The Dynamics of Hybrid Metabolic-Genetic Oscillators

The synthetic construction of intracellular circuits is frequently hindered by a poor knowledge of appropriate kinetics and precise rate parameters. Here, we use generalized modeling (GM) to study the dynamical behavior of topological models of a family of hybrid metabolic-genetic circuits known as "metabolators." Under mild assumptions on the kinetics, we use GM to analytically prove that all explicit kinetic models which are topologically analogous to one such circuit, the "core metabolator," cannot undergo Hopf bifurcations. Then, we examine more detailed models of the metabolator. Inspired by the experimental observation of a Hopf bifurcation in a synthetically constructed circuit related to the core metabolator, we apply GM to identify the critical components of the synthetically constructed metabolator which must be reintroduced in order to recover the Hopf bifurcation. Next, we study the dynamics of a re-wired version of the core metabolator, dubbed the "reverse" metabolator, and show that it exhibits a substantially richer set of dynamical behaviors, including both local and global oscillations. Prompted by the observation of relaxation oscillations in the reverse metabolator, we study the role that a separation of genetic and metabolic time scales may play in its dynamics, and find that widely separated time scales promote stability in the circuit. Our results illustrate a generic pipeline for vetting the potential success of a potential circuit design, simply by studying the dynamics of the corresponding generalized model

Spin wave dispersion softening in the ferromagnetic Kondo lattice model for manganites

Spin dynamics is calculated in the ferromagnetic (FM) state of the generalized Kondo lattice model taking into account strong on-site correlations between e_g electrons and antiferromagnetic (AFM) exchange among t_{2g} spins. Our study suggests that competing FM double-exchange and AFM super-exchange interaction lead to a rather nontrivial spin-wave spectrum. While spin excitations have a conventional Dq^2 spectrum in the long-wavelength limit, there is a strong deviation from the spin-wave spectrum of the isotropic Heisenberg model close to the zone boundary. The relevance of our results to the experimental data are discussed.Comment: 6 RevTex pages, 3 embedded PostScript figure

A Single-Loop DC Motor Control System Design with a Desired Aperiodic Degree of Stability

The application of the original analytical approach for Pi-controller synthesis of a stable second-order plant is considered. This approach allows finding controller parameters without any intensive computing by using the direct expressions. The plant model is obtained on the basis of identification, which is based on the automated real-interpolation method. The results of natural experiments are given

Measuring well-being in aphasia: The GHQ-28 versus the NHP

This study aimed to get the opinions of people with aphasia on two subjective well-being measures: the General Health Questionnaire 28-item version (GHQ-28) (Goldberg & Hillier, 1979) and the Nottingham Health Profile (NHP) (Hunt, McKenna, McEwen, Williams, & Papp, 1981). Twelve persons with moderate to mild aphasia of at least 2-years duration completed the GHQ-28 and the NHP. In a semistructured intenriew, they gave their feedback on the two questionnaires. All participants were able to complete both instruments. Nine out of 12 participants showed high psychological distress (> 5/28) in the GHQ-28. The NHP (part 1 less the physical abilities section) had a correlation of 0.78 (p < .01) with the GHQ-28. The social dysfunction subscale of the NHP identified more problems in the participants with aphasia than the social isolation subscale of the GHQ-28. The majority of the participants (10 out of 12) preferred the NHP, as they found it easier to understand and respond to. This small-scale study indicated that both the GHQ-28 and the NHP can be administered to people with moderate to mild aphasia and provide useful information on their well-being. Participants reported that the NHP was easier to do, and it asked questions more relevant to their situation

A method for the reconstruction of unknown non-monotonic growth functions in the chemostat

We propose an adaptive control law that allows one to identify unstable steady states of the open-loop system in the single-species chemostat model without the knowledge of the growth function. We then show how one can use this control law to trace out (reconstruct) the whole graph of the growth function. The process of tracing out the graph can be performed either continuously or step-wise. We present and compare both approaches. Even in the case of two species in competition, which is not directly accessible with our approach due to lack of controllability, feedback control improves identifiability of the non-dominant growth rate.Comment: expansion of ideas from proceedings paper (17 pages, 8 figures), proceedings paper is version v

A systematic review of the impact of stroke on social support and social networks: associated factors and patterns of change

Objective: Identify what factors are associated with functional social support and social network post stroke; explore stroke survivors’ perspectives on what changes occur and how they are perceived. Data sources: The following electronic databases were systematically searched up to May 2015: Academic Search Complete; CINAHL Plus; E-journals; Health Policy Reference Centre; MEDLINE; PsycARTICLES; PsycINFO; and SocINDEX. Review methods: PRISMA guidelines were followed in the conduct and reporting of this review. All included studies were critically appraised using the Critical Appraisal Skills Program tools. Meta-ethnographic techniques were used to integrate findings from the qualitative studies. Given the heterogeneous nature of the quantitative studies, data synthesis was narrative. Results: 70 research reports met the eligibility criteria: 22 qualitative and 48 quantitative reporting on 4,816 stroke survivors. The qualitative studies described a contraction of the social network, with non-kin contact being vulnerable. Although family were more robust network members, significant strain was observed within the family unit. In the quantitative studies, poor functional social support was associated with depression (13/14 studies), reduced quality of life (6/6 studies) and worse physical recovery (2/2 studies). Reduced social network was associated with depression (7/8 studies), severity of disability (2/2 studies) and aphasia (2/2 studies). Although most indicators of social network reduced post stroke (for example, contact with friends, 5/5 studies), the perception of feeling supported remained relatively stable (4/4 studies). Conclusion: Following a stroke non-kin contact is vulnerable, strain is observed within the family unit, and poor social support is associated with depressive symptoms

Identification of single-input–single-output quantum linear systems

The purpose of this paper is to investigate system identification for single-input–single-output general (active or passive) quantum linear systems. For a given input we address the following questions: (1) Which parameters can be identified by measuring the output? (2) How can we construct a system realization from sufficient input-output data? We show that for time-dependent inputs, the systems which cannot be distinguished are related by symplectic transformations acting on the space of system modes. This complements a previous result of Guţă and Yamamoto [IEEE Trans. Autom. Control 61, 921 (2016)] for passive linear systems. In the regime of stationary quantum noise input, the output is completely determined by the power spectrum. We define the notion of global minimality for a given power spectrum, and characterize globally minimal systems as those with a fully mixed stationary state. We show that in the case of systems with a cascade realization, the power spectrum completely fixes the transfer function, so the system can be identified up to a symplectic transformation. We give a method for constructing a globally minimal subsystem direct from the power spectrum. Restricting to passive systems the analysis simplifies so that identifiability may be completely understood from the eigenvalues of a particular system matrix

Active Learning in Persistent Surveillance UAV Missions

The performance of many complex UAV decision-making problems can be extremely sensitive to small errors in the model parameters. One way of mitigating this sensitivity is by designing algorithms that more effectively learn the model throughout the course of a mission. This paper addresses this important problem by considering model uncertainty in a multi-agent Markov Decision Process (MDP) and using an active learning approach to quickly learn transition model parameters. We build on previous research that allowed UAVs to passively update model parameter estimates by incorporating new state transition observations. In this work, however, the UAVs choose to actively reduce the uncertainty in their model parameters by taking exploratory and informative actions. These actions result in a faster adaptation and, by explicitly accounting for UAV fuel dynamics, also mitigates the risk of the exploration. This paper compares the nominal, passive learning approach against two methods for incorporating active learning into the MDP framework: (1) All state transitions are rewarded equally, and (2) State transition rewards are weighted according to the expected resulting reduction in the variance of the model parameter. In both cases, agent behaviors emerge that enable faster convergence of the uncertain model parameters to their true values

Guillain-Barré syndrome: a century of progress

In 1916, Guillain, Barré and Strohl reported on two cases of acute flaccid paralysis with high cerebrospinal fluid protein levels and normal cell counts — novel findings that identified the disease we now know as Guillain–Barré syndrome (GBS). 100 years on, we have made great progress with the clinical and pathological characterization of GBS. Early clinicopathological and animal studies indicated that GBS was an immune-mediated demyelinating disorder, and that severe GBS could result in secondary axonal injury; the current treatments of plasma exchange and intravenous immunoglobulin, which were developed in the 1980s, are based on this premise. Subsequent work has, however, shown that primary axonal injury can be the underlying disease. The association of Campylobacter jejuni strains has led to confirmation that anti-ganglioside antibodies are pathogenic and that axonal GBS involves an antibody and complement-mediated disruption of nodes of Ranvier, neuromuscular junctions and other neuronal and glial membranes. Now, ongoing clinical trials of the complement inhibitor eculizumab are the first targeted immunotherapy in GBS

Hybridization in parasites: consequences for adaptive evolution, pathogenesis and public health in a changing world

[No abstract available