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Periodic anode purges can remove excessive liquid water and nitrogen in the anode to mitigate hydrogen starvation in PEMFCs caused by flooding and nitrogen buildup. Experiments were conducted on a vehicular PEMFC stack to evaluate influences of operating conditions including current density, cathode flowrate, hydrogen recirculation and working pressures on performance decline during operations with anode purges. The accumulation of anode impurities was characterized by voltage decrease, voltage uniformity and anode pressure swing. The results reveal that anode flooding develops greatly with increasing current density. An optimal hydrogen recirculation pump speed of 1000 rpm substantially improves voltage stability and uniformity of the stack. High cathode pressure accelerates the impurity accumulation in the anode, while high anode pressure facilitates the removal of nitrogen. When the stack works with a constant pressure difference of 10–20 kPa between two electrodes, nitrogen buildup in the anode can be minimized and flooding becomes the primary contributor to performance decline under automotive operating conditions. As current density rises to 300–700 mA/cm2, the optimal pressure difference increases from 10.2 to 14.7 kPa. • An optimal recirculation rate greatly improves voltage stability and uniformity. • Anode nitrogen buildup can be minimized with a constant pressure difference. • The optimal pressure difference rises with the increase of current density. • Pressure swing at anode inlet reflects flooding development in the anode. [ABSTRACT FROM AUTHOR]

Feedback loops between strategies and the environment are commonly observed in socio-ecological, evolution-ecological, and psychology-economic systems. However, the impact of mutations in these feedback processes is often overlooked. This study proposes a novel model that integrates the public goods game with environmental feedback, considering the presence of mutations. In our model, the enhancement factor of the public goods game combines positive and negative incentives from the environment. By employing replicator–mutator (RM) equations, we provide an objective understanding of the system's evolutionary state, focusing on identifying conditions that foster cooperation and prevent the tragedy of the commons. Specifically, mutations play a crucial role in the RM dynamics, leading to the emergence of an oscillatory tragedy of the commons. By verifying the Hopf bifurcation condition, we establish the existence of a stable limit cycle, providing valuable insights into sustained oscillation strategies. Moreover, the feedback mechanism inherent in the public goods game model offers a fresh perspective on effectively addressing the classic dilemma of the tragedy of the commons. [ABSTRACT FROM AUTHOR]

Complex networks are widespread in real-world environments across diverse domains. Real-world networks tend to form spontaneously through interactions between individual agents. Inspired by this, we design an evolutionary game model in which agents participate in a prisoner's dilemma game (PDG) with their neighboring agents. Agents can autonomously modify their connections with neighbors using reinforcement learning to avoid unfavorable environments. Interestingly, our findings reveal some remarkable results. Exploiting reinforcement learning-based adaptive networks improves cooperation when juxtaposed with existing PDGs performed on homogeneous networks. At the same time, the network's topology evolves from homogeneous to heterogeneous states. This change occurs as players gain experience from past games and become more astute in deciding whether to join PDGs with their current neighbors or disconnect from the least profitable neighbors. Instead, they seek out more favorable environments by establishing connections with second-order neighbors with higher rewards. By calculating the degree distribution and modularity of the adaptive network in a steady state, we confirm that the adaptive network follows a power law and has a clear community structure, indicating that the adaptive network is similar to networks in the real world. Our study reports a new phenomenon in evolutionary game theory on networks. It proposes a new perspective to generate scale-free networks, which is generating scale-free networks by the evolution of homogeneous networks rather than typical ways of network growth and preferential connection. Our results provide new aspects to understanding the network structure, the emergence of cooperation, and the behavior of actors in nature and society. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to study how a decision-making rule for vaccination can affect epidemic spreading by exploiting the Bush–Mosteller (BM) model, one of the methodologies in reinforcement learning in artificial intelligence (AI), which can realize the systematic process of learning in humans, on complex networks. We consider the BM model with two stages—vaccination and epidemiological processes—and address two independent rules about fixed loss consideration and average payoff of neighbors to update agent's vaccination behavior for various stimuli, such as loss of payoffs and environments during the vaccination process. Higher sensitivity not only favors higher vaccination coverage rates but also delays the transition point in relative vaccination costs when transitioning from full vaccination (inoculation level 1) to incomplete vaccination (inoculation level less than 1). Extensive numerical simulations demonstrate that the vaccination dilemma can be overcome to some extent, and the distribution of the intended vaccination probabilities in both independent rules is either normal or skewed when different parameters are considered. Since AI is contributing to many fields, we expect that our BM-empowered learning can ultimately resolve the vaccination dilemma. [ABSTRACT FROM AUTHOR]

COVID-19 has brought a great challenge to the medical system. A key scientific question is how to make a balance between home quarantine and staying in the hospital. To this end, we propose a game-based susceptible-exposed-asymptomatic -symptomatic- hospitalized-recovery-dead model to reveal such a situation. In this new framework, time-varying cure rate and mortality are employed and a parameter m is introduced to regulate the probability that individuals are willing to go to the hospital. Through extensive simulations, we find that (1) for low transmission rates (β < 0.2), the high value of m (the willingness to stay in the hospital) indicates the full use of medical resources, and thus the pandemic can be easily contained; (2) for high transmission rates (β > 0.2), large values of m lead to breakdown of the healthcare system, which will further increase the cumulative number of confirmed cases and death cases. Finally, we conduct the empirical analysis using the data from Japan and other typical countries to illustrate the proposed model and to test how our model explains reality. [ABSTRACT FROM AUTHOR]

Recognizing surrounding situations, such as enemy attacks, which can be realized by predator–prey relationships, is one of the common behaviors of the population in ecosystems. In this paper, we explore the relationship between such species' behavior and biodiversity in the spatial rock–paper–scissors game by employing the ecological concept "vigilance." In order to describe the vigilance process, we adopt a multiplex structure where two distinct layers describe virtual and physical interactions. By investigating the process of evolution in species, we also found that species with different vigilance go together. In addition, by utilizing the dynamic time warping method, we found that species with the same vigilance have consistent behavior, but species with different vigilance have diverse behavior. Our findings may lead to broader interpretations of mechanisms promoting biodiversity via vigilance in species ecosystems. [ABSTRACT FROM AUTHOR]

We investigate evolving dynamics of cyclically competing species on spatially extended systems with considering a specific region, which is called the "wildlife refuge," one of the institutional ways to preserve species biodiversity. Through Monte-Carlo simulations, we found that the refuge can play not groundbreaking but an important role in species survival. Species coexistence is maintained at a moderate mobility regime, which traditionally leads to the collapse of coexistence, and eventually, the extinction is postponed depending on the competition rate rather than the portion of the refuge. Incorporating the extinction probability and Fourier transform supported our results in both stochastic and analogous ways. Our findings may provide valuable evidence to assist fields of ecological/biological sciences in understanding the presence and construction of refuges for wildlife with associated effects on species biodiversity. [ABSTRACT FROM AUTHOR]

Recognizing territories is essential to decide behavior of population either human or animals, and interaction between groups or individuals according to the territorial awareness is universal. Understanding various mechanisms which affect on such species behaviors can be possible by evolutionary games, and in particular, the rock–paper–scissors (RPS) game has been played a key role as a paradigmatic model to explore biodiversity from microbiota to societies. Among paramount mechanisms in systems of RPS, the role of intraspecific interaction has been recently noted in terms of promoting biodiversity. Since intraspecific interaction is defined by an invasive reaction between individuals in the same group, the interaction may be also sensitive to the territorial awareness. To explore how territorial awareness-based intraspecific interaction can affect species biodiversity, we endow species with the mechanism in the classic RPS game. By means of the Monte-Carlo method, we find the phenomenon that the presence of species' territorial awareness has an impact on intraspecific interaction which ultimately affects species biodiversity. At the same time, we also find that territorial awareness can play a significant role to the average waiting time for extinction which is numerically elucidated by exploiting the quantity: interface width statistic. Unlike prior research that concentrated solely on the relationship between interaction frequency and species diversity, our results shed lights on the important role of territorial awareness in models of RPS, and they reveal fascinating evolutionary outcomes in structured populations that are a unique consequence of such awareness behavior. [ABSTRACT FROM AUTHOR]

For analyzing ejector's performance in the system, an ejector for a 10 kW polymer electrolyte membrane fuel cell (PEMFC) system was first designed, manufactured, and a 10 kW PEMFC system bench was built up. A proportional valve and PI pressure feedback control method were adopted to control the hydrogen supply and anode inlet pressure. During the test, performances between dead-ended anode (DEA) mode and ejector mode were compared. Ejector's performances in the system, i.e., volume flow recirculated ratio, difference pressure, dynamic responses of primary pressure, anode inlet pressure, and recirculated gas flow rate during the purge process and current variation condition, were investigated. The results show that pressure adjustment is accurate, continuous, and fast using the proportional valve and PI pressure feedback control method. The hydrogen consumption rate in the ejector mode can reduce from 5% to 10% compared with the rate in the DEA mode except for the stack current 5 A and 10 A conditions. For better water removal out of the anode channel in ejector mode, the maximum stack power increases from 5.11 kW (DEA mode) to 9.56 kW (ejector mode). Anode pressure surge caused by the purge valve switching enhances the ejector's recirculated performance significantly. • An ejector for a 10 kW PEMFC system is designed, manufactured and evaluated. • The stack in ejector's mode shows a better performance than that in DEA mode. • Hydrogen recirculation can reduce the hydrogen consumption. • The proportional valve with the PI pressure feedback method can accurately control the anode inlet pressure. • Anode pressure surge can enhance ejector's recirculated performance. [ABSTRACT FROM AUTHOR]

Distributions of water and oxygen concentration are the two main factors that influence the consistency of current density in a polymer electrolyte membrane fuel cell. While the former type is relevant to the ohmic loss, the latter one associated with the mass transfer loss. In a self-humidified condition, higher demand for water management is requested as membrane drying often appears. To investigate the effects of flow pattern and hydrogen recirculation on the consistency of current density, the cell is tested under five different conditions, and a quasi-three-dimensional transient non-isothermal model is developed to explain different experimental phenomena in this study. Differences of distributions of current density, resistance and reaction gases are examined by comparing co-flow with counter-flow conditions, humidified with self-humidified conditions and dead-ended anode with hydrogen recirculation conditions. The results show that consistency reduces with the cell current density increasing, and gas humification is significantly beneficial. In co-flow configurations, the standard deviation of local current density increases from 0.02 at 0.2 A cm−2 to 0.14 at 1.2 A cm−2 under the humidified condition, increasing from 0.38 at 0.2 A cm−2 to 0.26 at 1.2 A cm−2 under the self-humidified condition. The water distribution of the cell in counter-flow configuration is more uniform than that in the co-flow configuration under the whole current density conditions. Hydrogen recirculation can improve the water content of segments near the inlet gas channel in the anode, and the consistency is the best when the current density is larger than 0.4 A cm−2. • A segmented single cell model is developed. • It has a higher demand for water management in a self-humidified condition. • Consistency in counter-flow configuration is better than that in co-flow way. • Recycled vapor in anode can improve consistency of local current density. [ABSTRACT FROM AUTHOR]

• Based on an activity-driven network, a model dividing individuals into two types, one is risk-ignorant, and the other is risk-averse who may reduce the potential risk of infection by being less social intensity is established. • The outbreak of an epidemic depends most on the proportion of risk-averse individuals. • A large number of risk-averse individuals who change their social intensity raises the theoretical threshold and reduces the epidemic size, thus suppressing the outbreak. • As risk-averse individuals increases, the epidemic is eliminated under small spreading rates. In human society, individual interactions intrinsically change, with profound implications for epidemics. The activity-driven model, a type of temporal network, offers an excellent framework to study epidemic processes in dynamical interaction. In this work, we study how social attitudes affect the transmission of infectious diseases in activity-driven networks. Here, we divide a population into "risk-ignorant" and "risk-averse", in which risk-averse individuals will reduce their social intensity (Social intensity refers to the number of social contacts in the social process) and risk-ignorant individuals will not. A parameter p controls the proportion of risk-averse individuals, and therefore risk-ignorant individuals by 1- p. With the aid of mean-field theory, we calculate epidemic thresholds, as well as validate theoretical predictions with extensive Monte Carlo simulations. It is shown numerically and theoretically that reducing the social intensity and increasing the number of risk-averse individuals are effective ways of controlling epidemic outbreaks. An appropriate proportion of the risk-averse individual will lead to an epidemic die-out, which is based on a small spreading rate. Our research provides a new perspective for understanding the effect of the population with different social attitudes in the epidemic process. [ABSTRACT FROM AUTHOR]

The maintenance of biological diversity has perpetually remained a central focus in the field of ecology. In the pursuit of enhanced survival rates, species have begun to explore cooperation with one another. However, the consequences of such collaboration remain largely unexplored. To delve into this matter, we introduce intraspecific cooperation within the framework of the classic rock-paper-scissors (RPS) game. In this model, the competition rate is intricately tied to interactions among individuals of the same species. A greater population of individuals from the same species tends to lead to an increased predation rate and a decreased prey rate. Through extensive simulations, we observe that (i) in the case of homogeneous intraspecific cooperation (all three species have intraspecific cooperation), increased cooperation between predators tends to increase the likelihood of species coexistence. In contrast, high levels of cooperation between prey appeared to decrease the favorability of species coexistence. Measurements of the characteristic length of spiral structures revealed that the characteristic length of spirals became longer when the intensity of prey cooperation increased. (ii) In the case of heterogeneous intraspecific cooperation (two species or only one species with intraspecific cooperation), neither an increase in the intensity of intraspecific cooperation of the predator nor an increase in the intensity of intraspecific cooperation of the prey is favorable for species coexistence. Our work underscores the critical role of intraspecific cooperation in maintaining biodiversity. • In rock-paper-scissors games, intraspecific cooperation promotes and jeopardizes biodiversity. • Under homogeneous intraspecific cooperation, predator cooperation promotes coexistence. • Under heterogeneous intraspecific cooperation, both predator and prey cooperation jeopardize coexistence. [ABSTRACT FROM AUTHOR]

In this paper, we explore the evolution of vaccination behavior in the SIR model. Among the participated individuals, a proportion of ρ individuals choose conformist-driven updating mechanism to update their strategies, while the rest of 1 − ρ individuals update strategies with payoff-driven updating mechanism. Our results show that conformists have rare effect on vaccination if the cost is pretty small except the moderate proportion of conformists, where conformists on the boundary play a leading role on epidemic prevention. While for medium values of cost, an excess of conformists conduces to infectious diseases diffusion. • Payoff-driven and conformist-driven individuals coexist in the population. • Cost of vaccination induces different effect of conformist determined. • A moderate proportion of conformist can improve vaccination level. [ABSTRACT FROM AUTHOR]

In the real world, a single homogeneous or heterogeneous network is very rare, so we consider a compound model which contains two different types of subnetworks. The compound model may be applied to analyze the contagion dynamics of two different communities where they have a probability to communicate. The global infection threshold is obtained, and many factors affecting spread of epidemics are analyzed, including subnetwork density, subnetwork size, connecting probability and the maximum degree. An interesting phenomenon is that we find the transition points of the global threshold from increasing to decreasing, which was not mentioned in previous work. Therefore, we give many measures to improve infection threshold and prevent the spread of epidemics. The experimental results confirm the conclusions of epidemic analysis. • The spreading process of epidemics on a mixed model is studied. • The transition points of epidemic threshold from increasing to decreasing are given. • Many factors to affect the global epidemic threshold are analyzed. • Many measures to prevent the spread of epidemics are proposed. [ABSTRACT FROM AUTHOR]

Background: Undifferentiated connective tissue disease (UCTD) is known to induce adverse pregnancy outcomes and even recurrent spontaneous abortion (RSA) by placental vascular damage and inflammation activation. Anticoagulation can prevent pregnancy morbidities. However, it is unknown whether the addition of immune suppressants to anticoagulation can prevent spontaneous pregnancy loss in UCTD patients. The purpose of this study is to evaluate the efficacy of hydroxychloroquine (HCQ) and low-dose prednisone on recurrent pregnancy loss for women with UCTD.Methods: The Immunosuppressant for Living Fetuses (ILIFE) Trial is a three-arm, multicenter, open-label randomized controlled trial with the primary objective of comparing hydroxychloroquine combined with low-dose prednisone and anticoagulation with anticoagulation alone in treating UCTD women with recurrent spontaneous abortion. The third arm of using hydroxychloroquine combined with anticoagulant for secondary comparison. A total of 426 eligible patients will be randomly assigned to each of the three arms with a 1:1:1 allocation ratio. The primary outcome is the rate of live births. Secondary outcomes include adverse pregnancy outcomes and progression of UCTD.Discussion: This is the first multi-center, open-label, randomized controlled trial which evaluates the efficacy of immunosuppressant regimens on pregnancy outcomes and UCTD progression. It will provide evidence on whether the immunosuppressant ameliorates the pregnancy prognosis in UCTD patients with RSA and the progression into defined connective tissue disease.Trial Registration: ClinicalTrials.gov NCT03671174 . Registered on 14 September 2018. [ABSTRACT FROM AUTHOR]

• Aspiration-based exit option in prisoners dilemma game can promote cooperation. • In structured population, the intermediate aspiration level promotes cooperation, because defectors around the cooperative cluster exit the game, which weakens the exploitation of cooperators, and help the cooperators at the edge of the cooperative cluster to expand to inactive nodes or the defectors through network reciprocity. • The combined effect of aspiration level and dilemma strength affects the active state of players. Cooperation is promoted in the structured population when individual has the exit option and it is found that aspiration driven updating rules can also promote cooperation to a certain extent. The right to exit gives individuals the opportunity to get rid of exploitation, and the aspiration is the self-evaluation of individuals. Stimulated by these, we study the effect of aspiration driven exit on cooperation in the spatial prisoner dilemma game. In the game, the aspiration level and payoff of interactive determine the individual's state. When the individual gets more than aspiration level by interacting with other players, the individual will continue to participate in the game as an active player. On the contrary, when the payoff is lower than the aspiration level, individual exits the game as an inactive player. At the same time, inactive player who exits from the game will get random payoff and pay a certain cost. The promotion of cooperative behavior mainly depends on the aspiration level of players. An appropriate level of aspiration will lead to a high cooperation, which is based on the formation of cooperative clusters. These cooperators can get rid of the invasion of defectors, even if there is a great temptation of defection, this is because the inactive defectors who exit have cut off the interaction between the cooperative cluster and the defectors. Our research provides a feasible way to solve the social dilemma and will stimulate further application. [ABSTRACT FROM AUTHOR]

• We consider the repeated pairwise prisoner's dilemma game among two groups of agents. • We found that the mixed strategy-update rule (Q-learning-based update rule and Fermi-function-based update rule) can evaluate cooperation. • If the proportion of AI is moderate, cooperators among the whole population exhibit conditional behavior and moody conditional behavior. Recent studies show that different update rules are invariant regarding the evolutionary outcomes for a well-mixed population or homogeneous network. In this paper, we investigate how the Q-learning algorithm, one of the reinforcement learning methods, affects the evolutionary outcomes in square lattice. Especially, we consider the mixed strategy update rule, among which some agents adopt Q-learning method to update their strategies, the proportion of these agents (these agents are denoted as Artificial Intelligence (AI)) is controlled by a simple parameter ρ. The rest of other agents, the proportion is denoted by 1 − ρ, adopt the Fermi function to update their strategies. Through extensive numerical simulations, we found that the mixed strategy-update rule can facilitate cooperation compared with the pure Fermi- function-based update rule. Besides, if the proportion of AI is moderate, cooperators among the whole population exhibit conditional behavior and moody conditional behavior. However, if the whole population adopts the pure Fermi-function-based strategy update rule or the pure Q-learning-based strategy update rule, then cooperators among the whole population exhibit the hump-shaped conditional behavior. Our results provide a new insight to understand the evolution of cooperation from AI's view. [ABSTRACT FROM AUTHOR]

Information exchange has a significant influence on human behaviour decision-making. To explore the impact of the information exchange mechanism on the evolution of cooperative behaviour on the complex networks, we establish two-layer interdependent networks. Individuals have a certain probability of having information exchange with individuals on another network. In detail, when individuals residing on different networks are connected by links, the update of strategies not only depends on their own payoffs, but also depends on the strategy selections of the corresponding nodes and neighbours on the other network. Numerous simulations reveal that high cooperation level can be achieved for a large coupling probability and intermediate heterogeneity. Counter-intuitively, cooperation is not always promoted by the expansion of information sources. Our study thus enhances the understanding of the evolution of cooperation on interdependent networks. • We explore the effect of information exchange for the evolution of cooperation on interdependent networks. • Information exchange is a double-edged sword for cooperation. • Large coupling density warrants strongest location synchronization effect for cooperation. [ABSTRACT FROM AUTHOR]

• Lupus-prone mouse has endothelial dysfunction. • RORα is decreased in aorta of lupus-prone mouse and in SLE medium treated HUVECs. • Melatonin prevents endothelial dysfunction in SLE by activating RORα. Atherosclerotic cardiovascular disease confers significant morbidity and mortality in patients with systemic lupus erythematosus (SLE). A substantial proportion of patients with SLE display accelerated endothelial dysfunction, which precedes cardiovascular disease. Melatonin and its nuclear receptor retinoid-related orphan receptor alpha (RORα) have been reported to have some protective effects on the development of atherosclerosis. However, the function of melatonin in SLE-induced endothelial dysfunction and the role that RORα plays are still unknown. In this study, we found that RORα protein expression was decreased in aortas of lupus-prone mice and in human umbilical vein endothelial cells (HUVECs) cultured with medium containing sera of patients with SLE. Melatonin-treated HUVECs showed a decrease of pro-inflammatory mRNAs [interleukin-1beta (IL-1β), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α)] under the stimulation of SLE medium. Melatonin increased nitric oxide and antioxidant mRNAs (SOD1 , GPX1 , and CAT) and downregulated reactive oxygen species (ROS) level in HUVECs, which may subsequently delay endothelial senescence and promote HUVEC proliferation and repair after injury. Melatonin inhibited SLE medium-induced RAW264.7 macrophage migration. HUVECs pretreated with melatonin expressed less adhesion-related proteins (ICAM-1 and VCAM-1); as a result, these cells adhered to fewer peripheral blood monocytes. In addition, we also showed that the protective effects of melatonin on endothelial cells were largely diminished when RORα was knockdown in HUVECs. In conclusion, by targeting the nuclear receptor RORα, melatonin preserves normal functions of endothelium in SLE by its anti-inflammatory, antioxidant, and anti-senescence effects. RORα may have the potential to become a prophylactic or therapeutic target in preventing endothelial dysfunction and atherosclerotic cardiovascular disease in patients with SLE. [ABSTRACT FROM AUTHOR]