Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal Discovery in Physical Systems from Videos

Causal discovery is at the core of human cognition. It enables us to reason about the environment and make counterfactual predictions about unseen scenarios, that can vastly differ from our previous experiences. We consider the task of causal discovery from videos in an end-to-end fashion without supervision on the ground-truth graph structure. In particular, our goal is to discover the structural dependencies among environmental and object variables: inferring the type and strength of interactions that have a causal effect on the behavior of the dynamical system. Our model consists of (a) a perception module that extracts a semantically meaningful and temporally consistent keypoint representation from images, (b) an inference module for determining the graph distribution induced by the detected keypoints, and (c) a dynamics module that can predict the future by conditioning on the inferred graph. We assume access to different configurations and environmental conditions, i.e., data from unknown interventions on the underlying system; thus, we can hope to discover the correct underlying causal graph without explicit interventions. We evaluate our method in a planar multi-body interaction environment and scenarios involving fabrics of different shapes like shirts and pants. Experiments demonstrate that our model can correctly identify the interactions from a short sequence of images and make long-term future predictions. The causal structure assumed by the model also allows it to make counterfactual predictions and extrapolate to systems of unseen interaction graphs or graphs of various sizes.
Constraining the masses of high-redshift clusters with weak lensing: Revised shape calibration testing for the impact of stronger shears and increased blending

Weak lensing measurements suffer from well-known shear estimation biases, which can be partially corrected for with the use of image simulations. In this work we present an analysis of simulated images that mimic Hubble Space Telescope/Advance Camera for Surveys observations of high-redshift galaxy clusters, including cluster specific issues such as non-weak shear and increased blending. Our synthetic galaxies have been generated to have similar observed properties as the background-selected source samples studied in the real images. First, we used simulations with galaxies placed on a grid to determine a revised signal-to-noise-dependent (S/NKSB) correction for multiplicative shear measurement bias, and to quantify the sensitivity of our KSB+ bias calibration to mismatches of galaxy or PSF properties between the real data and the simulations. Next, we studied the impact of increased blending and light contamination from cluster and foreground galaxies, finding it to be negligible for high-redshift (z > 0.7) clusters, whereas shear measurements can be affected at the ∼1% level for lower redshift clusters given their brighter member galaxies. Finally, we studied the impact of fainter neighbours and selection bias using a set of simulated images that mimic the positions and magnitudes of galaxies in Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) data, thereby including realistic clustering. While the initial SExtractor object detection causes a multiplicative shear selection bias of −0.028 ± 0.002, this is reduced to −0.016 ± 0.002 by further cuts applied in our pipeline. Given the limited depth of the CANDELS data, we compared our CANDELS-based estimate for the impact of faint neighbours on the multiplicative shear measurement bias to a grid-based analysis, to which we added clustered galaxies to even fainter magnitudes based on Hubble Ultra Deep Field data, yielding a refined estimate of ∼ − 0.013. Our sensitivity analysis suggests that our pipeline is calibrated to an accuracy of ∼0.015 once all corrections are applied, which is fully sufficient for current and near-future weak lensing studies of high-redshift clusters. As an application, we used it for a refined analysis of three highly relaxed clusters from the South Pole Telescope Sunyaev-Zeldovich survey, where we now included measurements down to the cluster core (r > 200 kpc) as enabled by our work. Compared to previously employed scales (r > 500 kpc), this tightens the cluster mass constraints by a factor 1.38 on average.
Effects of density on the oxygen ionization equilibrium in collisional plasmas

The ion populations most frequently adopted for diagnostics in collisional plasmas are derived from the density independent coronal approximation. In higher density, lower temperature conditions, ionization rates are enhanced once metastable levels become populated, and recombination rates are suppressed if ions recombine into Rydberg levels. As a result, the formation temperatures of ions shift, altering the diagnostics of the plasma. To accurately model the effect of ionization from metastable levels, new electron impact ionization cross-sections have been calculated for oxygen, both for direct ionization and excitation–auto-ionization of the ground and metastable levels. The results have been incorporated into collisional radiative modelling to show how the ionization equilibrium of oxygen changes once metastable levels become populated. Suppression of dielectronic recombination has been estimated and also included in the modelling, demonstrating the shifts with density in comparison to the coronal approximation. The final results for the ionization equilibrium are used in differential emission measure modelling to predict line intensities for many lines emitted by O ii–O vi in the solar transition region. The predictions show improved agreement by 15–40 per cent for O ii, O vi, and the intercombination lines of O iii–O v, when compared to results from coronal approximation modelling. While there are still discrepancies with observations of these lines, this could, to a large part, be explained by variability in the observations.
Data-driven Regularization via Racecar Training for Generalizing Neural Networks

We propose a novel training approach for improving the generalization in neural networks. We show that in contrast to regular constraints for orthogonality, our approach represents a {\em data-dependent} orthogonality constraint, and is closely related to singular value decompositions of the weight matrices. We also show how our formulation is easy to realize in practical network architectures via a reverse pass, which aims for reconstructing the full sequence of internal states of the network. Despite being a surprisingly simple change, we demonstrate that this forward-backward training approach, which we refer to as {\em racecar} training, leads to significantly more generic features being extracted from a given data set. Networks trained with our approach show more balanced mutual information between input and output throughout all layers, yield improved explainability and, exhibit improved performance for a variety of tasks and task transfers.
Deep Learning for Vision-based Prediction: A Survey

Vision-based prediction algorithms have a wide range of applications including autonomous driving, surveillance, human-robot interaction, weather prediction. The objective of this paper is to provide an overview of the field in the past five years with a particular focus on deep learning approaches. For this purpose, we categorize these algorithms into video prediction, action prediction, trajectory prediction, body motion prediction, and other prediction applications. For each category, we highlight the common architectures, training methods and types of data used. In addition, we discuss the common evaluation metrics and datasets used for vision-based prediction tasks. A database of all the information presented in this survey including, cross-referenced according to papers, datasets and metrics, can be found online at this https URL.
Description of Eggs, Nest, and Parental Care of the Smoky Bush Tyrant (Myiotheretes fumigatus) from Ecuador

Abstract We report the first nest of the Smoky Bush Tyrant (Myiotheretes fumigatus) which was found on 11 October 2009 at the Yanayacu Biological Station, Napo Province in Ecuador. The nest was a shallow open cup, 2 m above ground on the side of a dead stump covered in epiphytes. The nest was 12 cm wide by 6.5 cm in height; internally, the cup was 7 cm wide by 4 cm deep and was lined predominantly with scales from the tree-fern (Cyathea spp.), but included a few small sticks and brightly colored feathers. Both eggs were predominantly white with a few small, widely dispersed, dark reddish spots, predominantly around the fattest area. They measured 24.0 × 18 and 23.0 × 17.5 mm, and weighed 3.6 and 3.5 g, respectively. The first fully feathered fledgling left the nest on 2 November and the second on 3 November, for a nestling period of 16–17 days. We noted the presence of a third bird (besides the pair) which remained within the territory through the entire nesting period, at times in close association with the breeding pair.
Corn (Zea mays L.) Response to Trifloxysulfuron1

Experiments were conducted in weed-free environments to determine corn tolerance to trifloxysulfuron applied PRE or POST, and to determine the potential for trifloxysulfuron applied PRE or POST to cotton to injure corn grown in rotation the following year. Trifloxysulfuron at 3.75, 7.5, or 15 g ai/ha applied PRE or POST resulted in 98% stand reduction of imidazolinone-tolerant (IT) corn and 100% stand reduction in conventional corn. No injury occurred to imidazolinone-resistant (IR) corn. A corn cultivar yield response was observed, with conventional nontreated corn yielding 8,850 kg/ha and greater than nontreated IT corn at 7,900 kg/ha. Nontreated IR corn yielded the least, at 6,400 kg/ha, and these yields were equivalent to trifloxysulfuron-treated IR corn at 6,590 kg/ha. Cotton treated with trifloxysulfuron PRE at any rate was injured less than 8%. Both trifloxysulfuron at 7.5 g/ha POST and pyrithiobac at 70 g ai/ha POST injured cotton 11% early in the season. Neither trifloxysulfuron nor pyrithiobac influenced weed-free cotton lint yields. When grown in rotation, corn was not injured by trifloxysulfuron or pyrithiobac applied the previous year to cotton, and yields were not influenced. Nomenclature: Trifloxysulfuron; cotton, Gossypium hirsutum L. ; corn, Zea mays L. Additional index words: Carryover, crop injury, sulfonylurea herbicide. Abbreviations: ALS, acetolactate synthase.
Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes

Les humains apprennent toute leur vie. Ils accumulent des connaissances a partir d'une succession d'experiences d'apprentissage et en memorisent les aspects essentiels sans les oublier. Les reseaux de neurones artificiels ont des difficultes a apprendre dans de telles conditions. Ils ont en general besoin d'ensembles de donnees rigoureusement prepares pour pouvoir apprendre a resoudre des problemes comme de la classification ou de la regression. En particulier, lorsqu'ils apprennent sur des sequences d'ensembles de donnees, les nouvelles experiences leurs font oublier les anciennes. Ainsi, ils sont souvent incapables d'apprehender des scenarios reels tels ceux de robots autonomes apprenant en temps reel a s'adapter a de nouvelles situations et devant resoudre des problemes sans oublier leurs experiences passees.L'apprentissage continu est une branche de l'apprentissage automatique s'attaquant a ce type de scenarios. Les algorithmes continus sont crees pour apprendre des connaissances, les enrichir et les ameliorer au cours d'un curriculum d'experiences d'apprentissage.Dans cette these, nous proposons d'explorer l'apprentissage continu avec rejeu de donnees. Les methodes de rejeu de donnees rassemblent les methodes de repetitions et les methodes de rejeu par generation. Le rejeu par generation consiste a utiliser un reseau de neurones auxiliaire apprenant a generer les donnees actuelles. Ainsi plus tard le reseau auxiliaire pourra etre utilise pour regenerer des donnees du passe et les rememorer au modele principal. La repetition a le meme objectif, mais cette methode sauve simplement des images specifiques et les rejoue plus tard au modele principal pour eviter qu'il ne les oublie. Les methodes de rejeu permettent de trouver un compromis entre l'optimisation de l'objectif d'apprentissage actuel et ceux du passe. Elles permettent ainsi d'apprendre sans oublier sur des sequences de tâches. Nous montrons que ces methodes sont prometteuses pour l'apprentissage continu.En particulier, elles permettent la reevaluation des donnees du passe avec des nouvelles connaissances et de confronter des donnees issues de differentes experiences. Nous demontrons la capacite des methodes de rejeu a apprendre continuellement a travers des tâches d'apprentissage non-supervisees, supervisees et de renforcements.
Verrucophora farcimen gen. et sp. nov. (Dictyochophyceae, Heterokonta)—a bloom‐forming ichthyotoxic flagellate from the Skagerrak, Norway 1

Since 1998, a heterokont flagellate initially named Chattonella aff. verruculosa has formed recurrent extensive blooms in the North Sea and the Skagerrak, causing fish mortalities. Cells were isolated from the 2001 bloom off the south coast of Norway, and monoalgal cultures were established and compared with the Chattonella verruculosa Y. Hara et Chihara reference strain NIES 670 from Japan. The cells in Norwegian cultured isolates were very variable in size and form, being large oblong (up to 34 μm long) to small rounded (5–9 μm in diameter) with two unequal flagella, numerous chloroplasts, and mucocysts. The SSU and partial LSU rDNA sequences of strains from Norway and Japan were compared and differed by 0.4% (SSU) and 1.3% (LSU), respectively. Five strains from Norway were identical in the LSU rDNA region. Phylogenetic analyses based on heterokont SSU and concatenated SSU + LSU rDNA sequences placed C. aff. verruculosa and the Japanese C. verruculosa within the clade of Dictyochophyceae, with the picoflagellate Florenciella parvula Eikrem as the closest relative. Ultrastructure, morphology, and pigment composition supported this affinity. We propose the name Verrucophora farcimen sp. et gen. nov. for this flagellate and systematically place it within the class Dictyochophyceae. Our studies also show that C. verruculosa from Japan is genetically and morphologically different but closely related to V. farcimen. The species is transferred from the class Raphidophyceae to the class Dictyochophyceae and renamed Verrucophora verruculosa. We propose a new order, Florenciellales, to accommodate V. farcimen, V. verruculosa, and F. parvula.
JWST Transit Spectra. II. Constraining Aerosol Species, Particle-size Distributions, Temperature, and Metallicity for Cloudy Exoplanets

The James Webb Space Telescope (JWST) will provide moderate-resolution transit spectra with continuous wavelength coverage from the optical to the mid-infrared for the first time. In this paper, we illustrate how different aerosol species, size distributions, and spatial distributions encode information in the JWST transit spectra of warm exoplanets. We use the transit spectral modeling code METIS, along with Mie theory and several flexible treatments of aerosol size and spatial distributions to perform parameter sensitivity studies, calculate transit contribution functions, compute Jacobians, and retrieve parameters from simulated data. The broader wavelength coverage of the JWST can encompass enough non-gray aerosol behavior to recover information about the species and size distribution of particles under many feasible aerosol scenarios. Within the JWST wavelength range, the optical and mid-infrared typically provide information about 0.1–1 μm sized aerosols, while the near-infrared to mid-infrared wavelengths usually provide information about gaseous absorption. Strong gaseous absorption features in the infrared can remain visible, even when clouds and hazes are flattening the optical and near-infrared portion of the spectrum that is currently observable. For some combinations of aerosol properties, temperature, and surface gravity, one can make a precise measure of metallicity despite the presence of aerosols, but more often the retrieved metallicity of a cloudy or hazy atmosphere has significantly lower precision than for a clear atmosphere with otherwise similar properties. Future efforts to securely link aerosol properties to atmospheric metallicity and temperature in a physically motivated manner will ultimately enable a robust physical understanding of the processes at play in cloudy, hazy exoplanet atmospheres.
A mean-field approach to self-interacting networks, convergence and regularity

The propagation of chaos property for a system of interacting particles, describing the spatial evolution of a network of interacting filaments is studied. The creation of a network of mycelium is analyzed as representative case, and the generality of the modeling choices are discussed. Convergence of the empirical density for the particle system to its mean-field limit is proved, and a result of regularity for the solution is presented.
Herbicide-induced Chromosomal Aberrations and Inheritance of a Digenic Seedling Mutation in Sorghum

It is now widely known that herbicides are capable of inducing genetic effects on plants. Many studies have demonstrated the mutagenic action of herbicidal solutions on seeds, seedlings and growing plants and more work will likely be done on the problem as new herbicidal preparations are available. It is ironical that although herbicides are used in the modern technology of crop production, they are sources of potentially-hazardous substances in the human environment. This situ ation could be very serious in some tropical region where cropping is year round requiring continuous herbicidal applications. Herbicides have been reported to alter the chromosome number acting as spindle poison, causing stickiness of chromosomes or serving as cross-wall inhi bitors (Bartels and Hilton 1873, Liang et al. 1969) and produce chromosomal brea kage as inhibitors of protein and nucleic acid syntheses or as plain radiomimetic substances (Mann 1981, Kerkenaar 1981). While most workers have found the in duced mutant characters easily transmitted to the progeny (Wuu and Grant 1976, Sunneson and Jones 1960), others (Derscheid et al. 1952) found that some morpholo gical malformations are not readily inherited by the progeny. More studies need to be done on the genetic effects of herbicides to increase our understanding of these problems and to test the mutagenic action of new herbicidal solutions. The objectives of this work were to determine the types and frequencies of chromosomal aberrations and chlorophyll-deficiency seedling mutations induced by "Machete" herbicide and to study the inheritance of the viable types of such seedl ing mutations.
The Energetics of Launching the Most Powerful Jets in Quasars: A Study of 3C 82

3C 82 at a redshift of 2.87 is the most distant 3C (Third Cambridge Catalogue) quasar. Thus, it is a strong candidate to have the most-luminous radio lobes in the universe. 3C 82 belongs to the class of compact steep-spectrum radio sources. We use single-dish and interferometric radio observations in order to model the plasma state of these powerful radio lobes. It is estimated that the long-term time-averaged jet power required to fill these lobes with leptonic plasma is , among the largest time-averaged jet powers from a quasar. Positing protonic lobes is not tenable as they would require two orders of magnitude more mass transport to the lobes than was accreted to the central black hole during their formation. The first high signal-to-noise optical spectroscopic observation obtained of this object indicates that there is a powerful high-ionization broad-line wind with a kinetic power of ∼1045 erg s−1 and a velocity of ∼0.01c. We also estimate from the broad lines in 2018 and the UV continuum in three epochs spread out over three decades that the accretion flow bolometric luminosity is Lbol ≈ 3.2–5.8 × 1046 erg s−1. The ratio of is perhaps the largest of any known quasar. Extremely powerful jets tend to strongly suppress powerful winds of ionized baryonic matter. Consequently, 3C 82 provides a unique laboratory for studying the dynamical limits of the central engine of outflow initiation in quasars.
Duality and Approximation of Stochastic Optimal Control Problems under Expectation Constraints

We consider a continuous time stochastic optimal control problem under both equality and inequality constraints on the expectation of some functionals of the controlled process. Under a qualification condition, we show that the problem is in duality with an optimization problem involving the Lagrange multiplier associated with the constraints. Then by convex analysis techniques, we provide a general existence result and some a priori estimation of the dual optimizers. We further provide a necessary and sufficient optimality condition for the initial constrained control problem. The same results are also obtained for a discrete time constrained control problem. Moreover, under additional regularity conditions, it is proved that the discrete time control problem converges to the continuous time problem, possibly with a convergence rate. This convergence result can be used to obtain numerical algorithms to approximate the continuous time control problem, which we illustrate by two simple numerical examples.
Quality evaluation of canned cauliflower pickles prepared with different ingredients

The aim of this research was to evaluate sensory quality of canned cauliflower pickles having different ingredients in their brines and the losses occurred in nutritive value especially in total phenolics and antioxidant activity due to processing. For this purpose, cauliflower florets were blanched in water containing NaCl (0.1%), Ca-ascorbate (0.25%), citric acid (0.1%), ascorbic acid (0.5%) and sodium metabisulphite (160 ppm) for inhibiting enzymatic browning. Six different brines consisting of, salt (4%), Ca-ascorbate (0.25%), acetic acid, (1%) lactic acid (1%), citric acid (1%) and their combinations with L-c cysteine (0.25%) were used. The samples were pasteurized at 98°C for 30 min. Head space, net and drained weight, colour (L*, a*, b*), total dry matter, total acidity, salt, SO2, total phenolics and antioxidant activity analysis were done. Blanching and pasteurization significantly reduced the total phenolic compounds levels by 7.12 - 14.78 %. The lowest and the highest reduction ratio of the antioxidant activity were determined in the sample including citric acid and the control sample as 2.90 and 72.79% respectively. Although L - cysteine affected visual appearance and colour positively, it affected taste and odour negatively. While acetic and citric acid containing samples were preferred for odour, acetic and lactic acid containing samples were preferred for taste criteria. Also lactic acid containing sample was preferred for hardness (p < 0.05).