一类正广义系统的能控性和能观性

对于广义系统的能控性和能观性的研究已经取得了很多成果,但对于正广义系统的研究,目前还处于起步阶段,需要进一步的研究．本文研究了一类正广义系统,通过Drazin逆给出了判别系统能控性和能观性的充分条件,并通过例子验证了本文结论的有效性．     

CONTROLLABILITY OF NON-LINEAR MODELS OF INTERACTING BIOLOGICAL POPULATIONS

Inthispaper,theauthorstudiedthecontrollabilityforakindofinteractingbiologicalpopulations.whichwasconsideredasamodelonepredatortwopreysystems,theauthorformulatedandprovedthesufficientconditionsforthelocalcontrollabilityofthisdynamicalsystems.     

Nodal dynamics, not degree distributions, determine the structural controllability of complex networks

Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set, is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.     

Equilibrium, observability and controllability in selection-mutation models

In this paper we shortly discuss the problem of the equilibrium in the well-known Fisher type selection-mutation model, also providing a formula for particular three-allele models. The considered continuous-time dynamics is a known extension of the classical model of natural selection given by Fisher. We also extend the existing investigation of the observability of Fisher's model to the case when another evolutionary factor, mutation is also present. Moreover, we prove a result of technical character, which makes it possible to apply the methodology of nonlinear systems with invariant manifold, to models of artificial selection. For an illustration, a class of three-allele systems is presented in which the controllability into equilibrium is guaranteed without any condition on the biological parameters.     

Role of Quantity of Additional Food to Predators as a Control in Predator–Prey Systems with Relevance to Pest Management and Biological Conservation

Necessity to understand the role of additional food as a tool in biological control programs is being increasingly felt, particularly due to its eco-friendly nature. A thorough mathematical analysis in this direction revealed the vital role of quality and quantity of the additional food in the controllability of the predator–prey systems. In this article controllability of the additional food—provided predator–prey system is studied from perspectives of pest eradication and biological conservation. Time optimal paths have been constructed to drive the state of the system to a desired terminal state by choosing quantity of the additional food as control variable. The theory developed in this article has been illustrated by solving problems related to pest eradication and biological conservation.     

Exact Controllability of Age-Structured Predator-Prey Populations

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Neurocomputational mechanism of controllability inference under a multi-agent setting

Controllability perception significantly influences motivated behavior and emotion and requires an estimation of one’s influence on an environment. Previous studies have shown that an agent can infer controllability by observing contingency between one’s own action and outcome if there are no other outcome-relevant agents in an environment. However, if there are multiple agents who can influence the outcome, estimation of one’s genuine controllability requires exclusion of other agents’ possible influence. Here, we first investigated a computational and neural mechanism of controllability inference in a multi-agent setting. Our novel multi-agent Bayesian controllability inference model showed that other people’s action-outcome contingency information is integrated with one’s own action-outcome contingency to infer controllability, which can be explained as a Bayesian inference. Model-based functional MRI analyses showed that multi-agent Bayesian controllability inference recruits the temporoparietal junction (TPJ) and striatum. Then, this inferred controllability information was leveraged to increase motivated behavior in the vmPFC. These results generalize the previously known role of the striatum and vmPFC in single-agent controllability to multi-agent controllability, and this generalized role requires the TPJ in addition to the striatum of single-agent controllability to integrate both self- and other-related information. Finally, we identified an innate positive bias toward the self during the multi-agent controllability inference, which facilitated behavioral adaptation under volatile controllability. Furthermore, low positive bias and high negative bias were associated with increased daily feelings of guilt. Our results provide a mechanism of how our sense of controllability fluctuates due to other people in our lives, which might be related to social learned helplessness and depression.     

Controllability in Cancer Metabolic Networks According to Drug Targets as Driver Nodes

Networks are employed to represent many nonlinear complex systems in the real world. The topological aspects and relationships between the structure and function of biological networks have been widely studied in the past few decades. However dynamic and control features of complex networks have not been widely researched, in comparison to topological network features. In this study, we explore the relationship between network controllability, topological parameters, and network medicine (metabolic drug targets). Considering the assumption that targets of approved anticancer metabolic drugs are driver nodes (which control cancer metabolic networks), we have applied topological analysis to genome-scale metabolic models of 15 normal and corresponding cancer cell types. The results show that besides primary network parameters, more complex network metrics such as motifs and clusters may also be appropriate for controlling the systems providing the controllability relationship between topological parameters and drug targets. Consequently, this study reveals the possibilities of following a set of driver nodes in network clusters instead of considering them individually according to their centralities. This outcome suggests considering distributed control systems instead of nodal control for cancer metabolic networks, leading to a new strategy in the field of network medicine.     

Identifiability of time-dependent linear systems

This paper establishes a direct method for determining the identifiability of time-dependent linear systems. Contrary to most other results on identifiability, we do not require system controllability. We apply this method to a specific example and show that a time-dependent system may be identifiable on a finite interval without being identifiable on a longer time interval.     

Controllability of Deterministic Networks with the Identical Degree Sequence

Controlling complex network is an essential problem in network science and engineering. Recent advances indicate that the controllability of complex network is dependent on the network''s topology. Liu and Barabási, et.al speculated that the degree distribution was one of the most important factors affecting controllability for arbitrary complex directed network with random link weights. In this paper, we analysed the effect of degree distribution to the controllability for the deterministic networks with unweighted and undirected. We introduce a class of deterministic networks with identical degree sequence, called (x,y)-flower. We analysed controllability of the two deterministic networks ((1, 3)-flower and (2, 2)-flower) by exact controllability theory in detail and give accurate results of the minimum number of driver nodes for the two networks. In simulation, we compare the controllability of (x,y)-flower networks. Our results show that the family of (x,y)-flower networks have the same degree sequence, but their controllability is totally different. So the degree distribution itself is not sufficient to characterize the controllability of deterministic networks with unweighted and undirected.     

Control of anaerobic digesters using Generic Model Control

This paper describes the improved effluent control of industrial anaerobic digestion treatment systems. Previous research has shown the possibility of applying a model-based adaptive control technique to these processes. This paper reviews this technique and shows that improved controllability can be obtained by a modification to the existing algorithm, based on a new control technique known as Generic Model Control, that simplifies and improves the robustness of the control algorithm.     

Effects of Edge Directions on the Structural Controllability of Complex Networks

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain “inappropriate” edge directions. However, the existence of multiple sets of “inappropriate” edge directions suggests that different edges have different effects on optimal controllability—that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions—utilizing only local information—which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.     

Controllability of non-linear biochemical systems

Mathematical methods of biochemical pathway analysis are rapidly maturing to a point where it is possible to provide objective rationale for the natural design of metabolic systems and where it is becoming feasible to manipulate these systems based on model predictions, for instance, with the goal of optimizing the yield of a desired microbial product. So far, theory-based metabolic optimization techniques have mostly been applied to steady-state conditions or the minimization of transition time, using either linear stoichiometric models or fully kinetic models within biochemical systems theory (BST). This article addresses the related problem of controllability, where the task is to steer a non-linear biochemical system, within a given time period, from an initial state to some target state, which may or may not be a steady state. For this purpose, BST models in S-system form are transformed into affine non-linear control systems, which are subjected to an exact feedback linearization that permits controllability through independent variables. The method is exemplified with a small glycolytic-glycogenolytic pathway that had been analyzed previously by several other authors in different contexts.     

Genetic testing for late-onset diseases: effect of disease controllability, test predictivity, and gender on the decision to take the test

This study was designed to investigate the influence of the predictive power of the genetic test, the disease's controllability, and gender on the intention to take a predictive genetic test. Another aim was to examine the certainty of the intention to take the test. Nine scenarios were presented to a convenience sample of 121 men and women. Each scenario described a hypothetical and devastating late-onset disease and manipulated the level of disease controllability and test predictive value. The more predictivity the test offered and the more controllable the disease, the more the subjects were interested in being tested and the more certain their decision to take the test. Men's decisions were more positive than women's. There were also interactions between disease controllability and gender and between disease controllability and test predictivity. It seems that the factor that most influences the decision not to take the test is low disease controllability. This effect is more pronounced in women. Gender differences in decision making and information processing may be pertinent. The data show a marked gap between the decision itself and the certainty of that decision. The strength of the decision may be a better predictor of actual test uptake than the direction of the decision.     

Developmental shifts in computations used to detect environmental controllability

Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior—exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8–25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants’ controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one’s benefit.     

微生物微培养系统研究现状与展望

微生物培养是微生物学的起源和根本,成功的微生物培养是进行后续研究的重要前提与基础。但是,微生物培养操作不仅耗费了科研人员大量的精力和时间,还存在着极大的人为误差。近年来,容量小、高通量、模块化、可操作性良好并可进行在线检测的微生物微培养系统得到了微生物学领域的广泛关注。文中介绍了应用于微生物学领域的微培养系统,并按系统构成分类讨论了微生物微培养系统的发展、应用和展望。     

综述——纳米材料与药物输递：基于聚合物的环境敏感型纳米抗肿瘤药物传输系统的研究

环境敏感型聚合物纳米抗肿瘤药物传递系统能够响应外界环境的微小刺激,引起自身结构的变化,释放出药物,在肿瘤治疗方面具长效低毒、可控及高载药量等优势,已被广泛应用于生物医学领域．本文介绍了聚合物环境响应型纳米药物传输系统的发展近况,并从pH 值敏感型、温度敏感型、氧化还原敏感型、酶敏感型以及其他敏感型给药系统角度,阐述了环境敏感型药物传输系统在抗肿瘤领域的研究现状及未来展望．     

Targeted large fragment deletion in plants using paired crRNAs with type I CRISPR system

The CRISPR-Cas systems have been widely used as genome editing tools, with type II and V systems typically introducing small indels, and type I system mediating long-range deletions. However, the precision of type I systems for large fragment deletion is still remained to be optimized. Here, we developed a compact Cascade-Cas3 Dvu I-C system with Cas11c for plant genome editing. The Dvu I-C system was efficient to introduce controllable large fragment deletion up to at least 20 kb using paired crRNAs. The paired-crRNAs design also improved the controllability of deletions for the type I-E system. Dvu I-C system was sensitive to spacer length and mismatch, which was benefit for target specificity. In addition, we showed that the Dvu I-C system was efficient for generating stable transgenic lines in maize and rice with the editing efficiency up to 86.67%. Overall, Dvu I-C system we developed here is powerful for achieving controllable large fragment deletions.     

Structural Properties of Gene Regulatory Networks: Definitions and Connections

The study of gene regulatory networks is a significant problem in systems biology. Of particular interest is the problem of determining the unknown or hidden higher level regulatory signals by using gene expression data from DNA microarray experiments. Several studies in this area have demonstrated the critical aspect of the network structure in tackling the network modelling problem. Structural analysis of systems has proved useful in a number of contexts, viz., observability, controllability, fault diagnosis, sparse matrix computations etc. In this contribution, we formally define structural properties that are relevant to Gene Regulatory Networks. We explore the structural implications of certain quantitative methods and explain completely the connections between the identifiability conditions and structural criteria of observability and distinguishability. We illustrate these concepts in case studies using representative biologically motivated network examples. The present work bridges the quantitative modelling methods with those based on the structural analysis.     

Equilibrium control of nonlinear verticum-type systems,applied to integrated pest control

Linear verticum-type control and observation systems have been introduced for modelling certain industrial systems, consisting of subsystems, vertically connected by certain state variables. Recently the concept of verticum-type observation systems and the corresponding observability condition have been extended by the authors to the nonlinear case. In the present paper the general concept of a nonlinear verticum-type control system is introduced, and a sufficient condition for local controllability to equilibrium is obtained. In addition to a usual linearization, the basic idea is a decomposition of the control of the whole system into the control of the subsystems. Starting from the integrated pest control model of Rafikov and Limeira (2012) and Rafikov et al. (2012), a nonlinear verticum-type model has been set up an equilibrium control is obtained. Furthermore, a corresponding bioeconomical problem is solved minimizing the total cost of integrated pest control (combining chemical control with a biological one).