bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sub-stellar companions of intermediate-mass stars with CoRoT: CoRoT–34b, CoRoT–35b, and CoRoT–36b
Authors: Sebastian D , Guenther E W , Deleuil M , Dorsch M , Heber U , Heuser C , Gandolfi D , Grziwa S , Deeg H J , Alonso R , Bouchy F , Csizmadia Sz , Cusano F , Fridlund M , Geier S , Irrgang A , Korth J , Nespral D , Rauer H , Tal-Or L ,   the CoRoT-team
Published: August 2022

ABSTRACT
Theories of planet formation give contradicting results of how frequent close-in giant planets of intermediate mass stars (IMSs; $1.3\le M_{\star }\le 3.2\, \mathrm{M}_{\odot }$) are. Some theories predict a high rate of IMSs with close-in gas giants, while others predict a very low rate. Thus, determining the frequency of close-in giant planets of IMSs is an important test for theories of planet formation. We use the CoRoT survey to determine the absolute frequency of IMSs that harbour at least one close-in giant planet and compare it to that of solar-like stars. The CoRoT transit survey is ideal for this purpose, because of its completeness for gas-giant planets with orbital periods of less than 10 d and its large sample of main-sequence IMSs. We present a high precision radial velocity follow-up programme and conclude on 17 promising transit candidates of IMSs, observed with CoRoT. We report the detection of CoRoT–34b, a brown dwarf close to the hydrogen burning limit, orbiting a 1.1 Gyr A-type main-sequence star. We also confirm two inflated giant planets, CoRoT–35b, part of a possible planetary system around a metal-poor star, and CoRoT–36b on a misaligned orbit. We find that $0.12 \pm 0.10\, {{\ \rm per\ cent}}$ of IMSs between $1.3\le M_{\star }\le 1.6\, \mathrm{M}_{\odot }$ observed by CoRoT do harbour at least one close-in giant planet. This is significantly lower than the frequency ($0.70 \pm 0.16\, {{\ \rm per\ cent}}$) for solar-mass stars, as well as the frequency of IMSs harbouring long-period planets ($\sim 8\, {{\ \rm per\ cent}}$).
Abundance analysis of APOGEE spectra for 58 metal-poor stars from the bulge spheroid
Authors: Razera R , Barbuy B , Moura T C , Ernandes H , Pérez-Villegas A , Souza S O , Chiappini C , Queiroz A B A , Anders F , Fernández-Trincado J G , Friaça A C S , Cunha K , Smith V V , Santiago B X , Schiavon R P , Valentini M , Minniti D , Schultheis M , Geisler D , Sobeck J , Placco V M , Zoccali M 
Published: August 2022

ABSTRACTThe central part of the Galaxy hosts a multitude of stellar populations, including the spheroidal bulge stars, stars moved to the bulge through secular evolution of the bar, inner halo, inner thick disc, inner thin disc, as well as debris from past accretion events. We identified a sample of 58 candidate stars belonging to the stellar population of the spheroidal bulge, and analyse their abundances. The present calculations of Mg, Ca, and Si lines are in agreement with the ASPCAP abundances, whereas abundances of C, N, O, and Ce are re-examined. We find normal α-element enhancements in oxygen, similar to magnesium, Si, and Ca abundances, which are typical of other bulge stars surveyed in the optical in Baade’s Window. The enhancement of [O/Fe] in these stars suggests that they do not belong to accreted debris. No spread in N abundances is found, and none of the sample stars is N-rich, indicating that these stars are not second generation stars originated in globular clusters. Ce instead is enhanced in the sample stars, which points to an s-process origin such as due to enrichment from early generations of massive fast rotating stars, the so-called spinstars.
Biermann battery powered by resistive heating induced by cosmic ray streaming
Authors: Yokoyama Shota L , Ohira Yutaka 
Published: August 2022

ABSTRACT
It is recently proposed that cosmic rays generate a seed magnetic field in the early Universe. In this paper, we propose another generation mechanism of magnetic fields by cosmic rays, which is the Biermann battery driven by resistive heating induced by the streaming of cosmic rays. This mechanism is dominant in small-scale, low-temperature, and strongly ionized regions, compared with other previously proposed mechanisms. Because cosmic rays are expected to be accelerated after the death of the first stars, this mechanism can work during structure formation in the early Universe. We show that it makes the seed magnetic field with sufficient strength for the subsequent dynamo to amplify it to the micro Gauss level in the current galaxies.
A new emulated Monte Carlo radiative transfer disc-wind model: X-Ray Accretion Disc-wind Emulator – xrade
Authors: Matzeu G A , Lieu M , Costa M T , Reeves J N , Braito V , Dadina M , Nardini E , Boorman P G , Parker M L , Sim S A , Barret D , Kammoun E , Middei R , Giustini M , Brusa M , Cabrera J Pérez , Marchesi S 
Published: August 2022

ABSTRACT
We present a new X-Ray Accretion Disc-wind Emulator (xrade) based on the 2.5D Monte Carlo radiative transfer code that provides a physically motivated, self-consistent treatment of both absorption and emission from a disc wind by computing the local ionization state and velocity field within the flow. xrade is then implemented through a process that combines X-ray tracing with supervised machine learning. We develop a novel emulation method consisting in training, validating, and testing the simulated disc-wind spectra into a purposely built artificial neural network. The trained emulator can generate a single synthetic spectrum for a particular parameter set in a fraction of a second, in contrast to the few hours required by a standard Monte Carlo radiative transfer pipeline. The emulator does not suffer from interpolation issues with multidimensional spaces that are typically faced by traditional X-ray fitting packages such as xspec. xrade will be suitable to a wide number of sources across the black hole mass, ionizing luminosity, and accretion rate scales. As an example, we demonstrate the applicability of xrade to the physical interpretation of the X-ray spectra of the bright quasar PDS 456, which hosts the best-established accretion disc wind observed to date. We anticipate that our emulation method will be an indispensable tool for the development of high-resolution theoretical models, with the necessary flexibility to be optimized for the next generation microcalorimeters onboard future missions, like X-Ray Imaging and Spectroscopy Mission (XRISM)/Resolve and Athena/X-ray Integral Field Unit (X-IFU). This tool can also be implemented across a wide variety of X-ray spectral models and beyond.
Molecular flows in contemporary active galaxies and the efficacy of radio-mechanical feedback
Authors: Tamhane Prathamesh D , McNamara Brian R , Russell Helen R , Edge Alastair C , Fabian Andrew C , Nulsen Paul E J , Babyk Iurii V 
Published: August 2022

ABSTRACT
Molecular gas flows are analysed in 14 cluster galaxies (BCGs) centred in cooling hot atmospheres. The BCGs contain $10^{9}\!-\!10^{11}~\rm M_\odot$ of molecular gas, much of which is being moved by radio jets and lobes. The molecular flows and radio jet powers are compared to molecular outflows in 45 active galaxies within z &lt; 0.2. We seek to understand the relative efficacy of radio, quasar, and starburst feedback over a range of active galaxy types. Molecular flows powered by radio feedback in BCGs are ∼10–1000 times larger in extent compared to contemporary galaxies hosting quasar nuclei and starbursts. Radio feedback yields lower flow velocities but higher momenta compared to quasar nuclei, as the molecular gas flows in BCGs are usually ∼10–100 times more massive. The product of the molecular gas mass and lifting altitude divided by the AGN or starburst power – a parameter referred to as the lifting factor – exceeds starbursts and quasar nuclei by 2–3 orders of magnitude, respectively. When active, radio feedback is generally more effective at lifting gas in galaxies compared to quasars and starburst winds. The kinetic energy flux of molecular clouds generally lies below and often substantially below a few per cent of the driving power. We find tentatively that star formation is suppressed in BCGs relative to other active galaxies, perhaps because these systems rarely form molecular discs that are more impervious to feedback and are better able to promote star formation.
The Three Hundred: cluster dynamical states and relaxation period
Authors: Zhang Bowei , Cui Weiguang , Wang Yuhuan , Dave Romeel , De Petris Marco 
Published: August 2022

ABSTRACT
We introduce a new parameter λDS to quantify the dynamical state of galaxy clusters and test it using simulations from The Three Hundred cluster zoom suite. λDS is a combination of three previously used dynamical state measures, namely virial ratio, centre of mass offset, and substructure mass fraction, crafted to assume a double-Gaussian distribution, thereby yielding a natural division between relaxed and unrelaxed clusters where the Gaussians cross. Using dark matter-only simulations, we identify the optimal separator to be λDS = 3.424. We test this same criterion on two sets of fully hydrodynamical The Three Hundred runs (Gadget-X and GIZMO-SIMBA), and find only a weak dependence on the input baryonic physics. We correlate the evolution of λDS with the mass accretion history and find that halo mass changes of $\frac{\Delta M_{200}}{M_{200}} \lesssim 0.12$ do not typically alter the dynamical state. We examine the relaxation period, defined as the time taken to return to relaxation after becoming disturbed, and find a correlation between this relaxation period and the strength of halo mass change $\frac{\Delta M_{200}}{M_{200}}$. By fitting this correlation, we show that the relaxation period can be estimated from $\frac{\Delta M_{200}}{M_{200}}$ (even for multiple mass accretion events) with good accuracy.
Moon packing around an Earth-mass planet
Authors: Satyal Suman , Quarles Billy , Rosario-Franco Marialis 
Published: August 2022

ABSTRACT
All four giant planets in the Solar system host systems of multiple moons, whereas the terrestrial planets only host up to two moons. The Earth can capture small asteroids as temporary satellites, which begs the question as to how many moons could stably orbit the Earth, or an Earth-mass exoplanet. We perform a series of N-body simulations of closely spaced equal-mass moons in nested orbits around an Earth-mass planet orbiting a Sun-like star. The innermost moon begins near the host planet’s Roche radius, and the system is packed until the outermost moon begins near the stability limit for single moons. The initial spacing of the moons follows an iterative scheme commonly used for studies of compact planetary systems around single stars. For the three-moon system, we generate MEGNO maps to calculate periodic and chaotic regions and to identify the destabilizing mean motion resonances. Our calculations show that the maximum number of moons depends on the assumed masses of the satellites (Ceres-, Pluto-, and Luna-mass) that could maintain stable orbits in a tightly packed environment. Through our N-body simulations, we find stable configurations for up to 7 ± 1 Ceres-mass, 4 ± 1 Pluto-mass, and 3 ± 1 Luna-mass moons. However, outward tidal migration will likely play a substantial role in the number of moons on stable orbits over the 10 Gyr stellar lifetime of a Sun-like star.
The Role of Glia Underlying Acupuncture Analgesia in Animal Pain Models: A Systematic Review and Meta-Analysis
Authors: Yan Bing , Tang Shengyu , Zhang Yuqiu , Xiao Xiao 
Published: August 2022

AbstractBackgroundAs a traditional Chinese therapy, acupuncture is proposed worldwide as a treatment for pain and other health problems, but findings on acupuncture analgesia have been inconsistent because of its variable modalities of therapeutic intervention.ObjectiveThis study aimed to evaluate the existing animal studies for evidence on acupuncture and its effect on glia in association with a reduction in pain conditions.MethodsLiterature searches were performed in four English- and Chinese-language databases (Web of Science, PubMed, EMBASE, and CNKI) on October 8, 2021. Included studies reported the pain outcome (e.g., paw withdrawal latency, paw withdrawal threshold) and glia outcome (e.g., glial marker GFPA, Iba1, and OX42) in pain-induced animals during acupuncture treatment.ResultsFifty-two preclinical studies were included in the meta-analysis. A single acupuncture treatment in rodents had an analgesic effect, which was more effective in inflammatory pain than in neuropathic pain in the early phase of treatment. The analgesic efficacy became more curative after repeated acupuncture. Furthermore, acupuncture treatment could effectively inhibit the activity of astrocytes and microglia in both inflammatory pain and neuropathic pain in a time-course pattern.ConclusionsAcupuncture treatment improves analgesic effect in rodent pain conditions under the possible mechanism of glial inhibition. Therefore, these results provide an opportunity to evaluate the effectiveness of acupuncture analgesia and neuroinflammation in animal models to research further neurobiological mechanisms and to inform the design of future clinical trials.Study registrationPROSPERO (ID: CRD42020196011).
Prof. Koshiba and electron–positron physics
Authors: Yamada Sakue 
Published: August 2022

Abstract
Prof. Masatoshi Koshiba was the physicist who initiated the e+e− physics effort in Japan. The first attempt goes back to the 1960s. Following a hard time in the early days the attempt turned out to be successful, leading to a number of productive projects, and eventually supported his neutrino experiments. In this article we detail the history of how these projects developed and entangled.
Phylogenomic Analysis of the Parrots of the World Distinguishes Artifactual from Biological Sources of Gene Tree Discordance
Authors: Smith Brian Tilston , Merwin Jon , Provost Kaiya L , Thom Gregory , Brumfield Robb T , Ferreira Mateus , Mauck William M , Moyle Robert G , Wright Timothy F , Joseph Leo 
Published: August 2022

Abstract
Gene tree discordance is expected in phylogenomic trees and biological processes are often invoked to explain it. However, heterogeneous levels of phylogenetic signal among individuals within data sets may cause artifactual sources of topological discordance. We examined how the information content in tips and subclades impacts topological discordance in the parrots (Order: Psittaciformes), a diverse and highly threatened clade of nearly 400 species. Using ultraconserved elements from 96% of the clade’s species-level diversity, we estimated concatenated and species trees for 382 ingroup taxa. We found that discordance among tree topologies was most common at nodes dating between the late Miocene and Pliocene, and often at the taxonomic level of the genus. Accordingly, we used two metrics to characterize information content in tips and assess the degree to which conflict between trees was being driven by lower-quality samples. Most instances of topological conflict and nonmonophyletic genera in the species tree could be objectively identified using these metrics. For subclades still discordant after tip-based filtering, we used a machine learning approach to determine whether phylogenetic signal or noise was the more important predictor of metrics supporting the alternative topologies. We found that when signal favored one of the topologies, the noise was the most important variable in poorly performing models that favored the alternative topology. In sum, we show that artifactual sources of gene tree discordance, which are likely a common phenomenon in many data sets, can be distinguished from biological sources by quantifying the information content in each tip and modeling which factors support each topology. [Historical DNA; machine learning; museomics; Psittaciformes; species tree.]
PreS/MD: Predictor of Sensitization Hazard for Chemical Substances Released From Medical Devices
Authors: Alves Vinicius M , Borba Joyce V B , Braga Rodolpho C , Korn Daniel R , Kleinstreuer Nicole , Causey Kevin , Tropsha Alexander , Rua Diego , Muratov Eugene N 
Published: August 2022

AbstractIn the United States, a pre-market regulatory submission for any medical device that comes into contact with either a patient or the clinical practitioner must include an adequate toxicity evaluation of chemical substances that can be released from the device during its intended use. These substances, also referred to as extractables and leachables, must be evaluated for their potential to induce sensitization/allergenicity, which traditionally has been done in animal assays such as the guinea pig maximization test (GPMT). However, advances in basic and applied science are continuously presenting opportunities to employ new approach methodologies, including computational methods which, when qualified, could replace animal testing methods to support regulatory submissions. Herein, we developed a new computational tool for rapid and accurate prediction of the GPMT outcome that we have named PreS/MD (predictor of sensitization for medical devices). To enable model development, we (1) collected, curated, and integrated the largest publicly available dataset for GPMT results; (2) succeeded in developing externally predictive (balanced accuracy of 70%–74% as evaluated by both 5-fold external cross-validation and testing of novel compounds) quantitative structure-activity relationships (QSAR) models for GPMT using machine learning algorithms, including deep learning; and (3) developed a publicly accessible web portal integrating PreS/MD models that can predict GPMT outcomes for any molecule of interest. We expect that PreS/MD will be used by both industry and regulatory scientists in medical device safety assessments and help replace, reduce, or refine the use of animals in toxicity testing. PreS/MD is freely available at https://presmd.mml.unc.edu/.
Detection of Critical Spinal Epidural Lesions on CT Using Machine Learning
Authors: Harris Robert J. , Baginski Scott G. , Bronstein Yulia , Schultze Dietrich , Segel Kenneth , Kim Shwan , Lohr Jerry , Towey Steve , Shahi Nishit , Driscoll Ian , Baker Brian 
Published: July 2022

Background.
Critical spinal epidural pathologies can cause paralysis or death if untreated. Although magnetic resonance imaging is the preferred modality for visualizing these pathologies, computed tomography (CT) occurs far more commonly than magnetic resonance imaging in the clinical setting.

Objective.
A machine learning model was developed to screen for critical epidural lesions on CT images at a large-scale teleradiology practice. This model has utility for both worklist prioritization of emergent studies and identifying missed findings.

Materials and Methods.
There were 153 studies with epidural lesions available for training. These lesions were segmented and used to train a machine learning model. A test data set was also created using previously missed epidural lesions. The trained model was then integrated into a teleradiology workflow for 90 days. Studies were sent to secondary manual review if the model detected an epidural lesion but none was mentioned in the clinical report.

Results.
The model correctly identified 50.0% of epidural lesions in the test data set with 99.0% specificity. For prospective data, the model correctly prioritized 66.7% of the 18 epidural lesions diagnosed on the initial read with 98.9% specificity. There were 2.0 studies flagged for potential missed findings per day, and 17 missed epidural lesions were found during a 90-day time period. These results suggest almost half of critical spinal epidural lesions visible on CT imaging are being missed on initial diagnosis.

Conclusion.
A machine learning model for identifying spinal epidural hematomas and abscesses on CT can be implemented in a clinical workflow.
Assessment of Fusion After Anterior Cervical Discectomy and Fusion Using Convolutional Neural Network Algorithm
Authors: Park Sehan , Kim Jeoung Kun , Chang Min Cheol , Park Jeong Jin , Yang Jae Jun , Lee Gun Woo 
Published: July 2022

Background.
A convolutional neural network (CNN) is a deep learning (DL) model specialized for image processing, analysis, and classification.

Objective.
In this study, we evaluated whether a CNN model using lateral cervical spine radiographs as input data can help assess fusion after anterior cervical discectomy and fusion (ACDF).

Study Design.
Diagnostic imaging study using DL.

Patient Sample.
We included 187 patients who underwent ACDF and fusion assessment with postoperative one-year computed tomography and neutral and dynamic lateral cervical spine radiographs.

Outcome Measures.
The performance of the CNN-based DL algorithm was evaluated in terms of accuracy and area under the curve.

Materials and Methods.
Fusion or nonunion was confirmed by cervical spine computed tomography. Among the 187 patients, 69.5% (130 patients) were randomly selected as the training set, and the remaining 30.5% (57 patients) were assigned to the validation set to evaluate model performance. Radiographs of the cervical spine were used as input images to develop a CNN-based DL algorithm. The CNN algorithm used three radiographs (neutral, flexion, and extension) per patient and showed the diagnostic results as fusion (0) or nonunion (1) for each radiograph. By combining the results of the three radiographs, the final decision for a patient was determined to be fusion (fusion ≥2) or nonunion (fusion ≤1). By combining the results of the three radiographs, the final decision for a patient was determined as fusion (fusion ≥2) or nonunion (nonunion ≤1).

Results.
The CNN-based DL model demonstrated an accuracy of 89.5% and an area under the curve of 0.889 (95% confidence interval, 0.793–0.984).

Conclusion.
The CNN algorithm for fusion assessment after ACDF trained using lateral cervical radiographs showed a relatively high diagnostic accuracy of 89.5% and is expected to be a useful aid in detecting pseudarthrosis.