Miracle-dz/UniFAR-FTUs huggingface dataset:
Ontogenetic and stratigraphic influence on observed phenotypic integration in the limb skeleton of a fossil tetrapod

Abstract Understanding morphological integration is one of the central goals of evolutionary developmental biology. Despite its applicability to questions of paleontological interest, there are few studies on integration in fossil vertebrates. In this study, we examine limb integration in the Lower Jurassic ichthyosaur Stenopterygius quadriscissus, with the aim of examining the effect of ontogeny and anagenetic changes over short geological time spans on metrics of limb integration. Both ontogenetic and stratigraphic effects had a significant influence on measured values of integration, the identity of strongly integrated elements, and some common ratio values such as the relative integration of the forelimb to the hind limb, or within-limb to between-limb integration. Ontogenetic effects were relatively greater, although this could be linked to sample size. Although adults showed the lowest levels of overall integration, they possessed high levels of integration between serially homologous elements, something that was unexpected due to strong divergence in limb size and perhaps functional differences in derived ichthyosaurs. Ontogenetic differences in the relative integration of the forelimb to the hind limb are probably related to early locomotor demands on the forelimb. We conclude that if samples are pooled, the resulting pattern of integration may not reflect any one subsample but will be a composite created through the superposition of several variables. Pooling data in paleontological studies of integration has a non-trivial effect on the results obtained.
Morphology and ionization characteristics of planetary nebulae PB 1 and PC 19

We present results of our study of two planetary nebulae (PNe), PB1 and PC 19. We use the optical spectra of these two PNe observed at 2 m Himalayan Chandra Telescope and also archival and literature data for the study. We use the morphokinematic code shape to construct 3D morphologies of the PNe and the photoionization code cloudy to model the observed spectra. The 3D model of PB 1 consists of an elongated shell surrounded by a bipolar halo and that of PC 19 consists of an open lobed bipolar structure and a spiral filamentary pair. We analyse the ionization structure of the PNe by deriving several plasma parameters and by photoionization modelling. We estimate the elemental abundances of the elements, He, C, N, O, Ne, S, Ar, and Cl, from our analysis. We find He, C, and N abundances to be significantly higher in case of PB 1. We estimate different physical parameters of the central stars, namely effective temperature, luminosity, and gravity, and of the nebula, namely hydrogen density profiles, radii, etc., from photoionization modelling. We estimate distances to the PNe as ∼4.3 kpc for PB 1 and as ∼5.6 kpc for PC 19 by fitting the photoionization models to absolute observed fluxes. Progenitor masses are estimated from theoretical evolutionary trajectories and are found to be ∼1.67 and ∼2.38 M⊙ for PB 1 and PC 19, respectively.
Ideal Membership Problem for Boolean Minority

The Ideal Membership Problem (IMP) tests if an input polynomial $f\in \mathbb{F}[x_1,\dots,x_n]$ with coefficients from a field $\mathbb{F}$ belongs to a given ideal $I \subseteq \mathbb{F}[x_1,\dots,x_n]$. It is a well-known fundamental problem with many important applications, though notoriously intractable in the general case. In this paper we consider the IMP for polynomial ideals encoding combinatorial problems and where the input polynomial $f$ has degree at most $d=O(1)$ (we call this problem IMP$_d$). A dichotomy result between ``hard'' (NP-hard) and ``easy'' (polynomial time) IMPs was recently achieved for Constraint Satisfaction Problems over finite domains [Bulatov FOCS'17, Zhuk FOCS'17] (this is equivalent to IMP$_0$) and IMP$_d$ for the Boolean domain [Mastrolilli SODA'19], both based on the classification of the IMP through functions called polymorphisms. The complexity of the IMP$_d$ for five polymorphisms has been solved in [Mastrolilli SODA'19] whereas for the ternary minority polymorphism it was incorrectly declared to have been resolved by a previous result. As a matter of fact the complexity of the IMP$_d$ for the ternary minority polymorphism is open. In this paper we provide the missing link by proving that the IMP$_d$ for Boolean combinatorial ideals whose constraints are closed under the minority polymorphism can be solved in polynomial time. This result, along with the results in [Mastrolilli SODA'19], completes the identification of the precise borderline of tractability for the IMP$_d$ for constrained problems over the Boolean domain. This paper is motivated by the pursuit of understanding the issue of bit complexity of Sum-of-Squares proofs raised by O'Donnell [ITCS'17]. Raghavendra and Weitz [ICALP'17] show how the IMP$_d$ tractability for combinatorial ideals implies bounded coefficients in Sum-of-Squares proofs.
K3 carpets on minimal rational surfaces and their smoothings

In this article, we study K3 double structures on minimal rational surfaces $Y$. The results show there are infinitely many non-split abstract K3 double structures on $Y = \mathbb{F}_e$ parametrized by $\mathbb P^1$, countably many of which are projective. For $Y = \mathbb{P}^2$ there exist a unique non-split abstract K3 double structure which is non-projective (see Drezet's article in arXiv:2004.04921). We show that all projective K3 carpets can be smoothed to a smooth K3 surface. One of the byproducts of the proof shows that unless $Y$ is embedded as a variety of minimal degree, there are infinitely many embedded K3 carpet structures on $Y$. Moreover, we show any embedded projective K3 carpet on $\mathbb F_e$ with $e<3$ arises as a flat limit of embeddings degenerating to $2:1$ morphism. The rest do not, but we still prove the smoothing result. We further show that the Hilbert points corresponding to the projective K3 carpets supported on $\mathbb{F}_e$, embedded by a complete linear series are smooth points if and only if $0\leq e\leq 2$. In contrast, Hilbert points corresponding to projective K3 carpets supported on $\mathbb{P}^2$ and embedded by a complete linear series are always smooth. The results in an a recent paper of Bangere-Gallego-Gonzalez show that there are no higher dimensional analogues of the results in this article.
Mixed Logit Models and Network Formation

The study of network formation is pervasive in economics, sociology, and many other fields. In this article, we model network formation as a ‘choice’ that is made by nodes of a network to connect to other nodes. We study these ‘choices’ using discrete-choice models, in which agents choose between two or more discrete alternatives. We employ the ‘repeated-choice’ (RC) model to study network formation. We argue that the RC model overcomes important limitations of the multinomial logit (MNL) model, which gives one framework for studying network formation, and that it is well-suited to study network formation. We also illustrate how to use the RC model to accurately study network formation using both synthetic and real-world networks. Using edge-independent synthetic networks, we also compare the performance of the MNL model and the RC model. We find that the RC model estimates the data-generation process of our synthetic networks more accurately than the MNL model. Using a patent citation network, which forms sequentially, we present a case study of a qualitatively interesting scenario—the fact that new patents are more likely to cite older, more cited, and similar patents—for which employing the RC model yields interesting insights.
Inference in Difference-in-Differences with Few Treated Units and Spatial Correlation

We consider the problem of inference in Difference-in-Differences (DID) when there are few treated units and errors are spatially correlated. We first show that, when there is a single treated unit, some existing inference methods designed for settings with few treated and many control units remain asymptotically valid when errors are weakly dependent. However, these methods may be invalid with more than one treated unit. We propose alternatives that are asymptotically valid in this setting, even when the relevant distance metric across units is unavailable.
Beamspace Channel Estimation in Terahertz Communications: A Model-Driven Unsupervised Learning Approach

Terahertz (THz)-band communications have been one of the promising technologies for future wireless networks that integrate a wide range of data-demanding applications. To compensate for the large channel attenuation in THz band and avoid high hardware cost, a lens-based beamspace massive multiple-input multiple-output (MIMO) system is considered. However, the beam squint effect appeared in wideband THz systems, making channel estimation very challenging, especially when the receiver is equipped with a limited number of radio-frequency (RF) chains. Furthermore, the real channel data cannot be obtained before the THz system is used in a new environment, which makes it impossible to train a deep learning (DL)-based channel estimator using real data set beforehand. To solve the problem, we propose a model-driven unsupervised learning network, named learned denoising-based generalized expectation consistent (LDGEC) signal recovery network. By utilizing the Steins unbiased risk estimator loss, the LDGEC network can be trained only with limited measurements corresponding to the pilot symbols, instead of the real channel data. Even if designed for unsupervised learning, the LDGEC network can be supervisingly trained with the real channel via the denoiser-by-denoiser way. The numerical results demonstrate that the LDGEC-based channel estimator significantly outperforms state-of-the-art compressive sensing-based algorithms when the receiver is equipped with a small number of RF chains and low-resolution ADCs.
Measurements of the Time-Dependent Cosmic-Ray Sun Shadow with Seven Years of IceCube Data -- Comparison with the Solar Cycle and Magnetic Field Models

Observations of the time-dependent cosmic-ray Sun shadow have been proven as a valuable diagnostic for the assessment of solar magnetic field models. In this paper, seven years of IceCube data are compared to solar activity and solar magnetic field models. A quantitative comparison of solar magnetic field models with IceCube data on the event rate level is performed for the first time. Additionally, a first energy-dependent analysis is presented and compared to recent predictions. We use seven years of IceCube data for the Moon and the Sun and compare them to simulations on data rate level. The simulations are performed for the geometrical shadow hypothesis for the Moon and the Sun and for a cosmic-ray propagation model governed by the solar magnetic field for the case of the Sun. We find that a linearly decreasing relationship between Sun shadow strength and solar activity is preferred over a constant relationship at the 6.4sigma level. We test two commonly used models of the coronal magnetic field, both combined with a Parker spiral, by modeling cosmic-ray propagation in the solar magnetic field. Both models predict a weakening of the shadow in times of high solar activity as it is also visible in the data. We find tensions with the data on the order of $3\sigma$ for both models, assuming only statistical uncertainties. The magnetic field model CSSS fits the data slightly better than the PFSS model. This is generally consistent with what is found previously by the Tibet AS-gamma Experiment, a deviation of the data from the two models is, however, not significant at this point. Regarding the energy dependence of the Sun shadow, we find indications that the shadowing effect increases with energy during times of high solar activity, in agreement with theoretical predictions.
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport

We study Sinkhorn EM (sEM), a variant of the expectation maximization (EM) algorithm for mixtures based on entropic optimal transport. sEM differs from the classic EM algorithm in the way responsibilities are computed during the expectation step: rather than assign data points to clusters independently, sEM uses optimal transport to compute responsibilities by incorporating prior information about mixing weights. Like EM, sEM has a natural interpretation as a coordinate ascent procedure, which iteratively constructs and optimizes a lower bound on the log-likelihood. However, we show theoretically and empirically that sEM has better behavior than EM: it possesses better global convergence guarantees and is less prone to getting stuck in bad local optima. We complement these findings with experiments on simulated data as well as in an inference task involving C. elegans neurons and show that sEM learns cell labels significantly better than other approaches.
First Results from SMAUG: Insights into Star Formation Conditions from Spatially Resolved ISM Properties in TNG50

Physical and chemical properties of the interstellar medium (ISM) at subgalactic (∼kiloparsec) scales play an indispensable role in controlling the ability of gas to form stars. In this paper, we use the TNG50 cosmological simulation to explore the physical parameter space of eight resolved ISM properties in star-forming regions to constrain the areas of this hyperspace where most star-forming environments exist. We deconstruct our simulated galaxies spanning a wide range of mass (M ⋆ = 107–1011 M ⊙) and redshift (0 ≤ z ≤ 3) into kiloparsec-sized regions and statistically analyze the gas/stellar surface densities, gas metallicity, vertical stellar velocity dispersion, epicyclic frequency, and dark-matter volumetric density representative of each region in the context of their star formation activity and environment (radial galactocentric location). By examining the star formation rate (SFR) weighted distributions of these properties, we show that stars primarily form in two distinct environmental regimes, which are brought about by an underlying bicomponent radial SFR profile in galaxies. We examine how the relative prominence of these regimes depends on galaxy mass and cosmic time. We also compare our findings with those from integral field spectroscopy observations and find similarities as well as departures. Further, using dimensionality reduction, we characterize the aforementioned hyperspace to reveal a high degree of multicollinearity in relationships among ISM properties that drive the distribution of star formation at kiloparsec scales. Based on this, we show that a reduced 3D representation underpinned by a multivariate radius relationship is sufficient to capture most of the variance in the original 8D space.
Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion

Knowledge graph completion is an important task that aims to predict the missing relational link between entities. Knowledge graph embedding methods perform this task by representing entities and relations as embedding vectors and modeling their interactions to compute the matching score of each triple. Previous work has usually treated each embedding as a whole and has modeled the interactions between these whole embeddings, potentially making the model excessively expensive or requiring specially designed interaction mechanisms. In this work, we propose the multi-partition embedding interaction (MEI) model with block term format to systematically address this problem. MEI divides each embedding into a multi-partition vector to efficiently restrict the interactions. Each local interaction is modeled with the Tucker tensor format and the full interaction is modeled with the block term tensor format, enabling MEI to control the trade-off between expressiveness and computational cost, learn the interaction mechanisms from data automatically, and achieve state-of-the-art performance on the link prediction task. In addition, we theoretically study the parameter efficiency problem and derive a simple empirically verified criterion for optimal parameter trade-off. We also apply the framework of MEI to provide a new generalized explanation for several specially designed interaction mechanisms in previous models.
EXPERIMENTAL STUDIES ON THE DISTRIBUTION OF THE SEXES OF MERCURIALIS PERENNIS L.

1) In a beechwood, male shoots of Mercurialis perennis were more frequent than female shoots in canopy openings, while females were more frequent at treebases than in canopy openings. 2) Flowering shoots were more frequent than non-flowering in openings. 3) The pH, moisture and organic content of the soil were similar at treebases and openings. The light climate was similar in both habitats in April but greater in the openings in August. 4) Removal of canopies of Pteridium aquilinum and Rubus fruticosus, above populations of M. perennis, resulted in a greater increase in the numbers of male shoots than of female shoots. 5) These results suggest that male and female plants differ in numbers, or growth, in different woodland microhabitats and that these differences are correlated with the above-ground environment (e.g. light).
Molecular and functional comparison of 1,25‐dihydroxyvitamin D3 and the novel vitamin D receptor ligand, lithocholic acid, in activating transcription of cytochrome P450 3A4

The vitamin D receptor (VDR) binds to and mediates the effects of the 1,25‐dihydroxyvitamin D3 (1,25(OH)2D3) hormone to alter gene transcription. A newly recognized VDR ligand is the carcinogenic bile acid, lithocholic acid (LCA). We demonstrate that, in HT‐29 colon cancer cells, both LCA and 1,25(OH)2D3 induce expression of cytochrome P450 3A4 (CYP3A4), an enzyme involved in cellular detoxification. We also show that LCA‐VDR stimulates transcription of gene reporter constructs containing DR3 and ER6 vitamin D responsive elements (VDREs) from the human CYP3A4 gene. Utilizing gel mobility shift, pulldown, and mammalian two‐hybrid assays, we observe that: (i) 1,25(OH)2D3 enhances retinoid X receptor (RXR) heterodimerization with VDR more effectively than LCA, (ii) the 1,25(OH)2D3‐liganded VDR‐RXR heterodimer recruits full‐length SRC‐1 coactivator, whereas this interaction is minimal with LCA unless LXXLL‐containing fragments of SRC‐1 are employed, and (iii) both 1,25(OH)2D3 and LCA enhance the binding of VDR to DRIP205/mediator, but unlike 1,25(OH)2D3‐VDR, LCA‐VDR does not interact detectably with NCoA‐62 or TRIP1/SUG1, suggesting a different pattern of LCA‐VDR comodulator association. Finally, residues in the human VDR (hVDR) ligand binding domain (LBD) were altered to create mutants unresponsive to 1,25(OH)2D3‐ and/or LCA‐stimulated transactivation, identifying S237 and S225/S278 as critical for 1,25(OH)2D3 and LCA action, respectively. Therefore, these two VDR ligands contact distinct residues in the binding pocket, perhaps generating unique receptor conformations that determine the degree of RXR and comodulator binding. We propose that VDR is a bifunctional regulator, with the 1,25(OH)2D3‐liganded conformation facilitating high affinity endocrine actions, and the LCA‐liganded configuration mediating local, lower affinity cellular detoxification by upregulation of CYP3A4 in the colon. J. Cell. Biochem. 94: 917–943, 2005. © 2004 Wiley‐Liss, Inc.
First Results from SMAUG: Uncovering the Origin of the Multiphase Circumgalactic Medium with a Comparative Analysis of Idealized and Cosmological Simulations

We examine the properties of the circumgalactic medium (CGM) at low redshift in a range of simulated Milky Way mass halos. The sample is comprised of seven idealized simulations, an adaptive mesh refinement cosmological zoom-in simulation, and two groups of 50 halos with star-forming or quiescent galaxies taken from the TNG100 simulation. The simulations have very different setups, resolution, and feedback models, but are analyzed in a uniform manner. By comparing median radial profiles and mass distributions of CGM properties, we isolate key similarities and differences. In doing so, we advance the efforts of the Simulating Multiscale Astrophysics to Understand Galaxies project that aims to understand the inherently multiscale galaxy formation process. In the cosmological simulations, the CGM exhibits nearly flat temperature distributions, and broad pressure and radial velocity distributions. In the idealized simulations, similar distributions are found in the inner CGM ( ) when strong galactic feedback models are employed, but the outer CGM ( ) has a much less prominent cold phase, and narrower pressure and velocity distributions even in models with strong feedback. This comparative analysis demonstrates the dominant role feedback plays in shaping the inner CGM and the increased importance of cosmological effects, such as nonspherical accretion and satellite galaxies, in the outer CGM. Furthermore, our findings highlight that, while cosmological simulations are required to capture the multiphase structure of the CGM at large radii, idealized simulations provide a robust framework to study how galactic feedback interacts with the inner CGM, and thereby provide a reliable avenue to constrain feedback prescriptions.
Phylogenetic placement of the enigmatic angiosperm Hydrostachys

Summary Albach, D. C. , Soltis, D. E. , Chase, M. W. & Soltis, P. S. : Phylogenetic placement of the enigmatic angiosperm Hydrostachys. - Taxon 50: 781-805. 2001. - ISSN 0040-0262. Hydrostachys, an enigmatic aquatic plant genus from Madagascar and southern to central Africa, has been suggested to be related to Lamiales based on embryology, whereas rbcL sequences have indicated a relationship with Hydrangeaceae (Corales). We investigated these hypotheses by combining rbcL with atpB and ndhF sequences and increased taxon sampling in Hydrangeaceae compared to previous analyses. Rates and patterns of molecular evolution vary across ndhF with the 3' portion giving a different result than the 5' portion. The highly divergent sequences of Hydrostachys make phylogenetic placement difficult, but maximum parsimony and maximum likelihood analyses of combined data sets agree in placing Hydrostachys within Hydrangeaceae, as do separate analyses of rbcL, atpB, and the 5' portion of ndhF. Few morphological and embryological characters support this relationship.
Extracting the Cold Neutral Medium from H i Emission with Deep Learning: Implications for Galactic Foregrounds at High Latitude

Resolving the phase structure of neutral hydrogen (H i) is crucial for understanding the life cycle of the interstellar medium (ISM). However, accurate measurements of H i temperature and density are limited by the availability of background continuum sources for measuring H i absorption. Here we test the use of deep learning for extracting H i properties over large areas without optical depth information. We train a 1D convolutional neural network using synthetic observations of 3D numerical simulations of the ISM to predict the fraction ( ) of cold neutral medium (CNM) and the correction to the optically thin H i column density for optical depth ( ) from 21 cm emission alone. We restrict our analysis to high Galactic latitudes ( ), where the complexity of spectral line profiles is minimized. We verify that the network accurately predicts and by comparing the results with direct constraints from 21 cm absorption. By applying the network to the GALFA-H i survey, we generate large-area maps of and . Although the overall contribution to the total H i column of CNM-rich structures is small (∼5%), we find that these structures are ubiquitous. Our results are consistent with the picture that small-scale structures observed in 21 cm emission aligned with the magnetic field are dominated by CNM. Finally, we demonstrate that the observed correlation between H i column density and dust reddening ( ) declines with increasing , indicating that future efforts to quantify foreground Galactic using H i, even at high latitudes, should increase fidelity by accounting for H i phase structure.