Miracle-dz/UniFAR-FTUs huggingface dataset:
Position-dependent power spectra of the 21-cm signal from the epoch of reionization

The 21-cm signal from the epoch of reionization is non-Gaussian. Current radio telescopes are focused on detecting the 21-cm power spectrum, but in the future the Square Kilometre Array is anticipated to provide a first measurement of the bispectrum. Previous studies have shown that the position-dependent power spectrum is a simple and efficient way to probe the squeezed-limit bispectrum. In this approach, the survey is divided into subvolumes and the correlation between the local power spectrum and the corresponding mean density of the subvolume is computed. This correlation is equivalent to an integral of the bispectrum in the squeezed limit, but is much simpler to implement than the usual bispectrum estimators. It also has a clear physical interpretation: it describes how the small-scale power spectrum of tracers such as galaxies and the 21-cm signal respond to a large-scale environment. Reionization naturally couples large and small scales as ionizing radiation produced by galactic sources can travel up to tens of Megaparsecs through the intergalactic medium during this process. Here we apply the position-dependent power spectrum approach to fluctuations in the 21-cm background from reionization. We show that this statistic has a distinctive evolution in time that can be understood with a simple analytic model. We also show that the statistic can easily distinguish between simple “inside-out” and “outside-in” models of reionization. The position-dependent power spectrum is thus a promising method to validate the reionization signal and to extract higher-order information on this process.
Measuring repeatability of compositional diet estimates: An example using quantitative fatty acid signature analysis

Abstract By measuring the temporal consistency, or repeatability, in the diets of predators, we can gain a better understanding of the degree of individual specialization in resource utilization and implications for predator–prey interactions, population dynamics, and food web structure. To measure repeatability, we require repeated diet estimates of individuals over time, such as those derived from quantitative fatty acid signature analysis (QFASA), a popular diet estimation technique. However, diet estimates are often lengthy compositional vectors with many zeros, as some prey will not be consumed by all individuals, precluding the use of previously proposed measures of repeatability. In this paper, we propose a novel approach for inferring repeatability for multivariate data and, in particular, compositional diet estimates. We extend the commonly used measure of repeatability for univariate data to the multivariate compositional setting by utilizing the mean squares obtained from a nonparametric multivariate analysis of variance, and an appropriate choice of statistical distance. Our measure and its extension are compatible with both balanced and unbalanced data sets. Associated confidence intervals via nonparametric bootstrapping are also developed for the case of QFASA diet estimates that incorporate both sampling error and measurement error, where the latter error arises because the diets of predators are estimated. Simulation study results suggest that for practical levels of repeatability, our methods yield confidence intervals with the desired coverage probability even when the sample size relative to the dimension of the data (i.e., number of prey species eaten) is small. We tested our methods using QFASA diet estimates for free‐ranging Northwest Atlantic grey seals. Given the importance of understanding how predator diets vary over time and space, our method may find broad application to other compositional diet estimates, including those derived from the stomach or fecal contents, and stable isotope analyses.
Anti-populist populism: Musical challenges to Trump's America and Erdoğan's Turkey

Abstract Populism is a discursive construct that represents popular interests and values by ‘pretend[ing] to speak’ for the people who are constructed separate and opposed to a powerful elite. Yet populism, in its various forms and accents, ‘can adapt flexibly to a variety of substantive ideological values and principles’. This is manifested in ‘the people’ not being a prefixed natural category, but a signifier that acquires meaning through discourses and contexts. This article considers how populism is articulated in hip hop videos that criticise two authoritarian-populist politicians: America's Trump and Turkey's Erdoğan. Using Multimodal Critical Discourse Studies, Eminem's ‘The Storm’ and Ezhel's ‘Yarınımız Yok (We have no tomorrow)’ are analysed to demonstrate how oppositional popular music can articulate its own brands of populism, transcending contexts, yet shaped by them.
Multiliteracy in the Millennial Generation: A Case Study of Political Cartoons on Instagram Tempodotco

This article aims to explore how the millennial generation understands multimodal texts. The problem is focused on how readers construct real-world references from cartoons, narrate cartoons, interpret respondents' facial expressions depicted, understand the relationship between text and images, and build metaphorical relationships between fictional cartoon scenes and political arguments. The data were collected through interviews with six people who were selected by year of birth as the millennial generation category and follow tempodotco on Instagram, but came from different backgrounds, and this data was analyzed qualitatively. This study concludes that political cartooning is a fairly complex process and requires one to draw from different literacies. The millennial generation's experience with various related events also affects them in dealing with them and the reader's familiarity with the cartoon genre, knowledge of cultural symbols, and the experience of analytical thinking about events and situations in the real world are also factors that determine readers.
K-Band Properties of Well-Sampled Groups of Galaxies

We use a sample of 55 groups and six clusters of galaxies ranging in mass from 7 × 1011 to 1.5 × 1015 M⊙ to examine the correlation of the Ks-band luminosity with mass discovered by Lin and coauthors in 2003. We use the Two-Micron All-Sky Survey catalog and published redshifts to construct complete magnitude-limited redshift surveys of the groups. From these surveys we explore the IR photometric properties of groups members, including their IR color distribution and luminosity function. Although we find no significant difference between the group Ks luminosity function and the general field, there is a difference between the color distribution of luminous group members and their counterparts (generally background) in the field. There is a significant population of luminous galaxies with H - Ks ≳ 0.35, which are rarely, if ever, members of the groups in our sample. The most luminous galaxies that populate the groups have a very narrow range of IR color. Over the entire mass range covered by our sample, the Ks luminosity increases with mass as L ∝ M0.64±0.06, implying that the mass-to-light ratio in the Ks band increases with mass. The agreement between this result and earlier investigations of essentially nonoverlapping sets of systems shows that this window in galaxy formation and evolution is insensitive to the selection of the systems and to the details of the mass and luminosity computations.
The Inverse Laplace Transform of a Wide Class of Special Functions

The aim of the present work is to obtain the inverse Laplace transform of the product of the factors of the type , a general class of polynomials an the multivariable H-function. The polynomials and the functions involved in our main formula as well as their arguments are quite general in nature. On account of the general nature of our main findings, the inverse Laplace transform of the product of a large variety of polynomials and numerous simple special functions involving one or more variables can be obtained as simple special cases of our main result. We give here exact references to the results of seven research papers that follow as simple special cases of our main result.
The geometries of visual space

Contents: Preface. Introduction: Contrasting Visual, Experiential, and Physical Space. Traditional Views of Geometry and Vision. Synthetic Approaches to Visual Space Perception. An Analytic Approach to Space and Vision. Effects of Context on Judgments of Distance, Area, Volume, and Angle. Factors Affecting Size Constancy. The Metrics of Visual Space: Multidimensional Approaches to Space Perception. Cognitive Maps, Memory, and Space Perception. The Geometries of Visual Space: Conclusion.
Most pseudo-bulges can be formed at later stages of major mergers

Most giant spiral galaxies have pseudo or disc-like bulges that are considered to be the result of purely secular processes. This may challenge the hierarchical scenario predicting about one major merger per massive galaxy (>3 × 1010 M⊙) since the last ∼9 billion years. Here, we verify whether or not the association between pseudo-bulges and secular processes is irrevocable. Using GADGET2N-body/SPH simulations, we have conducted a systematic study of remnants of major mergers for which progenitors have been selected (1) to follow the gas richness-look back time relationship, and (2) with a representative distribution of orbits and spins in a cosmological frame. Analysing the surface mass density profile of both nearby galaxies and merger remnants with two components, we find that most of them show pseudo-bulges or bar dominated centres. Even if some orbits lead to classical bulges just after the fusion, the contamination by the additional gas that gradually accumulates to the centre and forming stars later on, leads to remnants apparently dominated by pseudo-bulges. We also found that simple smoothed particle hydrodynamics (SPH) simulations should be sufficient to form realistic spiral galaxies as remnants of ancient gas-rich mergers without the need for specifically tuned feedback conditions. We then conclude that pseudo-bulges and bars in spiral galaxies are natural consequences of major mergers when they are realized in a cosmological context, i.e. with gas-rich progenitors as expected when selected in the distant Universe.
Statistics of phase correlations as a test for non-Gaussianity of the CMB maps

Gaussianity is the very basis for derivation of the cosmological parameters from the cosmic microwave background (CMB) angular power spectrum. Non-Gaussian signal, whether originated from experimental error or primordial source, could mimic extra power in the power spectrum, thereby leading to a wrong set of parameters. In this paper we present a new Gaussianity analysis of the derived CMB signals. It is based on the trigonometric moments of phases, which can be concluded with a ``mean angle,'' allowing us to see the global trend of non-Gaussianity of the signals. These moments are also closely related to the Pearson's random walks. We apply these analyses on the derived CMB maps and their different morphologies manifest themselves through these functions. We also comment on rotational invariance of the trigonometric moments of phases as a non-Gaussianity test.
Visual-motor integration scale for Korean elderly (VMIS-KE) is an effective indicator for cognitive changes in diabetic older adults

This study aimed to investigate the adequacy of the visual-motor inte-gration (VMI) scale for Korean elderly (VMIS-KE) compared to tradition-al measures, mini-mental state examination of Korean version (MMSE-KC) and Beery VMI for cognitive decline in diabetic older adults. For this explanatory research, data were collected from September 1 to Sep-tember 15, 2013, from 34 diabetic older adults and 31 nondiabetic older adults in Daegu and Gyeongsan of Korea. Mean differences between the two groups were analyzed with SPSS 18.0. The diabetic older adults showed significantly lower scores in the VMIS-KE (t=4.128, P<0.001) and MMSE-KC (t=2.231, P=0.029) compared with the nondiabetic older adults. In all subcategories of VMI-KE, figure cognition (t=5.342, P<0.001), memory (t=3.011, P=0.004) and spatial cognition (t=2.639, P=0.011), there were significant differences whereas no significant difference in the VMI-6th revision (t=0.994, P=0.325). VMIS-KE could be a sensitive indicator to assess cognitive change in older adults with diabetes and health care providers should periodically evaluate vulnerable groups such as them with it.
Generalization of Probabilistic Latent Semantic Analysis to k-partite Graphs

: Many data can be easily modelled as bipartite or k-partite graphs. Among the many computational analyses that can be run on such graphs, link prediction, i.e., the inference of novel links between nodes, is one of the most valuable and has many applications on real world data. While for bipartite graphs many methods exist for this task, only few algorithms are able to perform link prediction on k-partite graphs. The Probabilistic Latent Semantic Analysis (PLSA) is an algorithm based on latent variables, named topics, designed to perform matrix factorisation. As such, it is straightforward to apply PLSA to the task of link prediction on bipartite graphs, simply by decomposing the association matrix. In this work we extend PLSA to k-partite graphs; in particular we designed an algorithm able to perform link prediction on k-partite graphs, by exploiting the information in all the layers of the target graph. Our experiments confirm the capability of the proposed method to effectively perform link prediction on k-partite graphs.
MMP-9/BDNF ratio predicts more severe COVID-19 outcomes

COVID-19 clinically manifests from asymptomatic to the critical range. Immune response provokes the pro-inflammatory interactions, which lead to the cytokines, reactive oxygen/nitrogen species, peptidases, and arachidonic acid metabolites enlargement and activation of coagulation components. Matrix metalloproteinases (MMPs) contribute to tissue destruction in the development of COVID-19. Due to the endothelial, systemic course of the disease, VEGF A participates actively in COVID-19 development, while neurotrophic and metabolic effects of BDNF recommends for the prediction of complications in COVID-19 patients. Searching for a marker that would improve and simplify the ranking in COVID-19, the study intended to evaluate the relationship of MMP-9 with VEGF A, BDNF, and MMP-8 with the COVID-19 severity. Upon admission to the hospital and before the therapy administration, 77 patients were classified into a mild, moderate, severe, or critical group. Due to the inflammatory stage in COVID-19, a comparison between groups showed related differences in leukocytes, neutrophils, lymphocytes, and platelets counts as anticipated. Only in seriously ill patients, there is a significant increase in the serum concentration of MMP-9, MMP-8, and VEGF A, while BDNF values did not show significant variations between groups. However, all those parameters positively correlated with each other. The ratio of MMP-9/BDNF markedly decreased in the severe and critically patients compared to the mild group. Testing the capability of this ratio to predict the COVID-19 stage by ROC curves, we found the MMP-9/BDNF could be a suitable marker for differentiating stages I/II (AUC 0.7597), stage I/III (AUC 0.9011), and stage I/IV (AUC 0.7727). Presented data describe for the first time the high-level systemic MMP-9/BDNF ratio in patients with COVID-19. This parameter could contribute to a more precise determination of the phase of the disease.
Few-shot Approach for Systematic Literature Review Classifications

: Systematic Literature Review (SLR) studies aim to leverage relevant insights from scientiﬁc publications to achieve a comprehensive overview of the academic progress of a speciﬁc ﬁeld. In recent years, a major effort has been expended in automating the SLR process by extracting, processing, and presenting the synthesized ﬁndings. However, implementations capable of few-shot classiﬁcation for ﬁelds of study with a smaller amount of material available seem to be lacking. This study aims to present a system capable of conducting automated systematic literature reviews on classiﬁcation constraint by a few-shot learning. We propose an open-source, domain-agnostic meta-learning SLR framework for few-shot classiﬁcation, which has been validated using 64 SLR datasets. We also deﬁne an Adjusted Work Saved over Sampling (AWSS) metric to take into account the class imbalance during validation. The initial results show that AWSS@95% scored as high as 0.9 when validating our learner with data from 32 domains (just 16 examples were used for training in each domain), and only four of them resulted in scores lower than 0.1. These ﬁndings indicate signiﬁcant savings in screening time for literature reviewers.
Arginase: Biological and Therapeutic Implications in Diabetes Mellitus and Its Complications

Arginase is a ubiquitous enzyme in the urea cycle (UC) that hydrolyzes L-arginine to urea and L-ornithine. Two mammalian arginase isoforms, arginase1 (ARG1) and arginase2 (ARG2), play a vital role in the regulation of β-cell functions, insulin resistance (IR), and vascular complications via modulating L-arginine metabolism, nitric oxide (NO) production, and inflammatory responses as well as oxidative stress. Basic and clinical studies reveal that abnormal alterations of arginase expression and activity are strongly associated with the onset and development of diabetes mellitus (DM) and its complications. As a result, targeting arginase may be a novel and promising approach for DM treatment. An increasing number of arginase inhibitors, including chemical and natural inhibitors, have been developed and shown to protect against the development of DM and its complications. In this review, we discuss the fundamental features of arginase. Next, the regulatory roles and underlying mechanisms of arginase in the pathogenesis and progression of DM and its complications are explored. Furthermore, we review the development and discuss the challenges of arginase inhibitors in treating DM and its related pathologies.
Kodama time: Geometrically preferred foliations of spherically symmetric spacetimes

In a general time-dependent ($3+1$)-dimensional spherically symmetric spacetime, the so-called Kodama vector is a naturally defined geometric quantity that is timelike outside the evolving horizon and so defines a preferred class of fiducial observers. However the Kodama vector does not by itself define any preferred notion of time. We first extract as much information as possible by invoking the ``warped product'' structure of spherically symmetric spacetime to study the Kodama vector, and the associated Kodama energy flux, in a coordinate-independent manner. Using this formalism we construct a general class of conservation laws, generalizing Kodama's energy flux. We then demonstrate that a preferred time coordinate---which we shall call Kodama time---can be introduced by taking the additional step of applying the Clebsch decomposition theorem to the Kodama vector. We thus construct a geometrically preferred coordinate system for any time-dependent spherically symmetric spacetime, and explore its properties. We study the geometrically preferred fiducial observers, and demonstrate that it is possible to define and calculate a generalized notion of surface gravity that is valid throughout the entire evolving spacetime. Furthermore, by building and suitably normalizing a set of radial null geodesics, we can show that this generalized surface gravity passes several consistency tests and has a physically appropriate static limit.
Association of the changes in pulmonary artery diameters with clinical outcomes in hospitalized patients with COVID-19 infection: A crosssectional study

Objective: Enlarged pulmonary artery diameter (PAD) can be associated with mortality risk in coronavirus disease 2019 (COVID-19) patients. Our aim is to find the factors that cause changes in PAD and the relationship between radiological findings and clinical outcomes in COVID-19 patients. Patients and Methods: In this descriptive, retrospective, and single centered study, among the hospitalized 3264 patients, 209 patients with previous chest computed tomography (CT) were included. Findings of current chest CTs of patients obtained during COVID-19 were compared with that of previous chest CTs. Pulmonary involvements, World Health Organization (WHO) Clinical Progression Scale scores and laboratory variables were recorded. Intensive Care Unit (ICU) admission, intubation and mortality were clinical outcomes that were evaluated by using uni – and multivariate analyses. Results: Patients with high D-dimer had significantly increased risk for enlarged PAD and increase in PAD compared to previous chest CT (ΔPAD) (OR=1.18, p
TYPE I ERROR CONTROL OF TWO-GROUP MULTIVARIATE TESTS ON MEANS UNDER CONDITIONS OF HETEROGENEOUS CORRELATION STRUCTURE AND VARIED MULTIVARIATE DISTRIBUTIONS

ABSTRACT A Monte Carlo study was conducted to evaluate the performance of two-group multivariate tests on means under conditions of homogeneous and heterogeneous correlation structure and multivariate normality and nonnormality. The test statistics under study included those based on the work of Hotelling and alternative procedures proposed by James, Yao, Johansen, Nel and van der Merwe, and Kim. Results indicated that the F statistic based on Hotelling's T 2 was outperformed by the alternative procedures which showed good Type I error control under moderate to large sample sizes. Under small sample sizes, the alternative procedures tended to have unacceptable Type I error control. The F statistic based on Hotelling's T 2 is recommended for use when the sample size in each group is small (e.g., n = p + 1) and correlation heterogeneity is mild (<.3), or when groups are approximately equal in size. Though simulated conditions of multivariate nonnormality had some impact on the Type I error rates on some of the procedures, the impact was in general small and apparent only under the smaller sample size conditions.
ISOPHOTE SHAPES OF EARLY-TYPE GALAXIES IN MASSIVE CLUSTERS AT z ∼ 1 AND 0

We compare the isophote shape parameter a4 of early-type galaxies (ETGs) between z ∼ 1 and 0 as a proxy for dynamics to investigate the epoch at which the dynamical properties of ETGs are established, using cluster ETG samples with stellar masses of which have spectroscopic redshifts. We have 130 ETGs from the Hubble Space Telescope Cluster Supernova Survey for z ∼ 1 and 355 ETGs from the Sloan Digital Sky Survey for z ∼ 0. We have developed an isophote shape analysis method, which can be used for high-redshift galaxies and has been carefully compared with published results. We have applied the same method for both the z ∼ 1 and 0 samples. We find similar dependence of the a4 parameter on the mass and size at z ∼ 1 and 0; the main population of ETGs changes from disky to boxy at a critical stellar mass of with the massive end dominated by boxy. The disky ETG fraction decreases with increasing stellar mass both at z ∼ 1 and 0, and is consistent between these redshifts in all stellar mass bins when the Eddington bias is taken into account. Although uncertainties are large, the results suggest that the isophote shapes and probably dynamical properties of ETGs in massive clusters are already in place at z > 1 and do not significantly evolve in z < 1, despite significant size evolution in the same galaxy population. The constant disky fraction favors less violent processes than mergers as the main cause of the size and morphological evolution of intermediate mass ETGs in z < 1.