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In this paper, we present a novel dataset captured using a VR headset to record conversations between participants within a physics simulator (AI2-THOR). Our primary objective is to extend the field of co-speech gesture generation by incorporating rich contextual information within referential settings. Participants engaged in various conversational scenarios, all based on referential communication tasks. The dataset provides a rich set of multimodal recordings such as motion capture, speech, gaze, and scene graphs. This comprehensive dataset aims to enhance the understanding and development of gesture generation models in 3D scenes by providing diverse and contextually rich data.

Plasmonic near-field transducers (NFTs) play a key role in administering nanoscale heating for a number of applications ranging from medical devices to next generation data processing technology. We present a novel multi-scale approach, combining quantum many-body perturbation theory with finite-element modelling, to predict the electric and thermal material parameters of various Au-based, noble metal (M) alloys. Specifically, we focus on modelling their performance within an NFT designed to focus high-intensity, sub-diffracted light for technologies such as nanoscale etching, manipulation, sensing, and heat-assisted magnetic recording (HAMR). Elemental Au is the long-standing general-purpose NFT medium due its excellent plasmonic performance at relevant wavelengths. However, elemental Au is a soft, ductile material that tends to extrude and deform in response to extreme temperature gradients. Therefore, alloying Au with other noble metals such as Ag, Cu, Pd or Pt, has attracted considerable interest for improved mechanical and thermal robustness while reaching threshold plasmonic generation at standard optoelectronics operating wavelengths (e.g., $\approx 830$~nm) and approximate high-power NFT temperatures ($\approx 400$~K). We predict that certain Au-Ag alloys may offer improved thermal stability as whole-NFT media compared to elemental Au, alongside plasmonic figures of merit comparable to that of Au. Simulations of certain solid solution Au-Pd/Pt alloys enable us to predict significantly enhanced thermal conductivity. We predict that alloying with Pd at low concentrations $\sim 10\%$ may preserve the NFT performance of Au, while offering the benefits of improved thermal and mechanical stability., Comment: 8 pages, 4 figures, 1 table. Includes Supplemental Material with 10 tables

Burgess et al. have recently introduced the BLOR corrective exchange-correlation functional that is, by construction, the unique simplified rotationally-invariant DFT+U functional that enforces the flat-plane condition separately on each effective orbital of a localized subspace. Detached from the Hubbard model, functionals of this type are both double-counting correction free and, when optimized in situ using appropriate error quantifiers, effectively parameter free. In this work, the extension of the BLOR functional to address many-body errors (mBLOR) is derived. The mBLOR functional is built to enforce the flat-plane condition on the entire subspace, rather than on each orbital individually. In this way inter-orbital errors are corrected on the same footing as the single-particle ones. Focusing on exact test cases with strong inter-orbital interactions, the BLOR and mBLOR functionals were benchmarked against contemporary DFT+U functionals using the total energy extensivity condition on stretched homo-nuclear p-block dimers that represent various self-interaction and static-correlation error regimes. The BLOR functional outperformed all other DFT+$U$ functionals tested, which often act to increase total-energy errors, yet it still yielded large errors in some systems. mBLOR instead yielded low energy errors across all four strongly-correlated dimers, while being constructed using only semi-local approximation ingredients. As mBLOR would not otherwise introduce a band-gap correction in the manner that is a desirable feature of DFT+U, we developed a cost-free technique to reintroduce it automatically by moving the functional's unusual explicit derivative discontinuity into the potential. With this in place, mBLOR is the only known DFT$+U$ functional that opens the bandgap of stretched neutral homo-nuclear dimers without the aid of unphysical spin-symmetry breaking., Comment: 21 pages, 9 figures, and 4 tables

We present the implementation of the Hubbard ($U$) and Hund ($J$) corrected Density Functional Theory (DFT+$U$+$J$) functionality in the Quickstep program, which is part of the CP2K suite. The tensorial and L\"owdin subspace representations are implemented and compared. Full analytical DFT+$U$+$J$ forces are implemented and benchmarked for the tensorial and L\"owdin representations. We also present the implementation of the recently proposed minimum-tracking linear-response method that enables the $U$ and $J$ parameters to be calculated on first principles basis without reference to the Kohn-Sham eigensystem. These implementations are benchmarked against recent results for different materials properties including DFT+$U$ band gap opening in NiO, the relative stability of various polaron distributions in TiO$_2$, the dependence of the calculated TiO$_2$ band gap on +$J$ corrections, and, finally, the role of the +$U$ and +$J$ corrections for the computed properties of a series of the hexahydrated transition metals. Our implementation provides results consistent with those already reported in the literature from comparable methods. We conclude the contribution with tests on the influence of the L\"owdin orthonormalization on the occupancies, calculated parameters, and derived properties.

Non-Gaussianity-based Independent Vector Extraction leads to the famous one-unit FastICA/FastIVA algorithm when the likelihood function is optimized using an approximate Newton-Raphson algorithm under the orthogonality constraint. In this paper, we replace the constraint with the analytic form of the minimum variance distortionless beamformer (MVDR), by which a semi-blind variant of FastICA/FastIVA is obtained. The side information here is provided by a weighted covariance matrix replacing the noise covariance matrix, the estimation of which is a frequent goal of neural beamformers. The algorithm thus provides an intuitive connection between model-based blind extraction and learning-based extraction. The algorithm is tested in simulations and speaker ID-guided speaker extraction, showing fast convergence and promising performance., Comment: accepted for IWAENC 2024

Images and structured tables are essential parts of real-world databases. Though tabular-image representation learning is promising to create new insights, it remains a challenging task, as tabular data is typically heterogeneous and incomplete, presenting significant modality disparities with images. Earlier works have mainly focused on simple modality fusion strategies in complete data scenarios, without considering the missing data issue, and thus are limited in practice. In this paper, we propose TIP, a novel tabular-image pre-training framework for learning multimodal representations robust to incomplete tabular data. Specifically, TIP investigates a novel self-supervised learning (SSL) strategy, including a masked tabular reconstruction task for tackling data missingness, and image-tabular matching and contrastive learning objectives to capture multimodal information. Moreover, TIP proposes a versatile tabular encoder tailored for incomplete, heterogeneous tabular data and a multimodal interaction module for inter-modality representation learning. Experiments are performed on downstream multimodal classification tasks using both natural and medical image datasets. The results show that TIP outperforms state-of-the-art supervised/SSL image/multimodal algorithms in both complete and incomplete data scenarios. Our code is available at https://github.com/siyi-wind/TIP., Comment: 28 pages (including 9 pages of supplementary materials), accepted by ECCV 2024

This paper provides the upper and lower bounds of blowup time and blowup rate as well as the exponential growth estimate of blowup solutions for a pseudo-parabolic equation with singular potential. These results complement the ones obtained in the previous literature.

Although humans engaged in face-to-face conversation simultaneously communicate both verbally and non-verbally, methods for joint and unified synthesis of speech audio and co-speech 3D gesture motion from text are a new and emerging field. These technologies hold great promise for more human-like, efficient, expressive, and robust synthetic communication, but are currently held back by the lack of suitably large datasets, as existing methods are trained on parallel data from all constituent modalities. Inspired by student-teacher methods, we propose a straightforward solution to the data shortage, by simply synthesising additional training material. Specifically, we use unimodal synthesis models trained on large datasets to create multimodal (but synthetic) parallel training data, and then pre-train a joint synthesis model on that material. In addition, we propose a new synthesis architecture that adds better and more controllable prosody modelling to the state-of-the-art method in the field. Our results confirm that pre-training on large amounts of synthetic data improves the quality of both the speech and the motion synthesised by the multimodal model, with the proposed architecture yielding further benefits when pre-trained on the synthetic data. See https://shivammehta25.github.io/MAGI/ for example output., Comment: 13+1 pages, 2 figures, accepted at the Human Motion Generation workshop (HuMoGen) at CVPR 2024

The Galvanostatic Intermittent Titration Technique (GITT) is a ubiquitous method for determining the solid-state diffusivity in lithium-ion battery materials. However, it is notoriously time-consuming and relies upon assumptions whose applicability is questionable. We propose a novel methodology that allows inference of the diffusivity for a more general class of data that is simpler and faster to harvest. We infer the diffusivity (as a function of stoichiometry) by minimising the residual sum of squares between data and solutions to a spherically-symmetric diffusion model in a single representative active material particle. Using data harvested from the NMC cathode of a commercial LG M50 cell we first demonstrate that our method is able to reproduce the diffusivities inferred by the GITT, which requires ten days of galvanostatic intermittent titration data. We then demonstrate that our method reliably reconstructs diffusivity using significantly less data. Despite arising from quick-to-measure data, our method more accurately infers diffusivities. This work is a contribution towards developing faster and more reliable techniques in parameter inference for lithium-ion batteries., Comment: 17 pages, 9 figures

Members of the DFT+U family of functionals are increasingly prevalent methods of addressing errors intrinsic to (semi-) local exchange-correlation functionals at minimum computational cost, but require their parameters U and J to be calculated in situ for a given system of interest, simulation scheme, and runtime parameters. The SCF linear response approach offers ab initio acquisition of the U and has recently been extended to compute the J analogously, which measures localized errors related to exchange-like effects. We introduce a renovated post-processor, the lrUJ utility, together with this detailed best-practices guide, to enable users of the popular, open-source Abinit first-principles simulation suite to engage easily with in situ Hubbard parameters and streamline their incorporation into material simulations of interest. Features of this utility, which may also interest users and developers of other DFT codes, include $n$-degree polynomial regression, error analysis, Python plotting facilities, didactic documentation, and avenues for further developments. In this technical introduction and guide, we place particular emphasis on the intricacies and potential pitfalls introduced by the projector augmented wave (PAW) method, SCF mixing schemes, and non-linear response, several of which are translatable to DFT+U(+J) implementations in other packages., Comment: 46 pages, 6 figures (+3 figures in appendix), 2 tables (+1 table in appendix)

The Niobium surface is almost always covered by a native oxide layer which greatly influences the performance of superconducting devices. Here we investigate the highly stable Niobium oxide overlayer of Nb(110), which is characterised by its distinctive nanocrystal structure as observed by scanning tunnelling microscopy (STM). Our ab-initio density functional theory (DFT) calculations show that a subtle reconstruction in the surface Niobium atoms gives rise to rows of 4-fold coordinated oxygen separated by regions of 3-fold coordinated oxygen. The 4-fold oxygen rows are determined to be the source of the nanocrystal pattern observed in STM, and the two chemical states of oxygen observed in core-level X-ray photoelectron spectroscopy (XPS) are ascribed to the 3-fold and 4-fold oxygens. Furthermore, we find excellent agreement between the DFT calculated electronic structure with scanning tunnelling spectroscopy and valence XPS measurements., Comment: 8 pages, 4 figures, plus 3 pages of Supporting Information

It has long been postulated that within density-functional theory (DFT) the total energy of a finite electronic system is convex with respect to electron count, so that 2 E_v[N_0] <= E_v[N_0 - 1] + E_v[N_0 + 1]. Using the infinite-separation-limit technique, this article proves the convexity condition for any formulation of DFT that is (1) exact for all v-representable densities, (2) size-consistent, and (3) translationally invariant. An analogous result is also proven for one-body reduced density matrix functional theory. While there are known DFT formulations in which the ground state is not always accessible, indicating that convexity does not hold in such cases, this proof nonetheless confirms a stringent constraint on the exact exchange-correlation functional. We also provide sufficient conditions for convexity in approximate DFT, which could aid in the development of density-functional approximations. This result lifts a standing assumption in the proof of the piecewise linearity condition with respect to electron count, which has proven central to understanding the Kohn-Sham band-gap and the exchange-correlation derivative discontinuity of DFT., Comment: This Communication has been published in the Journal of Chemical Physics 159, 211102 (2023) which can be found at the following link: https://doi.org/10.1063/5.0174159

3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardiovascular diseases. Current state-of-the art methods focus on estimating dense pixel-/voxel-wise motion fields in image space, which ignores the fact that motion estimation is only relevant and useful within the anatomical objects of interest, e.g., the heart. In this work, we model the heart as a 3D mesh consisting of epi- and endocardial surfaces. We propose a novel learning framework, DeepMesh, which propagates a template heart mesh to a subject space and estimates the 3D motion of the heart mesh from CMR images for individual subjects. In DeepMesh, the heart mesh of the end-diastolic frame of an individual subject is first reconstructed from the template mesh. Mesh-based 3D motion fields with respect to the end-diastolic frame are then estimated from 2D short- and long-axis CMR images. By developing a differentiable mesh-to-image rasterizer, DeepMesh is able to leverage 2D shape information from multiple anatomical views for 3D mesh reconstruction and mesh motion estimation. The proposed method estimates vertex-wise displacement and thus maintains vertex correspondences between time frames, which is important for the quantitative assessment of cardiac function across different subjects and populations. We evaluate DeepMesh on CMR images acquired from the UK Biobank. We focus on 3D motion estimation of the left ventricle in this work. Experimental results show that the proposed method quantitatively and qualitatively outperforms other image-based and mesh-based cardiac motion tracking methods.

The piecewise linearity condition on the total energy with respect to the total magnetization of finite quantum systems is derived, using the infinite-separation-limit technique. This generalizes the well-known constancy condition, related to static correlation error, in approximate density functional theory (DFT). The magnetic analog of the DFT Koopmans' theorem is also derived. Moving to fractional electron count, the tilted plane condition is derived, lifting certain assumptions in previous works. This generalization of the flat plane condition characterizes the total energy surface of a finite system for all values of electron count N and magnetization M. This result is used in combination with tabulated spectroscopic data to show the flat plane-structure of the oxygen atom, among others. We find that derivative discontinuities with respect to electron count sometimes occur at non-integer values. A diverse set of tilted plane structures is shown to occur in d-orbital subspaces, depending on chemical coordination. General occupancy-based total-energy expressions are demonstrated thereby to be necessarily dependent on the symmetry-imposed degeneracies., Comment: 13 pages, 7 figures

This study uses an associated Riccati equation to study the Ulam stability of non-autonomous linear differential vector equations that model the damped linear oscillator. In particular, the best (minimal) Ulam constants for these non-autonomous linear differential vector equations are derived. These robust results apply to vector equations with solutions that blow up in finite time, as well as to vector equations with solutions that exist globally on $(-\infty,\infty)$. Illustrative, non-trivial examples are presented, highlighting the main results., Comment: 22 pages

This study deals with the Ulam stability of non-autonomous linear differential systems without assuming the condition that they admit an exponential dichotomy. In particular, the best (minimal) Ulam constants for two-dimensional non-autonomous linear differential systems with generalized Jordan normal forms are derived. The obtained results are applicable not only to systems with solutions that exist globally on $(-\infty,\infty)$, but also to systems with solutions that blow up in finite time. New results are included even for constant coefficients. A wealth of examples are presented, and approximations of node, saddle, and focus are proposed. In addition, this is the first study to derive the best Ulam constants for non-autonomous systems other than periodic systems., Comment: 37 pages and 3 figures

High-performance batteries, heterogeneous catalysts and next-generation photovoltaics often centrally involve transition metal oxides (TMOs) that undergo charge or spin-state changes. Demand for accurate DFT modeling of TMOs has increased in recent years, driving improved quantification and correction schemes for approximate DFT's characteristic errors, notably those pertaining to self-interaction and static correlation. Of considerable interest, meanwhile, is the use of DFT-accessible quantities to compute parameters of coarse-grained models such as for magnetism. To understand the interference of error corrections and model mappings, we probe the prototypical Mott-Hubbard insulator NiO, calculating its electronic structure in its antiferromagnetic I/II and ferromagnetic states. We examine the pronounced sensitivity of the first principles calculated Hubbard U and Hund's J parameters to choices concerning Projector Augmented Wave (PAW) based population analysis, we reevaluate spin quantification conventions for the Heisenberg model, and we seek to develop best practices for calculating Hubbard parameters specific to energetically meta-stable magnetic orderings of TMOs. Within this framework, we assess several corrective functionals using in situ calculated U and J parameters, e.g., DFT+U and DFT+U+J. We find that while using a straightforward workflow with minimal empiricism, the NiO Heisenberg parameter RMS error with respect to experiment was reduced to 13%, an advance upon the state-of-the-art. Methodologically, we used a linear-response implementation for calculating the Hubbard U available in the open-source plane-wave DFT code Abinit. We have extended its utility to calculate the Hund's exchange coupling J, however our findings are anticipated to be applicable to any DFT+U implementation., Comment: 19 pages, 5 figures (+2 in SI), 7 tables (+1 in SI). Accepted Nov. 14, 2023 to Physical Review B

By making use of arithmetic information inequalities, we give a short new proof of the discretised ring theorem for sets of real numbers. Our proof gives a strong quantitative bound. In particular, we show that if $A \subset [1,2]$ is a $(\delta,\sigma)$-set, then $A+A$ or $A\cdot A$ has $\delta$-covering number at least $\delta^{-c}|A|$ for any $0 < c < \min\{\sigma/6, (1-\sigma)/6\}$ provided that $\delta > 0$ is small enough., Comment: 22 pages