Scalable Continuous-time Diffusion Framework for Network Inference and Influence Estimation

The study of continuous-time information diffusion has been an important area of research for many applications in recent years. When only the diffusion traces (cascades) are accessible, cascade-based network inference and influence estimation are two essential problems to explore. Alas, existing methods exhibit limited capability to infer and process networks with more than a few thousand nodes, suffering from scalability issues. In this paper, we view the diffusion process as a continuous-time dynamical system, based on which we establish a continuous-time diffusion model. Subsequently, we instantiate the model to a scalable and effective framework (FIM) to approximate the diffusion propagation from available cascades, thereby inferring the underlying network structure. Furthermore, we undertake an analysis of the approximation error of FIM for network inference. To achieve the desired scalability for influence estimation, we devise an advanced sampling technique and significantly boost the efficiency. We also quantify the effect of the approximation error on influence estimation theoretically. Experimental results showcase the effectiveness and superior scalability of FIM on network inference and influence estimation

Nearest Neighbor Machine Translation is Meta-Optimizer on Output Projection Layer

Nearest Neighbor Machine Translation ($k$NN-MT) has achieved great success in domain adaptation tasks by integrating pre-trained Neural Machine Translation (NMT) models with domain-specific token-level retrieval. However, the reasons underlying its success have not been thoroughly investigated. In this paper, we comprehensively analyze $k$NN-MT through theoretical and empirical studies. Initially, we provide new insights into the working mechanism of $k$NN-MT as an efficient technique to implicitly execute gradient descent on the output projection layer of NMT, indicating that it is a specific case of model fine-tuning. Subsequently, we conduct multi-domain experiments and word-level analysis to examine the differences in performance between $k$NN-MT and entire-model fine-tuning. Our findings suggest that: (1) Incorporating $k$NN-MT with adapters yields comparable translation performance to fine-tuning on in-domain test sets, while achieving better performance on out-of-domain test sets; (2) Fine-tuning significantly outperforms $k$NN-MT on the recall of in-domain low-frequency words, but this gap could be bridged by optimizing the context representations with additional adapter layers.Comment: Accepted by EMNLP202

OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control

In this work, we introduce OmniDrones, an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a bottom-up design approach that allows users to easily design and experiment with various application scenarios on top of GPU-parallelized simulations. It also offers a range of benchmark tasks, presenting challenges ranging from single-drone hovering to over-actuated system tracking. In summary, we propose an open-sourced drone simulation platform, equipped with an extensive suite of tools for drone learning. It includes 4 drone models, 5 sensor modalities, 4 control modes, over 10 benchmark tasks, and a selection of widely used RL baselines. To showcase the capabilities of OmniDrones and to support future research, we also provide preliminary results on these benchmark tasks. We hope this platform will encourage further studies on applying RL to practical drone systems.Comment: Submitted to IEEE RA-

Gains and losses from collusion: an empirical study on market behaviors of China’s power enterprises

Purpose: Collusion is a common behavior of oligarch enterprises aiming to get an advantage in market competition. The purpose of the research is to explore positive or negative effects from the electricity generation manufacturers’ collusion through statistical analysis approach. To be exact, these effects are discovered both in market economy at a macro-economic level and in enterprise behaviors at a micro-economic level. Design/methodology/approach: This research designs a model as an extension of Porter’s model (Green & Porter, 1984). In this model FIML is applied. Taking price bidding project launched in China’s power industry as an example, this paper conducts an empirical research on its relevant price data collected from subordinate power plants of China’s five power generation groups in the pilots. Findings: It is found in this paper that power generation enterprises are facing collusion issues in the market. To be exact, it is such a situation in which non-cooperative competition and collusion alternate. Under the competition, market is relatively steady, thus forming a lower network price. It is helpful to the development of the whole industry. However, once Cartel is formed, the price will rise and clash with power enterprises and transmission-distribution companies concerning the interests conflicts. At the same time, a higher power price will form in the market, making consumers suffer losses. All of these are bad for industry development. Not only the collusion of power enterprises affects power price but also the market power that caused by long-time Cartel will reduce the market entrant in electricity generation. Market resources are centralized in the hands of Cartel, causing a low effective competition in the market, which has passive effects on users. Implications: The empirical research also indicates that collusion undoubtedly benefits the power enterprises that involved. As a cooperation pattern, collusion can lead to the synergy between relevant companies. However, collusion harms the benefits of other market entities. During the process of enterprises creating common interests cooperatively, collusion may bring harm to the outside industry. Originality/value: Using empirical research method, the paper takes China’s power industry as an example to show the gains and losses of collusion from two aspects, namely market economy and strategic management.Peer Reviewe

Assessing the Inbound Tourism Efficiency of European Countries in China: 2006-2019

Assessing inbound tourism efficiency helps to understand the potential levels and constraints of inbound tourism flows. In this study, 35 European countries and China were selected as samples and influencing factors oftourism efficiency were constructed within the gravity model (GM) and stochastic frontier analysis (SFA). Taking into account individual heterogeneity, a true fixed-effects stochastic frontier gravity model (TFE-SFA-GM) was developed and empirically analysed using data from 2006 to 2019. The results show that (1) the inbound tourism efficiency of European countries in China is jointly affected by many core factors, such as economic scale, geographic distance, and population size on both sides; (2) the inefficiency factors that affect the inbound tourism efficiency of European countries in China are diversified;(3) the inbound tourism efficiency of European countries in China generally shows an upward trend during the sample period, but there are significant differences in the gap between the frontier level of inbound tourism flow in China and the actual inbound tourism flow. These findings imply that to better attract European tourists, China must continue to maintain and strengthen economic and trade relations with European countries, create a favourable security environment for tourism, highlight the integration of international tourism resources with Chinese culture, and continue to promote them in Europ

Targeting HMGB1 in endothelial cells reverses heme-induced SIRS after radiofrequency ablation of hepatic hemangioma

BackgroundAlthough radiofrequency ablation (RFA) is a safe and effective treatment for hepatic hemangiomas, post-RFA systemic inflammatory response syndrome (SIRS) frequently occurs. The role of high-mobility group box 1 (HMGB1) in endothelial cell pyroptosis and SIRS induction following RFA in hepatic hemangiomas remains unexplored.MethodsIn vitro, the levels of interleukin (IL)-1β, IL-18, and pyroptosis markers, such as GSDMD-N and Casp1 p20, were measured in human umbilical vein endothelial cells (HUVECs) after heme administration. In vivo, an orthotopic liver hemangioma mouse model was established, and RFA was performed to evaluate the levels of IL-1β and IL-18, wet-to-dry lung ratio, and inflammation score. In addition, hemopexin and glycyrrhizin were used to investigate the impact of HMGB1 on heme-induced SIRS post-RFA in hepatic hemangioma mice.ResultsHeme induced elevated levels of IL-1β and IL-18, endothelial cell death in vitro, and increased wet-to-dry lung ratio and inflammation score in vivo. These effects were rescued with the administration of heme-binding protein hemopexin, indicating the role of heme in inducing SIRS and pyroptosis post-RFA of hepatic hemangioma. HMGB1 participates in heme-induced SIRS in mice by regulating HMGB1/nod-like receptor family pyrin domain-containing 3 (NLRP3) pathway through reactive oxygen species (ROS). Treatment with hemopexin or the HMGB1 inhibitor glycyrrhizin reversed heme-induced SIRS after RFA of hepatic hemangioma in mice.ConclusionsCollectively, we demonstrated that heme induces SIRS through the ROS/HMGB1/NLRP3 pathway-regulated endothelial cell pyroptosis in mice, and hemopexin, a heme scavenger, and glycyrrhizin, a HMGB1 inhibitor, may be the potential strategies for further study for SIRS following the RFA of hepatic hemangioma for the first time

Mitochondrial stress response and myogenic differentiation

Regeneration and repair are prerequisites for maintaining effective function of skeletal muscle under high energy demands, and myogenic differentiation is one of the key steps in the regeneration and repair process. A striking feature of the process of myogenic differentiation is the alteration of mitochondria in number and function. Mitochondrial dysfunction can activate a number of transcriptional, translational and post-translational programmes and pathways to maintain cellular homeostasis under different types and degrees of stress, either through its own signaling or through constant signaling interactions with the nucleus and cytoplasm, a process known as the mitochondrial stress responses (MSRs). It is now believed that mitochondrial dysfunction is closely associated with a variety of muscle diseases caused by reduced levels of myogenic differentiation, suggesting the possibility that MSRs are involved in messaging during myogenic differentiation. Also, MSRs may be involved in myogenesis by promoting bioenergetic remodeling and assisting myoblast survival during myogenic differentiation. In this review, we will take MSRs as an entry point to explore its concrete regulatory mechanisms during myogenic differentiation, with a perspective to provide a theoretical basis for the treatment and repair of related muscle diseases

USP29-mediated HIF1α stabilization is associated with Sorafenib resistance of hepatocellular carcinoma cells by upregulating glycolysis

Understanding the mechanisms underlying evasive resistance in cancer is an unmet medical need to improve the efficacy of current therapies. In hepatocellular carcinoma (HCC), aberrant expression of hypoxia-inducible factor 1 α (HIF1α) and increased aerobic glycolysis metabolism are drivers of resistance to therapy with the multi-kinase inhibitor Sorafenib. However, it has remained unknown how HIF1α is activated and how its activity and the subsequent induction of aerobic glycolysis promote Sorafenib resistance in HCC. Here, we report the ubiquitin-specific peptidase USP29 as a new regulator of HIF1α and of aerobic glycolysis during the development of Sorafenib resistance in HCC. In particular, we identified USP29 as a critical deubiquitylase (DUB) of HIF1α, which directly deubiquitylates and stabilizes HIF1α and, thus, promotes its transcriptional activity. Among the transcriptional targets of HIF1α is the gene encoding hexokinase 2 (HK2), a key enzyme of the glycolytic pathway. The absence of USP29, and thus of HIF1α transcriptional activity, reduces the levels of aerobic glycolysis and restores sensitivity to Sorafenib in Sorafenib-resistant HCC cells in vitro and in xenograft transplantation mouse models in vivo. Notably, the absence of USP29 and high HK2 expression levels correlate with the response of HCC patients to Sorafenib therapy. Together, the data demonstrate that, as a DUB of HIF1α, USP29 promotes Sorafenib resistance in HCC cells, in parts by upregulating glycolysis, thereby opening new avenues for therapeutically targeting Sorafenib-resistant HCC in patients