EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

Speech-driven 3D face animation aims to generate realistic facial expressions that match the speech content and emotion. However, existing methods often neglect emotional facial expressions or fail to disentangle them from speech content. To address this issue, this paper proposes an end-to-end neural network to disentangle different emotions in speech so as to generate rich 3D facial expressions. Specifically, we introduce the emotion disentangling encoder (EDE) to disentangle the emotion and content in the speech by cross-reconstructed speech signals with different emotion labels. Then an emotion-guided feature fusion decoder is employed to generate a 3D talking face with enhanced emotion. The decoder is driven by the disentangled identity, emotional, and content embeddings so as to generate controllable personal and emotional styles. Finally, considering the scarcity of the 3D emotional talking face data, we resort to the supervision of facial blendshapes, which enables the reconstruction of plausible 3D faces from 2D emotional data, and contribute a large-scale 3D emotional talking face dataset (3D-ETF) to train the network. Our experiments and user studies demonstrate that our approach outperforms state-of-the-art methods and exhibits more diverse facial movements. We recommend watching the supplementary video: https://ziqiaopeng.github.io/emotalkComment: Accepted by ICCV 202

p53 independent epigenetic-differentiation treatment in xenotransplant models of acute myeloid leukemia

Suppression of apoptosis by TP53 mutation contributes to resistance of acute myeloid leukemia (AML) to conventional cytotoxic treatment. Using differentiation to induce irreversible cell cycle exit in AML cells could be a p53-independent treatment alternative, however, this possibility requires evaluation. In vitro and in vivo regimens of the cytosine analogue decitabine that deplete the chromatin modifying enzyme DNA methyl-transferase 1 (DNMT1) without phosphorylating p53 or inducing early apoptosis were determined. These decitabine regimens but not equimolar DNA-damaging cytarabine up regulated the key late differentiation factors CEBPε and p27/CDKN1B, induced cellular differentiation, and terminated AML cell-cycle, even in cytarabine-resistant p53- and p16/CDKN2A-null AML cells. Leukemia initiation by xeno-transplanted AML cells was abrogated but normal hematopoietic stem cell (HSC) engraftment was preserved. In vivo, the low toxicity allowed frequent drug administration to increase exposure, an important consideration for S-phase specific decitabine therapy. In xeno-transplant models of p53-null and relapsed/refractory AML, the non-cytotoxic regimen significantly extended survival compared to conventional cytotoxic cytarabine. Modifying in vivo dose and schedule to emphasize this pathway of decitabine action can bypass a mechanism of resistance to standard therapy

Relationship between freight accessibility and logistics employment in US counties

This paper analyzes the relationship between freight accessibility and logistics employment in the US. It develops an accessibility measure relevant for logistics companies based on a gravity model. This allows for an analysis of the accessibility of US counties focusing on four different modes of transportation: road, rail, air, and maritime. Using a Partial Least Squares model, these four different freight accessibility measures are combined into two constructs, continental and intercontinental freight accessibility, and related to logistics employment. Results show that highly accessible counties attract more logistics employment than other counties. The analyses show that it is very important to control for the effect of the county population on both freight accessibility and logistics employment. While county population explains the most variation in the logistics employment per county, there is a significant relationship between freight accessibility and logistics employment, when controlling for this effect

Influence of O2, H2O and airborne hydrocarbons on the properties of selected 2D materials

This paper reviews the effect of ambient exposure on the properties of selected 2D materials. Many molecules in ambient air can adsorb onto 2D material surfaces to impact their properties and device performance. This paper highlights recent work on the interaction between 2D materials and three ambient-present molecules: O2, H2O, and airborne hydrocarbons. We focus our discussions on graphene but also include research on other 2D materials, such as BN, transition metal dichalcogenides, and 2D heterostructures. We discuss the molecular mechanism of their interactions with 2D materials and the impact on electrical, optical, and wetting properties and device performances

First-principles study of the electronic, optical and transport of few-layer semiconducting MXene

First-principles study of the electronic, optical and transport of few-layer semiconducting MXen

Understanding the Evolution and Applications of Intelligent Systems via a Tri-X Intelligence (TI) Model

The evolution and application of intelligence have been discussed from perspectives of life, control theory and artificial intelligence. However, there has been no consensus on understanding the evolution of intelligence. In this study, we propose a Tri-X Intelligence (TI) model, aimed at providing a comprehensive perspective to understand complex intelligence and the implementation of intelligent systems. In this work, the essence and evolution of intelligent systems (or system intelligentization) are analyzed and discussed from multiple perspectives and at different stages (Type I, Type II and Type III), based on a Tri-X Intelligence model. Elemental intelligence based on scientific effects (e.g., conscious humans, cyber entities and physical objects) is at the primitive level of intelligence (Type I). Integrated intelligence formed by two-element integration (e.g., human-cyber systems and cyber-physical systems) is at the normal level of intelligence (Type II). Complex intelligence formed by ternary-interaction (e.g., a human-cyber-physical system) is at the dynamic level of intelligence (Type III). Representative cases are analyzed to deepen the understanding of intelligent systems and their future implementation, such as in intelligent manufacturing. This work provides a systematic scheme, and technical supports, to understand and develop intelligent systems

Vibration Control of Steel Wind Turbine Tower Using a Novel Tuned Mass Damper Refitted via Inner Platform

Steel large-megawatts wind turbines have the light-damping and long-period properties, resulting in the adverse vibrations under the wind loads. In this paper, a novel tuned mass damper refitted via inner platform (IP-TMD) is proposed to control the excessive vibration of steel wind turbine tower (WTT). Firstly, the dynamic equation of steel WTT controlled by the IP-TMD system is established according to the principle of virtual work, and its dynamic coefficient and frequency ratio at corresponding fixed points are deduced. Then, the optimal frequency ratio and optimal stiffness and damping coefficients are obtained by the system optimization. Furthermore, a numerical simulation research is employed to analyze the frequency-response curves and resonance mitigation effect of IP-TMD under harmonic excitation. Finally, the vibration control efficiency of IP-TMD is calculated using the Wilson-θ method under the wind loadings; the results indicated that IP-TMD is able to reduce the dynamic response of steel WTT over 45% compared with the uncontrolled WTT cases

Interfacial Electronic Rearrangement and Synergistic Catalysis for Alkaline Water Splitting in Carbon-Encapsulated Ni (111)/Ni₃C (113) Heterostructures

The realization of efficient water electrolysis is still blocked by the requirement for a high and stable driving potential above thermodynamic requirements. An Ni-based electrocatalyst, is a promising alternative for noble-metal-free electrocatalysts but tuning its surface electronic structure and exposing more active sites are the critical challenges to improving its intrinsic catalytic activity. Here, we tackle the challenge by tuning surface electronic structures synergistically with interfacial chemistry and crystal facet engineering, successfully designing and synthesizing the carbon-encapsulated Ni (111)/Ni3C (113) heterojunction electrocatalyst, demonstrating superior hydrogen evolution reaction (HER) activities, good stabilities with a small overpotential of −29 mV at 10 mA/cm2, and a low Tafel slope of 59.96 mV/dec in alkaline surroundings, approximating a commercial Pt/C catalyst and outperforming other reported Ni-based catalysts. The heterostructure electrocatalyst operates at 1.55 V and 1.26 V to reach 10 and 1 mA cm−2 in two-electrode measurements for overall alkaline water splitting, corresponding to 79% and 98% electricity-to-fuel conversion efficiency with respect to the lower heating value of hydrogen