Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Results from GLASS-JWST. V: The First Rest-frame Optical Size–Luminosity Relation of Galaxies at z > 7

We present the first rest-frame optical size–luminosity relation of galaxies at z > 7, using the NIRCam imaging data obtained by the GLASS James Webb Space Telescope Early Release Science (GLASS-JWST-ERS) program, providing the deepest extragalactic data of the ERS campaign. Our sample consists of 19 photometrically selected bright galaxies with m F444W ≤ 27.8 at 7 < z < 9 and m F444W < 28.2 at z ∼ 9−15. We measure the size of the galaxies in five bands, from rest-frame optical (∼4800 Å) to the UV (∼1600 Å) based on the Sérsic model, and analyse the size–luminosity relation as a function of wavelength. Remarkably, the data quality of the NIRCam imaging is sufficient to probe the half-light radius r e down to ∼100 pc at z > 7. Given the limited sample size and magnitude range, we first fix the slope to that observed for larger samples in rest-frame UV using Hubble Space Telescope samples. The median size r 0 at the reference luminosity M = −21 decreases slightly from rest-frame optical (600 ± 80 pc) to UV (450 ± 130 pc). We then refit the size–luminosity relation allowing the slope to vary. The slope is consistent with β ∼ 0.2 for all bands except F150W, where we find a marginally steeper slope of β = 0.53 ± 0.15. The steep UV slope is mainly driven by the smallest and faintest galaxies. If confirmed by larger samples, it implies that the UV size–luminosity relation breaks toward the faint end, as suggested by lensing studies.
Causal foundations of bias, disparity and fairness

The study of biases, such as gender or racial biases, is an important topic in the social and behavioural sciences. However, the literature does not always clearly define the concept. Definitions of bias are often ambiguous or not provided at all. To study biases in a precise manner, it is important to have a well-defined concept of bias. We propose to define bias as a direct causal effect that is unjustified. We propose to define the closely related concept of disparity as a direct or indirect causal effect that includes a bias. Our proposed definitions can be used to study biases and disparities in a more rigorous and systematic way. We compare our definitions of bias and disparity with various criteria of fairness introduced in the artificial intelligence literature. We also illustrate our definitions in two case studies, focusing on gender bias in science and racial bias in police shootings. Our proposed definitions aim to contribute to a better appreciation of the causal intricacies of studies of biases and disparities. We hope that this will also promote an improved understanding of the policy implications of such studies.
BEADS ON THE TORUS I: CONTINUOUS KASTELEYN THEORY

Consider the semi-discrete torus T n := [0 , 1) × { 0 , 1 , . , n − 1 } representing n unit length strings running in parallel. A bead configuration is a point process on T n with the property that between every two consecutive points on same string, there lies a point on each of the neighbouring strings. In this paper we develop a continuous version of Kasteleyn theory to show that partition functions for bead configurationson T n may be expressed in terms of Fredholm determinants of certain operators on T n . We obtain an explicit formula for the volume of bead configurations with n strings and k beads per string, whose asymptotics confirm a recent prediction of Shlyakhtenko and Tao [(2020) arXiv:2009.01882] in the free probability literature. Thereafter we study probabilistic aspects of bead configurations, expanding on the works of Boutillier [(2009) Ann. Probab. 37 (1), 107-142] and Gordenko [(2020) arXiv:2009.10480], and making connections with exclusion processes and providing a new probabilistic representation of TASEP on the ring.
Improved heat and particle flux mitigation in high core confinement, baffled, alternative divertor configurations in the TCV tokamak

Nitrogen seeded detachment has been achieved in the tokamak a configuration variable (TCV) in alternative divertor configurations (ADCs), namely X-divertor and X-point target, with and without baffles in H-mode plasmas with high core confinement. Both ADCs show a remarkable reduction in the inter-ELM particle and heat fluxes to the target compared to the standard divertor configuration. 95%–98% of the inter-ELM peak heat flux to the target is mitigated as a synergetic effect of ADCs, baffling, and nitrogen seeded detachment. The effect of divertor geometry and baffles on core-divertor compatibility is investigated in detail. The power balance in these experiments is also investigated to explore the physics behind the observed reduction in heat fluxes in the ADCs.
Resonant behavior of the $pp \to \{pp\}_s \pi^0$ reaction at the energy $\sqrt{s}$ = 2.65 GeV

We report on measurements of the diﬀerential cross section dσ/d Ω in the energy region of √ s = 2 . 5–2 . 9 GeV of the reaction pp → { pp } s π 0 where { pp } s is a 1 S 0 proton pair. The experiment has been performed with the ANKE spectrometer at COSY-J¨ulich. The data reveal a peak in the energy dependence of the forward { pp } s diﬀerential cross section at the energy √ s = 2 . 65 GeV with the width Γ = 0 . 26 GeV, and also the cross section slope changes its sign in the region of the observed peak. This is an indication for the excitation of a new D (2650) resonant state, that may be a dibaryon resonance system consisting of two excited baryons ∆(1232) and N ∗ (1440).
iCub Being Social: Exploiting Social Cues for Interactive Object Detection Learning

—Performing joint interaction requires constant mutual monitoring of own actions and their effects on the other’s behaviour. Such an action-effect monitoring is boosted by social cues and might result in an increasing sense of agency. Joint actions and joint attention are strictly correlated and both of them contribute to the formation of a precise temporal coordination. In human-robot interaction, the robot’s ability to establish joint attention with a human partner and exploit various social cues to react accordingly is a crucial step in creating communicative robots. Along the social component, an effective human-robot interaction can be seen as a new method to improve and make the robot’s learning process more natural and robust for a given task. In this work we use different social skills, such as mutual gaze, gaze following, speech and human face recognition, to develop an effective teacher-learner scenario tailored to visual object learning in dynamic environments. Experiments on the iCub robot demonstrate that the system allows the robot to learn new objects through a natural interaction with a human teacher in presence of distractors.
Dark Matter Admixed Neutron Star Properties in the Light of X-Ray Pulse Profile Observations

The distribution of the dark matter (DM) in DM-admixed neutron stars (DANSs) is supposed to result in either a dense dark core or an extended dark halo, subject to the DM fraction of the DANS (f χ ) and the DM properties, such as the mass (m χ ) and the strength of the self-interaction (y). In this paper, we perform an in-depth analysis of the formation criterion for dark cores/dark halos, and point out that the relative distribution of these two components is essentially determined by the ratio of the central enthalpy of the DM component to that of the baryonic matter component inside the DANSs. For the critical case where the radii of the DM and the baryonic matter are the same, we further derive an analytical formula to describe the dependence of fχcrit on m χ and y for a given DANS mass. The relative distribution of the two components in DANSs can lead to different observational effects. We here focus on the modification of the pulsar pulse profile, due to the extra light-bending effect in the case of a dark halo existence, and conduct the first investigation into the dark halo effects on the pulse profile. We find that the peak flux deviation is strongly dependent on the ratio of the halo mass to the radius of the DM component. Last, we perform Bayesian parameter estimation on the DM particle properties, based on the recent X-ray observations of PSR J0030+0451 and PSR J0740+6620 by the Neutron Star Interior Composition Explorer.
Multi-layer Representation Learning for Robust OOD Image Classification

Convolutional Neural Networks have become the norm in image classification. Nevertheless, their difficulty to maintain high accuracy across datasets has become apparent in the past few years. In order to utilize such models in real-world scenarios and applications, they must be able to provide trustworthy predictions on unseen data. In this paper, we argue that extracting features from a CNN’s intermediate layers can assist in the model’s final prediction. Specifically, we adapt the Hypercolumns method to a ResNet-18 and find a significant increase in the model’s accuracy, when evaluating on the NICO dataset.
Instabilities in field theories: Lecture notes with a view into modified gravity

Modified theories of gravity usually present new degrees of freedom, as well as higher order derivatives, wrong signs in certain terms and complicated couplings already present in the Lagrangian from the beginning or originated by the field redefinitions needed to reach an Einstein frame. As a consequence, they are very prone to present dynamical instabilities that could spoil any attempt to construct viable models within these frameworks. In these three lectures we introduce the most common types of instabilities that appear in field theory as well as some techniques to detect them, and supplement these contents with several examples. The goal is to understand the implications of having such pathological behaviors and the application of these notions to modified theories of gravity. This text is an extended and polished version of the lectures prepared for the course ‘Selected Topics in the Theories of Gravity’, given at the Institute of Physics (University of Tartu, Estonia) in spring 2022. Recordings of such course can be found in https://button.ut. ee/b/lau-a4e-8eb-es1. The last lecture contains part of the results in [1–4]. ar X iv :2 20 7. 13 43 1v 1 [ gr -q c] 2 7 Ju l 2 02 2
Words, thoughts, and theories

The other Socratic method: Socrates's problem Augustine's problem a road map. Part 1 The theory theory: the scientist as child - but surely it can't really be a theory? a cognitive view of science, naturalistic epistemology and development - an evolutionary speculation, science as horticulture, objections - sociology, objections - timing and convergence, objections - magic, empirical advances, what is theory? structural features of theories, functional features of theories, dynamic features of theories, theories in childhood, theories as representations theories, modules, and empirical generalizations - modules, theories and development, modules and development, modularity in peripheral and central processing, empirical generalization - scripts, narratives, and nets, interactions among theories, modules, and empirical generalizations, nonconceptual development - information processing and social construction. Part 2 Evidence for the theory theory: the child's theory of appearances - the adult theory, the initial theory, the paradox of invisible objects, an alternative - a theory-change account, the nine-month-old's theory, the A-not-B error as an auxiliary hypothesis, the 18-month-old's theory, other evidence for the theory theory, semantic developments - from objects permanence to perspective taking, later semantic developments - "gone" and "see", conclusion the child's theory of action - the adult theory, the initial theory, the nine-month-old's theory, the 18-month-old's theory, other evidence for the theory theory, semantic development - "no", "uh-oh" and "there", later developments - from actions to desires, later semantic developments - "want", conclusion the child's theory of kinds - the adult theory, categories and kinds, the initial theory, the nine-month-old's theory, the 18-month-old's theory , other evidence for the theory theory, semantic development - the naming Spurt, later developments, conclusion. Part 3 Theories and language: language and thought - prerequisites, interactions, a theory-theory view, methodological issues - specificity and correlation, developmental relations between language and cognition, theories and constraints, crosslinguistic studies, individual-difference studies, conclusion the Darwinian conclusion - who's afraid of semantic holism? a developmental cognitive science, computational and neurological mechanisms, after Piaget, sailing in Neurath's boat.
Dust grain size evolution in local galaxies: a comparison between observations and simulations

The evolution of the dust grain size distribution has been studied in recent years with great detail in cosmological hydrodynamical simulations taking into account all the channels under which dust evolves in the interstellar medium. We present a systematic analysis of the observed spectral energy distribution of a large sample of galaxies in the local Universe in order to derive not only the total dust masses but also the relative mass fraction between small and large dust grains (DS/DL). Simulations reproduce fairly well the observations except for the high-stellar mass regime where dust masses tend to be overestimated. We find that ∼45 per cent of galaxies exhibit DS/DL consistent with the expectations of simulations, while there is a subsample of massive galaxies presenting high DS/DL (log (DS/DL) ∼ −0.5), and deviating from the prediction in simulations. For these galaxies which also have high-molecular gas mass fractions and metallicities, coagulation is not an important mechanism affecting the dust evolution. Including diffusion, transporting large grains from dense regions to a more diffuse medium where they can be easily shattered, would explain the observed high DS/DL values in these galaxies. With this study, we reinforce the use of the small-to-large grain mass ratio to study the relative importance of the different mechanisms in the dust life cycle. Multiphase hydrodynamical simulations with detailed feedback prescriptions and more realistic subgrid models for the dense phase could help to reproduce the evolution of the dust grain size distribution traced by observations.
Early Estimates of Monkeypox Incubation Period, Generation Time, and Reproduction Number, Italy, May–June 2022

We analyzed the first 255 PCR-confirmed cases of monkeypox in Italy in 2022. Preliminary estimates indicate mean incubation period of 9.1 (95% CI 6.5–10.9) days, mean generation time of 12.5 (95% CI 7.5–17.3) days, and reproduction number among men who have sex with men of 2.43 (95% CI 1.82–3.26).
Unsupervised Contrastive Learning of Image Representations from Ultrasound Videos with Hard Negative Mining

Rich temporal information and variations in viewpoints make video data an attractive choice for learning image representations using unsupervised contrastive learning (UCL) techniques. State-of-the-art (SOTA) contrastive learning techniques consider frames within a video as positives in the embedding space, whereas the frames from other videos are considered negatives. We observe that unlike multiple views of an object in natural scene videos, an Ultrasound (US) video captures different 2D slices of an organ. Hence, there is almost no similarity between the temporally distant frames of even the same US video. In this paper we propose to instead utilize such frames as hard negatives. We advocate mining both intra-video and cross-video negatives in a hardness-sensitive negative mining curriculum in a UCL framework to learn rich image representations. We deploy our framework to learn the representations of Gallbladder (GB) malignancy from US videos. We also construct the first large-scale US video dataset containing 64 videos and 15,800 frames for learning GB representations. We show that the standard ResNet50 backbone trained with our framework improves the accuracy of models pretrained with SOTA UCL techniques as well as supervised pretrained models on ImageNet for the GB malignancy detection task by 2-6%. We further validate the generalizability of our method on a publicly available lung US image dataset of COVID-19 pathologies and show an improvement of 1.5% compared to SOTA. Source code, dataset, and models are available at https://gbc-iitd.github. io/usucl.
Point-McBert: A Multi-choice Self-supervised Framework for Point Cloud Pre-training

Masked language modeling (MLM) has become one of the most successful self-supervised pre-training task. Inspired by its success, Point-Bert, as a pioneer work in point cloud, proposed masked point modeling (MPM) to pre-train point transformer on large scale unanotated dataset. Despite its great performance, we ﬁnd inherent difference between language and point cloud tends to cause ambiguous tokenization for point cloud. For point cloud, there doesn’t exist a gold standard for point cloud tokenization. Although Point-Bert introduce a discrete Variational AutoEncoder (dVAE) as tokenizer to allocate token ids to local patches, it tends to generate ambigious token ids for local patches. We ﬁnd this imperfect tokenizer might generate different token ids for semantically-similar patches and same token ids for semantically-dissimilar patches. To tackle above problem, we propose our Point-McBert, a pre-training framework with eased and reﬁned supervision signals. Speciﬁcally, we ease the previous single-choice constraint on patches, and provide multi-choice token ids for each patch as supervision. More-over, we utilitze the high-level semantics learned by trans-former to further reﬁne our supervision signals. Extensive experiments on point cloud classiﬁcation, few-shot classiﬁ-cation and part segmentation tasks demonstrate the superiority of our method, e.g., the pre-trained transformer achieves 94.1% accuracy on ModelNet40, 84.28% accuracy on the hardest setting of ScanObjectNN and new state-of-the-art performance on few-shot learning. We also demonstrate that our method not only improves the performance of Point-Bert on
Stability in Bondy's theorem on paths and cycles

In this paper, we study the stability result of a well-known theorem of Bondy. We prove that for any 2-connected non-hamiltonian graph, if every vertex except for at most one vertex has degree at least $k$, then it contains a cycle of length at least $2k+2$ except for some special families of graphs. Our results imply several previous classical theorems including a deep and old result by Voss. We point out our result on stability in Bondy's theorem can directly imply a positive solution (in a slight stronger form) to the following problem: Is there a polynomial time algorithm to decide whether a 2-connected graph $G$ on $n$ vertices has a cycle of length at least $\min\{2\delta(G)+2,n\}$. This problem originally motivates the recent study on algorithmic aspects of Dirac's theorem by Fomin, Golovach, Sagunov and Simonov, although a stronger problem was solved by them by completely different methods. Our theorem can also help us to determine all extremal graphs for wheels on odd number of vertices. We also discuss the relationship between our results and some previous problems and theorems in spectral graph theory and generalized Tur\'{a}n problem.
Cryogenic front-end amplifier design for large SiPM arrays in the DUNE FD1-HD photon detection system

The photon detection system of the first far detector (FD1-HD) of the DUNE experiment will detect scintillation photons produced by particle interactions in a kiloton-scale liquid Argon time projection chamber. The photon detectors of choice are silicon photomultipliers (SiPM), 6×6 mm2 each, arranged in groups of 48, which present a significantly low impedance to the front-end electronics. This paper details the design of a cryogenic amplifier with exceptionally low white voltage noise of 0.37 nV√(Hz), based on a silicon-germanium input transistor and a BiCMOS fully differential operational amplifier. It yields excellent single photoelectron resolution even at low overvoltage values. The signal rise time is below 100 ns, and the dynamic range is about 2000 photoelectrons at the typical operating overvoltage. It draws 0.7 mA from a single 3.3 V supply, for a power consumption of 2.4 mW per channel. Simplified models were developed to predict the single photolectron signal shape and the signal to noise ratio, with a good match to measured performance.
Contrastive Masked Autoencoders are Stronger Vision Learners

Masked image modeling (MIM) has achieved promising results on various vision tasks. However, the limited discriminability of learned representation manifests there is still plenty to go for making a stronger vision learner. Towards this goal, we propose Contrastive Masked Autoencoders (CMAE), a new self-supervised pre-training method for learning more comprehensive and capable vision representations. By elaboratively unifying contrastive learning (CL) and masked image model (MIM) through novel designs, CMAE leverages their respective advantages and learns representations with both strong instance discriminability and local perceptibility. Specifically, CMAE consists of two branches where the online branch is an asymmetric encoder-decoder and the momentum branch is a momentum updated encoder. During training, the online encoder reconstructs original images from latent representations of masked images to learn holistic features. The momentum encoder, fed with the full images, enhances the feature discriminability via contrastive learning with its online counterpart. To make CL compatible with MIM, CMAE introduces two new components, i.e., pixel shifting for generating plausible positive views and feature decoder for complementing features of contrastive pairs. Thanks to these novel designs, CMAE effectively improves the representation quality and transfer performance over its MIM counterpart. CMAE achieves the state-of-the-art performance on highly competitive benchmarks of image classification, semantic segmentation and object detection. Notably, CMAE-Base achieves 85.3% top-1 accuracy on ImageNet and 52.5% mIoU on ADE20k, surpassing previous best results by 0.7% and 1.8% respectively.
The proteomic and particle composition of human platelet lysate for cell therapy products

Following health agencies warning, the use of animal origin supplements should be avoided in biological products proposed as therapy in humans. Platelet lysate and several other growth factors sources are alternatives to replace fetal calf serum, the current gold standard in clinical‐grade cell culture. However, the platelet supplement's content lacks data due to different production methods. The principle behind these products relays on the lysis of platelets that release several proteins, some of which are contained in heterogeneous granules and coordinate biological functions. This study aims to analyze the composition and reproducibility of a platelet lysate produced with a standardized method, by describing several batches' protein and particle content using proteomics and dynamic light scattering. Proteomics data revealed a diversified protein content, with some related to essential cellular processes such as proliferation, morphogenesis, differentiation, biosynthesis, adhesion, and metabolism. It also detected proteins responsible for activation and binding of transforming growth factor beta, hepatocyte growth factor, and insulin‐like growth factor. Total protein, biochemical, and growth factors quantitative data showed consistent and reproducible values across batches. Novel data on two major particle populations is presented, with high dispersion level at 231 ± 96 d.nm and at 30 ± 8 d.nm, possibly being an important way of protein trafficking through the cellular microenvironment. This experimental and descriptive analysis aims to support the content definition and quality criteria of a cell supplement for clinical applications.