Miracle-dz/UniFAR-FTUs huggingface dataset:
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication

Communication is compositional if complex signals can be represented as a combination of simpler subparts. In this paper, we theoretically show that inductive biases on both the training framework and the data are needed to develop a compositional communication. Moreover, we prove that compositionality spontaneously arises in the signaling games, where agents communicate over a noisy channel. We experimentally confirm that a range of noise levels, which depends on the model and the data, indeed promotes compositionality. Finally, we provide a comprehensive study of this dependence and report results in terms of recently studied compositionality metrics: topographical similarity, conflict count, and context independence.
Two-body hadronic decay of K+ in the presence of a circularly polarized laser field

In this study, we have investigated the two-body hadronic decay of the charged kaon, , in the presence of a laser field with circular polarization. We have derived, by analytical techniques, the laser-assisted decay width and the branching ratio of the charged kaon decay via the two-body hadronic channel. We have also taken into consideration the impressive results obtained for the laser-assisted charged kaon decay via the leptonic mode in order to understand more clearly the effect of the laser field on the quantities related to the charged kaon decay such as the decay width, the branching ratio and lifetime. A precise comparison of the ratios of hadronic-to-muonic decay in the presence of the laser field is made to show that the hadronic mode becomes slightly more important by increasing the laser field intensity.
Curvature estimates for the continuity method

We obtain curvature estimates for long time solutions of the continuity method on compact K\"ahler manifolds with semi-ample canonical line bundles. In this setting, initiated in arXiv:1410.3157 and arXiv:0709.0990, we adapt arguments from arXiv:1903.05939 for the K\"ahler-Ricci flow to this setup. As an application, we derive curvature bounds for general metrics on product manifolds.
Joint models for cause-of-death mortality in multiple populations

We investigate jointly modelling age–year-specific rates of various causes of death in a multinational setting. We apply multi-output Gaussian processes (MOGPs), a spatial machine learning method, to smooth and extrapolate multiple cause-of-death mortality rates across several countries and both genders. To maintain flexibility and scalability, we investigate MOGPs with Kronecker-structured kernels and latent factors. In particular, we develop a custom multi-level MOGP that leverages the gridded structure of mortality tables to efficiently capture heterogeneity and dependence across different factor inputs. Results are illustrated with datasets from the Human Cause-of-Death Database (HCD). We discuss a case study involving cancer variations in three European nations and a US-based study that considers eight top-level causes and includes comparison to all-cause analysis. Our models provide insights into the commonality of cause-specific mortality trends and demonstrate the opportunities for respective data fusion.
From Pebbles and Planetesimals to Planets and Dust: The Protoplanetary Disk–Debris Disk Connection

The similar orbital distances and detection rates of debris disks and the prominent rings observed in protoplanetary disks suggest a potential connection between these structures. We explore this connection with new calculations that follow the evolution of rings of pebbles and planetesimals as they grow into planets and generate dusty debris. Depending on the initial solid mass and planetesimal formation efficiency, the calculations predict diverse outcomes for the resulting planet masses and accompanying debris signature. When compared with debris disk incidence rates as a function of luminosity and time, the model results indicate that the known population of bright cold debris disks can be explained by rings of solids with the (high) initial masses inferred for protoplanetary disk rings and modest planetesimal formation efficiencies that are consistent with current theories of planetesimal formation. These results support the possibility that large protoplanetary disk rings evolve into the known cold debris disks. The inferred strong evolutionary connection between protoplanetary disks with large rings and mature stars with cold debris disks implies that the remaining majority population of low-mass stars with compact protoplanetary disks leaves behind only modest masses of residual solids at large radii and evolves primarily into mature stars without detectable debris beyond 30 au. The approach outlined here illustrates how combining observations with detailed evolutionary models of solids strongly constrains the global evolution of disk solids and underlying physical parameters such as the efficiency of planetesimal formation and the possible existence of invisible reservoirs of solids in protoplanetary disks.
Recurrent Activity from Active Asteroid (248370) 2005 QN173: A Main-belt Comet

We present archival observations of main-belt asteroid (248370) 2005 QN173 (also designated 433P) that demonstrate this recently discovered active asteroid (a body with a dynamically asteroidal orbit displaying a tail or coma) has had at least one additional apparition of activity near perihelion during a prior orbit. We discovered evidence of this second activity epoch in an image captured 2016 July 22 with the DECam on the 4 m Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile. As of this writing, (248370) 2005 QN173 is just the eighth active asteroid demonstrated to undergo recurrent activity near perihelion. Our analyses demonstrate (248370) 2005 QN173 is likely a member of the active asteroid subset known as main-belt comets, a group of objects that orbit in the main asteroid belt that exhibit activity that is specifically driven by sublimation. We implement an activity detection technique, wedge photometry, that has the potential to detect tails in images of solar system objects and quantify their agreement with computed antisolar and antimotion vectors normally associated with observed tail directions. We present a catalog and an image gallery of archival observations. The object will soon become unobservable as it passes behind the Sun as seen from Earth, and when it again becomes visible (late 2022) it will be farther than 3 au from the Sun. Our findings suggest (248370) 2005 QN173 is most active interior to 2.7 au (0.3 au from perihelion), so we encourage the community to observe and study this special object before 2021 December.
On Effective Secrecy Throughput of Underlay Spectrum Sharing $\alpha -\mu$/ Málaga Hybrid Model Under Interference-and-Transmit Power Constraints

The underlay cognitive radio-based hybrid radio frequency/free-space optical (RF/FSO) systems have emerged as a promising technology due to their ability to eliminate spectrum scarcity and spectrum under-utilization problems. The physical layer security of such a network with a primary user, a secondary source, a secondary receiver, and an eavesdropper is therefore examined in this work. In this network, secret communication occurs between two reliable secondary peers over the RF and FSO links simultaneously, and the eavesdropper can only overhear the RF link. In particular, the maximum transmits power limitation at the secondary user as well as the permissible interference power restriction at the primary user are also taken into consideration. All the RF and FSO links are modeled with $\alpha$-$\mu$ fading and Málaga turbulence with link blockage and pointing error impairments. At the receiver, the selection combining diversity technique is utilized to select the signal with the best electrical signal-to-ratio (SNR). Furthermore, to examine the secrecy performance taking into account the effects of each system parameter, closed-form expressions for the secrecy outage probability and effective secrecy throughput are derived. The resultant expressions are finally verified by Monte-Carlo simulations.
Continuity, Uniqueness and Long-Term Behavior of Nash Flows Over Time

We consider a dynamic model of traffic that has received a lot of attention in the past few years. Users control infinitesimal flow particles aiming to travel from a source to destination as quickly as possible. Flow patterns vary over time, and congestion effects are modeled via queues, which form whenever the inflow into a link exceeds its capacity. Despite lots of interest, some very basic questions remain open in this model. We resolve a number of them: • We show uniqueness of journey times in equilibria. • We show continuity of equilibria: small perturbations to the instance or to the traffic situation at some moment cannot lead to wildly different equilibrium evolutions. • We demonstrate that, assuming constant inflow into the network at the source, equilibria always settle down into a “steady state” in which the behavior extends forever in a linear fashion. One of our main conceptual contributions is to show that the answer to the first two questions, on uniqueness and continuity, are intimately connected to the third. Our result also shows very clearly that resolving uniqueness and continuity, despite initial appearances, cannot be resolved by analytic techniques, but are related to very combinatorial aspects of the model. To resolve the third question, we substantially extend the approach of Cominetti et al. [1], who show a steady-state result in the regime where the input flow rate is smaller than the network capacity. The full version of this extended abstract can be found on the arXiv preprint server as article 2111.06877
Transformer-based Image Compression

A Transformer-based Image Compression (TIC) approach is developed which reuses the canonical variational autoencoder (VAE) architecture with paired main and hyper encoder-decoders [1], as shown in Fig. 1a. Both main and hyper encoders are comprised of a sequence of neural transformation units (NTUs) to analyse and aggregate important information for more compact representation of input image, while the decoders mirror the encoder-side operations to generate pixel-domain im-age reconstruction from the compressed bitstream. Each NTU is consist of a Swin Transformer Block (STB) [2] and a convolutional layer (Conv) to best embed both long-range and short-range information; In the meantime, a causal attention module (CAM) is devised for adaptive context modeling of latent features to utilize both hyper and autoregressive priors. The TIC rivals with state-of-the-art approaches including deep convolutional neural networks (CNNs) based learnt image coding (LIC) methods and handcrafted rules-based intra profile of recently-approved Versatile Video Coding (VVC) standard, and requires much less model parameters, e.g., up to 45% reduction to leading-performance LIC.
Dynamic force and moment characteristics of annular gaps - Simulation results and evaluation of the relevance of the tilt and moment coefficients

Nowadays, most studies of the dynamic characteristics of annular gaps focus only on the force characteristics due to translational motions, while the tilt and moment coefficients are less well studied. To expand the knowledge of the additional coefficients, we investigate both the dynamic force and the dynamic and moment characteristics of annular gaps. First, the rotordynamic influence of annular gaps is recapitulated. Second, a new simulation method is presented, using a perturbed integro-differential approach in combination with a Hirs' model and power-law ansatz functions for the velocity profiles to calculate the dynamic force and moment characteristics. Subsequently, an extensive parameter study is carried out. To evaluate whether the hydraulic tilt and moment coefficients need to be considered, an effective stiffness is defined and the influence of the annulus length, an eccentrically operated shaft, the centre of rotation, a modified Reynolds number, the flow number and the pre-swirl is investigated. It is shown that despite the annulus length, the flow number as well a modified Reynolds number are crucial for the relevance of the additional coefficients. This leads to a simple three-dimensional diagram, which makes it possible to assess the necessity of including the additional coefficients on the basis of the three variables.
Finite Element Analysis of Time Fractional Integro-differential Equations of Kirchhoff type for Non-homogeneous Materials

In this paper, we study a time‐fractional initial‐boundary value problem of Kirchhoff type involving memory term for non‐homogeneous materials. As a consequence of energy argument, we derive bound as well as bound on the solution of the considered problem by defining two new discrete Laplacian operators. Using these a priori bounds, existence and uniqueness of the weak solution to the considered problem are established. Further, we study semi discrete formulation of the problem by discretizing the space domain using a conforming finite element method (FEM) and keeping the time variable continuous. The semi discrete error analysis is carried out by modifying the standard Ritz‐Volterra projection operator in such a way that it reduces the complexities arising from the Kirchhoff type nonlinearity. Finally, we develop a new linearized L1 Galerkin FEM to obtain numerical solution of the problem under consideration. This method has a convergence rate of , where is the fractional derivative exponent and and are the discretization parameters in the space and time directions, respectively. This convergence rate is further improved to second order in the time direction by proposing a novel linearized L2‐1 Galerkin FEM. We conduct a numerical experiment to validate our theoretical claims.
Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximation

Adversarial attacks during training can strongly influence the performance of multi-agent reinforcement learning algorithms. It is, thus, highly desirable to augment existing algorithms such that the impact of adversarial attacks on cooperative networks is eliminated, or at least bounded. In this work, we consider a fully decentralized network, where each agent receives a local reward and observes the global state and action. We propose a resilient consensus-based actor-critic algorithm, whereby each agent estimates the team-average reward and value function, and communicates the associated parameter vectors to its immediate neighbors. We show that in the presence of Byzantine agents, whose estimation and communication strategies are completely arbitrary, the estimates of the cooperative agents converge to a bounded consensus value with probability one, provided that there are at most $H$ Byzantine agents in the neighborhood of each cooperative agent and the network is $(2H+1)$-robust. Furthermore, we prove that the policy of the cooperative agents converges with probability one to a bounded neighborhood around a local maximizer of their team-average objective function under the assumption that the policies of the adversarial agents asymptotically become stationary.
Project Management Maturity Analysis in the Serbian Energy Sector

In this paper we will present an analysis of the current state of practice in project management in the energy sector in Serbia, wherein the mentioned analysis is based on the results of original research on project maturity in this field. This paper includes a literature review about the current situation in the Serbian energy system, the basic concepts and significance of the research of project maturity in organizations, the basic concepts related to the projects in the energy sector, as well as the general state of project management in Serbia. After this, an analysis of the results of the research is presented, which is structured according to the elements of project maturity included in the research, and the methods of analysis. The analysis of the results includes a general analysis as well as statistical and cluster analysis. At the end, based on the analysis results, recommendations for improvements in the area of project management in the energy sector in Serbia are presented.
Cuscuton inflation

We study the impact of (generalized) cuscuton models on standard single scalar field inflation. Generalized cuscuton models are characterized by spatial covariant gravity where a scalar degree of freedom is made non dynamical, and there are just two tensor degrees of freedom. The presence of the non-dynamical scalar field does not spoil inflation but instead the modifications are, in general, slow-roll suppressed leading to almost scale-invariant power spectra. However, the extra free parameters, which can be tuned relatively independently, lead to a larger parameter range for observable quantities, such as the tensor-to-scalar ratio. For the (generalized) cuscuton model the non-Gaussianties of the curvature bispectrum are suppressed by the slow-roll parameters, and, therefore, outside the reach of current experiments. However, generalized cuscuton models can lead to a different shape for the bispectrum which might be constrained by future experiments.
Construction of Spectrally-Null-Constrained Zero-Correlation Zone Sequences with Flexible Support

In recent years, traditional zero-correlation zone (ZCZ) sequences are being studied due to support interference-free quasi-synchronous code division multiple access (QS-CDMA) systems. However, in cognitive radio (CR) network, it is desirable to design ZCZ sequences having spectral null constraint (SNC) property to achieve low spectral density profile. This paper focuses on the construction of SNC-ZCZ sequences having flexible support, where support refers to a collection of indices corresponding to non-zero entries in the sequence. The proposed SNC-ZCZ sequences reduce to traditional ZCZ sequences when the size of the support becomes equal to the length of the sequence. To obtain ZCZ sequences, we first propose construction of traditional/SNC-Complete complementary codes (SNC-CCCs) using a class of extended Boolean functions (EBFs). With the help of this class we propose another class of EBFs that generates asymptotically optimal traditional/SNC-ZCZ sequences of prime-power lengths with respect to Tang-Fan-Matsufuzi bound. Furthermore, a relation between the second-order cosets of first-order generalized Reed-Muller code and the proposed traditional ZCZ sequences is also established.
Expansion in supercritical random subgraphs of the hypercube and its consequences

It is well-known that the behaviour of a random subgraph of a $d$-dimensional hypercube, where we include each edge independently with probability $p$, undergoes a phase transition when $p$ is around $\frac{1}{d}$. More precisely, standard arguments show that just below this value of $p$ all components of this graph have order $O(d)$ with probability tending to one as $d \to \infty$ (whp for short), whereas Ajtai, Koml\'{o}s and Szemer\'{e}di [Largest random component of a $k$-cube, Combinatorica 2 (1982), no. 1, 1--7; MR0671140] showed that just above this value, in the supercritical regime, whp there is a unique `giant' component of order $\Theta\left(2^d\right)$. We show that whp the vertex-expansion of the giant component is inverse polynomial in $d$. As a consequence we obtain polynomial in $d$ bounds on the diameter of the giant component and the mixing time of the lazy random walk on the giant component, answering questions of Bollob\'{a}s, Kohayakawa and {\L}uczak [On the diameter and radius of random subgraphs of the cube, Random Structures and Algorithms 5 (1994), no. 5, 627--648; MR1300592] and of Pete [A note on percolation on $\mathbb{Z}^d$: isoperimetric profile via exponential cluster repulsion, Electron. Commun. Probab. 13 (2008), 377--392; MR2415145]. Furthermore, our results imply lower bounds on the circumference and Hadwiger number of a random subgraph of the hypercube in this regime of $p$ which are tight up to polynomial factors in $d$.
SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy

The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ∼106 transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg2) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ∼15 deg2 of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ∼90% of all detections, corresponding to ∼1000 artifacts deg–2 in g band, and falling to 300 deg–2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.
AlphaRotate: A Rotation Detection Benchmark using TensorFlow

AlphaRotate is an open-source Tensorflow benchmark for performing scalable rotation detection on various datasets. It currently provides more than 18 popular rotation detection models under a single, well-documented API designed for use by both practitioners and researchers. AlphaRotate regards high performance, robustness, sustainability and scalability as the core concept of design, and all models are covered by unit testing, continuous integration, code coverage, maintainability checks, and visual monitoring and analysis. AlphaRotate can be installed from PyPI and is released under the Apache-2.0 License. Source code is available at https://github.com/yangxue0827/RotationDetection.