Does urbanization have spatial spillover effect on poverty reduction: empirical evidence from rural China

In light of a scarcity of research on the spatial effects of urbanization on poverty reduction, this study uses panel data on 30 provinces in China from 2009 to 2019 to construct a system of indices to assess poverty that spans the four dimensions of the economy, education, health, and living. We use the spatial autocorrelation test and the spatial Durbin model (SDM) to analyze the spatial effects of urbanization on poverty reduction in these different dimensions. The main conclusions are as follows: (a) China’s urbanization has the characteristics of spatial aggregation and a spatial spillover effect. (b) Different dimensions of poverty had the attributes of spatial agglomeration, and Moran’s index of a reduction in economic poverty was the highest. Under the SDM, the different dimensions of poverty also showed a significant positive spatial correlation. (c) Urbanization has a significant effect on poverty reduction along the dimensions of the economy, education, and living, but has little effect on reducing health poverty. It has a spatial spillover effect on poverty reduction in economic and living contexts. (d) There were spatial differences in the effect of urbanization on relieving economic and living-related poverty

Design of multi-resonance thermally activated delayed fluorescence materials for organic light-emitting diodes

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement no. 891606 (TADFNIR). We are also grateful for financial support from the University of St Andrews Restarting Research Funding Scheme (SARRF), which is funded through the Scottish Funding Council grant reference SFC/AN/08/020. J.W. thanks the China Scholarship Council (202006250026). We thank the Engineering and Physical Sciences Research Council for support (EP/P010482/1, EP/R511778/1 and EP/L017008/1).Two strategies to improve the performance of multiresonant thermally activated delayed fluorescence (MR-TADF) compounds are explored. These include incorporation of units to turn on aggregation-induced emission so as to permit use of MR-TADF compounds at high doping concentrations, and the use of heavy atoms to increase spin-orbit coupling to enhance reverse intersystem crossing rates. Preliminary photophysical investigations are presented.Postprin

ITportrait: Image-Text Coupled 3D Portrait Domain Adaptation

Domain adaptation of 3D portraits has gained more and more attention. However, the transfer mechanism of existing methods is mainly based on vision or language, which ignores the potential of vision-language combined guidance. In this paper, we propose a vision-language coupled 3D portraits domain adaptation framework, namely Image and Text portrait (ITportrait). ITportrait relies on a two-stage alternating training strategy. In the first stage, we employ a 3D Artistic Paired Transfer (APT) method for image-guided style transfer. APT constructs paired photo-realistic portraits to obtain accurate artistic poses, which helps ITportrait to achieve high-quality 3D style transfer. In the second stage, we propose a 3D Image-Text Embedding (ITE) approach in the CLIP space. ITE uses a threshold function to adaptively control the optimization direction of image or text in the CLIP space. Comprehensive quantitative and qualitative results show that our ITportrait achieves state-of-the-art (SOTA) results and benefits downstream tasks. All source codes and pre-trained models will be released to the public

An efficient route for electrooxidation of methanol to dimethoxymethane using ionic liquid as electrolyte

An ionic liquid 1-ethyl-3-methyl imidazolium tetrafloroborate (EmimBF4) was found to be highly active for one-pot synthesis of dimethoxymethane (DMM) by electrooxidation of methanol on platinum electrode, exhibiting 34.7% conversion, 96.9% selectivity to DMM, high current efficiency (99.2%) as well. The electrode reaction mechanism was proposed according to the experimental results and reported literature

Describing Strong Correlation with Block-Correlated Coupled Cluster Theory

A block-correlated coupled cluster (BCCC) method based on the generalized valence bond (GVB) wave function (GVB-BCCC in short) is proposed and implemented at the ab initio level, which represents an attractive multireference electronic structure method for strongly correlated systems. The GVB-BCCC method is demonstrated to provide accurate descriptions for multiple bond breaking in small molecules, although the GVB reference function is qualitatively wrong for the studied processes. For a challenging prototype of strongly correlated systems, tridecane with all 12 single C-C bonds at various distances, our calculations have shown that the GVB-BCCC2b method can provide highly comparable results as the density matrix renormalization group method for potential energy surfaces along simultaneous dissociation of all C-C bonds

Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars

3D-aware generative adversarial networks (GANs) synthesize high-fidelity and multi-view-consistent facial images using only collections of single-view 2D imagery. Towards fine-grained control over facial attributes, recent efforts incorporate 3D Morphable Face Model (3DMM) to describe deformation in generative radiance fields either explicitly or implicitly. Explicit methods provide fine-grained expression control but cannot handle topological changes caused by hair and accessories, while implicit ones can model varied topologies but have limited generalization caused by the unconstrained deformation fields. We propose a novel 3D GAN framework for unsupervised learning of generative, high-quality and 3D-consistent facial avatars from unstructured 2D images. To achieve both deformation accuracy and topological flexibility, we propose a 3D representation called Generative Texture-Rasterized Tri-planes. The proposed representation learns Generative Neural Textures on top of parametric mesh templates and then projects them into three orthogonal-viewed feature planes through rasterization, forming a tri-plane feature representation for volume rendering. In this way, we combine both fine-grained expression control of mesh-guided explicit deformation and the flexibility of implicit volumetric representation. We further propose specific modules for modeling mouth interior which is not taken into account by 3DMM. Our method demonstrates state-of-the-art 3D-aware synthesis quality and animation ability through extensive experiments. Furthermore, serving as 3D prior, our animatable 3D representation boosts multiple applications including one-shot facial avatars and 3D-aware stylization.Comment: Project page: https://mrtornado24.github.io/Next3D

Novel methods for reliability study of multi-dimensional non-linear dynamic systems

This research presents two unique techniques for engineering system reliability analysis of multi-dimensional non-linear dynamic structures. First, the structural reliability technique works best for multi-dimensional structural responses that have been either numerically simulated or measured over a long enough length to produce an ergodic time series. Second, a novel extreme value prediction method that can be used in various engineering applications is proposed. In contrast to those currently used in engineering reliability methodologies, the novel method is easy to use, and even a limited amount of data can still be used to obtain robust system failure estimates. As demonstrated in this work, proposed methods also provide accurate confidence bands for system failure levels in the case of real-life measured structural response. Additionally, traditional reliability approaches that deal with time series do not have the benefit of being able to handle a system's high dimensionality and cross-correlation across several dimensions readily. Container ship that experiences significant deck panel pressures and high roll angles when travelling in bad weather was selected as the example for this study. The main concern for ship transportation is the potential loss of cargo owing to violent movements. Simulating such a situation is difficult since waves and ship motions are non-stationary and complicatedly non-linear. Extreme movements greatly enhance the role of nonlinearities, activating effects of second and higher order. Furthermore, laboratory testing may also be called into doubt due to the scale and the choice of the sea state. Therefore, data collected from actual ships during difficult weather journeys offer a unique perspective on the statistics of ship movements. This work aims to benchmark state-of-the-art methods, making it possible to extract necessary information about the extreme response from available on-board measured time histories. Both suggested methods can be used in combination, making them attractive and ready to use for engineers. Methods proposed in this paper open up possibilities to predict simply yet efficiently system failure probability for non-linear multi-dimensional dynamic structure.publishedVersio

DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior

We present DreamCraft3D, a hierarchical 3D content generation method that produces high-fidelity and coherent 3D objects. We tackle the problem by leveraging a 2D reference image to guide the stages of geometry sculpting and texture boosting. A central focus of this work is to address the consistency issue that existing works encounter. To sculpt geometries that render coherently, we perform score distillation sampling via a view-dependent diffusion model. This 3D prior, alongside several training strategies, prioritizes the geometry consistency but compromises the texture fidelity. We further propose Bootstrapped Score Distillation to specifically boost the texture. We train a personalized diffusion model, Dreambooth, on the augmented renderings of the scene, imbuing it with 3D knowledge of the scene being optimized. The score distillation from this 3D-aware diffusion prior provides view-consistent guidance for the scene. Notably, through an alternating optimization of the diffusion prior and 3D scene representation, we achieve mutually reinforcing improvements: the optimized 3D scene aids in training the scene-specific diffusion model, which offers increasingly view-consistent guidance for 3D optimization. The optimization is thus bootstrapped and leads to substantial texture boosting. With tailored 3D priors throughout the hierarchical generation, DreamCraft3D generates coherent 3D objects with photorealistic renderings, advancing the state-of-the-art in 3D content generation. Code available at https://github.com/deepseek-ai/DreamCraft3D.Comment: Project Page: https://mrtornado24.github.io/DreamCraft3D

Efficient orange organic light-emitting diodes employing a central aniline bridged multiresonant thermally activated delayed fluorescence emitter

Funding: S. W. and J. X. W. thank the China Scholarship Council (201906250199, 202006250026) for support. Dianming Sun acknowledges support from the Royal Academy of Engineering Enterprise Fellowship (EF2122-13106). E. Z.-C. thanks the Engineering and Physical Sciences Research Council (EP/W015137/1, EP/W007517/1). X.-H. Z. acknowledges support by the National Natural Science Foundation of China (Grant No. 52130304, 51821002) and the Collaborative Innovation Center of Suzhou Nano Science & Technology.Multiresonant thermally activated delayed fluorescence (MR-TADF) compounds are attractive for use in organic light-emitting diodes as they show narrowband emission, are bright, and can harvest both singlet and triplet excitons for the emission of light. Reflected in the paucity of examples of orange-to-red emitters, developing MR-TADF emitters that emit beyond the green remains an outstanding materials design challenge. In this work, we report one of the first carbonyl-based orange MR-TADF emitters, DDiKTa-A , which is based on the dimerization of the sky-blue emitting DiKTa through a central aniline bridge. DDiKTa-A emits at λPL of 562 nm and has high photoluminescence quantum yield of 92% in 2 wt% doped films in mCP. DDiKTa-A exhibits temperature dependent steady-state photoluminescence in 2-MeTHF, acting as an indirect indicator of the polarity of the medium. The OLEDs with DDiKTa-A showed an EQEmax of 20.3%, but with significant efficiency roll-off (EQE100 of 13.2%). The EQEmax was improved, and the efficiency roll-off mitigated by incorporating an assistant dopant, 4CzIPN, within the emissive layer of the device. The hyperfluorescence device showed an EQEmax of 24.3%, which decreased to 22.5 and 14.6% at 100 and 1000 cd m−2, respectively.Peer reviewe