Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining the 56Ni distribution of type Ia supernovae from observations within days of explosion

Recent studies have shown how the distribution of 56Ni within the ejected material of type Ia supernovae can have profound consequences on the observed light curves. Observations at early times can therefore provide important details on the explosion physics in thermonuclear supernovae, which are poorly constrained. To this end, we present a series of radiative transfer calculations that explore variations in the 56Ni distribution. Our models also show the importance of the density profile in shaping the light curve, which is often neglected in the literature. Using our model set, we investigate the observations that are necessary to determine the 56Ni distribution as robustly as possible within the current model set. We find that this includes observations beginning at least ∼14 days before B-band maximum, extending to approximately maximum light with a relatively high (≲3 day) cadence, and in at least one blue and one red band (such as B and R, or g and r) are required. We compare a number of well-observed type Ia supernovae that meet these criteria to our models and find that the light curves of ∼70–80% of objects in our sample are consistent with being produced solely by variations in the 56Ni distributions. The remaining supernovae show an excess of flux at early times, indicating missing physics that is not accounted for within our model set, such as an interaction or the presence of short-lived radioactive isotopes. Comparing our model light curves and spectra to observations and delayed detonation models demonstrates that while a somewhat extended 56Ni distribution is necessary to reproduce the observed light curve shape, this does not negatively affect the spectra at maximum light. Investigating current explosion models shows that observations typically require a shallower decrease in the 56Ni mass towards the outer ejecta than is produced for models of a given 56Ni mass. Future models that test differences in the explosion physics and detonation criteria should be explored to determine the conditions necessary to reproduce the 56Ni distributions found here.
Signal Design for AF Relay Systems Using Superposition Coding and Finite-Alphabet Inputs

This paper focuses on the signal design in a Gaussian amplify-and-forward (AF) relay system with superposition coding (SC) being applied at the relay, which allows the source and relay to transmit their own information within two time slots. Practical quadrature amplitude modulation (QAM) constellations are adopted at the source and relay. To improve the system error performance, we optimize the weight coefficients adopted at the source and relay to maximize the minimum Euclidean distance of the received composite constellation, subject to their individual average power constraints. The formulated optimization problem is shown to be a mixed continuous-discrete one that is non-trivial to resolve in general. By resorting to the punched Farey sequence, we manage to obtain the optimal solution to the formulated problem by first partitioning the entire feasible region into a finite number of sub-intervals and then taking the maximum over all the possible sub intervals. Simulation results are provided to demonstrate the superior performance of our proposed design based on SC over that using conventional time division multiple access (TDMA).
Multi-focus Image Fusion Based on Similarity Characteristics

A novel multi-focus image fusion algorithm performed in spatial domain based on similarity characteristics is proposed incorporating with region segmentation. In this paper, a new similarity measure is developed based on the structural similarity (SSIM) index, which is more suitable for multi-focus image segmentation. Firstly, the SSNSIM map is calculated between two input images. Then we segment the SSNSIM map using watershed method, and merge the small homogeneous regions with fuzzy c-means clustering algorithm (FCM). For three source images, a joint region segmentation method based on segmentation of two images is used to obtain the final segmentation result. Finally, the corresponding segmented regions of the source images are fused according to their average gradient. The performance of the image fusion method is evaluated by several criteria including spatial frequency, average gradient, entropy, edge retention etc. The evaluation results indicate that the proposed method is effective and has good visual perception.
Analyzing Privacy Loss in Updates of Natural Language Models

To continuously improve quality and reflect changes in data, machine learning-based services have to regularly re-train and update their core models. In the setting of language models, we show that a comparative analysis of model snapshots before and after an update can reveal a surprising amount of detailed information about the changes in the data used for training before and after the update. We discuss the privacy implications of our findings, propose mitigation strategies and evaluate their effect.
Te-REX: a sample of extragalactic TeV-emitting candidates

The REX (Radio-Emitting X-ray sources) is a catalogue produced by cross-matching X-ray data from the ROSAT-PSPC archive of pointed observations and radio data from the NRAO VLA Sky Survey, aimed at the selection of blazars. From the REX catalogue, we select a well-defined and statistically complete sample of high-energy peaked BL Lac (HBL). HBL are expected to be the most numerous class of extragalactic TeV-emitting sources. Specifically, we have considered only the REX sources in the currently planned CTA extragalactic survey area satisfying specific criteria and with an optical spectroscopic confirmation. We obtain 46 HBL candidates that we called Te-REX (TeV-emitting REX). We estimate the very high-energy gamma-ray emission, in the TeV domain, using an empirical approach i.e. using specific statistical relations between gamma-rays (at GeV energies) and radio/X-rays properties observed in bright HBL from the literature. We compare the spectral energy distributions (SEDs) with the sensitivities of current and upcoming Cherenkov telescopes and we predict that 14 Te-REX could be detectable with 50 h of observations of CTA and 7 of them also with current Cherenkov facilities in 50 h. By extrapolating these numbers on the total extragalactic sky, we predict that about 800 HBL could be visible in pointed CTA observations and ∼400 with current Cherenkov telescopes in 50 h. Interestingly, our predictions show that a non-negligible fraction (∼30 per cent) of the HBL that will be detectable by CTA is composed of relatively weak objects whose optical nuclear emission is swamped by the host-galaxy light and not (yet) detected by Fermi-LAT.
Unintentional Childhood Injuries: A Cause for Concern.

Unintentional childhood injuries are common cause of mortality and morbidity among children in both developing and developed countries. The financial implications are also high for any country. The need of the hour to tackle this global menace is prevention. This paper explores some of the remedial interventions that needs to be undertaken to safeguard the rights of the child
Jointly Trained Image and Video Generation using Residual Vectors

In this work, we propose a modeling technique for jointly training image and video generation models by simultaneously learning to map latent variables with a fixed prior onto real images and interpolate over images to generate videos. The proposed approach models the variations in representations using residual vectors encoding the change at each time step over a summary vector for the entire video. We utilize the technique to jointly train an image generation model with a fixed prior along with a video generation model lacking constraints such as disentanglement. The joint training enables the image generator to exploit temporal information while the video generation model learns to flexibly share information across frames. Moreover, experimental results verify our approach’s compatibility with pre-training on videos or images and training on datasets containing a mixture of both. A comprehensive set of quantitative and qualitative evaluations reveal the improvements in sample quality and diversity over both video generation and image generation baselines. We further demonstrate the technique’s capabilities of exploiting similarity in features across frames by applying it to a model based on decomposing the video into motion and content. The proposed model allows minor variations in content across frames while maintaining the temporal dependence through latent vectors encoding the pose or motion features.
Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering

Based on further studying the low-rank subspace clustering (LRSC) and L2-graph subspace clustering algorithms, we propose a F-graph subspace clustering algorithm with a symmetric constraint (FSSC), which constructs a new objective function with a symmetric constraint basing on F-norm, whose the most significant advantage is to obtain a closed-form solution of the coefficient matrix. Then, take the absolute value of each element of the coefficient matrix, and retain the k largest coefficients per column, set the other elements to 0, to get a new coefficient matrix. Finally, FSSC performs spectral clustering over the new coefficient matrix. The experimental results on face clustering and motion segmentation show FSSC algorithm can not only obviously reduce the running time, but also achieve higher accuracy compared with the state-of-the-art representation-based subspace clustering algorithms, which verifies that the FSSC algorithm is efficacious and feasible.
WM-INS: A Wheel Mounted IMU Based Integrated Navigation System for Wheeled Robots

Microelectromechanical systems (MEMS) based inertial navigation systems (INS) are widely used for robot navigation as they are self-contained and low-cost for motion perception. Various methods have been utilized to restrict the error growth caused by the inherent inertial sensor noises. Inspired by the rotation-modulation INS that using intentional rotation to mitigate the drift errors, we propose an integrated navigation solution for mobile robots based on a single wheel mounted MEMS IMU. The IMU is leveraged to produce odometry measurements with wheel radius and estimate the wheel motion. Zero-type constraints and the vehicle motion constraints are also introduced to limit the navigation errors. Field experiments prove that the rotation scheme can effectively reduce the heading error. The horizontal position accuracy of the proposed system is two times better than the conventional odometry aided INS for large-scale polyline trajectory tests. The cancellation effect of the track on navigation errors drift is also illustrated.
Estimating a Behavioral New Keynesian Model

This paper analyzes identification issues of a behavorial New Keynesian model and estimates it using likelihood-based and limited-information methods with identification-robust confidence sets. The model presents some of the same difficulties that exist in simple benchmark DSGE models, but the analytical solution is able to indicate in what conditions the cognitive discounting parameter (attention to the future) can be identified and the robust estimation methods is able to confirm its importance for explaining the proposed behavioral model.
Dim the Lights! - Low-Rank Prior Temporal Data for Specular-Free Video Recovery

The appearance of an object is significantly affected by the illumination conditions in the environment. This is more evident with strong reflective objects as they suffer from more dominant specular reflections, causing information loss and discontinuity in the image domain. In this paper, we present a novel framework for specular-free video recovery with special emphasis on dealing with complex motions coming from objects or camera. Our solution is a twostep approach that allows for both detection and restoration of the damaged regions on video data. We first propose a spatially adaptive detection term that searches for the damage areas. We then introduce a variational solution for specular-free video recovery that allows exploiting spatio-temporal correlations by representing prior data in a low-rank form. We demonstrate that our solution prevents major drawbacks of existing approaches while improving the performance in both detection accuracy and inpainting quality. Finally, we show that our approach can be applied to other problems such as object removal.
Learning patient‐specific parameters for a diffuse interface glioblastoma model from neuroimaging data

Parameters in mathematical models for glioblastoma multiforme (GBM) tumour growth are highly patient specific. Here, we aim to estimate parameters in a Cahn–Hilliard type diffuse interface model in an optimised way using model order reduction (MOR) based on proper orthogonal decomposition (POD). Based on snapshots derived from finite element simulations for the full‐order model (FOM), we use POD for dimension reduction and solve the parameter estimation for the reduced‐order model (ROM). Neuroimaging data are used to define the highly inhomogeneous diffusion tensors as well as to define a target functional in a patient‐specific manner. The ROM heavily relies on the discrete empirical interpolation method, which has to be appropriately adapted in order to deal with the highly nonlinear and degenerate parabolic partial differential equations. A feature of the approach is that we iterate between full order solvers with new parameters to compute a POD basis function and sensitivity‐based parameter estimation for the ROM problems. The algorithm is applied using neuroimaging data for two clinical test cases, and we can demonstrate that the reduced‐order approach drastically decreases the computational effort.
Securing Big Data systems, A cybersecurity management discussion

This paper explores the essential areas of cybersecurity management for big data systems. Big data platform stems its complexity from being a collection of interrelated non-standardized systems that interact with each other to process large data-sets. This complexity increases the chances of overlooking critical cybersecurity management practices. The paper discusses various security management for each part of big data systems. This includes security measures, standards, and methodologies. The primary objective is to highlight the essential segments of security management that are expected to be implemented flawlessly in big data systems.
Game Theory based Joint Task Offloading and Resources Allocation Algorithm for Mobile Edge Computing

Mobile edge computing (MEC) has emerged for reducing energy consumption and latency by allowing mobile users to offload computationally intensive tasks to the MEC server. Due to the spectrum reuse in small cell network, the inter-cell interference has a great effect on MEC performances. In this paper, for reducing the energy consumption and latency of MEC, we propose a game theory based approach to join task offloading decision and resources allocation together in the MEC system. In this algorithm, the offloading decision, the CPU capacity adjustment, the transmission power control, and the network interference management of mobile users are regarded as a game. In this game, based on the best response strategy, each mobile user makes their own utility maximum rather than the utility of the whole system. We prove that this game is an exact potential game and the Nash equilibrium (NE) of this game exists. For reaching the NE, the best response approach is applied. We calculate the best response of these three variables. Moreover, we investigate the properties of this algorithm, including the convergence, the computational complexity, and the Price of anarchy (PoA). The theoretical analysis shows that the inter-cell interference affects on the performances of MEC greatly. The NE of this game is Pareto efficiency. Finally, we evaluate the performances of this algorithm by simulation. The simulation results illustrate that this algorithm is effective in improving the performances of the multi-user MEC system.
Baryon-Interacting Dark Matter: heating dark matter and the emergence of galaxy scaling relations

The empirical scaling relations observed in disk galaxies remain challenging for models of galaxy formation. The most striking among these is the Mass Discrepancy-Acceleration Relation (MDAR), which encodes both a tight baryonic Tully-Fisher relation (BTFR) and the observed diversity of galaxy rotation curves through the central surface density relation (CSDR) . Building on our earlier work [1], we propose here that the MDAR is the result of interactions between baryons and `Baryon-Interacting Dark Matter' (BIDM), which heat up the dark matter. Following a bottom-up, hydrodynamical approach, we find that the MDAR follows if: i) the BIDM equation of state approximates that of an ideal gas; ii) the BIDM relaxation time is order the Jeans time; iii) the heating rate is inversely proportional to the BIDM density. Remarkably, under these assumptions the set of hydrodynamical equations together with Poisson's equation enjoy an anisotropic scaling symmetry. In the BIDM-dominated regime, this gives rise to an enhanced symmetry which fully captures the low-acceleration limit of the MDAR . We then show that, assuming a cored pseudo-isothermal profile at equilibrium, this set of equations gives rise to parameters reproducing the MDAR . Specifically, in the flat part of the rotation curve the asymptotic rotational velocity matches the parametric dependence of the BTFR . Moreover, in the central region of high-surface brightness galaxies, the profile reproduces the CSDR . Finally, by studying the time-dependent approach to equilibrium, we derive a global combination of the BTFR and CSDR, which matches the expectations in low surface-brightness galaxies. The form of the heating rate also makes model-independent predictions for various cosmological observables. We argue that our scenario satisfies existing observational constraints, and, intriguingly, offers a possible explanation to the EDGES anomaly.
Body mass and territorial defence strategy affect the territory size of odonate species

The territory is a distinct mating place that a male defends against intruding conspecific males. The size of a territory varies between species and most of the variation between species has been found to scale allometrically with body mass. The variation that could not be explained by body mass has been explained with several variables such as habitat productivity, trophic level, locomotion strategy and thermoregulation. All previous interspecific comparative studies have been done on vertebrate species such as birds, mammals, reptiles and fishes, meaning that studies using invertebrate species are missing. Here, we studied the relationship of a species's territory size with its fresh body mass (FBM) in addition to other ecologically relevant traits using 86 damselfly and dragonfly (Odonata) species. We found that territory size is strongly affected by species FBM, following an allometric relationship similar to vertebrates. We also found that the territory size of a species was affected by its territorial defence strategy, constantly flying species having larger territories than species that mostly perch. Breeding habitat or the presence of sexual characters did not affect territory sizes, but lotic species and species without wing spots had steeper allometric slopes. It seems that an increase in a species’s body mass increases its territory size and may force the species to shift its territory defence strategy from a percher to a flier.
Bite marks and predation of fossil jawless fish during the rise of jawed vertebrates

Although modern vertebrate diversity is dominated by jawed vertebrates, early vertebrate assemblages were predominantly composed of jawless fishes. Hypotheses for this faunal shift and the Devonian decline of jawless vertebrates include predation and competitive replacement. The nature and prevalence of ecological interactions between jawed and jawless vertebrates are highly relevant to both hypotheses, but direct evidence is limited. Here, we use the occurrence and distribution of bite mark type traces in fossil jawless armoured heterostracans to infer predation interactions. A total of 41 predated specimens are recorded; their prevalence increases through time, reaching a maximum towards the end of the Devonian. The bite mark type traces significantly co-occur with jawed vertebrates, and their distribution through time is correlated with jawed vertebrate diversity patterns, particularly placoderms and sarcopterygians. Environmental and ecological turnover in the Devonian, especially relating to the nekton revolution, have been inferred as causes of the faunal shift from jawless to jawed vertebrates. Here, we provide direct evidence of escalating predation from jawed vertebrates as a potential contributing factor to the demise and extinction of ostracoderms.
Transcriptomic analysis and novel insights into lens fibre cell differentiation regulated by Gata3

Gata3 is a DNA-binding transcription factor involved in cellular differentiation in a variety of tissues including inner ear, hair follicle, kidney, mammary gland and T-cells. In a previous study in 2009, Maeda et al. (Dev. Dyn. 238, 2280–2291; doi:10.1002/dvdy.22035) found that Gata3 mutants could be rescued from midgestational lethality by the expression of a Gata3 transgene in sympathoadrenal neuroendocrine cells. The rescued embryos clearly showed multiple defects in lens fibre cell differentiation. To determine whether these defects were truly due to the loss of Gata3 expression in the lens, we generated a lens-specific Gata3 loss-of-function model. Analogous to the previous findings, our Gata3 null embryos showed abnormal regulation of cell cycle exit during lens fibre cell differentiation, marked by reduction in the expression of the cyclin-dependent kinase inhibitors Cdkn1b/p27 and Cdkn1c/p57, and the retention of nuclei accompanied by downregulation of Dnase IIβ. Comparisons of transcriptomes between control and mutated lenses by RNA-Seq revealed dysregulation of lens-specific crystallin genes and intermediate filament protein Bfsp2. Both Cdkn1b/p27 and Cdkn1c/p57 loci are occupied in vivo by Gata3, as well as Prox1 and c-Jun, in lens chromatin. Collectively, our studies suggest that Gata3 regulates lens differentiation through the direct regulation of the Cdkn1b/p27and Cdkn1c/p57 expression, and the direct/or indirect transcriptional control of Bfsp2 and Dnase IIβ.