Miracle-dz/UniFAR-FTUs huggingface dataset:
Maze: A Cost-Efficient Video Deduplication System at Web-scale

With the advancement and dominant service of Internet videos, the content-based video deduplication system becomes an essential and dependent infrastructure for Internet video service. However, the explosively growing video data on the Internet challenges the system design and implementation for its scalability in several ways. (1) Although the quantization-based indexing techniques are effective for searching visual features at a large scale, the costly re-training over the complete dataset must be done periodically. (2) The high-dimensional vectors for visual features demand increasingly large SSD space, degrading I/O performance. (3) Videos crawled from the Internet are diverse, and visually similar videos are not necessarily the duplicates, increasing deduplication complexity. (4) Most videos are edited ones. The duplicate contents are more likely discovered as clips inside the videos, demanding processing techniques with close attention to details. To address above-mentioned issues, we propose Maze, a full-fledged video deduplication system. Maze has an ANNS layer that indexes and searches the high dimensional feature vectors. The architecture of the ANNS layer supports efficient reads and writes and eliminates the data migration caused by re-training. Maze adopts the CNN-based feature and the ORB feature as the visual features, which are optimized for the specific video deduplication task. The features are compact and fully reside in the memory. Acoustic features are also incorporated in Maze so that the visually similar videos but having different audio tracks are recognizable. A clip-based matching algorithm is developed to discover duplicate contents at a fine granularity. Maze has been deployed as a production system for two years. It has indexed 1.3 billion videos and is indexing ~800 thousand videos per day. For the ANNS layer, the average read latency is 4 seconds and the average write latency is at most 4.84 seconds. The re-training over the complete dataset is no longer required no matter how many new data sets are added, eliminating the costly data migration between nodes. Maze recognizes the duplicate live streaming videos with both the similar appearance and the similar audio at a recall of 98%. Most importantly, Maze is also cost-effective. For example, the compact feature design helps save 5800 SSDs and the computation resources devoted to running the whole system decrease to 250K standard cores per billion videos.
The GEEC2 spectroscopic survey of Galaxy groups at 0.8 < z < 1

We present the data release of the Gemini-South GMOS spectroscopy in the fields of 11 galaxy groups at $0.8 50$ per cent complete for galaxies within the virial radius, and with stellar mass $M_{\rm star}>10^{10.3}M_\odot$. Including galaxies with photometric redshifts we have an effective sample size of $\sim 400$ galaxies within the virial radii of these groups. We present group velocity dispersions, dynamical and stellar masses. Combining with the GCLASS sample of more massive clusters at the same redshift we find the total stellar mass is strongly correlated with the dynamical mass, with $\log{M_{200}}=1.20\left(\log{M_{\rm star}}-12\right)+14.07$. This stellar fraction of $~\sim 1$ per cent is lower than predicted by some halo occupation distribution models, though the weak dependence on halo mass is in good agreement. Most groups have an easily identifiable most massive galaxy (MMG) near the centre of the galaxy distribution, and we present the spectroscopic properties and surface brightness fits to these galaxies. The total stellar mass distribution in the groups, excluding the MMG, compares well with an NFW profile with concentration $4$, for galaxies beyond $\sim 0. 2R_{200}$. This is more concentrated than the number density distribution, demonstrating that there is some mass segregation.
Two loop QCD vertices at the symmetric point

We compute the triple gluon, quark-gluon and ghost-gluon vertices of QCD at the symmetric subtraction point at two loops in the MSbar scheme. In addition we renormalize each of the three vertices in their respective momentum subtraction schemes, MOMggg, MOMq and MOMh. The conversion functions of all the wave functions, coupling constant and gauge parameter renormalization constants of each of the schemes relative to MSbar are determined analytically. These are then used to derive the three loop anomalous dimensions of the gluon, quark, Faddeev-Popov ghost and gauge parameter as well as the beta-function in an arbitrary linear covariant gauge for each MOM scheme. There is good agreement of the latter with earlier Landau gauge numerical estimates of Chetyrkin and Seidensticker.
Topological order in the Kitaev/Majorana chain in the presence of disorder and interactions

We study the combined effect of interactions and disorder on topological order in one dimension. Toward that end, we consider a generalized Kitaev chain including fermion-fermion interactions and disorder in the chemical potential. We determine the phase diagram by performing density-matrix renormalization-group calculations on the corresponding spin-1/2 chain. We find that moderate disorder or repulsive interactions individually stabilize the topological order, which remains valid for their combined effect. However, both repulsive and attractive interactions lead to a suppression of the topological phase at strong disorder.
Nature of the 5f states in actinide metals

Actinide elements produce a plethora of interesting physical behaviors due to the 5f states. This review compiles and analyzes progress in understanding of the electronic and magnetic structure of the 5f states in actinide metals. Particular interest is given to electron energy-loss spectroscopy and many-electron atomic spectral calculations, since there is now an appreciable library of core d -> valence f transitions for Th, U, Np, Pu, Am, and Cm. These results are interwoven and discussed against published experimental data, such as x-ray photoemission and absorption spectroscopy, transport measurements, and electron, x-ray, and neutron diffraction, as well as theoretical results, such as density-functional theory and dynamical mean-field theory.
Feeling Without Sharing: A Federated Video Emotion Recognition Framework Via Privacy-Agnostic Hybrid Aggregation

The explosion of video data brings new opportunities and challenges for emotion recognition. Video emotion applications have great commercial value, but the potential to involve illegal snooping on personal feelings has led to controversy over privacy protection. The federated learning (FL) paradigm can substantially address the growing public concerns about data privacy in video emotion recognition. However, conventional FL methods perform poorly due to the uniqueness of the task: the data are heterogeneous across clients induced by emotional label skew and cross-culture expression differences. To mitigate the heterogeneous data, we propose EmoFed, a practical framework of federated learning video-based emotion recognition via multi-group clustering and privacy-agnostic hybrid aggregation. It yields a generically applicable and improved model while protecting privacy, which trains local models under group-aware personalized aggregation. To further encourage communicating comprehensive and privacy-agnostic information among clients, we upload model parameters of both the global layers and personalization layers to the server. We utilize the homomorphically encrypted method for personalization layers, which incurs no learning accuracy loss since no noise is added to the model updates during the encryption/decryption process. The proposed method works on video-based emotion recognition tasks to predict actors' emotional expressions and induced emotion by viewers. Extensive experiments and ablation studies on four benchmarks have demonstrated the efficacy and practicability of our method.
THE SAGITTARIUS DWARF GALAXY: A MODEL FOR EVOLUTION IN A TRIAXIAL MILKY WAY HALO

We present a new N-body model for the tidal disruption of the Sagittarius (Sgr) dwarf that is capable of simultaneously satisfying the majority of angular position, distance, and radial velocity constraints imposed by current wide-field surveys of its dynamically young (≲3 Gyr) tidal debris streams. In particular, this model resolves the conflicting angular position and radial velocity constraints on the Sgr leading tidal stream that have been highlighted in recent years. While the model does not reproduce the apparent bifurcation observed in the leading debris stream, recent observational data suggest that this bifurcation may represent a constraint on the internal properties of the Sgr dwarf rather than the details of its orbit. The key element in the success of this model is the introduction of a non-axisymmetric component to the Galactic gravitational potential that can be described in terms of a triaxial dark matter halo whose minor/major axis ratio (c/a)Φ = 0.72 and intermediate/major axis ratio (b/a)Φ = 0.99 at radii 20 kpc < r < 60 kpc. The minor/intermediate/major axes of this halo lie along the directions (l, b) = (7°, 0°), (0°, 90°), and (97°, 0°) respectively, corresponding to a nearly oblate ellipsoid whose minor axis is contained within the Galactic disk plane. This particular disk/halo orientation is difficult to reconcile within the general context of galactic dynamics (and cold dark matter models in particular), suggesting either that the orientation may have evolved significantly with time or that inclusion of other non-axisymmetric components (such as the gravitational influence of the Magellanic Clouds) in the model may obviate the need for triaxiality in the dark matter halo. The apparent proper motion of Sgr in this model is estimated to be (μlcos b, μb) = (−2.16, 1.73) mas yr−1, corresponding to a Galactocentric space velocity (U, V, W) = (230, −35, 195) km s−1 . Based on the velocity dispersion in the stellar tidal streams, we estimate that Sgr has a current bound mass MSgr = 2.5+1.3−1.0 × 108 M☉. We demonstrate that with simple assumptions about the star formation history of Sgr, tidal stripping models naturally give rise to gradients in the metallicity distribution function (MDF) along the stellar debris streams similar to those observed in recent studies. These models predict a strong evolution in the MDF of the model Sgr dwarf with time, indicating that the chemical abundances of stars in Sgr at the present day may be significantly different than the abundances of those already contributed to the Galactic stellar halo. We conclude by using the new N-body model to re-evaluate previous claims of the association of miscellaneous halo substructure with the Sgr dwarf.
WATER MASERS IN THE ANDROMEDA GALAXY: THE FIRST STEP TOWARD PROPER MOTION

We have detected and confirmed five water maser complexes in the Andromeda Galaxy (M31) using the Green Bank Telescope. These masers will provide the high brightness temperature point sources needed for proper motion studies of M31, enabling measurement of its full three-dimensional velocity vector and its geometric distance via proper rotation. The motion of M31 is the keystone of Local Group dynamics and a gateway to the dark matter profiles of galaxies in general. Our survey for water masers selected 206 luminous compact 24 μm emitting regions in M31 and was sensitive enough to detect any maser useful for ∼10 μas yr−1 astrometry. The newly discovered masers span the isotropic luminosity range (0.3–1.9) × 10−3 L☉ in single spectral components and are analogous to luminous Galactic masers. The masers are distributed around the molecular ring, including locations close to the major and minor axes, which is nearly ideal for proper motion studies. We find no correlation between 24 μm luminosity and water maser luminosity, suggesting that while water masers arise in star-forming regions, the nonlinear amplification pathways and beamed nature of the water masers means that they are not predictable based on IR luminosity alone. This suggests that there are additional bright masers to be found in M31. We predict that the geometric distance and systemic proper motion of M31 can be measured in 2–3 years with current facilities. A “moving cluster” observation of diverging masers as M31 approaches the Galaxy may be possible in the long term.
Simulation-Based Evaluation of Interactive Recommender Systems

Offline data-driven evaluation is considered a low-cost and more accessible alternative for the online empirical method of assessing the quality of recommender systems. Despite their popularity and effectiveness, most data-driven approaches are unsuitable for evaluating interactive recommender systems. In this paper, we attempt to address this issue by simulating the user interactions with the system as a part of the evaluation process. Particularly, we demonstrate that simulated users find their desired item more efficiently when recommendations presented as a list of carousels compared to a simple ranked list.
Kohn anomaly and interplay of electron-electron and electron-phonon interactions in epitaxial graphene

The interplay of electron-phonon (el-ph) and electron-electron (el-el) interactions in epitaxial graphene is studied by directly probing its electronic structure. We found a strong coupling of electrons to the soft part of the A1g phonon evident by a kink at 150+/-15 meV, while the coupling of electrons to another expected phonon E2g at 195 meV can only be barely detected. The possible role of the el-el interaction to account for the enhanced coupling of electrons to the A1g phonon, and the contribution of el-ph interaction to the linear imaginary part of the self energy at high binding energy are also discussed. Our results reveal the dominant role of the A1g phonon in the el-ph interaction in graphene, and highlight the important interplay of el-el and el-ph interactions in the self energy of graphene.
Accretion of pristine gas and dilution during the formation of multiple-population globular clusters

We study the interaction of the early spherical GC wind powered by Type II supernovae (SNe II) with the surrounding ambient medium consisting of the gaseous disk of a star forming galaxy at redshift z ~> 2. The bubble formed by the wind eventually breaks out of the disk, and most of the wind moves directly out of the galaxy and is definitively lost. The fraction of the wind moving nearly parallel to the galactic plane carves a hole in the disk which will contract after the end of the SN activity. During the interval of time between the end of the SN explosions and the "closure" of the hole, very O-poor stars (the Extreme population) can form out of the super-AGB (asymptotic giant branch) ejecta collected in the GC center. Once the hole contracts, the AGB ejecta mix with the pristine gas, allowing the formation of stars with an oxygen abundance intermediate between that of the very O-poor stars and that of the pristine gas. We show that this mechanism may explain why Extreme populations are present only in massive clusters, and can also produce a correlation between the spread in helium and the cluster mass. Finally, we also explore the possibility that our proposed mechanism can be extended to the case of multiple populations showing bimodality in the iron content, with the presence of two populations characterized by a small difference in [Fe/H]. Such a result can be obtained taking into account the contribution of delayed SN II.
The Recurrent Novae and Their Relation with Classical Novae

Recurrent novae (RNe) are a subclass of cataclysmic variables classified based on recorded observations of more than one nova outburst. They form a small, but heterogeneous group of objects, with 10 known members, that undergo classical nova‐like outbursts, with the significant differences being in the amplitude and the frequency of the outbursts. RNe outbursts are of smaller amplitude with lesser energy released as compared to the classical novae. The outbursts occur with intervals of ∼ 10 – 100 yr. Some RNe systems are short period binaries similar to the classical novae, while other members of this group are long period binaries, with orbital periods of the order of several hundred days and consist of a hot white dwarf and a red giant similar to the symbiotic stars. It is widely believed that the white dwarfs in RNe are massive and close to the Chandrasekhar limit. The mass transfer rate from the companion is high, of the order of ∼ 10−7 M⊙ yr−1. The massive white dwarf and the high mass‐transfer rates.
C3CMR: Cross-Modality Cross-Instance Contrastive Learning for Cross-Media Retrieval

Cross-modal retrieval is an essential area of representation learning, which aims to retrieve instances with the same semantics from different modalities. In real implementation, a key challenge for cross-modal retrieval is to narrow the heterogeneity gap between different modalities and obtain modality-invariant and discriminative features. Typically, existing approaches for this task mainly learn inter-modal invariance and focus on how to combine pair-level loss and class-level loss, which cannot effectively and adequately learn discriminative features. To address these issues, in this paper, we propose a novel Cross-Modality Cross-Instance Contrastive Learning for Cross-Media Retrieval (C3CMR) method. Specifically, to fully employ the intra-modal similarities, we introduce the intra-modal contrastive learning to enhance the discriminative power of the unimodal features. Besides, we design a supervised inter-modal contrastive learning scheme to take full advantage of the label semantic associations. In this way, cross-semantic associations and inter-modal invariance can be further learned. Moreover, pertaining to the local suboptimal semantic similarity by only mining pairwise and triplewise sample relationships, we propose the cross-instance contrastive learning to mine the similarities among multiple instances. Comprehensive experimental results on four widely-used benchmark datasets demonstrate the superiority of our proposed method over several state-of-the-art cross-modal retrieval methods.
Cyclical Fusion: Accurate 3D Reconstruction via Cyclical Monotonicity

The dense correspondence estimation is crucial to RGB-D reconstruction systems. However, the projective correspondences are highly unreliable due to sensor depth and pose uncertainties. To tackle this challenge, we introduce a geometry-driven fusion framework, Cyclical Fusion. It pushes the correspondence finding forward to the 3D space instead of searching for candidates on the 2.5D projective map. Moreover, it establishes precise correspondence in two phases, coarse to fine. 1) First, the local surface (represented by a voxel) is characterized by Gaussian distribution. The Karcher-Frechet barycenter is adapted to conduct the robust approximation of covariance. Then, the metric between distributions is calculated via the L2-Wasserstein distance, and the correspondence voxel can be discovered through the nearest distribution-to-distribution model. 2) Our method utilizes an effective correspondence verification scheme derived from cyclical monotonicity related to Rockafellar's theorem. The concept of cyclical monotonicity reveals the geometrical nature of correspondences. A substantial constraint prevents the correspondences from twisting during the fusion process. Accordingly, precise point-to-point correspondence can be discovered. 3) The advection between correspondences is used to form a smooth manifold under regularization terms. Finally, Cyclical Fusion is integrated into a prototype reconstruction system (utilize multiple streams: depth, pose, RGB, and infrared). Experimental results on different benchmarks and real-world scanning verify the superior performance of the proposed method. Cyclical Fusion accomplishes the most authentic reconstruction for which the original projective correspondence-based scheme failed (See Fig.1). Our new techniques make the reconstruction applicable for multimedia content creation and many others.
STEAM for non-novice STEM students with Digital Musical Instruments

STEAM education extends STEM (Science, Technology, Engineering, and Mathematics) with Arts, often with the aim to attract newcomers to technical disciplines. We present and report on a university STEAM course implemented for non-novice STEM students: advanced Computer Science students with little or no musical background designed, built, and performed with Digital Musical Instruments. We examine the collected quantitative and qualitative data (attendance, dropouts, feedback, homework submissions, participation metrics) in the light of qualities and deficits of STEAM discussed in the literature. Our results coincide with purported beneficial outcomes of STEAM such as a growth in skills, evidenced for instance by our students’ success acquiring and applying both new technologies and musical insights. Furthermore, we avoid common pitfalls such as an unclear extent and role of artistic content and issues in the practical course implementation through thorough planning. This is corroborated by the students’ sustained participation and positive feedback.
Quotation and Narration in Contemporary Popular Fiction in Swedish - Stylometric Explorations

A fundamental feature of many genres of fiction is the alternation between a narrative frame (NF) and quoted inset (QI) dialogue. Both formal and representational features distinguish NF and QI segments. This paper is an explorative study on the stylistic differentiation between frame and inset material in recent commercially successful fiction in Swedish. There are mainly two orthographic options as regards this distinction: Explicitly enclosing inset segments within quotation marks is one. Using an initial dash to indicate utterance display is another, in which case frame and inset material typically alternate in a way not made explicit by the orthography. The corpus behind the present study comprised 450 novels. In order to deal with dash orthography data (135 books), we trained a multilayer perceptron classifier to tell NF and QI segments apart. We relied on the fact that native quotation mark text can be converted to annotated dash orthography data, which can then be used for supervised training and validation. A small-scale manual evaluation on the texts we aim to analyze, yielded an accuracy score around 95%. In order to explore the stylometric relations between NF and QI components in the novels, we looked at a selection of basic grammatical features. A characterization of each feature was made by means of recording the fraction of works in which the relative frequency of the feature is higher in QI than in NF. This summarizes how authors tend to “use” that feature to create a contrast between NF and QI. Another way to examine how the NF and QI styles are related is to apply a correlation test. We then saw, for instance, that QI material in 100% of the books are denser in auxiliary verbs, second person pronouns, and interjections, while NF segments in all or almost all cases are denser in nouns, adjectives, third person pronouns, and prepositions. We could also observe that e.g. noun density in NF and QI correlate in a strong way. The same holds for adverbs and cardinal numerals. This suggests that books and authors exhibit stylistic tendencies which affect both narrator and the characters, as far as the kind of fiction we have studied go.
Deep connection between f(R) gravity and the interacting dark sector model

We examine the conformal equivalence between the f(R) gravity and the interacting dark sector model. We review the well-known result that the conformal transformation physically corresponds to the mass dilation that marks the strength of interaction between dark sectors. Instead of modeling f(R) gravity in the Jordan frame, we construct the f(R) gravity in terms of mass dilation function in the Einstein frame. We find that the condition to keep f(R) gravity consistent with CMB observations ensures the energy flow from dark energy to dark matter in the corresponding interacting model, which meets the requirement to alleviate the coincidence problem in the Einstein framework.