bluuebunny/crossref_metadata_2025 huggingface dataset:
Stenting of a partially obstructed nasolacrimal duct using a steerable angle‐tipped hydrophilic guidewire in a cat
Authors: Park Shin Ae , Oetelaar Garrett , Kim Sun Young
Published: July 2022

Objective

This case report describes the successful correction of partial obstruction of the NL duct in a cat by means of a modified retrograde NL duct cannulation using a steerable angle‐tipped hydrophilic guidewire (AH guidewire) following a paranasal incision.

Animal Studied

A 2‐year‐old neutered male American domestic shorthair cat was referred to the Purdue University Veterinary Hospital (PUVH) for chronic epiphora suspected secondary to nasolacrimal (NL) system obstruction.

Procedures

At the first visit, the cat had epiphora OD and facial dermatitis but no other abnormalities on physical and ophthalmic examinations. Computed tomography (CT)‐dacryocystorhinography revealed partial obstruction of the NL duct secondary to stenosis near the distal root of the right maxillary third premolar (107). A digital three‐dimensional (3D) model of the right maxilla and NL duct was created for inspection and virtual cannulation of the NL. The model was 3D printed and cannulation of the NL duct was rehearsed with various stent materials. Retrograde NL stenting with the guidance of a steerable angle‐tipped hydrophilic guidewire was conducted following a paranasal incision. A urethral catheter was cannulated over the guidewire and maintained for 44 days.

Results

The epiphora resolved immediately after stenting. At 21 days post‐stenting, the cat developed acute bullous keratopathy secondary to self‐trauma which was treated with a third eyelid flap. On the final follow‐up communication with the owner at 210 days post‐stenting, no epiphora or any other concerns were reported.

Conclusion

To the authors' knowledge, this is the first report of successful NL stenting and resolution of epiphora in a cat with a partial NL system obstruction.
Perfect points on curves of genus 1 and consequences for supersingular K3 surfaces
Authors: Bragg Daniel , Lieblich Max
Published: July 2022

We describe a method to show that certain elliptic surfaces do not admit purely inseparable multisections (equivalently, that genus 1 curves over function fields admit no points over the perfect closure of the base field) and use it to show that any non-Jacobian elliptic structure on a very general supersingular K3 surface has no purely inseparable multisections. We also describe specific examples of genus 1 fibrations on supersingular K3 surfaces without purely inseparable multisections.
Caracterización de metodologías para la evaluación integral de la sostenibilidad del transporte urbano
Authors: Gutiérrez Elena Valentina , Flórez Maria Fernanda , Mazo Juan Sebastian , Medina Pacheco Santiago , Aristizábal Maria-Cristina , Cardenas Laura M.
Published: July 2022

Objetivo: Caracterizar las metodologías para la evaluación integral de la sostenibilidad del transporte urbano, e identificar las oportunidades de investigación en países en desarrollo. Materiales y métodos: Se hace una revisión estructurada de la literatura en tres etapas y se propone una taxonomía para la caracterización de marcos conceptuales, modelos analíticos, índices e indicadores. Se presenta también un análisis de los indicadores en once categorías propuestas. Resultados y discusión: Se evidencia un incremento en la literatura científica e institucional dedicada al estudio de metodologías para la evaluación de la sostenibilidad en las últimas dos décadas. Sin embargo, se observa también la carencia de métodos que permitan incluir las dimensiones económica, ambiental y social de manera integral, en particular para evaluar la sostenibilidad de los sistemas de transporte urbano. La mayor parte de los trabajos está centrada en el desarrollo de índices e indicadores, y en la aplicación en países europeos y norteamericanos. Conclusiones: La caracterización identifica cuáles son las metodologías, las instituciones y los países que han implementado evaluaciones integradas de la sostenibilidad del transporte urbano. Igualmente, se identifican las dimensiones de la sostenibilidad más estudiadas, y se reseñan las oportunidades de investigación en países en desarrollo.
Effectiveness of an Intelligent Foot Orthosis in Lateral Fall Prevention
Authors: Yamamoto Rieko , Itami Sho , Kawabata Masashi , Shiraishi Toshihiko
Published: July 2022

The aim of this study was to validate the effectiveness of the newly developed intelligent foot orthosis (IFO) at preventing lateral falls. The IFO is a wearable fall prevention system based on using a small magnetorheological brake to control the height of the lateral sole. Experiments were performed to compare the walking motions on a lateral slope under four conditions: without IFO, with IFO current-OFF, with IFO current-ON, and with IFO control-ON. The mediolateral center of gravity and center of pressure horizontal distance (ML COG–COP HD) were measured in three-dimensional motion analysis to represent the change in posture on the frontal plane. To observe the corresponding muscular activity, surface electromyography (EMG) was performed to obtain the mean and peak root-mean-square (RMS) for the tibia anterior (TA) and peroneus longus (PL) in the first half of the stance phase when the IFO applied control. In the results, ML COG-COP HD increased significantly under the “with IFO control-ON” compared to the “without IFO” and “with IFO current-ON” conditions. The mean RMS of the TA was significantly decreased under the “with IFO current-ON” and “with IFO control-ON” conditions compared to the “without IFO” condition. These results demonstrate that the posture moved away from the lateral fall direction primarily due to IFO assistance rather than muscular activity, which would be a consequence of human postural control. Thus, the IFO does appear to help prevent lateral falls.
Dynamic Resource Allocation in Systems-of-Systems Using a Heuristic-Based Interpretable Deep Reinforcement Learning
Authors: Chen Qiliang , Heydari Babak
Published: July 2022

Systems-of-systems (SoS) often include multiple agents that interact in both cooperative and competitive modes. Moreover, they involve multiple resources, including energy, information, and bandwidth. If these resources are limited, agents need to decide how to share resources cooperatively to reach the system-level goal, while performing the tasks assigned to them autonomously. This paper takes a step toward addressing these challenges by proposing a dynamic two-tier learning framework, based on deep reinforcement learning that enables dynamic resource allocation while acknowledging the autonomy of systems constituents. The two-tier learning framework that decouples the learning process of the SoS constituents from that of the resource manager ensures that the autonomy and learning of the SoS constituents are not compromised as a result of interventions executed by the resource manager. We apply the proposed two-tier learning framework on a customized OpenAI Gym environment and compare the results of the proposed framework to baseline methods of resource allocation to show the superior performance of the two-tier learning scheme across a different set of SoS key parameters. We then use the results of this experiment and apply our heuristic inference method to interpret the decisions of the resource manager for a range of environment and agent parameters.
Numerical Investigation on Heat Flux Variation in Fuel Bundle Over Fully Voided Concentric Channel of IPHWR Under Severe Accidental Scenario
Authors: Kashyap Ishan , Kumar Sidharth , Singh Saurav Kumar , Sharma Mukesh
Published: July 2022

A steady-state thermal analysis is performed on a fully voided channel of an Indian pressurized heavy water reactor (IPHWR) by providing variable heat flux inputs of 800 W/m2, 1500 W/m2, 2500 W/m2, 3500 W/m2, and 4500 W/m2 for evaluating the numerical results of temperature distributions in pressure tube (PT) and calandria tube (CT) at concentric scenarios using a numerical approach. The top to bottom temperature difference of PT and CT is found to be 0.57% and 3.31%, respectively, for 800 W/m2 input heat flux, and this variation decreases to 0.015% and 0.05%, respectively, for 4500 W/m2 input heat flux, thus pointing out that increasing the heat flux leads to the decreased top to bottom temperature difference. Also, the temperature distribution pattern is found to be similar for all the input heat fluxes, and for a particular heat flux, the change in circumferential temperature is found to be negligible. The boiling phenomenon starts at 2500 W/m2, and the volume fraction of moderator vapor increases as the heat flux is increased, the average density of moderators inside the enclosure decreases, and continuous variation in film thickness is also observed with respect to time for a particular heat flux value. The results also showed that the moderator acted as an effective heat sink for higher heat input rates.
Comparison of Sensorimotor Integration and Skill-Related Physical Fitness Components Between College Athletes With and Without Forward Head Posture
Authors: Moustafa Ibrahim , Kim Meeyoung , Harrison Deed E.
Published: July 2022

Objective: To evaluate sensorimotor integration and skill-related physical fitness components for participants with forward head posture (FHP) compared with strictly matched controls with normal head alignment. Material and Methods: We measured FHP, sensorimotor processing, and skill-related physical fitness variables in 50 participants with FHP and in 50 participants matched for age, gender, and body mass index with normal FHP, defined as having a craniovertebral angle >55°. Sensorimotor processing and integration variables were: (1) amplitudes of the spinal N13, (2) brainstem P14, (3) parietal N20 and P27, and (4) frontal N30 potentials. The skill-related physical fitness variables selected for the study were (1) T-test agility, (2) leg power, (3) stork static balance test, and (4) Y-balance test. Results: There was a statistically significant difference between the FHP group and control group for the sensorimotor integration variable: frontal N30 potentials (P < .05). Additionally, between-group differences were found for the sensorimotor processing variables: amplitudes of spinal N13, brainstem P14, and parietal N20, and P27 (P < .05). Statistically significant differences between groups for the skill-related physical fitness variables were also identified: T-test agility, leg power, stork static balance test, and Y-balance test (P < .05). The magnitude of the craniovertebral angle showed a correlation with all measured variables (P < .05). Conclusion: College athletes with FHP exhibited altered sensorimotor processing and integration measurements and less efficient skill-related physical fitness compared with athletes with normal sagittal head posture alignment.
Engineered immunomodulatory accessory cells improve experimental allogeneic islet transplantation without immunosuppression
Authors: Wang Xi , Wang Kai , Yu Ming , Velluto Diana , Hong Xuechong , Wang Bo , Chiu Alan , Melero-Martin Juan M. , Tomei Alice A. , Ma Minglin
Published: July 2022

Islet transplantation has been established as a viable treatment modality for type 1 diabetes. However, the side effects of the systemic immunosuppression required for patients often outweigh its benefits. Here, we engineer programmed death ligand-1 and cytotoxic T lymphocyte antigen 4 immunoglobulin fusion protein–modified mesenchymal stromal cells (MSCs) as accessory cells for islet cotransplantation. The engineered MSCs (eMSCs) improved the outcome of both syngeneic and allogeneic islet transplantation in diabetic mice and resulted in allograft survival for up to 100 days without any systemic immunosuppression. Immunophenotyping revealed reduced infiltration of CD4
+
or CD8
+
T effector cells and increased infiltration of T regulatory cells within the allografts cotransplanted with eMSCs compared to controls. The results suggest that the eMSCs can induce local immunomodulation and may be applicable in clinical islet transplantation to reduce or minimize the need of systemic immunosuppression and ameliorate its negative impact.
The ER protein Creld regulates ER-mitochondria contact dynamics and respiratory complex 1 activity
Authors: Paradis Marie , Kucharowski Nicole , Edwards Faret Gabriela , Maya Palacios Santiago José , Meyer Christian , Stümpges Birgit , Jamitzky Isabell , Kalinowski Julia , Thiele Christoph , Bauer Reinhard , Paululat Achim , Sellin Julia , Bülow Margret Helene
Published: July 2022

Dynamic contacts are formed between endoplasmic reticulum (ER) and mitochondria that enable the exchange of calcium and phospholipids. Disturbed contacts between ER and mitochondria impair mitochondrial dynamics and are a molecular hallmark of Parkinson’s disease, which is also characterized by impaired complex I activity and dopaminergic neuron degeneration. Here, we analyzed the role of cysteine-rich with EGF-like domain (Creld), a poorly characterized risk gene for Parkinson’s disease, in the regulation of mitochondrial dynamics and function. We found that loss of Creld leads to mitochondrial hyperfusion and reduced ROS signaling in
Drosophila melanogaster
,
Xenopus tropicalis
, and human cells. Creld fly mutants show differences in ER-mitochondria contacts and reduced respiratory complex I activity. The resulting low–hydrogen peroxide levels are linked to disturbed neuronal activity and lead to impaired locomotion, but not neurodegeneration, in Creld mutants. We conclude that Creld regulates ER-mitochondria communication and thereby hydrogen peroxide formation, which is required for normal neuron function.
The evolution of dog diet and foraging: Insights from archaeological canids in Siberia
Authors: Losey Robert J. , Nomokonova Tatiana , Guiry Eric , Fleming Lacey S. , Garvie-Lok Sandra J. , Waters-Rist Andrea L. , Bieraugle Megan , Szpak Paul , Bachura Olga P. , Bazaliiskii Vladimir I. , Berdnikova Natalia E. , Diatchina Natal’ia G. , Frolov Iaroslav V. , Gorbunov Vadim V. , Goriunova Olga I. , Grushin Sergei P. , Gusev Andrei V. , Iaroslavtseva Larisa G. , Ivanov Grigorii L. , Kharinskii Artur V. , Konstantinov Mikhail V. , Kosintsev Pavel A. , Kovychev Evgenii V. , Lazin Boris , Nikitin Iurii G. , Papin Dmitri V. , Popov Alexandr N. , Sablin Mikhail V. , Savel’ev Nikolai A. , Savinetsky Arkady B. , Tishkin Alexey A.
Published: July 2022

Research on the evolution of dog foraging and diet has largely focused on scavenging during their initial domestication and genetic adaptations to starch-rich food environments following the advent of agriculture. The Siberian archaeological record evidences other critical shifts in dog foraging and diet that likely characterize Holocene dogs globally. By the Middle Holocene, body size reconstruction for Siberia dogs indicates that most were far smaller than Pleistocene wolves. This contributed to dogs’ tendencies to scavenge, feed on small prey, and reduce social foraging. Stable carbon and nitrogen isotope analysis of Siberian dogs reveals that their diets were more diverse than those of Pleistocene wolves. This included habitual consumption of marine and freshwater foods by the Middle Holocene and reliance on C
4
foods by the Late Holocene. Feeding on such foods and anthropogenic waste increased dogs’ exposure to microbes, affected their gut microbiomes, and shaped long-term dog population history.
Human T-bet governs the generation of a distinct subset of CD11c
high
CD21
low
B cells
Authors: Yang Rui , Avery Danielle T. , Jackson Katherine J. L. , Ogishi Masato , Benhsaien Ibtihal , Du Likun , Ye Xiaofei , Han Jing , Rosain Jérémie , Peel Jessica N. , Alyanakian Marie-Alexandra , Neven Bénédicte , Winter Sarah , Puel Anne , Boisson Bertrand , Payne Kathryn J. , Wong Melanie , Russell Amanda J. , Mizoguchi Yoko , Okada Satoshi , Uzel Gulbu , Goodnow Christopher C. , Latour Sylvain , El Bakkouri Jalila , Bousfiha Aziz , Preece Kahn , Gray Paul E. , Keller Baerbel , Warnatz Klaus , Boisson-Dupuis Stéphanie , Abel Laurent , Pan-Hammarström Qiang , Bustamante Jacinta , Ma Cindy S. , Casanova Jean-Laurent , Tangye Stuart G.
Published: July 2022

High-level expression of the transcription factor T-bet characterizes a phenotypically distinct murine B cell population known as “age-associated B cells” (ABCs). T-bet–deficient mice have reduced ABCs and impaired humoral immunity. We describe a patient with inherited T-bet deficiency and largely normal humoral immunity including intact somatic hypermutation, affinity maturation and memory B cell formation in vivo, and B cell differentiation into Ig-producing plasmablasts in vitro. Nevertheless, the patient exhibited skewed class switching to IgG1, IgG4, and IgE, along with reduced IgG2, both in vivo and in vitro. Moreover, T-bet was required for the in vivo and in vitro development of a distinct subset of human B cells characterized by reduced expression of CD21 and the concomitantly high expression of CD19, CD20, CD11c, FCRL5, and T-bet, a phenotype that shares many features with murine ABCs. Mechanistically, human T-bet governed CD21
lo
CD11c
hi
B cell differentiation by controlling the chromatin accessibility of lineage-defining genes in these cells:
FAS
,
IL21R
,
SEC61B
,
DUSP4
,
DAPP1
,
SOX5
,
CD79B
, and
CXCR4
. Thus, human T-bet is largely redundant for long-lived protective humoral immunity but is essential for the development of a distinct subset of human CD11c
hi
CD21
lo
B cells.
LAMA2-related muscular dystrophy mimicking multiple sclerosis
Authors: Koshorek Jacqueline , de Macena Sobreira Nara , Saidha Shiv
Published: July 2022

Laminin-alpha2-related muscular dystrophy (LAMA2-MD) is a genetic condition due to reduced LAMA2, a protein found throughout the nervous system. Late-onset LAMA2-MD may present with proximal muscle weakness, joint contractures, neuropathy, epilepsy and/or cardiorespiratory issues, and is less common than the neonatal form. We describe a novel phenotype of LAMA2-MD with progressive myelopathy and spinal cord abnormalities.

A woman was referred for evaluation of multiple sclerosis (MS) with progressive gait difficulty and abnormal neuroimaging showing white matter abnormalities in the brain and spinal cord. Ancillary testing was not consistent with primary neuroinflammatory disorders, systemic autoimmunity or infection. Metabolic workup revealed low cyanocobalamin. Genetic testing identified two LAMA2-MD variants.

Genetic disorders can mimic treatable neurological conditions. Chronic progressive course, involvement of the peripheral and central nervous systems, and confluent white matter abnormalities should be investigated with molecular testing that includes LAMA2 sequencing to ensure proper diagnosis and management.
Pulmonary embolism diagnosis part 1: clinical assessment at the front door
Authors: Cafferkey John , Serebriakoff Philippa , de Wit Kerstin , Horner Daniel E , Reed Matthew James
Published: July 2022

This first of two practice reviews addresses pulmonary embolism (PE) diagnosis considering important aspects of PE clinical presentation and comparing evidence-based PE testing strategies. A companion paper addresses the management of PE. Symptoms and signs of PE are varied, and emergency physicians frequently use testing to ‘rule out’ the diagnosis in people with respiratory or cardiovascular symptoms. The emergency clinician must balance the benefit of reassuring negative PE testing with the risks of iatrogenic harms from over investigation and overdiagnosis.
Ethical decision making during a healthcare crisis: a resource allocation framework and tool
Authors: Guidolin Keegan , Catton Jennifer , Rubin Barry , Bell Jennifer , Marangos Jessica , Munro-Heesters Ann , Stuart-McEwan Terri , Quereshy Fayez
Published: July 2022

The COVID-19 pandemic has strained healthcare resources the world over, requiring healthcare providers to make resource allocation decisions under extraordinary pressures. A year later, our understanding of COVID-19 has advanced, but our process for making ethical decisions surrounding resource allocation has not. During the first wave of the pandemic, our institution uniformly ramped-down clinical activity to accommodate the anticipated demands of COVID-19, resulting in resource waste and inefficiency. In preparation for the second wave, we sought to make such ramp down decisions more prudently and ethically. We report the development of a tool that can be used to make fair and ethical decisions in times of resource scarcity. We formed an interprofessional team to develop and use this tool to ensure that a diverse range of stakeholder perspectives were represented in this development process. This team, called the clinical activity recovery team, established institutional objectives that were combined with well-established procedural values, substantive ethical principles and decision-making criteria by using a variation on the well-known accountability for reasonableness ethical framework. The result of this is a stepwise, semiquantitative, ethical decision tool that can be applied to resource allocation challenges in order to reach fair and ethically defensible decisions. This ethical decision tool can be applied in various contexts and may prove useful at both the institutional and the departmental level; indeed this is how it is applied at our centre. As the second wave of COVID-19 strains healthcare resources, this tool can help clinical leaders to make fair decisions.
Erratum to: All analytic solutions for geodesic motion in axially symmetric space-times
Authors: Ospino J. , Hernández-Pastora J. L. , Núñez L. A.
Published: July 2022

A Correction to this paper has been published: 10.1140/epjc/s10052-022-10544-1
Effect of the mass ratio on the escape in the 4-body ring problem
Authors: Belgharbi Ibrahim , Navarro Juan F.
Published: July 2022

The aim of this paper is to analyze the effect of the mass ratio on the distribution of short times of escape and the probability of escape of a particle from the 4-body ring configuration. To this purpose, we carry out a numerical exploration of the problem, considering three different values of the mass ratio between the central and the primary bodies and, for each of these values, a pair of values of the Jacobi constant.
Validity and feasibility of using a seated push-up test among community-dwelling older adults
Authors: Poncumhak Puttipong , Phadungkit Supaporn , Chokphukiao Pakwipa , Intaruk Roongnapa , Amatachaya Pipatana , Amatachaya Sugalya
Published: July 2022

Background: Older individuals face a high risk of mobility and body composition decline, which can affect their independence. In light of a current uncertain healthcare situation created by the coronavirus (COVID-19) pandemic, healthcare paradigm has been shifted with increased demand for a practical measure to promote standard home healthcare services for all individuals, including older adults.

Objective: This study explored the feasibility and validity of seated push-up tests (SPUTs) as clinical measures to reflect the body composition, muscle strength, and mobility among community-dwelling older individuals, aged [Formula: see text] years ([Formula: see text]).

Methods: Participants were cross-sectionally assessed using SPUTs with various demanding forms, including the 1-time SPUT (1SPUT) along with its upper limb loading SPUT (ULL-SPUT), 5-time SPUT (5SPUT), 10-time SPUT (10SPUT), and 1-min SPUT (1minSPUT) and standard measures.

Results: Participants who passed and failed a 1SPUT showed significant differences in the outcomes of all standard measures ([Formula: see text]). The ULL-SPUT significantly correlated to all body composition, muscle strength, and mobility ([Formula: see text]–0.785; [Formula: see text]). Outcomes of 1minSPUT significantly correlated with muscle strength and mobility outcomes ([Formula: see text]–0.526; [Formula: see text]). Participants reported no adverse effects following the SPUTs.

Conclusion: The findings suggest the use of the 1SPUT, ULL-SPUT, and 1minSPUT as practical measures to reflect the body composition, muscle strength, and mobility of older individuals, according to their functional levels. The tests may especially clinically benefit those with lower limb limitations and those in settings with limited space and equipment.
Digital Twin-enabled AI Enhancement in Smart Critical Infrastructures for 5G
Authors: Gai Keke , Xiao Qiang , Qiu Meikang , Zhang Guolei , Chen Jianyu , Wei Yihang , Zhang Yue
Published: July 2022

Artificial Intelligence (AI) technology has been empowered to be a significant driven force within the edge context for powering up contemporary complex systems, such as smart critical infrastructure. Interconnectivity between physical and cyber spaces further introduces the needs of digital twin, which allows AI-based solutions to optimize various tasks in physical operations. However, due to the complexity of the setting in digital twin, task allocation is encountering multiple challenges, such as concurrent meeting the requirements of energy saving, efficiency, and accuracy. In this work, we propose a Digital Twin-Enabled Edge AI (DTE2AI), supported by our Energy-aware High Accuracy Strategy (EAHAS), which focuses on optimizing the training accuracy of AI tasks under the limits of training time and energy consumption. The average of the training accuracy was enhanced 12% based on our experiment evaluations.
Loki
Authors: Lesser Steve , Stomakhin Alexey , Daviet Gilles , Wretborn Joel , Edholm John , Lee Noh-Hoon , Schweickart Eston , Zhai Xiao , Flynn Sean , Moffat Andrew
Published: July 2022

We introduce Loki, a new framework for robust simulation of fluid, rigid, and deformable objects with non-compromising fidelity on any single element, and capabilities for coupling and representation transitions across multiple elements. Loki adapts multiple best-in-class solvers into a unified framework driven by a declarative state machine where users declare 'what' is simulated but not 'when,' so an automatic scheduling system takes care of mixing any combination of objects. This leads to intuitive setups for coupled simulations such as hair in the wind or objects transitioning from one representation to another, for example bulk water FLIP particles to SPH spray particles to volumetric mist. We also provide a consistent treatment for components used in several domains, such as unified collision and attachment constraints across 1D, 2D, 3D deforming and rigid objects. Distribution over MPI, custom linear equation solvers, and aggressive application of sparse techniques keep performance within production requirements. We demonstrate a variety of solvers within the framework and their interactions, including FLIPstyle liquids, spatially adaptive volumetric fluids, SPH, MPM, and mesh-based solids, including but not limited to discrete elastic rods, elastons, and FEM with state-of-the-art constitutive models. Our framework has proven powerful and intuitive enough for voluntary artist adoption and has delivered creature and FX simulations for multiple major movie productions in the preceding four years.
Guided bubbles and wet foam for realistic whitewater simulation
Authors: Wretborn Joel , Flynn Sean , Stomakhin Alexey
Published: July 2022

We present a method for enhancing fluid simulations with realistic bubble and foam detail. We treat bubbles as discrete air particles, two-way coupled with a sparse volumetric Euler flow, as first suggested in [Stomakhin et al. 2020]. We elaborate further on their scheme and introduce a bubble inertia correction term for improved convergence. We also show how one can add bubbles to an already existing fluid simulation using our novel guiding technique, which performs local re-simulation of fluid to achieve more interesting bubble dynamics through coupling. As bubbles reach the surface, they are converted into foam and simulated separately. Our foam is discretized with smoothed particle hydrodynamics (SPH), and we replace forces normal to the fluid surface with a fluid surface manifold advection constraint to achieve more robust and stable results. The SPH forces are derived through proper constitutive modeling of an incompressible viscous liquid, and we explain why this choice is appropriate for "wet" types of foam. This allows us to produce believable dynamics from close-up scenarios to large oceans, with just a few parameters that work intuitively across a variety of scales. Additionally, we present relevant research on air entrainment metrics and bubble distributions that have been used in this work.
Energetically consistent inelasticity for optimization time integration
Authors: Li Xuan , Li Minchen , Jiang Chenfanfu
Published: July 2022

In this paper, we propose Energetically Consistent Inelasticity (ECI), a new formulation for modeling and discretizing finite strain elastoplasticity/viscoelasticity in a way that is compatible with optimization-based time integrators. We provide an in-depth analysis for allowing plasticity to be implicitly integrated through an augmented strain energy density function. We develop ECI on the associative von-Mises J2 plasticity, the non-associative Drucker-Prager plasticity, and the finite strain viscoelasticity. We demonstrate the resulting scheme on both the Finite Element Method (FEM) and the Material Point Method (MPM). Combined with a custom Newton-type optimization integration scheme, our method enables simulating stiff and large-deformation inelastic dynamics of metal, sand, snow, and foam with larger time steps, improved stability, higher efficiency, and better accuracy than existing approaches.
Sparse ellipsometry
Authors: Hwang Inseung , Jeon Daniel S. , Muñoz Adolfo , Gutierrez Diego , Tong Xin , Kim Min H.
Published: July 2022

Ellipsometry techniques allow to measure polarization information of materials, requiring precise rotations of optical components with different configurations of lights and sensors. This results in cumbersome capture devices, carefully calibrated in lab conditions, and in very long acquisition times, usually in the order of a few days per object. Recent techniques allow to capture polarimetric spatially-varying reflectance information, but limited to a single view, or to cover all view directions, but limited to spherical objects made of a single homogeneous material. We present
sparse ellipsometry
, a portable polarimetric acquisition method that captures both polarimetric SVBRDF and 3D shape simultaneously. Our handheld device consists of off-the-shelf, fixed optical components. Instead of days, the total acquisition time varies between twenty and thirty minutes per object. We develop a complete polarimetric SVBRDF model that includes diffuse and specular components, as well as single scattering, and devise a novel polarimetric inverse rendering algorithm with data augmentation of specular reflection samples via generative modeling. Our results show a strong agreement with a recent ground-truth dataset of captured polarimetric BRDFs of real-world objects.
ComplexGen
Authors: Guo Haoxiang , Liu Shilin , Pan Hao , Liu Yang , Tong Xin , Guo Baining
Published: July 2022

We view the reconstruction of CAD models in the boundary representation (B-Rep) as the detection of geometric primitives of different orders,
i.e.
, vertices, edges and surface patches, and the correspondence of primitives, which are holistically modeled as a chain complex, and show that by modeling such comprehensive structures more complete and regularized reconstructions can be achieved. We solve the complex generation problem in two steps. First, we propose a novel neural framework that consists of a sparse CNN encoder for input point cloud processing and a tri-path transformer decoder for generating geometric primitives and their mutual relationships with estimated probabilities. Second, given the probabilistic structure predicted by the neural network, we recover a definite B-Rep chain complex by solving a global optimization maximizing the likelihood under structural validness constraints and applying geometric refinements. Extensive tests on large scale CAD datasets demonstrate that the modeling of B-Rep chain complex structure enables more accurate detection for learning and more constrained reconstruction for optimization, leading to structurally more faithful and complete CAD B-Rep models than previous results.
Artemis
Authors: Luo Haimin , Xu Teng , Jiang Yuheng , Zhou Chenglin , Qiu Qiwei , Zhang Yingliang , Yang Wei , Xu Lan , Yu Jingyi
Published: July 2022

We, humans, are entering into a virtual era and indeed want to bring animals to the virtual world as well for companion. Yet, computer-generated (CGI) furry animals are limited by tedious off-line rendering, let alone interactive motion control. In this paper, we present ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS. Our ARTEMIS enables interactive motion control, real-time animation, and photo-realistic rendering of furry animals. The core of our ARTEMIS is a neural-generated (NGI) animal engine, which adopts an efficient octree-based representation for animal animation and fur rendering. The animation then becomes equivalent to voxel-level deformation based on explicit skeletal warping. We further use a fast octree indexing and efficient volumetric rendering scheme to generate appearance and density features maps. Finally, we propose a novel shading network to generate high-fidelity details of appearance and opacity under novel poses from appearance and density feature maps. For the motion control module in ARTEMIS, we combine state-of-the-art animal motion capture approach with recent neural character control scheme. We introduce an effective optimization scheme to reconstruct the skeletal motion of real animals captured by a multi-view RGB and Vicon camera array. We feed all the captured motion into a neural character control scheme to generate abstract control signals with motion styles. We further integrate ARTEMIS into existing engines that support VR headsets, providing an unprecedented immersive experience where a user can intimately interact with a variety of virtual animals with vivid movements and photo-realistic appearance. Extensive experiments and showcases demonstrate the effectiveness of our ARTEMIS system in achieving highly realistic rendering of NGI animals in real-time, providing daily immersive and interactive experiences with digital animals unseen before. We make available our ARTEMIS model and dynamic furry animal dataset at https://haiminluo.github.io/publication/artemis/.
Dual octree graph networks for learning adaptive volumetric shape representations
Authors: Wang Peng-Shuai , Liu Yang , Tong Xin
Published: July 2022

We present an adaptive deep representation of volumetric fields of 3D shapes and an efficient approach to learn this deep representation for high-quality 3D shape reconstruction and auto-encoding. Our method encodes the volumetric field of a 3D shape with an adaptive feature volume organized by an octree and applies a compact multilayer perceptron network for mapping the features to the field value at each 3D position. An encoder-decoder network is designed to learn the adaptive feature volume based on the graph convolutions over the dual graph of octree nodes. The core of our network is a new graph convolution operator defined over a regular grid of features fused from irregular neighboring octree nodes at different levels, which not only reduces the computational and memory cost of the convolutions over irregular neighboring octree nodes, but also improves the performance of feature learning. Our method effectively encodes shape details, enables fast 3D shape reconstruction, and exhibits good generality for modeling 3D shapes out of training categories. We evaluate our method on a set of reconstruction tasks of 3D shapes and scenes and validate its superiority over other existing approaches. Our code, data, and trained models are available at https://wang-ps.github.io/dualocnn.
Iterative poisson surface reconstruction (iPSR) for unoriented points
Authors: Hou Fei , Wang Chiyu , Wang Wencheng , Qin Hong , Qian Chen , He Ying
Published: July 2022

Poisson surface reconstruction (PSR) remains a popular technique for reconstructing watertight surfaces from 3D point samples thanks to its efficiency, simplicity, and robustness. Yet, the existing PSR method and subsequent variants work only for oriented points. This paper intends to validate that an improved PSR, called iPSR, can completely eliminate the requirement of point normals and proceed in an iterative manner. In each iteration, iPSR takes as input point samples with normals directly computed from the surface obtained in the preceding iteration, and then generates a new surface with better quality. Extensive quantitative evaluation confirms that the new iPSR algorithm converges in 5--30 iterations even with randomly initialized normals. If initialized with a simple visibility based heuristic, iPSR can further reduce the number of iterations. We conduct comprehensive comparisons with PSR and other powerful implicit-function based methods. Finally, we confirm iPSR's effectiveness and scalability on the AIM@SHAPE dataset and challenging (indoor and outdoor) scenes. Code and data for this paper are at https://github.com/houfei0801/ipsr.
As-locally-uniform-as-possible reshaping of vector clip-art
Authors: Araújo Chrystiano , Vining Nicholas , Rosales Enrique , Gori Giorgio , Sheffer Alla
Published: July 2022

Vector clip-art images consist of regions bounded by a network of vector curves. Users often wish to
reshape
, or rescale, existing clip-art images by changing the locations, proportions, or scales of different image elements. When reshaping images depicting synthetic content they seek to preserve global and local structures. These structures are best preserved when the gradient of the mapping between the original and the reshaped curve networks is locally as close as possible to a uniform scale; mappings that satisfy this property maximally preserve the input curve orientations and minimally change the shape of the input's geometric details, while allowing changes in the relative scales of the different features. The expectation of approximate scale uniformity is
local
; while reshaping operations are typically expected to change the
relative proportions
of a subset of network regions, users expect the change to be minimal away from the directly impacted regions and expect such changes to be gradual and distributed as evenly as possible. Unfortunately, existing methods for editing 2D curve networks do not satisfy these criteria. We propose a targeted
As-Locally-Uniform-as-Possible (ALUP)
vector clip-art reshaping method that satisfies the properties above. We formulate the computation of the desired output network as the solution of a constrained variational optimization problem. We effectively compute the desired solution by casting this continuous problem as a minimization of a non-linear discrete energy function, and obtain the desired minimizer by using a custom iterative solver. We validate our method via perceptual studies comparing our results to those created via algorithmic alternatives and manually generated ones. Participants preferred our results over the closest alternative by a ratio of 6 to 1.
Noise-based enhancement for foveated rendering
Authors: Tariq Taimoor , Tursun Cara , Didyk Piotr
Published: July 2022

Human visual sensitivity to spatial details declines towards the periphery. Novel image synthesis techniques, so-called foveated rendering, exploit this observation and reduce the spatial resolution of synthesized images for the periphery, avoiding the synthesis of high-spatial-frequency details that are costly to generate but not perceived by a viewer. However, contemporary techniques do not make a clear distinction between the range of spatial frequencies that must be reproduced and those that can be omitted. For a given eccentricity, there is a range of frequencies that are detectable but not resolvable. While the accurate reproduction of these frequencies is not required, an observer can detect their absence if completely omitted. We use this observation to improve the performance of existing foveated rendering techniques. We demonstrate that this specific range of frequencies can be efficiently replaced with procedural noise whose parameters are carefully tuned to image content and human perception. Consequently, these frequencies do not have to be synthesized during rendering, allowing more aggressive foveation, and they can be replaced by noise generated in a less expensive post-processing step, leading to improved performance of the rendering system. Our main contribution is a perceptually-inspired technique for deriving the parameters of the noise required for the enhancement and its calibration. The method operates on rendering output and runs at rates exceeding 200 FPS at 4K resolution, making it suitable for integration with real-time foveated rendering systems for VR and AR devices. We validate our results and compare them to the existing contrast enhancement technique in user experiments.
Position-free multiple-bounce computations for smith microfacet BSDFs
Authors: Wang Beibei , Jin Wenhua , Fan Jiahui , Yang Jian , Holzschuch Nicolas , Yan Ling-Qi
Published: July 2022

Bidirectional Scattering Distribution Functions (BSDFs) encode how a material reflects or transmits the incoming light. The most commonly used model is the microfacet BSDF. It computes the material response from the microgeometry of the surface assuming a single bounce on specular microfacets. The original model ignores multiple bounces on the microgeometry, resulting in an energy loss, especially for rough materials. In this paper, we present a new method to compute the multiple bounces inside the microgeometry, eliminating this energy loss. Our method relies on a position-free formulation of multiple bounces inside the microgeometry. We use an explicit mathematical definition of the path space that describes single and multiple bounces in a uniform way. We then study the behavior of light on the different vertices and segments in the path space, leading to a reciprocal multiple-bounce description of BSDFs. Furthermore, we present practical, unbiased Monte Carlo estimators to compute multiple scattering. Our method is less noisy than existing algorithms for computing multiple scattering. It is almost noise-free with a very-low sampling rate, from 2 to 4 samples per pixel (spp).
Dynamic optimal space partitioning for redirected walking in multi-user environment
Authors: Jeon Sang-Bin , Kwon Soon-Uk , Hwang June-Young , Cho Yong-Hun , Kim Hayeon , Park Jinhyung , Lee In-Kwon
Published: July 2022

In multi-user Redirected Walking (RDW), the space subdivision method divides a shared physical space into sub-spaces and allocates a sub-space to each user. While this approach has the advantage of precluding any collisions between users, the conventional space subdivision method suffers from frequent boundary resets due to the reduction of available space per user. To address this challenge, in this study, we propose a space subdivision method called Optimal Space Partitioning (OSP) that dynamically divides the shared physical space in real-time. By exploiting spatial information of the physical and virtual environment, OSP predicts the movement of users and divides the shared physical space into optimal sub-spaces separated with shutters. Our OSP framework is trained using deep reinforcement learning to allocate optimal sub-space to each user and provide optimal steering. Our experiments demonstrate that OSP provides higher sense of immersion to users by minimizing the total number of reset counts, while preserving the advantage of the existing space subdivision strategy: ensuring better safety to users by completely eliminating the possibility of any collisions between users beforehand. Our project is available at https://github.com/AppleParfait/OSP-Archive.
Computing sparse integer-constrained cones for conformal parameterizations
Authors: Li Mo , Fang Qing , Ouyang Wenqing , Liu Ligang , Fu Xiao-Ming
Published: July 2022

We propose a novel method to generate sparse integer-constrained cone singularities with low distortion constraints for conformal parameterizations. Inspired by [Fang et al. 2021; Soliman et al. 2018], the cone computation is formulated as a constrained optimization problem, where the objective is the number of cones measured by the
ℓ
0
-norm of Gaussian curvature of vertices, and the constraint is to restrict the cone angles to be multiples of
π
/2 and control the distortion while ensuring that the Yamabe equation holds. Besides, the holonomy angles for the non-contractible homology loops are additionally required to be multiples of
π
/2 for achieving rotationally seamless conformal parameterizations. The Douglas-Rachford (DR) splitting algorithm is used to solve this challenging optimization problem, and our success relies on two key components. First, replacing each integer constraint with the intersection of a box set and a sphere enables us to manage the subproblems in DR splitting update steps in the continuous domain. Second, a novel solver is developed to optimize the
ℓ
0
-norm without any approximation. We demonstrate the effectiveness and feasibility of our algorithm on a data set containing 3885 models. Compared to state-of-the-art methods, our method achieves a better tradeoff between the number of cones and the parameterization distortion.
Instant neural graphics primitives with a multiresolution hash encoding
Authors: Müller Thomas , Evans Alex , Schied Christoph , Keller Alexander
Published: July 2022

Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that permits the use of a smaller network without sacrificing quality, thus significantly reducing the number of floating point and memory access operations: a small neural network is augmented by a multiresolution hash table of trainable feature vectors whose values are optimized through stochastic gradient descent. The multiresolution structure allows the network to disambiguate hash collisions, making for a simple architecture that is trivial to parallelize on modern GPUs. We leverage this parallelism by implementing the whole system using fully-fused CUDA kernels with a focus on minimizing wasted bandwidth and compute operations. We achieve a combined speedup of several orders of magnitude, enabling training of high-quality neural graphics primitives in a matter of seconds, and rendering in tens of milliseconds at a resolution of 1920×1080.
Efficient kinetic simulation of two-phase flows
Authors: Li Wei , Ma Yihui , Liu Xiaopei , Desbrun Mathieu
Published: July 2022

Real-life multiphase flows exhibit a number of complex and visually appealing behaviors, involving bubbling, wetting, splashing, and glugging. However, most state-of-the-art simulation techniques in graphics can only demonstrate a limited range of multiphase flow phenomena, due to their inability to handle the real water-air density ratio and to the large amount of numerical viscosity introduced in the flow simulation and its coupling with the interface. Recently, kinetic-based methods have achieved success in simulating large density ratios and high Reynolds numbers efficiently; but their memory overhead, limited stability, and numerically-intensive treatment of coupling with immersed solids remain enduring obstacles to their adoption in movie productions. In this paper, we propose a new kinetic solver to couple the incompressible Navier-Stokes equations with a conservative phase-field equation which remedies these major practical hurdles. The resulting two-phase immiscible fluid solver is shown to be efficient due to its massively-parallel nature and GPU implementation, as well as very versatile and reliable because of its enhanced stability to large density ratios, high Reynolds numbers, and complex solid boundaries. We highlight the advantages of our solver through various challenging simulation results that capture intricate and turbulent air-water interaction, including comparisons to previous work and real footage.