Games on graphs: A minor modification of payoff scheme makes a big difference

Various social dilemma games that follow different strategy updating rules have been studied on many networks.The reported results span the entire spectrum, from significantly boosting,to marginally affecting,to seriously decreasing the level of cooperation.Experimental results that are qualitatively different from theoretical prediction have also been reported.It is widely believed that the results are largely determined by three elements,including payoff matrices of the underlying 2*2 games,the way that the strategic states of the players are updated and the structure of the networks.Here we discuss the impact of a seemly non-essential mechanism -- what we refer to as a "payoff scheme". Specifically, in each round after the states of all of the players are determined,the payoff scheme is how each player's payoff is calculated.In addition to the two conventions in which either the accumulated or the averaged payoff is calculated from playing with all of the neighboring players,we here study the effects of calculating the payoff from pairing up with one random player from among the neighboring players. Based on probability theory, in a situation of uncorrelated events, the average payoff that involves all of the neighbors should,in principal,be equivalent to the payoff from pairing up with one neighbor.However,our simulation of games on graphs shows that, in many cases,the two payoff schemes lead to qualitatively different levels of cooperation.This finding appears to provide a possible explanation for a wide spectrum of observed behaviors in the literature.We have also observed that results from the randomly-pairing-one mechanism are more robust than the involving-all-neighbours mechanism because,in the former case, neither the other three main elements nor the initial states of the players have a large impact on the final level of cooperation compared with in the latter case.Comment: 23 pages,171 figure

CGOF++: Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions, textures, and poses of the generated face images. However, previous methods focus on controllable 2D image generative models, which are prone to producing inconsistent face images under large expression and pose changes. In this paper, we propose a new NeRF-based conditional 3D face synthesis framework, which enables 3D controllability over the generated face images by imposing explicit 3D conditions from 3D face priors. At its core is a conditional Generative Occupancy Field (cGOF++) that effectively enforces the shape of the generated face to conform to a given 3D Morphable Model (3DMM) mesh, built on top of EG3D [1], a recent tri-plane-based generative model. To achieve accurate control over fine-grained 3D face shapes of the synthesized images, we additionally incorporate a 3D landmark loss as well as a volume warping loss into our synthesis framework. Experiments validate the effectiveness of the proposed method, which is able to generate high-fidelity face images and shows more precise 3D controllability than state-of-the-art 2D-based controllable face synthesis methods.Comment: This article is an extension of the NeurIPS'22 paper arXiv:2206.0836

Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions, textures, and poses of the generated face images. However, these methods focus on 2D image generative models, which are prone to producing inconsistent face images under large expression and pose changes. In this paper, we propose a new NeRF-based conditional 3D face synthesis framework, which enables 3D controllability over the generated face images by imposing explicit 3D conditions from 3D face priors. At its core is a conditional Generative Occupancy Field (cGOF) that effectively enforces the shape of the generated face to commit to a given 3D Morphable Model (3DMM) mesh. To achieve accurate control over fine-grained 3D face shapes of the synthesized image, we additionally incorporate a 3D landmark loss as well as a volume warping loss into our synthesis algorithm. Experiments validate the effectiveness of the proposed method, which is able to generate high-fidelity face images and shows more precise 3D controllability than state-of-the-art 2D-based controllable face synthesis methods. Find code and demo at https://keqiangsun.github.io/projects/cgof

Variaciones espaciales de las condiciones climáticas en el cultivo de la vid en China

En este TFM se realizó un análisis del cultivo de la uva en China, comenzando por el estudio de la distribución de las principales áreas productoras de uva, sus producciones y destino, y a continuación las condiciones del clima mediante el balance de agua en el suelo determinando los periodos de excedente de agua y déficit.El cultivo de uva en China ocupa cientos de miles de hectáreas y miles de personas con unas producciones destinadas a su consumo directo o producción de vino.Las áreas de cultivo se localizan en zonas muy diversas del país y con condiciones muy diferentes. El estudio de los balances de agua en el suelo tras estudiar y calcular los valores de evapotranspiración potencial, muestra qué áreas tienen mejores y peores condiciones desde el punto de vista del clima que se deberían tener en cuanta si se desea ampliar las zonas de cultivo.<br /

Antibody-drug conjugates in urinary tumors: clinical application, challenge, and perspectives

Urinary tumors primarily consist of kidney, urothelial, and prostate malignancies, which pose significant treatment challenges, particularly in advanced stages. Antibody-drug conjugates (ADCs) have emerged as a promising therapeutic approach, combining monoclonal antibody specificity with cytotoxic chemotherapeutic payloads. This review highlights recent advancements, opportunities, and challenges in ADC application for urinary tumors. We discuss the FDA-approved ADCs and other novel ADCs under investigation, emphasizing their potential to improve patient outcomes. Furthermore, we explore strategies to address challenges, such as toxicity management, predictive biomarker identification, and resistance mechanisms. Additionally, we examine the integration of ADCs with other treatment modalities, including immune checkpoint inhibitors, targeted therapies, and radiation therapy. By addressing these challenges and exploring innovative approaches, the development of ADCs may significantly enhance therapeutic options and outcomes for patients with advanced urinary tumor

10-qubit entanglement and parallel logic operations with a superconducting circuit

Here we report on the production and tomography of genuinely entangled Greenberger-Horne-Zeilinger states with up to 10 qubits connecting to a bus resonator in a superconducting circuit, where the resonator-mediated qubit-qubit interactions are used to controllably entangle multiple qubits and to operate on different pairs of qubits in parallel. The resulting 10-qubit density matrix is unambiguously probed, with a fidelity of $0.668 \pm 0.025$. Our results demonstrate the largest entanglement created so far in solid-state architectures, and pave the way to large-scale quantum computation.Comment: Revised version with 16 pages, 13 figures, and 2 table

Overexpression of RRM2 decreases thrombspondin-1 and increases VEGF production in human cancer cells in vitro and in vivo: implication of RRM2 in angiogenesis

<p>Abstract</p> <p>Background</p> <p>In addition to its essential role in ribonucleotide reduction, ribonucleotide reductase (RNR) small subunit, RRM2, has been known to play a critical role in determining tumor malignancy. Overexpression of RRM2 significantly enhances the invasive and metastatic potential of tumor. Angiogenesis is critical to tumor malignancy; it plays an essential role in tumor growth and metastasis. It is important to investigate whether the angiogenic potential of tumor is affected by RRM2.</p> <p>Results</p> <p>We examined the expression of antiangiogenic thrombospondin-1 (TSP-1) and proangiogenic vascular endothelial growth factor (VEGF) in two RRM2-overexpressing KB cells: KB-M2-D and KB-HURs. We found that TSP-1 was significantly decreased in both KB-M2-D and KB-HURs cells compared to the parental KB and mock transfected KB-V. Simultaneously, RRM2-overexpressing KB cells showed increased production of VEGF mRNA and protein. In contrast, attenuating RRM2 expression via siRNA resulted in a significant increased TSP-1 expression in both KB and LNCaP cells; while the expression of VEGF by the two cells was significantly decreased under both normoxia and hypoxia. In comparison with KB-V, overexpression of RRM2 had no significant effect on proliferation in vitro, but it dramatically accelerated in vivo subcutaneous growth of KB-M2-D. KB-M2-D possessed more angiogenic potential than KB-V, as shown in vitro by its increased chemotaxis for endothelial cells and in vivo by the generation of more vascularized tumor xenografts.</p> <p>Conclusion</p> <p>These findings suggest a positive role of RRM2 in tumor angiogenesis and growth through regulation of the expression of TSP-1 and VEGF.</p