Cation-anionicpalladium Complexes—New Types of Antitumor, Immune Response-modulating and Radioprotective Agents

Here we report results of our investigations of new class of bioactive palladium compounds (AH n ) m [PdCl 4 ], which were discovered as a result of systematic study of correlations between composition, structure and bioactivity of different types of platinum metals coordination compounds. For the first time we demonstrated in vivoa possibility of development of palladium compounds, which exceed cisplatin in antitumor activity and do not show immunosuppressive effects, and palladium compounds with immunostimulating and radioprotective activities. Combinations of cytostatic agents or radiation with palladium complexes lead to significant synergism of their activities and high therapeutic efficiency exceeded an efficiency of their separated use.

基于Immune Agent的城市水污染控制决策系统

将免疫算法和Agent思想应用于实现决策支持,建立基于免疫Agent的城市河流水环境污染控制决策支持系统,避免基于模型的决策支持系统在求解问题时难以适应动态环境变化的缺陷,使决策支持系统面向问题,提高其智能性和自适应性。实验结果表明,使用AHP方法选择Agent方案是可行的。

基于免疫Agent的电力电缆线路故障检测系统

为区别故障信号、非故障信号,实现对电缆线路故障的准确检测,设计了基于免疫Agent的电力电缆线路故障检测系统。利用前端检测电路为故障分析模块、测距方式切换模块提供电量传输信号,完成系统前端检测装置的连接。按照免疫Agent检测原理提取电力电缆线路故障信号的特征,联合已获取信号对象,求解检测插值指标的具体数值。结合各级硬件设备结构,完成系统设计。实验结果表明,该系统可同时检测波频为10~20 Hz、40~50 Hz、60~70 Hz的故障信号与波频为20~30 Hz、30~40 Hz、50~60 Hz的非故障信号,可以在精准辨别故障与非故障信号的同时,实现对电力电缆线路故障的准确检测。

Multi-Agent Network Intrusion Active Defense Model Based on Immune Theory

Inspired by the immune theory and multi-agent systems, an immune multi-agent active defense model for network intrusion is established. The concept of immune agent is introduced, and its running mechanism is established. The method, which uses antibody concentration to quantitatively describe the degree of intrusion danger, is presented. This model implements the multi-layer and distributed active defense mechanism for network intrusion. The experiment results show that this model is a good solution to the network security defense.

Immune multi-agent model using vaccine for cooperative air-defense system of systems for surface warship formation based on danger theory

Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.

Research on Application of Mobile Agent Based on Immune Algorithms in Ad Hoc Network

Ad Hoc network is a kind of multi hop, self-organizing wireless network without center. Each node in network can be used as host as well as router and it can form any network topology through wireless connections. Because of characteristics of itself, many new service items and application fields appear;meanwhile, it is also faced with many new security threats. Using immune agent can perceive the change of network node and make corresponding decision behavior, find the misbehavior nodes in the network as soon as possible and reduce the network attack and improve the immune competence of network.

A Multi-Agent Immune Network Algorithm and Its Application to Murphree Efficiency Determination for the Distillation Column

Artificial Immune Network （aiNet） algorithms have become popular for global optimization in many modem industrial applications. However, high-dimensional systems using such models suffer from a potential premature convergence problem. In the existing aiNet algorithms, the premature convergence problem can be avoided by implementing various clonal selection methods, such as immune suppression and mutation approaches, both for single population and multi-population cases. This paper presents a new Multi-Agent Artificial Immune Network （Ma-aiNet） algorithm, which combines immune mechanics and multiagent technology, to overcome the premature convergence problem in high-dimensional systems and to efficiently use the agent ability of sensing and acting on the environment. Ma-aiNet integrates global and local search algorithms. The perform- ance of the proposed method is evaluated using 10 benchmark problems, and the results are compared with other well-known intelligent algorithms. The study demonstrates that Ma-aiNet outperforms other algorithms tested. Ma-aiNet is also used to determine the Murphree efficiency of a distillation column with satisfactory results.

A Network Intrusion Detection Model Based on Immune Multi-Agent

A new network intrusion detection model based on immune multi-agent theory is established and the concept of multi-agents is advanced to realize the logical structure and running mechanism of immune multi-agent as well as multi-level and distributed detection mechanism against network intrusion, using the adaptability, diversity and memory properties of artificial immune algorithm and combing the robustness and distributed character of multi-agents system structure. The experiment results conclude that this system is working pretty well in network security detection.

Multi-agent immune recognition of water mine model

It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.

免疫Agents在网络故障诊断方法中的研究

针对传统的网络故障诊断方法普遍具有自适应差、误报率高等的不足,提出了一种结合免疫算法和agent技术的网络故障诊断方法。在分布式环境中,按照网络的不同特征和环境差异,利用不同功能、不同类别的agent进行故障诊断,同时各agent之间能够互相协作,彼此进行信息交流,和采集数据,从而对所获得的故障类型进行诊断。实验证明,该方法能够对网络故障类型进行有效的判定,对以后大型网络故障诊断是一个很好的借鉴。

Targeted and immune therapies for hepatocellular carcinoma:Predictions for 2019 and beyond

Systemic therapy for hepatocellular carcinoma(HCC) has markedly advanced since the survival benefit of a molecular targeted agent, sorafenib, were demonstrated in the SHARP and Asia Pacific trials in 2007. Treatment options for patients with advanced HCC increased by sorafenib, and long-term survival for patients with advanced stage HCC has become possible to some extent. However,development of a more potent first-line novel molecular targeted agent replacing sorafenib and a potent second-line agent after disease progression on or intolerant to sorafenib has been warranted because sorafenib lacks tumor shrinking/necrotizing effects and induces relatively severe adverse events such as hand foot skin reaction. Many agents in the 1 st line and 2 nd line setting were attempted to develop between 2007 and 2016, but all of these clinical trials failed.On the other hand, clinical trials of 4 agents(regorafenib, lenvatinib,cabozantinib, and ramucirumab) succeeded in succession in 2017 and 2018, and their use in clinical practice is possible(regorafenib and lenvatinib) or underway(cabozantinib and ramucirumab). Furthermore, all of 5 clinical trials of combination therapy with transcatheter chemoembolization(TACE) plus a molecular targeted agent failed to date, however, the combination of TACE and sorafenib(TACTICS trials) was reported to be successful and presented at ASCO in 2018. Phase 3 clinical trials of immune checkpoint inhibitors and a combination therapy of immune checkpoint inhibitors and molecular targeted agents are also ongoing, which suggests treatment paradigm of HCC in all stages from early,intermediate and advanced stage, is expected to be changed drastically in the very near future.

Small-molecule agents for cancer immunotherapy

Cancer immunotherapy,exemplified by the remarkable clinical benefits of the immune checkpoint blockade and chimeric antigen receptor T-cell therapy,is revolutionizing cancer therapy.They induce long-term tumor regression and overall survival benefit in many types of cancer.With the advances in our knowledge about the tumor immune microenvironment,remarkable progress has been made in the development of small-molecule drugs for immunotherapy.Small molecules targeting PRR-associated pathways,immune checkpoints,oncogenic signaling,metabolic pathways,cytokine/chemokine signaling,and immune-related kinases have been extensively investigated.Monotherapy of smallmolecule immunotherapeutic drugs and their combinations with other antitumor modalities are under active clinical investigations to overcome immune tolerance and circumvent immune checkpoint inhibitor resistance.Here,we review the latest development of small-molecule agents for cancer immunotherapy by targeting defined pathways and highlighting their progress in recent clinical investigations.

Modelling Immune System:Principles,Models,Analysis and Perspectives

The biological immune system is a complex adaptive system.There are lots of benefits for building the model of the immune system.For biological researchers,they can test some hypotheses about the infection process or simulate the responses of some drugs.For computer researchers,they can build distributed,robust and fault tolerant networks inspired by the functions of the immune system.This paper provides a comprehensive survey of the literatures on modelling the immune system.From the methodology perspective,the paper compares and analyzes the existing approaches and models,and also demonstrates the focusing research effort on the future immune models in the next few years.

Research of Anti-spam System Basing on Immunity Systemand Mobile Agent

The human immune system has the function of selfdiscern.It can identify the non-self antigen and clear it through the immune response automatically.So,human body has the power of resisting disease.The anti-spam system basing on immune system is proposed by using immune system′s theory,and it is introduced in the mail service of enterprise VPN.Regard VPN as the human body,the mobile agent is simulated the antibody because of its movable and intelligent,and the spam is simulated the antigen.It can clear the spam by using immune mechanism.This method is a new thinking of anti-spam mail.The advantage is overcoming the weakness on independence of traditional antispam system.

基于免疫Agent的配电网电缆线路故障自愈系统

传统配电网电缆线路无法有效管理负荷,且故障自愈时间较长。为了解决这个问题,设计了基于免疫Agent的配电网电缆线路故障自愈系统。采用免疫Agent结构采集电缆线路异常数据,并将数据发送给各个电缆线路内的成员代理完成信息交互。采用双中央处理的智能控制终端,实现就地控制。采用联邦式通信服务器,协调Agent通信行为。构建故障自愈模型,设定拓扑约束条件,确定评估价指标,设计自愈执行步骤。根据实验结果可知,应用该方法后,98%以上的配电网电缆故障得以自愈,且耗时更短,应用效果非常理想。

基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法

为实现煤矿内所有耗能设备的动态监控,为节能优化措施的提出提供重要依据,进一步贯彻落实国家绿色低碳环保的发展理念,提出基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法。结合自动控制理论和计算机技术,根据分站控制原理,合理划分煤矿内能源消耗设备的类型,并为每个设备配备可编程控制器。通过极大似然估计法构建线性方程,确定各组设备的监测节点位置。利用多种通信协议,在三层网络结构中部署B/S监测架构,从计量终端收集煤矿能耗设备的运行数据。基于免疫多Agent技术构建学习模型,分析并推理接收到的数据信息,实现对煤矿综合能耗的动态监测。结果表明:以不同的能耗设备为测试对象,基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法可以准确地获取全部运行信息,有效实现能耗设备的动态监测,能够全面监控煤矿中所有耗能设备的运行情况,并为其后期运行和管理提供理论依据,具有应用价值。

移动边缘计算下移动Agent的任务安全迁移策略

移动边缘计算中任务多在远离服务中心的边缘节点上执行,边缘节点的安全能力并不能得到保障,如何将任务迁移到安全可靠的边缘节点来执行是当前存在的一个问题。针对移动边缘计算下任务迁移中的安全风险问题,构建了适用于移动边缘计算环境的移动Agent安全风险计算模型,通过风险采集、风险处理和风险反馈综合评估边缘节点的抗风险值;并引入动态免疫算法,在任务计算和安全计算时间满足任务截止时间的前提下,实现任务迁移的安全能力最大化。仿真实验表明,相比于传统的任务迁移方案,该策略大大提高了移动边缘计算中任务迁移的抗风险能力,具有一定的鲁棒性。

免疫agent概念与模型

阐述了免疫 agent(Im A)这一新概念 ,分析了免疫 agent求解实体的个性特点 ,构造出一种能对动态环境进行实时监控和故障预警的多免疫 agent的形式化网络模型 ,并提出一种新颖的免疫 agent算法。以此构建的系统具有更强的灵活性、鲁棒性和局部更新能力 ,是一个适用于动态环境的自组织系统。

基于免疫Agent的网络入侵检测系统

结合计算机免疫学原理和多Agent技术构建了一个网络化、分布式、智能化的入侵检测系统,该系统融合了两者的优势,同时继承了多Agent系统和免疫系统的优点。其特点是能同时进行多层次的监测和不同级别的响应。系统是完全分布式结构,监视Agent生成后在网络上漫游,各个Agent分布在网络的各个结点上,单个结点受到攻击不会影响其他结点的检测能力,避免了单点失效问题。将疫苗概念引入系统,使得各个Agent可以实现互相学习,增强了整个网络的耐受性、"记忆"机制及新抗体生成机制的能力,提高了系统的适应性,不仅能检测到已知的攻击,而且还能检测到未知的攻击。

基于免疫计算的agent系统研究

由于免疫系统具有良好的特性以及与multi-agent系统的相似性,因此将免疫机理应用于multi-agent系统的研究越来越受到关注。该文提出了一种新的实体agent——免疫agent和多免疫agent系统。首先给出了免疫agent的功能、结构以及形式化描述,然后构造了基于独特性网络理论的多免疫agent系统模型,借鉴生态学协同进化机理提出了系统中免疫agent之间的四种交互关系:共生、共栖、捕食者-猎物和竞争关系,并给出了免疫agent的浓度函数表达式。