Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximation-Refinement Testing of Compute-Intensive Cyber-Physical Models: An Approach Based on System Identification

Black-box testing has been extensively applied to test models of Cyber-Physical systems (CPS) since these models are not often amenable to static and symbolic testing and verification. Black-box testing, however, requires to execute the model under test for a large number of candidate test inputs. This poses a challenge for a large and practically-important category of CPS models, known as compute-intensive CPS (CI-CPS) models, where a single simulation may take hours to complete. We propose a novel approach, namely ARIsTEO, to enable effective and efficient testing of CI-CPS models. Our approach embeds black-box testing into an iterative approximation-refinement loop. At the start, some sampled inputs and outputs of the CI-CPS model under test are used to generate a surrogate model that is faster to execute and can be subjected to black-box testing. Any failure-revealing test identified for the surrogate model is checked on the original model. If spurious, the test results are used to refine the surrogate model to be tested again. Otherwise, the test reveals a valid failure. We evaluated ARIsTEO by comparing it with S-Taliro, an open-source and industry-strength tool for testing CPS models. Our results, obtained based on five publicly-available CPS models, show that, on average, ARIsTEO is able to find 24% more requirements violations than S-Taliro and is 31% faster than S-Taliro in finding those violations. We further assessed the effectiveness and efficiency of ARIsTEO on a large industrial case study from the satellite domain. In contrast to S-Taliro, ARIsTEO successfully tested two different versions of this model and could identify three requirements violations, requiring four hours, on average, for each violation.
Probing fragmentation and velocity sub-structure in the massive NGC 6334 filament with ALMA

Context. Herschel imaging surveys of galactic interstellar clouds support a paradigm for low-mass star formation in which dense molecular filaments play a crucial role. The detailed fragmentation properties of star-forming filaments remain poorly understood, however, and the validity of the filament paradigm in the intermediate- to high-mass regime is still unclear. Aims. Here, following up on an earlier 350 μm dust continuum study with the ArTéMiS camera on the APEX telescope, we investigate the detailed density and velocity structure of the main filament in the high-mass star-forming region NGC 6334. Methods. We conducted ALMA Band 3 observations in the 3.1 mm continuum and of the N2H+(1–0), HC5N(36–35), HNC(1–0), HC3N(10–9), CH3CCH(6–5), and H2CS(3–2) lines at an angular resolution of ~3′′, corresponding to 0.025 pc at a distance of 1.7 kpc. Results. The NGC 6334 filament was detected in both the 3.1 mm continuum and the N2H+, HC3N, HC5N, CH3CCH, and H2CS lines with ALMA. We identified twenty-six compact (<0.03 pc) dense cores at 3.1 mm and five velocity-coherent fiber-like features in N2H+ within the main filament. The typical length (~0.5 pc) of, and velocity difference (~0.8 km s−1) between, the fiber-like features of the NGC 6334 filament are reminiscent of the properties for the fibers of the low-mass star-forming filament B211/B213 in the Taurus cloud. Only two or three of the five velocity-coherent features are well aligned with the NGC 6334 filament and may represent genuine, fiber sub-structures; the other two features may trace accretion flows onto the main filament. The mass distribution of the ALMA 3.1 mm continuum cores has a peak at ~10 M⊙, which is an order of magnitude higher than the peak of the prestellar core mass function in nearby, low-mass star-forming clouds. The cores can be divided into seven groups, closely associated with dense clumps seen in the ArTéMiS 350 μm data. The projected separation between ALMA dense cores (0.03–0.1 pc) and the projected spacing between ArTéMiS clumps (0.2–0.3 pc) are roughly consistent with the effective Jeans length (0.08 ± 0.03 pc) in the filament and a physical scale of about four times the filament width, respectively, if the inclination angle of the filament to line of sight is ~30°. These two distinct separation scales are suggestive of a bimodal fragmentation process in the filament. Conclusions. Despite being one order of magnitude denser and more massive than the Taurus B211/B213 filament, the NGC 6334 filament has a density and velocity structure that is qualitatively very similar. The main difference is that the dense cores embedded in the NGC 6334 filament appear to be an order of magnitude denser and more massive than the cores in the Taurus filament. This suggests that dense molecular filaments may evolve and fragment in a similar manner in low- and high-mass star-forming regions, and that the filament paradigm may hold in the intermediate-mass (if not high-mass) star formation regime.
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping

The distributional perspective on reinforcement learning (RL) has given rise to a series of successful Q-learning algorithms, resulting in state-of-the-art performance in arcade game environments. However, it has not yet been analyzed how these findings from a discrete setting translate to complex practical applications characterized by noisy, high dimensional and continuous state-action spaces. In this work, we propose Quantile QT-Opt (Q2-Opt), a distributional variant of the recently introduced distributed Q-learning algorithm for continuous domains, and examine its behaviour in a series of simulated and real vision-based robotic grasping tasks. The absence of an actor in Q2-Opt allows us to directly draw a parallel to the previous discrete experiments in the literature without the additional complexities induced by an actor-critic architecture. We demonstrate that Q2-Opt achieves a superior vision-based object grasping success rate, while also being more sample efficient. The distributional formulation also allows us to experiment with various risk distortion metrics that give us an indication of how robots can concretely manage risk in practice using a Deep RL control policy. As an additional contribution, we perform batch RL experiments in our virtual environment and compare them with the latest findings from discrete settings. Surprisingly, we find that the previous batch RL findings from the literature obtained on arcade game environments do not generalise to our setup.
Analysis of Multi-hour Continuous Observations of Seven Millisecond Pulsars

Precision pulsar timing can be used for a variety of astrophysical tests, from the detection of gravitational waves to probing the properties of the interstellar medium. Here we analyze various noise contributions to pulsar timing residuals from continuous multi-hour observations of seven millisecond pulsars (MSPs). We present scintillation bandwidth measurements for all MSPs in the sample, some for the first time. We also present scintillation timescale measurements and lower limits for all MSPs for the first time. In addition, we present upper limits on the contribution of pulse phase jitter to the timing residual error for all MSPs. These long observations also allow us to constrain variations in dispersion measures (DMs) on hour-long timescales for several millisecond pulsars. We find that there are no apparent DM variations in any of the MSPs studied on these timescales, as expected. In light of new radio telescopes, such as the Canadian Hydrogen Intensity Mapping Experiment, which will be able to time many pulsars for a short time each day, we search for differences in timing precisions from continuous pulse times of arrival (TOAs) and from equivalent length time-discontinuous TOAs. We find no differences in the precision for any of the MSPs in our sample, as expected. We conclude that the TOA variations are consistent with the expected breakdown into template-fitting, jitter, and scintillation errors.
Science with the Murchison Widefield Array: Phase I results and Phase II opportunities

Abstract The Murchison Widefield Array (MWA) is an open access telescope dedicated to studying the low-frequency (80–300 MHz) southern sky. Since beginning operations in mid-2013, the MWA has opened a new observational window in the southern hemisphere enabling many science areas. The driving science objectives of the original design were to observe 21 cm radiation from the Epoch of Reionisation (EoR), explore the radio time domain, perform Galactic and extragalactic surveys, and monitor solar, heliospheric, and ionospheric phenomena. All together $60+$ programs recorded 20 000 h producing 146 papers to date. In 2016, the telescope underwent a major upgrade resulting in alternating compact and extended configurations. Other upgrades, including digital back-ends and a rapid-response triggering system, have been developed since the original array was commissioned. In this paper, we review the major results from the prior operation of the MWA and then discuss the new science paths enabled by the improved capabilities. We group these science opportunities by the four original science themes but also include ideas for directions outside these categories.
Hd 1 , Hd 3 a , and Hd 6 Genes : Possible DNA Methylation Roles in Photoperiod Sensitive Gene Regulation of Rice KDML 105 ( Oryza sativa L . )

The study was aimed to investigate DNA methylation in rice after treatment with different photoperiods and to determine allelic differences of Hd1, Hd3a, and Hd6 genes, involved in photoperiod sensitivity, in KDML 105, a photoperiod-sensitive cultivar, and in Suphan Buri 1, a photoperiodinsensitive cultivar. Detection of DNA methylation was performed by Southern hybridization. The genomic DNA of KDML 105 was digested by HpaII or MspI restriction enzymes, separated by electrophoresis, Southern blotted and hybridized with probes amplified from the 5' region of Hd1, Hd3a, and Hd6 genes, respectively. The results showed no difference in band patterns of long-day treatment and short-day treatment of either HpaII or MspI digested groups indicating that the target sequences were not methylated. Primers were designed to amplify the overlapping fragments of Hd1, Hd3a, and Hd6 alleles from rice KDML 105 and Suphan Buri 1 to make a contig sequence covering the whole genes. Nucleotide and deduced amino acid sequences data obtained from this experiment indicated that Hd1, Hd3a, and Hd6 genes of KDML 105 and Suphan Buri 1 encoded normal Hd1, Hd3a, and Hd6 proteins, respectively. Taken together, the data suggested that DNA methylation and single amino acid polymorphisms (SAPs) might not be the mechanisms underlying the expression and function of photoperiod genes. However, the differences of the nucleotide in the 5' control region might be the cause of the photoperiod sensitivity difference between KDML 105 and Suphan Buri 1.
Memes and symbolic violence: #proudboys and the use of memes for propaganda and the construction of collective identity

ABSTRACT As a social media platform, Instagram has a strong influence on youth culture, identity, and perceptions of the world, with the application serving not only for youth to follow accounts that are aspirational but also for entertainment and identity building through memes. Meme accounts that are explicitly conservative and that espouse white supremacist, hateful ideology and subsequently, identity, are incredibly prevalent. Media serve as powerful institutions for the socialization of youth, and content on the platform reveals that memes are serving as building blocks of ideological meaning. This study conducted a discourse analysis of the memes and content circulated by the alt-right affiliate movement the ‘Proud Boys,’ which is being sold to young men as a fraternity-like organization to celebrate ‘Western ideals’. Proud Boys operate on an ideology that consists of both symbolic and physical violence, and the popularity of these groups is growing. Using Bourdieu’s work on language as a framework, this article is an exploration to their recruitment and world-building practices on Instagram using memes and will be necessary to understand the movement, and to gain further insight into how memes are being used as propaganda.
A central limit theorem for the number of isolated vertices in a preferential attachment random graph.

We study the number of isolated vertices in a preferential attachment random graph. In this graph model vertices are added over time and newly arriving vertices connect to older ones with probability proportional to some sublinear function of the indegree of the older vertex at that time. We consider the model with random outdegree introduced by Dereich and M\"orters in [DM09]. Using Stein's method and size bias coupling, we deduce bounds in the Wasserstein distance between the law of the rescaled number of isolated vertices and a standard Gaussian distribution.
Early Estimation of User's Intention of Tele-Operation Using Object Affordance and Hand Motion in a Dual First-Person Vision

This paper describes a method of estimating the intention of a user's motion in a robot tele-operation scenario. One of the issues in tele-operation is latency, which occurs due to various reasons such as a slow robot motion and a narrow communication channel. An effective way of reducing the latency is to estimate the human intention of motions and to move the robot proactively. To enable a reliable early intention estimation, we use both hand motion and object affordances in a dual first-person vision (robot and user) with an HMD. Experimental results in an object pickup scenario show the effectiveness of the method.
Irregular Convolutional Auto-Encoder on Point Clouds

We proposed a novel graph convolutional neural network that could construct a coarse, sparse latent point cloud from a dense, raw point cloud. With a novel non-isotropic convolution operation defined on irregular geometries, the model then can reconstruct the original point cloud from this latent cloud with fine details. Furthermore, we proposed that it is even possible to perform particle simulation using the latent cloud encoded from some simulated particle cloud (e.g. fluids), to accelerate the particle simulation process. Our model has been tested on ShapeNetCore dataset for Auto-Encoding with a limited latent dimension and tested on a synthesis dataset for fluids simulation. We also compare the model with other state-of-the-art models, and several visualizations were done to intuitively understand the model.
Energy localization in an atomic chain with a topological soliton

Topological defects in low-dimensional non-linear systems feature a sliding-to-pinning transition of relevance for a variety of research fields, ranging from biophysics to nano- and solid-state physics. We find that the dynamics after a local excitation results in a highly-non-trivial energy transport in the presence of a topological soliton, characterized by a strongly enhanced energy localization in the pinning regime. Moreover, we show that the energy flux in ion crystals with a topological defect can be sensitively regulated by experimentally accessible environmental parameters. Whereas, third-order non-linear resonances can cause an enhanced long-time energy delocalization, robust energy localization persists for distinct parameter ranges even for long evolution times and large local excitations.
CAN Radar: Sensing Physical Devices in CAN Networks based on Time Domain Reflectometry

The presence of security vulnerabilities in automotive networks has already been shown by various publications in recent years. Due to the specification of the Controller Area Network (CAN) as a broadcast medium without security mechanisms, attackers are able to read transmitted messages without being noticed and to inject malicious messages. In order to detect potential attackers within a network or software system as early as possible, Intrusion Detection Systems (IDSs) are prevalent. Many approaches for vehicles are based on techniques which are able to detect deviations from specified CAN network behaviour regarding protocol or payload properties. However, it is challenging to detect attackers who secretly connect to CAN networks and do not actively participate in bus traffic. In this paper, we present an approach that is capable of successfully detecting unknown CAN devices and determining the distance (cable length) between the attacker device and our sensing unit based on Time Domain Reflectometry (TDR) technique. We evaluated our approach on a real vehicle network.
Frame Soft Shrinkage as Proximity Operator

Let $\mathcal H$ and $\mathcal K$ be real Hilbert spaces and $T \in \mathcal{B} (\mathcal H,\mathcal K)$ an injective operator with closed range and Moore-Penrose inverse $T^\dagger$. Based on the well-known characterization of proximity operators by Moreau, we prove that for any proximity operator $\text{Prox} \colon \mathcal K \to \mathcal K$ the operator $T^\dagger \, \text{Prox} \, T$ is a proximity operator on the linear space $\mathcal H$ equipped with a suitable norm. In particular, it follows for the frequently applied soft shrinkage operator $\text{Prox} = S_{\lambda}\colon \ell_2 \rightarrow \ell_2$ and any frame analysis operator $T\colon \mathcal H \to \ell_2$, that the frame shrinkage operator $T^\dagger\, S_\lambda\, T$ is a proximity operator in a suitable Hilbert space.
Field-based Coordination with the Share Operator

Field-based coordination has been proposed as a model for coordinating collective adaptive systems, promoting a view of distributed computations as functions manipulating data structures spread over space and evolving over time, called computational fields. The field calculus is a formal foundation for field computations, providing specific constructs for evolution (time) and neighbor interaction (space), which are handled by separate operators (called rep and nbr, respectively). This approach, however, intrinsically limits the speed of information propagation that can be achieved by their combined use. In this paper, we propose a new field-based coordination operator called share, which captures the space-time nature of field computations in a single operator that declaratively achieves: (i) observation of neighbors' values; (ii) reduction to a single local value; and iii) update and converse sharing to neighbors of a local variable. We show that for an important class of self-stabilising computations, share can replace all occurrences of rep and nbr constructs. In addition to conceptual economy, use of the share operator also allows many prior field calculus algorithms to be greatly accelerated, which we validate empirically with simulations of frequently used network propagation and collection algorithms.
A Benchmark to Evaluate InfiniBand Solutions for Java Applications

Low-latency network interconnects, such as InfiniBand, are commonly used in HPC centers and are even accessible with todays cloud providers offering equipped instances for rent. Most big data applications and frameworks are written in Java. But, the JVM environment alone does not provide interfaces to directly utilize InfiniBand networks. In this paper, we present the ``Java InfiniBand Benchmark'' to evaluate the currently available (and supported) ``low-level'' solutions to utilize InfiniBand in Java. It evaluates socket- and verbs-based libraries using typical network microbenchmarks regarding throughput and latency. Furthermore, we present evaluation results of the solutions on two hardware configurations with 56 Gbit/s and 100 Gbit/s InfiniBand NICs. With transparency often traded for performance and vice versa, the benchmark helps developers with studying the pros and cons of each solution and support them in their decision which solution is more suitable for their existing or new use-case.
Exact and/or Fast Nearest Neighbors

Prior methods for retrieval of nearest neighbors in high dimensions are fast and approximate--providing probabilistic guarantees of returning the correct answer--or slow and exact performing an exhaustive search. We present Certified Cosine, a novel approach to nearest-neighbors which takes advantage of structure present in the cosine similarity distance metric to offer certificates. When a certificate is constructed, it guarantees that the nearest neighbor set is correct, possibly avoiding an exhaustive search. Certified Cosine's certificates work with high dimensional data and outperform previous exact nearest neighbor methods on these datasets.
Adversarial reconstruction for Multi-modal Machine Translation

Even with the growing interest in problems at the intersection of Computer Vision and Natural Language, grounding (i.e. identifying) the components of a structured description in an image still remains a challenging task. This contribution aims to propose a model which learns grounding by reconstructing the visual features for the Multi-modal translation task. Previous works have partially investigated standard approaches such as regression methods to approximate the reconstruction of a visual input. In this paper, we propose a different and novel approach which learns grounding by adversarial feedback. To do so, we modulate our network following the recent promising adversarial architectures and evaluate how the adversarial response from a visual reconstruction as an auxiliary task helps the model in its learning. We report the highest scores in term of BLEU and METEOR metrics on the different datasets.
Comparing shapes of high genus surfaces

In this paper, we define a new metric structure on the shape space of a high genus surface. We introduce a rigorous definition of a shape of a surface and construct a metric based on two energies measuring the area distortion and the angle distortion of a quasiconformal homeomorphism. We show that the energy minimizer in a fixed homotopy class is achieved by a quasiconformal homeomorphism by the lower semicontinuity property of these two energies. Finally, we explore the properties of several energies related to the Dirichlet energy.