Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Variance Reduction with Optimal Communication

We consider the problem of distributed variance reduction: $n$ machines each receive probabilistic estimates of an unknown true vector $\Delta$, and must cooperate to find a common estimate of $\Delta$ with lower variance, while minimizing communication. Variance reduction is closely related to the well-studied problem of distributed mean estimation, and is a key procedure in instances of distributed optimization, such as data-parallel stochastic gradient descent. Previous work typically assumes an upper bound on the norm of the input vectors, and achieves an output variance bound in terms of this norm. However, in real applications, the input vectors can be concentrated around the true vector $\Delta$, but $\Delta$ itself may have large norm. In this case, output variance bounds in terms of input norm perform poorly, and may even increase variance. In this paper, we show that output variance need not depend on input norm. We provide a method of quantization which allows variance reduction to be performed with solution quality dependent only on input variance, not on input norm, and show an analogous result for mean estimation. This method is effective over a wide range of communication regimes, from sublinear to superlinear in the dimension. We also provide lower bounds showing that in many cases the communication to output variance trade-off is asymptotically optimal. Further, we show experimentally that our method yields improvements for common optimization tasks, when compared to prior approaches to distributed mean estimation.
Nutritional interactions between the alga Symbiodinium and sea anemone Aiptasia pulchella

Many marine cnidarians obtain photosynthetic carbon compounds from symbiotic algae of the genus Sy in b io diniu in. This study explores the mechanism by which the algae are induced to release photosynthetic products, and the impact of translocated photosynthate on nitrogen metabolism in the animal: ammonium assimilation and essential amino acid biosynthesis. Taurine and animal extract exhibited broadly comparable effects on photosynthate metabolism and photosynthate translocation by Syinbiodiniuin derived from the sea anemone Aiptasia pulchella. Taurine-stimulated photosynthate release is inferred to be the signalling process from the evidence that (1) the km of taurine-stimulated photosynthate release is low (21 pM); (2) taurine is not intensively metabolized by Syinbiodinium; and (3) part of taurine uptake by Syinbiodiniu? n is reversible. Kinetics and inhibitor studies further revealed that the putative Sy? nbiodiniuin receptor for taurine-stimulated photosynthate release is distinct from the taurine transporter. The translocated photosynthate has a considerable impact on the nitrogen metabolism in the animal host. The ammonium concentration in the animal tissues of A. pulchella was elevated by incubation in darkness or , depletion of Symbiodinium, and the effect was partially or completely reversed by supplementing the medium with organic carbon (e. g. fumarate, (x-ketoglutarate). The effect of these treatments on the ammonium concentration was inversely correlated with their impact on
Seroprevalence of Toxoplasma gondii Antibodies in Dairy Cows in Kerman Province, South East Iran

Toxoplasma gondii is a ubiquitous protozoan that causes the most common parasitic infection in humans. Since the disease is of economic importance with regard to animal productions, it is necessary to investigate the prevalence of T. gondii infection in meat producing animals especially cattle which constitutes the main source of meat for local consumption. The aim of this study was to investigate the seroprevalence of toxoplasmosis in dairy cows of Kerman region (southeastern Iran) using Modified Agglutination Test (MAT). The sera of 300 dairy cows have been investigated for antibodies against Toxoplasma gondii. The results indicated two hundred and fourteen samples (71.3%) were seropositive and 86 samples (28.7%) were seronegative. Out of the 300 cattle (39 male, 261 female) screened, 87% of male and 13% of female cattle were contaminated with toxoplasmosis. Since cows are one of the most important meat sources in Iran, there is a high risk of contamination through meat from this host due to their susceptibility to infection. Further studies are required for more data on the prevalence of T. gondii in other meat producing animals to apply effective control strategies against toxoplasmosis.
Joint galaxy–galaxy lensing and clustering constraints on galaxy formation

We compare predictions for galaxy-galaxy lensing profiles and clustering from the Henriques et al. (2015) public version of the Munich semi-analytical model of galaxy formation (SAM) and the IllustrisTNG suite, primarily TNG300, with observations from KiDS+GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast > 10^{11}\,M_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode AGN accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. (2017). Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only ($\chi^2 = 1.81$ compared to $\chi^2 = 7.79$ for the SAM), and locally brightest galaxies samples ($\chi^2 = 3.80$ compared to $\chi^2 = 5.01$). With added dust corrections to the colours it matches the SDSS clustering signal well for red low mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\,\%$ excessive lensing signals for intermediate mass red galaxies with $10.2 < \log_{10} M_\ast [ M_\odot ] < 11.2$ at $r \approx 0.6\,h^{-1}\,\mathrm{Mpc}$, which require further theoretical development.
Dark Sirens to Resolve the Hubble–Lemaître Tension

The planned sensitivity upgrades to the LIGO and Virgo facilities could uniquely identify host galaxies of dark sirens—compact binary coalescences without any electromagnetic counterparts—within a redshift of z = 0.1. This is aided by the higher-order spherical harmonic modes present in the gravitational-wave signal, which also improve distance estimation. In conjunction, sensitivity upgrades and higher modes will facilitate an accurate, independent measurement of the host galaxy’s redshift in addition to the luminosity distance from the gravitational-wave observation to infer the Hubble–Lemaître constant H0 to better than a few percent in 5 yr. A possible Voyager upgrade or third-generation facilities would further solidify the role of dark sirens for precision cosmology in the future.
Palaeoecology and Development of Peatlands in Indiana

Abstract The progressive development of ten Holocene peatlands in northeast Indiana was determined by analysis of macroscopic subfossils recovered from sediment cores. All of the peatlands began as extremely mineral-rich lakes or ponds after retreat of Wisconsin-age glacial ice. The oldest basal date was 13,170 radiocarbon 14C y BP. The subfossil assemblage characterizing the lake stages included Chara sp. , Ceratophyllum demersum, Najas flexilis and Potamogeton spp. The transition from lake to peatland was marked by a marsh flora dominated by Nuphar sp. Nymphaea sp. , and, especially, Brasenia schreberi. Evidence for the development of a fen began early in the hydrosere (in the limnic phase) and colonization of the open water by a floating fen mat brought closure to the emergent marsh. Calcicolous mosses of the family Amblystegiaceae, including Calliergon stramineum, Calliergon trifarium, Campylium polygamum, Drepanocladus aduncus and Scorpidium scorpioides, dominated the fens. During the later stages of the fen phase an association of Calliergon trifarium and Meesia triquetra dominated the subfossil assemblage. Depending on the morphometry and geology of the respective basins, some of the fens became Sphagnum-dominated bogs. Subfossil assemblages of the bog phase included remains of ericaceous shrubs as well as sedges. Regardless of their developmental pathways, all of the peatlands exhibit an apparent trend towards senescence into lowland forests dominated by Acer rubrum.
Molecular markers for species discrimination in poriferans: a case study on species of the genus Aplysina

We tested different molecular markers for their utility as species discriminators in Porifera: internal transcribed spacer-1 and -2 (ITS-1, ITS-2) rDNA, mitochondrial 12S, 16S, and cytochrome oxidase subunit I (COI). The study was performed on specimens of the genus Aplysina from different locations in the Mediterranean Sea, East, and West Atlantic. This genus is widespread in tropical and subtropical waters and rich in natural substances. From the Mediterranean Sea, two different species are known: A. aerophoba (Schmidt, 1862) and A. cavernicola (Vacelet, 1959). We intended to find an adequate molecular marker to differentiate the Mediterranean species A. aerophoba and A. cavernicola. However, there was a high degree of intra-individual polymorphism within the markers ITS-1 and ITS-2. Consequently, these markers were not adequate for species differentiation of A. aerophoba and A. cavernicola for technical reasons discussed here. In contrast, the mitochondrial 12S and 16S are highly conserved and no differences among species were observed. Only the COI showed a low variability in the seven analysed Aplysina species. Based on COI, it was possible to classify the specimens COI in two clades. One clade is represented by A. aerophoba and A. cavernicola which could be distinguished from the Caribbean Aplysina species. However, the resolution was low in the second clade consisting of Western Atlantic Aplysina species, suggesting a recent radiation event. Our results suggest that a general molecular markers for species discrimination does not exist. Hence, the choice of a suitable marker strongly depends on the evolutionary context of each single taxon and will have to be tested accordingly.
Diversity of Rhizobium Bacteria Isolated from the Root Nodules of Leguminous Trees

Sixty rhizobial strains isolated from the root nodules of Acacia senegal and Prosopis chilensis in the Sudan were compared with 37 rhizobia isolated from woody legumes in other regions and with 25 representatives of recognized Rhizobium species by performing a numerical analysis of 115 phenotypic characteristics. Nineteen clusters were formed below the boundary level of 0.725 average distance, which was the level that separated the reference Rhizobium and Bradyrhizobium species. Our results indicated that tree rhizobia are very diverse with respect to their cross-nodulation patterns, as well as their physiological and biochemical properties, since 12 of the clusters formed consisted of tree rhizobia alone. Two distinctive features of tree rhizobia isolated in the Sudan were their high maximum growth temperature and their high salt tolerance.
The Effect of Bars on the Ionized ISM: Optical Emission Lines from Milky Way Analogs

Gas interior to the bar of the Milky Way has recently been shown to be the closest example of a low-ionization (nuclear) emission region (LI(N)ER) in the universe. To better understand the nature of this gas, a sample of face-on galaxies with integral field spectroscopy is used to study the ionized gas conditions of 240 barred and 250 nonbarred galaxies, focusing on those that are most similar to the Milky Way. Strong optical line emission of [N ii] λ6584, Hα, [O iii] λ5007, and Hβ are used to diagnose the dominant ionization mechanisms of gas across galaxies and the Galaxy via Baldwin–Phillips–Terlevich diagrams. Barred galaxies show a strong suppression of star formation and an increase in composite and LI(N)ER-like spectra in their inner regions when compared with similar nonbarred counterparts. This effect is lessened in galaxies of very low ( ) or very high ( ) total stellar mass. Bar masks from Galaxy Zoo:3D show the bar’s nonaxisymmetric effect on the ionized gas and help predict the face-on distribution of ionized gas conditions near the bar of the Milky Way.
Implementation of stellar heating feedback in simulations of star cluster formation: effects on the initial mass function

Explaining the initial mass function (IMF) of stars is a long-standing problem in astrophysics. The number of complex mechanisms involved in the process of star cluster formation, such as turbulence, magnetic fields and stellar feedback, make understanding and modeling the IMF a challenging task. In this paper, we aim to assert the importance of stellar heating feedback in the star cluster formation process and its effect on the shape of the IMF. We use an analytical sub-grid model to implement the radiative feedback in fully three-dimensional magnetohydrodynamical (MHD) simulations of star cluster formation, with the ultimate objective of obtaining numerical convergence on the IMF. We compare a set of MHD adaptive-mesh-refinement (AMR) simulations with three different implementations of the heating of the gas: 1) a polytropic equation of state (EOS), 2) a spherically symmetric stellar heating feedback, and 3) our newly developed polar heating model that takes into account the geometry of the accretion disc and the resulting shielding of stellar radiation by dust. For each of the three heating models, we analyse the distribution of stellar masses formed in ten molecular cloud simulations with different realizations of the turbulence to obtain a statistically representative IMF. We conclude that stellar heating feedback has a profound influence on the number of stars formed and plays a crucial role in controlling the IMF. We find that the simulations with the polar heating model achieve the best convergence on the observed IMF.
Radiative-transfer modeling of nebular-phase type II supernovae

Nebular phase spectra of core-collapse supernovae (SNe) provide critical and unique information on the progenitor massive star and its explosion. We present a set of one-dimensional steady-state non-local thermodynamic equilibrium radiative transfer calculations of type II SNe at 300 d after explosion. Guided by the results obtained from a large set of stellar evolution simulations, we craft ejecta models for type II SNe from the explosion of a 12, 15, 20, and 25 M⊙ star. The ejecta density structure and kinetic energy, the 56Ni mass, and the level of chemical mixing are parametrized. Our model spectra are sensitive to the adopted line Doppler width, a phenomenon we associate with the overlap of Fe II and O I lines with Ly α and Ly β. Our spectra show a strong sensitivity to 56Ni mixing since it determines where decay power is absorbed. Even at 300 d after explosion, the H-rich layers reprocess the radiation from the inner metal rich layers. In a given progenitor model, variations in 56Ni mass and distribution impact the ejecta ionization, which can modulate the strength of all lines. Such ionization shifts can quench Ca II line emission. In our set of models, the [O I] λλ 6300, 6364 doublet strength is the most robust signature of progenitor mass. However, we emphasize that convective shell merging in the progenitor massive star interior can pollute the O-rich shell with Ca, which would weaken the O I doublet flux in the resulting nebular SN II spectrum. This process may occur in nature, with a greater occurrence in higher mass progenitors, and this may explain in part the preponderance of progenitor masses below 17 M⊙ that are inferred from nebular spectra.
Learning Color Compatibility in Fashion Outfits

Color compatibility is important for evaluating the compatibility of a fashion outfit, yet it was neglected in previous studies. We bring this important problem to researchers' attention and present a compatibility learning framework as solution to various fashion tasks. The framework consists of a novel way to model outfit compatibility and an innovative learning scheme. Specifically, we model the outfits as graphs and propose a novel graph construction to better utilize the power of graph neural networks. Then we utilize both ground-truth labels and pseudo labels to train the compatibility model in a weakly-supervised manner.Extensive experimental results verify the importance of color compatibility alone with the effectiveness of our framework. With color information alone, our model's performance is already comparable to previous methods that use deep image features. Our full model combining the aforementioned contributions set the new state-of-the-art in fashion compatibility prediction.
Current-Induced Magnetization Switching of Exchange-Biased 
NiO
 Heterostructures Characterized by Spin-Orbit Torque

In this work, we study magnetization switching induced by spin-orbit torque in heterostructures with variable thickness of heavy-metal layers W and Pt, perpendicularly magnetized Co layer and an antiferromagnetic NiO layer. Using current-driven switching, magnetoresistance and anomalous Hall effect measurements, perpendicular and in-plane exchange bias field were determined. Several Hall-bar devices possessing in-plane exchange bias from both systems were selected and analyzed in relation to our analytical switching model of critical current density as a function of Pt and W thickness, resulting in estimation of effective spin Hall angle and effective perpendicular magnetic anisotropy. Approximately one order of magnitude smaller critical switching current densities in W- than Pt-based Hall-bar devices were found due to a higher effective spin Hall angle in W structures. The current switching stability and training process are discussed in detail.
Role of time scale in the spreading of asymmetrically interacting diseases

Diseases and other contagion phenomena in nature and society can interact asymmetrically, such that one can benefit from the other, which in turn impairs the first, in analogy with predator-prey systems. Here, we consider two models for interacting disease-like dynamics with asymmetric interactions and different associated time scales. Using rate equations for homogeneously mixed populations, we show that the stationary prevalences and phase diagrams of each model behave differently with respect to variations of the relative time scales. We also characterize in detail the regime where transient oscillations are observed, a pattern that is inherent to asymmetrical interactions but often ignored in the literature. Our results contribute to a better understanding of disease dynamics in particular, and interacting processes in general, and could provide interesting insights for real-world applications, most notably, the interplay between the dynamics of fact-checked and fake news.
Particle identification at MeV energies in JUNO

JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primarily aiming to determine the neutrino mass ordering. Moreover, its 20 kt target mass makes it an ideal detector to study neutrinos from various sources, including nuclear reactors, the Earth and its atmosphere, the Sun, and even supernovae. Due to the small cross section of neutrino interactions, the event rate of neutrino experiments is limited. In order to maximize the signal-to-noise ratio, it is extremely important to control the background levels. In this paper we discuss the potential of particle identification in JUNO, its underlying principles and possible areas of application in the experiment. While the presented concepts can be transferred to any large liquid scintillator detector, our methods are evaluated specifically for JUNO and the results are mainly driven by its high optical photon yield of 1,200 photo electrons per MeV of deposited energy. In order to investigate the potential of event discrimination, several event pairings are analysed, i.e. α/β, p/β, e+/e−, and e−/γ. We compare the discrimination performance of advanced analytical techniques based on neural networks and on the topological event reconstruction keeping the standard Gatti filter as a reference. We use the Monte Carlo samples generated in the physically motivated energy intervals. We study the dependence of our cuts on energy, radial position, PMT time resolution, and dark noise. The results show an excellent performance for α/β and p/β with the Gatti method and the neural network. Furthermore, e+/e− and e−/γ can partly be distinguished by means of neural network and topological reconstruction on a statistical basis. Especially in the latter case, the topological method proved very successful.
Submillimetre galaxies in cosmological hydrodynamical simulations – an opportunity for constraining feedback models

Submillimetre galaxies (SMGs) have long posed a challenge for theorists, and self-consistently reproducing the properties of the SMG population in a large-volume cosmological hydrodynamical simulation has not yet been achieved. In this work, we employ a relatively simple method based on previous work to predict the submm flux densities of simulated SMGs drawn from cosmological simulations from the Illustris and IllustrisTNG projects and compare the predicted number counts with observations. We find that the predicted SMG number counts based on IllustrisTNG are significantly less than observed (more than 1 dex at $S_{850} \gtrsim 4$ mJy). The simulation from the original Illustris project yields more SMGs than IllustrisTNG: the predicted counts are consistent with those observed at both $S_{850} \lesssim 5$ mJy and $S_{850} \gtrsim 9$ mJy and only a factor of $\sim 2$ lower than observed at intermediate flux densities. We demonstrate that IllustrisTNG hosts fewer SMGs than Illustris because in the former, high-mass ($M_{\star} \sim 10^{11} \, {\rm M}_{\odot}$) $z \sim 2-3$ galaxies have lower dust masses and star formation rates (SFRs) than in Illustris owing to differences in the sub-grid models for stellar or/and active galactic nucleus (AGN) feedback between the two simulations (we unfortunately cannot isolate the specific cause(s) post hoc). Our results demonstrate that because our method enables predicting SMG number counts in post-processing with a negligible computational expense, SMGs can provide useful constraints for tuning sub-grid models in future large-volume cosmological simulations. Higher resolution, which would lead to stronger SFR enhancements in starbursts, could at least partially reconcile the discrepancy between the IllustrisTNG SMG number counts and those observed.
TLIO: Tight Learned Inertial Odometry

In this letter we propose a tightly-coupled Extended Kalman Filter framework for IMU-only state estimation. Strap-down IMU measurements provide relative state estimates based on IMU kinematic motion model. However the integration of measurements is sensitive to sensor bias and noise, causing significant drift within seconds. Recent research by Yan et al. (RoNIN) and Chen et al. (IONet) showed the capability of using trained neural networks to obtain accurate 2D displacement estimates from segments of IMU data and obtained good position estimates from concatenating them. This letter demonstrates a network that regresses 3D displacement estimates and its uncertainty, giving us the ability to tightly fuse the relative state measurement into a stochastic cloning EKF to solve for pose, velocity and sensor biases. We show that our network, trained with pedestrian data from a headset, can produce statistically consistent measurement and uncertainty to be used as the update step in the filter, and the tightly-coupled system outperforms velocity integration approaches in position estimates, and AHRS attitude filter in orientation estimates. Video materials and code can be found on our project page: http://cathias.github. io/TLIO/.