bluuebunny/crossref_metadata_2025 huggingface dataset:
Mud cohesion governs unvegetated meander migration rates and deposit architecture
Authors: Douglas Madison M. , Miller Kimberly Litwin , Lamb Michael P.
Published: July 2024

Vegetation is thought to be a main source of riverbank cohesion, enabling meandering and a deposit architecture characterized by sandy channel belts isolated in mudstone. However, early Earth and Mars had meandering rivers without vegetation, implying that other sources of bank strength can allow meandering with potentially different deposit characteristics. Here we studied the Amargosa River in Death Valley, California, USA, as a modern analog of meandering rivers without vegetation. We monitored flow and erosion at two bends and used radiocarbon dating of strandlines to quantify flood frequency. We also sampled cutbank mud and constrained an erosion theory using flume experiments. Cutbank erosion occurred for floods with >2 yr recurrence intervals, and 18 cm occurred for an ~6 yr reoccurrence, bankfull event. Mud set the rate of meander migration: salt crusts rapidly and completely dissolved during floods, vegetation was absent, and mud entrainment theory matched observed erosion rates. Flood-frequency analysis showed that most bank erosion occurs at flows below bankfull, challenging the threshold channel hypothesis. We used meander migration rates to constrain the time scale of channel-belt formation and compared it to the time scale of avulsion. These calculations, combined with floodplain facies mapping and core sedimentology, indicated a likely deposit architecture of sandy point bar accretion sets intermixed with muddy overbank facies. This deposit architecture is characteristic of vegetated meandering rivers, but due to muddy banks, occurred for the Amargosa River in the absence of plants.
Oceanic anoxic event 3 in Arctic Canada—Arc volcanism and ocean fertilization drove anoxia
Authors: Grasby Stephen E. , Crowley James L. , Mohr Michael T. , Percival Jeanne B. , Ardakani Omid H. , Galloway Jennifer , Bringué Manuel , Smith I. Rod , Yuan Wanju
Published: July 2024

The global extent of the Late Cretaceous oceanic anoxic event 3 (OAE 3) remains uncertain. It is not considered to have extended into the Boreal Realm. To test this, we examined Late Cretaceous organic- and metal-rich black mudstones of the Smoking Hills Formation in Arctic Canada. New high-precision U-Pb zircon ages indicate that deposition of the Smoking Hills Formation (88.535–78.230 Ma) was temporally coincident with OAE 3, indicating a much broader global expression of this event than previously thought. OAE 3 was likely manifest throughout the proto–Arctic Ocean (now Arctic Canada). Abundant bentonite layers and cryptotephra within the Smoking Hills Formation have rare earth element (REE) patterns that are consistent with ashfall derived from Cretaceous arc volcanism. Anomalously high organic matter content in the Smoking Hills Formation, as compared to underlying and overlying units, suggests that ocean fertilization led to enhanced productivity and metal drawdown. A peak in arc volcanism may have been a key driver of the OAE 3 event. We also explored the potential use of cadmium as a geochemical marker of volcanism and show that high volcanogenic metal loading could affect the use of Cd and other proxies for marine productivity (e.g., Zn, Cu).
Pericardial tamponade after laparoscopic repair of a giant diaphragmatic hernia
Authors: Dębski Maciej , Sardar Abbas , Vickery Craig , Ring Liam
Published: July 2024

Laparoscopic intraperitoneal onlay mesh repair is favoured for diaphragmatic hernias due to better outcomes. However, fixation devices pose risks, including cardiac tamponade. A man underwent laparoscopic repair for a large diaphragmatic hernia. One week later, he presented with chest discomfort which was initially attributed to postoperative pain. Subsequently, patient represented with worsening of chest pain and tachycardia. CT requested to rule out pulmonary embolism revealed a large pericardial effusion. Urgent drainage via apical approach resolved tamponade. The case highlights the challenges in managing pericardial effusions post-laparoscopy in the presence of diaphragmatic mesh and stresses multidisciplinary collaboration. Literature review highlights risks associated with fixation devices. Suggestions include limiting their use near vital structures. Key learning point of this case report is to raise awareness of cardiac tamponade following diaphragmatic hernia repair. Limited evidence necessitates cautious use of fixation devices, emphasising patient safety.
Healthcare spending for non-fatal falls among older adults, USA
Authors: Haddad Yara K , Miller Gabrielle F , Kakara Ramakrishna , Florence Curtis , Bergen Gwen , Burns Elizabeth Rose , Atherly Adam
Published: July 2024

Background

The older adult (65+) population in the USA is increasing and with it the number of medically treated falls. In 2015, healthcare spending attributable to older adult falls was approximately US$50 billion. We aim to update the estimated medical expenditures attributable to older adult non-fatal falls.

Methods

Generalised linear models using 2017, 2019 and 2021 Medicare Current Beneficiary Survey and cost supplement files were used to estimate the association of falls with healthcare expenditures while adjusting for demographic characteristics and health conditions in the model. To portion out the share of total healthcare spending attributable to falls versus not, we adjusted for demographic characteristics and health conditions, including self-reported health status and certain comorbidities associated with increased risk of falling or higher healthcare expenditure. We calculated a fall-attributable fraction of expenditure as total expenditures minus total expenditures with no falls divided by total expenditures. We applied the fall-attributable fraction of expenditure from the regression model to the 2020 total expenditures from the National Health Expenditure Data to calculate total healthcare spending attributable to older adult falls.

Results

In 2020, healthcare expenditure for non-fatal falls was US$80.0 billion, with the majority paid by Medicare.

Conclusion

Healthcare spending for non-fatal older adult falls was substantially higher than previously reported estimates. This highlights the growing economic burden attributable to older adult falls and these findings can be used to inform policies on fall prevention efforts in the USA.
Do nurse plants and cattle exclusion help restore Parlatore's Podocarp forest?
Authors: Castellón Matías J. , Tálamo Andrés , Mazzini Flavia , Medina Ezequiel , Cuyckens Griet A.E.
Published: July 2024

In the Neotropical cloud forests of northwest Argentina, cattle ranching has been historically the primary economic activity, with potential negative impacts on the ecosystem. Understanding factors influencing tree regeneration is crucial for reforestation efforts in grazed areas. Given the limited understanding of Parlatore's Podocarp ( Podocarpus parlatorei Pilg.) regeneration ecology, a unique gymnosperm species in the Southern Yungas' Montane Forest, we evaluated the growth and survival of its saplings for 1 year after planting them both inside and outside an exclosure, and in association with or without unpalatable nurse plants. Inside the exclosure, sapling survival was 100%, regardless of nurse plants. However, outside the exclosure saplings associated with nurse plants had 19.5 times higher survival probability. Growth rates were higher inside the exclosure and for saplings associated with nurse plants. The positive effect of nurse plants on growth was similar inside and outside the exclosure. Cattle browsing and trampling on Parlatore's Podocarp were observed for the first time, highlighting a previously undocumented threat to the species. Our findings offer valuable insights for ecological restoration, potentially suggesting strategic sapling planting near unpalatable plants and considering cattle exclusion in key areas to enhance long-term restoration success in the Southern Yungas' Montane Forest.
Optimization-Based Vibration Control Analysis of Dampers in High-Rise Building
Authors: Vanshaj Kumar , Shukla A. K. , Shukla Mukesh , Mishra Abhishek
Published: July 2024

Tuned mass dampers (TMDs) are a useful control of vibrations for tall buildings and can be considered equal to burdens such as breezes and earthquakes. The better limits for TMD are to reduce the earthquake vibrations of tall buildings including soil–structure interaction (SSI) influences. This study proposes the multi-objective Black Widow Optimization (BWO) with Elman neural network (ENN) computation that is brought on to find the optimal limits of TMD. Considering that this proposed model analyzed the mass, stiffness, and damping ratio of TMD to get the maximum accelerations and displacement of 40 story building model, from the execution results, starting from this proposed BWO–Elman model to the expected methodology, the most outrageous TMD limits are better, likewise, the reduction of acceleration and displacement are 25% and 19.86% in the proposed study. This study assists the researchers with a better understanding of earthquake vibration and leads the fashioners to achieve superior TMD for tall designs. The impact of vibration control on the displacements and accelerations of both controlled and uncontrolled buildings is investigated in this work. It uses a MATLAB software technique to analyze their modal replies, moreover, this proposed optimal TMD model is compared with conventional techniques by acceleration and stiffness parameters.
Automata-Based Quantum Circuit Design Patterns Identification: A Novel Approach and Experimental Verification
Authors: Romero Francisco P. , Cruz-Lemus José A. , Jiménez-Fernández Sergio , Piattini Mario
Published: July 2024

This paper introduces a strategy for identifying design patterns in quantum circuits. The foundation of this approach relies on using the information procured from both the segmentation and the analysis of these circuits as primary data. The approach of the methodology is based on the novel interpretation of quantum circuit components through the lens of an automaton. Additionally, the method entails the generation of input symbols for this finite automaton. The symbols are derived from the matching process between design patterns and components of quantum circuits. Two tool prototypes, QPainter and QCDPDTool, have been developed to represent quantum circuits graphically and automatically detect quantum patterns. Using them, the primary reasoning process is carried out by an automaton that can manage representations of quantum circuit components. A suite of experiments on a set of quantum circuit sequences reveals promising results and offers empirical support for our approach. Furthermore, we explore how these experimental findings can be leveraged to improve the efficacy of design pattern identification in quantum circuits.
Shadows and quasinormal modes of black holes in the Einstein-SU(N) nonlinear sigma model
Authors: Al-Badawi Ahmad , Sekhmani Yassine , Rayimbaev Javlon , Myrzakulov Ratbay
Published: July 2024

This research surveys the impact of the flavor number parameter on a four-dimensional Black Hole (BH) solution in Einstein’s nonlinear sigma model-[Formula: see text] (NLSM) in accordance with the shadow, energy emission rate, sparsity, massless scalar, and electromagnetic quasinormal mode spectra. Related investigations are being carried out to explore the influence of the flavor number parameter. In particular, the findings show that shadow behavior and energy emission rate are antinomic processes in view of the flavor number parameter. On the other hand, the [Formula: see text]-NLSM BH’s quasinormal modes are computed by first calculating the effective potential generated by the perturbation of scalar and electromagnetic fields, followed by a numerical analysis based on the sixth-order WKB approach. Our results show that the QNMs of the [Formula: see text]-NLSM BH damp more slowly as flavor number N increases.
AFFINE MODELS WITH PATH-DEPENDENCE UNDER PARAMETER UNCERTAINTY AND THEIR APPLICATION IN FINANCE
Authors: GEUCHEN BENEDIKT , OBERPRILLER KATHARINA , SCHMIDT THORSTEN
Published: July 2024

In this paper, we consider one-dimensional generalized affine processes under the paradigm of Knightian uncertainty (the so-called nonlinear generalized affine models). This extends and generalizes previous results in Fadina et al.  ( 2019 ) and Lütkebohmert et al.  ( 2022 ). In particular, we study the case when the payoff is allowed to depend on the path, like it is the case for barrier options or Asian options.

To this end, we develop the path-dependent setting for the value function relying on functional Itô calculus. We establish a dynamic programming principle which then leads to a functional nonlinear Kolmogorov equation describing the evolution of the value function. While for Asian options, the valuation can be traced back to PDE methods, this is no longer possible for more complicated payoffs like barrier options. To handle such payoffs in an efficient manner, we approximate the functional derivatives with deep neural networks and show that the numerical valuation under parameter uncertainty is highly tractable.

Finally, we consider the application to structural modelling of credit and counterparty risk, where both parameter uncertainty and path-dependence are crucial and the approach proposed here opens the door to efficient numerical methods in this field.
Seismic Response Analysis of Composite Isolation Structures with Non-Classical Damping
Authors: Wang Jinghui , Tan Ping , Huang Tiancan , He Xuefeng , Zhou Fulin , Zheng Xiaojun
Published: July 2024

In this paper, a physical index for quantitatively evaluating the non-proportional damping characteristics is proposed. Additionally, a direct design approach applicable to composite isolated structures (consisting of an upper damping structure and a base isolation system) is proposed for performance analysis of practical three-dimensional non-proportional damped structures. Furthermore, the elastic–plastic behavior of the structure under acceleration excitation is considered to determine the structural damage and response, improving computational accuracy and providing better solutions for the analysis and design of composite isolated structures. Analysis studies have shown that under rare and extremely rare earthquake events, structures designed using the complex modal response spectrum method (CM-RSM) exhibit less damage compared to those designed using the forced decoupling response spectrum method (FD-RSM) compared to the results obtained using the complex modal response spectrum method. For the seismic performance study of non-proportional damped structures, it is recommended to use the complex modal response spectrum method. With an increasing earthquake intensity, the proportion of energy dissipation due to the nonlinear strain energy dissipation of a structure increases, and the proportion of energy dissipation due to the isolators and dampers in the damping energy portion decreases.
Generating quantum dissonance via local operations
Authors: Torun Gökhan
Published: July 2024

Correlations may arise in quantum systems through various means, of which the most remarkable one is quantum entanglement. Additionally, there are systems that exhibit nonclassical correlations even in the absence of entanglement. Quantum dissonance refers to how Quantum Discord (QD) — the difference between the total correlation and the classical correlation in a given quantum state — appears as a nonclassical correlation in a system without entanglement. It could be said that QD has the potential to provide a more inclusive viewpoint for discerning the nonclassical correlations. In this paper, we address the problem of manipulating the QD between two subsystems through local operations. We propose two explicit procedures for obtaining separable Werner states, a type of mixed state with nonzero QD. Both approaches involve performing local operations on classically correlated states and offers a step-by-step method for obtaining separable Werner states with nonzero discord, providing an alternative (explicit and user-friendly) to existing methods.
A Lumped Mass Meshfree Collocation Method with Frequency Error Estimates for Free Vibration Analysis of Elastic Solids
Authors: Deng Like , Yuan Kai , Wang Dongdong
Published: July 2024

A meshfree collocation method with particular reference to the lumped mass formulation is presented for the free vibration analysis of elastic solids. The lumped mass formulation leads to a simple unit entry for the collocation mass matrix. With the aid of the consistency conditions of meshfree approximation, a systematic theoretical investigation is provided to measure the frequency error of lumped mass meshfree collocation analysis of elastic solids, where both the pressure and shear waves are considered in the frequency accuracy order estimation. It is proven that the lumped mass meshfree collocation method yields similar convergence rates as those given by the consistent mass formulation, i.e., for a [Formula: see text]th degree basis function, the frequency accuracy order is [Formula: see text] for even basis degree and [Formula: see text] for odd basis degree, respectively. In addition, it is shown that the lumped mass collocation approach using interpolatory meshfree shape functions is free of spurious modes. Numerical results consistently validate the proposed theoretical frequency error estimates for the free vibration analysis of elastic solids.
Recent advances in near-infrared photobiomodulation for the intervention of acquired brain injury
Authors: Huang Yujing , Zhang Yujing , Yang Chen , Xu Mengze , Yuan Zhen
Published: July 2024

Acquired brain injury (ABI) is an injury that affects the brain structure and function. Traditional ABI treatment strategies, including medications and rehabilitation therapy, exhibit their ability to improve its impairments in cognition, emotion, and physical activity. Recently, near-infrared (NIR) photobiomodulation (PBM) has emerged as a promising physical intervention method for ABI, demonstrating that low-level light therapy can modulate cellular metabolic processes, reduce the inflammation and reactive oxygen species of ABI microenvironments, and promote neural repair and regeneration. Preclinical studies using ABI models have been carried out, revealing the potential of PBM in promoting brain injury recovery although its clinical application is still in its early stages. In this review, we first inspected the possible physical and biological mechanisms of NIR-PBM, and then reported the pathophysiology and physiology of ABI underlying NIR-PBM intervention. Therefore, the potential of NIR-PBM as a therapeutic intervention in ABI was demonstrated and it is also expected that further work can facilitate its clinical applications.
RISK-BASED CONTRIBUTION IN DEPOSIT GUARANTEE SCHEMES: A ROBUST PRINCIPAL COMPONENT ANALYSIS IN KEY RISK FACTORS’ WEIGHTING STEP
Authors: GIORGIO SAVERIO , MURÈ PINA , PACCIONE COSIMO , BITTUCCI LUCILLA
Published: July 2024

This paper investigates the method for calculating funding banks must provide to Deposit Guarantee Schemes (DGSs) according to the “ex-ante” and “risk-based” criteria introduced by Directive 2014/49/EU (DGSD). We aim to further support the existing documents providing an approach to identify risk indicators and assign weights thereof to determine fundings to be paid to DGSs. It is worth noting that such an approach could enhance current practices as it takes into account the risk and performance of banks as opposed to the overall banking market. By doing so, a more targeted funding can be encouraged. Our results consider the Texas ratio as one of the indicators to look out for. Likewise, such methods could serve as self-assessment frameworks for Institutional Protection Schemes (IPSs) and banks, fostering sound and prudent management, in turn warding off “moral hazard” issues.
From microfacets to participating media: A unified theory of light transport with stochastic geometry
Authors: Seyb Dario , d'Eon Eugene , Bitterli Benedikt , Jarosz Wojciech
Published: July 2024

Stochastic geometry models have enjoyed immense success in graphics for modeling interactions of light with complex phenomena such as participating media, rough surfaces, fibers, and more. Although each of these models operates on the same principle of replacing intricate geometry by a random process and deriving the average light transport across all instances thereof, they are each tailored to one specific application and are fundamentally distinct. Each type of stochastic geometry present in the scene is firmly encapsulated in its own appearance model, with its own statistics and light transport average, and no cross-talk between different models or deterministic and stochastic geometry is possible.

In this paper, we derive a theory of light transport on
stochastic implicit surfaces
, a geometry model capable of expressing deterministic geometry, microfacet surfaces, participating media, and an exciting new continuum in between containing aggregate appearance, non-classical media, and more. Our model naturally supports
spatial correlations
, missing from most existing stochastic models.

Our theory paves the way for tractable rendering of scenes in which all geometry is described by the same stochastic model, while leaving ample future work for developing efficient sampling and rendering algorithms.
Computational Homogenization for Inverse Design of Surface-based Inflatables
Authors: Ren Yingying , Panetta Julian , Suzuki Seiichi , Kusupati Uday , Isvoranu Florin , Pauly Mark
Published: July 2024

Surface-based inflatables are composed of two thin layers of nearly inextensible sheet material joined together along carefully selected fusing curves. During inflation, pressure forces separate the two sheets to maximize the enclosed volume. The fusing curves restrict this expansion, leading to a spatially varying in-plane contraction and hence metric frustration. The inflated structure settles into a 3D equilibrium that balances pressure forces with the internal elastic forces of the sheets.

We present a computational framework for analyzing and designing surface-based inflatable structures with arbitrary fusing patterns. Our approach employs numerical homogenization to characterize the behavior of parametric families of periodic inflatable patch geometries, which can then be combined to tessellate the sheet with smoothly varying patterns. We propose a novel parametrization of the underlying deformation space that allows accurate, efficient, and systematical analysis of the stretching and bending behavior of inflated patches with potentially open boundaries.

We apply our homogenization algorithm to create a database of geometrically diverse fusing patterns spanning a wide range of material properties and deformation characteristics. This database is employed in an inverse design algorithm that solves for fusing curves to best approximate a given input target surface. Local patches are selected and blended to form a global network of curves based on a geometric flattening algorithm. These fusing curves are then further optimized to minimize the distance of the deployed structure to target surface. We show that this approach offers greater flexibility to approximate given target geometries compared to previous work while significantly improving structural performance.
Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis
Authors: Reiser Christian , Garbin Stephan , Srinivasan Pratul , Verbin Dor , Szeliski Richard , Mildenhall Ben , Barron Jonathan , Hedman Peter , Geiger Andreas
Published: July 2024

While surface-based view synthesis algorithms are appealing due to their low computational requirements, they often struggle to reproduce thin structures. In contrast, more expensive methods that model the scene's geometry as a volumetric density field (e.g. NeRF) excel at reconstructing fine geometric detail. However, density fields often represent geometry in a "fuzzy" manner, which hinders exact localization of the surface. In this work, we modify density fields to encourage them to converge towards surfaces, without compromising their ability to reconstruct thin structures. First, we employ a discrete opacity grid representation instead of a continuous density field, which allows opacity values to discontinuously transition from zero to one at the surface. Second, we anti-alias by casting multiple rays per pixel, which allows occlusion boundaries and subpixel structures to be modelled without using semi-transparent voxels. Third, we minimize the binary entropy of the opacity values, which facilitates the extraction of surface geometry by encouraging opacity values to binarize towards the end of training. Lastly, we develop a fusion-based meshing strategy followed by mesh simplification and appearance model fitting. The compact meshes produced by our model can be rendered in real-time on mobile devices and achieve significantly higher view synthesis quality compared to existing mesh-based approaches. Our interactive webdemo is available at https://binary-opacity-grid.github.io.
Spin-Weighted Spherical Harmonics for Polarized Light Transport
Authors: Yi Shinyoung , Kim Donggun , Na Jiwoong , Tong Xin , Kim Min H.
Published: July 2024

The objective of polarization rendering is to simulate the interaction of light with materials exhibiting polarization-dependent behavior. However, integrating polarization into rendering is challenging and increases computational costs significantly. The primary difficulty lies in efficiently modeling and computing the complex reflection phenomena associated with polarized light. Specifically, frequency-domain analysis, essential for efficient environment lighting and storage of complex light interactions, is lacking. To efficiently simulate and reproduce polarized light interactions using frequency-domain techniques, we address the challenge of maintaining continuity in polarized light transport represented by Stokes vectors within angular domains. The conventional spherical harmonics method cannot effectively handle continuity and rotation invariance for Stokes vectors. To overcome this, we develop a new method called polarized spherical harmonics (PSH) based on the spin-weighted spherical harmonics theory. Our method provides a rotation-invariant representation of Stokes vector fields. Furthermore, we introduce frequency domain formulations of polarized rendering equations and spherical convolution based on PSH. We first define spherical convolution on Stokes vector fields in the angular domain, and it also provides efficient computation of polarized light transport, nearly on an entry-wise product in the frequency domain. Our frequency domain formulation, including spherical convolution, led to the development of the first real-time polarization rendering technique under polarized environmental illumination, named precomputed polarized radiance transfer, using our polarized spherical harmonics. Results demonstrate that our method can effectively and accurately simulate and reproduce polarized light interactions in complex reflection phenomena, including polarized environmental illumination and soft shadows.
Fabric Tessellation: Realizing Freeform Surfaces by Smocking
Authors: Segall Aviv , Ren Jing , Vaxman Amir , Sorkine-Hornung Olga
Published: July 2024

We present a novel method for realizing freeform surfaces with pieces of flat fabric, where curvature is created by stitching together points on the fabric using a technique known as
smocking.
Smocking is renowned for producing intricate geometric textures with voluminous pleats. However, it has been mostly used to realize flat shapes or manually designed, limited classes of curved surfaces. Our method combines the computation of directional fields with continuous optimization of a Tangram graph in the plane, which together allow us to realize surfaces of arbitrary topology and curvature with smocking patterns of diverse symmetries. Given a target surface and the desired smocking pattern, our method outputs a corresponding 2D smocking pattern that can be fabricated by sewing specified points together. The resulting textile fabrication approximates the target shape and exhibits visually pleasing pleats. We validate our method through physical fabrication of various smocked examples.
Training-Free Consistent Text-to-Image Generation
Authors: Tewel Yoad , Kaduri Omri , Gal Rinon , Kasten Yoni , Wolf Lior , Chechik Gal , Atzmon Yuval
Published: July 2024

Text-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language. However, using these models to consistently portraythe samesubject across diverse prompts remains challenging. Existing approaches fine-tune the model to teach it new words that describe specific user-provided subjects or add image conditioning to the model. These methods require lengthy persubject optimization or large-scale pre-training. Moreover, they struggle to align generated images with text prompts and face difficulties in portraying multiple subjects. Here, we presentConsiStory, atraining-freeapproach that enables consistent subject generation by sharing the internal activations of the pretrained model. We introduce a subject-driven shared attention block and correspondence-based feature injection to promote subject consistency between images. Additionally, we develop strategies to encourage layout diversity while maintaining subject consistency. We compareConsiStoryto a range of baselines, and demonstrate state-of-the-art performance on subject consistency and text alignment, without requiring a single optimization step. Finally,ConsiStorycan naturally extend to multi-subject scenarios, and even enable training-freepersonalizationfor common objects.
Neural Gaussian Scale-Space Fields
Authors: Mujkanovic Felix , Nsampi Ntumba Elie , Theobalt Christian , Seidel Hans-Peter , Leimkühler Thomas
Published: July 2024

Gaussian scale spaces are a cornerstone of signal representation and processing, with applications in filtering, multiscale analysis, anti-aliasing, and many more. However, obtaining such a scale space is costly and cumbersome, in particular for continuous representations such as neural fields. We present an efficient and lightweight method to learn the fully continuous, anisotropic Gaussian scale space of an arbitrary signal. Based on Fourier feature modulation and Lipschitz bounding, our approach is trained self-supervised, i.e., training does not require any manual filtering. Our neural Gaussian scale-space fields faithfully capture multiscale representations across a broad range of modalities, and support a diverse set of applications. These include images, geometry, light-stage data, texture anti-aliasing, and multiscale optimization.
Proxy Asset Generation for Cloth Simulation in Games
Authors: Zheng Zhongtian , Wang Tongtong , Feng Qijia , Pan Zherong , Gao Xifeng , Wu Kui
Published: July 2024

Simulating high-resolution cloth poses computational challenges in real-time applications. In the gaming industry, the proxy mesh technique offers an alternative, simulating a simplified low-resolution cloth geometry,
proxy mesh.
This proxy mesh's dynamics drive the detailed high-resolution geometry,
visual mesh
, through Linear Blended Skinning (LBS). However, generating a suitable proxy mesh with appropriate skinning weights from a given visual mesh is non-trivial, often requiring skilled artists several days for fine-tuning. This paper presents an automatic pipeline to convert an ill-conditioned highresolution visual mesh into a single-layer low-poly proxy mesh. Given that the input visual mesh may not be simulation-ready, our approach then simulates the proxy mesh based on specific use scenarios and optimizes the skinning weights, relying on differential skinning with several well-designed loss functions to ensure the skinned visual mesh appears plausible in the final simulation. We have tested our method on various challenging cloth models, demonstrating its robustness and effectiveness.
Capacitive Touch Sensing on General 3D Surfaces
Authors: Palma Gianpaolo , Pourjafarian Narges , Steimle Jürgen , Cignoni Paolo
Published: July 2024

Mutual-capacitive sensing is the most common technology for detecting multi-touch, especially on flat and simple curvature surfaces. Its extension to a more complex shape is still challenging, as a uniform distribution of sensing electrodes is required for consistent touch sensitivity across the surface. To overcome this problem, we propose a method to adapt the sensor layout of common capacitive multi-touch sensors to more complex 3D surfaces, ensuring high-resolution, robust multi-touch detection. The method automatically computes a grid of transmitter and receiver electrodes with as regular distribution as possible over a general 3D shape. It starts with the computation of a proxy geometry by quad meshing used to place the electrodes through the dual-edge graph. It then arranges electrodes on the surface to minimize the number of touch controllers required for capacitive sensing and the number of input/output pins to connect the electrodes with the controllers. We reach these objectives using a new simplification and clustering algorithm for a regular quad-patch layout. The reduced patch layout is used to optimize the routing of all the structures (surface grooves and internal pipes) needed to host all electrodes on the surface and inside the object's volume, considering the geometric constraints of the 3D shape. Finally, we print the 3D object prototype ready to be equipped with the electrodes. We analyze the performance of the proposed quad layout simplification and clustering algorithm using different quad meshing and characterize the signal quality and accuracy of the capacitive touch sensor for different non-planar geometries. The tested prototypes show precise and robust multi-touch detection with good Signal-to-Noise Ratio and spatial accuracy of about 1mm.
Scintilla: Simulating Combustible Vegetation for Wildfires
Authors: Kokosza Andrzej , Wrede Helge , Gonzalez Esparza Daniel , Makowski Milosz , Liu Daoming , Michels Dominik L. , Pirk Soren , Palubicki Wojtek
Published: July 2024

Wildfires are a complex physical phenomenon that involves the combustion of a variety of flammable materials ranging from fallen leaves and dried twigs to decomposing organic material and living flora. All these materials can potentially act as fuel with different properties that determine the progress and severity of a wildfire. In this paper, we propose a novel approach for simulating the dynamic interaction between the varying components of a wildfire, including processes of convection, combustion and heat transfer between vegetation, soil and atmosphere. We propose a novel representation of vegetation that includes detailed branch geometry, fuel moisture, and distribution of grass, fine fuel, and duff. Furthermore, we model the ignition, generation, and transport of fire by firebrands and embers. This allows simulating and rendering virtual 3D wildfires that realistically capture key aspects of the process, such as progressions from ground to crown fires, the impact of embers carried by wind, and the effects of fire barriers and other human intervention methods. We evaluate our approach through numerous experiments and based on comparisons to real-world wildfire data.
Lifting Directional Fields to Minimal Sections
Authors: Palmer David , Chern Albert , Solomon Justin
Published: July 2024

Directional fields, including unit vector, line, and cross fields, are essential tools in the geometry processing toolkit. The topology of directional fields is characterized by their singularities. While singularities play an important role in downstream applications such as meshing, existing methods for computing directional fields either require them to be specified in advance, ignore them altogether, or treat them as zeros of a relaxed field. While fields are ill-defined at their singularities, the graphs of directional fields with singularities are well-defined surfaces in a circle bundle. By lifting optimization of fields to optimization over their graphs, we can exploit a natural convex relaxation to a
minimal section
problem over the space of currents in the bundle. This relaxation treats singularities as first-class citizens, expressing the relationship between fields and singularities as an explicit boundary condition. As curvature frustrates finite element discretization of the bundle, we devise a hybrid spectral method for representing and optimizing minimal sections. Our method supports field optimization on both flat and curved domains and enables more precise control over singularity placement.
Lightning-fast Method of Fundamental Solutions
Authors: Chen Jiong , Schaefer Florian , Desbrun Mathieu
Published: July 2024

The method of fundamental solutions (MFS) and its associated boundary element method (BEM) have gained popularity in computer graphics due to the reduced dimensionality they offer: for three-dimensional linear problems, they only require variables on the domain boundary to solve and evaluate the solution throughout space, making them a valuable tool in a wide variety of applications. However, MFS and BEM have poor computational scalability and huge memory requirements for large-scale problems, limiting their applicability and efficiency in practice. By leveraging connections with Gaussian Processes and exploiting the sparse structure of the inverses of boundary integral matrices, we introduce a variational preconditioner that can be computed via a sparse inverse-Cholesky factorization in a massively parallel manner. We show that applying our preconditioner to the Preconditioned Conjugate Gradient algorithm greatly improves the efficiency of MFS or BEM solves, up to four orders of magnitude in our series of tests.
Real-Time Path Guiding Using Bounding Voxel Sampling
Authors: Lu Haolin , Chang Wesley , Hedstrom Trevor , Li Tzu-Mao
Published: July 2024

We propose a real-time path guiding method, Voxel Path Guiding (VXPG), that significantly improves fitting efficiency under limited sampling budget. Our key idea is to use a spatial irradiance voxel data structure across all shading points to guide the location of path vertices. For each frame, we first populate the voxel data structure with irradiance and geometry information. To sample from the data structure for a shading point, we need to select a voxel with high contribution to that point. To importance sample the voxels while taking visibility into consideration, we adapt techniques from offline many-lights rendering by clustering pairs of shading points and voxels. Finally, we unbiasedly sample within the selected voxel while taking the geometry inside into consideration. Our experiments show that VXPG achieves significantly lower perceptual error compared to other real-time path guiding and virtual point light methods under equal-time comparison. Furthermore, our method does not rely on temporal information, but can be used together with other temporal reuse sampling techniques such as ReSTIR to further improve sampling efficiency.
TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Prompts
Authors: Zhuang Jingyu , Kang Di , Cao Yan-Pei , Li Guanbin , Lin Liang , Shan Ying
Published: July 2024

Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified appearance and location of the editing result due to the inherent limitations of the text description. To this end, we propose a 3D scene editing framework, TIP-Editor, that accepts both text and image prompts and a 3D bounding box to specify the editing region. With the image prompt, users can conveniently specify the detailed appearance/style of the target content in complement to the text description, enabling accurate control of the appearance. Specifically, TIP-Editor employs a stepwise 2D personalization strategy to better learn the representation of the existing scene and the reference image, in which a localization loss is proposed to encourage correct object placement as specified by the bounding box. Additionally, TIP-Editor utilizes explicit and flexible 3D Gaussian splatting (GS) as the 3D representation to facilitate local editing while keeping the background unchanged. Extensive experiments have demonstrated that TIP-Editor conducts accurate editing following the text and image prompts in the specified bounding box region, consistently outperforming the baselines in editing quality, and the alignment to the prompts, qualitatively and quantitatively.
Efficient Debris-flow Simulation for Steep Terrain Erosion
Authors: Jain Aryamaan , Benes Bedrich , Cordonnier Guillaume
Published: July 2024

Erosion simulation is a common approach used for generating and authoring mountainous terrains. While water is considered the primary erosion factor, its simulation fails to capture steep slopes near the ridges. In these low-drainage areas, erosion is often approximated with slope-reducing erosion, which yields unrealistically uniform slopes. However, geomorphology observed that another process dominates the low-drainage areas: erosion by debris flow, which is a mixture of mud and rocks triggered by strong climatic events. We propose a new method to capture the interactions between debris flow and fluvial erosion thanks to a new mathematical formulation for debris flow erosion derived from geomorphology and a unified GPU algorithm for erosion and deposition. In particular, we observe that sediment and debris deposition tend to intersect river paths, which motivates the design of a new, approximate flow routing algorithm on the GPU to estimate the water path out of these newly formed depressions. We demonstrate that debris flow carves distinct patterns in the form of erosive scars on steep slopes and cones of deposited debris competing with fluvial erosion downstream.
NICER: A New and Improved Consumed Endurance and Recovery Metric to Quantify Muscle Fatigue of Mid-Air Interactions
Authors: Li Yi , Tag Benjamin , Dai Shaozhang , Crowther Robert , Dwyer Tim , Irani Pourang , Ens Barrett
Published: July 2024

Natural gestures are crucial for mid-air interaction, but predicting and managing muscle fatigue is challenging. Existing torque-based models are limited in their ability to model above-shoulder interactions and to account for fatigue recovery. We introduce a new hybrid model,
NICER
, which combines a torque-based approach with a new term derived from the empirical measurement of muscle contraction and a recovery factor to account for decreasing fatigue during rest. We evaluated NICER in a mid-air selection task using two interaction methods with different degrees of perceived fatigue. Results show that NICER can accurately model above-shoulder interactions as well as reflect fatigue recovery during rest periods. Moreover, both interaction methods show a stronger correlation with subjective fatigue measurement (
ρ
= 0.978/0.976) than a previous model, Cumulative Fatigue (
ρ
= 0.966/0.923), confirming that NICER is a powerful analytical tool to predict fatigue across a variety of gesture-based interactive applications.
Computational Illusion Knitting
Authors: Zhu Amy , Mei Yuxuan , Jones Benjamin , Tatlock Zachary , Schulz Adriana
Published: July 2024

Illusion-knit fabrics reveal distinct patterns or images depending on the viewing angle. Artists have manually achieved this effect by exploiting "microgeometry," i.e., small differences in stitch heights. However, past work in computational 3D knitting does not model or exploit designs based on stitch height variation. This paper establishes a foundation for exploring illusion knitting in the context of computational design and fabrication. We observe that the design space is highly constrained, elucidate these constraints, and derive strategies for developing effective, machine-knittable illusion patterns. We partially automate these strategies in a new interactive design tool that reduces difficult patterning tasks to familiar image editing tasks. Illusion patterns also uncover new fabrication challenges regarding mixed colorwork and texture; we describe new algorithms for mitigating fabrication failures and ensuring high-quality knit results.
Universal Facial Encoding of Codec Avatars from VR Headsets
Authors: Bai Shaojie , Wang Te-Li , Li Chenghui , Venkatesh Akshay , Simon Tomas , Cao Chen , Schwartz Gabriel , Saragih Jason , Sheikh Yaser , Wei Shih-En
Published: July 2024

Faithful real-time facial animation is essential for avatar-mediated telepresence in Virtual Reality (VR). To emulate authentic communication, avatar animation needs to be efficient and accurate: able to capture both extreme and subtle expressions within a few milliseconds to sustain the rhythm of natural conversations. The oblique and incomplete views of the face, variability in the donning of headsets, and illumination variation due to the environment are some of the unique challenges in generalization to unseen faces. In this paper, we present a method that can animate a photorealistic avatar in realtime from head-mounted cameras (HMCs) on a consumer VR headset. We present a self-supervised learning approach, based on a cross-view reconstruction objective, that enables generalization to unseen users. We present a lightweight expression calibration mechanism that increases accuracy with minimal additional cost to run-time efficiency. We present an improved parameterization for precise ground-truth generation that provides robustness to environmental variation. The resulting system produces accurate facial animation for unseen users wearing VR headsets in realtime. We compare our approach to prior face-encoding methods demonstrating significant improvements in both quantitative metrics and qualitative results.
Improving Fault Tolerance for FPGA SoCs through Post-Radiation Design Analysis
Authors: Wilson Andrew Elbert , Baker Nathan , Campbell Ethan , Wirthlin Michael
Published: July 2024

FPGAs have been shown to operate reliably within harsh radiation environments by employing single-event upset (SEU) mitigation techniques, such as configuration scrubbing, triple-modular redundancy, error correction coding, and radiation aware implementation techniques. The effectiveness of these techniques, however, is limited when using complex system-level designs that employ complex I/O interfaces with single-point failures. In previous work, a complex SoC system running Linux applied several of these techniques only to obtain an improvement of 14

\(\times\)

in mean time to failure (MTTF). A detailed post-radiation fault analysis found that the limitations in reliability were due to the DDR interface, the global clock network, and interconnect. This article applied a number of design-specific SEU mitigation techniques to address the limitations in reliability of this design. These changes include triplicating the global clock, optimizing the placement of the reduction output voters and input flip-flops, and employing a mapping technique called “striping.” The application of these techniques improved MTTF of the mitigated design by a factor of 1.54

\(\times\)

and thus provides a 22.8X

\(\times\)

MTTF improvement over the unmitigated design. A post-radiation fault analysis using BFAT was also performed to find the remaining design vulnerabilities.