal behaviors (smoking during pregnancy), increased frequency of distressing PEs in childhood. Maternal smoking and substance use, as well as cumulative number of prenatal complications increased risk of persistent PEs.
Models of mild cognitive deficits in risk assessment in early psychosis
Authors: Zhang TianHong , Cui HuiRu , Tang XiaoChen , Xu LiHua , Wei YanYan , Hu YeGang , Tang YingYing , Wang ZiXuan , Liu HaiChun , Chen Tao , Li ChunBo , Wang JiJun 
Published: March 2024

AbstractBackgroundMild cognitive deficits (MCD) emerge before the first episode of psychosis (FEP) and persist in the clinical high-risk (CHR) stage. This study aims to refine risk prediction by developing MCD models optimized for specific early psychosis stages and target populations.MethodsA comprehensive neuropsychological battery assessed 1059 individuals with FEP, 794 CHR, and 774 matched healthy controls (HCs). CHR subjects, followed up for 2 years, were categorized into converters (CHR-C) and non-converters (CHR-NC). The MATRICS Consensus Cognitive Battery standardized neurocognitive tests were employed.ResultsBoth the CHR and FEP groups exhibited significantly poorer performance compared to the HC group across all neurocognitive tests (all p < 0.001). The CHR-C group demonstrated poorer performance compared to the CHR-NC group on three sub-tests: visuospatial memory (p < 0.001), mazes (p = 0.005), and symbol coding (p = 0.023) tests. Upon adjusting for sex and age, the performance of the MCD model was excellent in differentiating FEP from HC, as evidenced by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.895 (p < 0.001). However, when applied in the CHR group for predicting CHR-C (AUC = 0.581, p = 0.008), the performance was not satisfactory. To optimize the efficiency of psychotic risk assessment, three distinct MCD models were developed to distinguish FEP from HC, predict CHR-C from CHR-NC, and identify CHR from HC, achieving accuracies of 89.3%, 65.6%, and 80.2%, respectively.ConclusionsThe MCD exhibits variations in domains, patterns, and weights across different stages of early psychosis and diverse target populations. Emphasizing precise risk assessment, our findings highlight the importance of tailored MCD models for different stages and risk levels.
Phonology, homophony, and eyes-closed rest in Mandarin novel word learning: An eye-tracking study in adult native and non-native speakers
Authors: Bao Wenfu , Arnhold Anja , Järvikivi Juhani 
Published: March 2024

AbstractThis study used the visual world paradigm to investigate novel word learning in adults from different language backgrounds and the effects of phonology, homophony, and rest on the outcome. We created Mandarin novel words varied by types of phonological contrasts and homophone status. During the experiment, native (n = 34) and non-native speakers (English; n = 30) learned pairs of novel words and were tested twice with a 15-minute break in between, which was spent either resting or gaming. In the post-break test of novel word recognition, an interaction appeared between language backgrounds, phonology, and homophony: non-native speakers performed less accurately than native speakers only on non-homophones learned in pairs with tone contrasts. Eye movement data indicated that non-native speakers’ processing of tones may be more effortful than their processing of segments while learning homophones, as demonstrated by the time course. Interestingly, no significant effects of rest were observed across language groups; yet after gaming, native speakers achieved higher accuracy than non-native speakers. Overall, this study suggests that Mandarin novel word learning can be affected by participants’ language backgrounds and phonological and homophonous features of words. However, the role of short periods of rest in novel word learning requires further investigation.
Implicational Kleene algebra with domain and the substructural logic of partial correctness
Authors: Sedlár Igor 
Published: March 2024

AbstractWe show that Kozen and Tiuryn’s substructural logic of partial correctness
$\mathsf{S}$
embeds into the equational theory of Kleene algebra with domain,
$\mathsf{KAD}$
. We provide an implicational formulation of
$\mathsf{KAD}$
which sets
$\mathsf{S}$
in the context of implicational extensions of Kleene algebra.
Whiteness and the Problem of Colourblind Listening: Revisiting Leonard Feather's 1951 Blindfold Test with Roy Eldridge
Authors: VAD MIKKEL 
Published: March 2024

Abstract‘I couldn't tell who was colored and who was white’, admitted the African American trumpet player Roy Eldridge after being submitted to a so-called blindfold test by the white critic Leonard Feather in 1951. Feather was happy that the blindfold test duped a prominent Black musician, because it proved his point about the fundamental colourblindness of music and listening. Through close reading of the source material, this article provides the full context for this infamous case and shows how the blindfold test was a product of transnational discourses of colourblindness, primitivism, ‘reverse racism’, and technological mediation. Building on current research in racialized practices of listening in musicology and sound studies, and mobilizing interventions from critical race studies, the article contends that acousmatic techniques of listening often promote a colourblind ideology invested in whiteness, which remains hegemonic in music culture.
Large data set of lensed quasars: higher accuracy on H0? The angular structures viewpoint
Authors: Van de Vyvere Lyne 
Published: March 2024

AbstractThanks to forthcoming large-scale surveys, a tremendous number of strong lenses will be discovered in the coming years. The gain in accuracy on H0 from such a large population of lensed quasars is a key question for the future of time-delay cosmography. In such context, lensed systems will have to be modeled in an automated way, with models that are sufficiently generic to apply to every lens. I explore the biases that may arise from unaccounted-for azimuthal structures in mass models. The non-modeled twists in lensing galaxies are expected to bias the shear inference but not H0. Disregarded ellipticity gradients, boxyness and discyness may impact the cosmological inference on a lens-by-lens basis. Nevertheless, the diversity of azimuthal mass profile in lenses balances the bias at a population level and the H0 inference can thus benefits from such large surveys.
Learning about the structure of strongly lensed AGNs from their lightcurves
Authors: Sluse Dominique 
Published: March 2024

AbstractThe lightcurves of strongly lensed AGNs get distorted due to gravitational microlensing, which differently magnifies the emission regions of AGNs depending on their size. This effect has been used to measure the size of the AGN accretion disc, but high photometric accuracy lightcurves reveal coherent variations on short time-scales that are not expected by standard accretion disc models. I show that this signal can be produced by emission from the Broad Line Region (BLR) but also by extended (diffuse) continuum emission. I explain how these features can be used to measure the size of the BLR but also reveal additional sources of emission. The multi-colour lightcurves of lensed AGNs, such as those to be obtained with the Vera Rubin Observatory, may become a powerful new tool to reveal the sub-parsec structure of AGNs, and shed light on elusive AGN emitting regions such as the one producing diffuse continuum emission.
Shapes and Centroids of 39 Strong Lensing Galaxy Clusters from the Sloan Giant Arcs Survey
Authors: Gassis Raven , Bayliss Matthew B. , Sharon Keren , Mahler Guillaume , Gladders Michael D. , Dahle Håkon , Florian Michael K. , Rigby Jane R. , Elicker Lauren , Riley Owens M. 
Published: March 2024

AbstractStrong lensing galaxy clusters provide a powerful observational test of Cold Dark Matter (CDM) structure predictions derived from simulation. Specifically, the shape and relative alignments of the dark matter halo, stars, and hot intracluster gas tells us the extent to which theoretical structure predictions hold for clusters in various dynamical states. We measure the position angles, ellipticities, and locations/centroids of the brightest cluster galaxy (BCG), intracluster light (ICL), the hot intracluster medium (ICM), and the core lensing mass for a sample of strong lensing galaxy clusters from the SDSS Giant Arcs Survey (SGAS). We use iterative elliptical isophote fitting methods and GALFIT modeling on HST WFC3/IR imaging data to extract ICL and BCG information and use CIAO’s Sherpa modeling on Chandra ACIS-I X-ray data to make measurements of the ICM. Using this multicomponent approach, we attempt to constrain the physical state of these strong lensing clusters and evaluate the different observable components in terms of their ability to trace out the gravitational potential of the cluster.
A High‐Resolution Seismic Catalog for the Southern Apennines (Italy) Built Through Template‐Matching
Authors: Diaferia G. , Valoroso L. , Improta L. , Piccinini D. 
Published: March 2024

AbstractThe incompleteness of earthquake catalogs is a well‐known issue caused by our technical limitation in detecting the small‐to very small‐magnitude seismicity falling near or below the background seismic noise. The detection of small‐magnitude events is fundamental for improving our knowledge of geometry and kinematics of seismogenic sources and the spatio‐temporal characteristics of seismicity, thus leading to better models for seismic hazard. Template‐matching (TM) is a powerful technique that, based on similarity measure (cross‐correlation) of seismic waveforms, allows to detect hidden earthquakes that are similar to known events (called templates). The high computational effort often limits such technique to small areas and for short time frames (less than 1 year). In this work, we present the first application of template‐matching at regional scale for the Italian Peninsula, focusing on the Southern Apennines. We use about 3,600 high‐quality events as templates, scanning 6‐year long continuous recordings (2009–2014), at more than 180 stations of the INGV network. About 20,000 new events are found, showing a comparable quality to the template catalog in terms of hypocentral solution, reaching a decrease of the magnitude of completeness of about one unit. To highlight the improved quality of the TM catalog, we report two main examples regarding the Sannio‐Matese area, where TM allowed us to unravel relevant details on the spatio‐temporal distribution of the local seismicity.
3D Diffusion of Water in Melt Inclusion‐Bearing Olivine Phenocrysts
Authors: Mutch Euan J. F. , Newcombe Megan E. , Rudge John F. 
Published: March 2024

AbstractOlivine‐hosted melt inclusions are an important archive of pre‐eruptive processes such as magma storage, mixing and subsequent ascent through the crust. However, this record can be modified by post‐entrapment diffusion of H+ through the olivine lattice. Existing studies often use spherical or 1D models to track melt inclusion dehydration that fail to account for complexities in geometry, diffusive anisotropy and sectioning effects. Here we develop a finite element 3D multiphase diffusion model for the dehydration of olivine‐hosted melt inclusions that includes natural crystal geometries and multiple melt inclusions. We use our 3D model to test the reliability of simplified analytical and numerical models (1D and 2D) using magma ascent conditions from the 1977 eruption of Seguam volcano, Alaska. We find that 1D models underestimate melt inclusion water loss, typically by ∼30%, and thus underestimate magma decompression rates, by up to a factor of 5, when compared to the 3D models. An anisotropic analytical solution that we present performs well and recovers decompression rates within a factor of 2, in the situations in which it is valid. 3D models that include multiple melt inclusions show that inclusions can shield each other and reduce the amount of water loss upon ascent. This shielding effect depends on decompression rate, melt inclusion size, and crystallographic direction. Our modeling approach shows that factors such as 3D crystal geometry and melt inclusion configuration can play an important role in constraining accurate decompression rates and recovering water contents in natural magmatic systems.
Quantifying the Relative Contributions of the Global Oceans to ENSO Predictability With Deep Learning
Authors: Li Tang , Tang Youmin , Lian Tao , Hu Anfeng 
Published: March 2024

AbstractWe propose a unified statistical method based on deep learning and heatmap analysis to quantify the relative contributions of the global oceans to El Niño–Southern Oscillation (ENSO) predictability. By incorporating subsurface signals in the Indian Ocean and Atlantic, the forecast lead can be skillfully extended by about one season. This skill enhancement mainly originates from the tropical Indian Ocean, presumably related to signals of the Indian Ocean Dipole passing to the tropical Pacific through the Indonesian Throughflow. The sea surface temperature anomaly (SSTA) in the Indian Ocean accounts for nearly 50% of surface contributions to both El Niño and La Niña predictions at a 15‐month lead. The north tropical Atlantic SSTA has a moderate impact on La Niña at a 9‐month lead. The Pacific Meridional Mode plays a significant role in both ENSO phases at a 12‐month lead. Thus, our study suggests that trans‐basin effects for ENSO are more vigorous than previously thought.
Two‐Dimensional Hybrid Simulation of the Second‐Harmonic Generation of EMIC Waves in the Inner Magnetosphere
Authors: Xue Zuxiang , Yuan Zhigang , Yu Xiongdong , Deng Dan 
Published: March 2024

AbstractTwo‐dimensional (2‐D) hybrid model is developed to investigate the second harmonic (SH) generation of electromagnetic ion cyclotron (EMIC) waves. Applying the singular value decomposition method to simulated fields, we show that the SH exhibits wave properties analogous to typical EMIC waves generated by ion cyclotron instabilities, that is, left‐hand polarization and small wave normal angle. However, the bicoherence index inferred from simulated fields reflects a strong phase coupling between the fundamental wave (FW) and the SH, illustrating the nonlinear generation of the SH by the FW. The necessary conditions, especially for the wave vector relation, are further verified from a 2‐D perspective. The simulated amplitude ratios well meet the theoretical results only in the SH saturation stage, while the necessary conditions remain satisfied almost throughout the simulation. This study provides a comprehensive analysis of the SH excitation in a 2‐D simulation domain, contributing to a deeper understanding of EMIC wave nonlinear generation.
The Impact of Gravity Waves on the Evolution of Tropical Anvil Cirrus Microphysical Properties
Authors: Jensen E. J. , Kärcher B. , Woods S. , Krämer M. , Ueyama R. 
Published: March 2024

AbstractAnvil cirrus generated by deep convection covers large fractions of the tropics and has important impacts on the Earth's radiation budget and climate. In situ measurements made with high‐altitude aircraft indicate a rapid transition in ice crystal size distributions and habits as anvil cirrus ages. We use numerical simulations to investigate the impact of high‐frequency gravity waves on the evolution of anvil cirrus microphysical properties. The impacts of both monochromatic gravity waves and ubiquitous stochastic mesoscale temperature fluctuations are simulated. In both cases, the interplay between wave‐driven temperature fluctuations, deposition growth/sublimation, and sedimentation causes accelerated removal of both small ice crystals (diameters less than about 10 μm) and large crystals (diameters larger than ≈30 μm). These changes are consistent with the observed evolution of anvil cirrus microphysical properties. The Kelvin effect (higher saturation vapor pressure over curved surfaces) is a critical factor in the anvil evolution, driving mass transfer from small to large ice crystals. The wave‐driven decrease in ice concentration is much faster for typical anvil cirrus detrained at ≃11.5–12.5 km than for less frequent anvils at 15.5–17.5 km because of the strong temperature dependence of deposition growth and sublimation rates. The simulations also show that waves, along with the Kelvin effect, drive growth of mid‐sized (5–20 μm) ice crystals, which is consistent with the observed transition to bullet rosette habits in aging anvil cirrus. We conclude that high‐frequency gravity waves, which are generally not resolved in large‐scale models, likely have important impacts on anvil cirrus microphysical properties and lifetimes.
Estimation of Soil Moisture Thresholds for Aggravation of Global Terrestrial Carbon Uptake Losses
Authors: Yan Heng , Xie Zhenghui , Jia Binghao , Qin Peihua , Zhang Xia , Dai Qiudan , Xie Jinbo , Wang Longhuan , Li Ruichao , Tian Yuhang , You Yanbin 
Published: March 2024

AbstractMost ecosystems have resistance to soil moisture (SM) deficit, which is termed drought resistance. Drought resistance can be invalid and global terrestrial carbon uptake losses can be aggravated when SM deficit exceeds a critical threshold. However, soil moisture thresholds (SMTs) that detrimentally impact global terrestrial carbon uptake are still unclear. We performed numerical simulations using the Community Earth System Model, and estimated the SMTs by the back propagation neural network method for the years 2004–2014. The SMTs represent the inflection point for vegetation changes from high to low drought resistance phase, and terrestrial carbon uptake losses from low to high rate. Soil moisture‐limited ecoregions have higher SMTs than energy‐limited ecoregions, indicating the increased vulnerability and sensitivity of SM‐limited ecoregions to SM deficit and more easily aggravated terrestrial carbon uptake losses during drought. SMTs varied in different vegetation types and broadleaf deciduous trees displayed the highest SMTs and C3 arctic grasses have lowest thresholds. Humid and high vegetation coverage rate regions have lower thresholds. The SMTs increase with the increase of clay content and the decrease of sand content. In addition, land‐atmosphere feedback caused by SM deficit has a large impact on terrestrial carbon uptake and may be one of the main reasons for the aggravation of vegetation carbon uptake losses. Our results provide a unique perspective for investigating the impact of drought on vegetation.
A Coordinated Sea‐Ice Assimilation Scheme Jointly Using Sea‐Ice Concentration and Thickness Observations With a Coupled Climate Model
Authors: Liu X. , Yao J. , Zhang S. , Wu T. , Chen Z. , Fang Y. , Chu M. , Yan J. , Jie W. 
Published: March 2024

AbstractFor jointly assimilating sea‐ice concentration (SIC) and sea‐ice thickness (SIT) observations into a global coupled climate system model consisting of sea‐ice component with multiple sea‐ice categories, we propose a new sea‐ice analysis update scheme in an ensemble assimilation framework and compare it with some previously used schemes. Different from the conventional scheme that often assigns SIC/SIT analysis to multiple sea‐ice categories according to the background ratios and thus directly updates the corresponding variables in model (i.e., direct‐update scheme), the new scheme converts SIC/SIT analysis into ice heating term to adjust the ice enthalpy using model freezing/melting physics and further updates the model sea‐ice state (i.e., enthalpy‐adjusting scheme). It has a capability in particularly adjusting multiple sea‐ice variables in addition to SIC and SIT in a coordinated way, and avoiding the artificial addition or elimination of sea‐ice in analysis that is often adopted in the direct‐update scheme. Evaluated by several sets of experiments assimilating satellite‐derived Arctic sea‐ice observations, the enthalpy‐adjusting scheme performs better than the direct‐update scheme in analysis of the Arctic SIT. Further, 4‐week forecasts after assimilation initialization exhibit slow growth of forecast error. Compared to the direct‐update scheme, the enthalpy‐adjusting scheme initialized forecasts show comparable skills in the SIC but significantly higher skills in the SIT, especially in the Arctic sea‐ice edge areas. These results highlight advantage of the enthalpy‐adjusting scheme that has promise to improve coupled data assimilation and reduce climate prediction uncertainty.
Impacts of Permeability Uncertainty in a Coupled Surface‐Subsurface Flow Model Under Perturbed Recharge Scenarios
Authors: Engdahl Nicholas B. 
Published: March 2024

AbstractCoupled simulations of surface and variably saturated subsurface flow, termed integrated hydrologic models (IHMs), can provide powerful insights into the complex dynamics of watersheds. The system of governing equations solved by an IHM is non‐linear, making them a significant computational burden and challenging to accurately parameterize. Consequently, a large fraction of the IHM studies to date have been “numerical hypothesis testing” studies, but, as parallel computing continues to improve, IHMs are approaching the point where they might also be useful as predictive tools. For this to become reality, the predictive uncertainty of such highly parameterized simulations must be considered. However, uncertainty is seldom considered in the IHM literature, likely due to the long runtimes of the complex simulations. The questions considered herein are how much uncertainty is there in an IHM for a common watershed simulation scenario, and how likely is it that any one realization of a system will give the same relative change as any other due to a perturbation in recharge? A stochastic ensemble of 250 permeability field realizations was used to show that uncertainty in a high‐mountain headwaters systems is dominated by the subsurface. Recharge perturbation scenarios echo these results, but the uncertainty of changes in streamflow or groundwater pressure heads were significantly smaller than the uncertainty in their base‐case values. The main finding is that IHMs do provide confident, predictive estimates of relative changes in watersheds, even when uncertainty in specific simulation outputs may be high.