Miracle-dz/UniFAR-FTUs huggingface dataset:
Tensor- and spinor-valued random fields with applications to continuum physics and cosmology

In this paper, we review the history, current state-of-art, and physical applications of the spectral theory of two classes of random functions. One class consists of homogeneous and isotropic random fields defined on a Euclidean space and taking values in a real finite-dimensional linear space. In applications to continuum physics, such a field describes physical properties of a homogeneous and isotropic continuous medium in the situation, when a microstructure is attached to all medium points. The range of the field is the fixed point set of a symmetry class, where two compact Lie groups act by orthogonal representations. The material symmetry group of a homogeneous medium is the same at each point and acts trivially, while the group of physical symmetries may act nontrivially. In an isotropic random medium, the rank 1 (resp. rank 2) correlation tensors of the field transform under the action of the group of physical symmetries according to the above representation (resp. its tensor square), making the field isotropic. Another class consists of isotropic random cross-sections of homogeneous vector bundles over a coset space of a compact Lie group. In applications to cosmology, the coset space models the sky sphere, while the random cross-section models a cosmic background. The Cosmological Principle ensures that the cross-section is isotropic. For convenience of the reader, a necessary material from multilinear algebra, representation theory, and differential geometry is reviewed in Appendix. ∗Corresponding author. Division of Mathematics and Physics, Mälardalen University, Box 883, 721 23 Västerås, Sweden. E-mail: anatoliy.malyarenko@mdh.se. †Department of Mechanical Science & Engineering, also Institute for Condensed Matter Theory and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801-2906 USA. E-mail: martinos@illinois.edu. 1 ar X iv :2 11 2. 04 82 6v 1 [ m at h. PR ] 9 D ec 2 02 1
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation

Knowledge Distillation (KD) is a widely-used technology to inherit information from cumbersome teacher models to compact student models, consequently realizing model compression and acceleration. Compared with image classification, object detection is a more complex task, and designing specific KD methods for object detection is non-trivial. In this work, we elaborately study the behaviour difference between the teacher and student detection models, and obtain two intriguing observations: First, the teacher and student rank their detected candidate boxes quite differently, which results in their precision discrepancy. Second, there is a considerable gap between the feature response differences and prediction differences between teacher and student, indicating that equally imitating all the feature maps of the teacher is the sub-optimal choice for improving the student's accuracy. Based on the two observations, we propose Rank Mimicking (RM) and Prediction-guided Feature Imitation (PFI) for distilling one-stage detectors, respectively. RM takes the rank of candidate boxes from teachers as a new form of knowledge to distill, which consistently outperforms the traditional soft label distillation. PFI attempts to correlate feature differences with prediction differences, making feature imitation directly help to improve the student's accuracy. On MS COCO and PASCAL VOC benchmarks, extensive experiments are conducted on various detectors with different backbones to validate the effectiveness of our method. Specifically, RetinaNet with ResNet50 achieves 40.4% mAP on MS COCO, which is 3.5% higher than its baseline, and also outperforms previous KD methods.
How Universal is Genre in Universal Dependencies?

This work provides the first in-depth analysis of genre in Universal Dependencies (UD). In contrast to prior work on genre identification which uses small sets of well-defined labels in mono-/bilingual setups, UD contains 18 genres with varying degrees of specificity spread across 114 languages. As most treebanks are labeled with multiple genres while lacking annotations about which instances belong to which genre, we propose four methods for predicting instance-level genre using weak supervision from treebank metadata. The proposed methods recover instance-level genre better than competitive baselines as measured on a subset of UD with labeled instances and adhere better to the global expected distribution. Our analysis sheds light on prior work using UD genre metadata for treebank selection, finding that metadata alone are a noisy signal and must be disentangled within treebanks before it can be universally applied.
Sharp nonlinear generalizations of stochastic Gronwall inequalities

We provide nonlinear generalizations of a class of stochastic Gronwall inequalities that have been studied by von Renesse and Scheutzow (2010), Scheutzow (2013), Xie and Zhang (2020), Mehri and Scheutzow (2021) and Le and Ling (2021). This class of stochastic Gronwall inequalities is a useful tool for SDEs. Our main focus are nonlinear generalizations of the Bihari-LaSalle type. Most of our estimates are sharp, in particular, we provide sharp constants for the stochastic Gronwall inequalities. The proofs are connected to the proof of a domination inequality by Lenglart (1977) and a proof by Pratelli (1976). We apply our results to prove existence and uniqueness of global solutions of path-dependent SDEs driven by Lévy processes under a one-sided non-Lipschitz condition. Furthermore, we provide conditions for the existence of exponential moments of solutions of path-dependent SDEs driven by Brownian motion, which are similar to the conditions known for non-path-dependent SDEs.
Bifurcations in inertial focusing of a particle suspended in flow through curved rectangular ducts

Particles suspended in a fluid flow through a curved duct can focus to specific locations within the duct cross-section. This particle focusing is a result of a balance between two dominant forces acting on the particle: (i) the inertial lift force arising from small but non-negligible inertia of the fluid, and (ii) the secondary drag force due to the cross-sectional vortices induced by the curvature of the duct. By adopting a simplified particle dynamics model developed by Ha et al.~[1], we investigate both analytically and numerically, the particle equilibria and their bifurcations when a small particle is suspended in low-flow-rate fluid flow through a curved duct having a $2\times1$ and a $1\times2$ rectangular cross-section. In certain parameter regimes of the model, we analytically obtain the particle equilibria and deduce their stability, while for other parameter regimes, we numerically calculate the particle equilibria and stability. Moreover, we observe a number of different bifurcations in particle equilibria such as saddle-node, pitchfork and Hopf, as the model parameters are varied. These results may aid in the design of inertial microfluidic devices aimed at particle separation by size.
VLT/MUSE and ATCA Observations of the Host Galaxy of the Short GRB 080905A at z = 0.122

Short-GRB progenitors could come in various flavors, depending on the nature of the merging compact stellar objects (including a stellar-mass black hole or not) or depending on their ages (millions or billions of years). At a redshift of z = 0.122, the nearly face-on spiral host of the short GRB 080905A is one of the closest short-GRB host galaxies identified so far. This made it a preferred target to explore spatially resolved star formation and to investigate the afterglow position in the context of its star formation structures. We used VLT/MUSE integral-field unit observations, supplemented by ATCA 5.5/9.0 GHz radio-continuum measurements and publicly available HST data, to study the star formation activity in the GRB 080905A host galaxy. The MUSE observations reveal that the entire host is characterized by strong line emission. Using the Hα line flux, we measure for the entire galaxy an SFR of about 1.6 M ⊙ yr−1, consistent with its non-detection by ATCA. Several individual star-forming regions are scattered across the host. The most luminous region has a Hα luminosity that is nearly four times as high as the luminosity of the Tarantula nebula in the Large Magellanic Cloud. Even though star-forming activity can be traced as close to about 3 kpc (in projection) distance to the GRB explosion site, stellar population synthesis calculations show that none of the Hα-bright star-forming regions is a likely birthplace of the short-GRB progenitor.
COVID-19: Post-recovery long-term symptoms among patients in Saudi Arabia

Background After recovery from acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many patients experience long-term symptoms in different body systems. The aim of the present study was to identify these symptoms, their severity, and their duration as a first step in building a system to classify post-recovery long-term symptoms of coronavirus disease 2019 (COVID-19). Methods An online-based cross-sectional survey was administered between September and October 2020. Data regarding the severity of post-recovery symptoms and their duration were collected using an Arabic questionnaire divided into six categories encompassing the 20 most prevalent symptoms. Results A total of 979 patients recovered from COVID-19 in Saudi Arabia in the study period, of whom 53% were male and 47% were female. The most common symptoms included general fatigue and weakness (73% each), with moderate severity of neurological symptoms including mood changes (41%) and insomnia (39%). Among the special senses, loss of smell and taste of marked severity were reported by 64% and 55% among respiratory symptoms, cough of mild severity (47%), and dyspnea of moderate severity (43%). Loss of appetite of moderate severity was reported in 42%, and diarrhea, abdominal pain, and nausea of mild severity were reported by 53%, 50%, and 44% of respondents, respectively. Conclusions Long-term symptoms after recovery from COVID-19 warrant patient follow-up. The authors propose a classification system as a starting point to guide the identification and follow-up of long-term symptoms post-recovery, and recommend larger-scale studies to broaden the definition of recovery from COVID-19, which appears to have two phases, acute and chronic.
Germ cell apoptosis is critical to maintain Caenorhabditis elegans offspring viability in stressful environments

Maintaining reproduction in highly variable, often stressful, environments is an essential challenge for all organisms. Even transient exposure to mild environmental stress may directly damage germ cells or simply tax the physiology of an individual, making it difficult to produce quality gametes. In Caenorhabditis elegans, a large fraction of germ cells acts as nurse cells, supporting developing oocytes before eventually undergoing so-called physiological germ cell apoptosis. Although C. elegans apoptosis has been extensively studied, little is known about how germline apoptosis is influenced by ecologically relevant environmental stress. Moreover, it remains unclear to what extent germline apoptosis contributes to maintaining oocyte quality, and thus offspring viability, in such conditions. Here we show that exposure to diverse environmental stressors, likely occurring in the natural C. elegans habitat (starvation, ethanol, acid, and mild oxidative stress), increases germline apoptosis, consistent with previous reports on stress-induced apoptosis. Using loss-of-function mutant alleles of ced-3 and ced-4, we demonstrate that eliminating the core apoptotic machinery strongly reduces embryonic survival when mothers are exposed to such environmental stressors during early adult life. In contrast, mutations in ced-9 and egl-1 that primarily block apoptosis in the soma but not in the germline, did not exhibit such reduced embryonic survival under environmental stress. Therefore, C. elegans germ cell apoptosis plays an essential role in maintaining offspring fitness in adverse environments. Finally, we show that ced-3 and ced-4 mutants exhibit concomitant decreases in embryo size and changes in embryo shape when mothers are exposed to environmental stress. These observations may indicate inadequate oocyte provisioning due to the absence of germ cell apoptosis. Taken together, our results show that the central genes of the apoptosis pathway play a key role in maintaining gamete quality, and thus offspring fitness, under ecologically relevant environmental conditions.
Ranking lifestyle risk factors for cervical cancer among Black women: A case-control study from Johannesburg, South Africa

Background Aside from human papillomavirus (HPV), the role of other risk factors in cervical cancer such as age, education, parity, sexual partners, smoking and human immunodeficiency virus (HIV) have been described but never ranked in order of priority. We evaluated the contribution of several known lifestyle co-risk factors for cervical cancer among black South African women. Methods We used participant data from the Johannesburg Cancer Study, a case-control study of women recruited mainly at Charlotte Maxeke Johannesburg Academic Hospital between 1995 and 2016. A total of 3,450 women in the study had invasive cervical cancers, 95% of which were squamous cell carcinoma. Controls were 5,709 women with cancers unrelated to exposures of interest. Unconditional logistic regression models were used to calculate adjusted odds ratios (ORadj) and 95% confidence intervals (CI). We ranked these risk factors by their population attributable fractions (PAF), which take the local prevalence of exposure among the cases and risk into account. Results Cervical cancer in decreasing order of priority was associated with (1) being HIV positive (ORadj = 2.83, 95% CI = 2.53–3.14, PAF = 17.6%), (2) lower educational attainment (ORadj = 1.60, 95% CI = 1.44–1.77, PAF = 16.2%), (3) higher parity (3+ children vs 2–1 children (ORadj = 1.25, 95% CI = 1.07–1.46, PAF = 12.6%), (4) hormonal contraceptive use (ORadj = 1.48, 95% CI = 1.24–1.77, PAF = 8.9%), (5) heavy alcohol consumption (ORadj = 1.44, 95% CI = 1.15–1.81, PAF = 5.6%), (6) current smoking (ORadj = 1.64, 95% CI = 1.41–1.91, PAF = 5.1%), and (7) rural residence (ORadj = 1.60, 95% CI = 1.44–1.77, PAF = 4.4%). Conclunsion This rank order of risks could be used to target educational messaging and appropriate interventions for cervical cancer prevention in South African women.
SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations

Pre-training has become a standard paradigm in many computer vision tasks. However, most of the methods are generally designed on the RGB image domain. Due to the discrepancy between the two-dimensional image plane and the three-dimensional space, such pre-trained models fail to perceive spatial information and serve as sub-optimal solutions for 3D-related tasks. To bridge this gap, we aim to learn a spatial-aware visual representation that can describe the three-dimensional space and is more suitable and effective for these tasks. To leverage point clouds, which are much more superior in providing spatial information compared to images, we propose a simple yet effective 2D Image and 3D Point cloud Unsupervised pre-training strategy, called SimIPU. Specifically, we develop a multi-modal contrastive learning framework that consists of an intra-modal spatial perception module to learn a spatial-aware representation from point clouds and an inter-modal feature interaction module to transfer the capability of perceiving spatial information from the point cloud encoder to the image encoder, respectively. Positive pairs for contrastive losses are established by the matching algorithm and the projection matrix. The whole framework is trained in an unsupervised end-to-end fashion. To the best of our knowledge, this is the first study to explore contrastive learning pre-training strategies for outdoor multi-modal datasets, containing paired camera images and LIDAR point clouds.
Preloaded D-methionine protects from steady state and impulse noise-induced hearing loss and induces long-term cochlear and endogenous antioxidant effects

Objective Determine effective preloading timepoints for D-methionine (D-met) otoprotection from steady state or impulse noise and impact on cochlear and serum antioxidant measures. Design D-met started 2.0-, 2.5-, 3.0-, or 3.5- days before steady-state or impulse noise exposure with saline controls. Auditory brainstem response (ABRs) measured from 2 to 20 kHz at baseline and 21 days post-noise. Samples were then collected for serum (SOD, CAT, GR, GPx) and cochlear (GSH, GSSG) antioxidant levels. Study sample Ten Chinchillas per group. Results Preloading D-met significantly reduced ABR threshold shifts for both impulse and steady state noise exposures but with different optimal starting time points and with differences in antioxidant measures. For impulse noise exposure, the 2.0, 2.5, and 3.0 day preloading start provide significant threshold shift protection at all frequencies. Compared to the saline controls, serum GR for the 3.0 and 3.5 day preloading groups was significantly increased at 21 days with no significant increase in SOD, CAT or GPx for any impulse preloading time point. Cochlear GSH, GSSG, and GSH/GSSG ratio were not significantly different from saline controls at 21 days post noise exposure. For steady state noise exposure, significant threshold shift protection occurred at all frequencies for the 3.5, 3.0 and 2.5 day preloading start times but protection only occurred at 3 of the 6 test frequencies for the 2.0 day preloading start point. Compared to the saline controls, preloaded D-met steady-state noise groups demonstrated significantly higher serum SOD for the 2.5–3.5 day starting time points and GPx for the 2.5 day starting time but no significant increase in GR or CAT for any preloading time point. Compared to saline controls, D-met significantly increased cochlear GSH concentrations in the 2 and 2.5 day steady-state noise exposed groups but no significant differences in GSSG or the GSH/GSSG ratio were noted for any steady state noise-exposed group. Conclusions The optimal D-met preloading starting time window is earlier for steady state (3.5–2.5 days) than impulse noise (3.0–2.0). At 21 days post impulse noise, D-met increased serum GR for 2 preloading time points but not SOD, CAT, or GpX and not cochlear GSH, GSSG or the GSH/GSSG ratio. At 21 days post steady state noise D-met increased serum SOD and GPx at select preloading time points but not CAT or GR. However D-met did increase the cochlear GSH at select preloading time points but not GSSG or the GSH/GSSG ratio.
Massive Star-Forming Galaxies Have Converted Most of Their Halo Gas into Stars

In the local Universe, the e ﬃ ciency for converting baryonic gas into stars is very low. In dark matter halos where galaxies form and evolve, the average e ﬃ ciency varies with galaxy stellar mass and has a maximum of about 20% for Milky-Way-like galaxies. The low e ﬃ ciency at higher mass is believed to be the result of some quenching processes, such as the feedback from active galactic nuclei. We perform an analysis of weak lensing and satellite kinematics for SDSS central galaxies. Our results reveal that the e ﬃ ciency is much higher, more than 60%, for a large population of massive star-forming galaxies around 10 11 M (cid:12) . This suggests that these galaxies acquired most of the gas in their halos and converted it into stars without being signiﬁcantly a ﬀ ected by quenching processes. This population of galaxies is not reproduced in current galaxy formation models, indicating that our understanding of galaxy formation is incomplete. The implications of our results on circumgalactic media, star-formation quenching, and disk galaxy rotation curves are discussed. We also examine systematic uncertainties in halo-mass and stellar-mass measurements that might inﬂuence our results.
The Transit Timing and Atmosphere of Hot Jupiter HAT-P-37b

We perform transit timing variation (TTV) and transmission spectroscopy analyses of the planet HAT-P-37b, which is a hot Jupiter orbiting a G-type star. Nine new transit light curves are obtained and analyzed together with 21 published light curves from the literature. The updated physical parameters of HAT-P-37b are presented. The TTV analyses show a possibility that the system has an additional planet that induced the TTVs amplitude signal of 1.74 ± 0.17 minutes. If the body is located near the 1:2 mean-motion resonance orbit, the sinusoidal TTV signal could be caused by the gravitational interaction of a sub-Earth-mass planet with mass of 0.06 M ⊕. From the analysis of an upper-mass limit for the second planet, a Saturn-mass planet with orbital period less than 6 days is excluded. The broadband transmission spectra of HAT-P-37b favors a cloudy atmospheric model with an outlier spectrum in the B filter.
Artificial Intelligence and Design of Experiments for Assessing Security of Electricity Supply: A Review and Strategic Outlook

Assessing the effects of the energy transition and liberalization of energy markets on resource adequacy is an increasingly important and demanding task. The rising complexity in energy systems requires adequate methods for energy system modeling leading to increased computational requirements. Furthermore, with complexity, uncertainty increases likewise calling for probabilistic assessments and scenario analyses. To adequately and efficiently address these various requirements, new methods from the field of data science are needed to accelerate current methods. With our systematic literature review, we want to close the gap between the three disciplines (1) assessment of security of electricity supply, (2) artificial intelligence, and (3) design of experiments. For this, we conduct a large-scale quantitative review on selected fields of application and methods and make a synthesis that relates the different disciplines to each other. Among other findings, we identify metamodeling of complex security of electricity supply models using AI methods and applications of AI-based methods for forecasts of storage dispatch and (non-)availabilities as promising fields of application that have not sufficiently been covered, yet. We end with deriving a new methodological pipeline for adequately and efficiently addressing the present and upcoming challenges in the assessment of security of electricity supply.
Topological Doping and Superconductivity in Cuprates: An Experimental Perspective

Hole doping into a correlated antiferromagnet leads to topological stripe correlations, involving charge stripes that separate antiferromagnetic spin stripes of opposite phases. The topological spin stripe order causes the spin degrees of freedom within the charge stripes to feel a geometric frustration with their environment. In the case of cuprates, where the charge stripes have the character of a hole-doped two-leg spin ladder, with corresponding pairing correlations, anti-phase Josephson coupling across the spin stripes can lead to a pair-density-wave order in which the broken translation symmetry of the superconducting wave function is accommodated by pairs with finite momentum. This scenario is now experimentally verified by recently reported measurements on La2−xBaxCuO4 with x=1/8. While pair-density-wave order is not common as a cuprate ground state, it provides a basis for understanding the uniform d-wave order that is more typical in superconducting cuprates.