Multiplicity of solutions for Dirichlet boundary conditions of second-order quasilinear equations with impulsive effects

This paper deals with the multiplicity of solutions for Dirichlet boundary conditions of second-order quasilinear equations with impulsive effects. By using critical point theory, a new result is obtained. An example is given to illustrate the main result

Accelerated Stochastic ADMM with Variance Reduction

Alternating Direction Method of Multipliers (ADMM) is a popular method in solving Machine Learning problems. Stochastic ADMM was firstly proposed in order to reduce the per iteration computational complexity, which is more suitable for big data problems. Recently, variance reduction techniques have been integrated with stochastic ADMM in order to get a fast convergence rate, such as SAG-ADMM and SVRG-ADMM,but the convergence is still suboptimal w.r.t the smoothness constant. In this paper, we propose a new accelerated stochastic ADMM algorithm with variance reduction, which enjoys a faster convergence than all the other stochastic ADMM algorithms. We theoretically analyze its convergence rate and show its dependence on the smoothness constant is optimal. We also empirically validate its effectiveness and show its priority over other stochastic ADMM algorithms

Project external environmental factors affecting project delivery systems selection

Project delivery systems (PDSs) selection is crucial to construction project management success. The matching between construction projects and PDSs is hypersensitive to project external environment. Existing studies on selecting PDSs mainly focus on owner’s and project’s characteristics and attach less attention to project environmental factors. This study, therefore, aims to formally identify key project external environmental factors affecting PDSs selection using a data-driven approach. Key factors are summarized and identified through the granular computing method based on 61 Chinese project samples. Empirical results indicate that four factors including market competitiveness, technology accessibility, material availability, and regulatory impact are critical to PDSs selection. This study extended previous research findings on PDSs selection from a perspective of project external environments. Research conclusions can be used as references underpinning construction owners selecting appropriate PDSs considering project external environmental factors

Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion

This paper presents a 3D generative model that uses diffusion models to automatically generate 3D digital avatars represented as neural radiance fields. A significant challenge in generating such avatars is that the memory and processing costs in 3D are prohibitive for producing the rich details required for high-quality avatars. To tackle this problem we propose the roll-out diffusion network (Rodin), which represents a neural radiance field as multiple 2D feature maps and rolls out these maps into a single 2D feature plane within which we perform 3D-aware diffusion. The Rodin model brings the much-needed computational efficiency while preserving the integrity of diffusion in 3D by using 3D-aware convolution that attends to projected features in the 2D feature plane according to their original relationship in 3D. We also use latent conditioning to orchestrate the feature generation for global coherence, leading to high-fidelity avatars and enabling their semantic editing based on text prompts. Finally, we use hierarchical synthesis to further enhance details. The 3D avatars generated by our model compare favorably with those produced by existing generative techniques. We can generate highly detailed avatars with realistic hairstyles and facial hair like beards. We also demonstrate 3D avatar generation from image or text as well as text-guided editability.Comment: Project Webpage: https://3d-avatar-diffusion.microsoft.com

Genome-Wide Characterization and Analysis of bHLH Transcription Factors Related to Anthocyanin Biosynthesis in Cinnamomum camphora ('Gantong 1')

Cinnamomum camphora is one of the most commonly used tree species in landscaping. Improving its ornamental traits, particularly bark and leaf colors, is one of the key breeding goals. The basic helix-loop-helix (bHLH) transcription factors (TFs) are crucial in controlling anthocyanin biosynthesis in many plants. However, their role in C. camphora remains largely unknown. In this study, we identified 150 bHLH TFs (CcbHLHs) using natural mutant C. camphora 'Gantong 1', which has unusual bark and leaf colors. Phylogenetic analysis revealed that 150 CcbHLHs were divided into 26 subfamilies which shared similar gene structures and conserved motifs. According to the protein homology analysis, we identified four candidate CcbHLHs that were highly conserved compared to the TT8 protein in A. thaliana. These TFs are potentially involved in anthocyanin biosynthesis in C. camphora. RNA-seq analysis revealed specific expression patterns of CcbHLHs in different tissue types. Furthermore, we verified expression patterns of seven CcbHLHs (CcbHLH001, CcbHLH015, CcbHLH017, CcbHLH022, CcbHLH101, CcbHLH118, and CcbHLH134) in various tissue types at different growth stages using qRT-PCR. This study opens a new avenue for subsequent research on anthocyanin biosynthesis regulated by CcbHLH TFs in C. camphora