bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a prediction model for actionable aspects of frailty in the text of clinicians’ encounter notes
Authors: Martin Jacob A , Crane-Droesch Andrew , Lapite Folasade C , Puhl Joseph C , Kmiec Tyler E , Silvestri Jasmine A , Ungar Lyle H , Kinosian Bruce P , Himes Blanca E , Hubbard Rebecca A , Diamond Joshua M , Ahya Vivek , Sims Michael W , Halpern Scott D , Weissman Gary E 
Published: October 2021

Abstract

Objective
Frailty is a prevalent risk factor for adverse outcomes among patients with chronic lung disease. However, identifying frail patients who may benefit from interventions is challenging using standard data sources. We therefore sought to identify phrases in clinical notes in the electronic health record (EHR) that describe actionable frailty syndromes.

Materials and Methods
We used an active learning strategy to select notes from the EHR and annotated each sentence for 4 actionable aspects of frailty: respiratory impairment, musculoskeletal problems, fall risk, and nutritional deficiencies. We compared the performance of regression, tree-based, and neural network models to predict the labels for each sentence. We evaluated performance with the scaled Brier score (SBS), where 1 is perfect and 0 is uninformative, and the positive predictive value (PPV).

Results
We manually annotated 155 952 sentences from 326 patients. Elastic net regression had the best performance across all 4 frailty aspects (SBS 0.52, 95% confidence interval [CI] 0.49–0.54) followed by random forests (SBS 0.49, 95% CI 0.47–0.51), and multi-task neural networks (SBS 0.39, 95% CI 0.37–0.42). For the elastic net model, the PPV for identifying the presence of respiratory impairment was 54.8% (95% CI 53.3%–56.6%) at a sensitivity of 80%.

Discussion
Classification models using EHR notes can effectively identify actionable aspects of frailty among patients living with chronic lung disease. Regression performed better than random forest and neural network models.

Conclusions
NLP-based models offer promising support to population health management programs that seek to identify and refer community-dwelling patients with frailty for evidence-based interventions.
Post-war Violence against Human Rights Defenders and State Protection in Colombia
Authors: Wesche Philipp 
Published: October 2021

AbstractIn transitions from armed conflict, human rights defenders play an important role: in many cases, they are the local protagonists of the peace process. At the same time, they are at high risk of becoming victims of post-war violence. This article explores how states can protect defenders from such violence by presenting a case study of the Colombian transition, which has been characterized by high rates of homicides of defenders and threats against their physical integrity. Based on qualitative interviews with experts involved in protection, the article argues that violence against defenders may evolve into a systemic problem in post-conflict settings. In such contexts, protection must go beyond providing individual security measures to defenders at risk. Instead, it should follow a collective approach that emphasizes the security of communities and organizations, strengthens their capacities and relations with the state, and strives to dismantle the armed groups responsible for attacking defenders.
Acres for the Affluent: An Interactive Model of Nonprofit Resources and Demand Heterogeneity
Authors: Zuhlke Samantha 
Published: October 2021

AbstractAccording to the theory of government failure, nonprofit organizations emerge when governments fail to provide goods or services to a public with heterogeneous demands. This study approaches this fundamental theory of the nonprofit sector from a pluralist political viewpoint, marrying the theory of government failure to resource-driven nonprofit arguments via updated modeling and measurement strategies. This article proposes a new, conditional demand heterogeneity hypothesis, wherein the effect of demand heterogeneity on the nonprofit sector increases in the presence of increasing resources: nonprofit service delivery is most likely when those experiencing government failure have access to resources. This article is the first to test supply and demand nonprofit arguments in tandem using an interactive modeling specification and the first to operationalize demand heterogeneity using policy-based measures. I employ a finite distributed lag model with an interactive term in a time series, cross-sectional analysis of public and nonprofit land conservation in the United States. I find that nonprofit land conservation increases when citizens express greater environmental concern but only in the presence of increasing disposable income. Examining nonprofit theory within the context of land conservation provides a comparable measure of government and nonprofit service provision, controls for the nature of the good provided by these institutions, and allows for a policy-driven measure of demand heterogeneity, improving upon previous studies’ employment of diversity-based proxy measures. The results advance our understanding of how to test and measure demand heterogeneity nonprofit arguments and suggest that access to resources conditions which interests find expression in nonprofit organizations.
Urban citizenship for all? Exploring the limits of an agenda in São Paulo’s squats
Authors: Zacca Thomaz Diana 
Published: October 2021

Abstract
Scholarly analyses often interpret the urban struggles of both marginalised citizens and marginalised migrants through the single frame of urban citizenship. Urban citizenship, in this literature, is generally understood as an agenda that seeks to achieve the full political belonging of all those who inhabit the city. This article questions two assumptions running through much of this scholarship. The first is the assumption that struggles for urban citizenship necessarily promote the full belonging of all city dwellers. I argue that this understanding does not adequately take into account the social hierarchies existing within citizenship. The second is the assumption that all marginalised city dwellers (including migrants) will claim for their political belonging to the city. These limitations in the urban citizenship agenda are explored in the divergent aspirations and claims-making of both Brazilians and international migrants living together in squats in central São Paulo, Brazil. I show how militant Brazilian squatters pursuing their full urban citizenship bring about progressive change while also unintentionally reinscribing social hierarchies within citizenship. I also show how migrant squatters are not clearly compelled by the prospect of full belonging in São Paulo, but instead often aspire to better futures elsewhere. In sum, I argue that analyses of urban struggles located at the intersection of migration and residential segregation should not assume that the urban citizenship agenda will be either universally inclusive or universally desirable in a given city.
Variable star classification across the Galactic bulge and disc with the VISTA Variables in the Vía Láctea survey
Authors: Molnar Thomas A , Sanders Jason L , Smith Leigh C , Belokurov Vasily , Lucas Philip , Minniti Dante 
Published: October 2021

Abstract
We present VIVACE, the VIrac VAriable Classification Ensemble, a catalogue of variable stars extracted from an automated classification pipeline for the Vista Variables in the Vía Láctea (VVV) infrared survey of the Galactic bar/bulge and southern disc. Our procedure utilises a two-stage hierarchical classifier to first isolate likely variable sources using simple variability summary statistics and training sets of non-variable sources from the Gaia early third data release, and then classify candidate variables using more detailed light curve statistics and training labels primarily from OGLE and VSX. The methodology is applied to point-spread-function photometry for ∼490 million light curves from the VIRAC v2 astrometric and photometric catalogue resulting in a catalogue of ∼1.4 million likely variable stars, of which ∼39, 000 are high-confidence (classification probability &gt;0.9) RR Lyrae ab stars, ∼8000 RR Lyrae c/d stars, ∼187, 000 detached/semi-detached eclipsing binaries, ∼18, 000 contact eclipsing binaries, ∼1400 classical Cepheid variables and ∼2200 Type II Cepheid variables. Comparison with OGLE-4 suggests a completeness of around 90  per cent for RRab and ≲ 60 per cent for RRc/d, and a misclassification rate for known RR Lyrae stars of around 1 per cent for the high confidence sample. We close with two science demonstrations of our new VIVACE catalogue: first, a brief investigation of the spatial and kinematic properties of the RR Lyrae stars within the disc/bulge, demonstrating the spatial elongation of bar-bulge RR Lyrae stars is in the same sense as the more metal-rich red giant population whilst having a slower rotation rate of ∼40 km s−1kpc−1; and secondly, an investigation of the Gaia EDR3 parallax zeropoint using contact eclipsing binaries across the Galactic disc plane and bulge.
Investigating variations in the dust emissivity index in the Andromeda Galaxy
Authors: Athikkat-Eknath G , Eales S A , Smith M W L , Schruba A , Marsh K A , Whitworth A P 
Published: October 2021

ABSTRACT
Over the past decade, studies of dust in the Andromeda Galaxy (M31) have shown radial variations in the dust emissivity index (β). Understanding the astrophysical reasons behind these radial variations may give clues about the chemical composition of dust grains, their physical structure, and the evolution of dust. We use 12CO(J = 1$\longrightarrow$0) observations taken by the Combined Array for Research in Millimeter-wave Astronomy and dust maps derived from Herschel images, both with an angular resolution of 8 arcsec and with spatial resolution of 30 pc, to study variations in β across an area of ≈18.6 kpc2 in M31. We extract sources, which we identify as molecular clouds, by applying the astrodendro algorithm to the 12CO and dust maps, which as a byproduct allows us to compare continuum emission from dust and CO emission as alternative ways of finding molecular clouds. We then use these catalogues to investigate whether there is evidence that β is different inside and outside molecular clouds. Our results confirm the radial variations of β seen in previous studies. However, we find little difference between the average β inside molecular clouds compared with that outside molecular clouds, in disagreement with models that predict an increase of β in dense environments. Finally, we find some clouds traced by dust with very little CO, which may be either clouds dominated by atomic gas or clouds of molecular gas that contain little CO.
The unusually high dark matter concentration of the galaxy group NGC 1600
Authors: Runge J , Walker S A , Mirakhor M S 
Published: October 2021

ABSTRACT
We investigate the properties of the dark matter (DM) halo surrounding the nearby galaxy group NGC 1600. Through the use of deep (252 ks) Chandra observations and 64.3 ks of XMM–Newton observations, we construct surface brightness profiles in multiple energy bands in order to perform hydrostatic equilibrium analysis of the hot plasma within NGC 1600. Regardless of the DM model profile assumed, we measure a halo concentration (c200) that is an extreme, positive outlier of the ΛCDM c200–M200 relation. For a typical NFW DM profile, we measure c200 = 26.7 ± 1.4 and M200 = (2.0 ± 0.2) × 1013 M⊙; assuming a similar halo mass, the average concentration expected is c200 = 6 − 7 for the theoretical ΛCDM c–M relation. Such a high concentration is similar to that of well-known fossil groups MRK 1216 and NGC 6482. While NGC 1600 exhibits some properties of a fossil group, it fails to meet the X-ray luminosity threshold of LX &gt; 5 × 1041 erg s−1. Whether or not it is considered a fossil group, the high concentration value makes it part of a select group of galaxy groups.
Data-Efficient Classification of Radio Galaxies
Authors: Samudre Ashwin , George Lijo T , Bansal Mahak , Wadadekar Yogesh 
Published: October 2021

Abstract
The continuum emission from radio galaxies can be generally classified into different morphological classes such as FRI, FRII, Bent, or Compact. In this paper, we explore the task of radio galaxy classification based on morphology using deep learning methods with a focus on using a small scale dataset (∼2000 samples). We apply few-shot learning techniques based on Twin Networks and transfer learning techniques using a pre-trained DenseNet model with advanced techniques like cyclical learning rate and discriminative learning to train the model rapidly. We achieve a classification accuracy of over 92% using our best performing model with the biggest source of confusion being between Bent and FRII type galaxies. Our results show that focusing on a small but curated dataset along with the use of best practices to train the neural network can lead to good results. Automated classification techniques will be crucial for upcoming surveys with next generation radio telescopes which are expected to detect hundreds of thousands of new radio galaxies in the near future.
Self-similarity of k-nearest neighbour distributions in scale-free simulations
Authors: Garrison Lehman H , Abel Tom , Eisenstein Daniel J 
Published: October 2021

ABSTRACT
We use the k-nearest neighbour probability distribution function (kNN-PDF; Banerjee & Abel 2021a) to assess convergence in a scale-free N-body simulation. Compared to our previous two-point analysis, the kNN-PDF allows us to quantify our results in the language of haloes and numbers of particles, while also incorporating non-Gaussian information. We find good convergence for 32 particles and greater at densities typical of haloes, while 16 particles and fewer appear unconverged. Halving the softening length extends convergence to higher densities, but not to fewer particles. Our analysis is less sensitive to voids, but we analyse a limited range of underdensities and find evidence for convergence at 16 particles and greater even in sparse voids.
Static and dynamic solar coronal loops with cross-sectional area variations
Authors: Cargill P J , Bradshaw S J , Klimchuk J A , Barnes W T 
Published: October 2021

ABSTRACT
The Enthalpy Based Thermal Evolution of Loops approximate model for static and dynamic coronal loops is developed to include the effect of a loop cross-sectional area which increases from the base of the transition region (TR) to the corona. The TR is defined as the part of a loop between the top of the chromosphere and the location where thermal conduction changes from an energy loss to an energy gain. There are significant differences from constant area loops due to the manner in which the reduced volume of the TR responds to conductive and enthalpy fluxes from the corona. For static loops with modest area variation the standard picture of loop energy balance is retained, with the corona and TR being primarily a balance between heating and conductive losses in the corona, and downward conduction and radiation to space in the TR. As the area at the loop apex increases, the TR becomes thicker and the density in TR and corona larger. For large apex areas, the coronal energy balance changes to one primarily between heating and radiation, with conduction playing an increasingly unimportant role, and the TR thickness becoming a significant fraction of the loop length. Approximate scaling laws are derived that give agreement with full numerical solutions for the density, but not the temperature. For non-uniform areas, dynamic loops have a higher peak temperature and are denser in the radiative cooling phase by of order 50 per cent than the constant area case for the examples considered. They also show a final rapid cooling and draining once the temperature approaches 1 MK. Although the magnitude of the emission measure will be enhanced in the radiative phase, there is little change in the important observational diagnostic of its temperature dependence.
Combining phosphate binder therapy with vitamin K2 inhibits vascular calcification in an experimental animal model of kidney failure
Authors: Neradova Aegida , Wasilewski Grzegorz , Prisco Selene , Leenders Peter , Caron Marjolein , Welting Tim , van Rietbergen Bert , Kramann Rafael , Floege Jürgen , Vervloet Marc G , Schurgers Leon J 
Published: October 2021

ABSTRACT

Background
Hyperphosphataemia is strongly associated with cardiovascular disease and mortality. Recently, phosphate binders (PBs), which are used to bind intestinal phosphate, have been shown to bind vitamin K, thereby potentially aggravating vitamin K deficiency. This vitamin K binding by PBs may offset the beneficial effects of phosphate reduction in reducing vascular calcification (VC). Here we assessed whether combining PBs with vitamin K2 supplementation inhibits VC.

Methods
We performed 3/4 nephrectomy in rats, after which warfarin was given for 3 weeks to induce vitamin K deficiency. Next, animals were fed a high phosphate diet in the presence of low or high vitamin K2 and were randomized to either control or one of four different PBs for 8 weeks. The primary outcome was the amount of thoracic and abdominal aorta VC measured by high-resolution micro-computed tomography (µCT). Vitamin K status was measured by plasma MK7 levels and immunohistochemically analysed in vasculature using uncarboxylated matrix Gla protein (ucMGP) specific antibodies.

Results
The combination of a high vitamin K2 diet and PB treatment significantly reduced VC as measured by µCT for both the thoracic (P = 0.026) and abdominal aorta (P = 0.023), compared with MK7 or PB treatment alone. UcMGP stain was significantly more present in the low vitamin K2–treated groups in both the thoracic (P &lt; 0.01) and abdominal aorta (P &lt; 0.01) as compared with high vitamin K2–treated groups. Moreover, a high vitamin K diet and PBs led to reduced vascular oxidative stress.

Conclusion
In an animal model of kidney failure with vitamin K deficiency, neither PB therapy nor vitamin K2 supplementation alone prevented VC. However, the combination of high vitamin K2 with PB treatment significantly attenuated VC.
‘Where Are the Proxenoi?’ Social Network Analysis, Connectivity and the Greek Poleis
Authors: Mack William 
Published: October 2021

Abstract
The aim of this article is to establish a new basis for exploring the network of ancient Greek city-states during the Classical and Hellenistic periods by applying Social Network Analysis to the record of inscriptions recording grants of proxeny. Proxeny was a generalized institution for facilitating interactions between Greek political communities. Because it left a rich and idiosyncratic record in the form of thousands of honorific inscriptions, it represents an important test case for Social Network Analysis. By drawing on work on partial samples of network data, we can identify a clear and historically significant structure in this material, namely a massively unequal hierarchy in the extent to which different communities were the focus of links. This allows us to compare, systematically, the hundreds of Greek city-states in terms of their connectivity in the network. As a result it provides a new empirical basis for testing prevailing models and assumptions about why these communities forged links and mapping the limits of the network. By reading this hierarchy alongside the other information we have, we can identify the role that political, economic and geographic factors played in determining connectivity in this network, and the surprising unimportance of religion.
An Equilibrium Analysis of the Long-Term Care Insurance Market
Authors: Ko Ami 
Published: October 2021

Abstract
Informal care provided by adult children substitutes for formal long-term care services. However, information about children is not used in pricing long-term care insurance which pays only for formal care. I start by providing descriptive evidence that private information about children’s informal care likelihood results in adverse selection: the market attracts a disproportionate number of individuals who face higher formal care utilization risk due to a lower probability of receiving care from their children. To quantify the welfare consequence of adverse selection, I develop and estimate a dynamic intergenerational model featuring long-term care insurance, savings, informal care provision, and employment choices. Based on the estimated equilibrium insurance market framework, I show that using information about children in pricing insurance contracts reduces adverse selection and results in the average welfare gain of $6,200 per family. Using the non-cooperative feature of the model, I also quantify to what extent parents forgo long-term care insurance to avoid diminishing children’s informal care incentive.
Risk factors of impaired humoral response to COVID-19 vaccination in rituximab-treated patients
Authors: Avouac Jérôme , Miceli-Richard Corinne , Combier Alice , Steelandt Alexia , Fogel Olivier , Mariaggi Alice Andrée , Meritet Jean-François , Rozenberg Flore , Molto Anna , Allanore Yannick 
Published: October 2021

Abstract

Objective
To identify which factors influence humoral response to coronavirus disease 2019 (COVID-19) vaccination in rituximab (RTX)-treated patients.

Methods
This was an observational, prospective, usual care study including consecutive patients with inflammatory rheumatic diseases in maintenance therapy with RTX. All patients received a two-dose regimen COVID-19 vaccination. Serum IgG antibody levels against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins were measured at the time of the new RTX infusion.

Results
From the recruited patients, 16/45 (36%) produced antibodies reaching the assay cut-off value of 15 AU/ml and 29/45 (64%) had a negative serology. Within RTX-treated patients, 25 (56%) had undetectable B cells. Negative serology was associated with undetectable B cells (24/25 vs 5/20, P &lt; 0.001). Moreover, SARS-CoV-2 spike antibodies correlated with CD19 counts (r = 0.86, P &lt; 0.001). The effect of RTX and MTX was additive in terms of seroconversion rates (23% vs 50% in patients receiving RTX in monotherapy, P = 0.12) and SARS-CoV-2 spike antibody levels [3.80 (95% CI 3.80, 7.50) vs 75 (95% CI 3.8, 353) AU/ml in patients receiving RTX in monotherapy; P = 0.025]. Multivariate analyses including demographics, disease characteristics, gammaglobulin levels, RTX and other therapies used, CD19 counts, and the time between the last RTX infusion and vaccination identified detectable B cells as the only variable independently associated with seropositivity [odds ratio 35.2 (95% CI 3.59, 344.20)].

Conclusions
B cell depletion is the main independent contributing factor of antibody response to SARS-CoV-2 vaccination in RTX-treated patients. Monitoring CD19 may be of interest to identify the most appropriate period to perform vaccination.