Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing for error invariance in separable instrumental variable models

The hypothesis of error invariance is central to the instrumental variable literature. It means that the error term of the model is the same across all potential outcomes. In other words, this assumption signiﬁes that treatment eﬀects are constant across all subjects. It allows to interpret instrumental variable estimates as average treatment eﬀects over the whole population of the study. When this assumption does not hold, the bias of instrumental variable estimators can be larger than that of naive estimators ignoring endogeneity. This paper develops two tests for the assumption of error invariance when the treatment is endogenous, an instrumental variable is available and the model is separable. The ﬁrst test assumes that the potential outcomes are linear in the regressors and is computationally simple. The second test is nonparametric and relies on Tikhonov regularization. The treatment can be either discrete or continuous. We show that the tests have asymptotically correct level and asymptotic power equal to one against a range of alternatives. Simulations demonstrate that the proposed tests attain excellent ﬁnite sample performances. The methodology is also applied to the evaluation of returns to schooling and the eﬀect of price on demand in a ﬁsh market. Section A is concerned with the linear test. It contains the proofs of a result regarding Example 1 (A.1) and of Theorem 1 (A.2). Section B treats the nonparametric test. It includes the proof of the results of Section 3 in the main text (B.1) and a theoretical analysis of the power of the test through examples (B.2).
Comparison of three numerical stabilization techniques of viscoelastic flows: vortex shedding behind a confined cylinder

In this study, the OpenFOAM platform, based on the finite volume method, is applied to investigate the two-dimensional viscoelastic flow past a circular cylinder. The FENE-P model, which considers the bounded elongation of polymer molecules, is chosen to describe the elastic constitutive relationship of the polymer solution. The maximum molecular chain lengths of L = 10, 50, 100, and 200 are considered, which describe the molecular conformation characteristics of the polymer solution. To improve the numerical instability of the viscoelastic flow simulation, three different methods, i.e., the traditional method ( Td ) with the addition of artificial viscosity, the logarithmic reconstruction method (Log), and the square root tensor method (Sqrt), are evaluated. The results show that the artificial viscosity has a little effect on the accuracy for the simulation with a small molecular chain length ( L = 10). However, for long molecular chain lengths such as L = 100 and L = 200, the addition of artificial dissipation tends to overestimate the drag, which indicates that special caution is needed to incorporate the artificial dissipation in the simulation. Moreover, the logarithmic reconstruction method shows a strong grid-dependent characteristics, which may produce unphysical results.
Online Learning in Fisher Markets: Static Pricing Limits and Adaptive Enhancements

In a Fisher market, agents (users) spend a budget of (artiﬁcial) currency to buy goods that maximize their utilities while a central planner sets prices on capacity-constrained goods such that the market clears. However, the eﬃcacy of pricing schemes in achieving an equilibrium outcome in Fisher markets typically relies on complete knowledge of users’ budgets and utility functions and requires that transactions happen in a static market wherein all users are present simultaneously. Motivated by these practical considerations, in this work, we study an online variant of Fisher markets, wherein budget-constrained users with privately known utility and budget parameters, drawn i.i. d. from a distribution D , enter the market sequentially. In this setting, we develop an algorithm that adjusts prices solely based on observations of user consumption, i.e., revealed preference feedback, and achieves a regret and capacity violation of O ( √ n ), where n is the number of users and the good capacities scale as O ( n ). Here, our regret measure is the optimality gap in the objective of the Eisenberg-Gale program between an online algorithm and an oﬄine oracle with complete information on users’ budgets and utilities. To establish the eﬃcacy of our approach, we show that any uniform (static) pricing algorithm, including one that sets expected equilibrium prices with complete knowledge of the distribution D , cannot achieve both a regret and constraint violation of less than Ω( √ n ). While our revealed preference algorithm requires no knowledge of the distribution D , we show that if D is known, then an adaptive variant of expected equilibrium pricing achieves O (log( n )) regret and constant capacity violation for discrete distributions. Finally, we present numerical experiments to demonstrate the performance of our revealed preference algorithm relative to several benchmarks.
Learning Degradation Representations for Image Deblurring

In various learning-based image restoration tasks, such as image denoising and image super-resolution, the degradation representations were widely used to model the degradation process and handle complicated degradation patterns. However, they are less explored in learning-based image deblurring as blur kernel estimation cannot perform well in real-world challenging cases. We argue that it is particularly necessary for image deblurring to model degradation representations since blurry patterns typically show much larger variations than noisy patterns or high-frequency textures.In this paper, we propose a framework to learn spatially adaptive degradation representations of blurry images. A novel joint image reblurring and deblurring learning process is presented to improve the expressiveness of degradation representations. To make learned degradation representations effective in reblurring and deblurring, we propose a Multi-Scale Degradation Injection Network (MSDI-Net) to integrate them into the neural networks. With the integration, MSDI-Net can handle various and complicated blurry patterns adaptively. Experiments on the GoPro and RealBlur datasets demonstrate that our proposed deblurring framework with the learned degradation representations outperforms state-of-the-art methods with appealing improvements. The code is released at https://github.com/dasongli1/Learning_degradation.
SEIFERT SURFACE COMPLEMENTS OF NEARLY FIBERED KNOTS

In this note, we study the nearly ﬁbered knots recently introduced by Baldwin and Sivek, i.e. , knots whose knot homology has top rank two. We give a topological description of the Seifert surface complement of a nearly ﬁbered knot by showing it must fall into one of the three basic models.
Operation-Based Refactoring-Aware Merging: An Empirical Evaluation

Dealing with merge conflicts in version control systems is a challenging task for software developers. Resolving merge conflicts is a time-consuming and error-prone process, which distracts developers from important tasks. Recent work shows that refactorings are often involved in merge conflicts and that refactoring-related conflicts tend to be larger, making them harder to resolve. In the literature, there are two refactoring-aware merging techniques that claim to automatically resolve refactoring-related conflicts; however, these two techniques have never been empirically compared. In this paper, we present RefMerge, a rejuvenated Java-based design and implementation of the first technique, which is an operation-based refactoring-aware merging algorithm. We compare RefMerge to Git and the state-of-the-art graph-based refactoring-aware merging tool, IntelliMerge, on 2,001 merge scenarios with refactoring-related conflicts from 20 open-source projects. We find that RefMerge resolves or reduces conflicts in 497 (25%) merge scenarios while increasing conflicting LOC in only 214 (11%) scenarios. On the other hand, we find that IntelliMerge resolves or reduces conflicts in 478 (24%) merge scenarios but increases conflicting LOC in 597 (30%) merge scenarios. We additionally conduct a qualitative analysis of the differences between the three merging algorithms and provide insights of the strengths and weaknesses of each tool. We find that while IntelliMerge does well with ordering and formatting conflicts, it struggles with class-level refactorings and scenarios with several refactorings. On the other hand, RefMerge is resilient to the number of refactorings in a merge scenario, but we find that RefMerge introduces conflicts when inverting move-related refactorings.
Probing the circumgalactic baryons through cross-correlations

We study the cross-correlation of distribution of galaxies, the Sunyaev-Zel’dovich (SZ) and X-ray power spectra of galaxies from current and upcoming surveys and show these to be excellent probes of the nature, i.e. extent, evolution and energetics, of the circumgalactic medium (CGM). We consider the contributions from the hot gas in only those galaxies in which the gas cooling time-scale is larger than the halo destruction time-scale. For a flat pressure profile, the SZ cross power spectrum shows oscillations at l-values corresponding to the length scales smaller than � 2 times the virial radius of the galaxy. These oscillations are sensitive to the steepness of the pressure profile of the CGM and vanish for a sufficiently steep profile. This property of the SZ signal can, thus, be used to constrain the pressure profile of the CGM. Similar oscillations are also present in the X-ray cross power spectrum which is, however, more sensitive to the density profile. We forecast the detectability of the cross-correlated galaxy distribution, SZ and X-ray signals by combining SPT-DES and eROSITADES/eROSITA-LSST surveys, respectively. We find that, for the SPT-DES survey, the signal-to-noise ratio (SNR) peaks at high mass and redshift with SNR � 9 around Mh � 10 13 h −1 M⊙ and z � 1.5–2 for flat density and temperature profiles. The SNR is also significant (> 3) for high mass and low redshift galaxies. The SNR peaks at � 6(12) for the eROSITA-DES (eROSITA-LSST) surveys. We also perform a Fisher matrix analysis and find that the gas fraction in the CGM can be constrained to a precision of � 34%(23%) by the SPT-DES and � 23%(14%) by the eROSITA-DES surveys in the presence (absence) of an unknown redshift evolution of the gas fraction. Finally, we demonstrate that the cross-correlated SZ-galaxy and X-ray-galaxy power spectrum can be used as powerful probes of the CGM energetics and potentially discriminate between different feedback models recently proposed in the literature; for example, one can distinguish a ‘no AGN feedback’ scenario from a CGM energized by ‘fixed-velocity hot winds’ at greater than 3σ.
U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?

Due to their extreme long-range modeling capability, vision transformer-based networks have become increasingly popular in deformable image registration. We believe, however, that the receptive field of a 5-layer convolutional U-Net is sufficient to capture accurate deformations without needing long-range dependencies. The purpose of this study is therefore to investigate whether U-Net-based methods are outdated compared to modern transformer-based approaches when applied to medical image registration. For this, we propose a large kernel U-Net (LKU-Net) by embedding a parallel convolutional block to a vanilla U-Net in order to enhance the effective receptive field. On the public 3D IXI brain dataset for atlas-based registration, we show that the performance of the vanilla U-Net is already comparable with that of state-of-the-art transformer-based networks (such as TransMorph), and that the proposed LKU-Net outperforms TransMorph by using only 1.12% of its parameters and 10.8% of its mult-adds operations. We further evaluate LKU-Net on a MICCAI Learn2Reg 2021 challenge dataset for inter-subject registration, our LKU-Net also outperforms TransMorph on this dataset and ranks first on the public leaderboard as of the submission of this work. With only modest modifications to the vanilla U-Net, we show that U-Net can outperform transformer-based architectures on inter-subject and atlas-based 3D medical image registration. Code is available at https://github.com/xi-jia/LKU-Net.
Exact and approximate computation of the scatter halfspace depth

The scatter halfspace depth (sHD) is an extension of the location halfspace (also called Tukey) depth that is applicable in the nonparametric analysis of scatter. Using sHD, it is possible to define minimax optimal robust scatter estimators for multivariate data. The problem of exact computation of sHD for data of dimension $d \geq 2$ has, however, not been addressed in the literature. We develop an exact algorithm for the computation of sHD in any dimension $d$ and implement it efficiently using C++ for $d \leq 5$, and in R for any dimension $d \geq 1$. Since the exact computation of sHD is slow especially for higher dimensions, we also propose two fast approximate algorithms. All our programs are freely available in the R package scatterdepth.
Contribution of Spicules to Solar Coronal Emission

Recent high-resolution imaging and spectroscopic observations have generated renewed interest in spicules’ role in explaining the hot corona. Some studies suggest that some spicules, often classified as type II, may provide significant mass and energy to the corona. Here we use numerical simulations to investigate whether such spicules can produce the observed coronal emission without any additional coronal heating agent. Model spicules consisting of a cold body and hot tip are injected into the base of a warm (0.5 MK) equilibrium loop with different tip temperatures and injection velocities. Both piston- and pressure-driven shocks are produced. We find that the hot tip cools rapidly and disappears from coronal emission lines such as Fe xii 195 and Fe xiv 274. Prolonged hot emission is produced by preexisting loop material heated by the shock and by thermal conduction from the shock. However, the shapes and Doppler shifts of synthetic line profiles show significant discrepancies with observations. Furthermore, spatially and temporally averaged intensities are extremely low, suggesting that if the observed intensities from the quiet Sun and active regions were solely due to type II spicules, one to several orders of magnitude more spicules would be required than have been reported in the literature. This conclusion applies strictly to the ejected spicular material. We make no claims about emissions connected with waves or coronal currents that may be generated during the ejection process and heat the surrounding area.
G-PCC Post-Processing Using Fractional Super-Resolution

We present a method for post-processing point clouds’ geometric information by applying a previously proposed fractional super-resolution technique to clouds compressed and decoded with MPEG’s G-PCC codec. In some sense, this is a continuation of that previous work, which requires only a down-scaled point cloud and a scaling factor, both of which are provided by the G-PCC codec. For non-solid point clouds, an a priori down-scaling is required for improved efﬁciency. The method is compared to the GPCC itself, as well as machine-learning-based techniques. Results show a great improvement in quality over GPCC and comparable perfor-mance to the latter techniques, with the advantage of not needing any kind of previous training.
Hundreds of Low-mass Active Galaxies in the Galaxy And Mass Assembly (GAMA) Survey

We present an entirely new sample of 388 low-mass galaxies (M ⋆ ≤ 1010 M ⊙) that have spectroscopic signatures indicating the presence of massive black holes (BHs) in the form of active galactic nuclei (AGNs) or tidal disruption events. Of these, 70 have stellar masses in the dwarf galaxy regime with 108 ≲ M ⋆/M ⊙ ≲ 109.5. We identify the active galaxies by analyzing optical spectra of a parent sample of ∼23,000 low-mass emission-line galaxies in the Galaxy and Mass Assembly (GAMA) Survey Data Release 4, and employing four different diagnostics based on narrow emission-line ratios and the detection of high-ionization coronal lines. We find that 47 of the 388 low-mass active galaxies exhibit broad Hα in their spectra, corresponding to virial BH masses in the range M BH ∼ 105.0–7.7 M ⊙ with a median BH mass of 〈M BH〉 ∼ 106.2 M ⊙. Our sample extends to higher redshifts (z ≤ 0.3; 〈z〉 = 0.13) than previous samples of AGNs in low-mass/dwarf galaxies based on Sloan Digital Sky Survey spectroscopy, which can be attributed to the spectroscopic limit of GAMA being ∼2 mag deeper. Moreover, our multi-diagnostic approach has revealed low-mass active galaxies spanning a wide range of properties, from blue star-forming dwarfs to luminous “miniquasars” powered by low-mass BHs. As such, this work has implications for BH seeding and AGN feedback at low masses.
Novel microfluidic strategy for the production of sodium alginate fibers with regular inclusions at very high throughput

Scalable technologies for the production of bio-compatible complex microﬁbers with controllable size and composition at competitively high throughput are urgently needed in order to meet the growing demand for such microstructures in pharmaceutical or biomedical applications. Here, we introduce a new in-air microﬂuidic strategy with throughput of > 1400 ml/h (corresponding to > 17000 m ﬁber per h ). The microﬁbers of uniform diameter have regular inclusions, which can potentially be used for encapsulating cells into a protecting and nutrient environment, or for ﬁnely tuning the release of various actives at individualized doses. With the help of a newly developed prototype, we test seven diﬀerent liquid combinations and obtain seven types of ﬁbers, whose ”dry” diameter range between 73 µm and 141 µm . The principle of our approach is to solidify the complex liquid structures generated by the controlled collisions of a drop stream with a continuous liquid jet, in air, via ionic crosslinking. After the stream of water-based droplets, which constitute the inclusions, collides in-air with the alginate-based jet (jet 1), the generated drops-in-jet compound is brought in contact with a second jet (jet 2) containing divalent cations ( Sr 2+ or Ca 2+ ) to initiate the solidiﬁcation. Finally, the ﬁbers are collected via a horizontal spinning plate, let to dry, i.e. to fully equilibrate under controlled conditions, and characterized by their elongation at break and Young’s modulus.
Common genetic variant of GC associated with vitamin D deficiency in a Chinese population in the Netherlands

Background Genome-wide association studies among European populations have identified four single nucleotide polymorphisms (SNPs) in genes involved in vitamin D transport and metabolism affecting 25-hydroxyvitamin D [25(OH)D] concentration: rs2282679 in GC, rs6013897 near CYP24A1, rs10741657 near CYP2R1, and rs12785878 near DHCR7. It is, however, unknown whether the association with 25(OH)D can also be observed in a Chinese population living in the Netherlands. Methods Observational study. Analyses were performed under an additive (univariate and multivariate) and genotypic model using logistic regression. Results The C allele (minor allele frequency 0.28) of rs2282679 in GC was associated with vitamin D deficiency as defined by the Health Council of the Netherlands: 25(OH)D <30 nmol/l (or <50 nmol/l for persons aged [≥]70 years). Univariate and multivariate odds ratios, 1.52 (95% CI 1.03, 2.24) and 1.57 (95% CI 1.04, 2.39), respectively, were not significant after Bonferroni correction. However, after extending the data by a meta-analysis, a significant association between C allele of rs2282679 and vitamin D deficiency (< 50 nmol/l) was observed (odds ratio 1.33; 95% CI 1.16, 1.52). Conclusion Our findings suggest that, apart from sun exposure, lifestyle, and environmental factors, a common variant of GC may be associated with vitamin D deficiency.
State and trait dimensions of subjective memory concerns: Genetic influences across 30 years

INTRODUCTION: Genetic influences on the stability of subjective memory concerns (SMC) may confound its interpretation as a state-related risk indicator. METHODS: We estimated genetic influences on SMC and SMC change from average ages 38 to 67, genetic correlations of SMC with memory and depressive symptoms at average ages 56, 62, and 67, and correlations of SMC with polygenic scores for Alzheimers disease and neuroticism, APOE genotype, and parental history or dementia. RESULTS: SMC was highly stable over this 30-year period. Heritability was . 51. Phenotypically and genetically, SMC was more strongly related to depressive symptoms than to objective memory. It was also correlated with parental history of dementia and polygenic risk for neuroticism. DISCUSSION: SMCs heritability and stability indicate a substantial trait-like component that is related more to depression and personality than objective memory. Improving it as an indicator of impending cognitive decline or dementia will require isolating its state-related component.
Modality and facivity : One perspective on the meaning of the English modal auxiliaries

This study concentrates on modality as expressed by the set of modal auxiliaries and seeks to establish that these verbs share semantic as well as syntactic properties by identifying a single core meaning which they share. The relationship between modality and factivity is examined with the aim of gaining an insight into the former, more complex concept. When viewed from this perspective, the defining characteristic of all the modal auxiliary verbs in almost all of their uses is found to be nonfactivity. The meanings expressed by this set of verbs are classified according to a framework derived from modal logic consisting of three basic types of modality each of which relates to a different set of laws or principles; the relative factivity associated with the modal auxiliaries is seen to vary with the nature of modality as defined and classified by this framework. Within each of the three types of modality, a semantic scale is identified and modality is described as a gradable concept for which scalar analysis is appropriate, both within and beyond these three scales. Relative factivity is also shown to vary according to the degree of modality expressed by each of the modal verbs. The nature and degree of modality expressed interact with features of the linguistic (and pragmatic) context to determine the particular factive or a contrafactive interpretation conveyed by a given modal auxiliary token. The influence of certain combinations of contextual features is sufficiently strong to force a factive or contrafactive reading of a modal token, although in general the role of such features is merely to strengthen or weaken the relative factivity associated with the modal verb. Epistemic modality is seen to be most directly related to nonfactivity and therefore to be the most central modal meaning. The modal auxiliaries are found to be semantically less modal when they occur in contexts of determinate factual status. Least modal are those members of this set of auxiliary verbs which in certain uses have determinate factual status even without the presence of any of the significant contextual features.