Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
100
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.7K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.7K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.3K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.3K
Reversible and Irreversible Processes01:14

Reversible and Irreversible Processes

4.5K
The thermodynamic processes can be classified into reversible and irreversible processes. The processes that can be restored to their initial state are called reversible processes. It is only possible if the process is in quasi-static equilibrium, i.e., it takes place in infinitesimally small steps, and the system remains at equilibrium However, these are ideal processes and do not occur naturally. An ideal system undergoing a reversible process is always in thermodynamic equilibrium within...
4.5K
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

494
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
494
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

126
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
126

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

A novel microprotein L3EMP triggers lung adenocarcinoma progression by catalysing the deubiquitination of SIRT1.

British journal of cancer·2026
Same author

Similarity scaling for low-pressure capacitive radio-frequency CF_{4} plasmas across operation modes.

Physical review. E·2026
Same author

Scaling medical device regulatory science using large language models.

NPJ digital medicine·2026
Same author

Post-Wildfire Indoor Pollution in WUI Areas following the 2025 Los Angeles Fires. Part I. Establishing Baseline Contaminant Levels Prior to Home Reoccupation.

ACS ES&T air·2026
Same author

All-photon logic gate calculation based on phase change materials.

Nanophotonics (Berlin, Germany)·2025
Same author

Liquid Crystal Microcavity Biosensors for Real-Time Liver Injury Monitoring via Whispering Gallery Mode Laser.

Research (Washington, D.C.)·2025
Same journal

ORTHOGONAL TRACE-SUM MAXIMIZATION: TIGHTNESS OF THE SEMIDEFINITE RELAXATION AND GUARANTEE OF LOCALLY OPTIMAL SOLUTIONS.

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics·2023
Same journal

NOISY MATRIX COMPLETION: UNDERSTANDING STATISTICAL GUARANTEES FOR CONVEX RELAXATION VIA NONCONVEX OPTIMIZATION.

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics·2021
Same journal

ANOTHER LOOK AT THE FAST ITERATIVE SHRINKAGE/THRESHOLDING ALGORITHM (FISTA).

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics·2018
Same journal

A STRICTLY CONTRACTIVE PEACEMAN-RACHFORD SPLITTING METHOD FOR CONVEX PROGRAMMING.

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics·2015
Same journal

On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces.

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics·2010
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Sep 10, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

9.9K

Un algoritmo de descomposición para programas estocásticos de dos etapas con funciones de recuperación no convexas

Hanyang Li1, Ying Cui1

  • 1Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, CA 94720 USA.

SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics
|August 25, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce un nuevo método de descomposición para resolver programas estocásticos complejos de dos etapas. El nuevo enfoque maneja efectivamente la no convexidad, ofreciendo una solución robusta para problemas de optimización desafiantes.

Palabras clave:
90C15 Se incluyen los siguientes:90C26, en el sentido de queDescomposiciónRecurso no convexoprograma estocástico de dos etapas

Más Videos Relacionados

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Videos de Experimentos Relacionados

Last Updated: Sep 10, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

9.9K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Área de la Ciencia:

  • Optimización
  • Programación matemática
  • Ciencias computacionales

Sus antecedentes:

  • Los métodos clásicos de descomposición fallan para las funciones de recurso no convexas en programas estocásticos de dos etapas.
  • La parametrización no lineal por variables de la primera etapa complica el objetivo y las restricciones de la segunda etapa.
  • El fallo de regularidad de Clarke impide la generalización directa de los algoritmos de Benders o Lagrange.

Objetivo del estudio:

  • Desarrollar un nuevo marco de descomposición para programas estocásticos de dos etapas no convexos.
  • Para abordar las limitaciones de los métodos existentes cuando falla la regularidad de Clarke.
  • Proporcionar un algoritmo eficaz para problemas con funciones de recurso de segunda etapa no linealmente parametrizadas.

Principales métodos:

  • Exploración de una estructura implícitamente cóncava y convexa de la función de recurso.
  • Introducción de un marco de descomposición que utiliza la envoltura parcial de Moreau.
  • Generación sucesiva de aproximaciones cuadráticas fuertemente convexas de la función de recurso.
  • Integración de aproximaciones en el problema maestro de la primera etapa a través de soluciones de subproblemas convexos de la segunda etapa.

Principales resultados:

  • Convergencia establecida tanto para los escenarios fijos como para los secuenciales.
  • Eficacia demostrada del algoritmo propuesto a través de experimentos numéricos.
  • Se abordó con éxito el desafío de la no convexidad en la programación estocástica de dos etapas.

Conclusiones:

  • El nuevo marco de descomposición parcial basado en la envolvente de Moreau es efectivo para programas estocásticos no convexos de dos etapas.
  • El método supera las limitaciones de los algoritmos de descomposición clásicos.
  • El enfoque ofrece una solución viable para problemas de optimización complejos con funciones de recurso no linealmente parametrizadas.