Miracle-dz/UniFAR-FTUs huggingface dataset:
Robots’ State Estimation and Observability Analysis Based on Statistical Motion Models

This article presents a generic motion model to capture mobile robots’ dynamic behaviors (translation and rotation). The model is based on statistical models driven by white random processes and is formulated into a full state estimation algorithm based on the error-state extended Kalman filtering framework (ESEKF). The major benefits of this method are its versatility, being applicable to different robotic systems without accurately modeling the robots’ specific dynamics, and the ability to estimate the robot’s (angular) acceleration, jerk, or higher order dynamic states with low delay. Mathematical analyses with numerical simulations are presented to show the properties of the statistical model-based estimation framework and reveal its connection to existing low-pass filters. Furthermore, a new paradigm is developed for robotic observability analysis by developing Lie derivatives and associated partial differentiation directly on manifolds. It is shown that this new paradigm is much simpler and more natural than existing methods based on quaternion parameterizations. It is also scalable to high-dimensional systems. A novel thin set concept is introduced to characterize the unobservable subset of the system states, providing the theoretical foundation to observability analysis of robotic systems operating on manifolds and in high dimension. Finally, extensive experiments, including full state estimation and extrinsic calibration (both POS-IMU and IMU-IMU) on a quadrotor unmanned aerial vehicle (UAV), a handheld platform, and a ground vehicle, are conducted. Comparisons with existing methods show that the proposed method can effectively estimate all extrinsic parameters, the robot’s translation/angular acceleration, and other state variables (e.g., position, velocity, and attitude) with high accuracy and low delay.
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs

Recent years have brought about a renewed interest in commonsense representation and reasoning in the field of natural language understanding. The development of new commonsense knowledge graphs (CSKG) has been central to these advances as their diverse facts can be used and referenced by machine learning models for tackling new and challenging tasks. At the same time, there remain questions about the quality and coverage of these resources due to the massive scale required to comprehensively encompass general commonsense knowledge. In this work, we posit that manually constructed CSKGs will never achieve the coverage necessary to be applicable in all situations encountered by NLP agents. Therefore, we propose a new evaluation framework for testing the utility of KGs based on how effectively implicit knowledge representations can be learned from them. With this new goal, we propose Atomic 2020, a new CSKG of general-purpose commonsense knowledge containing knowledge that is not readily available in pretrained language models. We evaluate its properties in comparison with other leading CSKGs, performing the first large-scale pairwise study of commonsense knowledge resources. Next, we show that Atomic 2020 is better suited for training knowledge models that can generate accurate, representative knowledge for new, unseen entities and events. Finally, through human evaluation, we show that the few-shot performance of GPT-3 (175B parameters), while impressive, remains ~12 absolute points lower than a BART-based knowledge model trained on Atomic 2020 despite using over 430x fewer parameters.
Oscillon collapse to black holes

Using numerical relativity simulations we study the dynamics of pseudo-topological objects called oscillons for a class of models inspired by axion-monodromy. Starting from free field solutions supported by gravitational attractions, we investigate the effect of adding self-interactions, and contrast this with the effect of adding self-interactions whilst removing gravitational support. We map out regions of the parameter space where the initial conditions rapidly collapse to black holes, and other regions where they remain pseudo-stable or disperse.
Effectiveness of Acupuncturing at the Sphenopalatine Ganglion Acupoint Alone for Treatment of Allergic Rhinitis: A Systematic Review and Meta-Analysis

Aim(s) To evaluate the efficiency of acupuncturing at the sphenopalatine ganglion acupoint alone for treatment of allergic rhinitis. Design A total of ten online databases were searched to find studies published up to Jan. 2018. Primary outcome measures include the TNSS, the RQLQ score, the VAS score, total effective rate, score for signs and symptoms, and the improvement of disease classification. Study quality of each included article was evaluated by the Cochrane Collaboration risk of bias tool. A meta-analysis was conducted based on the Cochrane systematic review method by using RevMan 5.3 software. Interventions Acupuncturing SGA alone was the only therapy in experimental group. Interventions in control groups includes sham acupuncture, acupuncturing other regular acupoints, and western medicine. Specific techniques included manual acupuncture and electroacupuncture only. Primary Outcomes They include TNSS, RQLQ, VAS score, total effective rate, the improvement of disease classification. Results Ten studies of eight articles involving 1004 participants were included. Result of meta-analysis showed that acupuncturing sphenopalatine ganglion acupoints alone was more effective than control groups. However, several adverse effects were reported. Conclusion These findings show that acupuncturing the sphenopalatine ganglion acupoint alone has a potential role in alleviating nasal symptoms, improving quality of life for patients, and the effectiveness of acupuncture in the treatment of allergic rhinitis, suggesting it as a considerable therapy for allergic rhinitis. However, more studies are needed to execute a subgroup analysis of various variables and to evaluate the publication bias of the study.
Projection techniques to update the truncated SVD of evolving matrices

This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time. Such matrix problems represent an important computational kernel in applications such as Latent Semantic Indexing and Recommender Systems. Nonetheless, the proposed framework is purely algebraic and targets general updating problems. The algorithm presented in this paper undertakes a projection view-point and focuses on building a pair of subspaces which approximate the linear span of the sought singular vectors of the updated matrix. We discuss and analyze two different choices to form the projection subspaces. Results on matrices from real applications suggest that the proposed algorithm can lead to higher accuracy, especially for the singular triplets associated with the largest modulus singular values. Several practical details and key differences with other approaches are also discussed.
Collapsible Pushdown Parity Games

This article studies a large class of two-player perfect-information turn-based parity games on infinite graphs, namely, those generated by collapsible pushdown automata. The main motivation for studying these games comes from the connections from collapsible pushdown automata and higher-order recursion schemes, both models being equi-expressive for generating infinite trees. Our main result is to establish the decidability of such games and to provide an effective representation of the winning region as well as of a winning strategy. Thus, the results obtained here provide all necessary tools for an in-depth study of logical properties of trees generated by collapsible pushdown automata/recursion schemes.
Magnetic Helicity Flux across Solar Active Region Photospheres. I. Hemispheric Sign Preference in Solar Cycle 24

A hemispheric preference in the dominant sign of magnetic helicity has been observed in numerous features in the solar atmosphere, i.e., left-handed/right-handed helicity in the northern/southern hemisphere. The relative importance of different physical processes that may contribute to the observed hemispheric sign preference (HSP) of magnetic helicity is still under debate. Here, we estimate magnetic helicity flux (dH/dt) across the photospheric surface for 4802 samples of 1105 unique active regions (ARs) that appeared over an 8 yr period from 2010 to 2017 during solar cycle 24, using photospheric vector magnetic field observations by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). The estimates of dH/dt show that 63% and 65% of the investigated AR samples in the northern and southern hemispheres, respectively, follow the HSP. We also find a trend that the HSP of dH/dt increases from ∼50%–60% up to ∼70%–80% as ARs (1) appear at the earlier inclining phase of the solar cycle or higher latitudes and (2) have larger values of , the total unsigned magnetic flux, and the average plasma-flow speed. These observational findings support the enhancement of the HSP mainly by the Coriolis force acting on a buoyantly rising and expanding flux tube through the turbulent convection zone. In addition, the differential rotation on the solar surface as well as the tachocline α-effect of a flux-transport dynamo may reinforce the HSP for ARs at higher latitudes.
Counting Subgraphs in Degenerate Graphs

We consider the problem of counting the number of copies of a fixed graph H within an input graph G. This is one of the most well-studied algorithmic graph problems, with many theoretical and practical applications. We focus on solving this problem when the input G has bounded degeneracy. This is a rich family of graphs, containing all graphs without a fixed minor (e.g., planar graphs), as well as graphs generated by various random processes (e.g., preferential attachment graphs). We say that H is easy if there is a linear-time algorithm for counting the number of copies of H in an input G of bounded degeneracy. A seminal result of Chiba and Nishizeki from ’85 states that every H on at most 4 vertices is easy. Bera, Pashanasangi, and Seshadhri recently extended this to all H on 5 vertices and further proved that for every \( k \gt 5 \) there is a k-vertex H which is not easy. They left open the natural problem of characterizing all easy graphs H. Bressan has recently introduced a framework for counting subgraphs in degenerate graphs, from which one can extract a sufficient condition for a graph H to be easy. Here, we show that this sufficient condition is also necessary, thus fully answering the Bera–Pashanasangi–Seshadhri problem. We further resolve two closely related problems; namely characterizing the graphs that are easy with respect to counting induced copies, and with respect to counting homomorphisms.
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding

Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods commonly ignore the constraint of sparsity in the search phase, but project the optimized solution onto a sparse one by post-processing. As a result, the dense super-net for search is inefficient to train and has a gap with the projected architecture for evaluation. In this paper, we formulate neural architecture search as a sparse coding problem. We perform the differentiable search on a compressed lower-dimensional space that has the same validation loss as the original sparse solution space, and recover an architecture by solving the sparse coding problem. The differentiable search and architecture recovery are optimized in an alternate manner. By doing so, our network for search at each update satisfies the sparsity constraint and is efficient to train. In order to also eliminate the depth and width gap between the network in search and the target-net in evaluation, we further propose a method to search and evaluate in one stage under the target-net settings. When training finishes, architecture variables are absorbed into network weights. Thus we get the searched architecture and optimized parameters in a single run. In experiments, our two-stage method on CIFAR-10 requires only 0.05 GPU-day for search. Our one-stage method produces state-of-the-art performances on both CIFAR-10 and ImageNet at the cost of only evaluation time.
Resolution as intersection subtyping via Modus Ponens

Resolution and subtyping are two common mechanisms in programming languages. Resolution is used by features such as type classes or Scala-style implicits to synthesize values automatically from contextual type information. Subtyping is commonly used to automatically convert the type of a value into another compatible type. So far the two mechanisms have been considered independently of each other. This paper shows that, with a small extension, subtyping with intersection types can subsume resolution. This has three main consequences. Firstly, resolution does not need to be implemented as a separate mechanism. Secondly, the interaction between resolution and subtyping becomes apparent. Finally, the integration of resolution into subtyping enables first-class (implicit) environments. The extension that recovers the power of resolution via subtyping is the modus ponens rule of propositional logic. While it is easily added to declarative subtyping, significant care needs to be taken to retain desirable properties, such as transitivity and decidability of algorithmic subtyping, and coherence. To materialize these ideas we develop λiMP, a calculus that extends a iprevious calculus with disjoint intersection types, and develop its metatheory in the Coq theorem prover.
Desenvolvimento e produtividade de couve-flor e repolho influenciados por tipos de cobertura do solo

A utilizacao de plantas de cobertura antecedendo o cultivo de hortalicas tem sido uma das alternativas utilizadas para diminuir o uso de adubacao mineral. Neste estudo avaliaram-se coberturas do solo aplicadas antes do plantio e seus efeitos em algumas caracteristicas agronomicas e na produtividade de couve-flor e repolho. Utilizou-se o delineamento de blocos ao acaso, em esquema fatorial, com quatro coberturas do solo (crotalaria juncea, braquiaria, milheto e pousio) e duas culturas (couve-flor e repolho), com quatro repeticoes, em parcelas de 20 m2 (4x5 m). Foi determinado o numero de folhas, altura, diâmetro da cabeca, do caule e horizontal, massa fresca e seca. As coberturas utilizadas influenciaram positivamente as caracteristicas agronomicas da couve-flor e do repolho para diâmetro da cabeca (55,1 e 194,8 cm), diâmetro do caule (70,4 e 49,2 mm) e diâmetro horizontal (169,9 e 14,8 mm), massa fresca (1,0 e 2,8 kg) e massa seca da cabeca (73,4 e 0,65 g) e produtividade (7,3 e 19,2 t/ha) das culturas, respectivamente, quando cultivadas sobre os residuos de braquiaria. A massa fresca comercial de repolho (2,8 kg) foi superior ao padrao exigido pelo mercado consumidor brasileiro.
Automated Reasoning and Detection of Specious Configuration in Large Systems with Symbolic Execution

Misconfiguration is a major cause of system failures. Prior solutions focus on detecting invalid settings that are introduced by user mistakes. But another type of misconfiguration that continues to haunt production services is specious configuration--settings that are valid but lead to unexpectedly poor performance in production. Such misconfigurations are subtle, so even careful administrators may fail to foresee them. We propose a tool called Violet to detect such misconfiguration. We realize the crux of specious configuration is that it causes some slow code path to be executed, but the bad performance effect cannot always be triggered. Violet thus takes a novel approach that uses selective symbolic execution to systematically reason about the performance effect of configuration parameters, their combination effect, and the relationship with input. Violet outputs a performance impact model for the automatic detection of poor configuration settings. We applied Violet on four large systems. To evaluate the effectiveness of Violet, we collect 17 real-world specious configuration cases. Violet detects 15 of them. Violet also identifies 9 unknown specious configurations.
arXiv : The Present and Future of Four Tops

We study the phenomenology of a strongly-interacting top quark at future hadron and lepton colliders, showing that the characteristic four-top contact operators give rise to the most significant effects. We demonstrate the extraordinary potential of a 100 TeV proton-proton collider to directly test such non-standard interactions in four-top production, a process that we thoroughly analyze in the same-sign dilepton and trilepton channels, and explore in the fully hadronic channel. Furthermore, high-energy electron-positron colliders, such as CLIC or the ILC, are shown to exhibit an indirect yet remarkable sensitivity to four-top operators, since these constitute, via renormalization group evolution, the leading new-physics deformations in top-quark pair production. We investigate the impact of our results on the parameter space of composite Higgs models with a strongly-coupled (right-handed) top quark, finding that four-top probes provide the best sensitivity on the compositeness scale at the future energy frontier. In addition, we investigate mild yet persisting LHC excesses in multilepton plus jets final states, showing that they can be consistently described in the effective field theory of such a new-physics scenario.
Evaluating the Effect of Audience in a Virtual Reality Presentation Training Tool

Public speaking is an essential skill in everyone's professional or academic career. Nevertheless, honing this skill is often tricky because training in front of a mirror does not give feedback or inspire the same anxiety as present-ing in front of an audience. Further, most people do not always have access to the place where the presentation will happen. In this research, we developed a Virtual Reality (VR) environment to assist in improving people's presentation skills. Our system uses 3D scanned people to create more realistic scenarios. We conducted a study with twelve participants who had no prior experience with VR. We validated our virtual environment by analyzing whether it was preferred to no VR system and accepted regardless of the existence of a virtual audience. Our results show that users overwhelmingly prefer to use the VR system as a tool to help them improve their public speaking skills than training in an empty environment. However, the preference for an audience is mixed.
SLEDGE: A Simple Yet Effective Zero-Shot Baseline for Coronavirus Scientific Knowledge Search

With worldwide concerns surrounding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of scientific literature on the virus. Clinicians, researchers, and policy-makers need to be able to search these articles effectively. In this work, we present a zero-shot ranking algorithm that adapts to COVID-related scientific literature. Our approach filters training data from another collection down to medical-related queries, uses a neural re-ranking model pre-trained on scientific text (SciBERT), and filters the target document collection. This approach ranks top among zero-shot methods on the TREC COVID Round 1 leaderboard, and exhibits a P@5 of 0.80 and an nDCG@10 of 0.68 when evaluated on both Round 1 and 2 judgments. Despite not relying on TREC-COVID data, our method outperforms models that do. As one of the first search methods to thoroughly evaluate COVID-19 search, we hope that this serves as a strong baseline and helps in the global crisis.
Neural-network-driven proton decay sensitivity in the $p\rightarrow \bar{\nu} K^{+}$ channel using large liquid argon time projection chambers

We report on an updated sensitivity for proton decay via $p \rightarrow \bar{\nu} K^+ $ at large, dual phase liquid argon time projection chambers (LAr TPCs). Our work builds on a previous study in which several nucleon decay channels have been simulated and analyzed [arXiv:hep-ph/0701101]. At the time several assumptions were needed to be made on the detector and the backgrounds. Since then, the community has made progress in defining these, and the computing power available enables us to fully simulate and reconstruct large samples in order to perform a better estimate of the sensitivity to proton decay. In this work, we examine the benchmark channel $p\rightarrow \bar{\nu} K^{+}$, which was previously found to be one of the cleanest channels. Using an improved neutrino event generator and a fully simulated LAr TPC detector response combined with a dedicated neural network for kaon identification, we demonstrate that a lifetime sensitivity of $ \tau / \text{Br} \left( p \rightarrow \bar{\nu} K^+ \right) > 7 \times 10^{34} \, \text{years}$ at $90 \, \%$ confidence level can be reached at an exposure of $1 \, \text{megaton} \cdot \text{year}$ in quasi-background-free conditions, confirming the superiority of the LAr TPC over other technologies to address the challenging proton decay modes.
Modeling the Music Genre Perception across Language-Bound Cultures

The music genre perception expressed through human annotations of artists or albums varies significantly across language-bound cultures. These variations cannot be modeled as mere translations since we also need to account for cultural differences in the music genre perception. In this work, we study the feasibility of obtaining relevant cross-lingual, culture-specific music genre annotations based only on language-specific semantic representations, namely distributed concept embeddings and ontologies. Our study, focused on six languages, shows that unsupervised cross-lingual music genre annotation is feasible with high accuracy, especially when combining both types of representations. This approach of studying music genres is the most extensive to date and has many implications in musicology and music information retrieval. Besides, we introduce a new, domain-dependent cross-lingual corpus to benchmark state of the art multilingual pre-trained embedding models.
Higher-Order Recursion Schemes and Collapsible Pushdown Automata: Logical Properties

This article studies the logical properties of a very general class of infinite ranked trees, namely, those generated by higher-order recursion schemes. We consider, for both monadic second-order logic and modal -calculus, three main problems: model-checking, logical reflection (a.k.a. global model-checking, that asks for a finite description of the set of elements for which a formula holds), and selection (that asks, if exists, for some finite description of a set of elements for which an MSO formula with a second-order free variable holds). For each of these problems, we provide an effective solution. This is obtained, thanks to a known connection between higher-order recursion schemes and collapsible pushdown automata and on previous work regarding parity games played on transition graphs of collapsible pushdown automata.