Situation-Dependent Causal Influence-Based Cooperative Multi-agent Reinforcement Learning

Learning to collaborate has witnessed significant progress in multi-agent reinforcement learning (MARL). However, promoting coordination among agents and enhancing exploration capabilities remain challenges. In multi-agent environments, interactions between agents are limited in specific situations. Effective collaboration between agents thus requires a nuanced understanding of when and how agents' actions influence others. To this end, in this paper, we propose a novel MARL algorithm named Situation-Dependent Causal Influence-Based Cooperative Multi-agent Reinforcement Learning (SCIC), which incorporates a novel Intrinsic reward mechanism based on a new cooperation criterion measured by situation-dependent causal influence among agents. Our approach aims to detect inter-agent causal influences in specific situations based on the criterion using causal intervention and conditional mutual information. This effectively assists agents in exploring states that can positively impact other agents, thus promoting cooperation between agents. The resulting update links coordinated exploration and intrinsic reward distribution, which enhance overall collaboration and performance. Experimental results on various MARL benchmarks demonstrate the superiority of our method compared to state-of-the-art approaches

Dismantling the Black Box: Understanding Consumers\u27 Motivations for the Usage of Live Streaming Shopping Platform

Capturing consumers’ motivations for using the live streaming shopping platform (LSSP) can help guide the optimization of the platform and enhance shopping experience of consumers while watching live videos. Previous studies on user motivation typically explored technical and psychological antecedents of usage by considering the platform holistically. However, this black-box like treatment to the platform blurs the finer-grained details of consumer usage. This study takes a micro-level approach, disassembling the LSSP into 13 representative design features, and refines nine user motivations based on the uses and gratifications theory. Through collecting 237 questionnaires and employing regression analysis, we reveal the nuanced relationship between platform design features and consumer motivations. Our findings show that different design features are driven by distinct motivations, diverging from overall LSSP usage motivations. This research broadens the scope of LSSP studies, improves platform functionality, and offers practical insights for service providers

A global long-term (1981–2000) land surface temperature product for NOAA AVHRR

Land surface temperature (LST) plays an important role in the research of climate change and various land surface processes. Before 2000, global LST products with relatively high temporal and spatial resolutions are scarce, despite a variety of operational satellite LST products. In this study, a global 0.05∘×0.05∘ historical LST product is generated from NOAA advanced very-high-resolution radiometer (AVHRR) data (1981–2000), which includes three data layers: (1) instantaneous LST, a product generated by integrating several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST; and (3) monthly averages of ODC LST. For an assumed maximum uncertainty in emissivity and column water vapor content of 0.04 and 1.0 g cm−2, respectively, evaluated against the simulation dataset, the RF-SWA method has a mean bias error (MBE) of less than 0.10 K and a standard deviation (SD) of 1.10 K. To compensate for the influence of orbital drift on LST, the retrieved RF-SWA LST was normalized with an improved ODC method. The RF-SWA LST were validated with in situ LST from Surface Radiation Budget (SURFRAD) sites and water temperatures obtained from the National Data Buoy Center (NDBC). Against the in situ LST, the RF-SWA LST has a MBE of 0.03 K with a range of −1.59–2.71 K, and SD is 1.18 K with a range of 0.84–2.76 K. Since water temperature only changes slowly, the validation of ODC LST was limited to SURFRAD sites, for which the MBE is 0.54 K with a range of −1.05 to 3.01 K and SD is 3.57 K with a range of 2.34 to 3.69 K, indicating good product accuracy. As global historical datasets, the new AVHRR LST products are useful for filling the gaps in long-term LST data. Furthermore, the new LST products can be used as input to related land surface models and environmental applications. Furthermore, in support of the scientific research community, the datasets are freely available at https://doi.org/10.5281/zenodo.3934354 for RF-SWA LST (Ma et al., 2020a), https://doi.org/10.5281/zenodo.3936627 for ODC LST (Ma et al., 2020c), and https://doi.org/10.5281/zenodo.3936641 for monthly averaged LST (Ma et al., 2020b)

Cordia subcordata (Boraginaceae), a distylous species on oceanic coral islands, is self-compatible and pollinated by a passerine bird

Background and aims – Distyly is usually rare on oceanic islands, which is probably due to the difficulty for distylous plants to colonize those islands. However, Cordia subcordata was observed to be distylous with short- and long-styled morphs on the Xisha Islands in the South China Sea. To characterize the reproduction system of Cordia subcordata and to understand how this distylous species maintains itself on these islands, we studied its reproductive and pollination biology.Methods – Seed set and pollen tube growth under manipulated intermorph, intramorph, and self-pollination were examined to investigate self-incompatibility in the species. The number of pollen grains deposited on the stigmas after a single pollinator visit were counted to investigate the pollination efficiency of different visitors. Key results – Our study indicated that Cordia subcordata shows reciprocal herkogamy as is typical in distylous species. Pollen tubes could reach the base of the style and move into the ovules under all the manipulated pollination treatments in both morphs. Seed set resulting from four hand-pollination experiments did not show any differences between both morphs, suggesting that Cordia subcordata lacks heterostylous self-incompatibility. The most frequent flower visitors, Zosterops japonicus and Apis cerana, were observed foraging on the large volumes of nectar and pollen grains, respectively, with Zosterops japonicus being the most effective pollinator, depositing large number of pollen grains on the stigmas during their visits.Conclusions – Our findings show that Cordia subcordata established itself and persists in the archipelago by producing fruits through a combination of self-compatibility and pollination by the most common passerine bird on the oceanic islands

Profile of immunoglobulin G N-glycome in COVID-19 patients: A case-control study

Coronavirus disease 2019 (COVID-19) remains a major health challenge globally. Previous studies have suggested that changes in the glycosylation of IgG are closely associated with the severity of COVID-19. This study aimed to compare the profiles of IgG N-glycome between COVID-19 patients and healthy controls. A case-control study was conducted, in which 104 COVID-19 patients and 104 age- and sex-matched healthy individuals were recruited. Serum IgG N-glycome composition was analyzed by hydrophilic interaction liquid chromatography with the ultra-high-performance liquid chromatography (HILIC-UPLC) approach. COVID-19 patients have a decreased level of IgG fucosylation, which upregulates antibody-dependent cell cytotoxicity (ADCC) in acute immune responses. In severe cases, a low level of IgG sialylation contributes to the ADCC-regulated enhancement of inflammatory cytokines. The decreases in sialylation and galactosylation play a role in COVID-19 pathogenesis via the activation of the lectin-initiated alternative complement pathway. IgG N-glycosylation underlines the complex clinical phenotypes of SARS-CoV-2 infection