Miracle-dz/UniFAR-FTUs huggingface dataset:
A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics

Inspired by humans’ remarkable ability to master arithmetic and generalize to unseen problems, we present a new dataset, H INT , to study ma-chines’ capability of learning generalizable concepts at three different levels: perception , syntax , and semantics . In particular, concepts in H INT , including both digits and operators, are required to learn in a weakly-supervised fashion: Only the ﬁnal results of handwriting expressions are provided as supervision. Learning agents need to reckon how concepts are perceived from raw signals such as images ( i.e ., perception), how multiple concepts are structurally combined to form a valid expression ( i.e ., syntax), and how concepts are realized to afford various reasoning tasks ( i.e ., semantics). With a focus on systematic generalization, we carefully design a ﬁve-fold test set to evaluate both the interpolation and the extrapolation of learned concepts. To tackle this challenging problem, we propose a neural-symbolic system by integrating neural networks with grammar parsing and program synthesis, learned by a novel deduction–abduction strategy. In experiments, the proposed neural-symbolic system demonstrates strong generalization capability and signiﬁcantly outperforms end-to-end neural methods like RNN and Transformer. The results also indicate the signiﬁcance of recursive priors for extrapolation on syntax and semantics.
Slow-Growing Trees

Random Forest's performance can be matched by a single slow-growing tree (SGT), which uses a learning rate to tame CART's greedy algorithm. SGT exploits the view that CART is an extreme case of an iterative weighted least square procedure. Moreover, a unifying view of Boosted Trees (BT) and Random Forests (RF) is presented. Greedy ML algorithms' outcomes can be improved using either"slow learning"or diversification. SGT applies the former to estimate a single deep tree, and Booging (bagging stochastic BT with a high learning rate) uses the latter with additive shallow trees. The performance of this tree ensemble quaternity (Booging, BT, SGT, RF) is assessed on simulated and real regression tasks.
LoBSTr: Real‐time Lower‐body Pose Prediction from Sparse Upper‐body Tracking Signals

With the popularization of games and VR/AR devices, there is a growing need for capturing human motion with a sparse set of tracking data. In this paper, we introduce a deep neural network (DNN) based method for real‐time prediction of the lower‐body pose only from the tracking signals of the upper‐body joints. Specifically, our Gated Recurrent Unit (GRU)‐based recurrent architecture predicts the lower‐body pose and feet contact states from a past sequence of tracking signals of the head, hands, and pelvis. A major feature of our method is that the input signal is represented by the velocity of tracking signals. We show that the velocity representation better models the correlation between the upper‐body and lower‐body motions and increases the robustness against the diverse scales and proportions of the user body than position‐orientation representations. In addition, to remove foot‐skating and floating artifacts, our network predicts feet contact state, which is used to post‐process the lower‐body pose with inverse kinematics to preserve the contact. Our network is lightweight so as to run in real‐time applications. We show the effectiveness of our method through several quantitative evaluations against other architectures and input representations with respect to wild tracking data obtained from commercial VR devices.
A Nearby Repeating Fast Radio Burst in the Direction of M81

We report on the discovery of FRB 20200120E, a repeating fast radio burst (FRB) with a low dispersion measure (DM) detected by the Canadian Hydrogen Intensity Mapping Experiment FRB project. The source DM of 87.82 pc cm−3 is the lowest recorded from an FRB to date, yet it is significantly higher than the maximum expected from the Milky Way interstellar medium in this direction (∼50 pc cm−3). We have detected three bursts and one candidate burst from the source over the period 2020 January–November. The baseband voltage data for the event on 2020 January 20 enabled a sky localization of the source to within ≃14 arcmin2 (90% confidence). The FRB localization is close to M81, a spiral galaxy at a distance of 3.6 Mpc. The FRB appears on the outskirts of M81 (projected offset ∼20 kpc) but well inside its extended H i and thick disks. We empirically estimate the probability of a chance coincidence with M81 to be <10−2. However, we cannot reject a Milky Way halo origin for the FRB. Within the FRB localization region, we find several interesting cataloged M81 sources and a radio point source detected in the Very Large Array Sky Survey. We search for prompt X-ray counterparts in Swift Burst Alert Telescope and Fermi/GBM data, and, for two of the FRB 20200120E bursts, we rule out coincident SGR 1806−20-like X-ray bursts. Due to the proximity of FRB 20200120E, future follow-up for prompt multiwavelength counterparts and subarcsecond localization could be constraining of proposed FRB models.
Microwave amplitude reflecting instability of LFP electrode ground field is useful for consciousness state identification

— Goal: We recently developed EEG indices that correlated with anesthesia concentration in dogs by focusing on microwaves of flattish period (named τ ). Aims of this study are to discriminate conscious states of mice using our original indices on LFP and to explore the principle of τ . Methods: We analyzed 20h LFP with various sampling rates at layer 5 of secondary motor cortex (M2) and primary somatosensory cortex (S1) in 6 mice. τ is defined as a subthreshold wave and burst wave is defined as an above-threshold wave. For every 60s LFP, the number of τ (N τ ), duration of τ (M τ ), and amplitude of burst (Abst) were computed with various thresholds. Results: Changes of new indices against changes of threshold showed the same pattern in all cases, whereas the results of frequency analysis varied. Those indices well quantified the morphological features of waveforms in milliseconds and made it possible to discriminate the specific waveforms of the state of consciousness; awake, shallow sleep, rapid eye movement (REM) sleep, and non-rapid eye movement (NREM) sleep. On the other hand, microwaves often fluctuated for each sample at any rate. N τ reached the maximum when M τ was about 2.5 to 3.0 sampling intervals in any state, and that threshold decreased in state order of awake, shallow sleep, REM sleep, and NREM sleep (p< 10 -5 ). Threshold differences between NREM and REM sleep states were more pronounce in S1 than M2. Conclusion: Microwaves were local fluctuations of electrode, whose amplitude correlated to level of consciousness.
Online Orthogonal Dictionary Learning Based on Frank–Wolfe Method

Dictionary learning is a widely used unsupervised learning method in signal processing and machine learning. Most existing works on dictionary learning adopt an off-line approach, and there are two main off-line ways of conducting it. One is to alternately optimize both the dictionary and the sparse code, while the other is to optimize the dictionary by restricting it over the orthogonal group. The latter, called orthogonal dictionary learning (ODL), has a lower implementation complexity and, hence, is more favorable for low-cost devices. However, existing schemes for ODL only work with batch data and cannot be implemented online, making them inapplicable for real-time applications. This article, thus, proposes a novel online orthogonal dictionary scheme to dynamically learn the dictionary from streaming data, without storing the historical data. The proposed scheme includes a novel problem formulation and an efficient online algorithm design with convergence analysis. In the problem formulation, we relax the orthogonal constraint to enable an efficient online algorithm. We then propose the design of a new Frank–Wolfe-based online algorithm with a convergence rate of $\mathcal {O}(\ln t/t^{1/4})$ . The convergence rate in terms of key system parameters is also derived. Experiments with synthetic data and real-world Internet of things (IoT) sensor readings demonstrate the effectiveness and efficiency of the proposed online ODL scheme.
Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing

Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to process and analyze these hyperspectral (HS) products mainly by means of seasoned experts. However, with the ever-growing volume of data, the bulk of costs in manpower and material resources poses new challenges on reducing the burden of manual labor and improving efficiency. For this reason, it is, therefore, urgent to develop more intelligent and automatic approaches for various HS RS applications. Machine learning (ML) tools with convex optimization have successfully undertaken the tasks of numerous artificial intelligence (AI)-related applications. However, their ability in handling complex practical problems remains limited, particularly for HS data, due to the effects of various spectral variabilities in the process of HS imaging and the complexity and redundancy of higher dimensional HS signals. Compared to the convex models, non-convex modeling, which is capable of characterizing more complex real scenes and providing the model interpretability technically and theoretically, has been proven to be a feasible solution to reduce the gap between challenging HS vision tasks and currently advanced intelligent data processing models.
A Survey On Universal Adversarial Attack

The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of universal adversarial perturbations (UAPs), i.e. a single perturbation to fool the target DNN for most images. With the focus on UAP against deep classifiers, this survey summarizes the recent progress on universal adversarial attacks, discussing the challenges from both the attack and defense sides, as well as the reason for the existence of UAP. We aim to extend this work as a dynamic survey that will regularly update its content to follow new works regarding UAP or universal attack in a wide range of domains, such as image, audio, video, text, etc. Relevant updates will be discussed at: https://bit.ly/2SbQlLG. We welcome authors of future works in this field to contact us for including your new findings.
Hubble Frontier Field Clusters and Their Parallel Fields: Photometric and Photometric Redshift Catalogs

We present a multiband analysis of the six Hubble Frontier Field clusters and their parallel fields, producing catalogs with measurements of source photometry and photometric redshifts. We release these catalogs to the public along with maps of intracluster light and models for the brightest galaxies in each field. This rich data set covers a wavelength range from 0.2 to 8 μm, utilizing data from the Hubble Space Telescope, Keck Observatories, Very Large Telescope array, and Spitzer Space Telescope. We validate our products by injecting into our fields and recovering a population of synthetic objects with similar characteristics to those in real extragalactic surveys. The photometric catalogs contain a total of over 32,000 entries, with 50% completeness at a threshold of magAB ∼ 29.1 for unblended sources and magAB ∼ 29 for blended ones, in the IR-weighted detection band. Photometric redshifts were obtained by means of template fitting and have an average outlier fraction of 10.3% and scatter σ = 0.067 when compared to spectroscopic estimates. The software we devised, after being tested in the present work, will be applied to new data sets from ongoing and future surveys.
An Empirical Study of the Landscape of Open Source Projects in Baidu, Alibaba, and Tencent

Open source software has drawn more and more attention from researchers, developers and companies nowadays. Meanwhile, many Chinese technology companies are embracing open source and choosing to open source their projects. Nevertheless, most previous studies are concentrated on international companies such as Microsoft or Google, while the practical values of open source projects of Chinese technology companies remain unclear. To address this issue, we conduct a mixed-method study to investigate the landscape of projects open sourced by three large Chinese technology companies, namely Baidu, Alibaba, and Tencent (BAT). We study the categories and characteristics of open source projects, the developer's perceptions towards open sourcing effort for these companies, and the internationalization effort of their open source projects. We collected 1,000 open source projects that were open sourced by BAT in GitHub and performed an online survey that received 101 responses from developers of these projects. Some key findings include: 1) BAT prefer to open source frontend development projects, 2) 88% of the respondents are positive towards open sourcing software projects in their respective companies, 3) 64% of the respondents reveal that the most common motivations for BAT to open source their projects are the desire to gain fame, expand their influence and gain recruitment advantage, 4) respondents believe that the most common internationalization effort is "providing an English version of readme files", 5) projects with more internationalization effort (i.e., include an English readme file) are more popular. Our findings provide directions for software engineering researchers and provide practical suggestions to software developers and Chinese technology companies.
The acoustics of churches

The acoustical requirements of churches and the problems which arise in meeting them are reviewed, particularly in respect of the influence of reverberation. Attenuation may be predicted from first principles with uniformly distributed absorption. When non-uniform, due to the concentrated absorption of blocks of pews, attenuation is greater than that predicted. Decay traces recorded in pews have an initial steep inclination followed by one less steep, an explanation of which is suggested. Of two parish churches examined one has acoustics good for music and for speech. The other illustrates the musical difficulties which can be caused by insufficient reverberation.
X-ray shapes of elliptical galaxies and implications for self-interacting dark matter

Several proposed models for dark matter posit the existence of self-interaction processes that can impact the shape of dark matter halos, making them more spherical than the ellipsoidal halos of collisionless dark matter. One method of probing the halo shapes, and thus the strength of the dark matter self-interaction, is by measuring the shape of the X-ray gas that traces the gravitational potential in relaxed elliptical galaxies. In this work we identify a sample of 11 relaxed, isolated elliptical galaxies and measure the ellipticity of the gravitating matter using X-ray images from the XMM-Newton and Chandra telescopes. We explore a variety of different mass configurations and find that the dark matter halos of these galaxies have ellipticities around ϵ ≃ 0.2-0.5. While we find non-negligible scatter in the ellipticity distribution, our results are consistent with some degree of self-interaction at the scale of σ/m ∼ 1 cm2/g, yet they also remain compatible with a cold dark matter scenario. We additionally demonstrate how our results can be used to directly constrain specific dark matter models and discuss implications for current and future simulations of self-interacting dark matter models.
Heavy Tetraquarks in the Relativistic Quark Model

We give a review of the calculations of the masses of tetraquarks with two and four heavy quarks in the framework of the relativistic quark model based on the quasipotential approach and QCD. The diquark-antidiquark picture of heavy tetraquarks is used. The quasipotentials of the quark-quark and diquark-antidiquark interactions are constructed similarly to the previous consideration of mesons and baryons. Diquarks are considered in the colour triplet state. It is assumed that the diquark and antidiquark interact in the tetraquark as a whole and the internal structure of the diquarks is taken into account by the calculated form factor of the diquark-gluon interaction. All parameters of the model are kept fixed from our previous calculations of meson and baryon properties. A detailed comparison of the obtained predictions for heavy tetraquark masses with available experimental data is given. Many candidates for tetraquarks are found. It is argued that the structures in the di-J/ψ mass spectrum observed recently by the LHCb collaboration can be interpreted as ccc¯c¯ tetraquarks.
Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrhoeal disease in Ifanadiana, rural Madagascar

Precision health mapping is a technique that uses spatial relationships between socio-ecological variables and disease to map the spatial distribution of disease, particularly for diseases with strong environmental signatures, such as diarrhoeal disease (DD). While some studies use GPS-tagged location data, other precision health mapping efforts rely heavily on data collected at coarse-spatial scales and may not produce operationally relevant predictions at fine enough spatio-temporal scales to inform local health programmes. We use two fine-scale health datasets collected in a rural district of Madagascar to identify socio-ecological covariates associated with childhood DD. We constructed generalized linear mixed models including socio-demographic, climatic and landcover variables and estimated variable importance via multi-model inference. We find that socio-demographic variables, and not environmental variables, are strong predictors of the spatial distribution of disease risk at both individual and commune-level (cluster of villages) spatial scales. Climatic variables predicted strong seasonality in DD, with the highest incidence in colder, drier months, but did not explain spatial patterns. Interestingly, the occurrence of a national holiday was highly predictive of increased DD incidence, highlighting the need for including cultural factors in modelling efforts. Our findings suggest that precision health mapping efforts that do not include socio-demographic covariates may have reduced explanatory power at the local scale. More research is needed to better define the set of conditions under which the application of precision health mapping can be operationally useful to local public health professionals.
Cuttlefish exert self-control in a delay of gratification task

The ability to exert self-control varies within and across taxa. Some species can exert self-control for several seconds whereas others, such as large-brained vertebrates, can tolerate delays of up to several minutes. Advanced self-control has been linked to better performance in cognitive tasks and has been hypothesized to evolve in response to specific socio-ecological pressures. These pressures are difficult to uncouple because previously studied species face similar socio-ecological challenges. Here, we investigate self-control and learning performance in cuttlefish, an invertebrate that is thought to have evolved under partially different pressures to previously studied vertebrates. To test self-control, cuttlefish were presented with a delay maintenance task, which measures an individual's ability to forgo immediate gratification and sustain a delay for a better but delayed reward. Cuttlefish maintained delay durations for up to 50–130 s. To test learning performance, we used a reversal-learning task, whereby cuttlefish were required to learn to associate the reward with one of two stimuli and then subsequently learn to associate the reward with the alternative stimulus. Cuttlefish that delayed gratification for longer had better learning performance. Our results demonstrate that cuttlefish can tolerate delays to obtain food of higher quality comparable to that of some large-brained vertebrates.
Strong and Significant Associations of Single Nucleotide Variants (SNVs) in the Promoter and 3'-Untranslated Region (3'-UTR) of Vascular Endothelial Growth Factor (VEGF) Gene with Head and Neck Cancers

Vascular Endothelial Growth Factor (VEGF) has a potent role in tumorigenesis and metastasis. VEGF gene is highly polymorphic. Specific variants have been associated with risk and disease progression in disorders with microvascular involvement such as diabetes mellitus and cancer. However, no study has reported association analysis of common single nucleotide variants (SNVs) in the promoter and 3' untranslated region (3'-UTR) with head and neck cancers (HNCs). The present study addresses this gap. It investigates the association of two SNVs, -2578 C/A (rs699947) in the promoter region and +936 C/T (rs3025039) in 3'-UTR of the VEGF gene, with risk of HNCs and tumour characteristics. After the ethical approval and informed consent, 323 participants were enrolled in the study. In the case-control component of the study, there were 121 HNC patients and 202 controls. Demographic details and medical history were recorded. Peripheral blood samples (10ml) were collected in ACD-coated vacutainers. DNA isolation was carried out by organic-solvent method. PCR-RFLP methods were optimized for the genotyping of selected SNVs. The protocol was validated by Sanger sequencing. The susceptibility association was determined by using genetic models applying Hardy-Weinberg equilibrium. Statistical analyses included Chi-squared test of independence or Fisher's exact test with significance at p-value <0.05, and odds ratios with 95% confidence interval. VEGF -2578 A-allele, A-carrier genotype (dominant model), and AA genotype (co-dominant model) were significantly associated with protective effect against HNCs (p-values <0.01, <0.042, and < 0.009, respectively). The odds ratios (95% CI) were: 0.651 (0.469 - 0.904), 0.613 (0.381 - 0.985), and 0.393 (0.193 - 0.804), respectively. The association analysis of VEGF +936 C/T polymorphism showed that T-allele, CT (over-dominant model), and T-carrier (dominant model) genotypes were significantly associated with the risk for head and neck cancers (p-values < 0.047, < 0.037, and < 0.038, respectively). The odds ratios (95% CI) were 1.882 (1.001 - 3.536); 2.060 (1.035 - 4.102); and 2.023 (1.032 - 3.966), respectively. Additionally, VEGF +936 CT and T-carrier genotypes showed significant associations with higher tumour grade (p-value <0.029, and <0.037). The odds ratios (95% CI) were 10.00 (1.435-72.806) and 9.00 (1.294 - 62.594), respectively. VEGF -2578 C/A and +936 C/T may be further investigated as susceptibility genetic markers for HNCs. Specifically, -2578 A-variant has a protective effect, whereas +936 T-variant increases the risk. Furthermore, +936 CT and T-carrier genotypes are also associated with higher tumour grade. The present study is the first positive association analysis report of both selected SNVs with HNCs in any population.