bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying uncertainty in deep learning approaches to radio galaxy classification
Authors: Mohan Devina , Scaife Anna M M , Porter Fiona , Walmsley Mike , Bowles Micah 
Published: January 2022

ABSTRACT
In this work we use variational inference to quantify the degree of uncertainty in deep learning model predictions of radio galaxy classification. We show that the level of model posterior variance for individual test samples is correlated with human uncertainty when labelling radio galaxies. We explore the model performance and uncertainty calibration for different weight priors and suggest that a sparse prior produces more well-calibrated uncertainty estimates. Using the posterior distributions for individual weights, we demonstrate that we can prune 30 per cent of the fully connected layer weights without significant loss of performance by removing the weights with the lowest signal-to-noise ratio. A larger degree of pruning can be achieved using a Fisher information based ranking, but both pruning methods affect the uncertainty calibration for Fanaroff–Riley type I and type II radio galaxies differently. Like other work in this field, we experience a cold posterior effect, whereby the posterior must be down-weighted to achieve good predictive performance. We examine whether adapting the cost function to accommodate model misspecification can compensate for this effect, but find that it does not make a significant difference. We also examine the effect of principled data augmentation and find that this improves upon the baseline but also does not compensate for the observed effect. We interpret this as the cold posterior effect being due to the overly effective curation of our training sample leading to likelihood misspecification, and raise this as a potential issue for Bayesian deep learning approaches to radio galaxy classification in future.
Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning
Authors: Tarsitano F , Bruderer C , Schawinski K , Hartley W G 
Published: January 2022

ABSTRACT
In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.
A GALAH view of the chemical homogeneity and ages of stellar strings identified in Gaia
Authors: Manea Catherine , Hawkins Keith , Maas Zachary G 
Published: January 2022

ABSTRACT
The advent of Gaia has led to the discovery of nearly 300 elongated stellar associations (called ‘strings’) spanning hundreds of parsecs in length and mere tens of parsecs in width. These newfound populations present an excellent laboratory for studying the assembly process of the Milky Way thin disc. In this work, we use data from GALAH DR3 to investigate the chemical distributions and ages of 18 newfound stellar populations, 10 of which are strings and 8 of which are compact in morphology. We estimate the intrinsic abundance dispersions in [X/H] of each population and compare them with those of both their local fields and the open cluster (OC) M 67. We find that all but one of these groups are more chemically homogeneous than their local fields. Furthermore, half of the strings, namely Theias 139, 169, 216, 303, and 309, have intrinsic [X/H] dispersions that range between 0.01 and 0.07 dex in most elements, equivalent to those of many OCs. These results provide important new observational constraints on star formation and the chemical homogeneity of the local interstellar medium (ISM). We investigate each population’s Li and chemical clock abundances (e.g. [Sc/Ba], [Ca/Ba], [Ti/Ba], and [Mg/Y]) and find that the ages suggested by chemistry generally support the isochronal ages in all but six structures. This work highlights the unique advantages that chemistry holds in the study of kinematically related stellar groups.
matryoshka: halo model emulator for the galaxy power spectrum
Authors: Donald-McCann Jamie , Beutler Florian , Koyama Kazuya , Karamanis Minas 
Published: January 2022

ABSTRACT
We present matryoshka, a suite of neural-network-based emulators and accompanying python package that have been developed with the goal of producing fast and accurate predictions of the non-linear galaxy power spectrum. The suite of emulators consists of four linear component emulators, from which fast linear predictions of the power spectrum can be made, allowing all non-linearities to be included in predictions from a non-linear boost component emulator. The linear component emulators include an emulator for the matter transfer function that produces predictions in ∼0.0004 s, with an error of ${\lt} 0.08{{\ \rm per\ cent}}$ (at 1σ level) on scales 10−4 &lt; k &lt; 101 h Mpc−1. In this paper, we demonstrate matryoshka by training the non-linear boost component emulator with analytic training data calculated with Halofit, which has been designed to replicate training data that would be generated using numerical simulations. Combining all the component emulator predictions we achieve an accuracy of ${\lt} 0.75{{\ \rm per\ cent}}$ (at 1σ level) when predicting the real space non-linear galaxy power spectrum on scales 0.0025 &lt; k &lt; 1 h Mpc−1. We use matryoshka to investigate the impact of the analysis set-up on cosmological constraints by conducting several full shape analyses of the real-space galaxy power spectrum. Specifically we investigate the impact of the minimum scale (or kmax), finding an improvement of ∼1.8× in the constraint on σ8 by pushing kmax from 0.25 to 0.85 h Mpc−1, highlighting the potential gains when using clustering emulators such as matryoshka in cosmological analyses.
Metallicity distribution of the progenitor of the Giant Stellar Stream in the Andromeda Galaxy
Authors: Milošević S , Mićić M , Lewis G F 
Published: January 2022

ABSTRACT
The Giant Stellar Stream (GSS) is a prominent tidal feature in the halo of the Andromeda galaxy (M31), representing the ongoing destruction of a satellite galaxy. In this paper, we investigate the formation of the GSS through detailed numerical simulations of the tidal disruption of a progenitor system. Assuming that the stream was created in a single merger event between M31 and a dwarf spheroidal galaxy with stellar mass $10^{9}\, {\rm M}_{\odot }$, we successfully reproduce the dynamical properties of the GSS. As the metallicity distribution along the stream has been well determined from observations (Pan-Andromeda Archaeological Survey and Absorption Maps in the Gas of Andromeda data sets), we use Monte Carlo simulations to reconstruct the original metallicity distribution of the dwarf progenitor. We find that a progenitor dwarf galaxy with a negative radial metallicity gradient, ΔFeH = −0.3 ± 0.2, reproduces the observed GSS properties at a time between 2.4 and 2.9 Gyr into the merger. We also show that the observed double-peak metallicity distribution along the stream is a transitory structure caused by unique merger circumstances where two groups of streaming stars are moving in opposite directions, intersecting to produce the peaks.
Filamentation of fast radio bursts in magnetar winds
Authors: Sobacchi Emanuele , Lyubarsky Yuri , Beloborodov Andrei M , Sironi Lorenzo 
Published: January 2022

ABSTRACT
Magnetars are the most promising progenitors of fast radio bursts (FRBs). Strong radio waves propagating through the magnetar wind are subject to non-linear effects, including modulation/filamentation instabilities. We derive the dispersion relation for modulations of strong waves propagating in magnetically dominated pair plasmas focusing on dimensionless strength parameters a0 ≲ 1, and discuss implications for FRBs. As an effect of the instability, the FRB-radiation intensity develops sheets perpendicular to the direction of the wind magnetic field. When the FRB front expands outside the radius where the instability ends, the radiation sheets are scattered due to diffraction. The FRB-scattering time-scale depends on the properties of the magnetar wind. In a cold wind, the typical scattering time-scale is τsc ∼  $\mu$s–ms at the frequency $\nu \sim 1\, {\rm GHz}$. The scattering time-scale increases at low frequencies, with the scaling τsc ∝ ν−2. The frequency-dependent broadening of the brightest pulse of FRB 181112 is consistent with this scaling. From the scattering time-scale of the pulse, one can estimate that the wind Lorentz factor is larger than a few tens. In a warm wind, the scattering time-scale can approach $\tau _{\rm sc}\sim \, {\rm ns}$. Then scattering produces a frequency modulation of the observed intensity with a large bandwidth, $\Delta \nu \sim 1/\tau _{\rm sc}\gtrsim 100\, {\rm MHz}$. Broad-band frequency modulations observed in FRBs could be due to scattering in a warm magnetar wind.
Quasi-periodic spicule-like cool jets driven by Alfvén pulses
Authors: Singh B , Srivastava A K , Sharma K , Mishra S K , Dwivedi B N 
Published: January 2022

ABSTRACT
We perform a 2.5D magnetohydrodynamic simulation to gain a comprehensive understanding of the formation of spicule-like cool jets caused by initial transverse velocity pulses akin to Alfvén pulses in the solar chromosphere. We invoke multiple velocity (Vz) pulses between 1.5 and 2.0 Mm in the solar atmosphere, which create the initial transverse velocity perturbations. These pulses transfer energy non-linearly to the field-aligned perturbations via the ponderomotive force. This physical process further creates magnetoacoustic shocks followed by quasi-periodic plasma motions in the solar atmosphere. The field-aligned magnetoacoustic shocks move upwards, which subsequently causes the quasi-periodic rise and fall of chromospheric plasma into the overlying corona as thin and cool spicule-like jets. The magnitude of the initial applied transverse velocity pulses is taken in the range of 50–90 km s−1. These pulses are found to be strong enough to generate spicule-like jets. We analyse the evolution, kinematics and energetics of these spicule-like jets. We find that the transported mass flux and kinetic energy density are substantial in the local solar corona. These mass motions generate in situ quasi-periodic oscillations on the scale of ≃ 4.0 min above the transition region.
Is Illicit Cigarette Market a Threat to Tobacco Control in Ethiopia?
Authors: Dauchy Estelle , Ross Hana 
Published: January 2022

Abstract

Introduction
The presence of an illicit cigarette trade is used as an argument in Ethiopia to halt pro-health tobacco tax policies. The National Tobacco Enterprise (NTE) recently reported that the illicit cigarette market accounts for over 61% of the total market, and over 90% in the Eastern part of Ethiopia.

Aims and Methods
The aim of the study is to estimate the magnitude of the illicit cigarette trade in Ethiopia. We employed a cross-sectional observational study of empty packs collected in Ethiopia from retailers and from the streets in 10 towns, representing 10 regional states, and two autonomous cities.

Results
The majority (80.1%) of the 6438 empty cigarette packs collected (5368 from the streets and 1070 from retailers) belonged to locally produced brands, while the remaining 19.9% were foreign packs, including those allowed to trade in Ethiopia. Overall, 18.9% of the collected empty packs were classified as illicit. However, the share of illicit cigarette packs varied considerably across the country with as many as 97.7% of the packs collected near the Eastern border being illicit. Since the smoking prevalence is significantly higher in that part of Ethiopia, the weighted estimate of illicit cigarette market reached 45.4%.

Conclusions
To address this alarming situation, Ethiopia should adopt technologies such as a track and trace system to control its cigarette supply chain, because cigarette packs currently bear no indication that the proper tax was paid. In addition, law enforcement and border security need to be strengthened, especially in the East.

Implications
This is the first study to estimate the magnitude of the illicit cigarette trade in Ethiopia. It shows that the illicit cigarette trade is low in most parts of the country, but points to some problematic areas near the border with Somalia where illicit cigarette prevalence and overall smoking prevalence are high. We propose a solution to control illicit cigarette trade in Ethiopia that the whole region would benefit from.
Antibiotic Resistance Patterns and Association With the Influenza Season in the United States: A Multicenter Evaluation Reveals Surprising Associations Between Influenza Season and Resistance in Gram-Negative Pathogens
Authors: Gupta Vikas , Yu Kalvin C , Kabler Heidi , Watts Janet A , Amiche Amine 
Published: January 2022

Abstract

Background
Viral infections are often treated with empiric antibiotics due to suspected bacterial coinfections, leading to antibiotic overuse. We aimed to describe antibiotic resistance (ABR) trends and their association with the influenza season in ambulatory and inpatient settings in the United States.

Methods
We used the BD Insights Research Database to evaluate antibiotic susceptibility profiles in 30-day nonduplicate bacterial isolates collected from patients &gt;17 years old at 257 US healthcare institutions from 2011 to 2019. We investigated ABR in Gram-positive (Staphylococcus aureus and Streptococcus pneumoniae) and Gram-negative (Enterobacterales [ENT], Pseudomonas aeruginosa [PSA], and Acinetobacter baumannii spp [ACB]) bacteria expressed as the proportion of isolates not susceptible ([NS], intermediate or resistant) and resistance per 100 admissions (inpatients only). Antibiotics included carbapenems (Carb), fluoroquinolones (FQ), macrolides, penicillin, extended-spectrum cephalosporins (ESC), and methicillin. Generalized estimating equations models were used to evaluate monthly trends in ABR outcomes and associations with community influenza rates.

Results
We identified 8 250 860 nonduplicate pathogens, including 154 841 Gram-negative Carb-NS, 1 502 796 Gram-negative FQ-NS, 498 012 methicillin-resistant S aureus (MRSA), and 44 131 NS S pneumoniae. All S pneumoniae rates per 100 admissions (macrolide-, penicillin-, and ESC-NS) were associated with influenza rates. Respiratory, but not nonrespiratory, MRSA was also associated with influenza. For Gram-negative pathogens, influenza rates were associated with the percentage of FQ-NS ENT, FQ-NS PSA, and Carb-NS ACB.

Conclusions
Our study showed expected increases in rates of ABR Gram-positive and identified small but surprising increases in ABR Gram-negative pathogens associated with influenza activity. These insights may help inform antimicrobial stewardship initiatives.
Efficient approaches for harvesting solar energy in cogeneration: a review
Authors: Yao Jian , Liu Wenjie , Jiang Yifan , Zheng Sihang , Zhao Yao , Dai Yanjun , Zhu Junjie , Novakovic Vojislav 
Published: January 2022

Abstract
Stronger urbanization will increase the demand for power and thermal energy to meet the new energy service requirements, which often leads to higher fossil fuels use and emissions. Renewable energy utilization has high potential in urban context to reduce carbon emissions. Solar energy in particular has proved to be promising renewable source due to its ubiquity, abundance and sustainability. Efficient utilization of solar energy for cogeneration is an important application in the built environment, with wide applicability. This review provides a comprehensive state-of-the-art analysis of solar energy for combined heat and power supply based on the available literature. Different approaches to solar cogeneration are classified and critically reviewed. The review shows that efficient solar cogeneration methods could significantly improve the utilization efficiency of solar energy.
High-Ultrahigh Temperature Metamorphism in the Larsemann Hills: Insights into the Tectono-Thermal Evolution of the Prydz Bay Region, East Antarctica
Authors: Wang Wei-(Rz) , Zhao Yue , Wei Chunjing , Daczko Nathan R , Liu Xiaochun , Xiao Wenjiao , Zhang Zhiyong 
Published: January 2022

Abstract
As one of the widest terranes exposed in icy Antarctica, the Larsemann Hills in the Prydz Bay belt preserves diverse rock types with a complex metamorphic history and thus is critical to the tectono-metamorphic evolution of East Antarctica. Garnet-sillimanite-spinel-cordierite–bearing and garnet-orthopyroxene–bearing granulites are typical rocks in the region. Phase equilibrium modelling and mineral thermometry based on detailed petrological and mineralogical analyses indicate that the granulites underwent extreme metamorphism with peak conditions to ultrahigh temperatures (UHTs). The high-UHT metamorphism is characterised by extremely high dT/dP values (&gt;1000°C/GPa) along a clockwise path with evident decompression at high temperatures and subsequent near isobaric cooling. Textural relationships, in situ NanoSIMS zircon U–Pb analysis, and LA-ICP-MS zircon and monazite dating and trace element analysis indicate protracted tectono-thermal evolution from the latest Neoproterozoic to early Palaeozoic (c. 570–500 Ma), with a prograde stage likely from c. 570 to c. 550 Ma, a peak stage from c. 550 to c. 540 Ma, and a retrograde stage from c. 540 to c. 500 Ma. During the retrograde stage, major decompression should have occurred before c. 530 Ma, as indicated by the age of zircon included in spinel, and then near isobaric cooling followed and persisted from c. 530 to c. 500 Ma. The geochronological data contribute to the establishment of the thermal–temporal framework of the late Neoproterozoic to early Palaeozoic Prydz tectonic event. The results also indicate that the assemblage of the investigated granulites basically resulted from the late Neoproterozoic to the early Palaeozoic tectono-thermal event, and the high-UHT conditions revealed by the granulites in the Larsemann Hills imply a much wider distribution of high heat flow and potential UHT metamorphism in the Prydz Bay region. Both the Larsemann Hills and the Rauer Group may have been in a similar and interrelated tectono-thermal setting from the late Neoproterozoic to the early Palaeozoic during the assembly of the Gondwana supercontinent.
BRASSINOSTEROID-SIGNALING KINASE1 modulates MAP KINASE15 phosphorylation to confer powdery mildew resistance in Arabidopsis
Authors: Shi Hua , Li Qiuyi , Luo Mingyu , Yan Haojie , Xie Bao , Li Xiang , Zhong Guitao , Chen Desheng , Tang Dingzhong 
Published: January 2022

Abstract
Perception of pathogen-associated molecular patterns (PAMPs) by plant cell surface-localized pattern-recognition receptors (PRRs) triggers the first line of plant innate immunity. In Arabidopsis thaliana, the receptor-like cytoplasmic kinase BRASSINOSTEROID-SIGNALING KINASE1 (BSK1) physically associates with PRR FLAGELLIN SENSING2 and plays an important role in defense against multiple pathogens. However, how BSK1 transduces signals to activate downstream immune responses remains elusive. Previously, through whole-genome phosphorylation analysis using mass spectrometry, we showed that phosphorylation of the mitogen-activated protein kinase (MAPK) MPK15 was affected in the bsk1 mutant compared with the wild-type plants. Here, we demonstrated that MPK15 is important for powdery mildew fungal resistance. PAMPs and fungal pathogens significantly induced the phosphorylation of MPK15 Ser-511, a key phosphorylation site critical for the functions of MPK15 in powdery mildew resistance. BSK1 physically associates with MPK15 and is required for basal and pathogen-induced MPK15 Ser-511 phosphorylation, which contributes to BSK1-mediated fungal resistance. Taken together, our data identified MPK15 as a player in plant defense against powdery mildew fungi and showed that BSK1 promotes fungal resistance in part by enhancing MPK15 Ser-511 phosphorylation. These results uncovered a mechanism of BSK1-mediated disease resistance and provided new insight into the role of MAPK phosphorylation in plant immunity.
Maize Interveinal Chlorosis 1 links the Yang Cycle and Fe homeostasis through Nicotianamine biosynthesis
Authors: Sun Wentao , Zhou Xiaojin J , Chen Chen , Zhang Xin , Tian Xiaolong , Xiao Ke , Liu Chenxu , Chen Rumei , Chen Shaojiang 
Published: January 2022

Abstract
The Yang cycle is involved in many essential metabolic pathways in plant growth and development. As extended products of the Yang cycle, the function and regulation network of ethylene and polyamines are well characterized. Nicotianamine (NA) is also a product of this cycle and works as a key metal chelator for iron (Fe) homeostasis in plants. However, interactions between the Yang cycle and NA biosynthesis remain unclear. Here, we cloned maize interveinal chlorosis 1 (mic1), encoding a 5′-methylthioadenosine nucleosidase (MTN), that is essential for 5′-methylthioadenosine (MTA) salvage and NA biosynthesis in maize (Zea mays). A single base G–A transition in the fourth exon of mic1 causes a Gly to Asp change, resulting in increased MTA, reduced Fe distribution, and growth retardation of seedlings. Knockout of ZmMIC1 but not its paralog ZmMTN2 by CRISPR/Cas9 causes interveinal chlorosis, indicating ZmMIC1 is mainly responsible for MTN activity in maize. Transcriptome analysis showed a typical response of Fe deficiency. However, metabolic analysis revealed dramatically reduced NA content in mic1, suggesting NA biosynthesis was impaired in the mutant. Exogenous application of NA transiently reversed the interveinal chlorosis phenotype of mic1 seedlings. Moreover, the mic1 mutant overexpressing a NA synthase gene not only recovered from interveinal chlorosis and growth retardation but was also fertile. These findings provide a link between the Yang cycle and NA biosynthesis, which highlights an aspect of Fe homeostasis regulation in maize.