Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Microtubule Instability

Microtubule Instability

Microtubules are hollow cylindrical filaments having a diameter of approximately 25 nm and a length that varies from 200 nm to 25 μm. GTP-bound tubulin subunits form αβ-heterodimers for microtubule assembly. These core building blocks interact longitudinally, polymerizing into protofilaments. The protofilaments then interact with one another through lateral bonding forces to form stable cylindrical microtubules. These cylindrical filaments are dynamic as they undergo repeated assembly and...

Multimachine Stability

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:

Nonlinear Pharmacokinetics: Causes of Nonlinearity

Nonlinear Pharmacokinetics: Causes of Nonlinearity

Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...

Rapidly Varying Flow

Rapidly Varying Flow

Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...

Capillary Exchange

Capillary Exchange

The cardiovascular system's chief role is to disseminate gases, nutrients, waste, and other substances to the body's cells. Small molecules like gases, lipids, and lipid-soluble substances directly diffuse through capillary wall endothelial cell membranes. Glucose, amino acids, and ions, including sodium, potassium, calcium, and chloride, use transporters for facilitated diffusion via membrane-specific channels. Glucose, ions, and bigger molecules may also pass through intercellular clefts.

BIBO stability of continuous and discrete -time systems

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Road safety policies and motor vehicle fatalities in Ecuador: a geographical and temporal analysis from 1990 to 2022.

BMJ public health·2026

Same author

Implementation of AESOP early-warning system for respiratory disease: a pilot and validation study using routinely collected data in Amazonas, Brazil.

Lancet regional health. Americas·2026

Same author

Rare Phyla, Such as CPR and DPANN, Shape Ecosystem-Level Microbial Community Structure Dissimilarities.

Microbial ecology·2025

Same author

An integrated framework for modelling respiratory disease transmission and designing surveillance networks using a sentinel index.

Royal Society open science·2025

Same author

Water, Health, and Social Technologies: One Million Cisterns Programme Case Study.

Annals of global health·2025

Same author

Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records.

BMC medical research methodology·2025

Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 23, 2026

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

Fluctuations in interbank network dynamics.

Daniel O Cajueiro¹, Benjamin M Tabak, Roberto F S Andrade

¹Departmento de Economia, Universidade de Brasília, 70910-900 Brasília, Brazil.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|April 28, 2009

Summary

This summary is machine-generated.

This study examines how bank credit fluctuations scale in interbank networks. Results indicate these scaling exponents change over time, suggesting the network

More Related Videos

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Related Experiment Videos

Last Updated: Jun 23, 2026

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Area of Science:

* Financial Network Analysis
* Statistical Physics
* Complex Systems

Background:

* Interbank networks are crucial for financial system stability.
* Understanding credit flow dynamics is essential for risk management.
* Previous studies have explored network properties, but scaling of individual agent flux requires further investigation.

Purpose of the Study:

* To investigate the scaling properties of individual agent flux fluctuations in an interbank network.
* To analyze the relationship between an agent's flux and its average flux.
* To assess the temporal dynamics of these scaling properties.

Main Methods:

* Analysis of daily credit provided (asset) and received (liab) by individual banks.
* Calculation of raw flux fluctuations: f(i)(asset), f(i)(liab), and net flux f(R,i)(ext).
* Application of a methodology to derive internal and external flux fluctuations: f(i)(int) and f(i)(ext).
* Implementation of a rolling sampling approach to address non-stationarity in flux data.

Main Results:

* Identified scaling properties in the fluctuations of individual bank fluxes (asset, liab, and net).
* Observed time-varying scaling exponents, indicating dynamic changes in the network.
* Demonstrated the utility of the rolling sampling method for non-stationary financial data.

Conclusions:

* The scaling exponents of bank flux fluctuations are not constant, implying a changing interbank network structure.
* The interbank network exhibits dynamic behavior, with scaling properties evolving over time.
* This research provides insights into the temporal evolution of financial networks.