Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal galaxy distance estimators

The statistical properties of galaxy distance estimators are studied and a rigorous framework is developed for identifying and removing the effects of Malmquist bias due to obsevational selection. The prescription of Schechter (1980) for defining unbiased distance estimators is extended to more general -- and more realistic -- cases. The derivation of `optimal' unbiased distance estimators of minimum dispersion, by utilising information from additional -- suitably correlated -- observables, is discussed and the results applied to a calibrating sample from the Fornax cluster, as used in the Mathewson spiral galaxy redshift survey. The optimal distance estimator derived from I-band magnitude, diameter and 21cm line width has an intrinsic scatter which is 25 \% smaller than that of the Tully-Fisher relation quoted for this calibrating sample. (Figures are available on request).
Spectral signatures of fractionalization in the frustrated Heisenberg model on the square lattice

We employ a variational Monte Carlo approach to efficiently obtain the dynamical structure factor for the spin-1/2 $J_1-J_2$ Heisenberg model on the square lattice. Upon increasing the frustrating ratio $J_2/J_1$, the ground state undergoes a continuous transition from a N\'eel antiferromagnet to a $\mathbb{Z}_{2}$ gapless spin liquid. We identify the characteristic spectral features in both phases and highlight the existence of a broad continuum of excitations in the proximity of the spin-liquid phase. The magnon branch, which dominates the spectrum of the unfrustrated Heisenberg model, gradually loses its spectral weight, thus releasing nearly-deconfined spinons, whose signatures are visible even in the magnetically ordered state. Our results show how free spinons emerge across a quantum critical point, providing evidence for the fractionalization of magnons into deconfined spinons.
The Relationship Between Volunteering and the Occurrence of Loneliness Among Older Adults: A Longitudinal Study with 12 Years of Follow-Up

ABSTRACT Informed by the social model of health promotion, this study examined the association between formal volunteering and the occurrence of loneliness among older adults over 12 years of follow-up and whether the association differs by gender. Data came from the Health and Retirement Study (2006–2018). The study sample included 5,000 individuals aged 60 and over who did not experience loneliness in 2006. Self-reported participation in formal volunteer work was classified into three levels: (0) no volunteering, (1) less than 100 hours of volunteering per year, and (2) more than 100 hours of volunteering per year. Cox regression was used to examine the relationship between volunteering level and the onset of loneliness during the 12 years of follow-up. Volunteering more than 100 hours per year was associated with a lower risk of loneliness compared to non-volunteers (HR = 0.55, p = .008). This protective effect was not observed for those who volunteered less than 100 hours per year (HR = 0.84, p = .246). The benefits of volunteering in mitigating loneliness did not differ by gender. Engagement in moderate to high levels of volunteering can protect against loneliness. More volunteering programs can be offered to older adults to reduce loneliness in later life.
2 Preliminaries and Notation 2 . 1 Constraint Satisfaction Problems

Linear Programming is one of the most important tools for finding approximate solutions to NP hard problems. Thus, many works have attempted to show lower bounds on linear programs i.e. how well can some problem be approximated by a polynomial sized linear program. The authors in [1] started a systematic study of linear programs and in particular showed integrality gaps for vertex cover for Lovasz Shreiver and Sherali Adams hierarchy. Now, there has been a lot of work in this area on proving integrality gaps for these LP/SDP hierarchies with a certain number of rounds for various problems. This rules out a large class of linear programs which cannot be used to approximate a problem within a certain factor however, still there is a gap since this does not rule out some other polynomial sized LPs. In this paper, the authors try to minimize this gap and try to show lower bounds for “natural” polynomial sized LPs for approximating constraint satisfaction problems.
Atomistic measurement and modeling of intrinsic fracture toughness of two-dimensional materials

Significance The promise of computational material design is based on atomistic models with predictive capabilities. While quantum chemistry simulations can be used during unit cell property screening of two-dimensional (2D) materials, device-level analysis requires large-scale atomistic simulations employing interatomic potentials. We present advances in experimentation and machine learning–inspired algorithms for accurate interatomic potential selection, parameterization, and validation. Through in-situ high-resolution transmission electron microscopy atomistic measurements, we directly compare atomic structures and material fracture toughness with those predicted by molecular dynamics simulations employing a potential informed by ab initio data in the nonequilibrium regime. The integrated framework provides a robust approach to obtaining intrinsic mechanical properties of 2D materials (in their pristine and defective states) and informs the analysis of device reliability with unprecedented accuracy.
Neutrophils Are Sophisticated Cells Able to Adapt to Changing Inflammation Neutrophils

Neutrophils are the most abundant leukocytes in peripheral blood and respond rapidly to danger, infiltrating tissues within minutes of infectious or sterile injury. Neutrophils were long thought of as simple killers, but now we recognise them as responsive cells able to adapt to inflammation and orchestrate subsequent events with some sophistication. Here, we discuss how these rapid responders release mediators which influence later adaptive T cell immunity through influences on DC priming and directly on the T cells themselves. We consider how the release of granule contents by neutrophils—through NETosis or degranulation—is one way in which the innate immune system directs the phenotype of the adaptive immune response.
Extracellular Vesicles Derived from Human Bone Marrow Stem Cells Inhibit Acute Lymphoblastic Leukemia Cell Growth by Inhibiting MAPK Pathway via the miR-29b-3p/GDF15 Axis

Introduction: Acute lymphoblastic leukemia (ALL) is a common hematologic neoplastic disease. This study discussed the effect of extracellular vesicles (EVs) released from bone marrow mesenchymal stem cells (BMSCs) on ALL cells and the mechanism. Methods: BMSCs-EVs were isolated by differential centrifugation and identified. The effect of BMSCs-EVs on ALL cell proliferation and apoptosis was evaluated. The expression of miR-29b-3p in ALL cells and EVs was detected. The uptake of EVs by ALL cells was observed. The effect of miR-29b-3p on ALL cell proliferation and apoptosis was assessed after silencing miR-29b-3p. The targeting relation of miR-29b-3p and GDF15 was analyzed by bioinformatics website and dual-luciferase assay. The role of GDF15 in proliferation and apoptosis of ALL cells was further confirmed, and Western blot assay was performed to measure MAPK pathway-related protein levels. Results: BMSC-derived EVs inhibited proliferation and promoted apoptosis of ALL cells, as shown by the up-regulation of caspase-3 and Bax expressions and down-regulation of Bcl-2 expression. EVs carried miR-29b-3p into ALL cells, upregulated miR-29b-3p expression in ALL cells, and inhibited GDF15 expression. Silencing of miR-29b-3p or overexpression of GDF15 partially reversed the effect of EVs. EVs inhibited the MAPK pathway through the miR-29b-3p/GDF15 axis. Conclusion: BMSCs-EVs carried miR-29b-3p into ALL cells, upregulated miR-29b-3p, and inhibited GDF15 to suppress the MAPK pathway and further inhibit proliferation and promote apoptosis of ALL cells.
First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases

We describe catalogue-level simulations of Type Ia supernova (SN Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN) and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light-curve analysis and to determine bias corrections for SN Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN Ia model, incorporates information from observations (point spread function, sky noise, zero-point), and uses summary information (e.g. detection efficiency versus signal-to-noise ratio) based on 10 000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05 mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue colour, distance biases can reach 0.4 mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at https://des.ncsa. illinois.edu/releases/sn.
Multiscale finite-difference-diffusion-Monte-Carlo method for simulating dendritic solidification

Abstract We present a novel hybrid computational method to simulate accurately dendritic solidification in the low undercooling limit where the dendrite tip radius is one or more orders of magnitude smaller than the characteristic spatial scale of variation of the surrounding thermal or solutal diffusion field. The first key feature of this method is an efficient multiscale diffusion Monte Carlo (DMC) algorithm which allows off-lattice random walkers to take longer and concomitantly rarer steps with increasing distance away from the solid–liquid interface. As a result, the computational cost of evolving the large-scale diffusion field becomes insignificant when compared to that of calculating the interface evolution. The second key feature is that random walks are only permitted outside of a thin liquid layer surrounding the interface. Inside this layer and in the solid, the diffusion equation is solved using a standard finite difference algorithm that is interfaced with the DMC algorithm using the local conservation law for the diffusing quantity. Here we combine this algorithm with a previously developed phase-field formulation of the interface dynamics and demonstrate that it can accurately simulate three-dimensional dendritic growth in a previously unreachable range of low undercoolings that is of direct experimental relevance.
Direct numerical simulations of Taylor–Couette turbulence: the effects of sand grain roughness

Progress in roughness research, mapping any given roughness geometry to its fluid dynamic behaviour, has been hampered by the lack of accurate and direct measurements of skin-friction drag, especially in open systems. The Taylor–Couette (TC) system has the benefit of being a closed system, but its potential for characterizing irregular, realistic, three-dimensional (3-D) roughness has not been previously considered in depth. Here, we present direct numerical simulations (DNSs) of TC turbulence with sand grain roughness mounted on the inner cylinder. The model proposed by Scotti (Phys. Fluids, vol. 18, 031701, 2006) has been modified to simulate a random rough surface of monodisperse sand grains. Taylor numbers range from $Ta=1.0\times 10^{7}$ (corresponding to $Re_{\unicode[STIX]{x1D70F}}=82$ ) to $Ta=1.0\times 10^{9}$ ( $Re_{\unicode[STIX]{x1D70F}}=635$ ). We focus on the influence of the roughness height $k_{s}^{+}$ in the transitionally rough regime, through simulations of TC with rough surfaces, ranging from $k_{s}^{+}=5$ up to $k_{s}^{+}=92$ . We analyse the global response of the system, expressed both by the dimensionless angular velocity transport $Nu_{\unicode[STIX]{x1D714}}$ and by the friction factor $C_{f}$ . An increase in friction with increasing roughness height is accompanied with enhanced plume ejection from the inner cylinder. Subsequently, we investigate the local response of the fluid flow over the rough surface. The equivalent sand grain roughness $k_{s}^{+}$ is calculated to be $1.33k$ , where $k$ is the size of the sand grains. We find that the downwards shift of the logarithmic layer, due to transitionally rough sand grains exhibits remarkably similar behaviour to that of the Nikuradse (VDI-Forsch., vol. 361, 1933) data of sand grain roughness in pipe flow, regardless of the Taylor number dependent constants of the logarithmic layer. Furthermore, we find that the dynamical effects of the sand grains are contained to the roughness sublayer $h_{r}$ with $h_{r}=2. 78k_{s}$ .
Ring Galaxies Through Off-center Minor Collisions by Tuning Bulge-to-disk Mass Ratio of Progenitors

Collisional ring galaxies (CRGs) are formed through off-center collisions between a target galaxy and an intruder dwarf galaxy. We study the mass distribution and kinematics of CRGs by tuning the bulge-to-disk mass ratio (B/D) for the progenitor; i.e., the target galaxy. We find that the lifetime of the ring correlates with the initial impact velocity vertical to the disk plane (i.e., vz0). Three orbits for the collisional galaxy pair, on which clear and asymmetric rings form after collisions, are selected to perform the N-body simulations at different values of B/D for the progenitor. It is found that the ring structures are the strongest for CRGs with small values of B/D. The Sérsic index, n, of the central remnant in the target galaxy becomes larger after collision. Moreover, the Sérsic index of a central remnant strongly correlates with the initial value of B/D for the progenitor. A bulge-less progenitor results in a late-type object in the center of the ring galaxy, whereas a bulge-dominated progenitor leads to an early-type central remnant. Progenitors with B/D ∈ [0.1, 0.3] (i.e., minor bulges) leave central remnants with n ≈ 4. These results provide a possible explanation for the formation of a recently observed CRG with an early-type central nucleus, SDSS J1634+2049. In addition, we find that the radial and azimuthal velocity profiles for a ring galaxy are more sensitive to the B/D than the initial relative velocity of the progenitor.
Influence of Crystalline Nanoprecipitates on Shear-Band Propagation in Cu-Zr Based Metallic Glasses

The interaction of shear bands with crystalline nanoprecipitates in Cu-Zr-based metallic glasses is investigated by a combination of high-resolution TEM imaging and molecular-dynamics computer simulations. Our results reveal different interaction mechanisms: Shear bands can dissolve precipitates, can wrap around crystalline obstacles, or can be blocked depending on size and density of the precipitates. If the crystalline phase has a low yield strength, we also observe slip transfer through the precipitate. Based on the computational results and experimental findings, a qualitative mechanism map is proposed that categorizes the various processes as a function of the critical stress for dislocation nucleation, precipitate size, and distance.
Prospects for Higgs- and Z-resonant Neutralino Dark Matter

In the minimal supersymmetric standard models, neutralino dark matter with mass of $m_{\chi}\sim m_Z/2\sim 45$ GeV and $m_{\chi}\sim m_h/2\sim 62$ GeV can have the thermal relic abundance $\Omega_{\chi_1}h^2\simeq 0.120$ via the $Z$- and Higgs-resonant annihilations, respectively, while avoiding all the current constraints. Phenomenology of such scenarios is determined only by three parameters, Bino mass $M_1$, Higgsino mass $\mu$, and $\tan\beta$, in the limit that all other supersymmetric particles and heavy Higgs bosons are decoupled. In this paper, we comprehensively study the constraints and future prospects of the search for such Higgs- and $Z$-resonant neutralino dark matter. It is shown that almost all the parameter space of the scenario will be probed complementarily by the LHC search for the chargino and neutralinos, the direct detection experiments, and the Higgs invisible decay search at the ILC.
Reduction in animal abundance and oxygen availability during and after the end‐Triassic mass extinction

The end‐Triassic biodiversity crisis was one of the most severe mass extinctions in the history of animal life. However, the extent to which the loss of taxonomic diversity was coupled with a reduction in organismal abundance remains to be quantified. Further, the temporal relationship between organismal abundance and local marine redox conditions is lacking in carbonate sections. To address these questions, we measured skeletal grain abundance in shallow‐marine limestones by point counting 293 thin sections from four stratigraphic sections across the Triassic/Jurassic boundary in the Lombardy Basin and Apennine Platform of western Tethys. Skeletal abundance decreased abruptly across the Triassic/Jurassic boundary in all stratigraphic sections. The abundance of skeletal organisms remained low throughout the lower‐middle Hettangian strata and began to rebound during the late Hettangian and early Sinemurian. A two‐way ANOVA indicates that sample age (p < .01, η2 = 0.30) explains more of the variation in skeletal abundance than the depositional environment or paleobathymetry (p < .01, η2 = 0.15). Measured I/Ca ratios, a proxy for local shallow‐marine redox conditions, show this same pattern with the lowest I/Ca ratios occurring in the early Hettangian. The close correspondence between oceanic water column oxygen levels and skeletal abundance indicates a connection between redox conditions and benthic organismal abundance across the Triassic/Jurassic boundary. These findings indicate that the end‐Triassic mass extinction reduced not only the biodiversity but also the carrying capacity for skeletal organisms in early Hettangian ecosystems, adding to evidence that mass extinction of species generally leads to mass rarity among survivors.
Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation

Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and medical imaging. However, only a few studies on how to generate acoustic holograms have been conducted, and even conventional acoustic hologram algorithms show limited performance in the fast and accurate generation of acoustic holograms, thus hindering the development of novel applications. We here propose a deep learning-based framework to achieve fast and accurate acoustic hologram generation. The framework has an autoencoder-like architecture; thus, the unsupervised training is realized without any ground truth. For the framework, we demonstrate a newly developed hologram generator network, the holographic ultrasound generation network (HU-Net), which is suitable for unsupervised learning of hologram generation, and a novel loss function that is devised for energy-efficient holograms. Furthermore, for considering various hologram devices (i.e., ultrasound transducers), we propose a physical constraint (PC) layer. Simulation and experimental studies were carried out for two different hologram devices, such as a 3-D printed lens, attached to a single element transducer, and a 2-D ultrasound array. The proposed framework was compared with the iterative angular spectrum approach (IASA) and the state-of-the-art (SOTA) iterative optimization method, Diff-PAT. In the simulation study, our framework showed a few hundred times faster generation speed, along with comparable or even better reconstruction quality, than those of IASA and Diff-PAT. In the experimental study, the framework was validated with 3-D printed lenses fabricated based on different methods, and the physical effect of the lenses on the reconstruction quality was discussed. The outcomes of the proposed framework in various cases (i.e., hologram generator networks, loss functions, and hologram devices) suggest that our framework may become a very useful alternative tool for other existing acoustic hologram applications, and it can expand novel medical applications.
Sociodemographic, behavioral, and clinical characteristics associated with perceived discrimination in healthcare settings among Black persons with diagnosed HIV in the United States

ABSTRACT Research that explores the intra-racial socio-demographic and clinical characteristics associated with perceived discrimination in healthcare settings in the US is lacking. We examined the prevalence of self-reported discrimination in HIV care settings during the past 12 months among Black persons from a nationally representative sample of US adults with diagnosed HIV collected 6/2018-5/2019. We assessed the prevalence of self-reported discrimination in HIV care settings during the past 12 months, perceived reasons for discrimination, and factors associated with discrimination among Black persons with diagnosed HIV (n = 1,631). Overall, 22% reported experiencing discrimination in a healthcare setting; discrimination was most often attributed to HIV status. Those reporting discrimination were younger, MSM, and living at or below the federal poverty level. They also experienced homelessness, incarceration and illicit substance use in the past 12 months, and anxiety and depression symptoms in the past 2 weeks. They were less likely to use ART or report 100% ART dose adherence in the past 30 days. No associations were found with viral suppression. Systems are needed to monitor, evaluate reports of, and address discrimination in healthcare settings. Incorporating anti-discrimination policies and continuing education opportunities for providers and staff may reduce experiences of discrimination among persons with HIV.
Numerical renormalization group study of the Anderson-Holstein impurity model

We present numerical renormalization group (NRG) calculations for a single-impurity Anderson model with a linear coupling to a local phonon mode. We calculate dynamical response functions, spectral densities, dynamic charge and spin susceptibilities. Being non-perturbative, the NRG is applicable for all parameter regimes. Our calculations cover both weak and strong electron-phonon coupling for zero and finite electron-electron interaction. We interpret the high- and low-energy features and compare our results to atomic limit calculations and perturbation theory. In certain restricted parameter regimes for strong electron-phonon coupling, a soft phonon mode develops inducing a very narrow resonance at the Fermi level.