Controllability on impulsive systems with delays in both input and impulse and its applications to multi-agent networks

This paper investigates the controllability of impulsive systems with input delay and impulse delay and its applications in multi-agent networks. We adopt the geometric and algebraic analytical tools to establish some easily verified controllability conditions for the considered system model. First, the analytic solution of the considered system is established on every impulsive interval by using ordinary differential equation theory. Then, according to the solution derived, some sufficient complete controllability criteria are developed to reveal the role of the Gramian matrices in different subintervals. By introducing a row matrix of different kinds of Gramian matrices, a complete controllability condition that is proved to be necessary and sufficient is further obtained. By using the relevant geometric matrix theory, the derived algebraic controllability condition is then converted to a geometric one. On other hand, we introduce a multi-agent network with delayed input and impulse and investigate its controllability. By resorting to graph theory and matrix theory, several factors affecting the controllability of the considered multi-agent networks are investigated, such as the topology structure, the inner coupling matrix, and the dynamics of each agent. Finally, two numerical examples are worked out to verify the derived controllability criteria.

Progress in the controllability technology of PROTAC

Proteolysis-targeting chimaera (PROTAC) technology functions by directly targeting proteins and catalysing their degradation through an event-driven mode of action, a novel mechanism with significant clinical application prospects for various diseases. Currently, the most advanced PROTAC drug is undergoing phase III clinical trials (NCT05654623). Although PROTACs exhibit significant advantages over traditional small-molecule inhibitors, their catalytic degradation of normal cellular proteins can potentially cause toxic side effects. Therefore, to achieve targeted release of PROTACs and minimize adverse reactions, researchers are actively exploring diverse controllable PROTACs. In this review, we comprehensively summarize the control strategies to provide a theoretical basis for the innovative application of PROTAC technology.

Controllability and accessibility analysis of nonlinear biosystems

BACKGROUND

We address the problem of determining the controllability and accessibility of nonlinear biosystems. We consider models described by affine-in-inputs ordinary differential equations, which are adequate for a wide array of biological processes. Roughly speaking, the controllability of a dynamical system determines the possibility of steering it from an initial state to any point in its neighbourhood; accessibility is a weaker form of controllability.

METHODS

While the methodology for analysing the controllability of linear systems is well established, its generalization to the nonlinear case has proven elusive. Thus, a number of related but different properties - including different versions of accessibility, reachability or weak local controllability - have been defined to approach its study, and several partial results exist in lieu of a general test. Here, leveraging the applicable results from differential geometric control theory, we source sufficient conditions to assess nonlinear controllability, as well as a necessary and sufficient condition for accessibility.

RESULTS

We develop an algorithmic procedure to evaluate these conditions efficiently, and we provide its open source implementation. Using this software tool, we analyse the accessibility and controllability of a number of models of biomedical interest. While some of them are fully controllable, we find others that are not, as is the case of some models of EGF and NFκB signalling networks.

CONCLUSIONS

The contributions in this paper facilitate the accessibility and controllability analysis of nonlinear models, not only in biomedicine but also in other areas in which they have been rarely performed to date.

ϵ-Controllability/ϵ-Observability of linear switched sampled-data systems with the non-equidistant time schedule

In this work, a novel perspective is developed to investigate the property of controllability/observability of linear switched sampled-data systems under the non-equidistant sampling schedule. In this regard, two new notions are introduced as ϵ-controllability and ϵ-observability to create a feasible ground for controlling and observing linear switched sampled-data systems with any initial time chosen from outside of ϵ neighborhood of switching instants. The main motivation is to control and observe the given switched sampled-data system, which consists of a finite number of discrete-time sub-systems within each sub-system. Hence, the system requires a lower number of sampling times for ϵ-controllability and ϵ-observability compared to the original notions of controllability and observability in this context. Although the number of sampling times in a certain time interval increases whenever ϵ tends to zero, the number of sampling candidates required for ϵ-controllability and ϵ-observability becomes finite. Numerical experiments are performed on several continuous time switched linear systems, and ϵ-controllability and ϵ-observability of their corresponding switched sampled-data systems are derived for various ϵ values under constructed non-equidistant sampling patterns.

Improved multi-agent controllability processing technique based on equitable partition

In this paper, we study the controllability of multi-agent systems by equitable partition and automorphism. For the case that cells are incompletely connected outside but completely connected inside, a necessary condition for controllability is given from the perspective of the rank of connection matrix. For the case of multiple cells being completely connected outside and incompletely connected inside, in terms of the eigenvalues and eigenvectors of L and L_π, several sufficient and necessary conditions for controllability are presented. Once the quotient graph is controllable under single input or all nodes in nontrivial cells are leaders, the lower bound of controllable subspace is determined. Finally, we give the gap between the necessary condition and the sufficient condition for controllability from the aspect of equitable partition. One highlight of the results in this paper is that we show sufficient conditions to judge controllability by equitable partition and automorphism, which, for specific cases, provides one method that how to break through the defect that equitable partition can only obtain necessary conditions.

Human and machine drivers: Sharing control, sharing responsibility

Machines are empowered with ever-increasing agency and decision-making authority to augment or even replace humans in various settings, making responsibility attribution less straightforward when they cause harm. Focusing on their applications in transportation, we consider human judgments of responsibility for automated vehicle crashes through a cross-national survey (N = 1657) and design hypothetical crashes after the 2018 Uber automated vehicle crash reportedly caused by a distracted human driver and an inaccurate machine driver. We examine the association between automation level-the human and machine drivers have different levels of agency (i.e., the human as a supervisor, backup driver, and mere passenger, respectively)-and human responsibility through the lens of perceived human controllability. We show the negative association between automation level and human responsibility, partly mediated by perceived human controllability, regardless of the involved responsibility metric (rating and allocation), the nationality of the involved participant (China and South Korea), and crash severity (injury and fatality). When the human and machine drivers in a conditionally automated vehicle jointly cause a crash (e.g., the 2018 Uber crash), the human driver and car manufacturer are asked to share responsibility. Our findings imply that the driver-centric tort law needs to be control-centric. They offer insights for attributing human responsibility for crashes involving automated vehicles.

Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy

Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ-band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ-band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de-/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME.

Rapid fabrication of the Au hexagonal cone arrays for SERS applications

This study performed trace detection using surface-enhanced Raman scattering (SERS) on Au hexagonal cone arrays (Au-HCAs). Uniform porous anodized aluminum oxide (AAO) templates were used, and an Ag film with a cone cavity was prepared using a thermal deposition technique. Next, a series of homogeneous Au-HCAs were prepared controllably via electrodeposition growth technology. The prepared Au-HCAs were used as SERS substrates, and according to the experimental results, the optimal electrodeposition time is 600 s. At this time, Au-HCAs had the highest SERS activity. The detection limit of R6G was 10^-9 M, exhibiting high reproducibility and high uniformity at 10^-6 M, indicating that Au-HCAs had good stability. Moreover, a good linear correlation between the Raman intensity and the molecular concentration endowed Au-HCAs with good quantitative analysis ability. Therefore, the Au-HCAs exhibited great potential for qualitative and quantitative detection.

Relationships between cognitive appraisal and roles/personality traits in basic life support

Objective

To examine the relationship between the cognitive assessment of stress (cognitive appraisal) caused in a scenario requiring basic life support (BLS) and the roles during BLS/personality traits in nursing students.

Methods

We conducted an anonymous self-administered questionnaire survey for 264 freshman and senior nursing students. The study period was one month from June 2019. The questionnaire included characteristics, roles (active involvement group/passive involvement group/no involvement group), Cognitive Appraisal Rating Scale (CARS), and Maudsley Personality Inventory (MPI). We only included data for female students (107 people) in the analysis because very little data is available for male students. The Mann-Whitney test was used for the comparison between two groups and the Kruskal-Wallis test was used for the comparison between three groups. The significance level was set at p<0.05.

Results

The total number of responses was 133 (50.4%), and the number of valid responses was 107 (40.5%). As a result of analyzing the relationship between the role and the CARS subscale, the controllability of the active and passive involvement groups was significantly lower than that of the no involvement group (p=0.046). Also, the analysis of the relationship between the grade and the CARS subscale showed that the controllability was significantly lower in freshmen than seniors (p=0.020).

Conclusion

This study showed the relationship between controllability and cognitive appraisal of stress in the simulation scenario of BLS. Therefore, it was suggested that support for improving controllability is necessary as a preventive measure to reduce the stress associated with BLS.

Longitudinal association of executive function and structural network controllability in the aging brain

Executive function encompasses effortful cognitive processes that are particularly susceptible to aging. Functional brain networks supporting executive function-such as the frontoparietal control network and the multiple demand system-have been extensively investigated. However, it remains unclear how structural networks facilitate and constrain the dynamics of functional networks to contribute to aging-related executive function declines. We examined whether changes in structural network modal controllability-a network's ability to facilitate effortful brain state transitions that support cognitive functions-are associated with changes in executive function cross-sectionally and longitudinally. Diffusion-weighted imaging and neuropsychological testing were conducted at two time points (Time 1: ages 56 to 66, N = 172; Time 2: ages 61 to 70, N = 267) in community-dwelling men from the Vietnam Era Twin Study of Aging. An executive function factor score was computed from six neuropsychological tasks. Structural networks constructed from white matter connectivity were used to estimate modal controllability in control network and multiple demand system. We showed that higher modal controllability in control network and multiple demand system was associated with better executive function at Time 2, after controlling for age, young adult general cognitive ability, and physical health status. Moreover, changes in executive function over a period of 5 to 6 years (Time 1-Time 2, N = 105) were associated with changes in modal controllability of the multiple demand system and weakly in the control network over the same time period. These findings suggest that changes in the ability of structural brain networks in facilitating effortful brain state transitions may be a key neural mechanism underlying aging-related executive function declines and cognitive aging.

Leader-follower controllability of signed networks

This study addresses leader-follower controllability of signed multi-agent networks with fixed and switching interactions (topologies), respectively, where weighted edges between agents may be positive or negative. In other words, there exist cooperative interactions (corresponding to positive edges) and antagonistic interactions (corresponding to negative edges) between agents in the multi-agent networks depicted by signed graphs. The goal of this study is to find the criteria of controllability for signed multi-agent networks, that is, how exactly do cooperation and antagonism affect controllability? It is proven that the followers of multi-agent networks under structurally balanced conditions can be controlled to the desired states if the leaders are chosen from the same partitioned subset. In addition, a signed multi-agent network with simultaneously structurally balanced conditions can be switching controllable even though each subsystem is uncontrollable. The leaders' selection is also discussed.

More engagement in inefficient avoidance through partial reinforcement

BACKGROUND AND OBJECTIVES

In anxiety-related disorders, excessive avoidance often coexists with an impaired sense of control over external threats. In contrast, lab studies have shown that avoidance responding increase with higher objective controllability over threat, accompanied with more confidence in the effectiveness of the avoidance response. One reason for this divergence could be that those lab studies are overly simplistic with a single, avoidable threat.

METHODS

We conducted an experiment that additionally included a completely uncontrollable threat, and we manipulated the reinforcement rate of the avoidance response to the (semi-)controllable threat (75% versus 100%).

RESULTS

The 100% group showed increased avoidance to the controllable threat and decreased avoidance to the unavoidable threat over learning. Interestingly, compared to the 100% group, the 75% group displayed less confidence in their avoidance to the controllable threat and they avoided the uncontrollable threat more often.

LIMITATIONS

Only two reinforcement rates of effective avoidance were included, which may limit the generalizability of the current findings. Perceived control was not directly measured.

CONCLUSIONS

Lower reinforcement rates create ambiguity between effective and ineffective situations of avoidance, which engenders generalization of unpredictability from effective to ineffective situation, thereby driving up ineffective avoidance rates. Partially reinforced effective avoidance responses and elevated ineffective avoidance responses together lead to more exposure to uncontrollable threat, weakening the sense of control over the threat, which could further increase avoidance behaviors. Controllability is often overlooked in avoidance research but can be key to understanding the development of maladaptive avoidance behaviors.

Augmented reality-delivered product information at the point of sale: when information controllability backfires

Augmented reality-delivered product information (ARPI) can overcome the limited space at the point of sale to inform shoppers on demand and will therefore become more widespread in brick-and-mortar stores. To fill the void of academic research, this paper develops a model of how consumers process ARPI and how ARPI can shape brand image and purchase intentions. Making use of the cues-filtered-out theory, this paper suggests that the effect of ARPI controllability depends on information detailedness. An unintended backfire effect of controllability occurs when the accessible information is detailed, which is explained by the mediating process via perceived comprehensiveness. This backfire effect is a risk primarily in busy shopping times. The main experiment conducted in a hypermarket and four follow-up studies (using field, lab, and video settings) empirically confirm the proposed model on the basis of different data sources, including usage tracking, questionnaires, and scanner data. The paper derives managerial implications and outlines directions for future research.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11747-022-00855-w.

The N -Link Swimmer in Three Dimensions: Controllability and Optimality Results

The controllability of a fully three-dimensional N -link swimmer is studied. After deriving the equations of motion in a low Reynolds number fluid by means of Resistive Force Theory, the controllability of the minimal 2-link swimmer is tackled using techniques from Geometric Control Theory. The shape of the 2-link swimmer is described by two angle parameters. It is shown that the associated vector fields that govern the dynamics generate, via taking their Lie brackets, all eight linearly independent directions in the combined configuration and shape space, leading to controllability; the swimmer can move from any starting configuration and shape to any target configuration and shape by operating on the two shape variables. The result is subsequently extended to the N -link swimmer. Finally, the minimal time optimal control problem and the minimization of the power expended are addressed and a qualitative description of the optimal strategies is provided.

Environmental certainty influences the neural systems regulating responses to threat and stress

Flexible calibration of threat responding in accordance with the environment is an adaptive process that allows an animal to avoid harm while also maintaining engagement of other goal-directed actions. This calibration process, referred to as threat response regulation, requires an animal to calculate the probability that a given encounter will result in a threat so they can respond accordingly. Here we review the neural correlates of two highly studied forms of threat response suppression: extinction and safety conditioning. We focus on how relative levels of certainty or uncertainty in the surrounding environment alter the acquisition and application of these processes. We also discuss evidence indicating altered threat response regulation following stress exposure, including enhanced fear conditioning, and disrupted extinction and safety conditioning. To conclude, we discuss research using an animal model of coping that examines the impact of stressor controllability on threat responding, highlighting the potential for previous experiences with control, or other forms of coping, to protect against the effects of future adversity.

Controllability and state feedback control of a cardiac ionic cell model

A phenomenon called alternans, which is a beat-to-beat alternation in action potential (AP) duration, sometimes precedes fatal cardiac arrhythmias. Alternans-suppressing electrical stimulus protocols are often represented as perturbations to the dynamics of membrane potential or AP duration variables in nonlinear models of cardiac tissue. Controllability analysis has occasionally been applied to cardiac AP models to determine whether different control or perturbation strategies are capable of suppressing alternans or other unwanted behavior. Since almost all previous cardiac controllability studies have focused on low-dimensional models, we conducted the present study to assess controllability of a higher-dimensional model, specifically the Luo Rudy dynamic (LRd) model of a cardiac ventricular myocyte. Higher-dimensional models are of interest because they provide information on the influence of a wider range of measurable quantities, including ionic concentrations, on controllability. After computing modal controllability measures, we found that larger eigenvalues of a linearized LRd model were on average more strongly controllable through perturbations to calcium-ion concentrations compared with perturbations to other variables. When only membrane potential was adjusted, the best time to apply perturbations (in the sense of maximizing controllability of the largest alternans eigenvalue) was near the AP peak time for shorter cycle lengths. Controllability results were found to be similar for both the default model parameters and for an alternans-promoting parameter set. Additionally, we developed several alternans-suppressing state feedback controllers that were tested in simulations. For the scenarios examined, our controllability measures correctly predicted which strategies and perturbation timings would lead to better feedback controller performance.

Modeling and staged assessments of the controllability of spread for repeated outbreaks of COVID-19

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been causing an outbreak of a new type of pneumonia globally, and repeated outbreaks have already appeared. Among the studies on the spread of the COVID-19, few studies have investigated the repeated outbreaks in stages, and the quantitative condition of a controllable spread has not been revealed. In this paper, a brief compartmental model is developed. The effective reproduction number (ERN) of the model is interpreted by the ratio of net newly infectious individuals to net isolation infections to assess the controllability of the spread of COVID-19. It is found that the value of the ERN at the inflection point of the pandemic is equal to one. The effectiveness of the quarantine, even the treatment, is parametrized in various stages with Gompertz functions to increase modeling accuracy. The impacts of the vaccinations are discussed by adding a vaccinated compartment. The results show that the sufficient vaccinations can make the inflection point appear early and significantly reduce subsequent increases in newly confirmed cases. The analysis of the ERNs of COVID-19 in the United States, Spain, France, and Peru confirms that the condition of a repeated outbreak is to relax or lift the interventions related to isolation and quarantine interventions to a level where the ERN is greater than one.

Stressor controllability modulates the stress response in fish

BACKGROUND

In humans the stress response is known to be modulated to a great extent by psychological factors, particularly by the predictability and the perceived control that the subject has of the stressor. This psychological dimension of the stress response has also been demonstrated in animals phylogenetically closer to humans (i.e. mammals). However, its occurrence in fish, which represent a divergent vertebrate evolutionary lineage from that of mammals, has not been established yet, and, if present, would indicate a deep evolutionary origin of these mechanisms across vertebrates. Moreover, the fact that psychological modulation of stress is implemented in mammals by a brain cortical top-down inhibitory control over subcortical stress-responsive structures, and the absence of a brain cortex in fish, has been used as an argument against the possibility of psychological stress in fish, with implications for the assessment of fish sentience and welfare. Here, we have investigated the occurrence of psychological stress in fish by assessing how stressor controllability modulates the stress response in European seabass (Dicentrarchus labrax).

RESULTS

Fish were exposed to either a controllable or an uncontrollable stressor (i.e. possibility or impossibility to escape a signaled stressor). The effect of loss of control (possibility to escape followed by impossibility to escape) was also assessed. Both behavioral and circulating cortisol data indicates that the perception of control reduces the response to the stressor, when compared to the uncontrollable situation. Losing control had the most detrimental effect. The brain activity of the teleost homologues to the sensory cortex (Dld) and hippocampus (Dlv) parallels the uncontrolled and loss of control stressors, respectively, whereas the activity of the lateral septum (Vv) homologue responds in different ways depending on the gene marker of brain activity used.

CONCLUSIONS

These results suggest the psychological modulation of the stress response to be evolutionary conserved across vertebrates, despite being implemented by different brain circuits in mammals (pre-frontal cortex) and fish (Dld-Dlv).

The Link Between COVID-19, Anxiety, and Religious Beliefs in the United States and the United Kingdom

Research has shown that stress impacts on people's religious beliefs. However, several aspects of this effect remain poorly understood, for example regarding the role of prior religiosity and stress-induced anxiety. This paper explores these aspects in the context of the recent coronavirus pandemic (COVID-19). The latter has impacted dramatically on many people's well-being; hence it can be considered a highly stressful event. Through online questionnaires administered to UK (n = 140) and USA (n = 140) citizens professing either Christian faith or no religion, this paper examines the impact of the coronavirus crisis upon common people's religious beliefs. Anxiety about the coronavirus and prior religiosity showed an interaction effect upon change in religious beliefs (t(276) = 2.27, p = .024): for strong believers higher anxiety about coronavirus was associated with increased strengthening of religious beliefs (r = .249), while for non-believers higher anxiety about coronavirus was associated with increased scepticism towards religious beliefs (r = - .157). These observations are consistent with the notion that stress-induced anxiety enhances support for an individual's existing ideology already embraced before a stressful event occurs. This study sheds light on the psychological and cultural implications of the coronavirus crisis, which represents one of the most serious health emergencies in recent times.

Structure-informed functional connectivity driven by identifiable and state-specific control regions

Describing how the brain anatomical wiring contributes to the emergence of coordinated neural activity underlying complex behavior remains challenging. Indeed, patterns of remote coactivations that adjust with the ongoing task-demand do not systematically match direct, static anatomical links. Here, we propose that observed coactivation patterns, known as functional connectivity (FC), can be explained by a controllable linear diffusion dynamics defined on the brain architecture. Our model, termed structure-informed FC, is based on the hypothesis that different sets of brain regions controlling the information flow on the anatomical wiring produce state-specific functional patterns. We thus introduce a principled framework for the identification of potential control centers in the brain. We find that well-defined, sparse, and robust sets of control regions, partially overlapping across several tasks and resting state, produce FC patterns comparable to empirical ones. Our findings suggest that controllability is a fundamental feature allowing the brain to reach different states.

Understanding how brain anatomy promotes particular patterns of coactivations among neural regions is a key challenge in neuroscience. This challenge can be addressed using network science and systems theory. Here, we propose that coactivations result from the diffusion of information through the network of anatomical links connecting brain regions, with certain regions controlling the dynamics. We translate this hypothesis into a model called structure-informed functional connectivity, and we introduce a framework for identifying control regions based on empirical data. We find that our model produces coactivation patterns comparable to empirical ones, and that distinct sets of control regions are associated with different functional states. These findings suggest that controllability is an important feature allowing the brain to reach different states.

Worry, Severity, Controllability, and Preventive Behaviours of COVID-19 and Their Associations with Mental Health of Turkish Healthcare Workers Working at a Pandemic Hospital

Previous research suggests that psychological and behavioural factors such as worry, severity, controllability, and preventive behaviours are associated with mental health and well-being. Less is known about simultaneous effects of those factors in predicting mental health and well-being. This study aimed to present the prevalence of mental health problems and identify the predictors of mental health and subjective well-being of healthcare workers during the COVID-19 pandemic. Participants included 245 healthcare workers (M_age = 33.16 ± 7.33; 50.61% females) from a pandemic hospital in Turkey. Healthcare workers reported mild/severe depression, anxiety, and stress. Females tended to be more vulnerable to developing psychiatric symptoms. Worry, severity, and controllability significantly predicted depression, anxiety, stress, and subjective well-being while preventive behaviours only predicted subjective well-being. These findings suggest the importance of assessing healthcare workers’ experiences of mental health and subjective well-being and their associated factors to assist mental health providers tailor assessments and treatment during a pandemic.

Self-choice preference: The propensity to under-delegate irrespective of sense of control

People are more likely to make choices themselves than delegate to an agent, even when it may not be the most optimal decision based on a cost-benefit analysis. Previous studies have demonstrated that retaining authority and controllability might be the primary reason for preferring self-choice. The current study asks whether impairment of controllability associated with self-choice can increase the rate of delegation and whether there are self-other discrepancies in self-choice preference. In three studies, we directly manipulated participants' controllability associated with choice through literal instructions (experiment 1) and visual presentation (experiments 2 and 3). We found that participants showed a robust propensity to under-delegate even when they were aware of their impaired controllability associated with self-choice. Moreover, only 40% impairment of controllability (but not 20%) can decrease the propensity to under-delegate. This trend differed between decision-for-self and decision-for-other. These findings suggest that pursuing a sense of control cannot fully explain self-choice preference and appears to occur equally in decisions for oneself as well as for others.

Tampering with Nature: A Systematic Review

Tampering with nature has been shown to be a strong, and sometimes even the strongest, predictor of the risk perception and acceptance of various technologies and behaviors, including environmental technologies, such as geoengineering. It is therefore helpful to understand what tampering with nature is as a construct, to which factors it relates, and when a technology or behavior is perceived as such. By means of a systematic review, we show that very little systematic research has been conducted on tampering with nature. Because tampering with nature has not yet been clearly defined, no systematic operationalization of tampering with nature has been used in the current literature. We show that tampering with nature is often used interchangeably with other constructs, such as naturalness. Based on the literature, we suggest that tampering with nature is related to and possibly influenced by three other constructs, which are naturalness, morality, and controllability. We discuss the influence of tampering with nature on the acceptance and risk perception of various technologies and behaviors and make suggestions for future research needs in order to better understand this construct.

Editorial: Network Communication in the Brain

Communication models describe the flow of signals among nodes of a network. In neural systems, communication models are increasingly applied to investigate network dynamics across the whole brain, with the ultimate aim to understand how signal flow gives rise to brain function. Communication models range from diffusion-like processes to those related to infectious disease transmission and those inspired by engineered communication systems like the internet. This Focus Feature brings together novel investigations of a diverse range of mechanisms and strategies that could shape communication in mammal whole-brain networks.

Target controllability with minimal mediators in complex biological networks

Controllability of a complex network system is related to finding a set of minimum number of nodes, known as drivers, controlling which allows having a full control on the dynamics of the network. For some applications, only a portion of the network is required to be controlled, for which target control has been proposed. Often, along the controlling route from driver nodes to target nodes, some mediators (intermediate nodes) are also unwillingly controlled, which might cause various side effects. In controlling cancerous cells, unwillingly controlling healthy cells, might result in weakening them, thus affecting the immune system against cancer. This manuscript proposes a suitable candidate solution to the problem of finding minimum number of driver nodes under minimal mediators. Although many others have attempted to develop algorithms to find minimum number of drivers for target control, the newly proposed algorithm is the first one that is capable of achieving this goal and at the same time, keeping the number of the mediators to a minimum. The proposed controllability condition, based on path lengths between node pairs, meets Kalman's controllability rank condition and can be applied on directed networks. Our results show that the path length is a major determinant of in properties of the target control under minimal mediators. As the average path length becomes larger, the ratio of drivers to target nodes decreases and the ratio of mediators to targets increases. The proposed methodology has potential applications in biological networks. The source code of the algorithm and the networks that have been used are available from the following link: https://github.com/LBBSoft/Target-Control-with-Minimal-Mediators.git.

Just data? Solidarity and justice in data-driven medicine

This paper argues that data-driven medicine gives rise to a particular normative challenge. Against the backdrop of a distinction between the good and the right, harnessing personal health data towards the development and refinement of data-driven medicine is to be welcomed from the perspective of the good. Enacting solidarity drives progress in research and clinical practice. At the same time, such acts of sharing could-especially considering current developments in big data and artificial intelligence-compromise the right by leading to injustices and affecting concrete modes of individual self-determination. In order to address this potential tension, two key elements for ethical reflection on data-driven medicine are proposed: the controllability of information flows, including technical infrastructures that are conducive towards controllability, and a paradigm shift towards output-orientation in governance and policy.

What is and what never should have been: Children's causal and counterfactual judgments about the same events

Substantial research with adults has characterized the contents of individuals' counterfactual thoughts. In contrast, little is known about the types of events children invoke in their counterfactual thoughts and how they compare with their causal ascriptions. In the current study, we asked children open-ended counterfactual and causal questions about events in which a character's action enabled a force of nature to cause a minor mishap. Children aged 3.5-8 years (N = 160) tended to invoke characters' actions in their counterfactual judgments to explain how an event could have been prevented (e.g., "She should have closed the window") and tended to invoke forces of nature in their causal judgments (e.g., "The rain got it wet"). Younger children were also significantly more likely than older children to invoke forces of nature in their counterfactuals (e.g., "It shouldn't have rained"). These results indicate that, similar to reasoning patterns found in adults, children tend to focus on controllable enabling conditions when reasoning counterfactually, but the results also point to some developmental differences. The developmental similarities suggest that counterfactual reasoning may serve a similar function from middle childhood through adulthood.

Clarifying stress-internalizing associations: Stress frequency and appraisals of severity and controllability are differentially related to depression-specific, anxiety-specific, and transdiagnostic internalizing factors

BACKGROUND

Dependent (self-generated) stress is a strong risk factor for depression and anxiety, but perceptions of stress can alter its impact. Appraisals of dependent stress controllability and severity additionally relate to depression and anxiety over and above stress exposure. Due to the high comorbidity of depression and anxiety, it is unclear whether dependent stress frequency and appraisals relate specifically to depression or anxiety or are transdiagnostically associated shared aspects of internalizing disorders. Consistent with the tripartite model, the current study represented internalizing symptoms with three latent factors - depression-specific, anxiety-specific, and common internalizing - and tested how dependent stress frequency and appraisals of controllability and severity were associated with these factors.

METHODS

Bifactor modeling was used to create the latent internalizing factors in a treatment-seeking sample of emerging adults (n = 356). Structural equation models tested dependent stress frequency and appraisals of controllability and severity as predictors of these latent factors.

RESULTS

Dependent stress frequency was associated with common internalizing while perceived controllability was associated uniquely with depression-specific variance. Continuous stress severity was not associated with latent factors, but high-severity stressors were associated with anxiety-specific variance.

LIMITATIONS

Without longitudinal data conclusions regarding temporal directionality cannot be made. Participants' appraisals of stressors could not be compared to expert ratings.

CONCLUSIONS

Dependent stress frequency, controllability appraisals, and high-severity stressful events have distinct links with different dimensions of internalizing psychopathology. This suggests there may be several distinct mediating mechanisms between stress constructs and psychopathology, which have potential to serve as targets for intervention.

A Machine Learning Approach to Characterize the Modulation of the Hippocampal Rhythms Via Optogenetic Stimulation of the Medial Septum

The medial septum (MS) is a potential target for modulating hippocampal activity. However, given the multiple cell types involved, the changes in hippocampal neural activity induced by MS stimulation have not yet been fully characterized. We combined MS optogenetic stimulation with local field potential (LFP) recordings from the hippocampus and leveraged machine learning techniques to explore how activating or inhibiting multiple MS neuronal subpopulations using different optical stimulation parameters affects hippocampal LFP biomarkers. First, of the seven different optogenetic viral vectors used for modulating different neuronal subpopulations, only two induced a substantial change in hippocampal LFP. Second, we found hippocampal low-gamma band to be most effectively modulated by the stimulation. Third, the hippocampal biomarkers were sensitive to the optogenetic virus type and the stimulation frequency, establishing those parameters as the critical ones for the regulation of hippocampal biomarker activity. Last, we built a Gaussian process regression model to describe the relationship between stimulation parameters and activity of the biomarker as well as to identify the optimal parameters for biomarker modulation. This new machine learning approach can further our understanding of the effects of neural stimulation and guide the selection of optimal parameters for neural control.

A dual controllability analysis of influenza virus-host protein-protein interaction networks for antiviral drug target discovery

Background

Host factors of influenza virus replication are often found in key topological positions within protein-protein interaction networks. This work explores how protein states can be manipulated through controllability analysis: the determination of the minimum manipulation needed to drive the cell system to any desired state. Here, we complete a two-part controllability analysis of two protein networks: a host network representing the healthy cell state and an influenza A virus-host network representing the infected cell state. In this context, controllability analyses aim to identify key regulating host factors of the infected cell’s progression. This knowledge can be utilized in further biological analysis to understand disease dynamics and isolate proteins for study as drug target candidates.

Results

Both topological and controllability analyses provide evidence of wide-reaching network effects stemming from the addition of viral-host protein interactions. Virus interacting and driver host proteins are significant both topologically and in controllability, therefore playing important roles in cell behavior during infection. Functional analysis finds overlap of results with previous siRNA studies of host factors involved in influenza replication, NF-kB pathway and infection relevance, and roles as interferon regulating genes. 24 proteins are identified as holding regulatory roles specific to the infected cell by measures of topology, controllability, and functional role. These proteins are recommended for further study as potential antiviral drug targets.

Conclusions

Seasonal outbreaks of influenza A virus are a major cause of illness and death around the world each year with a constant threat of pandemic infection. This research aims to increase the efficiency of antiviral drug target discovery using existing protein-protein interaction data and network analysis methods. These results are beneficial to future studies of influenza virus, both experimental and computational, and provide evidence that the combination of topology and controllability analyses may be valuable for future efforts in drug target discovery.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2917-z) contains supplementary material, which is available to authorized users.

Controllability, Matching Ratio and Graph Convergence

There is an important parameter in control theory which is closely related to the directed matching ratio of the network, as shown in the paper of Liu et al. (Nature 473:167-173, 2011). We give proofs of two main statements of Liu et al.  (2011) on the directed matching ratio, which were based on numerical results and heuristics from statistical physics. First, we show that the directed matching ratio of directed random networks given by a fix sequence of degrees is concentrated around its mean. We also examine the convergence of the (directed) matching ratio of a random (directed) graph sequence that converges in the local weak sense, and generalize the result of Elek and Lippner (Proc Am Math Soc 138(8):2939-2947, 2010). We prove that the mean of the directed matching ratio converges to the properly defined matching ratio parameter of the limiting graph. We further show the almost sure convergence of the matching ratios for the most widely used families of scale-free networks, which was the main motivation of Liu et al.  (2011).

On the number of driver nodes for controlling a Boolean network when the targets are restricted to attractors

It is known that many driver nodes are required to control complex biological networks. Previous studies imply that O(N) driver nodes are required in both linear complex network and Boolean network models with N nodes if an arbitrary state is specified as the target. In order to cope with this intrinsic difficulty, we consider a special case of the control problem in which the targets are restricted to attractors. For this special case, we mathematically prove under the uniform distribution of states in basins that the expected number of driver nodes is only O(log₂N+log₂M) for controlling Boolean networks, where M is the number of attractors. Since it is expected that M is not very large in many practical networks, the new model requires a much smaller number of driver nodes. This result is based on discovery of novel relationships between control problems on Boolean networks and the coupon collector's problem, a well-known concept in combinatorics. We also provide lower bounds of the number of driver nodes as well as simulation results using artificial and realistic network data, which support our theoretical findings.

From partial and high automation to manual driving: Relationship between non-driving related tasks, drowsiness and take-over performance

BACKGROUND

Until the level of full vehicle automation is reached, users of vehicle automation systems will be required to take over manual control of the vehicle occasionally and stay fallback-ready to some extent during the drive. Both, drowsiness caused by inactivity and the engagement in distracting non-driving related tasks (NDRTs) such as entertainment or office work have been suggested to impair the driver's ability to safely handle these transitions of control. Thus, it is an open question whether engagement in NDRTs will impair or improve take-over performance.

METHOD

In a motion-based driving simulator, 64 participants completed an automated drive that lasted either one or two hours using either a partially or highly automated driving system. In the partially automated driving condition, a warning was issued after several seconds when drivers took both hands off the steering wheel, while the highly automated driving system allowed hands-off driving permanently. Drivers were allowed to bring along their smartphones and to use them during the drive. They engaged in a wide variety of NDRTs such as reading or using social media. At the end of the session, drivers had to react to a sudden lead vehicle braking event. In the partial automation condition, there was no take-over request (TOR) to notify the drivers of the braking vehicle, while in the highly automated condition, the situation happened right after the drivers had deactivated the automation in response to a TOR. The lead time of the TOR was set at 8 s. Driver's level of drowsiness, workload (visual, mental and motoric) from carrying out the NDRT and motivational appeal of the NDRT right before the control transition were video-coded and used to predict the outcome of the braking event (i.e., reaction and system deactivation times, minimal Time-to-collision (TTC) and self-reported criticality) with a multiple regression approach.

RESULTS

In the partial automation condition, reaction times to the braking vehicle and situation criticality as measured by the minimum TTC could be well predicted. Main predictors for increased reaction time were drowsiness and motivational appeal of the NDRT. However, visual and mental demand associated with NDRTs did decrease reaction time, suggesting that the NDRT helped the drivers to maintain alertness during the partially automated drive. Accordingly, drowsiness and motivational appeal of the NDRT increased situation criticality, while cognitive load due to the NDRT decreased it. In the highly automated condition, however, it was not possible to predict system deactivation time (in reaction to the TOR), brake reaction time to the braking vehicle and situation criticality by observed drowsiness and NDRT engagement.

DISCUSSION

The results suggest a relationship between the driver's drowsiness and NDRT engagement in partial automation but not in highly automated driving. Several explanations for this finding are discussed. It could be possible that the lead time of 8 s might have given the drivers enough time to complete the driver state transition process from executing NDRTs to manual driving, putting them in a position to be able to cope with the driving event, while this was not possible in the partial automation condition. Methodological issues that might have led to a non-detection of an effect of drowsiness or NDRT engagement in the highly automated driving condition, such as the sample size and sensitivity of the observer ratings, are also discussed.

Calculation of controllability and observability matrices for special case of continuous-time multi-order fractional systems

In this paper, controllability and observability matrices for pseudo upper or lower triangular multi-order fractional systems are derived. It is demonstrated that these systems are controllable and observable if and only if their controllability and observability matrices are full rank. In other words, the rank of these matrices should be equal to the inner dimension of their corresponding state space realizations. To reduce the computational complexities, these matrices are converted to simplified matrices with smaller dimensions. Numerical examples are provided to show the usefulness of the mentioned matrices for controllability and observability analysis of this case of multi-order fractional systems. These examples clarify that the duality concept is not necessarily true for these special systems.

Impact of controllability on pain and suffering

Supplemental Digital Content is Available in the Text.

Introduction:

Chronic pain and pain-related suffering are major health problems. The lack of controllability of experienced pain seems to greatly contribute to the extent of suffering. This study examined how controllability affects the perception of pain and pain-related suffering, and the modulation of this effect by beliefs and emotions such as locus of control of reinforcement, pain catastrophizing, and fear of pain.

Methods:

Twenty-six healthy subjects received painful electric stimulation in both controllable and uncontrollable conditions. Visual analogue scales and the “Pictorial Representation of Illness and Self Measure” were used to assess pain intensity, unpleasantness, pain-related suffering, and the level of perceived control. We also investigated nonverbal indicators of pain and suffering such as heart rate, skin conductance, and corrugator electromyogram.

Results:

Controllability selectively reduced the experience of pain-related suffering, but did not affect pain intensity or pain unpleasantness. This effect was modulated by chance locus of control but was unrelated to fear of pain or catastrophizing. Physiological responses were not affected by controllability. In a second sample of 25 participants, we varied the instruction. The effect of controllability on pain-related suffering was only present when instructions focused on the person being able to stop the pain.

Discussion:

Our data suggest that the additional measure of pain-related suffering may be important in the assessment of pain and may be more susceptible to the effects of perceived control than pain intensity and unpleasantness. We also show that this effect depends on personal involvement.

Regenerative braking failures in battery electric vehicles and their impact on the driver

A unique feature of battery electric vehicles (BEV) is their regenerative braking system (RBS) to recapture kinetic energy in deceleration maneuvers. If such a system is triggered via gas pedal, most deceleration maneuvers can be executed by just using this pedal. This impacts the driving task as different deceleration strategies can be applied. Previous research has indicated that a RBS failure leading to a sudden reduced deceleration represents an adverse event for BEV drivers. In the present study, we investigated such a failure's impact on the driver's evaluation and behavior. We conducted an experiment on a closed-off test track using a modified BEV that could temporarily switch off the RBS. One half of the 44 participants in the study received information about an upcoming RBS failure whereas the other half did not. While 91% of the drivers receiving prior information noticed the RBS failure, only 48% recognized it in the "uniformed" group. In general, the failure and the perception of its occurrence influenced the driver's evaluation and behavior more than receiving prior information. Nevertheless, under the tested conditions, drivers kept control and were able to compensate for the RBS failure. As the participants drove quite simple maneuvers in our experiment, further studies are needed to validate our findings using more complex driving settings. Given that RBS failures could have severe consequences, appropriate information and warning strategies for drivers are necessary.

Anxiety moderates the effects of stressor controllability and cognitive reappraisal on distress following aversive exposure: An experimental investigation

BACKGROUND AND OBJECTIVES

Emerging evidence suggests that the effectiveness of cognitive reappraisal (CR) depends on different factors, including the individual's psychological wellbeing (e.g., level of anxiety) and the context in which the strategy is used (e.g., stressor controllability). The present study aimed to investigate the emotional (negative affect) and physiological (skin conductance levels) effects of emotion regulation following exposure to controllable versus uncontrollable stress.

METHODS

Ninety-five undergraduate students completed measures assessing anxiety, and were randomly assigned to a condition in which they had (a) control or (b) no control over the viewing duration of distressing film clips, and were then instructed to either (a) cognitively reappraise or (b) ruminate about the clips.

RESULTS

There were no significant interactions between controllability, emotion regulation, and pre-post changes in responses. However, individual differences in anxiety moderated the effects of controllability and emotion regulation on distress responses. For participants low in anxiety, CR was related to smaller increases in distress following uncontrollable than controllable stress. This pattern was not observed for those high in anxiety following stress exposure.

LIMITATIONS

This study used a non-clinical sample, limiting the generalizability of the findings.

CONCLUSIONS

These findings indicate that the utility of CR may depend upon contextual factors such as stressor controllability, and individual differences in psychological symptoms.

Evolution of control with learning classifier systems

In this paper we describe the application of a learning classifier system (LCS) variant known as the eXtended classifier system (XCS) to evolve a set of 'control rules' for a number of Boolean network instances. We show that (1) it is possible to take the system to an attractor, from any given state, by applying a set of 'control rules' consisting of ternary conditions strings (i.e. each condition component in the rule has three possible states; 0, 1 or #) with associated bit-flip actions, and (2) that it is possible to discover such rules using an evolutionary approach via the application of a learning classifier system. The proposed approach builds on learning (reinforcement learning) and discovery (a genetic algorithm) and therefore the series of interventions for controlling the network are determined but are not fixed. System control rules evolve in such a way that they mirror both the structure and dynamics of the system, without having 'direct' access to either.

Expert-based controllability assessment of control transitions from automated to manual driving

Up to a level of full vehicle automation, drivers will have to be available as a fallback level and take back manual control of the vehicle in case of system limits or failures. Before introducing automated vehicles to the consumer market, the controllability of these control transitions has to be demonstrated. This paper presents a novel procedure for an expert-based controllability assessment of control transitions from automated to manual driving. A standardized rating scheme is developed that allows trained raters to integrate different aspects of driving performance during control transitions (e.g., quality of lateral and longitudinal control, adequateness of signalling to other road users, etc.) into one global controllability measure based on video material of the driving situation. The method is adapted from an existing assessment procedure that has been successfully applied to assess the criticality of driving situations in manual driving conditions (e.g., assessment of substance-induced impairments, assessment of fitness-to-drive of novice drivers). This paper presents the rating procedure, including instructions of how to code relevant qualities of the drivers’ performance with accompanying video-demonstrations, and material used for rater training.

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A rating procedure for an expert-based controllability assessment of control transitions from automated to manual driving based on observation of video material was adapted from an existing method used in studies on manual driving.

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The advantage of this method consists in an integration of different dimensions of driving performance (e.g., operational and tactical driving behaviour, criticality of the situation) into one global controllability measure.

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The method allows an assessment and comparison of diverse take-over scenarios, detached from driver performance variables.

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The accompanying video-based training material allows reproducible and reliable execution of the rating procedure.

The effects of perceived torture controllability on symptom severity of posttraumatic stress, depression and anger in refugees and asylum seekers: A path analysis

Torture is associated with greater psychopathology, however, the specific mechanisms underlying the effects of torture remain unclear. Research suggests that the perceived uncontrollable nature of, rather than the exposure to, torture, influences the development of psychological disorders. Perceived distress during torture has also been shown to influence psychological outcomes. This cross-sectional study explored the relationship between perceived torture controllability, emotions (i.e., anger and fear) during torture, and current posttraumatic stress (PTS), depression and anger symptoms, controlling for the effects of post-migration living difficulties. Data were collected from 108 refugees and asylum seekers in treatment at two psychiatric clinics in Zurich, Switzerland. Path analyses revealed negative correlations between PTS, depression and anger symptoms, and perceived torture controllability, and positive correlations with anger and fear during torture. Furthermore, the effects of perceived torture controllability on PTS and depression symptoms were mediated by fear during torture, and on anger symptoms via anger during torture. This was over and above the effects of post-migration living difficulties on psychological symptoms. The study provides preliminary evidence that perceived uncontrollability and distress during torture might be significant risk factors for current mental health of torture survivors. These findings may have implications for informing interventions for torture survivors.

Effect of different alcohol levels on take-over performance in conditionally automated driving

Automated driving systems are getting pushed into the consumer market, with varying degrees of automation. Most often the driver's task will consist of being available as a fall-back level when the automation reaches its limits. These so-called take-over situations have attracted a great body of research, focusing on various human factors aspects (e.g., sleepiness) that could undermine the safety of control transitions between automated and manual driving. However, a major source of accidents in manual driving, alcohol consumption, has been a non-issue so far, although a false understanding of the driver's responsibility (i.e., being available as a fallback level) might promote driving under its influence. In this experiment, N = 36 drivers were exposed to different levels of blood alcohol concentrations (BACs: placebo vs. 0.05% vs. 0.08%) in a high fidelity driving simulator, and the effect on take-over time and quality was assessed. The results point out that a 0.08% BAC increases the time needed to re-engage in the driving task and impairs several aspects of longitudinal and lateral vehicle control, whereas 0.05% BAC did only go along with descriptive impairments in fewer parameters.

Fronto-limbic dysconnectivity leads to impaired brain network controllability in young people with bipolar disorder and those at high genetic risk

Recent investigations have used diffusion-weighted imaging to reveal disturbances in the neurocircuitry that underlie cognitive-emotional control in bipolar disorder (BD) and in unaffected siblings or children at high genetic risk (HR). It has been difficult to quantify the mechanism by which structural changes disrupt the superimposed brain dynamics, leading to the emotional lability that is characteristic of BD. Average controllability is a concept from network control theory that extends structural connectivity data to estimate the manner in which local neuronal fluctuations spread from a node or subnetwork to alter the state of the rest of the brain. We used this theory to ask whether structural connectivity deficits previously observed in HR individuals (n = 84, mean age 22.4), patients with BD (n = 38, mean age 23.9), and age- and gender-matched controls (n = 96, mean age 22.6) translate to differences in the ability of brain systems to be manipulated between states. Localized impairments in network controllability were seen in the left parahippocampal, left middle occipital, left superior frontal, right inferior frontal, and right precentral gyri in BD and HR groups. Subjects with BD had distributed deficits in a subnetwork containing the left superior and inferior frontal gyri, postcentral gyrus, and insula (p = 0.004). HR participants had controllability deficits in a right-lateralized subnetwork involving connections between the dorsomedial and ventrolateral prefrontal cortex, the superior temporal pole, putamen, and caudate nucleus (p = 0.008). Between-group controllability differences were attenuated after removal of topological factors by network randomization. Some previously reported differences in network connectivity were not associated with controllability-differences, likely reflecting the contribution of more complex brain network properties. These analyses highlight the potential functional consequences of altered brain networks in BD, and may guide future clinical interventions.

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Control theory estimates how neuronal fluctuations spread from local networks.

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We compare brain controllability in bipolar disorder and their high-risk relatives.

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These groups have impaired controllability in networks supporting cognitive and emotional control.

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Weaker connectivity as well as topological alterations contribute to these changes.

Controllability of social networks and the strategic use of random information

Background

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception.

Methods

Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network and considers two well-known strategies for influencing social contexts: One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad hoc metrics which are defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests.

Results

The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills.

Conclusions

These findings support our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable.

Qualitative Analysis of an ODE Model of a Class of Enzymatic Reactions : Some Results on Global Stability of Messenger RNA-MicroRNA Interaction

The present paper analyzes an ODE model of a certain class of (open) enzymatic reactions. This type of model is used, for instance, to describe the interactions between messenger RNAs and microRNAs. It is shown that solutions defined by positive initial conditions are well defined and bounded on [Formula: see text] and that the positive octant of [Formula: see text] is a positively invariant set. We prove further that in this positive octant there exists a unique equilibrium point, which is asymptotically stable and a global attractor for any initial state with positive components; a controllability property is emphasized. We also investigate the qualitative behavior of the QSSA system in the phase plane [Formula: see text]. For this planar system we obtain similar results regarding global stability by using Lyapunov theory, invariant regions and controllability.

Driving performance at lateral system limits during partially automated driving

This study investigated driver performance during system limits of partially automated driving. Using a motion-based driving simulator, drivers encountered different situations in which a partially automated vehicle could no longer safely keep the lateral guidance. Drivers were distracted by a non-driving related task on a touch display or driving without an additional secondary task. While driving in partially automated mode drivers could either take their hands off the steering wheel for only a short period of time (10s, so-called 'Hands-on' variant) or for an extended period of time (120s, so-called 'Hands-off' variant). When the system limit was reached (e.g., when entering a work zone with temporary lines), the lateral vehicle control by the automation was suddenly discontinued and a take-over request was issued to the drivers. Regardless of the hands-off interval and the availability of a secondary task, all drivers managed the transition to manual driving safely. No lane exceedances were observed and the situations were rated as 'harmless' by the drivers. The lack of difference between the hands-off intervals can be partly attributed to the fact that most of the drivers kept contact to the steering wheel, even in the hands-off condition. Although all drivers were able to control the system limits, most of them could not explain why exactly the take-over request was issued. The average helpfulness of the take-over request was rated on an intermediate level. Consequently, providing drivers with information about the reason for a system limit can be recommended.

Social stress models in rodents: Towards enhanced validity

Understanding the role of the social environment in the development of stress related diseases requires a more fundamental understanding of stress. Stress includes not only the stimulus and the response but also the individual appraisal of the situation. The social environment is not only essential for survival it is at the same time an important source of stressors. This review discusses the social stress concept, how it has been studied in rodents in the course of time and some more recent insights into the appraisal process. In addition to the factors controllability and predictability, outcome expectancy and feedback of the victim's own actions during the social stress are suggested to be important factors in the development of stress related disease. It is hypothesized that individual differences in the way in which these factors are used in the appraisal of everyday life situations may explain individual vulnerability.

Micropositioning and Control of an Underactuated Platform for Microscopic Applications

For automation of biological experiments at the micro-scale, highly precise manipulator equipped with a microscope is required. However, current micropositioning stages have several limitations, such as: 1) manual operation, 2) lack of rotational capability, 3) incompatibility with a microscope, and 4) small range of motion (RoM). This research aims to develop a microscope compatible XYθ micropositioning stage with large RoM for phenotyping multiple biological samples rapidly for various microscopic applications. An underactuated planar mechanism, kinematic analysis, and control of the XYθ stage are presented in this paper. The planar mechanism consists of two piezoelectric linear actuators for translational motion capability and two passive revolute joints at the tip of each linear actuator for rotational capability. Based on the kinematic analysis of the stage, controllability and control strategy of the underactuated stage is described. Finally, the feasibility of the micropositioning stage for a general positioning and orienting task is verified by both simulation and tissue core experiments.

Controllability and hippocampal activation during pain expectation in fibromyalgia syndrome

To examine the role of perceived control in pain perception, fibromyalgia patients and healthy controls participated in a reaction time experiment under different conditions of pain controllability. No significant differences between groups were found in pain intensity and unpleasantness ratings. However, during the expectation of uncontrollable pain, patients compared to controls showed higher hippocampal activation. In addition, hippocampal activity during the pain expectation period predicted activation of the posterior cingulate cortex (PCC), precuneus and hippocampus during pain stimulation in fibromyalgia patients. The increased activation of the hippocampus during pain expectation and subsequent activation of the PCC/precuneus during the lack of control phase points towards an influence of pain perception through heightening of alertness and anxiety responses to pain in fibromyalgia patients.

Microfluidic synthesis of multifunctional liposomes for tumour targeting

Nanotechnology has started a new era in engineering multifunctional nanoparticles for diagnosis and therapeutics by incorporating therapeutic drugs, targeting ligands, stimuli-responsive release and imaging molecules. However, more functionality requires more complex synthesis processes, resulting in poor reproducibility, low yield and high production cost, hence difficulties in clinical translation. Herein we report a one-step microfluidic method for making multifunctional liposomes. Three formulations were prepared using this simple method, including plain liposomes, PEGylated liposomes and folic acid functionalised liposomes, all with a fluorescence dye encapsulated for imaging. The size and surface properties of these liposomes can be precisely controlled by simply tuning the flow rate ratio and the ratio of the lipids to PEGylated lipid (DSPE-PEG₂₀₀₀) and to the DSPE-PEG₂₀₀₀-Folate, respectively. The synthesised liposomes remained stable under mimic serum conditions. Compared to the plain liposomes and PEGylated liposomes, the targeted folic acid functionalised liposomes exhibited enhanced cellular uptake by the FA receptor positive SKOV3 cells, but not the negative MCF7 cells, and this enhanced uptake could be inhibited by adding excess free folic acid, indicating high specificity of FA ligand-receptor endocytosis. Further evaluation using the 3D tumour spheroid model also showed higher internalisation of the targeted liposome formulation in comparison with the PEGylated one. To the best of our knowledge, this work demonstrates for the first time the versatility of this microfluidic method for making different liposome formulations in a single step, their superior physicochemical properties as well as the enhanced cellular uptake and tumour spheroid uptake of the targeted liposomes.

State feedback control design for Boolean networks

Background

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network.

Results

In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results.

Conclusions

This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.