scholarly journals Searching for Errors in Models of Complex Dynamic Systems

2021 ◽  
Vol 11 ◽  
Author(s):  
Dominik Kahl ◽  
Maik Kschischo
Keyword(s):  
Structural Model ◽  
Temporal Dynamics ◽  
Dynamic Networks ◽  
Model Errors ◽  
Complex Dynamic ◽  
Network Nodes ◽  
C Elegans ◽  
Daunting Task ◽  
Interacting Systems ◽  
And Control

Mathematical modeling is seen as a key step to understand, predict, and control the temporal dynamics of interacting systems in such diverse areas like physics, biology, medicine, and economics. However, for large and complex systems we usually have only partial knowledge about the network, the coupling functions, and the interactions with the environment governing the dynamic behavior. This incomplete knowledge induces structural model errors which can in turn be the cause of erroneous model predictions or misguided interpretations. Uncovering the location of such structural model errors in large networks can be a daunting task for a modeler. Here, we present a data driven method to search for structural model errors and to confine their position in large and complex dynamic networks. We introduce a coherence measure for pairs of network nodes, which indicates, how difficult it is to distinguish these nodes as sources of an error. By clustering network nodes into coherence groups and inferring the cluster inputs we can decide, which cluster is affected by an error. We demonstrate the utility of our method for the C. elegans neural network, for a signal transduction model for UV-B light induced morphogenesis and for synthetic examples.

scholarly journals Finite-Time Synchronization of Uncertain Complex Dynamic Networks with Nonlinear Coupling

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yiping Luo ◽  
Yuejie Yao
Keyword(s):  
Finite Time ◽  
Time Synchronization ◽  
Dynamic Networks ◽  
Nonlinear Function ◽  
Time Instant ◽  
Control Input ◽  
Parameter Uncertainties ◽  
Complex Dynamic ◽  
Network Nodes ◽  
Analysis Techniques

The finite-time synchronization control is studied in this paper for a class of nonlinear uncertain complex dynamic networks. The uncertainties in the network are unknown but bounded and satisfy some matching conditions. The coupling relationship between network nodes is described by a nonlinear function satisfying the Lipchitz condition. By introducing a simple Lyapunov function, two main results regarding finite-time synchronization of a class of complex dynamic networks with parameter uncertainties are derived. By employing some analysis techniques like matrix inequalities, suitable controllers can be designed based on the obtained synchronization criteria. Moreover, with the obtained control input, the time instant required for the system to achieve finite-time synchronization can be estimated if a set of LMIs are feasible or an assumption on the eigenvalues of some matrices can be satisfied. Finally, the effectiveness of the proposed results is verified by numerical simulation.

Localization of test/analysis structural model errors

1989 ◽  
Author(s):  
CHAUR-MING CHOU ◽  
JOHN O'CALLAHAN ◽  
CHI-HSING WU
Keyword(s):  
Structural Model ◽  
Model Errors ◽  
Test Analysis

scholarly journals Mutations that Affect Channel Opening of Innexin Hemichannels in the C. elegans Gonad

2020 ◽  
Author(s):  
Todd Starich ◽  
David Greenstein
Keyword(s):  
Cell Proliferation ◽  
Gap Junctions ◽  
Germ Cell ◽  
Structural Model ◽  
Loss Of Function ◽  
C Elegans ◽  
Somatic Gonad ◽  
Channel Opening ◽  
Germline Proliferation ◽  
Germ Cell Proliferation

In C. elegans, gap junctions couple cells of the somatic gonad with the germline to support germ cell proliferation and gametogenesis. We previously characterized a strong loss-of-function mutation (T239I) affecting the second extracellular loop (EL2) of the somatic INX-8 hemichannel subunit. These mutant hemichannels form non-functional gap junctions with germline-expressed innexins. Here we describe the characterization of mutations that restore germ cell proliferation in the T239I EL2 mutant background. We recovered seven intragenic mutations located in diverse domains of INX-8 but not the EL domains. These second-site mutations compensate for the original channel defect to varying degrees, from nearly complete wild-type rescue, to partial rescue of germline proliferation. One suppressor mutation (E350K) supports the innexin cryo-EM structural model that the channel pore opening is surrounded by a cytoplasmic dome. Two suppressor mutations (S9L and I36N) may form leaky hemichannels that support germline proliferation but cause the demise of somatic sheath cells. Phenotypic analyses of three other suppressors reveal an equivalency in the rescue of germline proliferation and comparable delays in gametogenesis but a graded rescue of fertility. These latter mutations may be useful to probe interactions with the biochemical pathways that produce the molecules transiting through soma-germline gap junctions.

scholarly journals Luqin-like RYamide peptides regulate food-evoked responses in C. elegans

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Hayao Ohno ◽  
Morikatsu Yoshida ◽  
Takahiro Sato ◽  
Johji Kato ◽  
Mikiya Miyazato ◽  
...  
Keyword(s):  
Critical Role ◽  
Egg Laying ◽  
Serotonergic Neuron ◽  
Pacemaker Neurons ◽  
C Elegans ◽  
Peptide Signaling ◽  
Multiple Organs ◽  
Locomotory Behavior ◽  
Control Food ◽  
And Control

Peptide signaling controls many processes involving coordinated actions of multiple organs, such as hormone-mediated appetite regulation. However, the extent to which the mode of action of peptide signaling is conserved in different animals is largely unknown, because many peptides and receptors remain orphan and many undiscovered peptides still exist. Here, we identify two novel Caenorhabditis elegans neuropeptides, LURY-1-1 and LURY-1-2, as endogenous ligands for the neuropeptide receptor-22 (NPR-22). Both peptides derive from the same precursor that is orthologous to invertebrate luqin/arginine-tyrosine-NH2 (RYamide) proneuropeptides. LURY-1 peptides are secreted from two classes of pharyngeal neurons and control food-related processes: feeding, lifespan, egg-laying, and locomotory behavior. We propose that LURY-1 peptides transmit food signals to NPR-22 expressed in feeding pacemaker neurons and a serotonergic neuron. Our results identified a critical role for luqin-like RYamides in feeding-related processes and suggested that peptide-mediated negative feedback is important for satiety regulation in C. elegans.

scholarly journals Progressive recruitment of distal MEC-4 channels determines touch response strength in C. elegans

2019 ◽  
Author(s):  
S. Katta ◽  
A. Sanzeni ◽  
A. Das ◽  
M. Vergassola ◽  
M.B. Goodman
Keyword(s):  
Temporal Dynamics ◽  
Mechanical Strain ◽  
Tissue Mechanics ◽  
Mechanical Stimuli ◽  
Patch Clamp Recording ◽  
Open Probability ◽  
C Elegans ◽  
Somatosensory Neurons ◽  
Touch Response

AbstractTouch deforms, or strains, the skin beyond the immediate point of contact. The spatiotemporal nature of the touch-induced strain fields depend on the mechanical properties of the skin and the tissues below. Somatosensory neurons that sense touch branch out within the skin and rely on a set of mechano-electrical transduction channels distributed within their dendrites to detect mechanical stimuli. Here, we sought to understand how tissue mechanics shape touch-induced mechanical strain across the skin over time and how individual channels located in different regions of the strain field contribute to the overall touch response. We leveraged C. elegans’ touch receptor neurons (TRNs) as a simple model amenable to in vivo whole-cell patch clamp recording and an integrated experimental-computational approach to dissect the mechanisms underlying the spatial and temporal dynamics that we observed. Consistent with the idea that strain is produced at a distance, we show that delivering strong stimuli outside the anatomical extent of the neuron is sufficient to evoke MRCs. The amplitude and kinetics of the MRCs depended on both stimulus displacement and speed. Finally, we found that the main factor responsible for touch sensitivity is the recruitment of progressively more distant channels by stronger stimuli, rather than modulation of channel open probability. This principle may generalize to somatosensory neurons with more complex morphologies.SummaryThrough experiment and simulation, Katta et al. reveal that pushing faster and deeper recruits more and more distant mechano-electrical transduction channels during touch. The net result is a dynamic receptive field whose size and shape depends on tissue mechanics, stimulus parameters, and channel distribution within sensory neurons.

Detecting Influential Spreaders in Complex, Dynamic Networks

Computer ◽  
2013 ◽  
Vol 46 (4) ◽  
pp. 24-29 ◽  
Author(s):  
Pavlos Basaras ◽  
Dimitrios Katsaros ◽  
Leandros Tassiulas
Keyword(s):  
Dynamic Networks ◽  
Complex Dynamic

Detection of local community structures in complex dynamic networks with random walks

2009 ◽  
Vol 3 (4) ◽  
pp. 266-278 ◽  
Author(s):  
G.S. Thakur ◽  
A.W.M. Dress ◽  
R. Tiwari ◽  
S.-S. Chen ◽  
M.T. Thai
Keyword(s):  
Random Walks ◽  
Local Community ◽  
Dynamic Networks ◽  
Community Structures ◽  
Complex Dynamic

scholarly journals Seasonal synchronization of foodborne outbreaks in the United States, 1996–2017

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ryan B. Simpson ◽  
Bingjie Zhou ◽  
Elena N. Naumova
Keyword(s):  
Food Systems ◽  
Negative Binomial ◽  
Phase Synchronization ◽  
Dynamic Networks ◽  
The United States ◽  
Foodborne Outbreaks ◽  
Seasonal Synchronization ◽  
Phase Amplitude ◽  
And Control ◽  
Phase Phase

Abstract Modern food systems represent complex dynamic networks vulnerable to foodborne infectious outbreaks difficult to track and control. Seasonal co-occurrences (alignment of seasonal peaks) and synchronization (similarity of seasonal patterns) of infections are noted, yet rarely explored due to their complexity and methodological limitations. We proposed a systematic approach to evaluate the co-occurrence of seasonal peaks using a combination of L-moments, seasonality characteristics such as the timing (phase) and intensity (amplitude) of peaks, and three metrics of serial, phase-phase, and phase-amplitude synchronization. We used public records on counts of nine foodborne infections abstracted from CDC’s FoodNet Fast online platform for the US and ten representative states from 1996 to 2017 (264 months). Based on annualized and trend-adjusted Negative Binomial Harmonic Regression (NBHR) models augmented with the δ-method, we determined that seasonal peaks of Campylobacter, Salmonella, and Shiga toxin-producing Escherichia Coli (STEC) were tightly clustered in late-July at the national and state levels. Phase-phase synchronization was observed between Cryptosporidium and Shigella, Listeria, and Salmonella (ρ = 0.51, 0.51, 0.46; p < 0.04). Later peak timing of STEC was associated with greater amplitude nationally (ρ = 0.50, p = 0.02) indicating phase-amplitude synchronization. Understanding of disease seasonal synchronization is essential for developing reliable outbreak forecasts and informing stakeholders on mitigation and preventive measures.

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