Background Broiler chickens are most vulnerable immediately after hatching due to their immature immune systems,making them susceptible to infectious diseases.The yolk plays an important role in early immune defence b...Background Broiler chickens are most vulnerable immediately after hatching due to their immature immune systems,making them susceptible to infectious diseases.The yolk plays an important role in early immune defence by showing relevant antioxidant and passive immunity capabilities during broiler embryonic development.The immunomodulatory effects of phytogenic compound carvacrol have been widely reported.After in ovo delivery in the amniotic fluid during embryonic development carvacrol is known to migrate to the yolk sac.However,it is unknown whether carvacrol in the yolk could enhance defence responsiveness in the yolk sac.Therefore,the aim of this study was to improve early immune function in chicken embryos,and it was hypothesized that in ovo delivery of carvacrol would result in immunomodulatory effects in the yolk sac,potentially improving post-hatch resilience.Methods On embryonic day(E)17.5,either a saline(control)or carvacrol solution was injected into the amniotic fluid.Yolk sac tissue samples were collected at E19.5,and transcriptomic analyses using RNA sequencing were performed,following functional enrichment analyses comparing the control(saline)and carvacrol-injected groups.Results The results showed that 268 genes were upregulated and 174 downregulated in the carvacrol group compared to the control(P<0.05;logFC<-0.5 or log FC>0.5).Functional analyses of these differentially expressed genes,using KEGG,REACTOME,and Gene Ontology databases,showed enrichment of several immune-related pathways.This included the pathways‘Antimicrobial peptides’(P=0.001)and‘Chemoattractant activity’(P=0.004),amongst others.Moreover,the‘NOD-like receptor signaling’pathway was enriched(P=0.002).Antimicrobial peptides are part of the innate immune defence and are amongst the molecules produced after the nucleotide oligomeriza-tion domain(NOD)-like receptor pathway activation.While these responses may be associated with an inflammatory reaction to an exogenous threat,they could also indicate that in ovo delivery of carvacrol could prepare the newly hatched chick against bacterial pathogens by potentially promoting antimicrobial peptide production through acti-vation of NOD-like receptor signaling in the yolk sac.Conclusion In conclusion,these findings suggest that in ovo delivery of carvacrol has the potential to enhance anti-pathogenic and pro-inflammatory responses in the yolk sac via upregulation of antimicrobial peptides,and NOD-like receptor pathways.展开更多
近日,中国科学院软件所智能博弈重点实验室研究团队的论文“Mimicking the Familiar:Dynamic Command Generation for Information Theft Attacks in LLM Tool-Learning System”被自然语言处理领域会议ACL 2025授予SAC Highlights奖。...近日,中国科学院软件所智能博弈重点实验室研究团队的论文“Mimicking the Familiar:Dynamic Command Generation for Information Theft Attacks in LLM Tool-Learning System”被自然语言处理领域会议ACL 2025授予SAC Highlights奖。该研究揭示了大语言模型工具学习系统(LLM Tool-Learning System)存在的安全隐患,通过模拟攻击者工具投毒,分析造成的信息窃取风险并提出针对性防御方法,弥补了现有推理端安全检测方法的不足。论文主要完成人为特别研究助理江子攸、副研究员李明阳、研究员王俊杰和研究员王青。展开更多
In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is propos...In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is proposed in this paper for automatic control of mobile robots.According to the environmental feedback,the RL agent of the upper controller outputs the optimal parameters to the lower MIMO PID controllers,which can realize the real-time PID optimal control.First,a model-free adaptive MIMO PID hybrid control strategy is presented to realize real-time optimal tuning of control parameters in terms of soft-actor-critic(SAC)algorithm,which is state-of-the-art RL algorithm.Second,in order to improve the RL convergence speed and the control performance,a Lyapunov-based reward shaping method for off-policy RL algorithm is designed,and a self-adaptive LSAC-PID tuning approach with Lyapunov-based reward is then determined.Through the policy evaluation and policy improvement of the soft policy iteration,the convergence and optimality of the proposed LSAC-PID algorithm are proved mathematically.Finally,based on the proposed reward shaping method,the reward function is designed to improve the system stability for the line-following robot.The simulation and experiment results show that the proposed adaptive LSAC-PID approach has good control performance such as fast convergence speed,high generalization and high real-time performance,and achieves real-time optimal tuning of MIMO PID parameters without the system model and control loop decoupling.展开更多
基金support by AgriFutures Australia’s Chicken Meat Program[grant number PRJ-011584]is gratefully acknowledged.
文摘Background Broiler chickens are most vulnerable immediately after hatching due to their immature immune systems,making them susceptible to infectious diseases.The yolk plays an important role in early immune defence by showing relevant antioxidant and passive immunity capabilities during broiler embryonic development.The immunomodulatory effects of phytogenic compound carvacrol have been widely reported.After in ovo delivery in the amniotic fluid during embryonic development carvacrol is known to migrate to the yolk sac.However,it is unknown whether carvacrol in the yolk could enhance defence responsiveness in the yolk sac.Therefore,the aim of this study was to improve early immune function in chicken embryos,and it was hypothesized that in ovo delivery of carvacrol would result in immunomodulatory effects in the yolk sac,potentially improving post-hatch resilience.Methods On embryonic day(E)17.5,either a saline(control)or carvacrol solution was injected into the amniotic fluid.Yolk sac tissue samples were collected at E19.5,and transcriptomic analyses using RNA sequencing were performed,following functional enrichment analyses comparing the control(saline)and carvacrol-injected groups.Results The results showed that 268 genes were upregulated and 174 downregulated in the carvacrol group compared to the control(P<0.05;logFC<-0.5 or log FC>0.5).Functional analyses of these differentially expressed genes,using KEGG,REACTOME,and Gene Ontology databases,showed enrichment of several immune-related pathways.This included the pathways‘Antimicrobial peptides’(P=0.001)and‘Chemoattractant activity’(P=0.004),amongst others.Moreover,the‘NOD-like receptor signaling’pathway was enriched(P=0.002).Antimicrobial peptides are part of the innate immune defence and are amongst the molecules produced after the nucleotide oligomeriza-tion domain(NOD)-like receptor pathway activation.While these responses may be associated with an inflammatory reaction to an exogenous threat,they could also indicate that in ovo delivery of carvacrol could prepare the newly hatched chick against bacterial pathogens by potentially promoting antimicrobial peptide production through acti-vation of NOD-like receptor signaling in the yolk sac.Conclusion In conclusion,these findings suggest that in ovo delivery of carvacrol has the potential to enhance anti-pathogenic and pro-inflammatory responses in the yolk sac via upregulation of antimicrobial peptides,and NOD-like receptor pathways.
文摘近日,中国科学院软件所智能博弈重点实验室研究团队的论文“Mimicking the Familiar:Dynamic Command Generation for Information Theft Attacks in LLM Tool-Learning System”被自然语言处理领域会议ACL 2025授予SAC Highlights奖。该研究揭示了大语言模型工具学习系统(LLM Tool-Learning System)存在的安全隐患,通过模拟攻击者工具投毒,分析造成的信息窃取风险并提出针对性防御方法,弥补了现有推理端安全检测方法的不足。论文主要完成人为特别研究助理江子攸、副研究员李明阳、研究员王俊杰和研究员王青。
基金the National Key R&D Program of China(No.2018YFB1308400)。
文摘In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is proposed in this paper for automatic control of mobile robots.According to the environmental feedback,the RL agent of the upper controller outputs the optimal parameters to the lower MIMO PID controllers,which can realize the real-time PID optimal control.First,a model-free adaptive MIMO PID hybrid control strategy is presented to realize real-time optimal tuning of control parameters in terms of soft-actor-critic(SAC)algorithm,which is state-of-the-art RL algorithm.Second,in order to improve the RL convergence speed and the control performance,a Lyapunov-based reward shaping method for off-policy RL algorithm is designed,and a self-adaptive LSAC-PID tuning approach with Lyapunov-based reward is then determined.Through the policy evaluation and policy improvement of the soft policy iteration,the convergence and optimality of the proposed LSAC-PID algorithm are proved mathematically.Finally,based on the proposed reward shaping method,the reward function is designed to improve the system stability for the line-following robot.The simulation and experiment results show that the proposed adaptive LSAC-PID approach has good control performance such as fast convergence speed,high generalization and high real-time performance,and achieves real-time optimal tuning of MIMO PID parameters without the system model and control loop decoupling.
