bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rebellion at the Fringe: Conspiracy, Surveillance, and State-Making in 1920s Mexico
Authors: Piña Ulices 
Published: August 2021

Abstract
In 1925, rumors of an alleged international conspiracy to overthrow the state circulated in central-western Mexico. The reports prompted the country’s newly created Departamento Confidencial (Confidential Department) to begin surveilling former rebels and zealous Catholics in the region, as well as political exiles in the American Southwest. This article explores how the intelligence services helped consolidate institutional power after the Mexican Revolution (1910–20). The investigations uncovered well-organized propaganda campaigns that centered on generating support, organization, and information. These networks originated abroad and circulated in the small hamlets, towns, and metropolitan centers of the region. The widespread rumors reflected what ordinary people thought was credible and socially conceivable, while also nourishing the belief among locals that a rebellion would breakout against the state. Ultimately, this type of surveillance transformed how the central state interacted with, and came to produce knowledge of, its citizenry.
Changes in Emergency Department Volumes at the Largest U.S. Military Hospital During the COVID-19 Pandemic
Authors: Long Adrianna , Fillinger Meghan , April Michael D , Hudson Ian L , Trueblood Wesley , Schmitz Gillian , Chin Eric J , Hartstein Bonnie , Pfaff James A , Schauer Steven G 
Published: August 2021

ABSTRACT

Introduction
The coronavirus-2019 (COVID-19) pandemic has significantly impacted global healthcare delivery. Brooke Army Medical Center (BAMC) is the DoD’s largest hospital and a critical platform for maintaining a ready medical force. We compare temporal trends in patient volumes and characteristics in the BAMC emergency department (ED) before versus during the pandemic.

Materials and Methods
We abstracted data on patient visits from the BAMC ED electronic medical record system. Data included patient demographics, visit dates, emergency severity index triage level, and disposition. We visually compared the data from January 1, 2019 to November 30, 2019 versus January 1, 2020 to November 30, 2020 to assess the period with the most apparent differences. We then used descriptive statistics to characterize the pre-pandemic control period (1 March-November 30, 2019) versus the pandemic period (1 March-November 30, 2020).

Results
Overall, when comparing the pre-pandemic and pandemic periods, the median number of visits per day was 232 (Interquartile Range (IQR) 214-250, range 145-293) versus 165 (144-193, range 89-308, P &lt; .0001). Specific to pediatric visits, we found the median number of visits per day was 39 (IQR 33-46, range 15-72) versus 18 (IQR 14-22, range 5-61, P &lt; .001). When comparing the median number of visits by month, the volumes were lower during the pandemic for all months, all of which were strongly significant (P &lt; .001 for all).

Conclusions
The BAMC ED experienced a significant decrease in patient volume during the COVID-19 pandemic starting in March 2020. This may have significant implications for the capacity of this facility to maintain a medically ready force.
The cosmological dependence of halo and galaxy assembly bias
Authors: Contreras S , Chaves-Montero J , Zennaro M , Angulo R E 
Published: August 2021

ABSTRACT
One of the main predictions of excursion set theory is that the clustering of dark matter haloes only depends on halo mass. However, it has been long established that the clustering of haloes also depends on other properties, including formation time, concentration, and spin; this effect is commonly known as halo assembly bias (HAB). We use a suite of gravity-only simulations to study the dependence of HAB on cosmology; these simulations cover cosmological parameters spanning 10σ around state-of-the-art best-fitting values, including standard extensions of the ΛCDM paradigm such as neutrino mass and dynamical dark energy. We find that, when studying the peak height-bias relation, the strength of HAB presents variations smaller than 0.05 dex across all cosmologies studied for concentration- and spin-selected haloes, letting us conclude that the dependence of HAB upon cosmology is negligible. We then study the dependence of galaxy assembly bias (i.e. the manifestation of HAB in galaxy clustering) on cosmology using subhalo abundance matching. We find that galaxy assembly bias also presents very small dependence upon cosmology (∼ 2 per cent–4 per cent of the total clustering); on the other hand, we find that the dependence of this signal on the galaxy formation parameters of our galaxy model is much stronger. Taken together, these results let us conclude that the dependence of halo and galaxy assembly bias on cosmology is practically negligible.
MAHGIC: a Model Adapter for the Halo–Galaxy Inter-Connection
Authors: Chen Yangyao , Mo H J , Li Cheng , Wang Kai , Wang Huiyuan , Yang Xiaohu , Zhang Youcai , Katz Neal 
Published: August 2021

ABSTRACT
We develop a model to establish the interconnection between galaxies and their dark matter haloes. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of haloes/subhaloes and the star formation histories of galaxies, and Gradient Boosted Decision Trees (GBDT) to transform halo/subhalo properties into galaxy properties. We use two sets of hydrodynamic simulations to motivate our model architecture and to train the transformation. We then apply the two sets of trained models to dark-matter-only (DMO) simulations to show that the transformation is reliable and statistically accurate. The model trained by a high-resolution hydrodynamic simulation, or by a set of such simulations implementing the same physics of galaxy formation, can thus be applied to large DMO simulations to make ‘mock’ copies of the hydrodynamic simulation. The model is both flexible and interpretable, which paves the way for future applications in which we will constrain the model using observations at different redshifts simultaneously and explore how galaxies form and evolve in dark matter haloes empirically.
Classification of Fermi-LAT sources with deep learning using energy and time spectra
Authors: Finke Thorben , Krämer Michael , Manconi Silvia 
Published: August 2021

ABSTRACT
Despite the growing number of gamma-ray sources detected by the Fermi-Large Area Telescope (LAT), about one-third of the sources in each survey remains of uncertain type. We present a new deep neural network approach for the classification of unidentified or unassociated gamma-ray sources in the last release of the Fermi-LAT catalogue (4FGL-DR2) obtained with 10 yr of data. In contrast to previous work, our method directly uses the measurements of the photon energy spectrum and time series as input for the classification, instead of specific, human-crafted features. Dense neural networks, and for the first time in the context of gamma-ray source classification recurrent neural networks, are studied in depth. We focus on the separation between extragalactic sources, i.e. active galactic nuclei, and Galactic pulsars, and on the further classification of pulsars into young and millisecond pulsars. Our neural network architectures provide powerful classifiers, with a performance that is comparable to previous analyses based on human-crafted features. Our benchmark neural network predicts that of the sources of uncertain type in the 4FGL-DR2 catalogue, 1050 are active galactic nuclei and 78 are Galactic pulsars, with both classes following the expected sky distribution and the clustering in the variability–curvature plane. We investigate the problem of sample selection bias by testing our architectures against a cross-match test data set using an older catalogue, and propose a feature selection algorithm using autoencoders. Our list of high-confidence candidate sources labelled by the neural networks provides a set of targets for further multiwavelength observations addressed to identify their nature. The deep neural network architectures we develop can be easily extended to include specific features, as well as multiwavelength data on the source photon energy and time spectra coming from different instruments.
Successive injection of opposite magnetic helicity: evidence for active regions without coronal mass ejections
Authors: Vemareddy P 
Published: August 2021

ABSTRACT
Magnetic helicity (MH) is a measure of twist and shear of magnetic field. MH is injected in the active region (AR) corona through photospheric footpoint motions causing twisted and sheared magnetic fields. From the conservation property of the helicity, it was conjectured that an already twisted flux rope (FR) with continuous injection of MH inevitably erupts to remove the excess accumulated coronal helicity. Therefore, understanding the nature and evolution of the photospheric helicity flux transfer is crucial to reveal the intensity of the flare/coronal mass ejection (CME) activity. Using the time-sequence vector magnetograms of Helioseismic Magnetic Imager, we study the evolution of MH injection in emerging AR 12257. The photospheric flux motions in this AR inject positive helicity in the first 2.5 days followed by negative helicity later. This successive injection of opposite helicity is consistent with the sign of mean force-free twist parameter (αav), orientation of magnetic tongues. Also, the extrapolated AR magnetic structure exhibits transformation of global shear without a twisted FR in the core of the AR. No CMEs are launched from this AR but C-class flaring activity is observed predominantly in the second half of the evolution period. The ARs with sign reversal of the MH injection are not favourable to twisted FR formation with excess coronal helicity, and therefore, are important to identify CME-less ARs readily. A possible scenario in these ARs is that when one sign of helicity flux is replaced by opposite sign, the magnetic field of different connectivity with opposite shear undergoes reconnection at different scales giving rise to both intermittent flares and enhanced coronal heating.
Pulsating subdwarf B stars observed with K2 during Campaign 7 and an examination of seismic group properties
Authors: Reed M D , Slayton A , Baran A S , Telting J H , Østensen R H , Jeffery C S , Uzundag M , Sanjayan S 
Published: August 2021

ABSTRACT
We report the discovery of four new pulsating subdwarf B (sdBV) stars from Campaign 7 of the Kepler spacecraft’s K2 mission. EPIC 215776487, EPIC 217280630, EPIC 218366972, and EPIC 218717602 are all gravity (g)-mode pulsators and we also detect two pressure (p)-mode pulsations in EPIC 218717602. We detect asymptotic $\ell \, =\, 1$ sequences in all four stars, allowing us to identify nearly all of the g modes. We detect evenly spaced frequency multiplets in EPIC 218717602 from which we determine a rotation period near 7 d. Spectroscopic observations determine that EPIC 218366972 is in a 5.92 d binary with most likely a white dwarf companion of canonical mass while the others have no detected companions. As we detect no multiplets in EPIC 218366972, it is added to the growing list of subsynchronously rotating stars. With 40 Kepler-detected sdBV stars and a growing number of Transiting Exoplanet Survey Satellite (TESS) publications, we update an examination of the group properties to provide direction for models. We notice a correlation between effective temperature and period of maximum pulsation amplitude, at least for g-mode pulsations, and update the previously observed effective temperature–rotation period relation.
Identifying low-amplitude pulsating stars through microlensing observations
Authors: Sajadian Sedighe , Ignace Richard , Neilson Hilding 
Published: August 2021

ABSTRACT
One possibility for detecting low-amplitude pulsational variations is through gravitational microlensing. During a microlensing event, the temporary brightness increase leads to improvement in the signal-to-noise ratio, and thereby better detectability of pulsational signatures in light curves. We explore this possibility under two primary considerations. The first is when the standard point-source and point-lens approximation applies. In this scenario, dividing the observed light curve by the best-fitted microlensing model leads to residuals that result in pulsational features with improved uncertainties. The second is for transit events (single lens) or caustic crossing (binary lens). The point-source approximation breaks down, and residuals relative to a simple best-fitted microlensing model display more complex behaviour. We employ a Monte Carlo simulation of microlensing of pulsating variables toward the Galactic bulge for the surveys of OGLE and of KMTNet. We demonstrate that the efficiency for detecting pulsational signatures with intrinsic amplitudes of &lt;0.25 mag during single and binary microlensing events, at differences in χ2 of Δχ2 &gt; 350, is $\sim \!50\!-\!60{{\ \rm per\ cent}}$. The maximum efficiency occurs for pulsational periods P ≃ 0.1–0.3 d. We also study the possibility that high-magnification microlensing events of non-radially pulsating stars could be misinterpreted as planetary or binary microlensing events. We conclude that small asymmetric features around light curve peaks due to stellar pulsations could be misdiagnosed with crossing (or passing close to) small caustic curves.
White dwarf and subdwarf stars in the Sloan Digital Sky Survey Data Release 16
Authors: Kepler S O , Koester Detlev , Pelisoli Ingrid , Romero Alejandra D , Ourique Gustavo 
Published: August 2021

ABSTRACT
White dwarfs are the end state of the evolution of more than 97 per cent of all stars, and therefore carry information on the structure and evolution of the Galaxy through their luminosity function and initial-to-final mass relation. Examining the new spectra of all white or blue stars in the Sloan Digital Sky Survey Data Release 16, we report the spectral classification of 2410 stars, down to our identification cut-off of signal-to-noise ratio equal to three. We newly identify 1404 DAs, 189 DZs, 103 DCs, 12 DBs, and nine CVs. The remaining objects are a mix of carbon or L stars (dC/L), narrow-lined hydrogen-dominated stars (sdA), dwarf F stars, and P Cyg objects. As white dwarf stars were not targeted by SDSS DR16, the number of new discoveries is much smaller than in previous releases. We also report atmospheric parameters and masses for a subset consisting of 555 new DAs, 10 new DBs, and 85 DZs for spectra with signal-to-noise ratio larger than 10.
The dependence of the hierarchical distribution of star clusters on galactic environment
Authors: Menon Shyam H , Grasha Kathryn , Elmegreen Bruce G , Federrath Christoph , Krumholz Mark R , Calzetti Daniela , Sánchez Néstor , Linden Sean T , Adamo Angela , Messa Matteo , Cook David O , Dale Daniel A , Grebel Eva K , Fumagalli Michele , Sabbi Elena , Johnson Kelsey E , Smith Linda J , Kennicutt Robert C 
Published: August 2021

ABSTRACT
We use the angular two-point correlation function (TPCF) to investigate the hierarchical distribution of young star clusters in 12 local (3–18 Mpc) star-forming galaxies using star cluster catalogs obtained with the Hubble Space Telescope (HST) as part of the Treasury Program Legacy ExtraGalactic UV Survey. The sample spans a range of different morphological types, allowing us to infer how the physical properties of the galaxy affect the spatial distribution of the clusters. We also prepare a range of physically motivated toy models to compare with and interpret the observed features in the TPCFs. We find that, conforming to earlier studies, young clusters ($T \lesssim 10\, \mathrm{Myr}$) have power-law TPCFs that are characteristic of fractal distributions with a fractal dimension D2, and this scale-free nature extends out to a maximum scale lcorr beyond which the distribution becomes Poissonian. However, lcorr, and D2 vary significantly across the sample, and are correlated with a number of host galaxy physical properties, suggesting that there are physical differences in the underlying star cluster distributions. We also find that hierarchical structuring weakens with age, evidenced by flatter TPCFs for older clusters ($T \gtrsim 10\, \mathrm{Myr}$), that eventually converges to the residual correlation expected from a completely random large-scale radial distribution of clusters in the galaxy in $\sim 100 \, \mathrm{Myr}$. Our study demonstrates that the hierarchical distribution of star clusters evolves with age, and is strongly dependent on the properties of the host galaxy environment.
Towards next generation antisense oligonucleotides: mesylphosphoramidate modification improves therapeutic index and duration of effect of gapmer antisense oligonucleotides
Authors: Anderson Brooke A , Freestone Graeme C , Low Audrey , De-Hoyos Cheryl L , III William J Drury , Østergaard Michael E , Migawa Michael T , Fazio Michael , Wan W Brad , Berdeja Andres , Scandalis Eli , Burel Sebastien A , Vickers Timothy A , Crooke Stanley T , Swayze Eric E , Liang Xuehai , Seth Punit P 
Published: August 2021

Abstract
The PS modification enhances the nuclease stability and protein binding properties of gapmer antisense oligonucleotides (ASOs) and is one of very few modifications that support RNaseH1 activity. We evaluated the effect of introducing stereorandom and chiral mesyl-phosphoramidate (MsPA) linkages in the DNA gap and flanks of gapmer PS ASOs and characterized the effect of these linkages on RNA-binding, nuclease stability, protein binding, pro-inflammatory profile, antisense activity and toxicity in cells and in mice. We show that all PS linkages in a gapmer ASO can be replaced with MsPA without compromising chemical stability and RNA binding affinity but these designs reduced activity. However, replacing up to 5 PS in the gap with MsPA was well tolerated and replacing specific PS linkages at appropriate locations was able to greatly reduce both immune stimulation and cytotoxicity. The improved nuclease stability of MsPA over PS translated to significant improvement in the duration of ASO action in mice which was comparable to that of enhanced stabilized siRNA designs. Our work highlights the combination of PS and MsPA linkages as a next generation chemical platform for identifying ASO drugs with improved potency and therapeutic index, reduced pro-inflammatory effects and extended duration of effect.
Anti-SARS-CoV-2 Seropositivity Among Medical Students in Copenhagen
Authors: Madsen Johannes R , Nielsen Jacob P S , Fogh Kamille , Hansen Cecilie B , Nielsen Pernille B , Lange Theis , Hasselbalch Rasmus B , Garred Peter , Iversen Kasper 
Published: August 2021

Abstract

Background
Health care workers are at a higher risk of getting infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than the general population. Knowledge about medical students’ exposure to SARS-CoV-2 is lacking. Thus, we measured the prevalence of SARS-CoV-2 antibodies in a cohort of Danish medical students.

Methods
We invited all medical students at the University of Copenhagen (UCPH) to participate. Students underwent venous blood sampling and a questionnaire about work-life behaviors possibly associated with SARS-CoV-2 exposure and coronavirus disease 2019 (COVID-19) symptoms. Samples were analyzed for total immunoglobulin G (IgG) antibodies against SARS-CoV-2, and seropositive samples were screened for IgG, immunoglobulin M, and immunoglobulin A antibodies. We determined associations between seropositivity and clinical and social activities and self-reported symptoms.

Results
Between October 19 and 26, 1120 students participated in the questionnaire and 1096 were included. Of all included, 379 (34.58%) were seropositive. Seropositivity was associated with attendance at 2 parties at UCPH, on February 29 and March 6, 2020 (odds ratio [OR], 5.96; 95% CI, 4.34–8.24; P &lt; .001). Four hundred sixty-one students (42.06%) worked with COVID-19 patients, which was significantly associated with seropositivity (OR, 1.38; 95% CI, 1.03–1.85; P = .033). The symptom most associated with seropositivity was loss of smell and/or taste (n = 183 of all, 31.35%; OR, 24.48; 95% CI, 15.49–40.60; P &lt; .001). Bachelor’s students were significantly more likely to be seropositive than Master’s students (42.28% vs 16.87%; P &lt; .001).

Conclusions
Medical students have the highest reported seropositivity in the Danish health care system. In this cohort of students at UCPH, seropositivity was associated with social behavior markers and, to a lesser extent, with self-reported contact with SARS-CoV-2-infected patients.
Enforced stripping of negative muons from $\mu$He+ ions to stimulate muon-catalyzed fusion by cyclotron resonance acceleration
Authors: Mori Yoshiharu 
Published: August 2021

Abstract
The addition (sticking) of a negative muon to an $\alpha$ particle to form a $\mu$He$^+$ ion limits the number of chain reactions in muon-catalyzed fusion (MuCF), making scientific break-even in MuCF difficult. The reduction in the sticking probability by boosting the negative muon stripping using resonance radio-frequency (RF) acceleration of $\mu$He$^+$ ions has been examined with multi-particle tracking simulations. It was found that the stripping efficiency was largely depressed by ion–electron capture processes that have not been considered so far. Improvement of the fusion chain cycles is rather difficult with an RF electric field strength of 50 MV m$^{-1}$ even at a small deuterium/tritium (D/T) gas pressure of approximately 5 atm. However, in the scheme of using spatially localized D/T mixture gas streams, the sticking probability could be reduced almost tenfold even at a large gas density of 100 atm with a modest RF field strength of less than 50 MV m$^{-1}$.
Transcriptomics data: pointing the way to subclassification and personalized medicine in systemic lupus erythematosus
Authors: Hubbard Erika L. , Grammer Amrie C. , Lipsky Peter E. 
Published: August 2021

Purpose of review
To summarize recent studies stratifying SLE patients into subgroups based on gene expression profiling and suggest future improvements for employing transcriptomic data to foster precision medicine.

Recent findings
Bioinformatic & machine learning pipelines have been employed to dissect the transcriptomic heterogeneity of lupus patients and identify more homogenous subgroups. Some examples include the use of unsupervised random forest and k-means clustering to separate adult SLE patients into seven clusters and hierarchical clustering of single-cell RNA-sequencing (scRNA-seq) of immune cells yielding four clusters in a cohort of adult SLE and pediatric SLE participants. Random forest classification of bulk RNA-seq data from sorted blood cells enabled prediction of high or low disease activity in European and Asian SLE patients. Inferred transcription factor activity stratified adult and pediatric SLE into two subgroups.

Summary
Several different endotypes of SLE patients with differing molecular profiles have been reported but a global consensus of clinically actionable groups has not been reached. Moreover, heterogeneity between datasets, reproducibility of predictions as well as the most effective classification approach have not been resolved. Nevertheless, gene expression-based precision medicine remains an attractive option to subset lupus patients.