Reply to “Comments on “Consensus and Cooperation in Networked Multi-Agent Systems””

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On Steering Swarms

The main contribution of this paper is a novel method allowing an external observer/controller to steer and guide swarms of identical and indistinguishable agents, in spite of the agents' lack of information on absolute location and orientation. Importantly, this is done via simple global broadcast signals, based on the observed average swarm location, with no need to send control signals to any specific agent in the swarm

Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data

Background: Displacement encoded Cardiovascular MR (CMR) can provide high spatial resolution measurements of three-dimensional (3D) Lagrangian displacement. Spatial gradients of the Lagrangian displacement field are used to measure regional myocardial strain. In general, adjacent parallel slices are needed in order to calculate the spatial gradient in the through-slice direction. This necessitates the acquisition of additional data and prolongs the scan time. The goal of this study is to define an analytic solution that supports the reconstruction of the out-of-plane components of the Lagrangian strain tensor in addition to the in-plane components from a single-slice displacement CMR dataset with high spatio-temporal resolution. The technique assumes incompressibility of the myocardium as a physical constraint. Results: The feasibility of the method is demonstrated in a healthy human subject and the results are compared to those of other studies. The proposed method was validated with simulated data and strain estimates from experimentally measured DENSE data, which were compared to the strain calculation from a conventional two-slice acquisition. Conclusion: This analytical method reduces the need to acquire data from adjacent slices when calculating regional Lagrangian strains and can effectively reduce the long scan time by a factor of two

Adjuvant Migraine Medications in the Treatment of Sudden Sensorineural Hearing Loss.

Objectives/hypothesisTo examine the hearing outcomes of patients with sudden sensorineural hearing loss (SSNHL) treated with oral and intratympanic (IT) steroid only or a combination of steroid and migraine treatment. Our hypothesis was that adjuvant migraine medications may improve outcomes in SSNHL.MethodsA retrospective chart review at a tertiary otology center was conducted to identify patients with SSNHL who received oral steroid and IT dexamethasone injection(s) with or without migraine medications (a combination of nortriptyline and topiramate).ResultsA total of 47 patients received oral steroid and IT dexamethasone injection(s) only, and 46 patients received oral steroid and IT dexamethasone injection(s) as well as migraine lifestyle changes plus a combination of nortriptyline and topiramate. There were no significant differences in demographics and baseline audiometric data between the two groups. Both groups demonstrated improvements in pure tone average (PTA) and hearing thresholds at 250 Hz and 8000 Hz posttreatment. However, compared to steroid-only group, the adjuvant migraine medications group had significantly greater improvements in hearing thresholds at the lower frequencies (250 Hz, 500 Hz, 1000 Hz). Patients in the latter cohort also had greater improvement in PTA (P = .01) and received fewer IT injections (P = .04) PTA improvement of ≥ 10 dB was observed in 36 patients (78%) in the adjuvant migraine medications group and 22 patients (46%) in the control group (P < .001).ConclusionIn multimodal treatment of SSNHL, supplementing oral and IT steroid with migraine medications may result in greater improvements in lower frequency hearing thresholds and PTA. Furthermore, adjuvant migraine treatment can lead to decrease in number of IT injections, thus reducing procedure-related risks and complications.Level of evidence3 Laryngoscope, 131:E283-E288, 2021

A new framework for consensus for discrete-time directed networks of multi-agents with distributed delays

Copyright @ 2012 Taylor & FrancisIn this article, the distributed consensus problem is considered for discrete-time delayed networks of dynamic agents with fixed topologies, where the networks under investigation are directed and the time-delays involved are distributed time delays including a single or multiple time delay(s) as special cases. By using the invariance principle of delay difference systems, a new unified framework is established to deal with the consensus for the discrete-time delayed multi-agent system. It is shown that the addressed discrete-time network with arbitrary distributed time delays reaches consensus provided that it is strongly connected. A numerical example is presented to illustrate the proposed methods.This work was supported in part by City University of Hong Kong under Grant 7008114, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313

Molecular Actuators in Action: Electron-Transfer-Induced Conformation Transformation in Cofacially Arrayed Polyfluorenes

There is much current interest in the design of molecular actuators, which undergo reversible, controlled motion in response to an external stimulus (light, heat, oxidation, etc.). Here we describe the design and synthesis of a series of cofacially arrayed polyfluorenes (MeFnHm) with varied end-capping groups, which undergo redox-controlled electromechanical actuation. Such cofacially arrayed polyfluorenes are a model molecular scaffold to investigate fundamental processes of charge and energy transfer across a π-stacked assembly, and we show with the aid of NMR and optical spectroscopies, X-ray crystallography and DFT calculations that in the neutral state the conformation of MeFnH1 and MeFnH2 is open rather than cofacial, with a conformational dependence that is highly influenced by the local environment. Upon (electro)chemical oxidation, these systems undergo a reversible transformation into a closed fully π-stacked conformation, driven by charge-resonance stabilization of the cationic charge. These findings are expected to aid the design of novel wire-like cofacially arrayed systems capable of undergo redox-controlled actuation

Happiness is assortative in online social networks

Social networks tend to disproportionally favor connections between individuals with either similar or dissimilar characteristics. This propensity, referred to as assortative mixing or homophily, is expressed as the correlation between attribute values of nearest neighbour vertices in a graph. Recent results indicate that beyond demographic features such as age, sex and race, even psychological states such as "loneliness" can be assortative in a social network. In spite of the increasing societal importance of online social networks it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that general happiness or Subjective Well-Being (SWB) of Twitter users, as measured from a 6 month record of their individual tweets, is indeed assortative across the Twitter social network. To our knowledge this is the first result that shows assortative mixing in online networks at the level of SWB. Our results imply that online social networks may be equally subject to the social mechanisms that cause assortative mixing in real social networks and that such assortative mixing takes place at the level of SWB. Given the increasing prevalence of online social networks, their propensity to connect users with similar levels of SWB may be an important instrument in better understanding how both positive and negative sentiments spread through online social ties. Future research may focus on how event-specific mood states can propagate and influence user behavior in "real life".Comment: 17 pages, 9 figure

Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays

This is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2012 ACM.This article is concerned with a new distributed state estimation problem for a class of dynamical systems in sensor networks. The target plant is described by a set of differential equations disturbed by a Brownian motion and randomly occurring nonlinearities (RONs) subject to time delays. The RONs are investigated here to reflect network-induced randomly occurring regulation of the delayed states on the current ones. Through available measurement output transmitted from the sensors, a distributed state estimator is designed to estimate the states of the target system, where each sensor can communicate with the neighboring sensors according to the given topology by means of a directed graph. The state estimation is carried out in a distributed way and is therefore applicable to online application. By resorting to the Lyapunov functional combined with stochastic analysis techniques, several delay-dependent criteria are established that not only ensure the estimation error to be globally asymptotically stable in the mean square, but also guarantee the existence of the desired estimator gains that can then be explicitly expressed when certain matrix inequalities are solved. A numerical example is given to verify the designed distributed state estimators.This work was supported in part by the National Natural Science Foundation of China under Grants 61028008, 60804028 and 61174136, the Qing Lan Project of Jiangsu Province of China, the Project sponsored by SRF for ROCS of SEM of China, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

A One-Bead-Per-Saccharide (1BPS) Model for Glycosaminoglycans

Glycosaminoglycans (GAGs) are polysaccharide compounds that play key roles in various biological processes. GAGs are important structural components of cartilage and the extracellular matrix of the brain. Due to the large size of these polysaccharides, coarse-grained approaches are indispensable for modeling these biopolymers. We develop a one-bead-per-saccharide model of chondroitin sulfates and hyaluronic acid based on an existing three-bead-per-saccharide coarse-grained model. Our coarse graining is carried out by using iterative Boltzmann inversion (IBI), including an additional coupling potential to incorporate the correlation between dihedral angles. The predictions of the model are verified against those of the existing three-bead-per-saccharin model and the experimental radius of gyration for hyaluronic acid.</p