Feature selection using DBPSO for Arabian horse identification Aboul Ella Hassanien
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
Feature selection using DBPSO for Arabian horse identification Aboul Ella Hassanien
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
Captronic séminaire électronique imprimée - 20/09/2017 - Présentation du Laboratoire IMS / Université de Bordeaux - En partenariat avec l’AFELIM (Association Française de l'Electronique Imprimée) et le soutien du Pôle Numérique de la CCI Bordeaux Gironde, Cap’tronic a organisé le mercredi 20 septembre dans les locaux de l’IMS à Talence, une rencontre autour de l' "électronique imprimée" afin de faire un tour d’horizon de la chaîne de valeur d'une filière dont le marché mondial est estimé à 330 milliards de dollars en 2027.
Yuki Oyama - Markov assignment for a pedestrian activity-based network design...Yuki Oyama
Oyama, Y., Hato, E., Scarinci, R., Bierlaire, M. (2017) Markov assignment for a pedestrian activity-based network design problem. The 6th symposium arranged by European Association for Research in Transportation (hEART), Haifa, Israel.
This Presentation is extracted from the research that I have done so far on the "Seismic Behaviour of Tunnels in Urban Areas" which I presented at the BTSYM 2017 Conference. Tunnels are commonly designed under seismic loading assuming “free field conditions”. However, in urban areas these structures pass beneath buildings, often high-rise ones, or are located close to them. During seismic excitation, above ground structures may cause complex interaction effects with the tunnel, altering its seismic response compared to the “free field conditions” case. My Research summarizes an attempt to identify and understand these interaction effects, focusing on the tunnel response. The problem is investigated in the transversal direction, by means of full dynamic time history analyses that are performed on representative tunnel-soil-above ground structures systems. Tunnels response characteristics are discussed, in terms of tunnel deformations, dynamic earth pressures and lining dynamic internal forces. Results indicate that the presence of the above ground structures may have a significant effect on the seismic response of the tunnel, especially when the latter is stiff and located in shallow depths.
Further material (Publications, Conference Papers, Master Thesis, Raw Data, etc..) can be found on my personal Research Gate page: https://www.researchgate.net/profile/Andrea_Leanza
For contact me:
LinkedIn: https://www.linkedin.com/in/andrealeanza85/
e-mail: andrea.leanza85@gmail.com
Captronic séminaire électronique imprimée - 20/09/2017 - Présentation de VFP Ink Technology- En partenariat avec l’AFELIM (Association Française de l'Electronique Imprimée) et le soutien du Pôle Numérique de la CCI Bordeaux Gironde, Cap’tronic a organisé le mercredi 20 septembre dans les locaux de l’IMS à Talence, une rencontre autour de l' "électronique imprimée" afin de faire un tour d’horizon de la chaîne de valeur d'une filière dont le marché mondial est estimé à 330 milliards de dollars en 2027.
This is the presentation of my 8th semester project on Application of Artificial Neural Network in Friction Stir Processing. We have used AA5052. The presentation starts from the basics of Aluminium and FSP process and then first we predict the properties of Hardness, Roughness and Tensile strength using Minitab16 and then use Minitab16 to create dummy outputs which are fed into the ANN to train it.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Captronic séminaire électronique imprimée - 20/09/2017 - Présentation du Laboratoire IMS / Université de Bordeaux - En partenariat avec l’AFELIM (Association Française de l'Electronique Imprimée) et le soutien du Pôle Numérique de la CCI Bordeaux Gironde, Cap’tronic a organisé le mercredi 20 septembre dans les locaux de l’IMS à Talence, une rencontre autour de l' "électronique imprimée" afin de faire un tour d’horizon de la chaîne de valeur d'une filière dont le marché mondial est estimé à 330 milliards de dollars en 2027.
Yuki Oyama - Markov assignment for a pedestrian activity-based network design...Yuki Oyama
Oyama, Y., Hato, E., Scarinci, R., Bierlaire, M. (2017) Markov assignment for a pedestrian activity-based network design problem. The 6th symposium arranged by European Association for Research in Transportation (hEART), Haifa, Israel.
This Presentation is extracted from the research that I have done so far on the "Seismic Behaviour of Tunnels in Urban Areas" which I presented at the BTSYM 2017 Conference. Tunnels are commonly designed under seismic loading assuming “free field conditions”. However, in urban areas these structures pass beneath buildings, often high-rise ones, or are located close to them. During seismic excitation, above ground structures may cause complex interaction effects with the tunnel, altering its seismic response compared to the “free field conditions” case. My Research summarizes an attempt to identify and understand these interaction effects, focusing on the tunnel response. The problem is investigated in the transversal direction, by means of full dynamic time history analyses that are performed on representative tunnel-soil-above ground structures systems. Tunnels response characteristics are discussed, in terms of tunnel deformations, dynamic earth pressures and lining dynamic internal forces. Results indicate that the presence of the above ground structures may have a significant effect on the seismic response of the tunnel, especially when the latter is stiff and located in shallow depths.
Further material (Publications, Conference Papers, Master Thesis, Raw Data, etc..) can be found on my personal Research Gate page: https://www.researchgate.net/profile/Andrea_Leanza
For contact me:
LinkedIn: https://www.linkedin.com/in/andrealeanza85/
e-mail: andrea.leanza85@gmail.com
Captronic séminaire électronique imprimée - 20/09/2017 - Présentation de VFP Ink Technology- En partenariat avec l’AFELIM (Association Française de l'Electronique Imprimée) et le soutien du Pôle Numérique de la CCI Bordeaux Gironde, Cap’tronic a organisé le mercredi 20 septembre dans les locaux de l’IMS à Talence, une rencontre autour de l' "électronique imprimée" afin de faire un tour d’horizon de la chaîne de valeur d'une filière dont le marché mondial est estimé à 330 milliards de dollars en 2027.
This is the presentation of my 8th semester project on Application of Artificial Neural Network in Friction Stir Processing. We have used AA5052. The presentation starts from the basics of Aluminium and FSP process and then first we predict the properties of Hardness, Roughness and Tensile strength using Minitab16 and then use Minitab16 to create dummy outputs which are fed into the ANN to train it.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
MVA methodologies for surface analysis data
1. MVA methodologies for surface analysis data
Wednesday, 20 September 2017 1
Gustavo Ferraz Trindade
The Surface Analysis Laboratory, University of Surrey, UK
3. Introduction
Wednesday, 20 September 2017 3
Surface analysis
expertise
Good
instrumentation
Sample knowledge
Sample prep.
Data handling
Data processing
Data visualisation
Good quality data
• File formats
• Import/export
• Memory
management
• Algorithms
• Error analysis
• Software
• Tables
• Plots
• Overlays
INTERPRETATION
4. Wednesday, 20 September 2017
No question about skills at Surrey
Very good literature in SIMS community
NPL’s
“good practices”2
SIA special issue
on MVA1
1February 2009. Volume 41, Issue 2. Pages 75–142
2www.npl.co.uk/upload/pdf/chemometrics.pdf
Great information on data processing
and interpretation, not as much on
data handling and visualisation
Introduction
4
5. Wednesday, 20 September 2017 5
Initial goal of my PhD: Learn and apply
those literature recommendations to data of
industrial samples* typically analysed at
Surrey’s Surface Analysis Lab.
*paints, adhesives, automotive polymers, additives…
Introduction
8. s i m s M V A
Wednesday, 20 September 2017 8
s i m s M V A is a Matlab-based app for
multivariate analysis of analytical data
(focus on ToF-SIMS)
Developed throughout my PhD,
motivated mainly by the idea of making
MVA quick and accessible to everyone in
the research group
PCA, NMF, MCR, k-means of different
data structures (spectra, images, depth
profiles, 3D)
9. s i m s M V A
Wednesday, 20 September 2017 9
Three examples from Surrey’s Surface Analysis Lab. were chosen
do demonstrate simsMVA and how data handling, processing and
visualising can aid data interpretation and ultimately surface
analysis.
1) Imaging of a resins
blend
2) Characterisation of
wood growth regions
3) Steel at high
temperature
10. s i m s M V A
Wednesday, 20 September 2017 10
1 – Imaging of a resin blend
Data from Surrey PhD student Ms Rene Tshulu
Sample is cut using ultra low angle microtomy, exposing/extending interfaces*
DOI 10.1002/sia.1985
*
2o
11. s i m s M V A
Wednesday, 20 September 2017 11
1 – Imaging of a resin blend
The area covering both interfaces is greater than the
primary ion beam raster size (500x500um2)
Several “patches” are needed (large area imaging)
Automated acquisition is tricky due to charging and
topography
Solution: create separate datasets and stitch them together
afterwards using s i m s M V A
12. s i m s M V A
Wednesday, 20 September 2017 12
.BIF6 files exported from IONTOF’s software
13. Wednesday, 20 September 2017 13
Normalised by total
counts
Poisson scaled MVA sampling 10% of
pixels*
*Low discrepancy subsampling as described in: 10.1002/sia.6042
Images mode
NMF Menu
s i m s M V A
14. Wednesday, 20 September 2017 14
Loadings / NMF spectra
Scores / NMF weights
MVA results tab
Variance / Error
s i m s M V A
15. Wednesday, 20 September 2017 15
NMF spectraOverlayed NMF weights
Overlay window
s i m s M V A
17. Wednesday, 20 September 2017 17
One single map gives a very complete initial description of the
sample, highlighting the two phases of the blend, the top surface
and the metal substrate with a chromate layer
- What if we have more samples?
- Which resin is which in the blend?
To expand the analysis even further, we can stitch measurements
of more than one sample together, and also include standards
s i m s M V A
18. Wednesday, 20 September 2017 18
Overlay window
Pure resins
(standards)
Patches of Sample 1
Patches of sample 2 Patches of sample 3
Distribution of peak intensity at 149 u
s i m s M V A
Cured BCured A
Resin A Resin B
SAMPLE 1
SAMPLE 3SAMPLE 2
19. Wednesday, 20 September 2017 19
Overlay window
K-means clustering
on NMF results
s i m s M V A
20. Wednesday, 20 September 2017 20
Overlay window
“Whole dataset processed as a single entity”
Scurr et. al 10.1002/sia.5040
s i m s M V A
Cured BCured A
Resin A Resin B
SAMPLE 1
SAMPLE 3SAMPLE 2
Cured resins 1 & 2
Uncured resin 1
Uncured resin 2
Metal substrate 1
Metal substrate 2
21. Wednesday, 20 September 2017 21
Surface mass spectra of different wood growth regions*
PLUS standard lignin and cellulose samples
Carefully selected peaks list for MVA (with characteristic peaks of cellulose, lignin and extractives)
2 – Characterisation of wood samples
DOI: 10.1002/sia.59154
s i m s M V A
*
22. Wednesday, 20 September 2017 22
Overlay windowData table
Poisson scaled
and
Mean centredVariables correlations
can be checked prior
to PCA
Spectra mode
Many variables selectedA few variables selected
PCA
s i m s M V A
23. Wednesday, 20 September 2017 23
Overlay window
Spectra mode
Loadings
Scores
Variance
Lignin peaks
Cellulose peaks
s i m s M V A
24. Wednesday, 20 September 2017 24
Overlay window
Spectra mode
Biplot shows loadings and
scores in the same plot
K-means finds categories
s i m s M V A
25. Wednesday, 20 September 2017 25
Stainless steel heated up in vacuum using special heating/cooling stage
Secondary ions images acquired periodically to create a data cube
3 – Stainless steel at high temperature
s i m s M V A
SAMPLE
HEAT
TOF-SIMS
Crater
with DC
beam
Scratch
using blade
DC beam removes the
oxide layer that regrows
after heating
26. Wednesday, 20 September 2017 26
Before any MVA, two crucial pre-processing steps
s i m s M V A
Peak background removal Pixels warping
27. Wednesday, 20 September 2017 27
Use simsMVA 3D mode to process
s i m s M V A
sub sampling of
voxels
NMF
28. Wednesday, 20 September 2017 28
Use simsMVA 3D mode to process
s i m s M V A
Video button to create a
“multivariate film”
30. Wednesday, 20 September 2017 30
s i m s M V A
Chamber Pressure
Temperature
Al+
Si+
Cr+
Al+
Go back and look at
individual ions
31. Wednesday, 20 September 2017 31
s i m s M V A can also be used to analyse other
analytical chemistry data
Data matrices can be loaded from Matlab
workspace
s i m s M V A
32. Wednesday, 20 September 2017 32
s i m s M V A
Al+
Si+
Cr+
Al+
Go back and look at
individual ions
FTIR of polyesters
33. Wednesday, 20 September 2017 33
s i m s M V A
Al+
Si+
Cr+
Al+
Go back and look at
individual ions
PIXE mapping of a fossil
34. Wednesday, 20 September 2017 34
s i m s M V A
Al+
Si+
Cr+
Al+
Go back and look at
individual ions
XPS depth profile
35. Wednesday, 20 September 2017 35
s i m s M V A
Al+
Si+
Cr+
Al+
Go back and look at
individual ions
SIMS depth profile of a solar cell
36. s i m s M V A
Wednesday, 20 September 2017 36
To know more about simsMVA visit
mvatools.com
37. Acknowledgements
Supervisors
- Prof. John F. Watts
- Dr. Marie-Laure Abel
simsMVA testers
- Ms Rene Tshulu
- Mr Jorge Banuls
- Ms Taraneh Moghim
Sponsors
- CAPES
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Editor's Notes
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.
- Fazer um rapido overview da apresentacao. Quando falar de resultados mencionar que foram feitas analyses SEM, EDX, XPS e SIMS.