bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemomechanical simulation of soap film flow on spherical bubbles
Authors: Huang Weizhen , Iseringhausen Julian , Kneiphof Tom , Qu Ziyin , Jiang Chenfanfu , Hullin Matthias B.
Published: August 2020

Soap bubbles are widely appreciated for their fragile nature and their colorful appearance. The natural sciences and, in extension, computer graphics, have comprehensively studied the mechanical behavior of films and foams, as well as the optical properties of thin liquid layers. In this paper, we focus on the dynamics of material flow within the soap film, which results in fascinating, extremely detailed patterns. This flow is characterized by a complex coupling between surfactant concentration and Marangoni surface tension. We propose a novel chemomechanical simulation framework rooted in lubrication theory, which makes use of a custom semi-Lagrangian advection solver to enable the simulation of soap film dynamics on spherical bubbles both in free flow as well as under body forces such as gravity or external air flow. By comparing our simulated outcomes to videos of real-world soap bubbles recorded in a studio environment, we show that our framework, for the first time, closely recreates a wide range of dynamic effects that are also observed in experiment.
RigNet
Authors: Xu Zhan , Zhou Yang , Kalogerakis Evangelos , Landreth Chris , Singh Karan
Published: August 2020

We present
RigNet
, an end-to-end automated method for producing animation rigs from input character models. Given an input 3D model representing an articulated character,
RigNet
predicts a skeleton that matches the animator expectations in joint placement and topology. It also estimates surface skin weights based on the predicted skeleton. Our method is based on a deep architecture that directly operates on the mesh representation without making assumptions on shape class and structure. The architecture is trained on a large and diverse collection of rigged models, including their mesh, skeletons and corresponding skin weights. Our evaluation is three-fold: we show better results than prior art when quantitatively compared to animator rigs; qualitatively we show that our rigs can be expressively posed and animated at multiple levels of detail; and finally, we evaluate the impact of various algorithm choices on our output rigs.
1
Projective dynamics with dry frictional contact
Authors: Ly Mickaël , Jouve Jean , Boissieux Laurence , Bertails-Descoubes Florence
Published: August 2020

Projective dynamics was introduced a few years ago as a fast method to yield an approximate yet stable solution to the dynamics of nodal systems subject to stiff internal forces. Previous attempts to include contact forces in that framework considered adding a quadratic penalty energy to the global system, which however broke the simple - constant matrix - structure of the global linear equation, while failing to treat contact in an implicit manner. In this paper we propose a simple yet effective method to integrate in a unified and semi-implicit way contact as well as dry frictional forces into the nested architecture of Projective dynamics. Assuming that contacts apply to nodes only, the key is to split the global matrix into a diagonal and a positive matrix, and use this splitting in the local step so as to make a good prediction of frictional contact forces at next iteration. Each frictional contact force is refined independently in the local step, while the original efficient structure of the global step is left unchanged. We apply our algorithm to cloth simulation and show that contact and dry friction can be captured at a reasonable precision within a few iterations only, hence one order of magnitude faster compared to global implicit contact solvers of the literature.
Uncertainty quantification for multi-scan registration
Authors: Huang Xiangru , Liang Zhenxiao , Huang Qixing
Published: August 2020

A fundamental problem in scan-based 3D reconstruction is to align the depth scans under different camera poses into the same coordinate system. While there are abundant algorithms on aligning depth scans, few methods have focused on assessing the quality of a solution. This quality checking problem is vital, as we need to determine whether the current scans are sufficient or not and where to install additional scans to improve the reconstruction. On the other hand, this problem is fundamentally challenging because the underlying ground-truth is generally unavailable, and it is challenging to predict alignment errors such as global drifts manually. In this paper, we introduce a local uncertainty framework for geometric alignment algorithms. Our approach enjoys several appealing properties, such as it does not require re-sampling the input, no need for the underlying ground-truth, informative, and high computational efficiency. We apply this framework to two multi-scan alignment formulations, one minimizes geometric distances between pairs of scans, and another simultaneously aligns the input scans with a deforming model. The output of our approach can be seamlessly integrated with view selection, enabling uncertainty-aware view planning. Experimental results and user studies justify the effectiveness of our approach on both synthetic and real datasets.
A model for soap film dynamics with evolving thickness
Authors: Ishida Sadashige , Synak Peter , Narita Fumiya , Hachisuka Toshiya , Wojtan Chris
Published: August 2020

Previous research on animations of soap bubbles, films, and foams largely focuses on the motion and geometric shape of the bubble surface. These works neglect the evolution of the bubble's thickness, which is normally responsible for visual phenomena like surface vortices, Newton's interference patterns, capillary waves, and deformation-dependent rupturing of films in a foam. In this paper, we model these natural phenomena by introducing the film thickness as a reduced degree of freedom in the Navier-Stokes equations and deriving their equations of motion. We discretize the equations on a non-manifold triangle mesh surface and couple it to an existing bubble solver. In doing so, we also introduce an incompressible fluid solver for 2.5D films and a novel advection algorithm for convecting fields across non-manifold surface junctions. Our simulations enhance state-of-the-art bubble solvers with additional effects caused by convection, rippling, draining, and evaporation of the thin film.
Informative scene decomposition for crowd analysis, comparison and simulation guidance
Authors: He Feixiang , Xiang Yuanhang , Zhao Xi , Wang He
Published: August 2020

Crowd simulation is a central topic in several fields including graphics. To achieve high-fidelity simulations, data has been increasingly relied upon for analysis and simulation guidance. However, the information in real-world data is often noisy, mixed and unstructured, making it difficult for effective analysis, therefore has not been fully utilized. With the fast-growing volume of crowd data, such a bottleneck needs to be addressed. In this paper, we propose a new framework which comprehensively tackles this problem. It centers at an unsupervised method for analysis. The method takes as input raw and noisy data with highly mixed multi-dimensional (space, time and dynamics) information, and automatically structure it by learning the correlations among these dimensions. The dimensions together with their correlations fully describe the scene semantics which consists of recurring activity patterns in a scene, manifested as space flows with temporal and dynamics profiles. The effectiveness and robustness of the analysis have been tested on datasets with great variations in volume, duration, environment and crowd dynamics. Based on the analysis, new methods for data visualization, simulation evaluation and simulation guidance are also proposed. Together, our framework establishes a highly automated pipeline from raw data to crowd analysis, comparison and simulation guidance. Extensive experiments and evaluations have been conducted to show the flexibility, versatility and intuitiveness of our framework.
XNect
Authors: Mehta Dushyant , Sotnychenko Oleksandr , Mueller Franziska , Xu Weipeng , Elgharib Mohamed , Fua Pascal , Seidel Hans-Peter , Rhodin Helge , Pons-Moll Gerard , Theobalt Christian
Published: August 2020

We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions by objects and by other people. Our method operates in subsequent stages. The first stage is a convolutional neural network (CNN) that estimates 2D and 3D pose features along with identity assignments for all visible joints of all individuals. We contribute a new architecture for this CNN, called
SelecSLS Net
, that uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy. In the second stage, a fullyconnected neural network turns the possibly partial (on account of occlusion) 2D pose and 3D pose features for each subject into a complete 3D pose estimate per individual. The third stage applies space-time skeletal model fitting to the predicted 2D and 3D pose per subject to further reconcile the 2D and 3D pose, and enforce temporal coherence. Our method returns the full skeletal pose in joint angles for each subject. This is a further key distinction from previous work that do not produce joint angle results of a coherent skeleton in real time for multi-person scenes. The proposed system runs on consumer hardware at a previously unseen speed of more than 30 fps given 512x320 images as input while achieving state-of-the-art accuracy, which we will demonstrate on a range of challenging real-world scenes.
Code replicability in computer graphics
Authors: Bonneel Nicolas , Coeurjolly David , Digne Julie , Mellado Nicolas
Published: August 2020

Being able to duplicate published research results is an important process of conducting research whether to build upon these findings or to compare with them. This process is called "replicability" when using the original authors' artifacts (e.g., code), or "reproducibility" otherwise (e.g., re-implementing algorithms). Reproducibility and replicability of research results have gained a lot of interest recently with assessment studies being led in various fields, and they are often seen as a trigger for better result diffusion and transparency. In this work, we assess replicability in Computer Graphics, by evaluating whether the code is available and whether it works properly. As a proxy for this field we compiled, ran and analyzed 151 codes out of 374 papers from 2014, 2016 and 2018 SIGGRAPH conferences. This analysis shows a clear increase in the number of papers with available and operational research codes with a dependency on the subfields, and indicates a correlation between code replicability and citation count. We further provide an interactive tool to explore our results and evaluation data.
High resolution étendue expansion for holographic displays
Authors: Kuo Grace , Waller Laura , Ng Ren , Maimone Andrew
Published: August 2020

Holographic displays can create high quality 3D images while maintaining a small form factor suitable for head-mounted virtual and augmented reality systems. However, holographic displays have limited étendue based on the number of pixels in their spatial light modulators, creating a tradeoff between the eyebox size and the field-of-view. Scattering-based étendue expansion, in which coherent light is focused into an image after being scattered by a static mask, is a promising avenue to break this tradeoff. However, to date, this approach has been limited to very sparse content consisting of, for example, only tens of spots.

In this work, we introduce new algorithms to scattering-based étendue expansion that support dense, photorealistic imagery at the native resolution of the spatial light modulator, offering up to a 20 dB improvement in peak signal to noise ratio over baseline methods. We propose spatial and frequency constraints to optimize performance for human perception, and performance is characterized both through simulation and a preliminary benchtop prototype. We further demonstrate the ability to generate content at multiple depths, and we provide a path for the miniaturization of our benchtop prototype into a sunglasses-like form factor.
Exact and efficient polyhedral envelope containment check
Authors: Wang Bolun , Schneider Teseo , Hu Yixin , Attene Marco , Panozzo Daniele
Published: August 2020

We introduce a new technique to check containment of a triangle within an envelope built around a given triangle mesh. While existing methods conservatively check containment within a Euclidean envelope, our approach makes use of a non-Euclidean envelope where containment can be checked both
exactly
and
efficiently.
Exactness is crucial to address major robustness issues in existing geometry processing algorithms, which we demonstrate by integrating our technique in two surface triangle remeshing algorithms and a volumetric tetrahedral meshing algorithm. We provide a quantitative comparison of our method and alternative algorithms, showing that our solution, in addition to being exact, is also more efficient. Indeed, while containment within large envelopes can be checked in a comparable time, we show that our algorithm outperforms alternative methods when the envelope becomes thin.
Massively parallel rendering of complex closed-form implicit surfaces
Authors: Keeter Matthew J.
Published: August 2020

We present a new method for directly rendering complex closed-form implicit surfaces on modern GPUs, taking advantage of their massive parallelism. Our model representation is unambiguously solid, can be sampled at arbitrary resolution, and supports both constructive solid geometry (CSG) and more unusual modeling operations (e.g. smooth blending of shapes). The rendering strategy scales to large-scale models with thousands of arithmetic operations in their underlying mathematical expressions. Our method only requires
C
0
continuity, allowing for warping and blending operations which break Lipshitz continuity.

To render a model, its underlying expression is evaluated in a shallow hierarchy of spatial regions, using a high branching factor for efficient parallelization. Interval arithmetic is used to both skip empty regions and construct reduced versions of the expression. The latter is the optimization that makes our algorithm practical: in one benchmark, expression complexity decreases by two orders of magnitude between the original and reduced expressions. Similar algorithms exist in the literature, but tend to be deeply recursive with heterogeneous workloads in each branch, which makes them GPU-unfriendly; our evaluation and expression reduction both run efficiently as massively parallel algorithms, entirely on the GPU.

The resulting system renders complex implicit surfaces in high resolution and at interactive speeds. We examine how performance scales with computing power, presenting performance results on hardware ranging from older laptops to modern data-center GPUs, and showing significant improvements at each stage.
An implicit compressible SPH solver for snow simulation
Authors: Gissler Christoph , Henne Andreas , Band Stefan , Peer Andreas , Teschner Matthias
Published: August 2020

Snow is a complex material. It resists elastic normal and shear deformations, while some deformations are plastic. Snow can deform and break. It can be significantly compressed and gets harder under compression. Existing snow solvers produce impressive results. E.g., hybrid Lagrangian/Eulerian techniques have been used to capture all material properties of snow. The auxiliary grid, however, makes it challenging to handle small volumes. In particular, snow fall and accumulation on surfaces have not been demonstrated with these solvers yet. Existing particle-based snow solvers, on the other hand, can naturally handle small snow volumes. However, existing solutions consider simplified material properties. In particular, shear deformation and the hardening effect are typically omitted.

We present a novel Lagrangian snow approach based on Smoothed Particle Hydrodynamics (SPH). Snow is modeled as an elastoplastic continuous material that captures all above-mentioned effects. The compression of snow is handled by a novel compressible pressure solver, where the typically employed state equation is replaced by an implicit formulation. Acceleration due to shear stress is computed using a second implicit formulation. The linear solvers of the two implicit formulations for accelerations due to shear and normal stress are realized with matrix-free implementations. Using implicit formulations and solving them with matrix-free solvers allows to couple the snow to other phases and is beneficial to the stability and the time step size, i.e., performance of the approach. Solid boundaries are represented with particles and a novel implicit formulation is used to handle friction at solid boundaries. We show that our approach can simulate accumulation, deformation, breaking, compression and hardening of snow. Furthermore, we demonstrate two-way coupling with rigid bodies, interaction with incompressible and highly viscous fluids and phase change from fluid to snow.
Sequential gallery for interactive visual design optimization
Authors: Koyama Yuki , Sato Issei , Goto Masataka
Published: August 2020

Visual design tasks often involve tuning many design parameters. For example, color grading of a photograph involves many parameters, some of which non-expert users might be unfamiliar with. We propose a novel user-in-the-loop optimization method that allows users to efficiently find an appropriate parameter set by exploring such a high-dimensional design space through much easier two-dimensional search subtasks. This method, called
sequential plane search
, is based on
Bayesian optimization
to keep necessary queries to users as few as possible. To help users respond to
plane-search
queries, we also propose using a gallery-based interface that provides options in the two-dimensional subspace arranged in an adaptive grid view. We call this interactive framework
Sequential Gallery
since users sequentially select the best option from the options provided by the interface. Our experiment with synthetic functions shows that our sequential plane search can find satisfactory solutions in fewer iterations than baselines. We also conducted a preliminary user study, results of which suggest that novices can effectively complete search tasks with Sequential Gallery in a photo-enhancement scenario.
MEgATrack
Authors: Han Shangchen , Liu Beibei , Cabezas Randi , Twigg Christopher D. , Zhang Peizhao , Petkau Jeff , Yu Tsz-Ho , Tai Chun-Jung , Akbay Muzaffer , Wang Zheng , Nitzan Asaf , Dong Gang , Ye Yuting , Tao Lingling , Wan Chengde , Wang Robert
Published: August 2020

We present a system for real-time hand-tracking to drive virtual and augmented reality (VR/AR) experiences. Using four fisheye monochrome cameras, our system generates accurate and low-jitter 3D hand motion across a large working volume for a diverse set of users. We achieve this by proposing neural network architectures for detecting hands and estimating hand keypoint locations. Our hand detection network robustly handles a variety of real world environments. The keypoint estimation network leverages tracking history to produce spatially and temporally consistent poses. We design scalable, semi-automated mechanisms to collect a large and diverse set of ground truth data using a combination of manual annotation and automated tracking. Additionally, we introduce a detection-by-tracking method that increases smoothness while reducing the computational cost; the optimized system runs at 60Hz on PC and 30Hz on a mobile processor. Together, these contributions yield a practical system for capturing a user's hands and is the default feature on the Oculus Quest VR headset powering input and social presence.
Constraint bubbles and affine regions
Authors: Goldade Ryan , Aanjaneya Mridul , Batty Christopher
Published: August 2020

We propose to enhance the capability of standard free-surface flow simulators with efficient support for immersed bubbles through two new models: constraint-based bubbles and affine fluid regions. Unlike its predecessors, our constraint-based model entirely dispenses with the need for advection or projection inside zero-density bubbles, with extremely modest additional computational overhead that is proportional to the surface area of all bubbles. This surface-only approach is easy to implement, realistically captures many familiar bubble behaviors, and even allows two or more distinct liquid bodies to correctly interact across completely unsimulated air. We augment this model with a per-bubble volume-tracking and correction framework to minimize the cumulative effects of gradual volume drift. To support bubbles with non-zero densities, we propose a novel reduced model for an irregular fluid region with a single pointwise incompressible affine vector field. This model requires only 11 interior velocity degrees of freedom per affine fluid region in 3D, and correctly reproduces buoyant, stationary, and sinking behaviors of a secondary fluid phase with non-zero density immersed in water. Since the pressure projection step in both the above schemes is a slightly modified Poisson-style system, we propose novel Multigrid-based preconditioners for Conjugate Gradients for fast numerical solutions of our new discretizations. Furthermore, we observe that by enforcing an incompressible affine vector field over a coalesced set of grid cells, our reduced model is effectively an irregular coarse super-cell. This offers a convenient and flexible adaptive coarsening strategy that integrates readily with the standard staggered grid approach for fluid simulation, yet supports coarsened regions that are arbitrary voxelized shapes, and provides an analytically divergence-free interior. We demonstrate its effectiveness with a new adaptive liquid simulator whose interior regions are coarsened into a mix of tiles with regular and irregular shapes.
Learning temporal coherence via self-supervision for GAN-based video generation
Authors: Chu Mengyu , Xie You , Mayer Jonas , Leal-Taixé Laura , Thuerey Nils
Published: August 2020

Our work explores temporal self-supervision for GAN-based video generation tasks. While adversarial training successfully yields generative models for a variety of areas, temporal relationships in the generated data are much less explored. Natural temporal changes are crucial for sequential generation tasks, e.g. video super-resolution and unpaired video translation. For the former, state-of-the-art methods often favor simpler norm losses such as
L
2
over adversarial training. However, their averaging nature easily leads to temporally smooth results with an undesirable lack of spatial detail. For unpaired video translation, existing approaches modify the generator networks to form spatio-temporal cycle consistencies. In contrast, we focus on improving learning objectives and propose a temporally self-supervised algorithm. For both tasks, we show that temporal adversarial learning is key to achieving temporally coherent solutions without sacrificing spatial detail. We also propose a novel Ping-Pong loss to improve the long-term temporal consistency. It effectively prevents recurrent networks from accumulating artifacts temporally without depressing detailed features. Additionally, we propose a first set of metrics to quantitatively evaluate the accuracy as well as the perceptual quality of the temporal evolution. A series of user studies confirm the rankings computed with these metrics. Code, data, models, and results are provided at https://github.com/thunil/TecoGAN.
Polar stroking
Authors: Kilgard Mark J.
Published: August 2020

Stroking and filling are the two basic rendering operations on paths in vector graphics. The theory of filling a path is well-understood in terms of contour integrals and winding numbers, but when path rendering standards specify stroking, they resort to the analogy of painting pixels with a brush that traces the outline of the path. This means important standards such as PDF, SVG, and PostScript lack a rigorous way to say what samples are inside or outside a stroked path. Our work fills this gap with a principled theory of stroking.

Guided by our theory, we develop a novel
polar stroking
method to render stroked paths robustly with an intuitive way to bound the tessellation error without needing recursion. Because polar stroking guarantees small uniform steps in tangent angle, it provides an efficient way to accumulate arc length along a path for texturing or dashing. While this paper focuses on developing the theory of our polar stroking method, we have successfully implemented our methods on modern programmable GPUs.
Fabrication-in-the-loop co-optimization of surfaces and styli for drawing haptics
Authors: Piovarči Michal , Kaufman Danny M. , Levin David I. W. , Didyk Piotr
Published: August 2020

Digital drawing tools are now standard in art and design workflows. These tools offer comfort, portability, and precision as well as native integration with digital-art workflows, software, and tools. At the same time, artists continue to work with long-standing, traditional drawing tools. One feature of traditional tools, well-appreciated by many artists and lacking in digital tools, is the specific and diverse range of haptic responses provided by them. Haptic feedback in traditional drawing tools provides unique, per-tool responses that help determine the precision and character of individual strokes. In this work, we address the problem of fabricating digital drawing tools that closely match the haptic feedback of their traditional counterparts. This requires the formulation and solution of a complex, co-optimization of both digital styli and the drawing surfaces they move upon. Here, a potentially direct formulation of this optimization with numerical simulation-in-the-loop is not yet viable. As in many complex design tasks, state-of-the-art methods do not currently offer predictive modeling at rates and scales that can account for the numerous, coupled, physical behaviors governing the haptics of styli and surfaces, nor for the limitations and uncertainties inherent in their fabrication processes. To address these challenges, we propose fabrication-in-the-loop optimization. Critical to making this strategy practical we construct our objective via a Gaussian Process that does not require computing derivatives with respect to design parameters. Our Gaussian Process surrogate model then provides both function estimates and confidence intervals that guide the efficient sampling of our design space. In turn, this sampling critically reduces the numbers of fabricated examples during exploration and automatically handles exploration-exploitation trade-offs. We apply our method to fabricate drawing tools that provide a wide range of haptic feedback, and demonstrate that they are often hard for users to distinguish from their traditional drawing-tool analogs.
LoopyCuts
Authors: Livesu Marco , Pietroni Nico , Puppo Enrico , Sheffer Alla , Cignoni Paolo
Published: August 2020

We present a new fully automatic block-decomposition algorithm for feature-preserving,
strongly
hex-dominant meshing, that yields results with a drastically larger percentage of hex elements than prior art. Our method is guided by a surface field that conforms to both surface curvature and feature lines, and exploits an ordered set of cutting loops that evenly cover the input surface, defining an arrangement of loops suitable for hex-element generation. We decompose the solid into coarse blocks by iteratively cutting it with surfaces bounded by these loops. The vast majority of the obtained blocks can be turned into hexahedral cells via simple midpoint subdivision. Our method produces pure hexahedral meshes in approximately 80% of the cases, and hex-dominant meshes with less than 2% non-hexahedral cells in the remaining cases. We demonstrate the robustness of our method on 70+ models, including CAD objects with features of various complexity, organic and synthetic shapes, and provide extensive comparisons to prior art, demonstrating its superiority.
The leopard never changes its spots
Authors: De Gomensoro Malheiros Marcelo , Fensterseifer Henrique , Walter Marcelo
Published: August 2020

Previous research in pattern formation using reaction-diffusion mostly focused on static domains, either for computational simplicity or mathematical tractability. In this work, we have explored the expressiveness of combining simple mechanisms as a possible explanation for pigmentation pattern formation, where tissue growth plays a crucial role. Our motivation is not only to realistically reproduce natural patterns but also to get insights into the underlying biological processes. Therefore, we present a novel approach to generate realistic animal skin patterns. First, we describe the approximation of tissue growth by a series of discrete matrix expansion operations. Then, we combine it with an adaptation of Turing's non-linear reaction-diffusion model, which enforces upper and lower bounds to the concentrations of the involved chemical reagents. We also propose the addition of a single-reagent continuous autocatalytic reaction, called reinforcement, to provide a mechanism to maintain an already established pattern during growth. By careful adjustment of the parameters and the sequencing of operations, we closely match the appearance of a few real species. In particular, we reproduce in detail the distinctive features of the leopard skin, also providing a hypothesis for the simultaneous productions of the most common melanin types, eumelanin and pheomelanin.
Lifting simplices to find injectivity
Authors: Du Xingyi , Aigerman Noam , Zhou Qingnan , Kovalsky Shahar Z. , Yan Yajie , Kaufman Danny M. , Ju Tao
Published: August 2020

Mapping a source mesh into a target domain while preserving local injectivity is an important but highly non-trivial task. Existing methods either require an already-injective starting configuration, which is often not available, or rely on sophisticated solving schemes. We propose a novel energy form, called Total Lifted Content (TLC), that is equipped with theoretical properties desirable for injectivity optimization. By lifting the simplices of the mesh into a higher dimension and measuring their contents (2D area or 3D volume) there, TLC is smooth over the entire embedding space and its global minima are always injective. The energy is simple to minimize using standard gradient-based solvers. Our method achieved 100% success rate on an extensive benchmark of embedding problems for triangular and tetrahedral meshes, on which existing methods only have varied success.
Accurate face rig approximation with deep differential subspace reconstruction
Authors: Song Steven L. , Shi Weiqi , Reed Michael
Published: August 2020

To be suitable for film-quality animation, rigs for character deformation must fulfill a broad set of requirements. They must be able to create highly stylized deformation, allow a wide variety of controls to permit artistic freedom, and accurately reflect the design intent. Facial deformation is especially challenging due to its nonlinearity with respect to the animation controls and its additional precision requirements, which often leads to highly complex face rigs that are not generalizable to other characters. This lack of generality creates a need for approximation methods that encode the deformation in simpler structures. We propose a rig approximation method that addresses these issues by learning localized shape information in differential coordinates and, separately, a subspace for mesh reconstruction. The use of differential coordinates produces a smooth distribution of errors in the resulting deformed surface, while the learned subspace provides constraints that reduce the low frequency error in the reconstruction. Our method can reconstruct both face and body deformations with high fidelity and does not require a set of well-posed animation examples, as we demonstrate with a variety of production characters.
GS-PAT
Authors: Plasencia Diego Martinez , Hirayama Ryuji , Montano-Murillo Roberto , Subramanian Sriram
Published: August 2020

Phased Arrays of Transducers (PATs) allow accurate control of ultrasound fields, with applications in haptics, levitation (i.e. displays) and parametric audio. However, algorithms for multi-point levitation or tactile feedback are usually limited to computing solutions in the order of hundreds of sound-fields per second, preventing the use of multiple high-speed points, a feature that can broaden the scope of applications of PATs. We present
GS-PAT
, a GPU multi-point phase retrieval algorithm, capable of computing 17K solutions per second for up to 32 simultaneous points in a mid-end consumer grade GPU (NVidia GTX 1660). We describe the algorithm and compare it to state of the art multi-point algorithms used for ultrasound haptics and levitation, showing similar quality of the generated sound-fields, and much higher computation rates. We then illustrate how the shift in paradigm enabled by
GS-PAT
(i.e. real-time control of several high-speed points) opens new applications for PAT technologies, such as in volumetric fully coloured displays, multi-point spatio-temporal tactile feedback, parametric audio and simultaneous combinations of these modalities.
Highly Sensitive and Selective Electrochemical Determination of 4-Aminophenol Based on Flower-Like Ag-Au Nanocomposites Modified Glassy Carbon Electrode
Authors: Zhang Hongding , Xing Zhenhua , Pan Miaomiao , Wang Hai-Bo , Liu Yan-Ming
Published: August 2020

4-aminophenol (4-AP), a typical secondary product from pharmaceuticals preparation, can lead to dangerous collateral effects in drugs. It’s crucial to develop suitable methods for fast and accurate determination of 4-AP. Herein, a novel and fast electrochemical method based on flower-like Ag-Au nanocomposites modified electrode has been developed for accurate determination of 4-AP. The flower-like Ag-Au nanocomposites were synthesized via a seed-mediated growth route utilizing L-dopa as reduction agent and assembled by 2-dimension nanosheets. The electrochemical oxidation of 4-AP on Ag-Au nanocomposites modified electrode was studied by using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The modified electrode exhibited excellent electrocatalytic activity toward 4-AP. Under the optimized conditions, the sensor displayed high sensitivity for the detection of 4-AP in the linear range from 0.1 to 100 μM with detection limit of 36 nM (S/N = 3). The fabricated electrode showed high selectivity, good reproducibility, and long-term stability to 4-AP detection. Furthermore, the developed electrochemical sensor showed no interference for simultaneous detection of 4-AP and acetaminophen. It was also demonstrated that the sensor could be applied for the analysis of pharmaceutical products.
High Energy-Density Supercapacitor, Enabled by Carbon Nanostructures
Authors: Carley Christopher Scott , Espinoza Danny J. , Reyes-Rodríguez José Luis , Ahn Ethan C.
Published: August 2020

The rapidly increasing demand for renewable energy sources has revived interest in energy storage devices due to the intermittent nature of energy generated from these sources (e.g., solar, wind). Compared to lithium-ion batteries and hydrogen fuel cells, supercapacitors exhibit superior power-density (W/kg), enabling fast charging/discharging cycles. Although supercapacitors generally promise long life-cycle and a robust thermal operating range, a relatively low energy-density (Wh/kg) still remains the greatest challenge. This research presents a relatively simple, low-cost experimental methodology to develop all solid-state, flexible, and high-performance supercapacitor devices. The interdigitated electrodes will consist of two different types of solution-processable carbon nanostructures – namely, reduced graphene oxide (rGO) and single-walled carbon nanotube (SWCNT). We developed models to better guide the experimental work while predicting the power-density and energy-density characteristics of supercapacitors with varying physical dimensions.
Real-Time Under Load Electrochemical Impedance Spectroscopy (EIS) Analysis and Modeling
Authors: Leduc Hugo , Okamura Russell , Kyeyune-Nyombi Eru , Huynh Kenny , Chung Steven
Published: August 2020

As renewable energy usage continues to rise, the need for reliable energy storage solutions also grows. Today, battery systems are expected to last for several years. The challenge comes in monitoring battery safety and degradation. A major limitation in tracking the performance of battery cells is the lack of relevant measurements. Electrochemical impedance spectroscopy (EIS) has been used to study underlying battery phenomena. However, EIS is typically only performed on batteries which have been at rest for long periods of time—a requirement that is impractical in today’s energy storage systems. Here, the usability of EIS in real-time is investigated on batteries subjected to different current loads. Limitations in signal processing and electrochemistry for EIS taken under load are also discussed and its usability is demonstrated in estimating the internal cell temperature in extreme conditions. This broadens the use of EIS for commercial applications.
Stem cells and lung regeneration
Authors: Parekh Kalpaj R. , Nawroth Janna , Pai Albert , Busch Shana M. , Senger Christiana N. , Ryan Amy L.
Published: August 2020

The ability to replace defective cells in an airway with cells that can engraft, integrate, and restore a functional epithelium could potentially cure a number of lung diseases. Progress toward the development of strategies to regenerate the adult lung by either in vivo or ex vivo targeting of endogenous stem cells or pluripotent stem cell derivatives is limited by our fundamental lack of understanding of the mechanisms controlling human lung development, the precise identity and function of human lung stem and progenitor cell types, and the genetic and epigenetic control of human lung fate. In this review, we intend to discuss the known stem/progenitor cell populations, their relative differences between rodents and humans, their roles in chronic lung disease, and their therapeutic prospects. Additionally, we highlight the recent breakthroughs that have increased our understanding of these cell types. These advancements include novel lineage-traced animal models and single-cell RNA sequencing of human airway cells, which have provided critical information on the stem cell subtypes, transition states, identifying cell markers, and intricate pathways that commit a stem cell to differentiate or to maintain plasticity. As our capacity to model the human lung evolves, so will our understanding of lung regeneration and our ability to target endogenous stem cells as a therapeutic approach for lung disease.
Succinylation at a key residue of FEN1 is involved in the DNA damage response to maintain genome stability
Authors: Shi Rongyi , Wang Yiyi , Gao Ya , Xu Xiaoli , Mao Shuyu , Xiao Yue , Song Shuang , Wang Liangyan , Tian Bing , Zhao Ye , Hua Yuejin , Xu Hong
Published: August 2020

Human flap endonuclease 1 (FEN1) is a structure-specific, multifunctional endonuclease essential for DNA replication and repair. Our previous study showed that in response to DNA damage, FEN1 interacts with the PCNA-like Rad9-Rad1-Hus1 complex instead of PCNA to engage in DNA repair activities, such as stalled DNA replication fork repair, and undergoes SUMOylation by SUMO-1. Here, we report that succinylation of FEN1 was stimulated in response to DNA replication fork-stalling agents, such as ultraviolet (UV) irradiation, hydroxyurea, camptothecin, and mitomycin C. K200 is a key succinylation site of FEN1 that is essential for gap endonuclease activity and could be suppressed by methylation and stimulated by phosphorylation to promote SUMO-1 modification. Succinylation at K200 of FEN1 promoted the interaction of FEN1 with the Rad9-Rad1-Hus1 complex to rescue stalled replication forks. Impairment of FEN1 succinylation led to the accumulation of DNA damage and heightened sensitivity to fork-stalling agents. Altogether, our findings suggest an important role of FEN1 succinylation in regulating its roles in DNA replication and repair, thus maintaining genome stability.
miRNA degradation in the mammalian brain
Authors: Kim Chun K. , Pak Toni R.
Published: August 2020

MicroRNAs (miRNAs) are short, noncoding RNAs that are evolutionarily conserved across many different species. miRNA regulation of gene expression, specifically in the context of the mammalian brain, has been well characterized; however, the regulation of miRNA degradation is still a focus of ongoing research. This review focuses on recent findings concerning the cellular mechanisms that govern miRNA degradation, with an emphasis on target-mediated miRNA degradation and how this phenomenon is uniquely poised to maintain homeostasis in neuronal systems.
Prenatal smoke exposure dysregulates lung epithelial cell differentiation in mouse offspring: role for AREG-induced EGFR signaling
Authors: Lkhagvadorj Khosbayar , Zeng Zhijun , Song Juan , Reinders-Luinge Marjan , Kooistra Wierd , Song Shanshan , Krauss-Etschmann Susanne , Melgert Barbro N. , Cao Junjun , Hylkema Machteld N.
Published: August 2020

Prenatal smoke exposure is a risk factor for impaired lung development in children. Recent studies have indicated that amphiregulin (AREG), which is a ligand of the epidermal growth factor receptor (EGFR), has a regulatory role in airway epithelial cell differentiation. In this study, we investigated the effect of prenatal smoke exposure on lung epithelial cell differentiation and linked this with AREG-EGFR signaling in 1-day-old mouse offspring. Bronchial and alveolar epithelial cell differentiations were assessed by immunohistochemistry. Areg, epidermal growth factor ( Egf), and mRNA expressions of specific markers for bronchial and alveolar epithelial cells were assessed by RT-qPCR. The results in neonatal lungs were validated in an AREG-treated three-dimensional mouse lung organoid model. We found that prenatal smoke exposure reduced the number of ciliated cells and the expression of the cilia-related transcription factor Foxj1, whereas it resulted in higher expression of mucus-related transcription factors Spdef and Foxm1 in the lung. Moreover, prenatally smoke-exposed offspring had higher numbers of alveolar epithelial type II cells (AECII) and lower expression of the AECI-related Pdpn and Gramd2 markers. This was accompanied by higher expression of Areg and lower expression of Egf in prenatally smoke-exposed offspring. In bronchial organoids, AREG treatment resulted in fewer ciliated cells and more basal cells when compared with non-treated bronchiolar organoids. In alveolar organoids, AREG treatment led to more AECII cells than non-treated AECII cells. Taken together, the observed impaired bronchial and alveolar cell development in prenatally smoke-exposed neonatal offspring may be induced by increased AREG-EGFR signaling.
Quantification of bronchoalveolar neutrophil extracellular traps and phagocytosis in murine pneumonia
Authors: Gautam Samir , Stahl Yannick , Young Grant M. , Howell Rebecca , Cohen Avi J. , Tsang Derek A. , Martin Tommy , Sharma Lokesh , Dela Cruz Charles S.
Published: August 2020

The past two decades have witnessed a resurgence in neutrophil research, inspired in part by the discovery of neutrophil extracellular traps (NETs) and their myriad roles in health and disease. Within the lung, dysregulation of neutrophils and NETosis have been linked to an array of diseases including pneumonia, cystic fibrosis, acute respiratory distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), and severe asthma. However, our understanding of pathologic neutrophil responses in the lung remains incomplete. Two methodologic issues have contributed to this gap: first, an emphasis on studying neutrophils from blood rather than the lung and second, the technical difficulties of interrogating neutrophil responses in mice, which has largely restricted basic murine research to specialized laboratories. To address these limitations, we have developed a suite of techniques for studying neutrophil effector functions specifically in the mouse lung. These include ex vivo assays for phagocytosis and NETosis using bronchoalveolar neutrophils and in situ evaluation of NETosis in a murine model of pneumonia. Throughout, we have prioritized technical ease and robust, quantitative readouts. We hope these assays will help to standardize research on lung neutrophils and improve accessibility to this burgeoning field.
Experimental Research on Mechanical Property and Environmental Safety of an Industrial Residue Waste Subgrade Material
Authors: Zhang Yangpeng , Xiong Jianping , Li Qinglin , Cui Jiuhui
Published: August 2020

In order to promote the sustainable use of oil shale residues, a novel subgrade material (SOF) composed of silty clay, oil shale ash residue, and fly ash was developed. The aim of this paper is to study the mechanical behavior and environmental impact of SOF, which is regarded as the safety assessment and prediction for the application of this novel material. To this purpose, the road performance, dynamic properties, and environment impact tests are conducted. In terms of the road performance, the test results of SOF exceed the standard requirement, especially for CBR (California bearing ratio), which can maintain good performance at bad conditions of low compaction degree and being soaked for a long time. The dynamic properties under cyclic loadings are better than most of original and stabilized soils. The shear strength parameters and the anti‐damage mechanism are also discussed; research results show that the friction of SOF mostly contributes to shear strength under high stress conditions, while its cohesion tends to play a more important role under low stress conditions. According to the deformation variation, the accumulation settlement of SOF under vehicle loadings after several years is predicted, which is far lower than the limit of expressway and Grade I highway. Furthermore, the chemical stability and toxicity of SOF leachates are environmentally friendly, which are in line with the benchmarks of Class II surface water and Class III ground water. All the experimental results manifest that SOF used as subgrade filling has good application potential and safety.
Lactobacillus acidophilus Endocarditis Complicated by Pauci-Immune Necrotizing Glomerulonephritis
Authors: Chukwurah Vivian O. , Takang Comfort , Uche Chinelo , Thomas David B. , El Masry Waguih , Toka Hakan R.
Published: August 2020

Infective endocarditis (IE) is more common in patients with predisposing cardiac lesions and has many potential complications, including stroke and arterial thromboembolisms. Renal manifestations have an estimated prevalence of ∼20%. Rapidly progressive glomerulonephritis (RPGN) is a nephrological emergency manifested by autoimmune-mediated progressive loss of renal function over a relatively short period of time. Here, we report the case of a 60-year-old Caucasian male, who presented with speech impairment and was found to have multiple embolic strokes caused by aortic valve IE. His renal function declined rapidly, and his urine sediment featured hematuria and proteinuria. ANCA titer was negative by immunofluorescence (IF); however, the PR3 antibody was elevated. The renal biopsy revealed pauci-immune focally necrotizing glomerulonephritis with the presence of ∼25% cellular crescents. He was initially treated with plasmapheresis and pulse dose steroids. Hemodialysis was initiated for uremic symptoms. After four weeks of antibiotic therapy and with blood cultures remaining negative, he was treated with rituximab. Two months after discharge, his renal function showed improvement, and hemodialysis was discontinued. This case highlights several complications associated with lactobacillus endocarditis including RPGN.