bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinicians’ consent law knowledge: The case for education
Authors: Craig Denise Patricia , Thompson Fintan
Published: November 2020

Introduction: The short-term objectives of this study were to investigate clinicians’ confidence with, and knowledge of, consent laws, their behaviour regarding familiarisation with patients’ advance care plans and the potential benefit of brief education. Education covered patients’ rights to refuse treatment, including via advance directive, and the legislated hierarchy of decision-making authority.Methods: Throughout 2018, all clinicians at one Queensland Hospital and Health Service were invited to attend a 1-hour legal education session. The study used a crosssectional survey to measure clinicians’ knowledge before and after education. Responses from 316 pre- and 319 post-education questionnaires were analysed.Results: A 1-hour legal education session improved clinicians’ understanding of legislated consent hierarchy and patients’ rights. Pre education, 4.1% of participants correctly identified the lawful consent hierarchy, rising to 65.5% after education. Accuracy increased significantly after education; however, substantial errors persisted.Conclusions: The potential benefit of education to increase multidisciplinary clinicians’ legal knowledge was supported. Education can ensure that clinicians are made aware of patients’ rights and the potential complexity of lawful substitute decision making.
Pitch perception at very high frequencies: On psychometric functions and integration of frequency information
Authors: Gockel Hedwig E. , Moore Brian C. J. , Carlyon Robert P.
Published: November 2020

Lau et al. [J. Neurosci. 37, 9013–9021 (2017)] showed that discrimination of the fundamental frequency (F0) of complex tones with components in a high-frequency region was better than predicted from the optimal combination of information from the individual harmonics. The predictions depend on the assumption that psychometric functions for frequency discrimination have a slope of 1 at high frequencies. This was tested by measuring psychometric functions for F0 discrimination and frequency discrimination. Difference limens for F0 (F0DLs) and difference limens for frequency for each frequency component were also measured. Complex tones contained harmonics 6–10 and had F0s of 280 or 1400 Hz. Thresholds were measured using 210-ms tones presented diotically in diotic threshold-equalizing noise (TEN), and 1000-ms tones presented diotically in dichotic TEN. The slopes of the psychometric functions were close to 1 for all frequencies and F0s. The ratio of predicted to observed F0DLs was around 1 or smaller for both F0s, i.e., not super-optimal, and was significantly smaller for the low than for the high F0. The results are consistent with the idea that place information alone can convey pitch, but pitch is more salient when phase-locking information is available.
Laser fusion reactor approaches ‘burning plasma’ milestone
Authors: Clery Daniel
Published: November 2020

After a decade, National Ignition Facility nears a self-heated, sustained reaction, though net energy gain is still elusive.
Two-photon frequency comb spectroscopy of atomic hydrogen
Authors: Grinin Alexey , Matveev Arthur , Yost Dylan C. , Maisenbacher Lothar , Wirthl Vitaly , Pohl Randolf , Hänsch Theodor W. , Udem Thomas
Published: November 2020

Testing physics using the hydrogen atom

Discrepancy between the proton radius determined from hydrogen and muonic hydrogen spectroscopy data, the so-called “proton radius puzzle,” has been a focus of the physics community for more than a decade now. Using two-photon ultraviolet frequency comb spectroscopy below 1 kilohertz, Grinin
et al.
report a high-precision measurement of the 1S-3S transition frequency in atomic hydrogen (see the Perspective by Ubachs). Combining this measurement with the data for the 1S-2S transition, the authors obtained the Rydberg constant with improved accuracy and an independent value for the proton charge radius that favors the data from muonic hydrogen. However, the present frequency value differs from the one obtained previously using a different spectroscopic technique, leaving the puzzle still unresolved.

Science
, this issue p.
1061
; see also p.
1033
Elongational stalling activates mitoribosome-associated quality control
Authors: Desai Nirupa , Yang Hanting , Chandrasekaran Viswanathan , Kazi Razina , Minczuk Michal , Ramakrishnan V.
Published: November 2020

Quality control in mitochondria

Human mitochondria have their own genome and ribosomes called mitoribosomes that respectively encode and synthesize essential subunits of complexes that use the energy from the oxidation of metabolites to drive the synthesis of adenosine triphosphate (ATP). These complexes are key to the health of the cell. Desai
et al.
studied a mitoribosome-associated quality control pathway that prevents aberrant translation. They purified mitoribosomes under conditions designed to induce stalling and determined the structures of two intermediates in the rescue pathway. These structures revealed two proteins that eject the unfinished polypeptide chain and peptidyl transfer RNA from the ribosome. Their cryo–electron microscopy dataset also revealed additional states that may correspond to intermediates in the mitochondrial translation elongation cycle.

Science
, this issue p.
1105
Response to Comment on “Forest microclimate dynamics drive plant responses to warming”
Authors: Zellweger Florian , De Frenne Pieter , Lenoir Jonathan , Vangansbeke Pieter , Verheyen Kris , Bernhardt-Römermann Markus , Baeten Lander , Hédl Radim , Berki Imre , Brunet Jörg , Van Calster Hans , Chudomelová Markéta , Decocq Guillaume , Dirnböck Thomas , Durak Tomasz , Heinken Thilo , Jaroszewicz Bogdan , Kopecký Martin , Máliš František , Macek Martin , Malicki Marek , Naaf Tobias , Nagel Thomas A. , Ortmann-Ajkai Adrienne , Petřík Petr , Pielech Remigiusz , Reczyńska Kamila , Schmidt Wolfgang , Standovár Tibor , Świerkosz Krzysztof , Teleki Balázs , Vild Ondřej , Wulf Monika , Coomes David
Published: November 2020

Bertrand
et al
. question our interpretation about warming effects on the thermophilization in forest plant communities and propose an alternative way to analyze climatic debt. We show that microclimate warming is a better predictor than macroclimate warming for studying forest plant community responses to warming. Their additional analyses do not affect or change our interpretations and conclusions.
Exceptional nexus with a hybrid topological invariant
Authors: Tang Weiyuan , Jiang Xue , Ding Kun , Xiao Yi-Xin , Zhang Zhao-Qing , Chan C. T. , Ma Guancong
Published: November 2020

When all routes are exceptional

The exploration of non-Hermitian physics and parity-time symmetry have provided a route to develop a wealth of exotic physical effects. In such dissipative systems, the balance of gain and loss of the system lead to what are called exceptional points, or “sweet spots,” which relate to optimal device operation or material properties. The ability to tune the gain and loss over a range of system properties leads to exceptional arcs. Tang
et al.
show that systems can be designed in which the tuning of multiple parameters leads to a crossroads, or nexus, of exceptional arcs. Illustrating the effect in an acoustic system, the same properties should be attainable over various types of dissipative systems and thus provide a versatile route to fine-tune optimal performance of materials and devices.

Science
, this issue p.
1077
Staying connected under tension
Authors: Raghavan Srikala , Vasioukhin Valeri
Published: November 2020

A tyrosine kinase connects tension with strength of junctions between three adjacent cells
Disorders of vision in neonatal hypoxic-ischaemic encephalopathy: a systematic review
Authors: Nagy Eva , Self Jay , Williams Cathy , Vollmer Brigitte
Published: November 2020

Objective

Neonatal hypoxic-ischaemic encephalopathy (HIE) following perinatal asphyxia in term infants is associated with neonatal mortality and a high risk of neurodevelopmental impairment later in life. Visual disorders are an accepted complication of HIE and the association has been cited in the literature many times. This review aims to study the evidence for this association and assess the quality of the data on which this is based.

Design

A systematic literature review was conducted and 922 citations were assessed using standard methods outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol.

Results

The results demonstrate that the majority of studies have reported on various neurodevelopmental outcomes but rarely specifically vision. Based on limited currently available data, extracted from a number of small studies, an association of neonatal HIE with visual impairments seems to exist but detail is lacking. Notably, in the existing studies, there is a striking lack of consistency in the methods used to diagnose HIE and, similarly, a wide variation in the methods employed to measure visual function.

Conclusions

To explore the observed association further in terms of prognosis and the effects of HIE treatments on visual outcomes, future studies will need to address the issues of standardised diagnostic criteria, severity grading and robust, age-appropriate visual assessment.
Regional ventilation characteristics during non-invasive respiratory support in preterm infants
Authors: Thomson Jessica , Rüegger Christoph M , Perkins Elizabeth J , Pereira-Fantini Prue M , Farrell Olivia , Owen Louise S , Tingay David G
Published: November 2020

Objectives

To determine the regional ventilation characteristics during non-invasive ventilation (NIV) in stable preterm infants. The secondary aim was to explore the relationship between indicators of ventilation homogeneity and other clinical measures of respiratory status.

Design

Prospective observational study.

Setting

Two tertiary neonatal intensive care units.

Patients

Forty stable preterm infants born <30 weeks of gestation receiving either continuous positive airway pressure (n=32) or high-flow nasal cannulae (n=8) at least 24 hours after extubation at time of study.

Interventions

Continuous electrical impedance tomography imaging of regional ventilation during 60 min of quiet breathing on clinician-determined non-invasive settings.

Main outcome measures

Gravity-dependent and right–left centre of ventilation (CoV), percentage of whole lung tidal volume (VT) by lung region and percentage of lung unventilated were determined for 120 artefact-free breaths/infant (4770 breaths included). Oxygen saturation, heart and respiratory rates were also measured.

Results

Ventilation was greater in the right lung (mean 69.1 (SD 14.9)%) total VT and the gravity-non-dependent (ND) lung; ideal–actual CoV 1.4 (4.5)%. The central third of the lung received the most VT, followed by the non-dependent and dependent regions (p<0.0001 repeated-measure analysis of variance). Ventilation inhomogeneity was associated with worse peripheral capillary oxygen saturation (SpO2)/fraction of inspired oxygen (FiO2) (p=0.031, r2 0.12; linear regression). In those infants that later developed bronchopulmonary dysplasia (n=25), SpO2/FiO2 was worse and non-dependent ventilation inhomogeneity was greater than in those that did not (both p<0.05, t-test Welch correction).

Conclusions

There is high breath-by-breath variability in regional ventilation patterns during NIV in preterm infants. Ventilation favoured the ND lung, with ventilation inhomogeneity associated with worse oxygenation.
From cognitive targets to symptom reduction: overview of attention and interpretation bias modification research
Authors: Gober Chelsea Dyan , Lazarov Amit , Bar-Haim Yair
Published: November 2020

Cognitive bias modification (CBM) is a class of mechanised psychological interventions designed to target specific aberrant cognitive processes considered key in the aetiology and/or maintenance of specific psychiatric disorders. In this review, we outline a multistage translational process that allows tracking progress in CBM research. This process involves four steps: (1) the identification of reliable cognitive targets and establishing their association with specific disorders; (2) clinical translations designed to rectify the identified cognitive targets; (3) verification of effective target engagement and (4) testing of clinical utility in randomised controlled trials. Through the prism of this multistage process, we review progress in clinical CBM research in two cognitive domains: attention and interpretation; in six psychiatric conditions: anxiety disorders, major depressive disorder, post-traumatic stress disorder, addictive disorders, eating disorders and obsessive–compulsive disorder. The review highlights achievement as well as shortcomings of the CBM approach en route to becoming a recognised evidence-supported therapy for these disorders.
Diacylglycerol kinase ζ limits IL-2-dependent control of PD-1 expression in tumor-infiltrating T lymphocytes
Authors: Arranz-Nicolás Javier , Martin-Salgado Miguel , Rodríguez-Rodríguez Cristina , Liébana Rosa , Moreno-Ortiz Maria C , Leitner Judith , Steinberger Peter , Ávila-Flores Antonia , Merida Isabel
Published: November 2020

Background

The inhibitory functions triggered by the programmed cell death-1 (PD-1) receptor following binding to its ligand (PD-L1) protect healthy organs from cytotoxic T cells, and neutralize antitumor T cell attack. Antibody-based therapies to block PD-1/PD-L1 interaction have yielded notable results, but most patients eventually develop resistance. This failure is attributed to CD8+ T cells achieving hyporesponsive states from which recovery is hardly feasible. Dysfunctional T cell phenotypes are favored by a sustained imbalance in the diacylglycerol (DAG)- and Ca2+-regulated transcriptional programs. In mice, DAG kinase ζ (DGKζ) facilitates DAG consumption, limiting T cell activation and cytotoxic T cell responses. DGKζ deficiency facilitates tumor rejection in mice without apparent adverse autoimmune effects. Despite its therapeutic potential, little is known about DGKζ function in human T cells, and no known inhibitors target this isoform.

Methods

We used a human triple parameter reporter cell line to examine the consequences of DGKζ depletion on the transcriptional restriction imposed by PD-1 ligation. We studied the effect of DGKζ deficiency on PD-1 expression dynamics, as well as the impact of DGKζ absence on the in vivo growth of MC38 adenocarcinoma cells.

Results

We demonstrate that DGKζ depletion enhances DAG-regulated transcriptional programs, promoting interleukin-2 production and partially counteracting PD-1 inhibitory functions. DGKζ loss results in limited PD-1 expression and enhanced expansion of cytotoxic CD8+ T cell populations. This is observed even in immunosuppressive milieus, and correlates with the reduced ability of MC38 adenocarcinoma cells to form tumors in DGKζ-deficient mice.

Conclusions

Our results, which define a role for DGKζ in the control of PD-1 expression, confirm DGKζ potential as a therapeutic target as well as a biomarker of CD8+ T cell dysfunctional states.
Diagnostic approach to the evaluation of myeloid malignancies following CAR T-cell therapy in B-cell acute lymphoblastic leukemia
Authors: Mo George , Wang Hao-Wei , Talleur Aimee C , Shahani Shilpa A , Yates Bonnie , Shalabi Haneen , Douvas Michael G , Calvo Katherine R , Shern Jack F , Chaganti Sridhar , Patrick Katharine , Song Young , Fry Terry J , Wu Xiaolin , Triplett Brandon M , Khan Javed , Gardner Rebecca A , Shah Nirali N
Published: November 2020

Immunotherapeutic strategies targeting B-cell acute lymphoblastic leukemia (B-ALL) effectively induce remission; however, disease recurrence remains a challenge. Due to the potential for antigen loss, antigen diminution, lineage switch or development of a secondary or treatment-related malignancy, the phenotype and manifestation of subsequent leukemia may be elusive. We report on two patients with multiply relapsed/refractory B-ALL who, following chimeric antigen receptor T-cell therapy, developed myeloid malignancies. In the first case, a myeloid sarcoma developed in a patient with a history of myelodysplastic syndrome. In the second case, two distinct events occurred. The first event represented a donor-derived myelodysplastic syndrome with monosomy 7 in a patient with a prior hematopoietic stem cell transplantation. This patient went on to present with lineage switch of her original B-ALL to ambiguous lineage T/myeloid acute leukemia. With the rapidly evolving field of novel immunotherapeutic strategies, evaluation of relapse and/or subsequent neoplasms is becoming increasingly more complex. By virtue of these uniquely complex cases, we provide a framework for the evaluation of relapse or evolution of a subsequent malignancy following antigen-targeted immunotherapy.
Healthcare professionals’ responsibility for informing relatives at risk of hereditary disease
Authors: Grill Kalle , Rosén Anna
Published: November 2020

Advances in genetic diagnostics lead to more patients being diagnosed with hereditary conditions. These findings are often relevant to patients’ relatives. For example, the success of targeted cancer prevention is dependent on effective disclosure to relatives at risk. Without clear information, individuals cannot take advantage of predictive testing and preventive measures. Against this background, we argue that healthcare professionals have a duty to make actionable genetic information available to their patients’ at-risk relatives. We do not try to settle the difficult question of how this duty should be balanced against other duties, such as the duty of confidentiality and a possible duty not to know one’s genetic predisposition. Instead, we argue for the importance of recognising a general responsibility towards at-risk relatives, to be discharged as well as possible within the limits set by conflicting duties and practical considerations. According to a traditional and still dominant perspective, it is the patient’s duty to inform his or her relatives, while healthcare professionals are only obliged to support their patients in discharging this duty. We argue that this perspective is a mistake and an anomaly. Healthcare professionals do not have a duty to ensure that their patients promote the health of third parties. It is often effective and desirable to engage patients in disseminating information to their relatives. However, healthcare professionals should not thereby deflect their own moral responsibility.
Transitions in decision-making authority at the end of life: a problem of law, ethics and practice in deceased donation
Authors: Then Shih-Ning , Martin Dominique E
Published: November 2020

Where a person is unable to make medical decisions for themselves, law and practice allows others to make decisions on their behalf. This is common at the end of a person’s life where decision-making capacity is often lost. A further, and separate, decision that is often considered at the time of death (and often preceding death) is whether the person wanted to act as an organ or tissue donor. However, in some jurisdictions, the lawful decision-maker for the donation decision (the ‘donation decision-maker’) is different from the person who was granted decision-making authority for medical decisions during the person’s life. To date, little attention has been given in the literature to the ethical concerns and practical problems that arise where this shift in legal authority occurs. Such a change in decision-making authority is particularly problematic where premortem measures are suggested to maximise the chances of a successful organ donation. This paper examines this shift in decision-making authority and discusses the legal, ethical and practical implications of such frameworks.
The notes on rotational surfaces in Galilean space
Authors: Almaz Fatma , Külahcı Mi̇hri̇ban Alyamaç
Published: November 2020

In this study, we provide a brief description of rotational surfaces in 4-dimensional (4D) Galilean space using a curve and matrices in [Formula: see text]. That is, we provide different types of rotational matrices, which are the subgroups of [Formula: see text] by rotating a selected axis in [Formula: see text]. Hence, we choose two parameter matrices groups of rotations and we give the matrices of rotation corresponding to the appropriate subgroup in Galilean 4-space and we generate rotated surfaces.
Observation of a 27 Days Periodicity in Melanoma Diagnosis
Authors: Zioutas Konstantin , Maroudas Marios , Hofmann Sebastian , Kryemadhi Abaz , Matteson Eric L.
Published: November 2020

Streams from the dark universe may affect biologic processes on Earth including occurrence of cancer. Here, we have recovered complete daily melanoma incidence rates 1982–2014 in Australia. If there is no other external cause for melanoma, its seasonal rate should be steady with a broad maximum during local summertime due to increased solar UV exposure. The reported melanoma cases show instead: (A) a modulation repeating every [Formula: see text] weeks; (B) a time-dependence which relates also with Moon’s geocentric orbital position, while it does not fit concurrently measured solar activity; and (C) a modulation periodicity strikingly coinciding with the Moon’s sidereal periodicity of 27.3 days, which is fixed to remote stars and not to the Sun. These findings show that the associated cause must be of exo-solar origin, and not only due steady solar UV exposure. A possible interpretation of the finding is the underlying working hypothesis itself, namely the flux of slow speed streaming DM is temporally enhanced due to gravitational (self-)focusing by the solar system. Interestingly, the gravitational focusing effect by the Moon itself towards the Earth covers speeds up to [Formula: see text][Formula: see text]km/s, fitting within the widely assumed velocity distribution of DM constituents at [Formula: see text][Formula: see text]km/s. The derived observations for melanoma diagnosis are a novel model-independent finding with potential public health implications and possible relevance for other diseases. The results of this work also serve as accumulating and independent signatures strengthening previous physics claims being at work at the Sun and Earth’s upper atmosphere, inspiring a novel cross-disciplinary approach for the dark matter (DM) paradigm. In future, the 27.3 days periodicity does not necessarily require long-term physical and medical measurements to search for a direct cause-effect relationship. Potential candidates from the dark sector are the highly ionizing anti-quark nuggets, magnetic monopoles, but also particles like dark photons; other as yet unpredicted DM constituents with sufficient impact on the highly sensitive living matter could be at work.
EFFECT OF INDIAN OCEAN CYCLONE ON COASTAL REGION USING REMOTE SENSING AND GIS
Authors: KUMARI KHUSHBOO , DEO ASMITA A.
Published: November 2020

The effect of four different cyclones making land fall on four different coastal regions is studied viz., Nisha (2008, Tamil Nadu), Laila (2010, Andhra Pradesh), Sidr (2007, Bangladesh) and land depression BOB 03 (2008, Orissa). Remote sensing and Geographic Information System (GIS) technique are used to detect change in Land use and Land cover (LU/LC). Change in vegetation cover by Normalized Vegetation Index (NDVI) is also investigated. Further, preparation of slope map, processing of buffer zoning map is exercised. These parameters are analyzed to find the impression of cyclones after hitting the coastal boundaries by considering the images before and after the cyclone has passed. Change detection assessment of LU/LC features provides information for monitoring the trend of change in an area. In almost every considered region, it is found that dense vegetation is changed to sparse vegetation. Also, decrease in the irrigated cropland due to heavy rainfall caused by cyclone is noted. Risk zone is created by buffer ring of cyclone track to spot the area under risk zone. The area calculation suggests the effect of cyclone at the distance of 20–50[Formula: see text]km from the cyclone path which is validated from the slope effect on LU/LC, also. Some of the common features such as dense vegetation, show decrease in the area by 71%, 17%, 67% and 60%, or settlement area also shows decrease by 38%, 15%, 57% and 17% due to Laila, BOB 03, Nisha and Sidr cyclones, respectively. Increase in shrubland mix with rangeland by 18%, 113% and 98% is also seen due to Laila, Nisha and Sidr cyclones. Other LU/LC shows changes such as, water bodies increasing by 6%, 189% due to BOB 03 and Nisha cyclones. Changes are also seen in sparsed vegetation, which is decreased in Orissa and Tamil Nadu and increased in Andhra Pradesh and Bangladesh. It is demonstrated that by preparing risk zonation map, risk assessment can be done.
SymmetryNet
Authors: Shi Yifei , Huang Junwen , Zhang Hongjia , Xu Xin , Rusinkiewicz Szymon , Xu Kai
Published: November 2020

We study the problem of symmetry detection of 3D shapes from single-view RGB-D images, where severely missing data renders geometric detection approach infeasible. We propose an end-to-end deep neural network which is able to predict both reflectional and rotational symmetries of 3D objects present in the input RGB-D image. Directly training a deep model for symmetry prediction, however, can quickly run into the issue of overfitting. We adopt a multi-task learning approach. Aside from symmetry axis prediction, our network is also trained to predict symmetry correspondences. In particular, given the 3D points present in the RGB-D image, our network outputs for each 3D point its symmetric counterpart corresponding to a specific predicted symmetry. In addition, our network is able to detect for a given shape multiple symmetries of different types. We also contribute a benchmark of 3D symmetry detection based on single-view RGB-D images. Extensive evaluation on the benchmark demonstrates the strong generalization ability of our method, in terms of high accuracy of both symmetry axis prediction and counterpart estimation. In particular, our method is robust in handling unseen object instances with large variation in shape, multi-symmetry composition, as well as novel object categories.
A reduced-precision network for image reconstruction
Authors: Thomas Manu Mathew , Vaidyanathan Karthik , Liktor Gabor , Forbes Angus G.
Published: November 2020

Neural networks are often quantized to use reduced-precision arithmetic, as it greatly improves their storage and computational costs. This approach is commonly used in image classification and natural language processing applications. However, using a quantized network for the reconstruction of HDR images can lead to a significant loss in image quality. In this paper, we introduce
QW-Net
, a neural network for image reconstruction, in which close to 95% of the computations can be implemented with 4-bit integers. This is achieved using a combination of two U-shaped networks that are specialized for different tasks, a
feature extraction
network based on the U-Net architecture, coupled to a
filtering
network that reconstructs the output image. The feature extraction network has more computational complexity but is more resilient to quantization errors. The filtering network, on the other hand, has significantly fewer computations but requires higher precision. Our network recurrently warps and accumulates previous frames using motion vectors, producing temporally stable results with significantly better quality than TAA, a widely used technique in current games.
Monolith
Authors: Takahashi Tetsuya , Batty Christopher
Published: November 2020

We propose
Monolith
, a monolithic pressure-viscosity-contact solver for more accurately, robustly, and efficiently simulating non-trivial two-way interactions of rigid bodies with inviscid, viscous, or non-Newtonian liquids. Our solver simultaneously handles incompressibility and (optionally) implicit viscosity integration for liquids, contact resolution for rigid bodies, and mutual interactions between liquids and rigid bodies by carefully formulating these as a single unified minimization problem. This monolithic approach reduces or eliminates an array of problematic artifacts, including liquid volume loss, solid interpenetrations, simulation instabilities, artificial "melting" of viscous liquid, and incorrect slip at liquid-solid interfaces. In the absence of solid-solid friction, our minimization problem is a Quadratic Program (QP) with a symmetric positive definite (SPD) matrix and can be treated with a single Linear Complementarity Problem (LCP) solve. When friction is present, we decouple the unified minimization problem into two subproblems so that it can be effectively handled via staggered projections with alternating LCP solves. We also propose a complementary approach for non-Newtonian fluids which can be seamlessly integrated and addressed during the staggered projections. We demonstrate the critical importance of a
contact-aware
, unified treatment of fluid-solid coupling and the effectiveness of our proposed Monolith solver in a wide range of practical scenarios.
Slope-space integrals for specular next event estimation
Authors: Loubet Guillaume , Zeltner Tizian , Holzschuch Nicolas , Jakob Wenzel
Published: November 2020

Monte Carlo light transport simulations often lack robustness in scenes containing specular or near-specular materials. Widely used uni- and bidirectional sampling strategies tend to find light paths involving such materials with insufficient probability, producing unusable images that are contaminated by significant variance.

This article addresses the problem of sampling a light path connecting two given scene points via a single specular reflection or refraction, extending the range of scenes that can be robustly handled by unbiased path sampling techniques. Our technique enables efficient rendering of challenging transport phenomena caused by such paths, such as underwater caustics or caustics involving glossy metallic objects.

We derive analytic expressions that predict the total radiance due to a single reflective or refractive triangle with a microfacet BSDF and we show that this reduces to the well known Lambert boundary integral for irradiance. We subsequently show how this can be leveraged to efficiently sample connections on meshes comprised of vast numbers of triangles.

Our derivation builds on the theory of off-center microfacets and involves integrals in the space of surface slopes.

Our approach straightforwardly applies to the related problem of rendering glints with high-resolution normal maps describing specular microstructure. Our formulation alleviates problems raised by singularities in filtering integrals and enables a generalization of previous work to perfectly specular materials. We also extend previous work to the case of GGX distributions and introduce new techniques to improve accuracy and performance.
ShapeAssembly
Authors: Jones R. Kenny , Barton Theresa , Xu Xianghao , Wang Kai , Jiang Ellen , Guerrero Paul , Mitra Niloy J. , Ritchie Daniel
Published: November 2020

Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: they offer high-quality and editable results but are difficult to author and often produce outputs with limited diversity. On the other extreme are deep generative models: given enough data, they can learn to generate any class of shape but their outputs have artifacts and the representation is not editable.

In this paper, we take a step towards achieving the best of both worlds for novel 3D shape synthesis. First, we propose ShapeAssembly, a domain-specific "assembly-language" for 3D shape structures. ShapeAssembly programs construct shape structures by declaring cuboid part proxies and attaching them to one another, in a hierarchical and symmetrical fashion. ShapeAssembly functions are parameterized with continuous free variables, so that one program structure is able to capture a family of related shapes.

We show how to extract ShapeAssembly programs from existing shape structures in the PartNet dataset. Then, we train a deep generative model, a hierarchical sequence VAE, that learns to write novel ShapeAssembly programs. Our approach leverages the strengths of each representation: the program captures the subset of shape variability that is interpretable and editable, and the deep generative model captures variability and correlations across shape collections that is hard to express procedurally.

We evaluate our approach by comparing the shapes output by our generated programs to those from other recent shape structure synthesis models. We find that our generated shapes are more plausible and physically-valid than those of other methods. Additionally, we assess the latent spaces of these models, and find that ours is better structured and produces smoother interpolations. As an application, we use our generative model and differentiable program interpreter to infer and fit shape programs to unstructured geometry, such as point clouds.
CPPM
Authors: Lin Zehui , Li Sheng , Zeng Xinlu , Zhang Congyi , Jia Jinzhu , Wang Guoping , Manocha Dinesh
Published: November 2020

We present a novel chi-squared progressive photon mapping algorithm (CPPM) that constructs an estimator by controlling the bandwidth to obtain superior image quality. Our estimator has parametric statistical advantages over prior nonparametric methods. First, we show that when a probability density function of the photon distribution is subject to uniform distribution, the radiance estimation is unbiased under certain assumptions. Next, the local photon distribution is evaluated via a chi-squared test to determine whether the photons follow the hypothesized distribution (uniform distribution) or not. If the statistical test deems that the photons inside the bandwidth are uniformly distributed, bandwidth reduction should be suspended. Finally, we present a pipeline with a bandwidth retention and conditional reduction scheme according to the test results. This pipeline not only accumulates sufficient photons for a reliable chi-squared test, but also guarantees that the estimate converges to the correct solution under our assumptions. We evaluate our method on various benchmarks and observe significant improvement in the running time and rendering quality in terms of mean squared error over prior progressive photon mapping methods.
MoGlow
Authors: Henter Gustav Eje , Alexanderson Simon , Beskow Jonas
Published: November 2020

Data-driven modelling and synthesis of motion is an active research area with applications that include animation, games, and social robotics. This paper introduces a new class of probabilistic, generative, and controllable motion-data models based on normalising flows. Models of this kind can describe highly complex distributions, yet can be trained efficiently using exact maximum likelihood, unlike GANs or VAEs. Our proposed model is autoregressive and uses LSTMs to enable arbitrarily long time-dependencies. Importantly, is is also causal, meaning that each pose in the output sequence is generated without access to poses or control inputs from future time steps; this absence of algorithmic latency is important for interactive applications with real-time motion control. The approach can in principle be applied to any type of motion since it does not make restrictive, task-specific assumptions regarding the motion or the character morphology. We evaluate the models on motion-capture datasets of human and quadruped locomotion. Objective and subjective results show that randomly-sampled motion from the proposed method outperforms task-agnostic baselines and attains a motion quality close to recorded motion capture.
Speech gesture generation from the trimodal context of text, audio, and speaker identity
Authors: Yoon Youngwoo , Cha Bok , Lee Joo-Haeng , Jang Minsu , Lee Jaeyeon , Kim Jaehong , Lee Geehyuk
Published: November 2020

For human-like agents, including virtual avatars and social robots, making proper gestures while speaking is crucial in human-agent interaction. Co-speech gestures enhance interaction experiences and make the agents look alive. However, it is difficult to generate human-like gestures due to the lack of understanding of how people gesture. Data-driven approaches attempt to learn gesticulation skills from human demonstrations, but the ambiguous and individual nature of gestures hinders learning. In this paper, we present an automatic gesture generation model that uses the multimodal context of speech text, audio, and speaker identity to reliably generate gestures. By incorporating a multimodal context and an adversarial training scheme, the proposed model outputs gestures that are human-like and that match with speech content and rhythm. We also introduce a new quantitative evaluation metric for gesture generation models. Experiments with the introduced metric and subjective human evaluation showed that the proposed gesture generation model is better than existing end-to-end generation models. We further confirm that our model is able to work with synthesized audio in a scenario where contexts are constrained, and show that different gesture styles can be generated for the same speech by specifying different speaker identities in the style embedding space that is learned from videos of various speakers. All the code and data is available at https://github.com/ai4r/Gesture-Generation-from-Trimodal-Context.
RGB2Hands
Authors: Wang Jiayi , Mueller Franziska , Bernard Florian , Sorli Suzanne , Sotnychenko Oleksandr , Qian Neng , Otaduy Miguel A. , Casas Dan , Theobalt Christian
Published: November 2020

Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a challenging problem that has a high relevance for several human-computer interaction applications, including AR/VR, robotics, or sign language recognition. Existing works are either limited to simpler tracking settings (
e.g.
, considering only a single hand or two spatially separated hands), or rely on less ubiquitous sensors, such as depth cameras. In contrast, in this work we present the first real-time method for motion capture of skeletal pose and 3D surface geometry of hands from a single RGB camera that explicitly considers close interactions. In order to address the inherent depth ambiguities in RGB data, we propose a novel multi-task CNN that regresses multiple complementary pieces of information, including segmentation, dense matchings to a 3D hand model, and 2D keypoint positions, together with newly proposed intra-hand relative depth and inter-hand distance maps. These predictions are subsequently used in a generative model fitting framework in order to estimate pose and shape parameters of a 3D hand model for both hands. We experimentally verify the individual components of our RGB two-hand tracking and 3D reconstruction pipeline through an extensive ablation study. Moreover, we demonstrate that our approach offers previously unseen two-hand tracking performance from RGB, and quantitatively and qualitatively outperforms existing RGB-based methods that were not explicitly designed for two-hand interactions. Moreover, our method even performs on-par with depth-based real-time methods.
Manga filling style conversion with screentone variational autoencoder
Authors: Xie Minshan , Li Chengze , Liu Xueting , Wong Tien-Tsin
Published: November 2020

Western color comics and Japanese-style screened manga are two popular comic styles. They mainly differ in the style of region-filling. However, the conversion between the two region-filling styles is very challenging, and manually done currently. In this paper, we identify that the major obstacle in the conversion between the two filling styles stems from the difference between the fundamental properties of screened region-filling and colored region-filling. To resolve this obstacle, we propose a screentone variational autoencoder, ScreenVAE, to map the screened manga to an intermediate domain. This intermediate domain can summarize local texture characteristics and is interpolative. With this domain, we effectively unify the properties of screening and color-filling, and ease the learning for bidirectional translation between screened manga and color comics. To carry out the bidirectional translation, we further propose a network to learn the translation between the intermediate domain and color comics. Our model can generate quality screened manga given a color comic, and generate color comic that retains the original screening intention by the bitonal manga artist. Several results are shown to demonstrate the effectiveness and convenience of the proposed method. We also demonstrate how the intermediate domain can assist other applications such as manga inpainting and photo-to-comic conversion.
Real-time rendering of decorative sound textures for soundscapes
Authors: Zheng Jinta , Hung Shih-Hsuan , Hiebel Kyle , Zhang Yue
Published: November 2020

Audio recordings contain rich information about sound sources and their properties such as the location, loudness, and frequency of events. One prevalent component in sound recordings is the sound texture, which contains a massive number of events. In such a texture, there can be some distinct and repeated sounds that we term as a foreground sound. Birds chirping in the wind is one such decorative sound texture with the chirping as a foreground sound and the wind as a background texture. To render these decorative sound textures in real-time and with high quality, we create two-layer Markov Models to enable smooth transitions from sound grain to sound grain and propose a hierarchical scheme to generate Head-Related Transfer Function filters for localization cues of sounds represented as area/volume sources. Moreover, during the synthesis stage, we provide control over the frequency and intensity of sounds for customization. Lastly, foreground sounds are often blended into background textures such as the sound of rain splats on car surfaces becoming submerged in the background rain. We develop an extraction component that outperforms existing learning-based methods to facilitate our synthesis with perceptible foreground sounds and well-defined textures.
Neural light field 3D printing
Authors: Zheng Quan , Babaei Vahid , Wetzstein Gordon , Seidel Hans-Peter , Zwicker Matthias , Singh Gurprit
Published: November 2020

Modern 3D printers are capable of printing large-size light-field displays at high-resolutions. However, optimizing such displays in full 3D volume for a given light-field imagery is still a challenging task. Existing light field displays optimize over relatively small resolutions using a few co-planar layers in a 2.5D fashion to keep the problem tractable. In this paper, we propose a novel end-to-end optimization approach that encodes input light field imagery as a continuous-space implicit representation in a neural network. This allows fabricating high-resolution, attenuation-based volumetric displays that exhibit the target light fields. In addition, we incorporate the physical constraints of the material to the optimization such that the result can be printed in practice. Our simulation experiments demonstrate that our approach brings significant visual quality improvement compared to the multilayer and uniform grid-based approaches. We validate our simulations with fabricated prototypes and demonstrate that our pipeline is flexible enough to allow fabrications of both planar and non-planar displays.
Improving the Performance of Heterogeneous Data Centers through Redundancy
Authors: Anton Elene , Ayesta Urtzi , Jonckheere Matthieu , Verloop Ina Maria
Published: November 2020

We analyze the performance of redundancy in a multi-type job and multi-type server system. We assume the job dispatcher is unaware of the servers' capacities, and we set out to study under which circumstances redundancy improves the performance. With redundancy an arriving job dispatches redundant copies to all its compatible servers, and departs as soon as one of its copies completes service. As a benchmark comparison, we take the non-redundant system in which a job arrival is routed to only one randomly selected compatible server. Service times are generally distributed and all copies of a job are identical, i.e., have the same service requirement. In our first main result, we characterize the sufficient and necessary stability conditions of the redundancy system. This condition coincides with that of a system where each job type only dispatches copies into its least-loaded servers, and those copies need to be fully served. In our second result, we compare the stability regions of the system under redundancy to that of no redundancy. We show that if the server's capacities are sufficiently heterogeneous, the stability region under redundancy can be much larger than that without redundancy. We apply the general solution to particular classes of systems, including redundancy-d and nested models, to derive simple conditions on the degree of heterogeneity required for redundancy to improve the stability. As such, our result is the first in showing that redundancy can improve the stability and hence performance of a system when copies are non-i.i.d..
Magma
Authors: Hazimeh Ahmad , Herrera Adrian , Payer Mathias
Published: November 2020

High scalability and low running costs have made fuzz testing the de facto standard for discovering software bugs. Fuzzing techniques are constantly being improved in a race to build the ultimate bug-finding tool. However, while fuzzing excels at finding bugs in the wild, evaluating and comparing fuzzer performance is challenging due to the lack of metrics and benchmarks. For example, crash count---perhaps the most commonly-used performance metric---is inaccurate due to imperfections in deduplication techniques. Additionally, the lack of a unified set of targets results in ad hoc evaluations that hinder fair comparison. We tackle these problems by developing Magma, a ground-truth fuzzing benchmark that enables uniform fuzzer evaluation and comparison. By introducing real bugs into real software, Magma allows for the realistic evaluation of fuzzers against a broad set of targets. By instrumenting these bugs, Magma also enables the collection of bug-centric performance metrics independent of the fuzzer. Magma is an open benchmark consisting of seven targets that perform a variety of input manipulations and complex computations, presenting a challenge to state-of-the-art fuzzers. We evaluate seven widely-used mutation-based fuzzers (AFL, AFLFast, AFL++, FairFuzz, MOpt-AFL, honggfuzz, and SymCC-AFL) against Magma over 200,000 CPU-hours. Based on the number of bugs reached, triggered, and detected, we draw conclusions about the fuzzers' exploration and detection capabilities. This provides insight into fuzzer performance evaluation, highlighting the importance of ground truth in performing more accurate and meaningful evaluations.