Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical determination of bulk flow motions

We present here a new parameterization for the bulk motions of galaxies and clusters (in the linear regime) that can be measured statistically from the shape and amplitude of the two-dimensional two-point correlation function. We further propose the one-dimensional velocity dispersion (vp) of the bulk flow as a complementary measure of redshift-space distortions, which is model-independent and not dependent on the normalisation method. As a demonstration, we have applied our new methodology to the C4 cluster catalogue constructed from Data Release Three (DR3) of the Sloan Digital Sky Survey. We find vp = 270+433 km/s (also consistent with vp = 0) for this cluster sample (at = 0.1), which is in agreement with that predicted for a WMAP5-normalised ΛCDM model (i.e., vp(ΛCDM) = 203 km/s). This measurement does not lend support to recent claims of excessive bulk motions ( 1000 km/s) which appear in conflict with ΛCDM, although our large statistical error cannot rule them out. From the measured coherent evolution of vp, we develop a technique to re-construct the perturbed potential, as well as estimating the unbiased matter density fluctuations and scale-independent bias.
Child Welfare Reform: A Scoping Review

While there have been ongoing calls to reform child welfare so that it better meets children’s and families’ needs, to date there have been no comprehensive summaries of child welfare reform strategies. For this systematic scoping review, we summarized authors’ recommendations for improving child welfare. We conducted a systematic search (2010 to 2021) and included published reviews that addressed authors’ recommendations for improving child welfare for children, youth, and families coming into contact with child welfare in high-income countries. A total of 4758 records was identified by the systematic search, 685 full-text articles were screened for eligibility, and 433 reviews were found to be eligible for this scoping review. Reviews were theoretically divided, with some review authors recommending reform efforts at the macro level (e.g., addressing poverty) and others recommending reform efforts at the practice level (e.g., implementing evidence-based parenting programs). Reform efforts across socioecological levels were summarized in this scoping review. An important next step is to formulate what policy solutions are likely to lead to the greatest improvement in safety and well-being for children and families involved in child welfare.
Vasoplegic Syndrome after Cardiopulmonary Bypass in Cardiovascular Surgery: Pathophysiology and Management in Critical Care

Vasoplegic syndrome (VS) is a common complication following cardiovascular surgery with cardiopulmonary bypass (CPB), and its incidence varies from 5 to 44%. It is defined as a distributive form of shock due to a significant drop in vascular resistance after CPB. Risk factors of VS include heart failure with low ejection fraction, renal failure, pre-operative use of angiotensin-converting enzyme inhibitors, prolonged aortic cross-clamp and left ventricular assist device surgery. The pathophysiology of VS after CPB is multi-factorial. Surgical trauma, exposure to the elements of the CPB circuit and ischemia-reperfusion promote a systemic inflammatory response with the release of cytokines (IL-1β, IL-6, IL-8, and TNF-α) with vasodilating properties, both direct and indirect through the expression of inducible nitric oxide (NO) synthase. The resulting increase in NO production fosters a decrease in vascular resistance and a reduced responsiveness to vasopressor agents. Further mechanisms of vasodilation include the lowering of plasma vasopressin, the desensitization of adrenergic receptors, and the activation of ATP-dependent potassium (KATP) channels. Patients developing VS experience more complications and have increased mortality. Management includes primarily fluid resuscitation and conventional vasopressors (catecholamines and vasopressin), while alternative vasopressors (angiotensin 2, methylene blue, hydroxocobalamin) and anti-inflammatory strategies (corticosteroids) may be used as a rescue therapy in deteriorating patients, albeit with insufficient evidence to provide any strong recommendation. In this review, we present an update of the pathophysiological mechanisms of vasoplegic syndrome complicating CPB and discuss available therapeutic options.
Playing Games with the Law

* Assistant Professor, Northwestern University School of Law; Research Fellow, American Bar Foundation. B.A., Yale University; J.D. , Yale Law School; Ph.D. (Economics), Massachusetts Institute of Technology. Avery Katz and Daryl Warder provided helpful comments. 1. Franklin M. Fisher, Games Economists Play. A Noncooperative View, 20 RANDJ. ECON. 113, 113 (1989). Fisher's description of the "ascendancy" is echoed by other economists. See, e.g., Carl Shapiro, The Theory of Business Strategy, 20 RANDJ. ECON. 125, 125 (1989) ("This new wave of [industrial organization] research consists almost exclusively of game-theoretic studies of behavior and performance in imperfectly competitive markets."). 2. A casual glance at any issue of the leading microeconomic journals such as RandJournal of Economics or Review of Economic Studies will reveal several game theory articles. See, e.g., Joseph Farrell & Garth Saloner, Standardization, Compatibility, and Innovation, 16 RANDJ. ECON. 70 (1985); Drew Fudenberg & Jean Tirole, Sequential Bargaining with Incomplete Information, 50 REV. ECON. STUD. 221 (1983). 3. Nobel Prize winning economist Paul Anthony Samuelson formalized the marginalist method of utility and profit maximization. See PAUL ANTHONY SAMUELSON, FOUNDATIONS OF ECONOMIC ANALYSIS (1947). 4. The new game theory is dominated by a closely knit group of co-authors which includes David Kreps, Eric Maskin, Roger Myerson, Garth Saloner, Jean Tirole, and Robert Wilson. These theorists often collaborate, and the history of game-theoretic advances turns on the axes of their academic institutions: Stanford, M.I. T. , Northwestern, and Harvard. See, e.g., David M. Kreps, Paul Milgrom, John Roberts & Robert Wilson, Rational Cooperation in the Finitely Repeated Prisoners' Dilemma, 27J. ECON. THEORY 245 (1982); Eric Maskin & Jean Tirole, Correlated Equilibria and Sunspots, 43 J. ECON. THEORY 364 (1987).
Emergent Gravity and Weyl's Volume Formula

In physical theories where the energy (action) is localized near a submanifold of Euclidean (Minkowski) space, there is a universal expression for the energy (or the action). We derive a multipole expansion for the energy that has a finite number of terms, and depends on intrinsic geometric invariants of the submanifold and extrinsic invariants of the embedding of the submanifold. This universal expression is a generalization of an exact formula of Hermann Weyl for the volume of a tube. We describe when our result is applicable, when our generalization gives an exact result, and when there are corrections (often exponentially small) to our formula. In special situations, dictated by spherical symmetry, the expression is a generalized Lovelock lagrangian for gravity, a class of theories that are interesting because they have no negative metric states. We discuss whether these results represent a true theory of emergent gravity by discussing simple models where a higher dimensional quantum field theory without a fundamental graviton leads to a gravity-like theory on a submanifold where all or some of the dynamical degrees of freedom are fluctuations of the metric on the submanifold.
Impact of PM2.5 and PM10 Emissions on Changes of Their Concentration Levels in Lithuania: A Case Study

Due to negative effects on human health and visibility, atmospheric particulate matter (PM) is a prioritized contaminant for urban air pollution management. Over the past few decades, managing emissions have been a top priority. This paper investigated PM national inventory data and mass concentration trends for Lithuania. This analysis considers primary (sum of filterable and condensable) PM2.5 and PM10 emissions from point, mobile on-road and off-road, industry, agriculture, and waste sectors. In this study, by examining both the emissions and the mass concentrations of PM10, the effects of emissions decreasing with a concentration decrease were revealed. The slower decreasing tendency of PM10 and BC (0.03 Gg/year) than that of PM2.5 (0.1 Gg/year) should be noted. Furthermore, the correlation analysis also finds that the increase in PM10 from stationary and mobile combustion sources is closely related to the increase in the contribution to the pollution level.
FOREIGN DIRECTORS AND FIRM FINANCIAL PERFORMANCE: EVIDENCE FROM THE TANZANIAN LISTED COMPANIES

This study investigates the impact of foreign directors on the financial performance of the Tanzanian listed firms. The study applies balanced panel data Ordinary Least Square (OLS) regression analysis on 120 firm-years observations obtained from the firms’ audited annual reports and from the OSIRIS database from 2006 to 2018. The study findings support agency and resource dependence theories that foreign directors have a positive relationship with the firms’ financial performance. The findings indicate further that foreign directors enhance firm performance by providing the firm’s Board of Directors with effective and efficient overseeing and advice to the CEO and the top management. This study contributes to the understanding of the impact of foreign directors on firm performance and provides researched based evidence to Tanzanian policy makers on the importance of foreign members on the firm’s Board of Directors. Unlike the previous corporate governance studies, which focused on developed countries, this study examines the effects of foreign members on the Boards of Directors of listed firms in Tanzania, a developing country where very few corporate governance studies have been conducted. The study recommends policy makers in Tanzania to use the results of this original study while preparing or reviewing Corporate Governance Regulations.
Past and Present Star Formation in the SMC: NGC 346 and its Neighborhood

In the quest to understand how star formation occurs and propagates in the low-metallicity environment of the Small Magellanic Cloud (SMC), we acquired deep F555W (∼V) and F814W (∼I) Hubble Space Telescope ACS images of the young and massive star-forming region NGC 346. These images and their photometric analysis provide us with a snapshot of the star formation history of the region. We find evidence for star formation extending from ≈10 Gyr in the past until ≈150 Myr in the field of the SMC. The youngest stellar population (∼3 ± 1 Myr) is associated with the NGC 346 cluster. It includes a rich component of low-mass pre-main-sequence stars mainly concentrated in a number of subclusters spatially colocated with CO clumps previously detected by Rubio and coworkers. Within our analysis uncertainties, these subclusters appear coeval with each other. The most massive stars appear concentrated in the central subclusters, indicating possible mass segregation. A number of embedded clusters are also observed. This finding, combined with the overall wealth of dust and gas, could imply that star formation is still active. An intermediate-age star cluster, BS 90, formed ∼4.3 ± 0.1 Gyr ago, is also present in the region. Thus, this region of the SMC has supported star formation with varying levels of intensity over much of the cosmic time.
Force-Extension Curve of a Polymer Chain Entangled with a Static Ring-Shaped Obstacle

The way to theoretically approach dynamic and static topological constraints of polymer entanglements still presents a great challenge in polymer physics. So far, only the problem of static entanglement with multiple simple objects has been solved in theory by a superspace approach in our previous work. This work is devoted to extending the superspace approach to study a polymer chain entangled with a relatively complicated object—a ring-shaped object with genus one. Taking advantage of the axial symmetry of the model setup, the 3D diffusion equations in the superspace can be numerically solved within the 2D coordinates using a specially designed alternating-direction implicit (ADI) scheme. A series of numerical calculations reveal that the topological entanglement effect of the ring will exert a topological entropy attractive force on the linear chain, which can be used to explain the viscosity-increase phenomenon observed in recent simulations and experiments. Furthermore, the influences of the ring size and the entangling modes on the topological entropy force are also investigated by examining the corresponding force-extension curves. This work, together with our previous work, might pave the path toward the complete formulation of static topological constraints.
Tissue Factor, Thrombosis, and Chronic Kidney Disease

Coagulation abnormalities are common in chronic kidney disease (CKD). Tissue factor (TF, factor III) is a master regulator of the extrinsic coagulation system, activating downstream coagulation proteases, such as factor Xa and thrombin, and promoting fibrin formation. TF and coagulation proteases also activate protease-activated receptors (PARs) and are implicated in various organ injuries. Recent studies have shown the mechanisms by which thrombotic tendency is increased under CKD-specific conditions. Uremic toxins, such as indoxyl sulfate and kynurenine, are accumulated in CKD and activate TF and coagulation; in addition, the TF–coagulation protease–PAR pathway enhances inflammation and fibrosis, thereby exacerbating renal injury. Herein, we review the recent research studies to understand the role of TF in increasing the thrombotic risk and CKD progression.
Two Tails in NGC 3656 and the Major Merger Origin of Shell and Minor-Axis Dust Lane Elliptical Galaxies

I report on the discovery of two faint (~26.8 R mag arcsec-2) tidal tails around the shell elliptical galaxy NGC 3656 (Arp 155). This galaxy had previously been interpreted as a case of accretion, or minor merger. The two tidal tails are inconsistent with a minor merger and point instead to a disk-disk major merger origin. NGC 3656 extends Toomre's merger sequence toward normal elliptical galaxies and hints at a major merger origin for shells and minor-axis dust lanes. A dwarf galaxy lies at the tip of one of the tidal tails. A prominent shell, which shows sharp azimuthal color discontinuities, belongs to a rotating dynamical component with young stars that includes the inner dust lane.
Data-Driven Medicine in the Diagnosis and Treatment of Infertility

Infertility, although not a life-threatening condition, affects around 15% of couples trying for a pregnancy. The increasing availability of large datasets from various sources, together with advances in machine learning (ML) and artificial intelligence (AI), are enabling a transformational change in infertility care. However, real-world applications of data-driven medicine in infertility care are still relatively limited. At present, very little can prevent infertility from arising; more work is required to learn about ways to improve natural conception and the detection and diagnosis of infertility, improve assisted reproduction treatments (ART) and ultimately develop useful clinical-decision support systems to assure the successful outcome of either fertility preservation or infertility treatment. In this opinion article, we discuss recent influential work on the application of big data and AI in the prevention, diagnosis and treatment of infertility. We evaluate the challenges of the sector and present an interpretation of the different innovation forces that are driving the emergence of a systems approach to infertility care. Efforts including the integration of multi-omics information, collection of well-curated biological samples in specialised biobanks, and stimulation of the active participation of patients are considered. In the era of Big Data and AI, there is now an exciting opportunity to leverage the progress in genomics and digital technologies and develop more sophisticated approaches to diagnose and treat infertility disorders.
The Star–Planet Connection. I. Using Stellar Composition to Observationally Constrain Planetary Mineralogy for the 10 Closest Stars

The compositions of stars and planets are connected, but the definition of “habitability” and the “habitable zone” only take into account the physical relationship between the star and planet. Planets, however, are made truly habitable by both chemical and physical processes that regulate climatic and geochemical cycling between atmosphere, surface, and interior reservoirs. Despite this, an “Earth-like” planet is often defined as a planet made of a mixture of rock and Fe that is roughly 1 Earth-density. To understand the interior of a terrestrial planet, the stellar abundances of planet-building elements (e.g., Mg, Si, and Fe) can be used as a proxy for the planet’s composition. We explore the planetary mineralogy and structure for fictive planets around the 10 stars closest to the Sun using stellar abundances from the Hypatia Catalog. Although our sample contains stars that are both sub- and super-solar in their abundances, we find that the mineralogies are very similar for all 10 planets—since the error or spread in the stellar abundances create significant degeneracy in the models. We show that abundance uncertainties need to be on the order of [Fe/H] < 0.02 dex, [Si/H] < 0.01 dex, [Al/H] < 0.002 dex, while [Mg/H] and [Ca/H] < 0.001 dex in order to distinguish two unique planetary populations in our sample of 10 stars. While these precisions are high, we believe that they are possible given certain abundance techniques, in addition to methodological transparency, that have recently been demonstrated in the literature. However, without these precisions, the uncertainty in planetary structures will be so high that we will be unable to confidently state that a planet is like the Earth, or unlike anything we have ever seen.
An Unsupervised Machine Learning Method for Electron–Proton Discrimination of the DAMPE Experiment

Galactic cosmic rays are mostly made up of energetic nuclei, with less than 1% of electrons (and positrons). Precise measurement of the electron and positron component requires a very efficient method to reject the nuclei background, mainly protons. In this work, we develop an unsupervised machine learning method to identify electrons and positrons from cosmic ray protons for the Dark Matter Particle Explorer (DAMPE) experiment. Compared with the supervised learning method used in the DAMPE experiment, this unsupervised method relies solely on real data except for the background estimation process. As a result, it could effectively reduce the uncertainties from simulations. For three energy ranges of electrons and positrons, 80–128 GeV, 350–700 GeV, and 2–5 TeV, the residual background fractions in the electron sample are found to be about (0.45 ± 0.02)%, (0.52 ± 0.04)%, and (10.55 ± 1.80)%, and the background rejection power is about (6.21 ± 0.03) ×104, (9.03 ± 0.05) ×104, and (3.06 ± 0.32) ×104, respectively. This method gives a higher background rejection power in all energy ranges than the traditional morphological parameterization method and reaches comparable background rejection performance compared with supervised machine learning methods.
An Intermediate-Band Imaging Survey for High-Redshift Lyman Alpha Emitters: The Mahoroba-11

We present results of our intermediate-band optical imaging survey for high-$z$ Ly$\alpha$ emitters (LAEs) using the prime focus camera, Suprime-Cam, on the 8.2m Subaru Telescope. In our survey, we use eleven filters; four broad-band filters ($B$, $R_{\rm c}$, $i^\prime$, and $z^\prime$) and seven intermediate-band filters covering from 500 nm to 720 nm; we call this imaging program as the Mahoroba-11. The seven intermediate-band filters are selected from the IA filter series that is the Suprime-Cam intermediate-band filter system whose spectral resolution is $R = 23$. Our survey has been made in a $34^\prime \times 27^\prime$ sky area in the Subaru XMM Newton Deep Survey field. We have found 409 IA-excess objects that provide us a large photometric sample of strong emission-line objects. Applying the photometric redshift method to this sample, we obtained a new sample of 198 LAE candidates at $3 42.67$ between $z \sim 3$ and 5.
Proteoglycans Determine the Dynamic Landscape of EMT and Cancer Cell Stemness

Simple Summary Proteoglycans are important structural and functional components of extracellular matrices that govern phenotype and functions of resident cells. They are often deregulated in cancer cells and their stroma, providing a favorable microenvironment for cancer cell growth and spread. Proteoglycans, by influencing cell–cell and cell–matrix interactions and oncogenic signaling, affect cancer cell phenotype and properties. In this article, we discussed the implication of proteoglycans with cancer cell stemness and epithelial-to-mesenchymal transition. Abstract Proteoglycans (PGs) are pivotal components of extracellular matrices, involved in a variety of processes such as migration, invasion, morphogenesis, differentiation, drug resistance, and epithelial-to-mesenchymal transition (EMT). Cellular plasticity is a crucial intermediate phenotypic state acquired by cancer cells, which can modulate EMT and the generation of cancer stem cells (CSCs). PGs affect cell plasticity, stemness, and EMT, altering the cellular shape and functions. PGs control these functions, either by direct activation of signaling cascades, acting as co-receptors, or through regulation of the availability of biological compounds such as growth factors and cytokines. Differential expression of microRNAs is also associated with the expression of PGs and their interplay is implicated in the fine tuning of cancer cell phenotype and potential. This review summarizes the involvement of PGs in the regulation of EMT and stemness of cancer cells and highlights the molecular mechanisms.
A Hierarchical Spatial–Temporal Cross-Attention Scheme for Video Summarization Using Contrastive Learning

Video summarization (VS) is a widely used technique for facilitating the effective reading, fast comprehension, and effective retrieval of video content. Certain properties of the new video data, such as a lack of prominent emphasis and a fuzzy theme development border, disturb the original thinking mode based on video feature information. Moreover, it introduces new challenges to the extraction of video depth and breadth features. In addition, the diversity of user requirements creates additional complications for more accurate keyframe screening issues. To overcome these challenges, this paper proposes a hierarchical spatial–temporal cross-attention scheme for video summarization based on comparative learning. Graph attention networks (GAT) and the multi-head convolutional attention cell are used to extract local and depth features, while the GAT-adjusted bidirection ConvLSTM (DB-ConvLSTM) is used to extract global and breadth features. Furthermore, a spatial–temporal cross-attention-based ConvLSTM is developed for merging hierarchical characteristics and achieving more accurate screening in similar keyframes clusters. Verification experiments and comparative analysis demonstrate that our method outperforms state-of-the-art methods.