Hardware-in-the-Loop Simulation for Spacecraft Formation Flying

This paper presents a hardware-in-the-loop (HITL) simulation approach for multiple spacecraft formation flying. Considering a leader-follower formation flying configuration, a Fuzzy Logic controller is developed first to maintain the desired formation shape under external perturbations and the initial position offsets. Cold-gas on/off thrusters are developed to be introduced to the simulation loop, and the HITL simulations are conducted to validate the effectiveness of the proposed simulation configuration and Fuzzy Logic control

Application of Ghost-DeblurGAN to Fiducial Marker Detection

Feature extraction or localization based on the fiducial marker could fail due to motion blur in real-world robotic applications. To solve this problem, a lightweight generative adversarial network, named Ghost-DeblurGAN, for real-time motion deblurring is developed in this paper. Furthermore, on account that there is no existing deblurring benchmark for such task, a new large-scale dataset, YorkTag, is proposed that provides pairs of sharp/blurred images containing fiducial markers. With the proposed model trained and tested on YorkTag, it is demonstrated that when applied along with fiducial marker systems to motion-blurred images, Ghost-DeblurGAN improves the marker detection significantly. The datasets and codes used in this paper are available at: https://github.com/York-SDCNLab/Ghost-DeblurGAN.Comment: 6 pages, 6 figure

Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems

This paper studies the robust bipartite consensus problems for heterogeneous nonlinear nonaffine discrete-time multi-agent systems (MASs) with fixed and switching topologies against data dropout and unknown disturbances. At first, the controlled system's virtual linear data model is developed by employing the pseudo partial derivative technique, and a distributed combined measurement error function is established utilizing a signed graph theory. Then, an input gain compensation scheme is formulated to mitigate the effects of data dropout in both feedback and forward channels. Moreover, a data-driven learning-based robust bipartite consensus control (LRBCC) scheme based on a radial basis function neural network observer is proposed to estimate the unknown disturbance, using the online input/output data without requiring any information on the mathematical dynamics. The stability analysis of the proposed LRBCC approach is given. Simulation and hardware testing also illustrate the correctness and effectiveness of the designed method

Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks

This paper studies fully distributed data-driven problems for nonlinear discrete-time multi-agent systems (MASs) with fixed and switching topologies preventing injection attacks. We first develop an enhanced compact form dynamic linearization model by applying the designed distributed bipartite combined measurement error function of the MASs. Then, a fully distributed event-triggered bipartite consensus (DETBC) framework is designed, where the dynamics information of MASs is no longer needed. Meanwhile, the restriction of the topology of the proposed DETBC method is further relieved. To prevent the MASs from injection attacks, neural network-based detection and compensation schemes are developed. Rigorous convergence proof is presented that the bipartite consensus error is ultimately boundedness. Finally, the effectiveness of the designed method is verified through simulations and experiment

Integrated Serum and Fecal Metabolomics Study of Collagen-Induced Arthritis Rats and the Therapeutic Effects of the Zushima Tablet

The Zushima tablet (ZT) has been used for decades in the clinical treatment of rheumatoid arthritis (RA) in China. However, its therapeutic mechanism is unclear. In this study, we aimed to explore the distinctive metabolic patterns in collagen-induced arthritis (CIA) rats and evaluate the therapeutic effects of ZT on RA using untargeted serum and fecal metabolomics approaches based on gas chromatography coupled with mass spectrometry. Body weight, hind paw swelling, TNF-α and IL-1β levels, arthritis scores, and histopathological parameters were assessed. In the metabolomics study, 31 altered metabolites in the serum and 30 in the feces were identified by comparing the model with the control group using statistical processing. These altered metabolites revealed that the tricarboxylic acid cycle, glycolysis metabolism, fatty acid metabolism, and purine metabolism were disturbed in CIA rats, and most of these altered metabolites including l-isoleucine, l-aspartic acid, pyruvic acid, cholic acid, and hypoxanthine, were rectified by ZT. Furthermore, short-chain fatty acids in feces were quantitatively determined, and the results showed that ZT could regulate the levels of propionate, butyrate, and valerate in CIA rats. Then, gut microbiota were analyzed by 16S rRNA analysis. Our results showed that Firmicutes and Bacteroidetes were the most abundant bacteria in rats. The levels of 19 types of bacteria at the family level were altered in RA rats, and most of them could be regulated by ZT. This study demonstrated that metabolomics analysis is a powerful tool for providing novel insight into RA and for elucidating the potential mechanism of ZT

Sharing tableware reduces waste generation, emissions and water consumption in China’s takeaway packaging waste dilemma

China has a rapidly growing online food delivery and takeaway market, serving 406 million customers with 10.0 billion orders and generating 323kilotonnes of tableware and packaging waste in 2018. Here we use a top-down approach with city-level takeaway order data to explore the packaging waste and life-cycle environmental impacts of the takeaway industry in China. The ten most wasteful cities, with just 7% of the population, in terms of per capita waste generation, were responsible for 30% of the country's takeaway waste, 27-34% of the country's pollutant emissions and 30% of the country's water consumption. We defined one paper substitution and two sharing tableware scenarios to simulate the environmental mitigation potentials. The results of the scenario simulations show that sharing tableware could reduce waste generation by up to 92%, and environmental emissions and water consumption by more than two-thirds. Such a mechanism provides a potential solution to address the food packaging waste dilemma and a new strategy for promoting sustainable and zero-waste lifestyles. The online food delivery and takeaway market is growing in China, serving 406 million customers with 10.0 billion orders in 2018. Here, data from an online food delivery platform, life-cycle environmental impacts of packaging and tableware waste generated across 353 cities in China, and scenarios for paper alternatives and tableware sharing are presented

The Last Decade in Review: Tracing the Evolution of Safety Assurance Cases through a Comprehensive Bibliometric Analysis

Safety assurance is of paramount importance across various domains, including automotive, aerospace, and nuclear energy, where the reliability and acceptability of mission-critical systems are imperative. This assurance is effectively realized through the utilization of Safety Assurance Cases. The use of safety assurance cases allows for verifying the correctness of the created systems capabilities, preventing system failure. The latter may result in loss of life, severe injuries, large-scale environmental damage, property destruction, and major economic loss. Still, the emergence of complex technologies such as cyber-physical systems (CPSs), characterized by their heterogeneity, autonomy, machine learning capabilities, and the uncertainty of their operational environments poses significant challenges for safety assurance activities. Several papers have tried to propose solutions to tackle these challenges, but to the best of our knowledge, no secondary study investigates the trends, patterns, and relationships characterizing the safety case scientific literature. This makes it difficult to have a holistic view of the safety case landscape and to identify the most promising future research directions. In this paper, we, therefore, rely on state-of-the-art bibliometric tools(e.g., VosViewer) to conduct a bibliometric analysis that allows us to generate valuable insights, identify key authors and venues, and gain a birds eye view of the current state of research in the safety assurance area. By revealing knowledge gaps and highlighting potential avenues for future research, our analysis provides an essential foundation for researchers, corporate safety analysts, and regulators seeking to embrace or enhance safety practices that align with their specific needs and objectives

Polymeric Nanoparticles Amenable to Simultaneous Installation of Exterior Targeting and Interior Therapeutic Proteins

Effective delivery of therapeutic proteins is a formidable challenge. Herein, using a unique polymer family with a wide-ranging set of cationic and hydrophobic features, we developed a novel nanoparticle (NP) platform capable of installing protein ligands on the particle surface and simultaneously carrying therapeutic proteins inside by a self-assembly procedure. The loaded therapeutic proteins (e.g., insulin) within the NPs exhibited sustained and tunable release, while the surface-coated protein ligands (e.g., transferrin) were demonstrated to alter the NP cellular behaviors. In vivo results revealed that the transferrin-coated NPs can effectively be transported across the intestinal epithelium for oral insulin delivery, leading to a notable hypoglycemic response.National Institutes of Health (U.S.) (Grants EB015419, R00CA160350, and CA151884)Prostate Cancer Foundation (Challenge Award)National Research Foundation of Korea (Grant K1A1A2048701)David H. Koch Institute for Integrative Cancer Research at MIT. Prostate Cancer Foundation Program in Cancer NanotherapeuticsNational Natural Science Foundation (China) (Grant 81173010

PD-1hi CD8+ resident memory T cells balance immunity and fibrotic sequelae

CD8+ tissue-resident memory T (TRM) cells provide frontline immunity in mucosal tissues. The mechanisms regulating CD8+ TRM maintenance, heterogeneity, and protective and pathological functions are largely elusive. Here, we identify a population of CD8+ TRM cells that is maintained by major histocompatibility complex class I (MHC-I) signaling, and CD80 and CD86 costimulation after acute influenza infection. These TRM cells have both exhausted-like phenotypes and memory features and provide heterologous immunity against secondary infection. PD-L1 blockade after the resolution of primary infection promotes the rejuvenation of these exhausted-like TRM cells, restoring protective immunity at the cost of promoting postinfection inflammatory and fibrotic sequelae. Thus, PD-1 serves to limit the pathogenic capacity of exhausted-like TRM cells at the memory phase. Our data indicate that TRM cell exhaustion is the result of a tissue-specific cellular adaptation that balances fibrotic sequelae with protective immunity