bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Assessment of Glyphosate Exposures from Pilot Study with Simulated Heavy Residential Consumer Application of Roundup® using a Margin of Safety (MOS) Approach
Authors: Kougias Daniel G. , Miller Eric , McEwen Abigail , Reamer Heidi , Kovochich Michael , Pierce Jennifer
Published: November 2020

Due to the widespread application of glyphosate, a nonselective herbicide, to a variety of resistant food crops, the general population is exposed to glyphosate through dietary intake. Despite this, dietary exposures to glyphosate are considered low in comparison to application‐related exposures. Although previous studies have evaluated exposure to horticultural and agricultural workers, to date only one study, which we recently conducted, has characterized exposure to glyphosate in consumers following heavy residential application of a glyphosate‐containing herbicide in a residential yard and garden setting. In this previous study, we demonstrated that urinary glyphosate concentrations in these applicators were similar to or in some circumstances greater than those in occupational applicators, likely due to the nature of the simulation study, which ensured a heavy application protocol. However, it is unknown whether these urinary glyphosate concentrations in consumer applicators correspond to internal doses that may be of concern. Therefore, the purpose of this study is to provide a comprehensive risk assessment of glyphosate exposure in consumer applicators using a margin of safety approach. Here, we incorporated data collected from multiple spot urine samples across time from our previous study that assessed consumer exposure to glyphosate from Roundup® application. Estimated internal doses, even with the use of conservative assumptions across unique approaches, were below internal doses estimated from established health‐based guidance values. Overall, this study demonstrates that glyphosate exposure from even heavy consumer application of a commercially available glyphosate‐containing herbicide does not appear to be a health concern.
A pilot study towards the immunological effects of omalizumab treatment used to facilitate oral immunotherapy in peanut‐allergic adolescents
Authors: van der Heiden Marieke , Nopp Anna , Brandström Josef , Carvalho‐Queiroz Claudia , Nilsson Caroline , Sverremark‐Ekström Eva
Published: November 2020

Anti‐IgE treatments, such as omalizumab, have shown promising effects in allergy treatment. Our previous work has shown that individualized omalizumab treatment (OT) allows a safe initiation and rapid up‐dosing of peanut oral immunotherapy (OIT) in peanut‐allergic adolescents. However, the broader immunological effects of this OT are incompletely understood. In this pilot study, we longitudinally followed the total B‐ and T‐cell immunity during OT, using flow cytometry, ELISpot and ELISA. Peripheral blood mononuclear cells (PBMCs) and plasma were collected from participants (n = 17) at several timepoints during treatment, before starting OT (baseline), prior to starting OIT during OT (start OIT) and at maintenance dose OIT prior to OT reduction (maintenance). OT did not affect the total B‐cell compartment over treatment time, but our results suggest an association between the OT dosage scheme and the B‐cell compartment. Further, in vitro polyclonal T‐cell activation at the different timepoints suggests a cytokine skewing towards the Th1 phenotype at the expense of Th2‐ and Th9‐related cytokines during treatment. No differences in the frequencies or phenotype of regulatory T cells (Tregs) over treatment time were observed. Finally, plasma chemokine levels were stable over treatment time, but suggest elevated gut homing immune responses in treatment successes during the treatment as compared to treatment failures. The novel and explorative results of this pilot study help to improve our understanding on the immunological effects of OT used to facilitate OIT and provide guidance for future immunological investigation in large clinical trials.
Finding connection virtually through shared deep stories
Authors: Dorroll Courtney , Dorroll Phil
Published: November 2020

In the context of a global pandemic, techniques for remote instruction have become increasingly vital to undergraduate instruction. This essay discusses how synchronous virtual encounters can have a similar pedagogical impact as in‐person encounters by outlining specific methods of intercultural learning via Virtual Exchange Pedagogy (VEP), in which students in different locations interact with one another through structured online activities. This essay shares techniques used prior to the pandemic to connect undergraduate students in the American south to students in an urban setting in Egypt. VEP can facilitate successful intercultural learning by enabling students to share and discover the deep emotional narratives that structure their view of self and others, assisting participants to achieve empathic understanding between our students and their interlocutors, even while separated by great physical distances and never able to meet physically in person.
Higher prevalence of seizure activity in a small population of atopic dogs: a retrospective breed‐ and age‐matched study
Authors: Herrmann Ina , Kradischnig Clarissa , Skor Ondrej , Pakozdy Akos , Panakova Lucia
Published: November 2020

Background – Atopic dermatitis (AD) is considered to be a systemic disease in people shown to have an association with epilepsy. However, so far, no data about the association of epilepsy and atopy have been reported in dogs. Objectives – Given the homology between human and canine AD, and the increased incidence of epilepsy in atopic people, we investigated the association between AD and seizure‐associated activity in a small canine population. Conclusion and clinical importance – In our small retrospective study, we observed an increased prevalence of seizure activity in the atopic dog population. Further larger and prospective studies are needed to confirm these results.
Controlling colloidal crystals via morphing energy landscapes and reinforcement learning
Authors: Zhang Jianli , Yang Junyan , Zhang Yuanxing , Bevan Michael A.
Published: November 2020

A feedback control scheme is developed for rapid assembly of perfect target structures on morphing energy landscapes.
Evidence that investors penalize female founders for lack of industry fit
Authors: Kanze Dana , Conley Mark A. , Okimoto Tyler G. , Phillips Damon J. , Merluzzi Jennifer
Published: November 2020

Female-led ventures are penalized in funding and valuation when catering to male-dominated industries due to a “lack of fit.”
A CRISPR Interference Platform for Selective Downregulation of Gene Expression in Borrelia burgdorferi
Authors: Takacs Constantin N. , Scott Molly , Chang Yunjie , Kloos Zachary A. , Irnov Irnov , Rosa Patricia A. , Liu Jun , Jacobs-Wagner Christine
Published: November 2020

Gene function studies are facilitated by the availability of rapid and easy-to-use genetic tools. Homologous recombination-based methods traditionally used to genetically investigate gene function remain cumbersome to perform in
B. burgdorferi
, as they often are relatively inefficient.
Detection and Identification ofAcanthamoebaand Other Nonviral Causes of Infectious Keratitis in Corneal Scrapings by Real-Time PCR and Next-Generation Sequencing-Based 16S-18S Gene Analysis
Authors: Holmgaard Dennis Back , Barnadas Celine , Mirbarati Seyed Hossein , O’Brien Andersen Lee , Nielsen Henrik Vedel , Stensvold Christen Rune
Published: November 2020

Acanthamoebais a free-living amoeba of extensive genetic diversity. It may cause infectious keratitis (IK), which can also be caused by bacteria, fungi, and viruses.
Strategies for writing a successful National Institutes of Health grant proposal for the early-career neurointerventionalist
Authors: Kan Peter , Mokin Maxim , Mack William J , Starke Robert M , Sheth Kevin N , Albuquerque Felipe C , Levitt Michael R
Published: November 2020

Objective

The goal of this article is to provide a succinct review of the key components of a NIH grant application and the NIH reviewprocess for the early career neurointerventionalist.

Methods

The authors reviewed NIH rules and regulations and also reflected on their own collective experiencein writing NIH grant proposals in the area of cerebrovascular disease andneurointerventional surgery.

Results

Key components of theresearch strategy include specific aims, significance, innovation and approach.The specific aims page is the most important page of the application and should be written first. The NIH review isbased on these key components along with an assessment of the appropriatenessof the investigators and environment for the research.

Conclusion

Detailed knowledge ofthe key components of the research grant is critical to a successful application.The information in the article may aid in the grant writing for early careerneurointerventionalists.
Hyperdense artery sign, symptomatic infarct swelling and effect of alteplase in acute ischaemic stroke
Authors: Wu Simiao , Mair Grant , Cohen Geoff , Morris Zoe , von Heijne Anders , Bradey Nick , Cala Lesley , Peeters Andre , Farrall Andrew J , Adami Alessandro , Potter Gillian , Liu Ming , Lindley Richard I , Sandercock Peter A G , Wardlaw Joanna M
Published: November 2020

Background

Alteplase improves functional outcomes of patients with acute ischaemic stroke, but its effects on symptomatic infarct swelling, an adverse complication of stroke and the influence of CT hyperdense artery sign (HAS) are unclear. This substudy of the Third International Stroke Trial aimed to investigate the association between HAS and symptomatic infarct swelling and effect of intravenous alteplase on this association.

Methods

We included stroke patients whose prerandomisation scan was non-contrast CT. Raters, masked to clinical information, assessed baseline (prerandomisation) and follow-up (24–48 hours postrandomisation) CT scans for HAS, defined as an intracranial artery appearing denser than contralateral arteries. Symptomatic infarct swelling was defined as clinically significant neurological deterioration ≤7 days after stroke with radiological evidence of midline shift, effacement of basal cisterns or uncal herniation.

Results

Among 2961 patients, HAS presence at baseline was associated with higher risk of symptomatic infarct swelling (OR 2.21; 95% CI 1.42 to 3.44). Alteplase increased the risk of swelling (OR 1.69; 95% CI 1.11 to 2.57), with no difference between patients with and those without baseline HAS (p=0.49). In patients with baseline HAS, alteplase reduced the proportion with HAS at follow-up (OR 0.67; 95% CI 0.50 to 0.91), where HAS disappearance was associated with reduced risk of swelling (OR 0.25, 95% CI 0.14 to 0.47).

Conclusion

Although alteplase was associated with increased risk of symptomatic infarct swelling in patients with or without baseline HAS, it was also associated with accelerated clearance of HAS, which in return reduced swelling, providing further mechanistic insights to underpin the benefits of alteplase.
H2S promotes developmental brain angiogenesis via the NOS/NO pathway in zebrafish
Authors: Jiang Weiqing , Liu Chen , Deng Mingzhu , Wang Fei , Ren Xiao , Fan Yilin , Du Jiulin , Wang Yonggang
Published: November 2020

Background

Hydrogen sulphide (H2S) is considered as the third member of the gasotransmitter family, along with nitric oxide (NO) and carbon monoxide. H2S has been reported to induce angiogenesis by promoting the growth, migration and tube-like structure formation of endothelial cells. Those studies were conducted in conditions of cell culture, mouse Matrigel plug assay model, rat wound healing model or rat hindlimb ischaemia model. Recent in vivo studies showed the physiological importance of H2S in muscle angiogenesis. However, the importance of endogenous H2S for brain angiogenesis during development remains unknown. We therefore aimed at determining the role of H2S in brain vascular development.

Methods and results

Both knockdown and knockout of H2S-producing enzymes, cystathionine β-synthase (cbs) and cystathionine γ-lyase (cth), using morpholino oligonucleotides and clustered regularly interspaced short palindromic repeats/Cas9-mediated mutation, impaired brain vascular development of larval zebrafish. Incubation with the slow-releasing H2S donor GYY4137 alleviated the defects of brain vascular development incbsandcthmorphants. Quantitative analysis of the midbrain vascular network showed that H2S enhances angiogenesis without affecting the topological structure of the brain vasculature. Mechanically, nitric oxide synthase 2a (nos2a) expression and NO production were decreased in bothcbsandcthmorphants. Overexpression ofnos2aby coinjection ofcbsorcthMO with full-length zebrafish nos2a mRNA alleviated the brain vascular developmental defects incbsandcthmorphants.

Conclusion

We conclude that H2S promotes brain developmental angiogenesis via the NOS/NO pathway in zebrafish.
Mycorrhizal colonisation in roots ofHolcus lanatus(Yorkshire Fog) in a permanent pasture under conditions of reduced precipitation
Authors: Ayling Sarah M. , George Belinda H. , Rogers Jacqueline B.
Published: November 2020

The UK climate is projected to become warmer, with more frequent hotter, drier summers. Many governments and international organisations are concerned about how climate change will affect food production and security. Mycorrhizal fungi are an essential part of agricultural systems and yet little is known about how climate change will affect mycorrhizal fungi. We investigated the effect of reduced precipitation on levels of arbuscular mycorrhizal (AM) colonisation in the top 10 cm of soil in the grass Holcus lanatus L. (Yorkshire Fog) in a permanent pasture in South Gloucestershire, UK. Incident rainfall was reduced, by approximately 50%, using clear gutters supported on steel frames. Over three growing seasons we observed little difference in levels of AM colonisation and numbers of intra-root fungal structures between the roots of H. lanatus grown with reduced or full incident rainfall. Time of year when water stress occurred had a stronger effect on levels of colonisation than the absolute amount of precipitation received. In H. lanatus, growing in a permanent pasture, levels of AM colonisation were around 40%–50%, across a range of precipitation, from 18% above to 36% below the long-term average. The results highlight the complex relationships between mycorrhizal fungi, host plant, and abiotic stress.
Drone data for decision making in regeneration forests: from raw data to actionable insights1
Authors: Puliti Stefano , Granhus Aksel
Published: November 2020

In this study, we aim at developing ways to directly translate raw drone data into actionable insights, thus enabling us to make management decisions directly from drone data. Drone photogrammetric data and data analytics were used to model stand-level immediate tending need and cost in regeneration forests. Field reference data were used to train and validate a logistic model for the binary classification of immediate tending need and a multiple linear regression model to predict the cost to perform the tending operation. The performance of the models derived from drone data was compared to models utilizing the following alternative data sources: airborne laser scanning data (ALS), prior information from forest management plans (Prior) and the combination of drone +Prior and ALS +Prior. The use of drone data and prior information outperformed the remaining alternatives in terms of classification of tending needs, whereas drone data alone resulted in the most accurate cost models. Our results are encouraging for further use of drones in the operational management of regeneration forests and show that drone data and data analytics are useful for deriving actionable insights.
Chaos Suppression via Integrative Time Delay Control
Authors: Arafa Ayman A. , Xu Yong , Mahmoud Gamal M.
Published: November 2020

A general strategy for suppressing chaos in chaotic Burke–Shaw system using integrative time delay (ITD) control is proposed, as an example. The idea of ITD is that the feedback is integrated over a time interval. Physically, the chaotic system responds to the average information it receives from the feedback. The main feature of integrative is that the stability of the chaotic system occurs over a wider range of the space parameters. Controlling chaotic systems with ITD has not been discussed before as far as we know. Stability and the existence of Hopf bifurcation are studied which demonstrate that the switch stability occurs at critical values of the time delay. Employing the normal form theory and center manifold argument, an explicit formula is derived to determine the stability and the direction of the bifurcating periodic solutions. Numerically, the bifurcation diagram and the eigenvalues of the corresponding characteristic equations are computed to supply a clear interpretation for suppressing chaos via ITD. Furthermore, ITD method is compared with the time delayed feedback (TDF) control numerically. This comparison shows that the stability area with ITD is larger than TDF which demonstrates the feasibility and effectiveness of the ITD. Other examples of chaotic systems can be similarly investigated.
Finite Characterization of the Coarsest Balanced Coloring of a Network
Authors: Stewart Ian
Published: November 2020

Balanced colorings of networks correspond to flow-invariant synchrony spaces. It is known that the coarsest balanced coloring is equivalent to nodes having isomorphic infinite input trees, but this condition is not algorithmic. We provide an algorithmic characterization: two nodes have the same color for the coarsest balanced coloring if and only if their [Formula: see text]th input trees are isomorphic, where [Formula: see text] is the number of nodes. Here [Formula: see text] is the best possible. The proof is analogous to that of Leighton’s theorem in graph theory, using the universal cover of the network and the notion of a symbolic adjacency matrix to set up a partition refinement algorithm whose output is the coarsest balanced coloring. The running time of the algorithm is cubic in [Formula: see text].
Hopf Bifurcation of KdV–Burgers–Kuramoto System with Delay Feedback
Authors: Guan Junbiao , Liu Jie , Feng Zhaosheng
Published: November 2020

Chaotic phenomena may exist in nonlinear evolution equations. In many cases, they are undesirable but can be controlled. In this study, we deal with the chaos control of a three-dimensional chaotic system, reduced from a KdV–Burgers–Kuramoto equation. By adding a single delay feedback term into the chaotic system, we investigate the local stability and occurrence of Hopf bifurcation near the equilibrium point. Some dynamical properties including the direction and stability of bifurcated periodic solutions are presented by using the normal form theory and the center manifold theorem. Numerical simulations are illustrated which agree well with the theoretical results.
Driving Factors of Transportation CO2 Emissions in Beijing: An Analysis from the Perspective of Urban Development
Authors: SUN Yan , ZHANG Yu , LIU Xuemin
Published: November 2020

There is a coupling relationship between the development of urban transportation and cities: Urban growth leads to increase in the demand for urban transportation and consequently, a lot of transportation emissions. Therefore, an in-depth understanding of the mechanism behind the driving effect of urban development on transportation emissions is a crucial prerequisite for coordinated development of low-carbon urban transportation and cities. Based on the oil product allocation method, this paper estimates the transportation emission in Beijing from 1995 to 2016. Then based on the understanding of the driving mechanism, this paper applies the urban allometric scaling law to analyze the relationship between city size and transportation emission. Finally, the driving mechanism is analyzed using the STRIPAT model. The results reveal a superlinear relationship between transportation emission in Beijing and the expansion of the city, as the former outgrew the latter. Population size, urbanization, economic size, industrial structure, spatial scale and infrastructure construction are positive driving factors of transportation emission, whereas progress of energy technologies as a negative driving factor can restrain the growth of transportation emission. Urbanization has the most significant impact on urban transportation emission, and economic size contributes the most to the growth of transportation emission. Based on the results, we make a few policy recommendations for low-carbon urban transportation of Beijing, which include: improving transportation efficiency in the process of urbanization; promoting energy conservation and emission reduction while pursuing economic development so as to decouple transportation emission from urban development; restricting unordered urban expansion and updating the concept of transportation infrastructure supply; and developing energy technologies to improve energy efficiency.
Fairness of Scoring in Online Job Marketplaces
Authors: Elbassuoni Shady , Amer-Yahia Sihem , Ghizzawi Ahmad
Published: November 2020

We study fairness of scoring in online job marketplaces. We focus on group fairness and aim to algorithmically explore how a scoring function, through which individuals are ranked for jobs, treats different demographic groups. Previous work on group-level fairness has focused on the case where groups are pre-defined or where they are defined using a single protected attribute (e.g., whites vs. blacks or males vs. females). In this article, we argue for the need to examine fairness for groups of people defined with any combination of protected attributes (the-so called subgroup fairness). Existing work also assumes the availability of worker’s data (i.e., data transparency) and the scoring function (i.e., process transparency). We relax that assumption in this work and run user studies to assess the effect of different data and process transparency settings on the ability to assess fairness.

To quantify the fairness of a scoring of a group of individuals, we formulate an optimization problem to find a partitioning of those individuals on their protected attributes that exhibits the highest unfairness with respect to the scoring function. The scoring function yields one histogram of score distributions per partition and we rely on Earth Mover’s Distance, a measure that is commonly used to compare histograms, to quantify unfairness. Since the number of ways to partition individuals is exponential in the number of their protected attributes, we propose a heuristic algorithm to navigate the space of all possible partitionings to identify the one with the highest unfairness. We evaluate our algorithm using a simulation of a crowdsourcing platform and show that it can effectively quantify unfairness of various scoring functions. We additionally run experiments to assess the applicability of our approach in other less-transparent data and process settings. Finally, we demonstrate the effectiveness of our approach in assessing fairness of scoring in a real dataset crawled from the online job marketplace TaskRabbit.
Measuring Female Representation and Impact in Films over Time
Authors: Yang Luoying , Xu Zhou , Luo Jiebo
Published: November 2020

Women have always been underrepresented in movies and not until recently has the representation of women in movies improved. To investigate the improvement of female representation and its relationship with a movie’s success, we propose a new measure, the female cast ratio, and compare it to the commonly used Bechdel test result. We employ generalized linear regression with
L
1
penalty and a Random Forest model to identify the predictors that influence female representation, and evaluate the relationship between female representation and a movie’s success in three aspects: revenue/budget ratio, rating, and popularity. Three important findings in our study have highlighted the difficulties women in the film industry face both upstream and downstream. First, female filmmakers, especially female screenplay writers, are instrumental for movies to have better female representation, but the percentage of female filmmakers has been very low. Second, movies that have the potential to tell insightful stories about women are often provided with lower budgets, and this usually causes the films to in turn receive more criticism. Finally, the demand for better female representation from moviegoers has also not been strong enough to compel the film industry to change, as movies that have poor female representation can still be very popular and successful in the box office.
Mixed integer ink selection for spectral reproduction
Authors: Ansari Navid , Alizadeh-Mousavi Omid , Seidel Hans-Peter , Babaei Vahid
Published: November 2020

We introduce a novel ink selection method for spectral printing. The ink selection algorithm takes a spectral image and a set of inks as input, and selects a subset of those inks that results in optimal spectral reproduction. We put forward an optimization formulation that searches a huge combinatorial space based on mixed integer programming. We show that solving this optimization in the conventional reflectance space is intractable. The main insight of this work is to solve our problem in the spectral absorbance space with a linearized formulation. The proposed ink selection copes with large-size problems for which previous methods are hopeless. We demonstrate the effectiveness of our method in a concrete setting by lifelike reproduction of handmade paintings. For a successful spectral reproduction of high-resolution paintings, we explore their spectral absorbance estimation, efficient coreset representation, and accurate data-driven reproduction.
P-cloth
Authors: Li Cheng , Tang Min , Tong Ruofeng , Cai Ming , Zhao Jieyi , Manocha Dinesh
Published: November 2020

We present a novel parallel algorithm for cloth simulation that exploits multiple GPUs for fast computation and the handling of very high resolution meshes. To accelerate implicit integration, we describe new parallel algorithms for sparse matrix-vector multiplication (SpMV) and for dynamic matrix assembly on a multi-GPU workstation. Our algorithms use a novel work queue generation scheme for a fat-tree GPU interconnect topology. Furthermore, we present a novel collision handling scheme that uses spatial hashing for discrete and continuous collision detection along with a non-linear impact zone solver. Our parallel schemes can distribute the computation and storage overhead among multiple GPUs and enable us to perform almost interactive simulation on complex cloth meshes, which can hardly be handled on a single GPU due to memory limitations. We have evaluated the performance with two multi-GPU workstations (with 4 and 8 GPUs, respectively) on cloth meshes with 0.5 -- 1.65
M
triangles. Our approach can reliably handle the collisions and generate vivid wrinkles and folds at 2 -- 5 fps, which is significantly faster than prior cloth simulation systems. We observe almost linear speedups with respect to the number of GPUs.
Mononizing binocular videos
Authors: Hu Wenbo , Xia Menghan , Fu Chi-Wing , Wong Tien-Tsin
Published: November 2020

This paper presents the idea of
mono-nizing
binocular videos and a framework to effectively realize it. Mono-nize means we purposely convert a binocular video into a regular monocular video with the stereo information implicitly encoded in a visual but nearly-imperceptible form. Hence, we can impartially distribute and show the mononized video as an ordinary monocular video. Unlike ordinary monocular videos, we can restore from it the original binocular video and show it on a stereoscopic display. To start, we formulate an encoding-and-decoding framework with the pyramidal deformable fusion module to exploit long-range correspondences between the left and right views, a quantization layer to suppress the restoring artifacts, and the compression noise simulation module to resist the compression noise introduced by modern video codecs. Our framework is self-supervised, as we articulate our objective function with loss terms defined on the input: a monocular term for creating the mononized video, an invertibility term for restoring the original video, and a temporal term for frame-to-frame coherence. Further, we conducted extensive experiments to evaluate our generated mononized videos and restored binocular videos for diverse types of images and 3D movies. Quantitative results on both standard metrics and user perception studies show the effectiveness of our method.
VDAC
Authors: Mahdavi-Amiri Ali , Yu Fenggen , Zhao Haisen , Schulz Adriana , Zhang Hao
Published: November 2020

We introduce
carvable volume decomposition
for efficient 3-axis CNC machining of 3D freeform objects, where our goal is to develop a fully automatic method to jointly optimize setup and path planning. We formulate our joint optimization as a volume decomposition problem which prioritizes minimizing the number of setup directions while striving for a minimum number of
continuously carvable
volumes, where a 3D volume is continuously carvable, or simply carvable, if it can be carved with the machine cutter traversing a
single continuous
path. Geometrically, carvability combines visibility and monotonicity and presents a new shape property which had not been studied before. Given a target 3D shape and the initial material block, our algorithm first finds the minimum number of carving directions by solving a
set cover
problem. Specifically, we analyze cutter accessibility and select the carving directions based on an assessment of how likely they would lead to a small carvable volume decomposition. Next, to obtain a minimum decomposition based on the selected carving directions efficiently, we narrow down the solution search by focusing on a special kind of points in the residual volume,
single access
or SA points, which are points that can be accessed from
one and only one
of the selected carving directions. Candidate carvable volumes are
grown
starting from the SA points. Finally, we devise an energy term to evaluate the carvable volumes and their combinations, leading to the final decomposition. We demonstrate the performance of our decomposition algorithm on a variety of 2D and 3D examples and evaluate it against the ground truth, where possible, and solutions provided by human experts. Physically machined models are produced where each carvable volume is continuously carved following a connected Fermat spiral toolpath.
Match
Authors: Shi Liang , Li Beichen , Hašan Miloš , Sunkavalli Kalyan , Boubekeur Tamy , Mech Radomir , Matusik Wojciech
Published: November 2020

We present
MATch
, a method to automatically convert photographs of material samples into production-grade procedural material models. At the core of MATch is a new library
DiffMat
that provides differentiable building blocks for constructing procedural materials, and automatic translation of large-scale procedural models, with hundreds to thousands of node parameters, into differentiable node graphs. Combining these translated node graphs with a rendering layer yields an end-to-end differentiable pipeline that maps node graph parameters to rendered images. This facilitates the use of gradient-based optimization to estimate the parameters such that the resulting material, when rendered, matches the target image appearance, as quantified by a style transfer loss. In addition, we propose a deep neural feature-based graph selection and parameter initialization method that efficiently scales to a large number of procedural graphs. We evaluate our method on both rendered synthetic materials and real materials captured as flash photographs. We demonstrate that MATch can reconstruct more accurate, general, and complex procedural materials compared to the state-of-the-art. Moreover, by producing a procedural output, we unlock capabilities such as constructing arbitrary-resolution material maps and parametrically editing the material appearance.
A general framework for pearlescent materials
Authors: Guillén Ibón , Marco Julio , Gutierrez Diego , Jakob Wenzel , Jarabo Adrian
Published: November 2020

The unique and visually mesmerizing appearance of pearlescent materials has made them an indispensable ingredient in a diverse array of applications including packaging, ceramics, printing, and cosmetics. In contrast to their natural counterparts, such synthetic examples of pearlescence are created by dispersing microscopic interference pigments within a dielectric resin. The resulting space of materials comprises an enormous range of different phenomena ranging from smooth lustrous appearance reminiscent of pearl to highly directional metallic gloss, along with a gradual change in color that depends on the angle of observation and illumination. All of these properties arise due to a complex optical process involving multiple scattering from platelets characterized by wave-optical interference. This article introduces a flexible model for simulating the optics of such pearlescent 3D microstructures. Following a thorough review of the properties of currently used pigments and manufacturing-related effects that influence pearlescence, we propose a new model which expands the range of appearance that can be represented, and closely reproduces the behavior of measured materials, as we show in our comparisons. Using our model, we conduct a systematic study of the parameter space and its relationship to different aspects of pearlescent appearance. We observe that several previously ignored parameters have a substantial impact on the material's optical behavior, including the multi-layered nature of modern interference pigments, correlations in the orientation of pigment particles, and variability in their properties (e.g. thickness). The utility of a general model for pearlescence extends far beyond computer graphics: inverse and differentiable approaches to rendering are increasingly used to disentangle the physics of scattering from real-world observations. Our approach could inform such reconstructions to enable the predictive design of tailored pearlescent materials.
DeformSyncNet
Authors: Sung Minhyuk , Jiang Zhenyu , Achlioptas Panos , Mitra Niloy J. , Guibas Leonidas J.
Published: November 2020

Shape deformation is an important component in any geometry processing toolbox. The goal is to enable intuitive deformations of single or multiple shapes or to transfer example deformations to new shapes while preserving the plausibility of the deformed shape(s). Existing approaches assume access to point-level or part-level correspondence or establish them in a preprocessing phase, thus limiting the scope and generality of such approaches. We propose DeformSyncNet, a new approach that allows consistent and synchronized shape deformations without requiring explicit correspondence information. Technically, we achieve this by encoding deformations into a class-specific idealized latent space while decoding them into an individual, model-specific linear deformation action space, operating
directly
in 3D. The underlying encoding and decoding are performed by specialized (jointly trained) neural networks. By design, the inductive bias of our networks results in a deformation space with several desirable properties, such as path invariance across different deformation pathways, which are then also approximately preserved in real space. We qualitatively and quantitatively evaluate our framework against multiple alternative approaches and demonstrate improved performance.
Path cuts
Authors: Wang Beibei , Hašan Miloš , Yan Ling-Qi
Published: November 2020

In scenes lit with sharp point-like light sources, light can bounce several times on specular materials before getting into our eyes, forming purely specular light paths. However, to our knowledge, rendering such multi-bounce pure specular paths has not been handled in previous work: while many light transport methods have been devised to sample various kinds of light paths, none of them are able to find multi-bounce pure specular light paths from a point light to a pinhole camera. In this paper, we present path cuts to efficiently render such light paths. We use a path space hierarchy combined with interval arithmetic bounds to prune non-contributing regions of path space, and to slice the path space into regions small enough to empirically contain at most one solution. Next, we use an automatic differentiation tool and a Newton-based solver to find an admissible specular path within a given path space region. We demonstrate results on several complex specular configurations, including RR, TT, TRT and TTTT paths.
TAP-Net
Authors: Hu Ruizhen , Xu Juzhan , Chen Bin , Gong Minglun , Zhang Hao , Huang Hui
Published: November 2020

We introduce the
transport-and-pack
(TAP) problem, a frequently encountered instance of real-world packing, and develop a
neural optimization
solution based on
reinforcement learning.
Given an initial spatial configuration of boxes, we seek an efficient method to iteratively transport and pack the boxes compactly into a target container. Due to obstruction and accessibility constraints, our problem has to add a new search dimension, i.e., finding an optimal
transport sequence
, to the already immense search space for packing alone. Using a learning-based approach, a trained network can learn and encode solution patterns to guide the solution of new problem instances instead of executing an expensive online search. In our work, we represent the transport constraints using a
precedence graph
and train a neural network, coined TAP-Net, using reinforcement learning to reward
efficient
and
stable
packing. The network is built on an encoder-decoder architecture, where the encoder employs convolution layers to encode the box geometry and precedence graph and the decoder is a recurrent neural network (RNN) which inputs the current encoder output, as well as the current box packing state of the target container, and outputs the next box to pack, as well as its orientation. We train our network on
randomly generated
initial box configurations,
without supervision
, via policy gradients to learn optimal TAP policies to maximize packing efficiency and stability. We demonstrate the performance of TAP-Net on a variety of examples, evaluating the network through ablation studies and comparisons to baselines and alternative network designs. We also show that our network generalizes well to larger problem instances, when trained on small-sized inputs.
Stormscapes
Authors: Hädrich Torsten , Makowski Miłosz , Pałubicki Wojtek , Banuti Daniel T. , Pirk Sören , Michels Dominik L.
Published: November 2020

The complex interplay of a number of physical and meteorological phenomena makes simulating clouds a challenging and open research problem. We explore a physically accurate model for simulating clouds and the dynamics of their transitions. We propose first-principle formulations for computing buoyancy and air pressure that allow us to simulate the variations of atmospheric density and varying temperature gradients. Our simulation allows us to model various cloud types, such as cumulus, stratus, and stratoscumulus, and their realistic formations caused by changes in the atmosphere. Moreover, we are able to simulate large-scale cloud super cells - clusters of cumulonimbus formations - that are commonly present during thunderstorms. To enable the efficient exploration of these stormscapes, we propose a lightweight set of high-level parameters that allow us to intuitively explore cloud formations and dynamics. Our method allows us to simulate cloud formations of up to about 20 km × 20 km extents at interactive rates. We explore the capabilities of physically accurate and yet interactive cloud simulations by showing numerous examples and by coupling our model with atmosphere measurements of real-time weather services to simulate cloud formations in the now. Finally, we quantitatively assess our model with cloud fraction profiles, a common measure for comparing cloud types.
SketchPatch
Authors: Fish Noa , Perry Lilach , Bermano Amit , Cohen-Or Daniel
Published: November 2020

The paradigm of image-to-image translation is leveraged for the benefit of sketch stylization via transfer of geometric textural details. Lacking the necessary volumes of data for standard training of translation systems, we advocate for operation at the patch level, where a handful of stylized sketches provide ample mining potential for patches featuring basic geometric primitives. Operating at the patch level necessitates special consideration of full sketch translation, as individual translation of patches with no regard to neighbors is likely to produce visible seams and artifacts at patch borders. Aligned pairs of styled and plain primitives are combined to form input hybrids containing styled elements around the border and plain elements within, and given as input to a seamless translation (ST) generator, whose output patches are expected to reconstruct the fully styled patch. An adversarial addition promotes generalization and robustness to diverse geometries at inference time, forming a simple and effective system for arbitrary sketch stylization, as demonstrated upon a variety of styles and sketches.
Complementary dynamics
Authors: Zhang Jiayi Eris , Bang Seungbae , Levin David I. W. , Jacobson Alec
Published: November 2020

We present a novel approach to enrich arbitrary rig animations with elastodynamic secondary effects. Unlike previous methods which pit rig displacements and physical forces as adversaries against each other, we advocate that physics should complement artists' intentions. We propose optimizing for elastodynamic displacements in the subspace orthogonal to displacements that can be created by the rig. This ensures that the additional dynamic motions do not
undo
the rig animation. The complementary space is high-dimensional, algebraically constructed without manual oversight, and capable of rich high-frequency dynamics. Unlike prior tracking methods, we do not require extra painted weights, segmentation into fixed and free regions or tracking clusters. Our method is agnostic to the physical model and plugs into non-linear FEM simulations, geometric as-rigid-as-possible energies, or mass-spring models. Our method does not require a particular type of rig and adds secondary effects to skeletal animations, cage-based deformations, wire deformers, motion capture data, and rigid-body simulations.
Glossy probe reprojection for interactive global illumination
Authors: Rodriguez Simon , Leimkühler Thomas , Prakash Siddhant , Wyman Chris , Shirley Peter , Drettakis George
Published: November 2020

Recent rendering advances dramatically reduce the cost of global illumination. But even with hardware acceleration, complex light paths with multiple glossy interactions are still expensive; our new algorithm stores these paths in precomputed light probes and reprojects them at runtime to provide interactivity. Combined with traditional light maps for diffuse lighting our approach interactively renders all light paths in static scenes with opaque objects. Naively reprojecting probes with glossy lighting is memory-intensive, requires efficient access to the correctly reflected radiance, and exhibits problems at occlusion boundaries in glossy reflections. Our solution addresses all these issues. To minimize memory, we introduce an adaptive light probe parameterization that allocates increased resolution for shinier surfaces and regions of higher geometric complexity. To efficiently sample glossy paths, our novel gathering algorithm reprojects probe texels in a view-dependent manner using efficient reflection estimation and a fast rasterization-based search. Naive probe reprojection often sharpens glossy reflections at occlusion boundaries, due to changes in parallax. To avoid this, we split the convolution induced by the BRDF into two steps: we precompute probes using a lower material roughness and apply an adaptive bilateral filter at runtime to reproduce the original surface roughness. Combining these elements, our algorithm interactively renders complex scenes while fitting in the memory, bandwidth, and computation constraints of current hardware.
Single image portrait relighting via explicit multiple reflectance channel modeling
Authors: Wang Zhibo , Yu Xin , Lu Ming , Wang Quan , Qian Chen , Xu Feng
Published: November 2020

Portrait relighting aims to render a face image under different lighting conditions. Existing methods do not explicitly consider some challenging lighting effects such as specular and shadow, and thus may fail in handling extreme lighting conditions. In this paper, we propose a novel framework that explicitly models multiple reflectance channels for single image portrait relighting, including the facial albedo, geometry as well as two lighting effects,
i.e.
, specular and shadow. These channels are finally composed to generate the relit results via deep neural networks. Current datasets do not support learning such multiple reflectance channel modeling. Therefore, we present a large-scale dataset with the ground-truths of the channels, enabling us to train the deep neural networks in a supervised manner. Furthermore, we develop a novel module named Lighting guided Feature Modulation (LFM). In contrast to existing methods which simply incorporate the given lighting in the bottleneck of a network, LFM fuses the lighting by layer-wise feature modulation to deliver more convincing results. Extensive experiments demonstrate that our proposed method achieves better results and is able to generate challenging lighting effects.
Learned feature embeddings for non-line-of-sight imaging and recognition
Authors: Chen Wenzheng , Wei Fangyin , Kutulakos Kiriakos N. , Rusinkiewicz Szymon , Heide Felix
Published: November 2020

Objects obscured by occluders are considered lost in the images acquired by conventional camera systems, prohibiting both visualization and understanding of such hidden objects. Non-line-of-sight methods (NLOS) aim at recovering information about hidden scenes, which could help make medical imaging less invasive, improve the safety of autonomous vehicles, and potentially enable capturing unprecedented high-definition RGB-D data sets that include geometry beyond the directly visible parts. Recent NLOS methods have demonstrated scene recovery from time-resolved pulse-illuminated measurements encoding occluded objects as faint indirect reflections. Unfortunately, these systems are fundamentally limited by the quartic intensity fall-off for diffuse scenes. With laser illumination limited by eye-safety limits, recovery algorithms must tackle this challenge by incorporating scene priors. However, existing NLOS reconstruction algorithms do not facilitate learning scene priors. Even if they did, datasets that allow for such supervision do not exist, and successful encoder-decoder networks and generative adversarial networks fail for real-world NLOS data. In this work, we close this gap by learning hidden scene feature representations tailored to both reconstruction and recognition tasks such as classification or object detection, while still relying on physical models at the feature level. We
overcome the lack of real training data
with a generalizable architecture that can be trained in simulation. We learn the differentiable scene representation jointly with the reconstruction task using a differentiable transient renderer in the objective, and demonstrate that it
generalizes to unseen classes and unseen real-world scenes
, unlike existing encoder-decoder architectures and generative adversarial networks. The proposed method allows for
end-to-end training for different NLOS tasks
, such as image reconstruction, classification, and object detection, while being memory-efficient and running at real-time rates. We demonstrate
hidden view synthesis, RGB-D reconstruction, classification, and object detection
in the hidden scene in an end-to-end fashion.