Miracle-dz/UniFAR-FTUs huggingface dataset:
Smooth Non-Rigid Shape Matching via Effective Dirichlet Energy Optimization

We introduce pointwise map smoothness via the Dirich-let energy into the functional map pipeline, and propose an algorithm for optimizing it efficiently, which leads to highquality results in challenging settings. Specifically, we first formulate the Dirichlet energy of the pulled-back shape coordinates, as a way to evaluate smoothness of a pointwise map across discrete surfaces. We then extend the recently proposed discrete solver and show how a strategy based on auxiliary variable reformulation allows us to optimize pointwise map smoothness alongside desirable functional map properties such as bijectivity. This leads to an efficient map refinement strategy that simultaneously improves functional and point-to-point correspondences, obtaining smooth maps even on non-isometric shape pairs. Moreover, we demonstrate that several previously proposed methods for computing smooth maps can be reformulated as variants of our approach, which allows us to compare different formulations in a consistent framework. Finally, we compare these methods both on existing benchmarks and on a new rich dataset that we introduce, which contains non-rigid, non-isometric shape pairs with inter-category and cross-category correspondences. Our work leads to a general framework for optimizing and analyzing map smoothness both conceptually and in challenging practical settings.
JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMT

JoeyS2T is a JoeyNMT extension for speech-to-text tasks such as automatic speech recognition and end-to-end speech translation. It inherits the core philosophy of JoeyNMT, a minimalist NMT toolkit built on PyTorch, seeking simplicity and accessibility. JoeyS2T's workflow is self-contained, starting from data pre-processing, over model training and prediction to evaluation, and is seamlessly integrated into JoeyNMT's compact and simple code base. On top of JoeyNMT's state-of-the-art Transformer-based encoder-decoder architecture, JoeyS2T provides speech-oriented components such as convolutional layers, SpecAugment, CTC-loss, and WER evaluation. Despite its simplicity compared to prior implementations, JoeyS2T performs competitively on English speech recognition and English-to-German speech translation benchmarks. The implementation is accompanied by a walk-through tutorial and available on https://github.com/may-/joeys2t.
Perturbative BV-BFV formalism with homotopic renormalization: a case study

We report a rigorous quantization of topological quantum mechanics on $\mathbb{R}_{\geqslant 0}$ and $\mathbf{I}= [0, 1]$ in perturbative BV-BFV formalism. Costello's homotopic renormalization is extended, and incorporated in our construction. Moreover, BV quantization of the same model studied in our previous work is derived from the BV-BFV quantization, leading to a comparison between different interpretations of ''state'' in these two frameworks.
Selfsimilarity relations for torsional oscillations of neutron stars

Selfsimilarity relations for torsional oscillation frequencies of neutron star crust are discussed. For any neutron star model, the frequencies of fundamental torsional oscillations (with no nodes of radial wave function, i.e. at n = 0, and at all possible angular wave numbers ℓ ≥ 2) is determined by a single constant. Frequencies of ordinary torsional oscillations (at any n > 0 with ℓ ≥ 2) are determined by two constants. These constants are easily calculated through radial integrals over the neutron star crust, giving the simplest method to determine full oscillation spectrum. All constants for a star of fixed mass can be accurately interpolated for stars of various masses (but the same equation of state). In addition, the torsional oscillations can be accurately studied in the flat space-time approximation within the crust. The results can be useful for investigating magneto-elastic oscillations of magnetars which are thought to be observed as quasi-periodic oscillations after flares of soft-gamma repeaters.
Weak lensing forecasts for dark energy, neutrinos and initial conditions

Weak gravitational lensing provides a sensitive probe of cosmological parameters by measuring the mass distribution and the geometry of the low redshift universe. We show how an all‐sky weak lensing tomographic survey can jointly constrain different sets of cosmological parameters describing dark energy, massive neutrinos, and the primordial power spectrum. Using the Fisher matrix formalism with and without CMB priors, we examine how the constraints vary as the parameter set is enlarged. We find that weak lensing with CMB priors provides robust constraints on dark energy parameters and can simultaneously provide strong constraints on all three parameter sets. We also find that the dark energy sector is largely insensitive to the inclusion of the other cosmological sectors.
DBkWik++ - Multi Source Matching of Knowledge Graphs

Large knowledge graphs like DBpedia and YAGO are always based on the same source, i.e., Wikipedia. But there are more wikis that contain information about long-tail entities such as wiki hosting platforms like Fandom. In this paper, we present the approach and analysis of DBkWik++, a fused Knowledge Graph from thousands of wikis. A modified version of the DBpedia framework is applied to each wiki which results in many isolated Knowledge Graphs. With an incremental merge based approach, we reuse one-to-one matching systems to solve the multi source KG matching task. Based on this alignment we create a consolidated knowledge graph with more than 15 million instances.
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter Video

A single rolling-shutter (RS) image may be viewed as a row-wise combination of a sequence of global-shutter (GS) images captured by a (virtual) moving GS camera within the exposure duration. Although rolling-shutter cameras are widely used, the RS effect causes obvious image distortion especially in the presence of fast camera motion, hindering downstream computer vision tasks. In this paper, we propose to invert the rolling-shutter image capture mechanism, i.e., recovering a continuous high framerate global-shutter video from two time-consecutive RS frames. We call this task the RS temporal super-resolution (RSSR) problem. The RSSR is a very challenging task, and to our knowledge, no practical solution exists to date. This paper presents a novel deep-learning based solution. By leveraging the multi-view geometry relationship of the RS imaging process, our learning based framework successfully achieves high framerate GS generation. Specifically, three novel contributions can be identified: (i) novel formulations for bidirectional RS undistortion flows under constant velocity as well as constant acceleration motion model. (ii) a simple linear scaling operation, which bridges the RS undistortion flow and regular optical flow. (iii) a new mutual conversion scheme between varying RS undistortion flows that correspond to different scanlines. Our method also exploits the underlying spatial-temporal geometric relationships within a deep learning framework, where no additional supervision is required beyond the necessary middle-scanline GS image. Building upon these contributions, this paper represents the very first rolling-shutter temporal super-resolution deep-network that is able to recover high framerate global-shutter videos from just two RS frames. Extensive experimental results on both synthetic and real data show that our proposed method can produce high-quality GS image sequences with rich details, outperforming the state-of-the-art methods.
Three-point correlators: Examples from Lunin-Maldacena background

Recently there has been progress on the calculation of three-point functions with two "heavy" operators via semiclassical methods. We extend this analysis to the case of the Lunin-Maldacena background, and examine the suggested procedure for several simple string solutions. By making use of AdS/CFT duality, we derive the relevant correlation functions of operators belonging to the dual N=1 superconformal gauge theory, and recover an important relation connecting the dimensions of "heavy" states and the structure constants.
Just ClozE! A Novel Framework for Evaluating the Factual Consistency Faster in Abstractive Summarization

The issue of factual consistency in abstractive summarization has received extensive attention in recent years, and the evaluation of factual consistency between summary and document has become an important and urgent task. Most of the current evaluation metrics are adopted from the question answering (QA) or natural language inference (NLI) task. However, the application of QA-based metrics is extremely time-consuming in practice while NLI-based metrics are lack of interpretability. In this paper, we propose a cloze-based evaluation framework called ClozE and show the great potential of the cloze-based metric. It inherits strong interpretability from QA, while maintaining the speed of NLI- level reasoning. We demonstrate that ClozE can reduce the evaluation time by nearly 96% relative to QA-based metrics while retaining their interpretability and performance through experiments on six human-annotated datasets and a meta-evaluation benchmark GO FIGURE (Gabriel et al., 2021). Finally, we discuss three important facets of ClozE in practice, which further shows better overall performance of ClozE compared to other metrics.
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning

In cooperative multi-agent reinforcement learning, a team of agents works together to achieve a common goal. Different environments or tasks may require varying degrees of coordination among agents in order to achieve the goal in an optimal way. The nature of coordination will depend on the properties of the environment -- its spatial layout, distribution of obstacles, dynamics, etc. We term this variation of properties within an environment as heterogeneity. Existing literature has not sufficiently addressed the fact that different environments may have different levels of heterogeneity. We formalize the notions of coordination level and heterogeneity level of an environment and present HECOGrid, a suite of multi-agent RL environments that facilitates empirical evaluation of different MARL approaches across different levels of coordination and environmental heterogeneity by providing a quantitative control over coordination and heterogeneity levels of the environment. Further, we propose a Centralized Training Decentralized Execution learning approach called Stateful Active Facilitator (SAF) that enables agents to work efficiently in high-coordination and high-heterogeneity environments through a differentiable and shared knowledge source used during training and dynamic selection from a shared pool of policies. We evaluate SAF and compare its performance against baselines IPPO and MAPPO on HECOGrid. Our results show that SAF consistently outperforms the baselines across different tasks and different heterogeneity and coordination levels. We release the code for HECOGrid as well as all our experiments.
Parity in Markets - Methods, Costs, and Consequences

Fisher markets are those where buyers with budgets compete for scarce items, a natural model for many real world markets including online advertising. We show how market designers can use taxes or subsidies in Fisher markets to ensure that market equilibrium outcomes fall within certain constraints. We adapt various types of fairness constraints proposed in existing literature to the market case and show who beneﬁts and who loses from these constraints, as well as the extent to which properties of markets including Pareto optimality, envy-freeness, and incentive compatibility are preserved. We ﬁnd that several prior proposed constraints applied to markets can hurt the groups they are intended to help.
Quantum-teleportation benchmarks for independent and identically distributed spin states and displaced thermal states

A successful state-transfer (or teleportation) experiment must perform better than the benchmark set by the 'best' measure and prepare procedure. We consider the benchmark problem for the following families of states: (i) displaced thermal equilibrium states of a given temperature; (ii) independent identically prepared qubits with a completely unknown state. For the first family we show that the optimal procedure is heterodyne measurement followed by the preparation of a coherent state. This procedure was known to be optimal for coherent states and for squeezed states with the 'overlap fidelity' as the figure of merit. Here, we prove its optimality with respect to the trace norm distance and supremum risk. For the second problem we consider n independent and identically distributed (i.i.d.) spin-(1/2) systems in an arbitrary unknown state {rho} and look for the measurement-preparation pair (M{sub n},P{sub n}) for which the reconstructed state {omega}{sub n}:=P{sub n} circle M{sub n}({rho}{sup xn}) is as close as possible to the input state (i.e., parallel {omega}{sub n}-{rho}{sup xn} parallel {sub 1} is small). The figure of merit is based on the trace norm distance between the input and output states. We show that asymptotically with n this problem is equivalent to the first one.more » The proof and construction of (M{sub n},P{sub n}) uses the theory of local asymptotic normality developed for state estimation which shows that i.i. d. quantum models can be approximated in a strong sense by quantum Gaussian models. The measurement part is identical to 'optimal estimation', showing that 'benchmarking' and estimation are closely related problems in the asymptotic set up. « less
Quasar candidate selection and photometric redshift estimation based on SDSS and UKIDSS data

We present a sample of 8498 quasars with both SDSS ugriz optical and UKIDSS Y JHK near-IR photometric data. With this sample, we obtain the median colour-z relations based on 7400 quasars with magnitude uncertainties less than 0.1mag in all bands. By analyzing the quasar colours, we propose an empirical criterion in the Y K vs. g z colour-colour diagram to separate stars and quasars with redshift z < 4, and two other criteria for selecting high redshift quasars. Using the SDSS-UKIDSS colourz relations, we estimate the photometric redshifts of 8498 SDSS-UKIDSS quasars, and find that 85.0% of them are consistent with the spectroscopic redshifts within |�z| < 0.2, which leads to a significant increase of the photometric redshift accuracy than that based on the SDSS colour-z relations only. As two tests, we compare our colour selection criterion with a small UKIDSS/EDR quasar/star sample and a sample of 4671 variable sources in the SDSS Stripe 82 region with both SDSS and UKIDSS data. We find that they can be clearly divided into two classes (quasars and stars) by our criterion in the Y K vs. g z plot. We select 3834 quasar candidates from the variable sources with g < 20.5 in Stripe 82, 826 of them being SDSS quasars and the rest without SDSS spectroscopy. We estimate the photometric redshifts for 3519 quasar candidates with all UKIDSS Y JHK data and find an accuracy of 87.5% within |�z| < 0.2 with the spectroscopic redshifts of 819 SDSS-UKIDSS identified quasars among them. We demonstrate that even at the same spectroscopy limit as SDSS, with our criterion we can at least partially recover the missing quasars with z � 2.7 in SDSS. The SDSS identified quasars only take a small fraction (21.5%) of our quasar candidates selected from the variable sources in Stripe 82, indicating that a deeper spectroscopy is very promising in producing a much larger sample of quasars than SDSS. The implications of our current results to the future Chinese LAMOST quasar survey are also discussed.
Negative conditional entropy of postselected states

We define a quantum entropy conditioned on post-selection which has the von Neumann entropy of pure states as a special case. This conditional entropy can take negative values which is consistent with part of a quantum system containing less information than the whole which can be in a pure state. The definition is based on generalised density operators for postselected ensembles. The corresponding density operators are consistent with the quantum generalisation of classical conditional probabilities following Dirac s formalism of quasiprobability distributions.
Nonclassical interference between independent intrinsically pure single photons at telecommunication wavelength

We demonstrate a Hong-Ou-Mandel interference between two independent, intrinsically pure, heralded single photons from spontaneous parametric down-conversion (SPDC) at telecommunication wavelength. A visibility of $85.5\ifmmode\pm\else\textpm\fi{}8.3%$ was achieved without using any bandpass filter. Thanks to the group-velocity-matched SPDC and superconducting nanowire single-photon detectors (SNSPDs), the fourfold coincidence counts are one order higher than that in the previous experiments. The combination of bright single-photon sources and SNSPDs is a crucial step for future practical quantum infocommunication systems at telecommunication wavelength.
Développement d'une méthode de simulation de couplage fluide-structure à l'aide de la méthode SPH

The Fluid-Structure Interaction (FSI) effects are of great importance for many multi-physical problems in academic researches as well as in engineering sciences. Various types of numerical simulation approaches may be used to investigate the FSI problems in order to get more reliable conception and to avoid unexpected disasters. In this work, the fluid sub-domain is simulated by a hybrid mesh-less method (SPH-ALE), and the structure is discretized by the Finite Element (FE) method. As the fluid is considered as a set of particles, one can easily track the fluid structure interface. An energy-conserving coupling strategy is proposed for transient fluid-structure interaction problems where different time integrators are used for each sub-domain: 2nd order Runge-Kutta scheme for the fluid and Newmark time integrator for the solid. By imposing a normal velocity constraint condition at the interface, this proposed coupling method ensures that neither energy injection nor energy dissipation will occur at the interface so that the interface energy is rigorously zero during the whole period of numerical simulation. This coupling method thus ensures that the coupling simulation shall be stable in time, and secondly, the numerical simulation will converge in time with the minimal convergence rate of all the time integrators chosen for each sub-domain. The proposed method is first applied to a mono-dimensional piston problem in which we verify that this method does not degrade the order of accuracy in time of the used time integrators. Then we use this coupling method to investigate the phenomena of propagation of shock waves across the fluidstructure interface. A good agreement is observed between the numerical results and the analytical solutions in the 1-D shock wave propagation test cases. Finally, some multi-dimensional examples are presented. The results are compared with the ones obtained by other coupling approaches.
The onset and severity of acute opioid toxicity in heroin overdose cases: a retrospective cohort study at a supervised injecting facility in Melbourne, Australia

Abstract Aim To differentiate the severity of acute opioid toxicity and describe both the clinical and physiological features associated with heroin overdose in a cohort of witnessed overdose cases. Methods Witnessed heroin overdose cases over a 12-month period (30 June 2018 – 30 June 2019) at the Medically Supervised Injecting Room (MSIR) in Melbourne, Australia were examined. The severity of acute opioid toxicity was classified according to the level of clinical intervention required to manage the overdose cases where an escalating level of care was provided. Heroin overdose cases were classified into one of three graded severity categories and a fourth complicated heroin overdose category. Results A total of 1218 heroin overdose cases were identified from 60,693 supervised injecting visits over the study period. On the spectrum of toxicity, 78% (n = 955) of overdose cases were classified as Grade 1 severity, 7% (n = 83) as Grade 2 severity, and 13% (n = 161) as Grade 3 acute opioid toxicity severity cases, as well as 2% (n = 19) classified as complicated heroin overdose cases. The median onset time for heroin overdose cases was 17 min (IQR 11–28 min) from the time the individual was ready to prepare and inject heroin until clinical intervention was initiated. Conclusion We demonstrated that heroin overdose is a dynamic illness and cases differ in the severity of acute opioid toxicity. The risk of airway occlusion including positional asphyxia was an early and consistent feature across all levels of toxicity, while exaggerated respiratory depression together with exaggerated depression of consciousness was increasingly observed with greater levels of toxicity. We also demonstrated the importance of early intervention in overdose cases, where in a large cohort of heroin overdose cases there were no fatal outcomes, a very low hospitalisation rate and most cases were able to be managed to clinical resolution on-site.
Evolution of antithrombotic therapy for patients with atrial fibrillation: The prospective global GLORIA-AF registry program

Objective To assess baseline characteristics and antithrombotic treatment (ATT) prescription patterns in patients enrolled in the third phase of the GLORIA-AF Registry Program, evaluate predictors of treatment prescription, and compare results with phase II. Methods GLORIA-AF is a large, global, prospective registry program, enrolling patients with newly diagnosed nonvalvular atrial fibrillation (AF) at risk of stroke. Patients receiving dabigatran were followed for two years in phase II, and all patients were followed for 3 years in phase III. Phase II started when dabigatran became available; phase III started when the characteristics of patients receiving dabigatran became roughly comparable with those receiving vitamin K antagonists (VKAs). Results Between 2014 and 2016, 21,241 patients were enrolled in phase III. In total, 82% of patients were prescribed oral anticoagulation ([OAC]; 59.5% novel/nonvitamin K oral anticoagulants [NOACs], 22.7% VKAs). A further 11% of patients were prescribed antiplatelets without OAC and 7% were prescribed no ATT. A high stroke risk was the main driver of OAC prescription. Factors associated with prescription of VKA over NOAC included type of site, region, physician specialty, and impaired kidney function. Conclusion Over the past few years, data from phase III of GLORIA-AF show that OACs have become the standard treatment option, with most newly diagnosed AF patients prescribed a NOAC. However, in some regions a remarkable proportion of patients remain undertreated. In comparison with phase II, more patients received NOACs in phase III while the prescription of VKA decreased. VKAs were preferred over NOACs in patients with impaired kidney function.