bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of entropy in real-world noise on speech perception in listeners with normal hearing and hearing loss
Authors: Jorgensen Erik , Wu Yu-Hsiang
Published: December 2023

Hearing aids show more benefit in traditional laboratory speech-in-noise tests than in real-world noisy environments. Real-world noise comprises a large range of acoustic properties that vary randomly and rapidly between and within environments, making quantifying real-world noise and using it in experiments and clinical tests challenging. One approach is to use acoustic features and statistics to quantify acoustic properties of real-world noise and control for them or measure their relationship to listening performance. In this study, the complexity of real-world noise from different environments was quantified using entropy in both the time- and frequency-domains. A distribution of noise segments from low to high entropy were extracted. Using a trial-by-trial design, listeners with normal hearing and hearing loss (in aided and unaided conditions) repeated back sentences embedded in these noise segments. Entropy significantly affected speech perception, with a larger effect of entropy in the time-domain than the frequency-domain, a larger effect for listeners with normal hearing than for listeners with hearing loss, and a larger effect for listeners with hearing loss in the aided than unaided condition. Speech perception also differed between most environment types. Combining entropy with the environment type improved predictions of speech perception above the environment type alone.
Subcortical auditory model including efferent dynamic gain control with inputs from cochlear nucleus and inferior colliculus
Authors: Farhadi Afagh , Jennings Skyler G. , Strickland Elizabeth A. , Carney Laurel H.
Published: December 2023

An auditory model has been developed with a time-varying, gain-control signal based on the physiology of the efferent system and subcortical neural pathways. The medial olivocochlear (MOC) efferent stage of the model receives excitatory projections from fluctuation-sensitive model neurons of the inferior colliculus (IC) and wide-dynamic-range model neurons of the cochlear nucleus. The response of the model MOC stage dynamically controls cochlear gain via simulated outer hair cells. In response to amplitude-modulated (AM) noise, firing rates of most IC neurons with band-enhanced modulation transfer functions in awake rabbits increase over a time course consistent with the dynamics of the MOC efferent feedback. These changes in the rates of IC neurons in awake rabbits were employed to adjust the parameters of the efferent stage of the proposed model. Responses of the proposed model to AM noise were able to simulate the increasing IC rate over time, whereas the model without the efferent system did not show this trend. The proposed model with efferent gain control provides a powerful tool for testing hypotheses, shedding insight on mechanisms in hearing, specifically those involving the efferent system.
Hsa_circ_0007321 regulates Zika virus replication through miR-492/NFKBID/NF-κB signaling pathway
Authors: Kang Lan , Xie He , Ye Haiyan , Jeyarajan Andre J. , Warner Charlotte A. , Huang Yike , Shi Yaoqiang , Li Yujia , Yang Chunhui , Xu Min , Lin Wenyu , Sun Jujun , Chen Limin , Duan Xiaoqiong , Li Shilin
Published: December 2023

Circular RNAs (CircRNAs) have been shown to play a critical role in regulating viral infection and replication. We performed RNA sequencing to identify differentially expressed circRNAs in A549 human lung adenocarcinoma cells with and without Zika virus (ZIKV) infection. Notably, hsa_circ_0007321 was significantly downregulated after ZIKV infection. We then explored the role and mechanism of hsa_circ_0007321 in the regulation of ZIKV replication. Hsa_circ_0007321, derived from exons 2, 3, 4, and 5 of the DIS3L2 (DIS3 like 3'−5' exoribonuclease 2) gene, was mainly enriched in cytoplasm. We found that the knockdown of hsa_circ_0007321 significantly increased microRNA-492 levels to decrease NFKBID (NFKB inhibitor delta) expression, leading to the activation of the nuclear factor-κB (NF-κB) signaling pathway, inflammatory cytokine production, and subsequently, inhibition of ZIKV replication. These findings illustrate that hsa_circ_0007321 acts as a competitive endogenous RNA that regulates ZIKV replication through the miR-492/NFKBID NF-κB signaling pathway.

IMPORTANCE

Over the past decade, increasing evidence has shown that circular RNAs (circRNAs) play important regulatory roles in viral infection and host antiviral responses. However, reports on the role of circRNAs in Zika virus (ZIKV) infection are limited. In this study, we identified 45 differentially expressed circRNAs in ZIKV-infected A549 cells by RNA sequencing. We clarified that a downregulated circRNA, hsa_circ_0007321, regulates ZIKV replication through targeting of miR-492 and the downstream gene NFKBID. NFKBID is a negative regulator of nuclear factor-κB (NF-κB), and we found that inhibition of the NF-κB pathway promotes ZIKV replication. Therefore, this finding that hsa_circ_0007321 exerts its regulatory role on ZIKV replication through the miR-492/NFKBID/NF-κB signaling pathway has implications for the development of strategies to suppress ZIKV and possibly other viral infections.
Complete genome sequences of cluster F1 and cluster B1
Mycobacterium smegmatis
phages Karhdo and Basato
Authors: Kim Jireh , Herrera Carlos , Aung Wai Yan , Gonzales Boyles Gino Pablo , Chavez Carmina , Cibulka Mona , Foley Emma , Guerra Jose , Kumar Disha Byadarahalli Mohan , Levrant Willow , Lim Lewis , Llanes Jose , O'Brien Zachary Kamuela , Pagaduan Art , Richardson Justin Aaron , Rosales Khristian , Schrecengost James , Shin Tommy , Strong-Lundquist Gabriel , Tat Winnie , Vanderford Fritz , Vrinceanu Isabelle , Wang Vicky , Yang Stephanie , Strong Christy , Tsourkas Philippos K. , Regner Kurt
Published: December 2023

We present the complete genome sequences of
Mycobacterium smegmatis
phages Karhdo and Basato, isolated in Clark County, Nevada. The phages were isolated and annotated by students enrolled in undergraduate research courses over two semesters at the University of Nevada, Las Vegas.
Epidemiological characteristics of respiratory viruses in children during the COVID-19 epidemic in Chengdu, China
Authors: Gao Zheng-Xiang , Wang Ya , Yan Ling-Yi , Liu Ting , Peng Lei-Wen
Published: December 2023

The purpose of this retrospective study was to analyze the prevalence of respiratory viruses among children with acute respiratory tract infections (ARTIs) during the coronavirus disease 2019 epidemic (1 March 2020–28 February 2022). This study investigated respiratory viral specimens from children with ARTIs. A total of 7,092 children (<14 years) with ARTIs were included in this study, with a boy-to-girl ratio of 1.43. The median age was 1 year and 5 months. The average age of the patients was 2.7 ± 3.1 years. Patients < 3 years of age were the main population with ARTIs (67%). The predominant viruses were respiratory syncytial virus (RSV) (10.1%) and influenza virus (A and B 9.7%) during the 2 years of the pandemic (1 March 2020–28 February 2022). The proportion of positive viral test results among patients with ARTIs < 6 years of age was higher than that among patients with ARTIs aged 6–14 years (17.3% vs. 5.7%,
P
< 0.01). RSV infections were more common among patients < 3 years of age (
P
< 0.01). Influenza A infections were more common among patients aged 3–6 years (
P
< 0.01). Influenza B infections were more common among patients aged 6–14 years (
P
< 0.01). The positive proportion among boys was higher than that among girls (14.4% vs. 8.6%,
P
< 0.01). Peak virus infections occurred in the autumn and winter seasons, and the lowest activity level occurred in the spring and summer of the 2 years. Compared with that before the epidemic, the number of samples and positive proportion of respiratory viruses decreased significantly.

IMPORTANCE

During the coronavirus disease 2019 epidemic, the Chinese government launched and used a series of nonpharmaceutical interventions (NPIs), including banning social gatherings, wearing face masks, home isolation, and maintaining hand hygiene, to control the disease spread. Whether and how NPIs influence other respiratory viruses in children remain unclear. In this article, we analyzed relative data and found that the number of samples and positive proportion of respiratory viruses decreased significantly compared with that before the epidemic. Clinicians and public health policymakers should pay attention to changes in the epidemic trends and types of respiratory viruses and maintain monitoring of respiratory-related viruses to avoid possible abnormal rebounds and epidemic outbreaks of these viruses.
Noncanonical-NF-κB activation and DDX3 inhibition reduces the HIV-1 reservoir by elimination of latently infected cells
ex-vivo
Authors: Jansen Jade , Kroeze Stefanie , Man Shirley , Andreini Matteo , Bakker Jan-Willem , Zamperini Claudio , Tarditi Alessia , Kootstra Neeltje A. , Geijtenbeek Teunis B. H.
Published: December 2023

Latency reversal and subsequent elimination of the human immunodeficiency virus-1 (HIV-1) reservoir using a combination of compounds with different mechanisms of action are considered a promising tool for HIV-1 cure. Here, we analyzed HIV-1 reservoir reduction by targeting the two host factors; inhibitor of apoptosis proteins (IAPs) and DEAD-box polypeptide 3 (DDX3) using a SMAC mimetic (SMACm) and DDX3 inhibitor (DDX3i), respectively. We observed that SMACm efficiently reactivated HIV-1 in a latency Jurkat model, which was further enhanced by DDX3 inhibition. Strikingly, this compound combination strongly decreased the proportion of latently as well as transcriptionally active infected cells in a T cell line model with a dual-reporter virus. To determine the efficacy of compounds to eradicate the HIV-1 reservoir in people living with HIV (PWH), a novel
ex vivo
HIV-1 reservoir reduction assay (HIVRRA) was developed. DDX3i and SMACm alone reduced the HIV-1 reservoir in peripheral blood mononuclear cells (PBMCs) from the majority of PWH, whereas notably, the SMACm/DDX3i combination reduced the HIV-1 reservoir even further with 53%–90% in all PWH analyzed, while uninfected bystander cells were not affected. Our data highlight that IAPs as well as factors involved in HIV-1 replication like DDX3 are excellent targets for HIV-1 cure strategies. We show for the first time that the combination of SMACm and DDX3i reverses viral latency and specifically eliminates the HIV-1-infected cells
in vitro
and
ex vivo
.

IMPORTANCE

HIV-1 continues to be a major global health challenge. Current HIV-1 treatments are effective but need lifelong adherence. An HIV-1 cure should eliminate the latent viral reservoir that persists in people living with HIV-1. Different methods have been investigated that focus on reactivation and subsequent elimination of the HIV-1 reservoir, and it is becoming clear that a combination of compounds with different mechanisms of actions might be more effective. Here, we target two host factors, inhibitor of apoptosis proteins that control apoptosis and the DEAD-box helicase DDX3, facilitating HIV mRNA transport/translation. We show that targeting of these host factors with SMAC mimetics and DDX3 inhibitors induce reversal of viral latency and eliminate HIV-1-infected cells
in vitro
and
ex vivo
.
Validation of the PyloPlus Urea Breath Test System in pediatric patients
Authors: Price Travis K. , Realegeno Susan , Azad Kamran , Shier Kileen L.
Published: December 2023

This study evaluated the performance of the PyloPlus Urea Breath Test (UBT) System, a Food and Drug Administration (FDA)-approved assay for diagnosis of
Helicobacter pylori
infection in adult patients, using samples from 111 pediatric patients (3–17 years old). Both qualitative results (100% correlation) and quantitative delta over baseline values (
R
2
= 0.9989) from the PyloPlus UBT strongly correlated with the Meridian BreathTek POCone UBT reference method, which is FDA approved for use in pediatric patients (3–17 years old). The PyloPlus UBT performed comparably to the BreathTek UBT without any calculation correction factors for pediatric samples. Consistent with previous studies, male pediatric patients had a significantly higher positivity rate (64%) than female pediatric patients (33%) (
P
= 0.001). There was no difference in positivity rate between two performing locations. This study shows that the PyloPlus UBT system can be used for testing pediatric patient specimens.

IMPORTANCE

For the diagnosis and post-treatment monitoring of
H. pylori
infection, non-invasive testing methodologies improve patient comfort, particularly for children. Previously, only the BreathTek UBT had FDA approval for use in pediatric patients and required an adjustment calculation based on age, height, and weight of the patient. The purpose of this study was to evaluate the performance of the PyloPlus UBT assay in a pediatric population.
Diverse nature of ClpX degradation motifs in
Streptococcus mutans
Authors: Gurung Vivek , Biswas Saswati , Biswas Indranil
Published: December 2023

Protein homeostasis is an essential process that depends on concerted effort of different proteins involved in proper protein folding, deciding the fate of misfolded proteins by either refolding them into their proper conformation or degrading the misfolded proteins. In Gram-positive bacteria, AAA+ ATPases such as ClpX, ClpC, and ClpE interact with the proteolytic ClpP and degrade misfolded proteins. Clp ATPases also maintain amounts of different proteins based on the cellular need. In streptococci, these Clp ATPases play a crucial role in various physiological processes that contribute to virulence, cell growth and division, stress tolerance, competence development, and biofilm formation. Among the Clp ATPase complexes present in low G + C Gram-positive bacteria, ClpX/P is the major proteolytic system. In contrast to numerous ClpX/P substrates identified in
Escherichia coli
and other bacteria, very little is known about the identity of the ClpX/P substrates in streptococci. Using a proteomic approach under late logarithmic growth condition, we screened for putative substrates that might be degraded by ClpX/P; several potential substrates were identified and verified by other methods. SpxA2 is one such candidate protein, and by Western blot, we confirmed that it indeed recognizes SpxA2. We further identified Ala-Ala-Leu, located at the C-terminal of SpxA2, as a ClpX/P degradation signal. Using a green fluorescent protein reporter system, we further confirmed several ClpX/P degradation signals. Furthermore, we found that the zinc-binding domain of ClpX is needed for substrate recognition. Our
in vitro
data indicate that the adaptor or other accessory factors might be needed for the ClpX/P-mediated substrate recognition or degradation. Additional investigations are needed to determine the identity of these factors in the cell.

IMPORTANCE

Cytoplasmic Clp-related proteases play a major role in maintaining cellular proteome in bacteria. ClpX/P is one such proteolytic complex that is important for conserving protein homeostasis. In this study, we investigated the role of ClpX/P in
Streptococcus mutans
, an important oral pathogen. We identified several putative substrates whose cellular levels are regulated by ClpX/P in
S. mutans
and subsequently discovered several recognition motifs that are critical for degradation. Our study is the first comprehensive analysis of determining ClpX/P motifs in streptococci. We believe that identifying the substrates that are regulated by ClpX/P will enhance our understanding about virulence regulation in this important group of pathogens.
Plant based drinks in the diets of infants and young children
Authors: Merritt Russell
Published: December 2023

Plant based drinks (PBD) do not have a role in providing nutrition to infants, other than the feeding of commercial soy and rice hydrolysate based infant formulas for medical, religious or ethical reasons. For toddlers and young children, cow’s milk (CM) has a traditional place in their modern Western diet as an important source of protein, calcium and other nutrients. While milk is not essential to provide a healthy diet for young children, considerable dietary adjustments need to be made to compensate for its absence. Most PBD are not equivalent to CM in terms of inherent nutrient content and bioavailability and are more expensive. There is notable heterogeneity in their nutritional composition. According to recent studies, children who do not drink CM grow slower than those who do. There is relatively little information about the role of specific PBD in children’s diets. Their impact needs to be assessed in the context of their percent of the diet, child age, health status, nutritional requirements and the composition of the rest of the diet. There are both questionable and valid reasons consumers and parents drink and provide PBD to young children, including misinformation, medical conditions, worries about toxins in CM and ethical/religious beliefs. Parents, and consumers in general, are increasingly acting on concerns about animal welfare related to modern farming practices and the adverse environmental impact of meat and dairy farming. Improvements in available alternative drinks and more informative labelling of such products are likely to be welcomed by the marketplace. The new technology of precision fermentation has the potential to lead to milk alternatives that address many of the concerns about both CM and PBD.
Justicia americana exhibits stem density–aboveground biomass relationships and variability in elemental composition and isotopic signature across tissue types and land use gradients
Authors: Wood James L. , Huff Emily
Published: December 2023

Riverine macrophytes are increasingly understood to influence both the physical and chemical dynamics of rivers by creating biogeochemical hotspots and stabilizing benthic sediments. They contribute carbon and nutrients to both aquatic and adjacent terrestrial ecosystems through senescence and herbivory. Here, we report the relationships between Justicia americana biomass, stem length, and stem density, and % carbon (%C), % nitrogen (%N), C:N, δ15N, and δ13C relationships between tissues types (roots, stems, and leaves). Additionally, we report the effects of land use on the plant's tissue. We found that (1) J. americana stem density and dry biomass were positively correlated ( P < 0.001); (2) δ13C and %N were significantly different in leaf and root tissue; (3) δ13C and δ15N were both positively correlated across tissue types; (4) Leaf C:N was less than ½ of root and stem tissue; (5) %C in leaf tissue was positively correlated ( P < 0.05) with forest cover and negatively correlated with urbanization and watershed area; and (6) provide evidence that J. americana utilizes a C3 photosynthetic pathway. Overall, this study provides novel insight into the ecology of J. americana by elucidating the nutritional quality of different plant tissues and stoichiometric changes in the plant in response to land use.
LidarBoX: a 3D-printed, open-source altimeter system to improve photogrammetric accuracy for off-the-shelf drones
Authors: Bierlich K.C. , Wengrove Drummond , Bird Clara N. , Davidson Robert , Chandler Todd , Torres Leigh G. , Cantor Mauricio
Published: December 2023

Drones provide a privileged birds’-eye view for collecting high-resolution imagery for morphometric and behavioral sampling of animals. Biologically meaningful measurements extracted from overhead images require an accurate estimate of altitude, but current commercial drones include inaccurate barometer estimates. Recent proposals for coupling altimeter systems to drones have provided customized, open-source solutions, yet assembling such altimeter systems requires advanced technical skills, thereby potentially limiting their use. Here, we built upon recent advances to provide a 3D-printed enclosure for an altimeter system that is inexpensive, self-contained, easy to setup, and transferable across commercial drones. We depart from a published, successful data logger system composed of a GPS and LiDAR sensor and design a more compact and self-powered version (“LidarBoX”) that easily attaches to a variety of commercial drones. We compare flight times with/without LidarBoX attached, test flight maneuverability and performance, and validate the reliability of measurement accuracy. To make LidarBoX accessible, we provide an open-source repository with design code and files and a how-to-assemble guide for non-specialists. We hope this work helps popularize LiDAR altimeter systems on commercial drones to improve the accuracy and reliability of drones as a sampling platform for ecology and wildlife research.
Wetlands as integral parts of surface water–groundwater interactions in the Athabasca Oil Sands Area: Review and synthesis
Authors: Volik Olena , Petrone Richard , Price Jonathan
Published: December 2023

Wetlands comprise unique water storage and conveyance mechanisms that maintain landscape integrity under the sub-humid climate in the Athabasca Oil Sands Area. In addition to their internal function, wetlands support a two-way hydrological connection to adjacent uplands and provide water for downstream water courses. Understanding the role of wetlands as integral parts of surface water (SW)–groundwater (GW) exchange can provide insights into the functioning of the hydrological system as a whole and contribute to thoughtful water management strategies and better coordination of monitoring efforts in the areas affected by oil sands (OS) activities. As such, this study summarizes the current state of hydrological knowledge on the role of wetlands in SW–GW interactions based on studies conducted within the Western Boreal Plains. In particular, the role of wetland soils and their properties in SW–GW interactions, the effects of wetlands on landscape hydrological connectivity and watershed runoff, and features of “wetland–aquifer” and “wetland–open waterbody” interactions were reviewed. Given that alterations of SW–GW interactions in wetlands can occur as a result of anthropogenic disturbances, the coordination of GW, SW, and wetland monitoring efforts and targeting areas where increased SW–GW exchange occurs would be beneficial for the economic and logistical efficiency of the OS monitoring network.
Non-Newtonian ViRheometry via Similarity Analysis
Authors: Hamamichi Mitsuki , Nagasawa Kentaro , Okada Masato , Seto Ryohei , Yue Yonghao
Published: December 2023

We estimate the three Herschel-Bulkley parameters (yield stress
σ
Y
, power-law index
n
, and consistency parameter
η
) for shear-dependent fluid-like materials possibly with large-scale inclusions, for which rheometers may fail to provide a useful measurement. We perform experiments using the unknown material for dam-break (or column collapse) setups and capture video footage. We then use simulations to optimize for the material parameters. For better match up with the simple shear flow encountered in a rheometer, we modify the flow rule for the elasto-viscoplastic Herschel-Bulkley model. Analyzing the loss landscape for optimization, we realize a
similarity relation
; material parameters far away within this relation would result in matched simulations, making it hard to distinguish the parameters. We found that by exploiting the setup dependency of the similarity relation, we can improve on the estimation using multiple setups, which we propose by analyzing the Hessian of the similarity relation. We validate the efficacy of our method by comparing the estimations to the measurements from a rheometer (for materials without large-scale inclusions) and show applications to materials with large-scale inclusions, including various salad or pasta sauces, and congee.
EXIM: A Hybrid Explicit-Implicit Representation for Text-Guided 3D Shape Generation
Authors: Liu Zhengzhe , Hu Jingyu , Hui Ka-Hei , Qi Xiaojuan , Cohen-Or Daniel , Fu Chi-Wing
Published: December 2023

This paper presents a new text-guided technique for generating 3D shapes. The technique leverages a hybrid 3D shape representation, namely EXIM, combining the strengths of explicit and implicit representations. Specifically, the explicit stage controls the topology of the generated 3D shapes and enables local modifications, whereas the implicit stage refines the shape and paints it with plausible colors. Also, the hybrid approach separates the shape and color and generates color conditioned on shape to ensure shape-color consistency. Unlike the existing state-of-the-art methods, we achieve high-fidelity shape generation from natural-language descriptions without the need for time-consuming per-shape optimization or reliance on human-annotated texts during training or test-time optimization. Further, we demonstrate the applicability of our approach to generate indoor scenes with consistent styles using text-induced 3D shapes. Through extensive experiments, we demonstrate the compelling quality of our results and the high coherency of our generated shapes with the input texts, surpassing the performance of existing methods by a significant margin. Codes and models are released at https://github.com/liuzhengzhe/EXIM.
Concept Decomposition for Visual Exploration and Inspiration
Authors: Vinker Yael , Voynov Andrey , Cohen-Or Daniel , Shamir Ariel
Published: December 2023

A creative idea is often born from transforming, combining, and modifying ideas from existing visual examples capturing various concepts. However, one cannot simply copy the concept as a whole, and inspiration is achieved by examining certain aspects of the concept. Hence, it is often necessary to separate a concept into different aspects to provide new perspectives. In this paper, we propose a method to decompose a visual concept, represented as a set of images, into different visual
aspects
encoded in a hierarchical tree structure. We utilize large vision-language models and their rich latent space for concept decomposition and generation. Each node in the tree represents a sub-concept using a learned vector embedding injected into the latent space of a pretrained text-to-image model. We use a set of regularizations to guide the optimization of the embedding vectors encoded in the nodes to follow the hierarchical structure of the tree. Our method allows to explore and discover new concepts derived from the original one. The tree provides the possibility of endless visual sampling at each node, allowing the user to explore the hidden sub-concepts of the object of interest. The learned aspects in each node can be combined within and across trees to create new visual ideas, and can be used in natural language sentences to apply such aspects to new designs.

Project page: https://inspirationtree.github.io/inspirationtree/
Commonsense Knowledge-Driven Joint Reasoning Approach for Object Retrieval in Virtual Reality
Authors: Jiang Haiyan , Weng Dongdong , Dongye Xiaonuo , Luo Le , Zhang Zhenliang
Published: December 2023

National Key Laboratory of General Artificial Intelligence, Beijing Institute for General Artificial Intelligence (BIGAI), China

Retrieving out-of-reach objects is a crucial task in virtual reality (VR). One of the most commonly used approaches for this task is the gesture-based approach, which allows for bare-hand, eyes-free, and direct retrieval. However, previous work has primarily focused on assigned gesture design, neglecting the context. This can make it challenging to accurately retrieve an object from a large number of objects due to the one-to-one mapping metaphor, limitations of finger poses, and memory burdens. There is a general consensus that objects and contexts are related, which suggests that the object expected to be retrieved is related to the context, including the scene and the objects with which users interact. As such, we propose a commonsense knowledge-driven joint reasoning approach for object retrieval, where human grasping gestures and context are modeled using an And-Or graph (AOG). This approach enables users to accurately retrieve objects from a large number of candidate objects by using natural grasping gestures based on their experience of grasping physical objects. Experimental results demonstrate that our proposed approach improves retrieval accuracy. We also propose an object retrieval system based on the proposed approach. Two user studies show that our system enables efficient object retrieval in virtual environments (VEs).
Amortizing Samples in Physics-Based Inverse Rendering Using ReSTIR
Authors: Wang Yu-Chen , Wyman Chris , Wu Lifan , Zhao Shuang
Published: December 2023

Recently, great progress has been made in physics-based differentiable rendering. Existing differentiable rendering techniques typically focus on
static
scenes, but during inverse rendering---a key application for differentiable rendering---the scene is updated
dynamically
by each gradient step. In this paper, we take a first step to leverage temporal data in the context of inverse direct illumination. By adopting reservoir-based spatiotemporal resampled importance resampling (ReSTIR), we introduce new Monte Carlo estimators for both interior and boundary components of differential direct illumination integrals. We also integrate ReSTIR with antithetic sampling to further improve its effectiveness. At equal frame time, our methods produce gradient estimates with up to 100× lower relative error than baseline methods. Additionally, we propose an inverse-rendering pipeline that incorporates these estimators and provides reconstructions with up to 20× lower error.
The Shortest Route is Not Always the Fastest: Probability-Modeled Stereoscopic Eye Movement Completion Time in VR
Authors: Duinkharjav Budmonde , Liang Benjamin , Patney Anjul , Brown Rachel , Sun Qi
Published: December 2023

Speed and consistency of target-shifting play a crucial role in human ability to perform complex tasks. Shifting our gaze between objects of interest quickly and consistently requires changes both in depth and direction. Gaze changes in depth are driven by slow, inconsistent
vergence movements
which rotate the eyes in opposite directions, while changes in direction are driven by ballistic, consistent movements called
saccades
, which rotate the eyes in the same direction. In the natural world, most of our eye movements are a combination of both types. While scientific consensus on the nature of saccades exists, vergence and combined movements remain less understood and agreed upon.

We eschew the lack of scientific consensus in favor of proposing an operationalized computational model which predicts the completion time of any type of gaze movement during target-shifting in 3D. To this end, we conduct a psychophysical study in a stereo VR environment to collect more than 12,000 gaze movement trials, analyze the temporal distribution of the observed gaze movements, and fit a probabilistic model to the data. We perform a series of objective measurements and user studies to validate the model. The results demonstrate its predictive accuracy, generalization, as well as applications for optimizing visual performance by altering content placement. Lastly, we leverage the model to measure differences in human target-changing time relative to the natural world, as well as suggest scene-aware projection depth. By incorporating the complexities and randomness of human oculomotor control, we hope this research will support new behavior-aware metrics for VR/AR display design, interface layout, and gaze-contingent rendering.
Constrained Delaunay Tetrahedrization: A Robust and Practical Approach
Authors: Diazzi Lorenzo , Panozzo Daniele , Vaxman Amir , Attene Marco
Published: December 2023

We present a numerically robust algorithm for computing the constrained Delaunay tetrahedrization (CDT) of a piecewise-linear complex, which has a 100% success rate on the 4408 valid models in the Thingi10k dataset.

We build on the underlying theory of the well-known tetgen software, but use a floating-point implementation based on indirect geometric predicates to implicitly represent Steiner points: this new approach dramatically simplifies the implementation, removing the need for ad-hoc tolerances in geometric operations. Our approach leads to a robust and parameter-free implementation, with an empirically manageable number of added Steiner points. Furthermore, our algorithm addresses a major gap in tetgen's theory which may lead to algorithmic failure on valid models, even when assuming perfect precision in the calculations.

Our output tetrahedrization conforms with the input geometry without approximations. We can further round our output to floating-point coordinates for downstream applications, which almost always results in valid floating-point meshes unless the input triangulation is very close to being degenerate.
Controllable Group Choreography Using Contrastive Diffusion
Authors: Le Nhat , Do Tuong , Do Khoa , Nguyen Hien , Tjiputra Erman , Tran Quang D. , Nguyen Anh
Published: December 2023

Music-driven group choreography poses a considerable challenge but holds significant potential for a wide range of industrial applications. The ability to generate synchronized and visually appealing group dance motions that are aligned with music opens up opportunities in many fields such as entertainment, advertising, and virtual performances. However, most of the recent works are not able to generate high-fidelity long-term motions, or fail to enable controllable experience. In this work, we aim to address the demand for high-quality and customizable group dance generation by effectively governing the consistency and diversity of group choreographies. In particular, we utilize a diffusion-based generative approach to enable the synthesis of flexible number of dancers and long-term group dances, while ensuring coherence to the input music. Ultimately, we introduce a Group Contrastive Diffusion (GCD) strategy to enhance the connection between dancers and their group, presenting the ability to control the consistency or diversity level of the synthesized group animation via the classifier-guidance sampling technique. Through intensive experiments and evaluation, we demonstrate the effectiveness of our approach in producing visually captivating and consistent group dance motions. The experimental results show the capability of our method to achieve the desired levels of consistency and diversity, while maintaining the overall quality of the generated group choreography.
Locally-Adaptive Level-of-Detail for Hardware-Accelerated Ray Tracing
Authors: Haydel Jacob , Yuksel Cem , Seiler Larry
Published: December 2023

We introduce an adaptive level-of-detail technique for ray tracing triangle meshes that aims to reduce the memory bandwidth used during ray traversal, which can be the bottleneck for rendering time with large scenes and the primary consumer of energy. We propose a specific data structure for hierarchically representing triangle meshes, allowing localized decisions for the desired mesh resolution per ray. Starting with the lowest-resolution triangle mesh level, higher-resolution levels are generated by tessellating each triangle into four via splitting its edges with arbitrarily-placed vertices. We fit the resulting mesh hierarchy into a specialized acceleration structure to perform on-the-fly tessellation level selection during ray traversal. Our structure reduces both storage cost and data movement during rendering, which are the main consumers of energy. It also allows continuous transitions between detail levels, while locally adjusting the mesh resolution per ray and preserving watertightness. We present how this structure can be used with both primary and secondary rays for reflections and shadows, which can intersect with different tessellation levels, providing consistent results. We also propose specific hardware units to cover the cost of additional compute needed for level-of-detail operations. We evaluate our method using a cycle-accurate simulation of a custom ray tracing hardware architecture. Our results show that, as compared to traditional bounding volume hierarchies, our method can provide more than an order of magnitude reduction in energy use and render time, given sufficient computational resources.
GeoLatent: A Geometric Approach to Latent Space Design for Deformable Shape Generators
Authors: Yang Haitao , Sun Bo , Chen Liyan , Pavel Amy , Huang Qixing
Published: December 2023

We study how to optimize the latent space of neural shape generators that map latent codes to 3D deformable shapes. The key focus is to look at a deformable shape generator from a differential geometry perspective. We define a Riemannian metric based on as-rigid-as-possible and as-conformal-as-possible deformation energies. Under this metric, we study two desired properties of the latent space: 1) straight-line interpolations in latent codes follow geodesic curves; 2) latent codes disentangle pose and shape variations at different scales. Strictly enforcing the geometric interpolation property, however, only applies if the metric matrix is a constant. We show how to achieve this property approximately by enforcing that geodesic interpolations are axis-aligned, i.e., interpolations along coordinate axis follow geodesic curves. In addition, we introduce a novel approach that decouples pose and shape variations via generalized eigendecomposition. We also study efficient regularization terms for learning deformable shape generators, e.g., that promote smooth interpolations. Experimental results on benchmark datasets show that our approach leads to interpretable latent codes, improves the generalizability of synthetic shapes, and enhances performance in geodesic interpolation and geodesic shooting.
K-Surfaces: Bézier-Splines Interpolating at Gaussian Curvature Extrema
Authors: Djuren Tobias , Kohlbrenner Maximilian , Alexa Marc
Published: December 2023

K-surfaces are an interactive modeling technique for Bézier-spline surfaces. Inspired by
k
-curves by [Yan et al. 2017], each patch provides a single control point that is being interpolated at a local extremum of Gaussian curvature. The challenge is to solve the inverse problem of finding the center control point of a Bézier patch given the boundary control points and the handle. Unlike the situation in 2D, bi-quadratic Bézier patches may exhibit none, one, or several extrema, and finding them is non-trivial. We solve the difficult inverse problem, including the possible selection among several extrema, by learning the desired function from samples, generated by computing Gaussian curvature of random patches. This approximation provides a stable solution to the ill-defined inverse problem and is much more efficient than direct numerical optimization, facilitating the interactive modeling framework. The local solution is used in an iterative optimization incorporating continuity constraints across patches. We demonstrate that the surface varies smoothly with the handle location and that the resulting modeling system provides local and generally intuitive control. The idea of learning the inverse mapping from handles to patches may be applicable to other parametric surfaces.
Differentiable Rendering of Parametric Geometry
Authors: Worchel Markus , Alexa Marc
Published: December 2023

We propose an efficient method for differentiable rendering of parametric surfaces and curves, which enables their use in inverse graphics problems. Our central observation is that a representative triangle mesh can be extracted from a continuous parametric object in a
differentiable
and
efficient
way. We derive differentiable meshing operators for surfaces and curves that provide varying levels of approximation granularity. With triangle mesh approximations, we can readily leverage existing machinery for differentiable mesh rendering to handle parametric geometry. Naively combining differentiable tessellation with inverse graphics settings lacks robustness and is prone to reaching undesirable local minima. To this end, we draw a connection between our setting and the optimization of triangle meshes in inverse graphics and present a set of optimization techniques, including regularizations and coarse-to-fine schemes. We show the viability and efficiency of our method in a set of image-based computer-aided design applications.
Computational Design of Flexible Planar Microstructures
Authors: Zhang Zhan , Brandt Christopher , Jouve Jean , Wang Yue , Chen Tian , Pauly Mark , Panetta Julian
Published: December 2023

Mechanical metamaterials enable customizing the elastic properties of physical objects by altering their fine-scale structure. A broad gamut of effective material properties can be produced even from a single fabrication material by optimizing the geometry of a periodic microstructure tiling. Past work has extensively studied the capabilities of microstructures in the small-displacement regime, where periodic homogenization of linear elasticity yields computationally efficient optimal design algorithms. However, many applications involve flexible structures undergoing large deformations for which the accuracy of linear elasticity rapidly deteriorates due to geometric nonlinearities. Design of microstructures at finite strains involves a massive increase in computation and is much less explored; no computational tool yet exists to design metamaterials emulating target hyperelastic laws
over finite regions of strain space.

We make an initial step in this direction, developing algorithms to accelerate homogenization and metamaterial design for nonlinear elasticity and building a complete framework for the optimal design of planar metamaterials. Our nonlinear homogenization method works by efficiently constructing an accurate interpolant of a microstructure's deformation over a finite space of macroscopic strains likely to be endured by the metamaterial. From this interpolant, the homogenized energy density, stress, and tangent elasticity tensor describing the microstructure's effective properties can be inexpensively computed at any strain. Our design tool then fits the effective material properties to a target constitutive law over a region of strain space using a parametric shape optimization approach, producing a directly manufacturable geometry. We systematically test our framework by designing a catalog of materials fitting isotropic Hooke's laws as closely as possible. We demonstrate significantly improved accuracy over traditional linear metamaterial design techniques by fabricating and testing physical prototypes.
Thin On-Sensor Nanophotonic Array Cameras
Authors: Chakravarthula Praneeth , Sun Jipeng , Li Xiao , Lei Chenyang , Chou Gene , Bijelic Mario , Froesch Johannes , Majumdar Arka , Heide Felix
Published: December 2023

Today's commodity camera systems rely on compound optics to map light originating from the scene to positions on the sensor where it gets recorded as an image. To record images without optical aberrations, i.e., deviations from Gauss' linear model of optics, typical lens systems introduce increasingly complex stacks of optical elements which are responsible for the height of existing commodity cameras. In this work, we investigate
flat nanophotonic computational cameras
as an alternative that employs an array of skewed lenslets and a learned reconstruction approach. The optical array is embedded on a metasurface that, at 700 nm height, is flat and sits on the sensor cover glass at 2.5 mm focal distance from the sensor. To tackle the highly chromatic response of a metasurface and design the array over the entire sensor, we propose a differentiable optimization method that continuously samples over the visible spectrum and factorizes the optical modulation for different incident fields into individual lenses. We reconstruct a megapixel image from our flat imager with a
learned probabilistic reconstruction
method that employs a generative diffusion model to sample an implicit prior. To tackle
scene-dependent aberrations in broadband
, we propose a method for acquiring paired captured training data in varying illumination conditions. We assess the proposed flat camera design in simulation and with an experimental prototype, validating that the method is capable of recovering images from diverse scenes in broadband with a single nanophotonic layer.
Statistical Verification using Surrogate Models and Conformal Inference and a Comparison with Risk-Aware Verification
Authors: Qin Xin , Xia Yuan , Zutshi Aditya , Fan Chuchu , Deshmukh Jyotirmoy V.
Published: December 2023

Uncertainty in safety-critical cyber-physical systems can be modeled using a finite number of parameters or parameterized input signals. Given a system specification in Signal Temporal Logic (STL), we would like to verify that for all (infinite) values of the model parameters/input signals, the system satisfies its specification. Unfortunately, this problem is undecidable in general.
Statistical model checking
(SMC) offers a solution by providing guarantees on the correctness of CPS models by statistically reasoning on model simulations. We propose a new approach for statistical verification of CPS models for user-provided distribution on the model parameters. Our technique uses model simulations to learn
surrogate models
, and uses
conformal inference
to provide probabilistic guarantees on the satisfaction of a given STL property. Additionally, we can provide prediction intervals containing the quantitative satisfaction values of the given STL property for any user-specified confidence level. We compare this prediction interval with the interval we get using risk estimation procedures. We also propose a refinement procedure based on Gaussian Process (GP)-based surrogate models for obtaining fine-grained probabilistic guarantees over sub-regions in the parameter space. This in turn enables the CPS designer to choose assured validity domains in the parameter space for safety-critical applications. Finally, we demonstrate the efficacy of our technique on several CPS models.
VT-IO: A Virtual Time System Enabling High-Fidelity Container-Based Network Emulation for I/O Intensive Applications
Authors: Chen Gong , Hu Zheng , Qu Yanfeng , Jin Dong
Published: December 2023

Network emulation allows unmodified code execution on lightweight containers to enable accurate and scalable networked application testing. However, such testbeds cannot guarantee fidelity under high workloads, especially when many processes concurrently request resources (e.g., CPU, disk I/O, GPU, and network bandwidth) that are more than the underlying physical machine can offer. A virtual time system enables the emulated hosts to maintain their own notion of virtual time. A container can stop advancing its time when not running (e.g., in an idle or suspended state). The existing virtual time systems focus on precise time management for CPU-intensive applications but are not designed to handle other operations, such as disk I/O, network I/O, and GPU computation. In this article, we develop a lightweight virtual time system that integrates precise I/O time for container-based network emulation. We model and analyze the temporal error during I/O operations and develop a barrier-based time compensation mechanism in the Linux kernel. We also design and implement Dynamic Load Monitor (DLM) to mitigate the temporal error during I/O resource contention. VT-IO enables accurate virtual time advancement with precise I/O time measurement and compensation. The experimental results demonstrate a significant improvement in temporal error with the introduction of DLM. The temporal error is reduced from 7.889 seconds to 0.074 seconds when utilizing the DLM in the virtual time system. Remarkably, this improvement is achieved with an overall overhead of only 1.36% of the total execution time.