bluuebunny/crossref_metadata_2025 huggingface dataset:
Trading Spaces: Adaptive Subspace Time Integration for Contacting Elastodynamics
Authors: Trusty Ty , Fei Yun (Raymond) , Levin David , Kaufman Danny
Published: November 2024

We construct a subspace simulator that adaptively balances solution improvement against system size. The core components of our simulator are an adaptive subspace oracle, model, and parallel time-step solver algorithm. Our in-time-step adaptivity oracle continually assesses subspace solution quality and candidate update proposals while accounting for temporal variations in deformation and spatial variations in material. In turn our adaptivity model is subspace agnostic. It allows application across subspace representations and expresses unrestricted deformations independent of subspace choice. We couple our oracle and model with a custom-constructed parallel time-step solver for our enriched systems that exposes a pair of user tolerances which provide controllable simulation quality. As tolerances are tightened our model converges to full-space solutions (with expected cost increases). On the other hand, as tolerances are relaxed we obtain output-bound simulation costs. We demonstrate the efficacy of our approach across a wide range of challenging nonlinear materials models, material stiffnesses, heterogeneities, dynamic behaviors, and frictionally contacting conditions, obtaining scalable and efficient simulations of complex elastodynamic scenarios.
All you need is rotation: Construction of developable strips
Authors: Maekawa Takashi , Scholz Felix
Published: November 2024

We present a novel approach to generate developable strips along a space curve. The key idea of the new method is to use the rotation angle between the Frenet frame of the input space curve, and its Darboux frame of the curve on the resulting developable strip as a free design parameter, thereby revolving the strip around the tangential axis of the input space curve. This angle is not restricted to be constant but it can be any differentiable function defined on the curve, thereby creating a large design space of developable strips that share a common directrix curve. The range of possibilities for choosing the rotation angle is diverse, encompassing constant angles, linearly varying angles, sinusoidal patterns, and even solutions derived from initial value problems involving ordinary differential equations. This enables the potential of the proposed method to be used for a wide range of practical applications, spanning fields such as architectural design, industrial design, and papercraft modeling. In our computational and physical examples, we demonstrate the flexibility of the method by constructing, among others, toroidal and helical windmill blades for papercraft models, curved foldings, triply orthogonal structures, and developable strips featuring a log-aesthetic directrix curve.
Skeleton-Driven Inbetweening of Bitmap Character Drawings
Authors: Brodt Kirill , Bessmeltsev Mikhail
Published: November 2024

One of the primary reasons for the high cost of traditional animation is the inbetweening process, where artists manually draw each intermediate frame necessary for smooth motion. Making this process more efficient has been at the core of computer graphics research for years, yet the industry has adopted very few solutions. Most existing solutions either require vector input or resort to tight inbetweening; often, they attempt to fully automate the process. In industry, however, keyframes are often spaced far apart, drawn in raster format, and contain occlusions. Moreover, inbetweening is fundamentally an artistic process, so the artist should maintain high-level control over it.

We address these issues by proposing a novel inbetweening system for bitmap character drawings, supporting both
tight
and
far
inbetweening. In our setup, the artist can control motion by animating a skeleton between the keyframe poses. Our system then performs skeleton-based deformation of the bitmap drawings into the same pose and employs discrete optimization and deep learning to blend the deformed images. Besides the skeleton and the two drawn bitmap keyframes, we require very little annotation.

However, deforming drawings with occlusions is complex, as it requires a piecewise smooth deformation field. To address this, we observe that this deformation field is smooth when the drawing is lifted into 3D. Our system therefore optimizes topology of a 2.5D partially layered template that we use to lift the drawing into 3D and get the final piecewise-smooth deformaton, effectively resolving occlusions.

We validate our system through a series of animations, qualitative and quantitative comparisons, and user studies, demonstrating that our approach consistently outperforms the state of the art and our results are consistent with the viewers' perception.

Code and data for our paper are available at http://www-labs.iro.umontreal.ca/~bmpix/inbetweening/.
Solid-Fluid Interaction on Particle Flow Maps
Authors: Chen Duowen , Li Zhiqi , Zhou Junwei , Feng Fan , Du Tao , Zhu Bo
Published: November 2024

We propose a novel solid-fluid interaction method for coupling elastic solids with impulse flow maps. Our key idea is to unify the representation of fluid and solid components as particle flow maps with different lengths and dynamics. The solid-fluid coupling is enabled by implementing two novel mechanisms: first, we developed an impulse-to-velocity transfer mechanism to unify the exchanged physical quantities; second, we devised a particle path integral mechanism to accumulate coupling forces along each flow-map trajectory. Our framework integrates these two mechanisms into an Eulerian-Lagrangian impulse fluid simulator to accommodate traditional coupling models, exemplified by the Material Point Method (MPM) and Immersed Boundary Method (IBM), within a particle flow map framework. We demonstrate our method's efficacy by simulating solid-fluid interactions exhibiting strong vortical dynamics, including various vortex shedding and interaction examples across swimming, falling, breezing, and combustion.
Medial Skeletal Diagram: A Generalized Medial Axis Approach for Compact 3D Shape Representation
Authors: Guo Minghao , Wang Bohan , Matusik Wojciech
Published: November 2024

We propose the Medial Skeletal Diagram, a novel skeletal representation that tackles the prevailing issues around skeleton sparsity and reconstruction accuracy in existing skeletal representations. Our approach augments the continuous elements in the medial axis representation to effectively shift the complexity away from the discrete elements. To that end, we introduce generalized enveloping primitives, an enhancement over the standard primitives in the medial axis, which ensure efficient coverage of intricate local features of the input shape and substantially reduce the number of discrete elements required. Moreover, we present a computational framework for constructing a medial skeletal diagram from an arbitrary closed manifold mesh. Our optimization pipeline ensures that the resulting medial skeletal diagram comprehensively covers the input shape with the fewest primitives. Additionally, each optimized primitive undergoes a post-refinement process to guarantee an accurate match with the source mesh in both geometry and tessellation. We validate our approach on a comprehensive benchmark of 100 shapes, demonstrating the sparsity of the discrete elements and superior reconstruction accuracy across a variety of cases. Finally, we exemplify the versatility of our representation in downstream applications such as shape generation, mesh decomposition, shape optimization, mesh alignment, mesh compression, and user-interactive design.
Dense Server Design for Immersion Cooling
Authors: Kodnongbua Milin , Englhardt Zachary , Bianchini Ricardo , Fonseca Rodrigo , Lebeck Alvin , Berger Daniel S. , Iyer Vikram , Kazhamiaka Fiodar , Schulz Adriana
Published: November 2024

The growing demands for computational power in cloud computing have led to a significant increase in the deployment of high-performance servers. The growing power consumption of servers and the heat they produce is on track to outpace the capacity of conventional air cooling systems, necessitating more efficient cooling solutions such as liquid immersion cooling. The superior heat exchange capabilities of immersion cooling both eliminates the need for bulky heat sinks, fans, and air flow channels while also unlocking the potential go beyond conventional 2D blade servers to three-dimensional designs. In this work, we present a computational framework to explore designs of servers in three-dimensional space, specifically targeting the maximization of server density within immersion cooling tanks. Our tool is designed to handle a variety of physical and electrical server design constraints. We demonstrate our optimized designs can reduce server volume by 25--52% compared to traditional flat server designs. This increased density reduces land usage as well as the amount of liquid used for immersion, with significant reduction in the carbon emissions embodied in datacenter buildings. We further create physical prototypes to simulate dense server designs and perform real-world experiments in an immersion cooling tank demonstrating they operate at safe temperatures. This approach marks a critical step forward in sustainable and efficient datacenter management.
Deformation Recovery: Localized Learning for Detail-Preserving Deformations
Authors: Sundararaman Ramana , Donati Nicolas , Melzi Simone , Corman Etienne , Ovsjanikov Maks
Published: November 2024

We introduce a novel data-driven approach aimed at designing high-quality shape deformations based on a coarse localized input signal. Unlike previous data-driven methods that require a global shape encoding, we observe that detail-preserving deformations can be estimated reliably without any global context in certain scenarios. Building on this intuition, we leverage Jacobians defined in a one-ring neighborhood as a coarse representation of the deformation. Using this as the input to our neural network, we apply a series of MLPs combined with feature smoothing to learn the Jacobian corresponding to the detail-preserving deformation, from which the embedding is recovered by the standard Poisson solve. Crucially, by removing the dependence on a global encoding, every
point
becomes a training example, making the supervision particularly lightweight. Moreover, when trained on a class of shapes, our approach demonstrates remarkable generalization across different object categories. Equipped with this novel network, we explore three main tasks: refining an approximate shape correspondence, unsupervised deformation and mapping, and shape editing. Our code is made available at https://github.com/sentient07/LJN.
StyleCrafter: Taming Artistic Video Diffusion with Reference-Augmented Adapter Learning
Authors: Liu Gongye , Xia Menghan , Zhang Yong , Chen Haoxin , Xing Jinbo , Wang Yibo , Wang Xintao , Shan Ying , Yang Yujiu
Published: November 2024

Text-to-video (T2V) models have shown remarkable capabilities in generating diverse videos. However, they struggle to produce user-desired artistic videos due to (i) text's inherent clumsiness in expressing specific styles and (ii) the generally degraded style fidelity. To address these challenges, we introduce StyleCrafter, a generic method that enhances pretrained T2V models with a style control adapter, allowing video generation in any style by feeding a reference image. Considering the scarcity of artistic video data, we propose to first train a style control adapter using style-rich image datasets, then transfer the learned stylization ability to video generation through a tailor-made finetuning paradigm. To promote content-style disentanglement, we employ carefully designed data augmentation strategies to enhance decoupled learning. Additionally, we propose a scale-adaptive fusion module to balance the influences of text-based content features and image-based style features, which helps generalization across various text and style combinations. StyleCrafter efficiently generates high-quality stylized videos that align with the content of the texts and resemble the style of the reference images. Experiments demonstrate that our approach is more flexible and efficient than existing competitors. Project page: https://gongyeliu.github.io/StyleCrafter.github.io/
Learned Multi-aperture Color-coded Optics for Snapshot Hyperspectral Imaging
Authors: Shi Zheng , Dun Xiong , Wei Haoyu , Dong Siyu , Wang Zhanshan , Cheng Xinbin , Heide Felix , Peng Yifan
Published: November 2024

Learned optics, which incorporate lightweight diffractive optics, coded-aperture modulation, and specialized image-processing neural networks, have recently garnered attention in the field of snapshot hyperspectral imaging (HSI). While conventional methods typically rely on a single lens element paired with an off-the-shelf color sensor, these setups, despite their widespread availability, present inherent limitations. First, the Bayer sensor's spectral response curves are not optimized for HSI applications, limiting spectral fidelity of the reconstruction. Second, single lens designs rely on a single diffractive optical element (DOE) to simultaneously encode spectral information and maintain spatial resolution across all wavelengths, which constrains spectral encoding capabilities. This work investigates a multi-channel lens array combined with aperture-wise color filters, all co-optimized alongside an image reconstruction network. This configuration enables independent spatial encoding and spectral response for each channel, improving optical encoding across both spatial and spectral dimensions. Specifically, we validate that the method achieves over a 5dB improvement in PSNR for spectral reconstruction compared to existing single-diffractive lens and coded-aperture techniques. Experimental validation further confirmed that the method is capable of recovering up to 31 spectral bands within the 429--700 nm range in diverse indoor and outdoor environments.
NFPLight: Deep SVBRDF Estimation via the Combination of Near and Far Field Point Lighting
Authors: Wang Li , Zhang Lianghao , Gao Fangzhou , Kang Yuzhen , Zhang Jiawan
Published: November 2024

Recovering spatial-varying bi-directional reflectance distribution function (SVBRDF) from a few hand-held captured images has been a challenging task in computer graphics. Benefiting from the learned priors from data, single-image methods can obtain plausible SVBRDF estimation results. However, the extremely limited appearance information in a single image does not suffice for high-quality SVBRDF reconstruction. Although increasing the number of inputs can improve the reconstruction quality, it also affects the efficiency of real data capture and adds significant computational burdens. Therefore, the key challenge is to minimize the required number of inputs, while keeping high-quality results. To address this, we propose maximizing the effective information in each input through a novel co-located capture strategy that combines near-field and far-field point lighting. To further enhance effectiveness, we theoretically investigate the inherent relation between two images. The extracted relation is strongly correlated with the slope of specular reflectance, substantially enhancing the precision of roughness map estimation. Additionally, we designed the registration and denoising modules to meet the practical requirements of hand-held capture. Quantitative assessments and qualitative analysis have demonstrated that our method achieves superior SVBRDF estimations compared to previous approaches. All source codes will be publicly released.
Procedural Material Generation with Reinforcement Learning
Authors: Li Beichen , Hu Yiwei , Guerrero Paul , Hasan Milos , Shi Liang , Deschaintre Valentin , Matusik Wojciech
Published: November 2024

Modern 3D content creation heavily relies on procedural assets. In particular, procedural materials are ubiquitous in the industry, but their manipulation remains challenging. Previous work [Hu et al. 2023] conditionally generates procedural graphs that match a given input image. However, the parameter generation step limits how accurately the generated graph matches the input image, due to a reliance on supervision with scarcely available procedural data. We propose to improve parameter prediction accuracy for image-conditioned procedural material generation by leveraging reinforcement learning (RL) and present the first RL approach for procedural materials. RL circumvents the limited availability of procedural data, the domain gap between real and synthetic materials, and the need for end-to-end differentiable loss functions. Given a target image, we retrieve a procedural material and use an RL-trained transformer model to predict a set of parameters that reconstruct the target image as closely as possible. We show that using RL significantly improves parameter prediction to match a given target image compared to supervised methods on both synthetic and real target images.
360-degree Human Video Generation with 4D Diffusion Transformer
Authors: Shao Ruizhi , Pang Youxin , Zheng Zerong , Sun Jingxiang , Liu Yebin
Published: November 2024

We present a novel approach for generating 360-degree high-quality, spatiotemporally coherent human videos from a single image. Our framework combines the strengths of diffusion transformers for capturing global correlations across viewpoints and time, and CNNs for accurate condition injection. The core is a hierarchical 4D transformer architecture that factorizes self-attention across views, time steps, and spatial dimensions, enabling efficient modeling of the 4D space. Precise conditioning is achieved by injecting human identity, camera parameters, and temporal signals into the respective transformers. To train this model, we collect a multi-dimensional dataset spanning images, videos, multi-view data, and limited 4D footage, along with a tailored multi-dimensional training strategy. Our approach overcomes the limitations of previous methods based on generative adversarial networks or vanilla diffusion models, which struggle with complex motions, viewpoint changes, and generalization. Through extensive experiments, we demonstrate our method's ability to synthesize 360-degree realistic, coherent human motion videos, paving the way for advanced multimedia applications in areas such as virtual reality and animation.
Volume Scattering Probability Guiding
Authors: Xu Kehan , Herholz Sebastian , Manzi Marco , Papas Marios , Gross Markus
Published: November 2024

Simulating the light transport of volumetric effects poses significant challenges and costs, especially in the presence of heterogeneous volumes. Generating stochastic paths for volume rendering involves multiple decisions, and previous works mainly focused on directional and distance sampling, where the volume scattering probability (VSP), i.e., the probability of scattering inside a volume, is indirectly determined as a byproduct of distance sampling. We demonstrate that direct control over the VSP can significantly improve efficiency and present an unbiased volume rendering algorithm based on an existing resampling framework for precise control over the VSP. Compared to previous state-of-the-art, which can only increase the VSP without guaranteeing to reach the desired value, our method also supports decreasing the VSP. We further present a data-driven guiding framework to efficiently learn and query an approximation of the optimal VSP everywhere in the scene without the need for user control. Our approach can easily be combined with existing path-guiding methods for directional sampling at minimal overhead and shows significant improvements over the state-of-the-art in various complex volumetric lighting scenarios.
Colorful Diffuse Intrinsic Image Decomposition in the Wild
Authors: Careaga Chris , Aksoy Yağız
Published: November 2024

Intrinsic image decomposition aims to separate the surface reflectance and the effects from the illumination given a single photograph. Due to the complexity of the problem, most prior works assume a single-color illumination and a Lambertian world, which limits their use in illumination-aware image editing applications. In this work, we separate an input image into its diffuse albedo, colorful diffuse shading, and specular residual components. We arrive at our result by gradually removing first the single-color illumination and then the Lambertian-world assumptions. We show that by dividing the problem into easier sub-problems, in-the-wild colorful diffuse shading estimation can be achieved despite the limited ground-truth datasets. Our extended intrinsic model enables illumination-aware analysis of photographs and can be used for image editing applications such as specularity removal and per-pixel white balancing.
Multi-level Partition of Unity on Differentiable Moving Particles
Authors: He Jinjin , Zhang Taiyuan , Kobayashi Hiroki , Kawamoto Atsushi , Zhou Yuqing , Nomura Tsuyoshi , Zhu Bo
Published: November 2024

We introduce a differentiable moving particle representation based on the multi-level partition of unity (MPU) to represent dynamic implicit geometries. At the core of our representation are two groups of particles, named feature particles and sample particles, which can move in space and produce dynamic surfaces according to external velocity fields or optimization gradients. These two particle groups iteratively guide and correct each other by alternating their roles as inputs and outputs. Each feature particle carries a set of coefficients for a local quadratic patch. These particle patches are assembled with partition-of-unity weights to derive a continuous implicit global shape. Each sampling particle carries its position and orientation, serving as dense surface samples for optimization tasks. Based on these moving particles, we develop a fully differentiable framework to infer and evolve highly detailed implicit geometries, enhanced by a multi-level background grid for particle adaptivity, across different inverse tasks. We demonstrated the efficacy of our representation through various benchmark comparisons with state-of-the-art neural representations, achieving lower memory consumption, fewer training iterations, and orders of magnitude higher accuracy in handling topologically complex objects and dynamic tracking tasks.
Gaussian Surfel Splatting for Live Human Performance Capture
Authors: Dong Zheng , Xu Ke , Gao Yaoan , Bao Hujun , Xu Weiwei , Lau Rynson W. H.
Published: November 2024

High-quality real-time rendering using user-affordable capture rigs is an essential property of human performance capture systems for real-world applications. However, state-of-the-art performance capture methods may not yield satisfactory rendering results under a very sparse (e.g., four) capture setting. Specifically, neural radiance field (NeRF)-based methods and 3D Gaussian Splatting (3DGS)-based methods tend to produce local geometry errors for unseen performers, while occupancy field (PIFu)-based methods often produce unrealistic rendering results. In this paper, we propose a novel generalizable neural approach to reconstruct and render the performers from very sparse RGBD streams in high quality. The core of our method is a novel point-based generalizable human (PGH) representation conditioned on the pixel-aligned RGBD features. The PGH representation learns a
surface implicit function
for the regression of surface points and a
Gaussian implicit function
for parameterizing the radiance fields of the regressed surface points with 2D Gaussian surfels, and uses surfel splatting for fast rendering. We learn this hybrid human representation via two novel networks. First, we propose a novel point-regressing network (PRNet) with a depth-guided point cloud initialization (DPI) method to regress an accurate surface point cloud based on the denoised depth information. Second, we propose a novel neural blending-based surfel splatting network (SPNet) to render high-quality geometries and appearances in novel views based on the regressed surface points and high-resolution RGBD features of adjacent views. Our method produces free-view human performance videos of 1K resolution at 12 fps on average. Experiments on two benchmarks show that our method outperforms state-of-the-art human performance capture methods.
Perspective-Aligned AR Mirror with Under-Display Camera
Authors: Wang Jian , Ma Sizhuo , Bayer Karl , Zhang Yi , Wang Peihao , Zhou Bing , Nayar Shree , Krishnan Gurunandan
Published: November 2024

Augmented reality (AR) mirrors are novel displays that have great potential for commercial applications such as virtual apparel try-on. Typically the camera is placed beside the display, leading to distorted perspectives during user interaction. In this paper, we present a novel approach to address this problem by placing the camera behind a transparent display, thereby providing users with a perspective-aligned experience. Simply placing the camera behind the display can compromise image quality due to optical effects. We meticulously analyze the image formation process, and present an image restoration algorithm that benefits from physics-based data synthesis and network design. Our method significantly improves image quality and outperforms existing methods especially on the underexplored wire and backscatter artifacts. We then carefully design a full AR mirror system including display and camera selection, real-time processing pipeline, and mechanical design. Our user study demonstrates that the system is exceptionally well-received by users, highlighting its advantages over existing camera configurations not only as an AR mirror, but also for video conferencing. Our work represents a step forward in the development of AR mirrors, with potential applications in retail, cosmetics, fashion,
etc.
The image restoration dataset and code are available at https://perspective-armirror.github.io/.
Interventional Oncology Meets Immuno-oncology: Combination Therapies for Hepatocellular Carcinoma
Authors: Bitar Ryan , Salem Riad , Finn Richard , Greten Tim F. , Goldberg S. Nahum , Chapiro Julius
Published: November 2024

This review discusses mechanisms behind the immunosuppressive tumor microenvironment, the influence of locoregional therapy on immunotherapy, and the development of imaging and serologic biomarkers in relation to hepatocellular carcinoma.
Isorhamnetin ameliorates dopaminergic neuronal damage via targeting FOSL1 to activate AKT/mTOR in 6-OHDA-induced SH-SY5Y cells
Authors: Qin Shaochen , Wan Xiaobo , Kong Shanshan , Xu Kunmei , Jin Jungong , He Shiming , Chen Mingsheng
Published: November 2024

Isorhamnetin (Iso) ameliorated neuronal activity damage, senescence, apoptosis, and oxidative stress injury in 6-hydroxydopamine (6-OHDA)-induced SH-SY5Y cells. Iso activated AKT/mTOR signaling pathway via inhibiting Fos-like antigen (FOSL1) in 6-OHDA-induced SH-SY5Y cells. Overexpression of FOSL1 attenuated the protective effect of Iso against 6-OHDA-induced neuronal damage in SH-SY5Y cells.
Power Quality Management of Inverter Based on Gradient Descent Optimization
Authors: Hu Changbin , Huang Haiyang , Zhang Sai , Cheng Linshu , Luo Shanna , Wang Gaowei
Published: November 2024

In isolated microgrids, the dynamic performance of the inverter output voltage is degraded due to the connection of unbalanced and nonlinear load, load switching, and significant perturbation of filter parameters. A compensation control structure based on the residual generator integrated with an optimization algorithm is proposed to improve the power quality of the inverter output voltage in this paper. First, the structure and mathematical model of the inverter are analyzed. The sensitivity results show that the residual generator–based compensating control structure improves the robustness of the inverter compared to the conventional V/f control. Second, a controller structure with lower order is derived with reduced‐order theory for easier engineering implementation. Then, the compensation controller parameters are optimized online using the gradient descent optimization algorithm to improve the load disturbance’s dynamic compensation performance and reduce the power quality degradation resulting from parameter perturbation. Finally, the PEK‐530 inverter platform developed by GWinstek is utilized for experimental verification. When the inverter is tested with unbalanced loads and nonlinear loads at load switching and with LC filter parameter perturbation, the three‐phase unbalance, total harmonic distortion rate, d‐axis voltage fluctuation, and total harmonic distortion rate of the inverter output voltage are 3.2%, 5.4%, ±2 V, and 0.5%, respectively, and are further reduced to 0.3%, 2.8%, ±0.2 V, and 0.22%, after the compensation controller is optimized by the gradient descent method. The experimental results show that the proposed improved control strategy can effectively improve the disturbance’s fast compensation performance, robustness to inverter parameter perturbation, and the power quality.
Effects of Hierarchical Unit Culture and Power Distance Orientation on Nurses’ Silence Behavior: The Roles of Perceived Futility and Hospital Management Support for Patient Safety
Authors: Lee Seung Eun , Lee Jeong Won
Published: November 2024

Background: Patient safety is paramount in healthcare, and effective communication is a cornerstone of preventing adverse patient events. Despite nurses’ crucial role in improving patient safety, they often keep silent about their concerns. This study investigated links among hierarchical unit culture, nurses’ power distance orientation, perception of futility, and silence behavior in healthcare environments. Moreover, we aimed to determine whether nurse‐perceived hospital management support for patient safety moderated the association between nurses’ perceived futility and silence behavior.

Methods: This cross‐sectional, correlational study utilized survey data from 730 direct‐care nurses working in 88 medical, surgical, or medical–surgical units across 34 hospitals in South Korea. Validated psychometric scales measured the study variables, and data were analyzed using a 2‐1‐1 type of multilevel structural equation model.

Results: Hierarchical unit culture and power distance orientation showed significant positive associations with nurses’ perception of futility (b = 0.62, p < 0.001, and b = 0.37, p < 0.001, respectively) and subsequently with their silence behavior (b = 0.22, p < 0.01, and b = 0.31, p < 0.001, respectively). Futility was found to mediate the relationship of both hierarchical unit culture (indirect effect = 0.222, 95% confidence interval (CI) [0.006, 0.438]) and power distance orientation (indirect effect = 0.132, 95% CI [0.003, 0.261]) to silence behavior. Hospital management support for patient safety significantly moderated the relationship between futility and silence behavior (b = 0.04, p < 0.05); nurses were less likely to remain silent when they perceived high management support as opposed to low support, regardless of their futility level.

Conclusion: Our findings highlight the crucial influence of organizational culture on nurses’ silence behavior. The findings also underscore the importance of hospital management support with respect to patient safety. Management support may be necessary to combat nurses’ perceived futility and to promote open communication.
Wide‐Passband Microstrip Filters With Wide Stopband Based on Half‐Wavelength Resonators Coupled by Short Connected Line
Authors: Fan Chunfeng , Han Jiahui , Gong Ke , Hu Xuehui , Liu Qing , Liu Yufang
Published: November 2024

A novel and simple design method of wide‐passband filters with wide stopband based on half‐wavelength (λ/2) resonators coupled by a short connected line (SCL) is proposed and analysed in this paper. Different from the traditional parallel‐coupled structure filters, SCL is proposed to realize a strong coupling between two adjacent resonators and suppress the parasitic passbands simultaneously. And the eigenmode analysis method and impedance ratio characteristics are both used to reveal the mechanism of wide‐stopband implementation. To further expand the stopband, filters based on step‐impedance resonators (SIRs) with SCL are proposed and analysed in detail. To verify the proposed design method and wide‐stopband filtering structures, three 4‐pole filters with uniform‐impedance resonators (UIRs), SIRs with same impedance ratio, and SIRs with different impedance ratios are designed, fabricated, and measured. The proposed filters can realize a wide stopband up to 5.8f0 with rejection level better than 20 dB. Moreover, the proposed filters can easily realize a wide bandwidth.
A Phase II Study of Fulvestrant plus Abemaciclib in Hormone Receptor–Positive Advanced or Recurrent Endometrial Cancer
Authors: Green Angela K. , Zhou Qin , Iasonos Alexia , Zammarrelli William A. , Weigelt Britta , Ellenson Lora H. , Chhetri-Long Rashmi , Shah Pooja , Loh Jade , Hom Vania , Selenica Pier , Erinjeri Joseph , Petkovska Iva , Chandarlapaty Sarat , Cohen Seth , Grisham Rachel , Konner Jason , Rubinstein Maria M. , Tew William , Troso-Sandoval Tiffany , Aghajanian Carol , Makker Vicky
Published: November 2024

Purpose:

Inhibition of the cyclin D–cyclin-dependent kinase (CDK)4/6–INK4–retinoblastoma pathway can overcome acquired or de novo treatment resistance to endocrine monotherapy. Responses to endocrine monotherapy in advanced endometrial cancer are suboptimal, perhaps due to genomic alterations that promote estrogen receptor–independent cyclin D1–CDK4/6 activation. We hypothesized that the addition of abemaciclib, a CDK4/6 kinase inhibitor, to antiestrogen therapy with fulvestrant would be an effective therapeutic strategy in patients with advanced or recurrent endometrial cancer.

Patients and Methods:

In this phase II study, patients with advanced or recurrent endometrial cancer received 150 mg of abemaciclib orally twice daily with 500 mg of fulvestrant intramuscularly monthly with a 2-week loading dose. Eligibility included estrogen receptor or progesterone receptor expression ≥1% by IHC, measurable disease, ≤2 prior lines of chemotherapy, and ≤1 prior lines of hormonal therapy. The primary endpoint was the objective response rate by RECIST v1.1.

Results:

Twenty-seven patients initiated therapy, and 25 were evaluable for efficacy. Eleven patients achieved partial response; 10 responses (91%) were in copy number–low/no specific molecular profile tumors, 1 response (9%) was in a microsatellite instability–high tumor, and no responses were observed in copy number–high/TP53abnormal tumors. The objective response rate was 44% (90% confidence interval, 27.0%–62.1%). The median duration of response was 15.6 months. The median progression-free survival was 9.0 months (90% confidence interval, 1.8–20.4). The most common grade ≥3 treatment-related adverse events were neutropenia (26%) and anemia (19%); no new safety signals were identified.

Conclusions:

The combination of abemaciclib and fulvestrant has promising activity with durable responses in advanced or recurrent endometrial cancer; a randomized trial is planned.
NOTCH1 Drives Sexually Dimorphic Immune Responses in Hepatocellular Carcinoma
Authors: Lindblad Katherine E. , Donne Romain , Liebling Ian , Barcena-Varela Marina , Lozano Anthony , Ruiz de Galarreta Marina , Dhainaut Maxime , Param Nesteene J. , Giotti Bruno , Cappuyns Sarah , Kodama Takahiro , Wang Yulei , Kamphorst Alice O. , Tsankov Alexander M. , Lujambio Amaia
Published: November 2024

Hepatocellular carcinoma presents strong sexual dimorphism, being two to three times more frequent in males than in females; however, the role of sex in response to immunotherapies in HCC remains unknown. We demonstrate that NOTCH1, an understudied oncogene in HCC, elicits sexually dimorphic antitumor immunity and response to FDA-approved immunotherapies. Surprisingly, males harboring NOTCH1-driven tumors displayed enhanced antitumor immune responses, which, in mice, were mediated by dendritic and T cells. Conversely, females harboring NOTCH1-driven tumors presented immune evasion and resistance to immunotherapies through a defect in dendritic cell (DC)–mediated priming and activation of CD8+ T cells in mice, which was restored therapeutically with CD40 agonism. Mechanistically, the sexually dimorphic immunity was mediated by genes in the sex chromosomes but not by sex hormones. Together, our study unravels an unexpected association between NOTCH1 and sex in cancer immunity and highlights the potential of restoring the DC−CD8+ T-cell axis with CD40 agonism to improve outcomes.

Significance:

Although HCC presents strong sexual dimorphism, the role of sex in response to immunotherapies remains elusive. With a novel HCC mouse model and validation in patients with HCC, we demonstrate that NOTCH1 disrupts antitumor immunity specifically in females through a mechanism mediated by sex chromosome genes, which is reversed with CD40 agonism.
DYRK2 regulates epithelial-mesenchymal transition restriction in pancreatic cancer liver metastasis by inhibiting Twist
Authors: Pan Hang , Liu Yin , Bao Kejiu , Wang Yulin , Zhang Yuping , Zhou Lina
Published: November 2024

Objectives: To explore the underlying variables and molecular pathways leading to pancreatic cancer liver metastasis.
Methods: Hs766T and Hs766T-L3 cells were used to create in vitro and in vivo pancreatic cancer liver metastasis models. DYRK2 involvement in pancreatic cancer metastasis was investigated using cell adhesion assays, wound healing assays, and migration and invasion assays. To examine the link between DYRK2 expression and epithelial-mesenchymal transition, Western blot, quantitative real-time PCR, immunofluorescence assays, and immunoprecipitation (IP) were utilized. We found that mice with DYRK2 overexpression had a lower incidence of liver metastasis compared to controls.
Results: DYRK2 expression decreased pancreatic cancer tumorigenic activities, including proliferation, migration, and invasion. By analyzing the expression levels of epithelial-mesenchymal transition markers and IP results after overexpressing DYRK2, we found that DYRK2 decreased Twist levels by increasing Twist ubiquitination, thereby inhibiting epithelial-mesenchymal transition.
Conclusions: Our findings provide theoretical and experimental support for the ongoing development of DYRK2-based targeted therapies for pancreatic cancer liver metastases.
Pathogenesis and Key Cells in Allergic Rhinitis
Authors: He Yuzhu , Chen Yuxiang , Xu Shuang , Luo Yang , Qin Fengfeng , Hu Wenjian
Published: November 2024

Background: Allergic rhinitis (AR) is one of the most common chronic diseases worldwide, with prevalence rates as high as 50% in high-income countries. Patients with AR often have symptoms such as runny nose, itchy nose, nasal congestion, sneezing, and signs of edema and pallor of the nasal mucosa, and these pathologies have a major impact on the patient’s learning, sleep, and quality of life, often resulting in significant pain and a huge economic burden for the patient. Summary: Among the current treatments for AR, immunotherapy is able to achieve satisfactory clinical outcomes. This shows the importance of immune cells in AR. However, current therapies do not provide a complete cure for AR. The reason for this is that current research on AR focuses on the mechanism of Th1 and Th2 immune cells in AR, ignoring the role of other key cells in AR. Key Messages: Group 2 innate lymphoid cells, B cells, T cells, and macrophages can play a role in the pathogenesis of AR by producing appropriate cytokines and mediating the inflammatory response. M2 macrophages can promote Th2 cells and eosinophils in AR to enhance the type 2 inflammatory response and further promote AR.
Simultaneous Urothelial Carcinoma in the Upper Urinary Tract and Contralateral Renal Cell Carcinoma: A Case Report
Authors: Ishikawa Keisuke , Nagata Masayoshi , Tomari Miki , Mito Osamu , Hirano Hisashi , Shimizu Fumitaka , Isotani Shuji , Ide Hisamitsu , Horie Shigeo
Published: November 2024

Introduction: Although urological surgeons often diagnose cases of simultaneous double cancers of the urinary tract in our clinical practice, few reports have shown that treatment strategies achieve both anticancer effects and preservation of renal function for simultaneous contralateral renal cell carcinoma and urothelial carcinoma. Although there are many options for the treatment of renal cancer, such as immunotherapy and - drugs, and many surgical procedures, such as laparoscopic surgery and robot-assisted surgery, no treatment strategy has been established for double cancer of the bilateral urinary tracts. We encountered a case in which contralateral renal surgery was performed under a precise preoperative plan; as a result, the introduction of dialysis could be avoided, and the anticancer effect could be maintained. Case Presentation: A 73-year-old man was diagnosed with contralateral left renal cell carcinoma and right ureteral cancer. Initially, the patient underwent laparoscopic radical nephroureterectomy for right ureteral urothelial carcinoma. Subsequently, robot-assisted laparoscopic partial nephrectomy for left renal cell carcinoma was performed after treatment with the molecular-targeted agent, pazopanib. Even after partial nephrectomy, renal function was maintained, and dialysis was avoided. Conclusion: In cases of simultaneous renal cell carcinoma and contralateral ureteral cancer, it is possible to preserve both anticancer effects and renal function using careful treatment strategies.
Rubens Borba de Moraes: Anotações de um bibliófilo
Authors:   Universidade de São Paulo, Antunes Cristina
Published: November 2024

Pensando no importante papel desempenhado pelo bibliotecário, bibliófilo, bibliógrafo, historiador, professor e pesquisador Rubens Borba de Moraes (1899-1986) no universo da bibliografia brasiliana, o livro Rubens Borba de Moraes: Anotações de um Bibliófilo, de Cristina Antunes, reúne o conjunto das notas manuscritas por ele nos livros que constituem sua biblioteca – hoje parte integrante da Biblioteca Brasiliana Guita e José Mindlin, na Universidade de São Paulo (BBM-USP) –, a partir do levantamento, registro e transcrição de toda a marginalia presente nas referidas obras, na forma de anotações feitas no próprio livro, ou notas manuscritas em papéis avulsos, recortes de jornais, recortes de catálogos e notas de venda emitidas por livreiros.
“Porque o maior medo de uma mulher…”: o Terror vivido pela Mulher Brasileira por meio de “Os porcos” e “O caso de Ruth”, de Júlia Lopes de Almeida, e “Brasil”, de Eliane Potiguara
Authors: Lopes Julia de Souza , Melo Leticia dos Montes , Fachin Phablo Roberto Marchis
Published: November 2024

Este artigo apresenta, a partir de teorias da literatura comparada, a análise comparativa de dois contos de Júlia Lopes de Almeida, “Os porcos”, e “O caso de Ruth”, ambos de 1903, e um poema de Eliane Potiguara, “Brasil”, de 2018, de forma a traçar paralelos entre a literatura de horror, a combativa, a feminina e a literatura indígena, produzidas no Brasil, além de discutir a violência sofrida pela mulher brasileira e a existência da Literatura como um elemento central para a combatividade de povos oprimidos.
Current and Emerging Approaches to Imaging Large Vessel Vasculitis
Authors: Tawakol Ahmed , Weber Brittany Nicole , Osborne Michael T. , Matza Mark A. , Baliyan Vinit , Arevalo Molina Ana Belen , Lau Hui Chong , Heidari Pedram , Bucerius Jan , Wallace Zachary S. , Hedgire Sandeep , Unizony Sebastian
Published: November 2024

Large vessel vasculitides (LVV) comprise a group of inflammatory disorders that involve the large arteries, such as the aorta and its primary branches. The cause of LVV is often rheumatologic and includes giant cell arteritis and Takayasu arteritis. Giant cell arteritis is the most common form of LVV affecting people >50 years of age with a slight female predominance. Takayasu arteritis is more frequently seen in younger populations and is significantly more common in women. Prompt identification of LVV is crucial as it can lead to debilitating complications if left untreated, including blindness in the case of giant cell arteritis and large artery stenosis and aneurysms in the case of all forms of LVV. Noninvasive imaging methods have greatly changed the approach to managing LVV. Today, imaging (with ultrasound, magnetic resonance imaging, computed tomography, and positron emission tomography) is routinely used in the diagnosis of LVV. In patients with giant cell arteritis, imaging often spares the use of invasive procedures such as temporal artery biopsy. In addition, vascular imaging is also crucial for longitudinal surveillance of arterial damage. Finally, imaging is currently being studied for its role in assessing treatment response and ongoing disease activity and its potential value in determining the presence of vascular wall remodeling (eg, scarring). This review explores the current uses of noninvasive vascular imaging in LVV.
Contemporary State-of-the-Art PCI of Left Main Coronary Artery Disease
Authors: Wee Seong-Bong , Ahn Jung-Min , Kang Do-Yoon , Park Seung-Jung , Park Duk-Woo
Published: November 2024

The left main coronary artery (LMCA) supplies over 70% of the myocardium, and significant LMCA disease is associated with high morbidity and mortality. With remarkable advances in percutaneous coronary intervention (PCI), including stent technology, antithrombotic agents, and evolving procedural techniques, PCI has become an important treatment option in clinical practice guidelines for the revascularization of LMCA disease. In contemporary clinical practice, a heart-team approach to shared decision-making, considering clinical/anatomic factors along with patient preferences, is emphasized for patients with significant LMCA disease requiring myocardial revascularization. Furthermore, recent progress in PCI procedures combined with intravascular imaging or functional guidance has resulted in significant improvements in PCI outcomes, especially for complex lesions, including LMCA disease. Nevertheless, owing to inherent anatomic complexities and frequent multivessel involvement, several unmet issues remain regarding the determination of the appropriate treatment approach for significant LMCA disease, for which further clinical research is required. This contemporary review article provides a comprehensive overview of left main PCI based on current guidelines and underlying trial data, addresses important unresolved diagnostic and therapeutic issues, and identifies future perspectives likely to advance progress in this field.
Clematis alopecuros (Ranunculaceae), another new synonym of C. hastata from China
Authors: HUANG QIAO-LAN , FEI WEN-QUN , YU QI , YUAN QIONG , YANG QIN-ER
Published: November 2024

Based on consultation of literature, survey of herbarium specimens (including type material) and observations of living plants in the wild, we demonstrate that Clematis alopecuros (Ranunculaceae), recently described from Zhuxi county in western Hubei, China, is not essentially different from C. hastata in any characters and most readily distinguishable by a unique array of characters in the Chinese Clematis. We therefore place C. alopecuros in synonymy with C. hastata herein.
Leveraging Community Assets and Carving Out the Anti-Racist Futures: Asian American Teachers’ Pedagogies and Praxis in Urban Schools
Authors: Kim Yeji , An Sohyun
Published: November 2024

Framed by community-responsive pedagogy, this study focused on Asian American teachers in NYC public schools and explored how they used community resources in their teaching for students who were predominantly of Asian descent. The findings show that the teachers centered their students’ own ethnic communities to discuss and make sense of hatred and harassment targeting Asian communities during the pandemic. Teachers also used various locally available and culturally and ethnically rich community resources to help young students affirm their racial, ethnic, and cultural identities while developing their critical consciousness of the history of racism amidst the dehumanization and criminalization of Asians.