bluuebunny/crossref_metadata_2025_split huggingface dataset:
An energetics tale of the 2022 mega-heatwave over central-eastern China
Authors: Zhang Tuantuan , Deng Yi , Chen Junwen , Yang Song , Dai Yongjiu 
Published: October 2023

AbstractIt remains a major challenge to attribute heatwave’s lifecycle characteristics quantitatively to interwoven atmospheric and surface actions. By constructing a process-resolving, energetics-based attribution framework, here we quantitatively delineate the lifecycle of the record-breaking 2022 mega-heatwave over central-eastern China from a local energetics perspective. It is found that the cloudlessness induced radiative heating and atmospheric dynamics dominate the total energy buildup during the developing stage, while the land-atmosphere coupling and atmospheric horizontal advection act most effectively to sustain and terminate the heatwave, respectively. A reduction in anthropogenic aerosols provides a persistent positive contribution during the event, suggesting that pollution mitigation measures may actually increase the amplitudes of future heatwaves. With this framework, initial efforts are made to unravel culprits in a model’s sub-seasonal prediction of this mega-heatwave, demonstrating the framework’s potential for efficiently detecting the origins of climate extremes and quantitatively assessing the impacts of mitigation policies for sustainable development.
Phenotypic but not genetically predicted heart rate variability associated with all-cause mortality
Authors: Tegegne Balewgizie S. , Said M. Abdullah , Ani Alireza , van Roon Arie M. , Shah Sonia , de Geus Eco J. C. , van der Harst Pim , Riese Harriëtte , Nolte Ilja M. , Snieder Harold 
Published: October 2023

AbstractLow heart rate variability (HRV) has been widely reported as a predictor for increased mortality. However, the molecular mechanisms are poorly understood. Therefore, this study aimed to identify novel genetic loci associated with HRV and assess the association of phenotypic HRV and genetically predicted HRV with mortality. In a GWAS of 46,075 European ancestry individuals from UK biobank, we identified 17 independent genome-wide significant genetic variants in 16 loci associated with HRV traits. Notably, eight of these loci (RNF220, GNB4, LINCR-002, KLHL3/HNRNPA0, CHRM2, KCNJ5, MED13L, and C160rf72) have not been reported previously. In a prospective phenotypic relationship between HRV and mortality during a median follow-up of seven years, individuals with lower HRV had higher risk of dying from any cause. Genetically predicted HRV, as determined by the genetic risk scores, was not associated with mortality. To the best of our knowledge, the findings provide novel biological insights into the mechanisms underlying HRV. These results also underline the role of the cardiac autonomic nervous system, as indexed by HRV, in predicting mortality.
The impact of imputation quality on machine learning classifiers for datasets with missing values
Authors: Shadbahr Tolou , Roberts Michael , Stanczuk Jan , Gilbey Julian , Teare Philip , Dittmer Sören , Thorpe Matthew , Torné Ramon Viñas , Sala Evis , Lió Pietro , Patel Mishal , Preller Jacobus ,   AIX-COVNET Collaboration, Selby Ian , Breger Anna , Weir-McCall Jonathan R. , Gkrania-Klotsas Effrossyni , Korhonen Anna , Jefferson Emily , Langs Georg , Yang Guang , Prosch Helmut , Babar Judith , Escudero Sánchez Lorena , Wassin Marcel , Holzer Markus , Walton Nicholas , Lió Pietro , Rudd James H. F. , Mirtti Tuomas , Rannikko Antti Sakari , Aston John A. D. , Tang Jing , Schönlieb Carola-Bibiane 
Published: October 2023

Abstract
Background
Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial. Missing data is found in most real-world datasets and these missing values are typically imputed using established methods, followed by classification of the now complete samples. The focus of the machine learning researcher is to optimise the classifier’s performance.

Methods
We utilise three simulated and three real-world clinical datasets with different feature types and missingness patterns. Initially, we evaluate how the downstream classifier performance depends on the choice of classifier and imputation methods. We employ ANOVA to quantitatively evaluate how the choice of missingness rate, imputation method, and classifier method influences the performance. Additionally, we compare commonly used methods for assessing imputation quality and introduce a class of discrepancy scores based on the sliced Wasserstein distance. We also assess the stability of the imputations and the interpretability of model built on the imputed data.

Results
The performance of the classifier is most affected by the percentage of missingness in the test data, with a considerable performance decline observed as the test missingness rate increases. We also show that the commonly used measures for assessing imputation quality tend to lead to imputed data which poorly matches the underlying data distribution, whereas our new class of discrepancy scores performs much better on this measure. Furthermore, we show that the interpretability of classifier models trained using poorly imputed data is compromised.

Conclusions
It is imperative to consider the quality of the imputation when performing downstream classification as the effects on the classifier can be considerable.
Effectiveness of Stuttering Modification Treatment in School-Age Children Who Stutter: A Randomized Clinical Trial
Authors: Kohmäscher Anke , Primaßin Annika , Heiler Sabrina , Avelar Patricia Da Costa , Franken Marie-Christine , Heim Stefan 
Published: October 2023

Purpose:
This study investigated the effectiveness of the stuttering modification intervention Kinder Dürfen Stottern (KIDS) in school-age children who stutter.

Method:
Seventy-three children who stutter were included in this multicenter, two-group parallel, randomized, wait-list controlled trial with a follow-up of 12 months. Children aged 7–11 years were recruited from 34 centers for speech therapy and randomized to either the immediate-treatment group or the 3 months delayed-treatment group. KIDS was provided by 26 clinicians who followed a treatment manual. Although the primary outcome measure was the impact of stuttering (Overall Assessment of the Speaker's Experience of Stuttering–School-Age [OASES-S]), the secondary outcomes included objective and subjective data on stuttering severity.

Results:

At 3 months postrandomization, the mean score changes of the OASES-S differed significantly between the experimental (
n
= 33) and control group (
n
= 29;
p
= .026). Furthermore, treatment outcomes up to 12 months were analyzed (
n
= 59), indicating large effects of time on the OASES-S score (
p
< .001, partial η
2
=
.324). This was paralleled by significant improvements in parental ratings and objective ratings (stuttering severity, frequency, and physical concomitants).

Conclusions:
The significant short-term treatment effects in the OASES-S are in line with the (initial) focus of KIDS on cognitive and affective aspects of stuttering. Over 12 months, these changes were maintained and accompanied by behavioral improvements. The results suggest that individual treatment with KIDS is an adequate treatment option for this age group.

Supplemental Material:

https://doi.org/10.23641/asha.24207864
Overview of Issues in Autism Intervention Research: Research Design and Reporting
Authors: Bottema-Beutel Kristen , Sandbank Micheal , Woynaroski Tiffany 
Published: October 2023

Purpose:
Neurodiversity-affirming practices for people with autism need to be backed by rigorous evidence of effectiveness. We discuss aspects of research design and reporting in autism intervention research that should be considered by intervention providers when providing evidence-based practices to support people with autism. We describe risks of bias, which are features of the study design that make it more likely that ineffective interventions will show evidence of effectiveness; social validation, which are procedures that determine community members' views on the intervention goals, procedures, and outcomes; the design of intervention outcome variables, including the extent to which they index lasting, meaningful change; adverse event monitoring and reporting, which is the extent to which researchers track and transparently communicate negative events that occur during or after participation in the intervention; and conflicts of interest (COIs), which are relationships held by the researcher that could result in positive researcher benefits for showing particular outcomes in their studies. We discuss several systematic reviews and evaluations of autism intervention literature that have explored the extent to which researchers have adhered to ethical guidelines around each of these issues.

Conclusions:
Risks of bias are prevalent in this literature, social validation is rarely rigorously conducted, and positive intervention outcomes tend to index narrow, specific change. Additionally, researchers rarely monitor or report adverse events despite evidence that they occur, and they often fail to disclose COIs or falsely claim not to have them. Clinicians and researchers should be aware of these features of autism intervention studies, so that they can make informed decisions as new, and hopefully improved, research is produced.
A novel fault location strategy based on Bi‐LSTM for MMC‐HVDC systems
Authors: Inwumoh Jude , Baguley Craig , Madawala Udaya , Gunawardane Kosala 
Published: October 2023

AbstractThe integration of modular multilevel converters (MMCs) with high voltage direct current (HVDC) transmission systems is an efficient method for transporting electricity from distant renewable energy sources to demand centres. However, MMC‐HVDC systems face reliability challenges during DC overcurrent faults, often caused by component failures that can lead to HVDC network shutdowns. Consequently, a reliable fault location approach is crucial for grid protection and restoration, aiding in fault isolation and alternate power flow identification. Conventional fault location methods struggle with manual protective threshold setting, susceptibility to fault resistance and noise, and the need for communication channels, resulting in signal delays. In multi‐terminal HVDC networks, fault location becomes even more complex due to poor selectivity and sensitivity in traditional schemes. This study proposes a robust fault location approach based on bidirectional long short‐term memory (bi‐LSTM). The method offers a simplified decision‐making model with low computational requirements, utilizing fault features from one end of the network, eliminating the need for a communication channel. Remarkably, this approach achieves high fault location accuracy, even with varying fault types, resistances, and noise levels, as demonstrated by an MSE of 0.006 and a percentage error below 1% in simulations conducted using a real‐time simulator with MATLAB/Simulink.
Cold atomic gas identified by H I self-absorption
Authors: Syed J. , Beuther H. , Goldsmith P. F. , Henning Th. , Heyer M. , Klessen R. S. , Stil J. M. , Soler J. D. , Anderson L. D. , Urquhart J. S. , Rugel M. R. , Johnston K. G. , Brunthaler A. 
Published: October 2023

Context. Stars form in the dense interiors of molecular clouds. The dynamics and physical properties of the atomic interstellar medium (ISM) set the conditions under which molecular clouds and eventually stars form. It is, therefore, critical to investigate the relationship between the atomic and molecular gas phase to understand the global star formation process.
Aims. Using the high angular resolution data from The H I/OH/Recombination (THOR) line survey of the Milky Way, we aim to constrain the kinematic and physical properties of the cold atomic hydrogen gas phase toward the inner Galactic plane.
Methods. H I self-absorption (HISA) has proven to be a viable method to detect cold atomic hydrogen clouds in the Galactic plane. With the help of a newly developed self-absorption extraction routine (astroSABER), we built upon previous case studies to identify H I self-absorption toward a sample of giant molecular filaments (GMFs).
Results. We find the cold atomic gas to be spatially correlated with the molecular gas on a global scale. The column densities of the cold atomic gas traced by HISA are usually on the order of 1020 cm−2 whereas those of molecular hydrogen traced by 13CO are at least an order of magnitude higher. The HISA column densities are attributed to a cold gas component that accounts for a fraction of ~5% of the total atomic gas budget within the clouds. The HISA column density distributions show pronounced log-normal shapes that are broader than those traced by H I emission. The cold atomic gas is found to be moderately supersonic with Mach numbers of approximately a few. In contrast, highly supersonic dynamics drive the molecular gas within most filaments.
Conclusions. While H I self-absorption is likely to trace just a small fraction of the total cold neutral medium within a cloud, probing the cold atomic ISM by the means of self-absorption significantly improves our understanding of the dynamical and physical interaction between the atomic and molecular gas phase during cloud formation.
The role of radial migration in open cluster and field star populations withGaiaDR3
Authors: Viscasillas Vázquez C. , Magrini L. , Spina L. , Tautvaišienė G. , Van der Swaelmen M. , Randich S. , Sacco G. G. 
Published: October 2023

Context.The survival time of a star cluster depends on its total mass, density, and thus size, as well as on the environment in which it was born and in which lies. Its dynamical evolution is influenced by various factors such as gravitational effects of the Galactic bar, spiral structures, and molecular clouds. Overall, the factors that determine the longevity of a cluster are complex and not fully understood.Aims.This study aims to investigate whether open clusters and field stars respond differently to the perturbations that cause radial migration. In particular, we aim to understand the nature of the oldest surviving clusters.Methods.We compared the time evolution of the kinematic properties of twoGaiaDR3 samples. The first sample is composed of ∼40 open clusters and the second one of ∼66 000 main sequence turn off field stars. Both of the samples are composed of stars selected with the same quality criterion, and they belong to the thin disc, are in a similar metallicity range, are located in the same Galactocentric region [7.5–9 kpc], and have ages greater than 1 Gyr. We performed a statistical analysis comparing the properties of the samples of the field stars and of the open clusters.Results.A qualitative comparison of kinematic and orbital properties revealed that clusters younger than 2–3 Gyr are more resistant to perturbations than field stars, and they move along quasi-circular orbits. Conversely, clusters older than approximately 3 Gyr have more eccentric and inclined orbits than isolated stars in the same age range. Such orbits lead the older clusters to reach higher elevations on the Galactic plane, maximising their probability to survive several more gigayears. A formal statistical analysis revealed that there are differences among the time evolution of most of the kinematic and orbital properties of the field stars and open clusters. However, the comparison between some properties (e.g.,VϕandLZ) do not reach a sufficient statistical significance.Conclusions.Our results suggest that the oldest surviving clusters are usually more massive and move on orbits with a higher eccentricity. Although they are still reliable tracers of the Galaxy’s past composition, they do not reflect the composition of the place where they are currently found. Therefore, we cannot avoid considering kinematic properties when comparing data and models of chemical evolution and also taking into account the intrinsic differences between clusters and isolated stars. To validate the results, new studies that increase the sample of open clusters, especially at older ages, are needed.
White dwarf Random Forest classification through Gaia spectral coefficients
Authors: García-Zamora Enrique Miguel , Torres Santiago , Rebassa-Mansergas Alberto 
Published: October 2023

Context. The third data release of Gaia has provided approximately 220 million low resolution spectra. Among these, about 100 000 correspond to white dwarfs. The magnitude of this quantity of data precludes the possibility of performing spectral analysis and type determination by human inspection. In order to tackle this issue, we explore the possibility of utilising a machine learning approach, based on a Random Forest algorithm.
Aims. Our goal is to analyse the viability of the Random Forest algorithm for the spectral classification of the white dwarf population within 100 pc from the Sun, based on the Hermite coefficients of Gaia spectra.
Methods. We utilised the assigned spectral type from the Montreal White Dwarf Database for training and testing our Random Forest algorithm. Once validated, our algorithm model was applied to the rest of the unclassified white dwarfs within 100 pc. First, we started by classifying the two major spectral type groups of white dwarfs: hydrogen-rich (DA) and hydrogen-deficient (non-DA). Next, we explored the possibility of classifying the various spectral subtypes, including the secondary spectral types in some cases.
Results. Our Random Forest classification presented a very high recall (>80%) for DA and DB white dwarfs, and a very high precision (>90%) for DB, DQ, and DZ white dwarfs. As a result we have assigned a spectral type to 9446 previously unclassified white dwarfs: 4739 DAs, 76 DBs (60 of them DBAs), 4437 DCs, 132 DZs, and 62 DQs (nine of them DQpec).
Conclusions. Despite the low resolution of Gaia spectra, the Random Forest algorithm applied to the Gaia spectral coefficients proves to be a highly valuable tool for spectral classification.
The existence of hot X-ray onsets in solar flares
Authors: Battaglia Andrea Francesco , Hudson Hugh , Warmuth Alexander , Collier Hannah , Jeffrey Natasha L. S. , Caspi Amir , Dickson Ewan C. M. , Saqri Jonas , Purkhart Stefan , Veronig Astrid M. , Harra Louise , Krucker Säm 
Published: October 2023

Context. It is well known among the scientific community that solar flare activity often begins well before the main impulsive energy release. However, a consistent explanation for this phenomenon has not yet been established.
Aims. Our aim is to investigate the earliest phase of four distinct flares observed by Solar Orbiter/STIX and determine the relationships of the newly heated plasma to flare structure and dynamics.
Methods. The analysis focuses on four events that were observed from both Earth and Solar Orbiter, which allows for a comparison of STIX observations with those of GOES/XRS and SDO/AIA. The early phases of the events were studied using STIX and GOES spectroscopic analysis to investigate the evolution of the physical parameters of the plasma, including the isothermal temperature and emission measure. Furthermore, to determine the location of the heated plasma, STIX observations were combined with AIA images.
Results. The events with clear emission prior to the impulsive phase show elevated temperatures (> 10 MK) from the very beginning, which indicates that energy release started before any detection by STIX. Although the temperature shows little variation during the initial phase, the emission measure increases by about two orders of magnitude, implying a series of incrementally greater energy releases. The spectral analysis of STIX and GOES from the very first time bins suggests that the emission has a multi-thermal nature, with a hot component of more than 10 MK. Alternative heating mechanisms may be more significant during this phase, since nonthermal emission, as observed by STIX, is only detected later. STIX and AIA images reveal the presence of more compact sources of hot plasma early in the flare that originate from different locations with respect to the standard loop-top source that is observed later in the flare. However, because extended bremsstrahlung sources are much more difficult to detect than compact sources, there might be additionally heated plasma in the loop-top during hot onsets.
Conclusions. This analysis confirms the existence of “hot onsets”, with STIX detecting the hot onset pattern even earlier than GOES. These elevated temperatures imply that energy release actually begins well before any detection by STIX. Therefore, hot onsets may be significant in the initiation, early development, or even prediction of solar flares.
Patient radiation doses from adult CT examinations at the Souss Massa Regional Hospital
Authors: EL Fahssi M. , Semghouli S. , Amaoui B. , Jroundi L. , Çaoui M. 
Published: October 2023

Objective: This study aimed to assess patient radiation doses, and to establish diagnostic reference levels for Adult CT examinations at the Souss Massa Regional Hospital, Morocco.
Method: Data from 6 CT examinations were collected between January and June 2023 at the Souss Massa Regional Hospital, including patient age, sex, weight, and height, as well as scanner acquisition parameters such as the number of series, use of contrast media, rotation time plus slice thickness, the displayed Computed Tomography Dose Index (CTDIvol), and the Dose Length Product (DLP). Diagnostic reference levels (DRLs) were calculated for each type of CT examination by estimating the 75% percentile of CTDIvol and DLP. The effective dose is calculated using the following formula: E(mSv) = EDLP × DLP (mGy.cm). The data were statistically analyzed using SPSS version 21.0 software.
Results: DRLs in terms of CTDIvol, and DLP for the brain without contrast media are 64,45 mGy, and 1405,77 mGy.cm respectively. For chest CT without contrast media, they are 11,13 mGy, and 417,73 mGy.cm respectively. The data from the abdominal CT show that the CTDIvol (9,74 mGy) and DLP (529,31 mGy.cm) values with contrast media are higher than those without contrast media, which are (9,35 mGy) and (515,21 mGy.cm) respectively. DRls in terms of CTDIvol and DLP for abdomen and pelvis (AP) CT with contrast media are 8,14 mGy and 444,51 mGy.cm respectively. For chest abdomen and pelvis (CAP) with contrast media they are 8,51 mGy, and 571,30 mGy.cm respectively. The effective doses were 2,37, 6,50, 6,24, 6,76, 5,07, 7,13 mSv for the brain without contrast media, chest without contrast media, abdomen without contrast media, abdomen with contrast media, AP with contrast media, and CAP respectively.
Conclusion: Adapting CT protocols according to the morphology of patients and the conditions under which each examination is performed can help maintain the doses received by patients at an optimum level.