bluuebunny/crossref_metadata_2025_split huggingface dataset:
Online Surveys in Latin America
Authors: Castorena Oscar , Lupu Noam , Schade Maita , Zechmeister Elizabeth J. 
Published: January 2023

ABSTRACTOnline surveys of public opinion are less expensive and faster to administer than other surveys. However, nonprobability online samples diverge from the gold standard of probabilistic sampling. Although scholars have examined the quality of nonprobability samples in the United States and Europe, we know little about how these samples perform in developing contexts. We use nine online surveys fielded in six Latin American countries to examine the bias in these samples. We also ask whether two common tools that researchers use to mitigate sample bias—post-stratification and sample matching—improve these online samples. We find that online samples in the region exhibit high levels of bias, even in countries where Internet access is widespread. We also find that post-stratification does little to improve sample quality; sample matching outperforms the provider’s standard approach, but the gains are substantively small. This is partly because unequal Internet access and lack of investment in panel recruitment means that providers are unlikely to have enough panelists in lower socioeconomic categories to draw representative online samples, regardless of the sampling method. Researchers who want to draw conclusions about the attitudes or behaviors of the public as a whole in contexts like Latin America still need probability samples.
A cloud-cloud collision in Sgr B2? 3D simulations meet SiO observations
Authors: Banda-Barragán Wladimir E. , Armijos-Abendaño Jairo , Dénes Helga 
Published: January 2023

AbstractWe compare the properties of shocked gas in Sgr B2 with maps obtained from 3D simulations of a collision between two fractal clouds. In agreement with 13CO(1-0) observations, our simulations show that a cloud-cloud collision produces a region with a highly turbulent density substructure with an average . Similarly, our numerical multi-channel shock study shows that colliding clouds are efficient at producing internal shocks with velocities of 5 − 50 km s−1 and Mach numbers of ∼ 4 − 40, which are needed to explain the ∼ 10−9 SiO abundances inferred from our SiO(2-1) IRAM observations of Sgr B2. Overall, we find that both the density structure and the shocked gas morphology in Sgr B2 are consistent with a Myr-old cloud-cloud collision. High-velocity shocks are produced during the early stages of the collision and can ignite star formation, while moderate- and low-velocity shocks are important over longer time-scales and can explain the extended SiO emission in Sgr B2.
Dynamic complexity based analysis on the relationship between solar activity and cosmic ray intensity
Authors: Vipindas V. , Sumesh Gopinath , Vinod Kumar R. , Girish T.E. 
Published: January 2023

AbstractThe Earth’s atmosphere is incessantly bombarded by energetic charged particles called cosmic rays (CR) which are having either solar or non-solar origin. Analysis based on information theoretic estimators can be effectively employed as a potential technique to analyze the dynamical changes in cosmic ray intensity during different solar cycles. In the present study, dynamical complexity based analysis using Jensen-Shannon divergence (JSD) has been employed which reveals the existence of some peculiar fluctuation properties in CRI flux at Jung neutron monitor station. JSD based dynamical complexity analyses confirm the existence of difference in dynamical properties of CR flux during solar cycles 20-21 and 22-23.
Formation process of the Orion Nebula Cluster
Authors: Fujii Michiko S. , Wang Long , Saitoh Takayuki R. , Hirai Yutaka , Shimajiri Yoshito 
Published: January 2023

AbstractThe Orion Nebula Cluster (ONC) is one of the nearest open clusters, which we can directly compare to numerical simulations. We performed a simulation of star cluster formation similar to the ONC using our new N-body/smoothed particle hydrodynamics code, ASURA+BRIDGE. We found that the hierarchical formation of star clusters via clump mergers can explain the observed three peaks in the stellar age distribution as well as the dynamically anisotropic structures of the ONC.
Thermal atmospheric escape of close-in exoplanets
Authors: Kalinicheva Eugenia S. , Shematovich Valery I. 
Published: January 2023

AbstractIn this work we applied the previously developed self-consistent 1D model of hydrogen-helium atmosphere with suprathermal electrons to close-in hot neptune GJ 436 b. The obtained height profile of density shows the two-scale structure of the planetary atmosphere. The mass-loss rate is found to be about .
X-ray spectral and image spatial models of NGC 3081 with Chandra data
Authors: Kompaniiets O.V. , Babyk Iu.V. , Vasylenko A.A. , Izviekova I.O. , Vavilova I.B. 
Published: January 2023

AbstractThe physical properties of AGN such as accretion rate, column density, temperature of hot corona and other characteristics can be found from X-ray spectral data. We present the results of spatial and spectral analysis for Sy2 type galaxy NGC 3081 obtained with different mathematical tools of the Chandra Interactive Analysis of Observations software. We found evidence of extended emission in 0.5-3.0 keV as well as derived parameters for model A: photon index , column density , warm component and hot component . We detected the presence of a component of the reflection spectrum, Fe Kα emission line with and .
Clustering stellar pairs to detect extended stellar structures
Authors: Sapozhnikov Sergey , Kovaleva Dana 
Published: January 2023

AbstractGaia data allows for search for extended stellar structures in phase (coordinates plus velocities) space. We describe a method of using DBSCAN clustering algorithm, which is used to group closely-packed-together data points, to a list of preliminary selected pairs of stars, with parameters expected to be found within stellar streams and comoving groups: loose structures in which stars are not gravitationally bound, but do share motion and evolutionary properties. To test our approach, we construct a model population of background stars, and use pair-constructing and clustering algorithms on it. Results show that transitioning to a list of pairs sharply reveals structures not presented in background model, which then become more apparent targets in coordinate-velocity phase space for DBSCAN algorithm thanks to now increased relative density of the extended stellar structure.
A novel generative method for star clusters from hydro-dynamical simulations
Authors: Torniamenti Stefano 
Published: January 2023

AbstractMost stars form in clumpy and sub-structured clusters. These properties also emerge in hydro-dynamical simulations of star-forming clouds, which provide a way to generate realistic initial conditions for N-body runs of young stellar clusters. However, producing large sets of initial conditions by hydro-dynamical simulations is prohibitively expensive in terms of computational time. We introduce a novel technique for generating new initial conditions from a given sample of hydro-dynamical simulations, at a tiny computational cost. In particular, we apply a hierarchical clustering algorithm to learn a tree representation of the spatial and kinematic relations between stars, where the leaves represent the single stars and the nodes describe the structure of the cluster at larger and larger scales. This procedure can be used as a basis for the random generation of new sets of stars, by simply modifying the global structure of the stellar cluster, while leaving the small-scale properties unaltered.
Predicting the Expansion of Supernova Shells Using Deep Learning toward Highly Resolved Galaxy Simulations
Authors: Hirashima Keiya , Moriwaki Kana , Fujii Michiko , Hirai Yutaka , Saitoh Takayuki , Makino Junichiro 
Published: January 2023

AbstractThe load imbalance and communication overhead of parallel computing are crucial bottlenecks for galaxy simulations. A successful way to improve the scalability of astronomical simulations is a Hamiltonian splitting method, which needs to identify such regions integrated with smaller timesteps than the global timestep for integrating the entire galaxy. In the case of galaxy simulations, the regions inside supernova (SN) shells require the smallest steps. We developed the deep learning model to forecast the region affected by the SN shell’s expansion during one global step. In addition, we identified the particles with small timesteps using image processing. We can identify target particles using our method with a higher identification rate (88 % to 98 % on average) and lower “non-target”-to-“target” fraction (6.4 to 5.5 on average) compared to the analytic approach with the Sedov-Taylor solution. Our method using Hamiltonian splitting and deep learning will improve the performance of extremely high-resolution galaxy simulations.
Multi-component MHD model for hydrogen-helium extended envelope of hot Jupiter
Authors: Gladysheva Y.G. , Zhilkin A.G. , Bisikalo D.V. 
Published: January 2023

AbstractWe describe a numerical model of hot Jupiter extended envelope that interacts with stellar wind. Our model is based on approximation of multi-component magnetic hydrodynamic. The processes of ionization, recombination, dissosiation and chemical reactions in hydrogen-helium envelope are taken into account. In particular, the ionization of neutral hydrogen atoms takes place due to processes of photo-ionization, charge-exchange and thermal collisions. Further, this model is supposed to be used for research on biomarkers’ dynamics in extended envelopes of hot Jupiters.
An idealized setup for cosmological evolution of baryonic gas in isolated halos
Authors: Dattathri S. , Sharma P. 
Published: January 2023

AbstractWe use hydrodynamical simulations to study the evolution of baryonic gas in a cosmologically evolving dark matter halo. We model both the inner and outer regions of the halo using a density profile that transitions from an inner NFW profile to a flat profile far from the halo. Metallicity-dependent radiative cooling and AGN jet feedback are implemented, which lead to heating and cooling cycles in the core. We analyze the evolution of gas and the central supermassive black hole (SMBH) across cosmological time. We find that the properties of the gas and the SMBH are correlated across halo masses and feedback efficiencies.
Simulating star formation in spiral galaxies
Authors: Rieder Steven , Dobbs Clare , Bending Thomas , Liow Kong You , Wurster James 
Published: January 2023

AbstractWe present Ekster, a new method for simulating the formation and dynamics of individual stars in a relatively low-resolution gas background. Here, we use Ekster to simulate star cluster formation in two different regions from each of two galaxy models with different spiral potentials. We simulate these regions for 3 Myr to study where and how star clusters form. We find that massive GMC regions form more massive clusters than sections of spiral arms. Additionally we find that clusters form both by accreting gas and by merging with other proto-clusters, the latter happening more frequently in the denser GMC regions.
The Deep‐Water Plume in the Northwestern Weddell Sea, Antarctica: Mean State, Seasonal Cycle and Interannual Variability Influenced by Climate Modes
Authors: Llanillo Pedro J. , Kanzow Torsten , Janout Markus A. , Rohardt Gerd 
Published: January 2023

AbstractWe provide an updated estimate of the annual‐mean, seasonal cycle and interannual variability of the transports and properties of the Weddell Sea Bottom Water (WSBW) plume in the northwestern Weddell Sea. For this we used a densely instrumented mooring array deployed across the continental slope between January 2017 and January 2019. We found that the annual‐mean WSBW transport is 3.4 ± 1.5 Sv, corresponding to a cross‐section area of 35 km2 and a maximum thickness of 203 m. The annual mean transport‐weighted properties of WSBW are −0.99°C (Θ), 34.803 g/kg (SA) and 28.44 kg/m3 (γn). The WSBW is characterized by 3 bottom‐intensified velocity cores, which display seasonal variations in flow speed and transport different varieties of WSBW. The seasonal peak of WSBW transport and density is reached in May (4.7 Sv, 28.443 kg m−3) while the minimum values are observed in February (2.8 Sv, 28.435 kg m−3). The coldest WSBW is found between March and May, and the warmest between August and October. The density decrease of WSBW observed in the austral autumn of 2018 can be explained by warmer ambient waters being entrained during the formation of WSBW. This was enabled by the weakening of the along‐shore winds associated with a positive Southern Annular Mode index, reinforced by a La Niña event in early 2018. The synchronous decrease of total WSBW transport and volume between September 2018 and February 2019 indicates a reduction in the export of the dense precursors of WSBW from the Weddell Sea continental shelf.
TRIM15 forms a regulatory loop with the AKT/FOXO1 axis and LASP1 to modulate the sensitivity of HCC cells to TKIs
Authors: Yang Chong , Jin Xin , Liu Xingchao , Wu Gang , Yang Wenhao , Pang Beichuan , Jiang Jipeng , Liao Dongxu , Zhang Yu 
Published: January 2023

AbstractFor patients with advanced or metastatic Hepatocellular carcinoma (HCC) who are not suitable for surgical resection, systemic therapy has been considered to be the standard treatment. In recent years, a small subset of patients with unresectable HCC have been benefit from tyrosine kinase inhibitors (TKIs), and the overall survival time of these patients is significantly increased. However, all responders ultimately develop resistance to TKI treatment. The tripartite motif (TRIM) family member TRIM15 acts as an E3 ligase to mediate the polyubiquitination of substrates in cells. However, the biological role of TRIM15 in HCC is still an enigma. In our study, our results demonstrated that TRIM15 was abnormally upregulated in liver cancer cells after treated with TKIs and that this upregulation of TRIM15 contributed to TKI resistance in liver cancer cells. Then, we demonstrated that the upregulation of TRIM15 after TKI treatment was mediated by the AKT/FOXO1 axis. Moreover, we demonstrated that TRIM15 induced the nuclear translocation of LASP1 by mediating its K63-linked polyubiquitination, which modulated sensitivity to TKIs by increasing the phosphorylation of AKT and the expression of Snail in liver cancer cells. Collectively, we identified a novel AKT/FOXO1/TRIM15/LASP1 loop in cells, which provided potential candidates for overcoming TKI resistance in HCC.
Saline irrigation versus gauze wiping and suction only for peritoneal decontamination during laparoscopic repair for perforated peptic ulcer disease
Authors: Tsao Lien-Cheng , Lin Joseph , Lin Kuo-Hua , Ng Sze-Yuin , Huang Cheng-Yen , Hung Yu-Ju , Wu Szu-Chia , Gao Shih-Ling , Yu Shu-Fen , Lin Chi-Chien , Chang Wei-Jung 
Published: January 2023

AbstractThe aim of current single-center study was to compare the short-term outcome of suction and gauze wiping alone versus the irrigation and suction technique for peritoneal decontamination among patients who underwent laparoscopic repair of PPU. Using data from our institution’s prospectively maintained database, 105 patients who underwent laparoscopic repair were enrolled in this study. The participants were further divided into the group who received peritoneal irrigation (irrigation group, n = 67) and group who received gauze wiping and suction only (suction only group, n = 38). The irrigation group had a longer operative time (140 vs. 113 min, p = 0.0001), higher number of drainage tubes (38.8% vs. 0%, p < 0.0001) and a higher incidence of intra-abdominal abscess (10.4% vs. 0%, p = 0.0469) than the suction only group. Peritoneal irrigation may be associated with a prolonged operative time and a higher number of abdominal drains. Meanwhile, gauze wiping and suction may be sufficient for peritoneal decontamination during the laparoscopic repair of PPU as further infectious complications are not observed.
Y-type hexagonal ferrite-based band-pass filter with dual magnetic and electric field tunability
Authors: Popov Maksym , Xiong Yuzan , Zavislyak Igor , Chumak Hryhorii , Fedorchuk Oleksandr , Saha Sujoy , Bidthanapally Rao , Qu Hongwei , Page Michael R. , Srinivasan Gopalan 
Published: January 2023

AbstractThis work is on the design, fabrication and characterization of a hexagonal ferrite band-pass filter that can be tuned either with a magnetic field or an electric field. The filter operation is based on a straight-edge Y-type hexagonal ferrite resonator symmetrically coupled to the input and output microstrip transmission lines. The Zn2Yfilter demonstrated magnetic field tunability in the 8–12 GHz frequency range by applying an in-plane bias magnetic field H0 provided by a built-in permanent magnet. The insertion loss and 3 dB bandwidth within this band were 8.6 ± 0.4 dB and 350 ± 40 MHz, respectively. The electric field E tunability of the pass-band of the device was facilitated by the nonlinear magnetoelectric effect (NLME) in the ferrite. The E-tuning of the center frequency of the filter by (1150 ± 90) MHz was obtained for an input DC electric power of 200 mW. With efforts directed at a significant reduction in the insertion loss, the compact and power efficient magnetic and electric field tunable Zn2Y band-pass filter has the potential for use in novel reconfigurable RF/microwave devices and communication systems.
Structural brain abnormalities and their association with language impairment in school-aged children with Autism Spectrum Disorder
Authors: Arutiunian Vardan , Gomozova Militina , Minnigulova Alina , Davydova Elizaveta , Pereverzeva Darya , Sorokin Alexander , Tyushkevich Svetlana , Mamokhina Uliana , Danilina Kamilla , Dragoy Olga 
Published: January 2023

AbstractLanguage impairment is comorbid in most children with Autism Spectrum Disorder (ASD) but its neural basis is poorly understood. Using structural magnetic resonance imaging (MRI), the present study provides the whole-brain comparison of both volume- and surface-based characteristics between groups of children with and without ASD and investigates the relationships between these characteristics in language-related areas and the language abilities of children with ASD measured with standardized tools. A total of 36 school-aged children participated in the study: 18 children with ASD and 18 age- and sex-matched typically developing controls. The results revealed that multiple regions differed between groups of children in gray matter volume, gray matter thickness, gyrification, and cortical complexity (fractal dimension). White matter volume and sulcus depth did not differ between groups of children in any region. Importantly, gray matter thickness and gyrification of language-related areas were related to language functioning in children with ASD. Thus, the results of the present study shed some light on the structural brain abnormalities associated with language impairment in ASD.
Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning
Authors: Nené Nuno R. , Ney Alexander , Nazarenko Tatiana , Blyuss Oleg , Johnston Harvey E. , Whitwell Harry J. , Sedlak Eva , Gentry-Maharaj Aleksandra , Apostolidou Sophia , Costello Eithne , Greenhalf William , Jacobs Ian , Menon Usha , Hsuan Justin , Pereira Stephen P. , Zaikin Alexey , Timms John F. 
Published: January 2023

AbstractBackgroundEarlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough.MethodsThe primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets.ResultsHere we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75–1.0), sensitivity of 92% (95% CI 0.54–1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74–0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17–0.83, at 90% specificity).ConclusionsThe ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.
Sleep-Based Memory Consolidation Stabilizes Perceptual Learning of Noise-Vocoded Speech
Authors: Drouin Julia R. , Zysk Victoria A. , Myers Emily B. , Theodore Rachel M. 
Published: January 2023

Purpose:
Sleep-based memory consolidation has been shown to facilitate perceptual learning of atypical speech input including nonnative speech sounds, accented speech, and synthetic speech. The current research examined the role of sleep-based memory consolidation on perceptual learning for noise-vocoded speech, including maintenance of learning over a 1-week time interval. Because comprehending noise-vocoded speech requires extensive restructuring of the mapping between the acoustic signal and prelexical representations, sleep consolidation may be critical for this type of adaptation. Thus, the purpose of this study was to investigate the role of sleep-based memory consolidation on adaptation to noise-vocoded speech in listeners without hearing loss as a foundational step toward identifying parameters that can be useful to consider for auditory training with clinical populations.

Method:
Two groups of normal-hearing listeners completed a transcription training task with feedback for noise-vocoded sentences in either the morning or the evening. Learning was assessed through transcription accuracy before training, immediately after training, 12 hr after training, and 1 week after training for both trained and novel sentences.

Results:
Both the morning and evening groups showed improved comprehension of noise-vocoded sentences immediately following training. Twelve hours later, the evening group showed stable gains (following a period of sleep), whereas the morning group demonstrated a decline in gains (following a period of wakefulness). One week after training, the morning and evening groups showed equivalent performance for both trained and novel sentences.

Conclusion:
Sleep-consolidated learning helps stabilize training gains for degraded speech input, which may hold clinical utility for optimizing rehabilitation recommendations.