Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

123
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...
123
Econometric Views (EViews)01:29

Econometric Views (EViews)

305
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
305
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

805
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
805
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

914
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
914
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

3.2K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
3.2K
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

438
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
438

You might also read

Related Articles

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

Sort by
Same author

New macroporous support for the preparation of plastic scintillation resins.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2025
Same author

Design of radionuclide separations based on MD simulations.

Analytica chimica acta·2025
Same author

Simultaneous radionuclide determination using PSresin: 2in2 and 2in1 tandem configuration.

Analytica chimica acta·2025
Same author

Quantifying Memory in Spin Glasses.

Physical review letters·2025
Same author

Ultra-fast, selective and pseudo-quantitative analysis of <sup>99</sup>Tc in nuclear waste for screening purposes.

Journal of hazardous materials·2024
Same author

Scintillation and structural properties of copolymers and mixtures of styrene, 9-vinylcarbazole and 4-vinylbenzyl chloride based plastic scintillators.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2024
Same journal

Predictive drift compensation of multi-frame STEM via live scan modification.

Ultramicroscopy·2026
Same journal

Deep PACBED: Multitask analysis of PACBED images using deep neural networks.

Ultramicroscopy·2026
Same journal

Guided progressive reconstructive imaging: A new quantization-based framework for low-dose, high-throughput and real-time analytical ptychography.

Ultramicroscopy·2026
Same journal

Brightness optimization in a 200 keV DTEM source by geometry-driven aberration suppression.

Ultramicroscopy·2026
Same journal

Characterization of the Timepix4 hybrid pixel detector and its impact on four-dimensional scanning transmission electron microscopy (4D-STEM).

Ultramicroscopy·2026
Same journal

Contamination analysis of the residual gas composition in transmission electron microscopy.

Ultramicroscopy·2026
See all related articles

Related Experiment Video

Updated: Oct 17, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K

WhatEELS. A python-based interactive software solution for ELNES analysis combining clustering and NLLS.

J Blanco-Portals1, P Torruella1, F Baiutti2

  • 1LENS-MIND, Department of Electronics and Biomedical Engineering, Universitat de Barcelona, 08028 Barcelona, Spain; Institute of Nanoscience and Nanotechnology (IN2UB), Universitat de Barcelona, 08028 Barcelona, Spain.

Ultramicroscopy
|October 12, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method combining clustering analysis and non-linear least squares fitting for electron energy loss spectroscopy (EELS) spectral unmixing. This approach enhances elemental analysis and atomic coordination characterization in complex materials.

Keywords:
Clustering analysisElectron energy loss spectroscopy (EELS)Elemental quantificationEnergy loss near edge structure (ELNES)Non-linear least squares fitting (NLLS)Oxidation state analysis

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.1K
Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

4.3K

Related Experiment Videos

Last Updated: Oct 17, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.1K
Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

4.3K

Area of Science:

  • Materials Science
  • Spectroscopy
  • Data Analysis

Background:

  • Electron Energy Loss Spectroscopy (EELS) offers high-resolution elemental and coordination state analysis.
  • Traditional spectral unmixing methods like multiple linear least squares fitting can be limited with complex datasets.
  • Non-linear least squares fitting provides more detailed component information but struggles with mixed-composition samples.

Purpose of the Study:

  • To develop an improved spectral unmixing method for EELS data analysis.
  • To address limitations of existing methods in handling complex, mixed-composition samples.
  • To present a user-friendly software solution for advanced EELS analysis.

Main Methods:

  • Combined clustering analysis for sample segmentation with non-linear least squares (NLLS) fitting for spectral analysis.
  • Utilized clustering to group pixels by spectral characteristics, enabling region-specific analysis.
  • Developed and provided the WhatEELS software for integrated clustering and NLLS analysis, including white-lines and quantification tools.

Main Results:

  • The combined approach effectively segments complex samples, improving control over spectral fitting parameters.
  • Demonstrated successful application on a challenging mesoporous cerium oxide sample doped with rare-earth elements.
  • The WhatEELS software facilitates efficient spectral unmixing and quantitative analysis.

Conclusions:

  • The integration of clustering and NLLS offers a robust solution for EELS spectral unmixing, particularly for complex materials.
  • The WhatEELS software provides a valuable tool for researchers performing quantitative EELS analysis.
  • This method enhances the precision of elemental oxidation state and atomic coordination characterization using EELS.