bluuebunny/crossref_metadata_2025_split huggingface dataset:
The ALMA REBELS Survey: discovery of a massive, highly star-forming, and morphologically complex ULIRG at z = 7.31
Authors: Hygate A P S , Hodge J A , da Cunha E , Rybak M , Schouws S , Inami H , Stefanon M , Graziani L , Schneider R , Dayal P , Bouwens R J , Smit R , Bowler R A A , Endsley R , Gonzalez V , Oesch P A , Stark D P , Algera H S B , Aravena M , Barrufet L , Ferrara A , Fudamoto Y , Hilhorst J H A , De Looze I , Nanayakkara T , Pallottini A , Riechers D A , Sommovigo L , Topping M W , van der Werf P 
Published: May 2023

ABSTRACT
We present Atacama Large Millimeter/Submillimeter Array (ALMA) [C ii] and ∼158 $\rm \mu m$ continuum observations of REBELS-25, a massive, morphologically complex ultra-luminous infrared galaxy (ULIRG; LIR = $1.5^{+0.8}_{-0.5} \times 10^{12}$ L⊙) at z = 7.31, spectroscopically confirmed by the Reionization Era Bright Emission Line Survey (REBELS) ALMA Large Programme. REBELS-25 has a significant stellar mass of $M_{*} = \mbox{$ 8^{+4}_{-2} \times 10^{9} $}{} ~\mbox{M$_\odot $}{}$. From dust-continuum and ultraviolet observations, we determine a total obscured + unobscured star formation rate of SFR $= \mbox{$199^{+101}_{-63}$}{} ~ \mbox{M$_\odot $}~ \mbox{${\rm yr}$}^{-1}$. This is about four times the SFR estimated from an extrapolated main sequence. We also infer a [C ii]-based molecular gas mass of $M_{{\rm H}_{2}} = \mbox{$5.1^{+5.1}_{-2.6} \times 10^{10}$}{} ~\mbox{M$_\odot $}{}$, implying a molecular gas depletion time of $t_{\rm depl, {\rm H}_{2}} = \mbox{$0.3^{+0.3}_{-0.2} $}{}$ Gyr. We observe a [C ii] velocity gradient consistent with disc rotation, but given the current resolution we cannot rule out a more complex velocity structure such as a merger. The spectrum exhibits excess [C ii] emission at large positive velocities (∼500 km s−1), which we interpret as either a merging companion or an outflow. In the outflow scenario, we derive a lower limit of the mass outflow rate of 200 $\mbox{M$_\odot $}~ \mbox{${\rm yr}$}^{-1}$, which is consistent with expectations for a star-formation-driven outflow. Given its large stellar mass, SFR, and molecular gas reservoir ∼700 Myr after the big bang, we explore the future evolution of REBELS-25. Considering a simple, conservative model assuming an exponentially declining star formation history, constant star formation efficiency, and no additional gas inflow, we find that REBELS-25 has the potential to evolve into a galaxy consistent with the properties of high-mass quiescent galaxies recently observed at z ∼ 4.
Cometary surface dust layers built out of millimetre-scale aggregates: dependence of modelled cometary gas production on the layer transport properties
Authors: Skorov Yu , Markkanen J , Reshetnyk V , Mottola S , Küppers M , Besse S , El-Maarry M R , Hartogh P 
Published: May 2023

ABSTRACT
The standard approach to obtaining knowledge about the properties of the surface layer of a comet from observations of gas production consists of two stages. First, various thermophysical models are used to calculate gas production for a few sets of parameters. Second, a comparison of observations and theoretical predictions is performed. This approach is complicated because the values of many model characteristics are known only approximately. Therefore, it is necessary to investigate the sensitivity of the simulated outgassing to variations in the properties of the surface layer. This problem was recently considered by us for aggregates up to tens of microns in size. For millimetre-size aggregates, a qualitative extension of the method used to model the structural characteristics of the layer is required. It is also necessary to study the role of radiative thermal conductivity, which may play an important role for such large particles. We investigated layers constructed from large aggregates and having various thicknesses and porosity and evaluated the effective sublimation of water ice at different heliocentric distances. For radiative conductivity, approximate commonly used models and the complicated model based on the dense-medium radiative transfer theory were compared. It was shown that for millimetre-size aggregates careful consideration of the radiative thermal conductivity is required since this mechanism of energy transfer may change the resulting gas productivity by several times. We demonstrate that our model is more realistic for an evolved comet than simple models parameterizing the properties of the cometary surface layer, yet maintains comparable computational complexity.
Rapid determination of LISA sensitivity to extreme mass ratio inspirals with machine learning
Authors: Chapman-Bird Christian E A , Berry Christopher P L , Woan Graham 
Published: May 2023

ABSTRACT
Gravitational wave observations of the inspiral of stellar-mass compact objects into massive black holes (MBHs), extreme mass ratio inspirals (EMRIs), enable precision measurements of parameters such as the MBH mass and spin. The Laser Interferometer Space Antenna is expected to detect sufficient EMRIs to probe the underlying source population, testing theories of the formation and evolution of MBHs and their environments. Population studies are subject to selection effects that vary across the EMRI parameter space, which bias inference results if unaccounted for. This bias can be corrected, but evaluating the detectability of many EMRI signals is computationally expensive. We mitigate this cost by (i) constructing a rapid and accurate neural network interpolator capable of predicting the signal-to-noise ratio of an EMRI from its parameters, and (ii) further accelerating detectability estimation with a neural network that learns the selection function, leveraging our first neural network for data generation. The resulting framework rapidly estimates the selection function, enabling a full treatment of EMRI detectability in population inference analyses. We apply our method to an astrophysically motivated EMRI population model, demonstrating the potential selection biases and subsequently correcting for them. Accounting for selection effects, we predict that with 116 EMRI detections LISA will measure the MBH mass function slope to a precision of 8.8 per cent, the CO mass function slope to a precision of 4.6 per cent, the width of the MBH spin magnitude distribution to a precision of 10 per cent, and the event rate to a precision of 12 per cent with EMRIs at redshifts below z = 6.
Peering into the central region of a nano-quasar: XMM–Newton and Chandra views of the CH Cyg symbiotic system
Authors: Toalá J A , González-Martín O , Karovska M , Montez R , Botello M K , Sabin L 
Published: May 2023

ABSTRACT
We present the analysis of archival XMM–Newton and Chandra observations of CH Cyg, one of the most studied symbiotic stars (SySts). The combination of the high-resolution XMM–Newton RGS and Chandra HETG X-ray spectra allowed us to obtain reliable estimates of the chemical abundances and to corroborate the presence of multitemperature X-ray-emitting gas. Spectral fitting of the medium-resolution XMM–Newton MOS (MOS1+MOS2) spectrum required the use of an additional component not seen in previous studies in order to fit the 2.0–4.0 keV energy range. Detailed spectral modelling of the XMM–Newton MOS data suggests the presence of a reflection component, very similar to that found in active galactic nuclei. The reflection component is very likely produced by an ionized disc (the accretion disc around the white dwarf) and naturally explains the presence of the fluorescent Fe emission line at 6.4 keV while also contributing to the soft and medium energy ranges. The variability of the global X-ray properties of CH Cyg are discussed as well as the variation of the three Fe lines around the 6–7 keV energy range. We conclude that reflection components are needed to model the hard X-ray emission and may be present in most β/δ-type SySt.
Stars on the edge: Galactic tides and the outskirts of the Sculptor dwarf spheroidal
Authors: Sestito Federico , Roediger Joel , Navarro Julio F , Jensen Jaclyn , Venn Kim A , Smith Simon E T , Hayes Christian , McConnachie Alan W 
Published: May 2023

ABSTRACT
The formation of ‘stellar haloes’ in dwarf galaxies have been discussed in terms of early mergers or Galactic tides, although fluctuations in the gravitational potential due to stellar feedback is also a possible candidate mechanism. A Bayesian algorithm is used to find new candidate members in the extreme outskirts of the Sculptor dwarf galaxy. Precise metallicities and radial velocities (RVs) for two distant stars are measured from their spectra taken with the Gemini South GMOS spectrograph. The radial velocity, proper motion, and metallicity of these targets are consistent with Sculptor membership. As a result, the known boundary of the Sculptor dwarf extends now out to an elliptical distance of ∼10rh (half-light radii), which corresponds to a projected physical distance of ∼3 kpc. As reported in earlier work, the overall distribution of RVs and metallicities indicate the presence of a more spatially and kinematically dispersed metal-poor population that surrounds the more concentrated and colder metal-rich stars. Sculptor’s density profile shows a ‘kink’ in its logarithmic slope at a projected distance of ∼25 arcmin (620 pc), which we interpret as evidence that Galactic tides have helped to populate the distant outskirts of the dwarf. We discuss further ways to test and validate this tidal interpretation for the origin of these distant stars.
Low-frequency radio observations of recurrent nova RS Ophiuchi with MeerKAT and LOFAR
Authors: de Ruiter Iris , Nyamai Miriam M , Rowlinson Antonia , Wijers Ralph A M J , O’Brien Tim J , Williams David R A , Woudt Patrick 
Published: May 2023

ABSTRACT
We report low-frequency radio observations of the 2021 outburst of the recurrent nova RS Ophiuchi. These observations include the lowest frequency observations of this system to date. Detailed light curves are obtained by MeerKAT at 0.82 and 1.28 GHz and LOFAR at 54 and 154 MHz. These low-frequency detections allow us to put stringent constraints on the brightness temperature that clearly favour a non-thermal emission mechanism. The radio emission is interpreted and modelled as synchrotron emission from the shock interaction between the nova ejecta and the circumbinary medium. The light curve shows a plateauing behaviour after the first peak, which can be explained by either a non-uniform density of the circumbinary medium or a second emission component. Allowing for a second component in the light-curve modelling captures the steep decay at late times. Furthermore, extrapolating this model to 15 yr after the outburst shows that the radio emission might not fully disappear between outbursts. Further modelling of the light curves indicates a red giant mass-loss rate of ∼5 × 10−8 M⊙ yr−1. The spectrum cannot be modelled in detail at this stage, as there are likely at least four emission components. Radio emission from stellar wind or synchrotron jets is ruled out as the possible origin of the radio emission. Finally, we suggest a strategy for future observations that would advance our understanding of the physical properties of RS Ophiuchi.
MicrobiomeAnalyst 2.0: comprehensive statistical, functional and integrative analysis of microbiome data
Authors: Lu Yao , Zhou Guangyan , Ewald Jessica , Pang Zhiqiang , Shiri Tanisha , Xia Jianguo 
Published: May 2023

Abstract
Microbiome studies have become routine in biomedical, agricultural and environmental sciences with diverse aims, including diversity profiling, functional characterization, and translational applications. The resulting complex, often multi-omics datasets demand powerful, yet user-friendly bioinformatics tools to reveal key patterns, important biomarkers, and potential activities. Here we introduce MicrobiomeAnalyst 2.0 to support comprehensive statistics, visualization, functional interpretation, and integrative analysis of data outputs commonly generated from microbiome studies. Compared to the previous version, MicrobiomeAnalyst 2.0 features three new modules: (i) a Raw Data Processing module for amplicon data processing and taxonomy annotation that connects directly with the Marker Data Profiling module for downstream statistical analysis; (ii) a Microbiome Metabolomics Profiling module to help dissect associations between community compositions and metabolic activities through joint analysis of paired microbiome and metabolomics datasets; and (iii) a Statistical Meta-Analysis module to help identify consistent signatures by integrating datasets across multiple studies. Other important improvements include added support for multi-factor differential analysis and interactive visualizations for popular graphical outputs, updated methods for functional prediction and correlation analysis, and expanded taxon set libraries based on the latest literature. These new features are demonstrated using a multi-omics dataset from a recent type 1 diabetes study. MicrobiomeAnalyst 2.0 is freely available at microbiomeanalyst.ca.
A cellular overview of immunometabolism in systemic lupus erythematosus
Authors: Psarras Antonios , Clarke Alexander 
Published: May 2023

Abstract
Systemic lupus erythematosus (SLE) is a complex autoimmune disease, characterized by a breakdown of immune tolerance and the development of autoantibodies against nucleic self-antigens. Immunometabolism is a rapidly expanding scientific field investigating the metabolic programming of cells of the immune system. During the normal immune response, extensive reprogramming of cellular metabolism occurs, both to generate adenosine triphosphate and facilitate protein synthesis, and also to manage cellular stress. Major pathways upregulated include glycolysis, oxidative phosphorylation, the tricarboxylic acid cycle and the pentose phosphate pathway, among others. Metabolic reprogramming also occurs to aid resolution of inflammation. Immune cells of both patients with SLE and lupus-prone mice are characterized by metabolic abnormalities resulting in an altered functional and inflammatory state. Recent studies have described how metabolic reprogramming occurs in many cell populations in SLE, particularly CD4+ T cells, e.g. favouring a glycolytic profile by overactivation of the mechanistic target of rapamycin pathway. These advances have led to an increased understanding of the metabolic changes affecting the inflammatory profile of T and B cells, monocytes, dendritic cells and neutrophils, and how they contribute to autoimmunity and SLE pathogenesis. In the current review, we aim to summarize recent advances in the field of immunometabolism involved in SLE and how these could potentially lead to new therapeutic strategies in the future.
Stress-related biomolecular condensates in plants
Authors: Solis-Miranda Jorge , Chodasiewicz Monika , Skirycz Aleksandra , Fernie Alisdair R , Moschou Panagiotis N , Bozhkov Peter V , Gutierrez-Beltran Emilio 
Published: May 2023

Abstract
Biomolecular condensates are membraneless organelle-like structures that can concentrate molecules and often form through liquid-liquid phase separation. Biomolecular condensate assembly is tightly regulated by developmental and environmental cues. Although research on biomolecular condensates has intensified in the past 10 years, our current understanding of the molecular mechanisms and components underlying their formation remains in its infancy, especially in plants. However, recent studies have shown that the formation of biomolecular condensates may be central to plant acclimation to stress conditions. Here, we describe the mechanism, regulation, and properties of stress-related condensates in plants, focusing on stress granules and processing bodies, 2 of the most well-characterized biomolecular condensates. In this regard, we showcase the proteomes of stress granules and processing bodies in an attempt to suggest methods for elucidating the composition and function of biomolecular condensates. Finally, we discuss how biomolecular condensates modulate stress responses and how they might be used as targets for biotechnological efforts to improve stress tolerance.
The dynamin GTPase mediates regenerative axonal fusion inCaenorhabditis elegansby regulating fusogen levels
Authors: Vijayaraghavan Tarika , Dhananjay Samiksha , Ho Xue Yan , Giordano-Santini Rosina , Hilliard Massimo , Neumann Brent 
Published: May 2023

AbstractAxonal fusion is a neuronal repair mechanism that results in the reconnection of severed axon fragments, leading to the restoration of cytoplasmic continuity and neuronal function. While synaptic vesicle recycling has been linked to axonal regeneration, its role in axonal fusion remains unknown. Dynamin proteins are large GTPases that hydrolyze lipid-binding membranes to carry out clathrin-mediated synaptic vesicle recycling. Here, we show that the Caenorhabditis elegans dynamin protein DYN-1 is a key component of the axonal fusion machinery. Animals carrying a temperature-sensitive allele of dyn-1(ky51) displayed wild-type levels of axonal fusion at the permissive temperature (15°C) but presented strongly reduced levels at the restrictive temperature (25°C). Furthermore, the average length of regrowth was significantly diminished in dyn-1(ky51) animals at the restrictive temperature. The expression of wild-type DYN-1 cell-autonomously into dyn-1(ky51) mutant animals rescued both the axonal fusion and regrowth defects. Furthermore, DYN-1 was not required prior to axonal injury, suggesting that it functions specifically after injury to control axonal fusion. Finally, using epistatic analyses and superresolution imaging, we demonstrate that DYN-1 regulates the levels of the fusogen protein EFF-1 post-injury to mediate axonal fusion. Together, these results establish DYN-1 as a novel regulator of axonal fusion.
Worried Sick: Perceptions of Low Public Support, Stress, and Somatic Health Problems in Law Enforcement
Authors: Baker Daniel B , Marier Christopher J , Cheek Merrily 
Published: May 2023

AbstractRecent surveys suggest that confidence in police reached its lowest level on record in the wake of controversial police custody deaths and associated protests in recent years. Meanwhile, research has found links between perceptions of low public support for police and a variety of negative outcomes among police officers, including stress and withdrawal. The consequences of psychological stress, according to much other research, include a variety of physical health problems. The present study synthesizes these bodies of research by examining whether perceptions of low public support are associated with physical, somatic symptoms in police officers, including headaches, gastrointestinal problems, sleep disturbances, and upper respiratory infections. Structural equation modelling of 4,221 officer surveys from a Southeastern U.S. state collected in January of 2022 suggests that officers are quite literally worried sick about poor police–public relations, and that stress mediates this relationship. We discuss the implications of these findings for officer wellness and the relationship between mental and physical well being among officers. Furthermore, we discuss practical recommendations for police leaders who may be struggling to promote officer wellness during a period of intense public scrutiny.
No More Women Killed in Spain! A Collaborative Femicide Prevention Effort of a Police-Led Team of Ministry of Interior and Academia
Authors: González-Álvarez José Luís , Viñas-Racionero Rosa , Santos-Hermoso Jorge , Carbonell-Vayá Enrique , Bermúdez-Sánchez María Paz , Pineda-Sánchez David , Borrás-Sansaloni Carmen , Chiclana-de la Fuente Sandra , Sotoca-Plaza Andrés , López-Ossorio Juan José , Garrido-Antón María José 
Published: May 2023

Abstract
With the turn of the new century, the Spanish government developed a series of initiatives to eradicate gender violence and intimate partner femicides. Among these initiatives, the Secretary of State for Security (SSS) of the Ministry of Interior organized a National Project (Team) for the Detailed Review of Intimate Partner Homicides—a police-led team that partnered with 21 Spanish universities and several correctional facilities across 50 provinces—to conduct a concurrent embedded, correlational mixed-methods study of a nationally representative sample of 171 femicide cases and a control group of 210 non-lethal partner abuse cases (2006–2021). The results of this study served to improve current law enforcement femicide risk prediction tools (Valoracion Policial del Riesgo, VPR) and to develop different offender typologies aiming at guiding treatment interventions. New recommendations were also provided to enhance collaboration between law enforcement and other agencies so extant partner violence cases can be appropriately managed.
Improving Police Data Collection to Measure Repeat Demand: A Focus on Domestic Violence and Abuse
Authors: Phoenix Jessica 
Published: May 2023

AbstractTargeting police resources at repeat demand may reduce overall demand. To effectively target resources at repetition requires repeat demand to be accurately measured in police data. Using domestic violence and abuse (DVA) as a case study of repeat demand, this study takes a deep dive into the data and information systems used by one police force to identify the key issues that prevent the effective measurement of repeat DVA-related demand. From observations of the police response to DVA and manual review of 325 DVA case files, four key issues are identified: (1) fragmented units of measurement across multiple information systems; (2) inconsistent recording of personal details; (3) multiple methods of identifying DVA; and (4) the embedding of information in free-text. This paper makes recommendations to improve the measurement of repeat demand in police data, with implications for police practitioners and researchers.
p-Adic statistical field theory and convolutional deep Boltzmann machines
Authors: Zúñiga-Galindo W A , He C , Zambrano-Luna B A 
Published: May 2023

Abstract
Understanding how deep learning architectures work is a central scientific problem. Recently, a correspondence between neural networks (NNs) and Euclidean quantum field theories has been proposed. This work investigates this correspondence in the framework of p-adic statistical field theories (SFTs) and neural networks. In this case, the fields are real-valued functions defined on an infinite regular rooted tree with valence p, a fixed prime number. This infinite tree provides the topology for a continuous deep Boltzmann machine (DBM), which is identified with a statistical field theory on this infinite tree. In the p-adic framework, there is a natural method to discretize SFTs. Each discrete SFT corresponds to a Boltzmann machine with a tree-like topology. This method allows us to recover the standard DBMs and gives new convolutional DBMs. The new networks use O(N) parameters while the classical ones use O(N2) parameters.