Pixel is All You Need: Adversarial Spatio-Temporal Ensemble Active Learning for Salient Object Detection.

Although weakly-supervised techniques can reduce the labeling effort, it is unclear whether a saliency model trained with weakly-supervised data (e.g., point annotation) can achieve the equivalent performance of its fully-supervised version.

IG-Net: An Instrument-guided real-time semantic segmentation framework for prostate dissection during surgery for low rectal cancer.

Background And Objective: Accurate prostate dissection is crucial in transanal surgery for patients with low rectal cancer. Improper dissection can lead to adverse events such as urethral injury, severely affecting the patient's postoperative recovery. However, unclear boundaries, irregular shape of the prostate, and obstructive factors such as smoke present significant challenges for surgeons.

Understanding the mechanisms behind the antibacterial activity of magnesium hydroxide nanoparticles against sulfate-reducing bacteria in sediments.

Nanomaterials, with their small size, surface characteristics, and antibacterial properties, are extensively employed across environmental, energy, biomedical, agricultural, and other industries. This study examined the antibacterial efficacy of magnesium hydroxide (Mg(OH)) nanoparticles (NPs) against sulfate-reducing bacteria (SRB) within sediments. The inhibitory effects of two types of Mg(OH) NPs with distinct particle sizes (20.

Expressive 3D Facial Animation Generation Based on Local-to-Global Latent Diffusion.

3D Facial animations, crucial to augmented and mixed reality digital media, have evolved from mere aesthetic elements to potent storytelling media. Despite considerable progress in facial animation of neutral emotions, existing methods still struggle to capture the authenticity of emotions. This paper introduces a novel approach to capture fine facial expressions and generate facial animations using audio synchronization.

TalkingStyle: Personalized Speech-Driven 3D Facial Animation with Style Preservation.

It is a challenging task to create realistic 3D avatars that accurately replicate individuals' speech and unique talking styles for speech-driven facial animation. Existing techniques have made remarkable progress but still struggle to achieve lifelike mimicry. This paper proposes "TalkingStyle", a novel method to generate personalized talking avatars while retaining the talking style of the person.

Fluid Inverse Volumetric Modeling and Applications from Surface Motion.

In this study, we devise a framework for volumetrically reconstructing fluid from observable, measurable free surface motion. Our innovative method amalgamates the benefits of deep learning and conventional simulation to preserve the guiding motion and temporal coherence of the reproduced fluid. We infer surface velocities by encoding and decoding spatiotemporal features of surface sequences, and a 3D CNN is used to generate the volumetric velocity field, which is then combined with 3D labels of obstacles and boundaries.

A Unified Particle-Based Solver for Non-Newtonian Behaviors Simulation.

In this article, we present a unified framework to simulate non-Newtonian behaviors. We combine viscous and elasto-plastic stress into a unified particle solver to achieve various non-Newtonian behaviors ranging from fluid-like to solid-like. Our constitutive model is based on a Generalized Maxwell model, which incorporates viscosity, elasticity and plasticity in one non-linear framework by a unified way.

Single-cell dissection of the multicellular ecosystem and molecular features underlying microvascular invasion in HCC.

Background And Aims: Microvascular invasion (MVI) is a crucial pathological hallmark of HCC that is closely associated with poor outcomes, early recurrence, and intrahepatic metastasis following surgical resection and transplantation. However, the intricate tumor microenvironment and transcriptional programs underlying MVI in HCC remain poorly understood.

Approach And Results: We performed single-cell RNA sequencing of 46,789 individual cells from 10 samples of MVI+ (MVI present) and MVI- (MVI absent) patients with HCC.

FineStyle: Semantic-Aware Fine-Grained Motion Style Transfer with Dual Interactive-Flow Fusion.

We present FineStyle, a novel framework for motion style transfer that generates expressive human animations with specific styles for virtual reality and vision fields. It incorporates semantic awareness, which improves motion representation and allows for precise and stylish animation generation. Existing methods for motion style transfer have all failed to consider the semantic meaning behind the motion, resulting in limited controls over the generated human animations.

Interactive Virtual Ankle Movement Controlled by Wrist sEMG Improves Motor Imagery: An Exploratory Study.

Virtual reality (VR) techniques can significantly enhance motor imagery training by creating a strong illusion of action for central sensory stimulation. In this article, we establish a precedent by using surface electromyography (sEMG) of contralateral wrist movement to trigger virtual ankle movement through an improved data-driven approach with a continuous sEMG signal for fast and accurate intention recognition. Our developed VR interactive system can provide feedback training for stroke patients in the early stages, even if there is no active ankle movement.

ZetaDesign: an end-to-end deep learning method for protein sequence design and side-chain packing.

Computational protein design has been demonstrated to be the most powerful tool in the last few years among protein designing and repacking tasks. In practice, these two tasks are strongly related but often treated separately. Besides, state-of-the-art deep-learning-based methods cannot provide interpretability from an energy perspective, affecting the accuracy of the design.

MPMNet: A Data-Driven MPM Framework for Dynamic Fluid-Solid Interaction.

High-accuracy, high-efficiency physics-based fluid-solid interaction is essential for reality modeling and computer animation in online games or real-time Virtual Reality (VR) systems. However, the large-scale simulation of incompressible fluid and its interaction with the surrounding solid environment is either time-consuming or suffering from the reduced time/space resolution due to the complicated iterative nature pertinent to numerical computations of involved Partial Differential Equations (PDEs). In recent years, we have witnessed significant growth in exploring a different, alternative data-driven approach to addressing some of the existing technical challenges in conventional model-centric graphics and animation methods.

Graph Diffusion Convolutional Network for Skeleton Based Semantic Recognition of Two-Person Actions.

Graph Convolutional Networks (GCNs) have successfully boosted skeleton-based human action recognition. However, existing GCN-based methods mostly cast the problem as separated person's action recognition while ignoring the interaction between the action initiator and the action responder, especially for the fundamental two-person interactive action recognition. It is still challenging to effectively take into account the intrinsic local-global clues of the two-person activity.

How does digital village construction influences carbon emission? The case of China.

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions.

Salient Object Detection via Dynamic Scale Routing.

Recent research advances in salient object detection (SOD) could largely be attributed to ever-stronger multi-scale feature representation empowered by the deep learning technologies. The existing SOD deep models extract multi-scale features via the off-the-shelf encoders and combine them smartly via various delicate decoders. However, the kernel sizes in this commonly-used thread are usually "fixed".

Foveated Stochastic Lightcuts.

Foveated rendering provides an idea for accelerating rendering algorithms without sacrificing the perceived rendering quality in virtual reality applications. In this paper, we propose a foveated stochastic lightcuts method to render high-quality many-lights illumination effects in high perception-sensitive regions. First, we introduce a spatiotemporal-luminance based lightcuts generation method to generate lightcuts with different accuracy for different visual perception-sensitive regions.

Neurophysiological and Subjective Analysis of VR Emotion Induction Paradigm.

The ecological validity of emotion-inducing scenarios is essential for emotion research. In contrast to the classical passive induction paradigm, immersive VR fully engages the psychological and physiological components of the subject, which is considered an ecologically valid paradigm for studying emotion. Several studies investigate the emotional responses to different VR tasks or games using subjective scales.

Hierarchical anatomical structure-aware based thoracic CT images registration.

Accurate thoracic CT image registration remains challenging due to complex joint deformations and different motion patterns in multiple organs/tissues during breathing. To combat this, we devise a hierarchical anatomical structure-aware based registration framework. It affords a coordination scheme necessary for constraining a general free-form deformation (FFD) during thoracic CT registration.

Nonfinite-modality data augmentation for brain image registration.

Brain image registration is fundamental for brain medical image analysis. However, the lack of paired images with diverse modalities and corresponding ground truth deformations for training hinder its development. We propose a novel nonfinite-modality data augmentation for brain image registration to combat this.

Effect of remediation reagents on bacterial composition and ecological function in black-odorous water sediments.

Black-odorous urban water bodies and sediments pose a serious environmental problem. In this study, we conducted microcosm batch experiments to investigate the effect of remediation reagents (magnesium hydroxide and calcium nitrate) on native bacterial communities and their ecological functions in the black-odorous sediment of urban water. The dominant phyla (Proteobacteria, Actinobacteria, Chloroflexi, and Planctomycetes) and classes (Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria, Actinobacteria, Anaerolineae, and Planctomycetia) were determined under calcium nitrate and magnesium hydroxide treatments.

Blue light irradiation increases the relative abundance of the diatom Nitzschia palea in co-culture with cyanobacterium Microcystis aeruginosa.

Lake eutrophication is associated with cyanobacterial blooms. The pennate diatom Nitzschia palea (N. palea) inhibits the growth of the cyanobacterium Microcystis aeruginosa (M.

Quantitative influence and performance analysis of virtual reality laparoscopic surgical training system.

Background: Virtual reality (VR) surgery training has become a trend in clinical education. Many research papers validate the effectiveness of VR-based surgical simulators in training medical students. However, most existing articles employ subjective methods to study the residents' surgical skills improvement.