Transcript Evidence Analyte/Characteristic Techniques Blood Ethanol

Lecture: Forensic Evidence
Physical Evidence
Any material either in gross or trace
quantities that can establish through
scientific examination and analysis
that a crime has been committed.
Forensic laboratories
Items of physical evidence
identification
evaluation
individualization
Classification of Physical Evidence
• Trace evidence
extremely small items
• Direct evidence
stands on its own to prove an
alleged fact
• Prima facie evidence
evidence established by law
• Circumstantial
evidence
incriminates a person
• Exculpatory evidence
helps to prove that an
accused individual is not
guilty
Physical evidence utilization in other areas
of forensic investigation
• Provides investigative leads for a case
• Ties one crime to a similar crime or connects one
suspect with another
• Corroborates statements from witnesses to or
victims of a crime
• The elements of a crime help to determine what
will be useful as evidence.
• Besides knowing what types of evidence to search
for, it is necessary to know where evidence is most
likely to be found.
Characteristics of evidence
Class characteristics
features that place the item
into a specific category
Individual characteristics
features that distinguish one
item from another of the same
type
E x a m in a t io n a n d a n a l y s is o f p h y s ic a l
e v id e n c e
H ig h e s t d e g r e e o f s c ie n t ific c e r ta in t y p o s s ib le w ith
c u rre n t te c h n o lo g y
p h y s ic a l
id e n tific a tio n
c h e m ic a l
id e n tific a tio n
b io lo g ic a l
id e n tific a tio n
Evidence
Analyte/Characteristic Techniques
Blood
Ethanol
Drugs of abuse
Composition
Color
Fabric
Fibers
Glass
Shoes
Powder
Soil
Saliva stain
Hair
Composition
Physical properties
Refractive index
Magnesium
Miscellaneous
Drugs of abuse
pH
Iron
Proteins
DNA
Appearance
Headspace analysis GC GC/MS
FT-Raman spectroscopy
Visible, diffuse reflectance
spectroscopy
FT-IR microscopy
Solubility, melting point
Microscopy
Atomic absorption
spectrophotometry
Solid-phase extraction; LC
FT-IR
Potentiometry
UV-Visible Spectr.
Immunological tests
Short tandem repeat
DNA analysis
Microscopy
Evidence
Techniques
Gunshot residue
Atomic absorption spectrophotometry,
scanning electron microscopy
Visible reflectance, FT-IR microscopy, FTRaman
UV–vis, LC
FT-IR, UV–vis
Thermal analysis, FT-IR
Liquid- and solid-phase extraction, GC/MS
Fluorescent visualization
Atomic absorption spectrophotometry,
titrations
Clothing
Pen inks
Plastic fragments
Tire fragments
Food (poisoned)
Fingerprints
Metals
Arson samples
GC, GC/MS
One morning in the summer of 1961, hundreds of crazed birds attacked the seaside
town of Capitola, California. The birds "cried like babies" as they dove into streetlamps,
crashed through glass windows, and attacked people on the ground. Most of the birds
were sooty shearwaters, a normally nonaggressive species that feeds on small fish and
comes ashore only to breed. The incident fascinated Alfred Hitchcock, who frequently
vacationed in nearby Santa Cruz. He included newspaper clippings about the Capitola
attack in his studio proposal for The Birds, which appeared in cinemas two years later.
In the winter of 1987, the agent that is now believed to be responsible for the Capitola
incident struck on the opposite shore of the continent. This time, it struck higher on the
food chain. Over a hundred people became extremely ill within hours after dining on
cultured blue mussels in restaurants around Prince Edward Island in Canada. It quickly
became apparent that this was no ordinary outbreak of food poisoning. Vomiting,
cramps, diarrhea, and incapacitating headaches were followed by confusion, loss of
memory, disorientation, and (in severe cases) seizures and coma. A few exhibited
emotional volatility, with uncontrolled crying or aggressiveness. Three elderly victims
died. [Perl].
A tragic symptom of poisoning was the destruction of short term memory in about one
quarter of the survivors. They could remember nothing that happened after the
poisoning. Some were unable to recognize their surroundings or relatives. They could
learn no new facts or skills. The most severely affected lost memories several years old.
For twelve of the victims, the loss of short term memory was permanent.
Figure 1. General strategy for isolation of the toxin responsible for
amnesic shellfish poisoning. Based on a diagram by M. Quilliam and J. L.
C. Wright (Analytical Chemistry, 61, 1054 (1989)).
A band very close to the band for glutamic acid was observed in the electrophoresis of the toxic XAD-2
fraction, but not in the control fraction. It stained a distinctly different color from the glutamic acid. When
the material in the band was collected and injected onto the HPLC column, it took exactly the same
amount of time to move through the column as the toxic component found by the HPLC analysis. It also
produced exactly the same amount of toxicity as the HPLC fraction had.
Mass spectrometry was used to determine the compound's molecular weight (312 g/mol) and molecular
formula (C15H22NO6). Spectroscopic analysis revealed the presence of conjugated double bonds and
features characteristic of an amino acid. By matching the spectra with those from STN International's
Registry system, the compound was unambiguously identified as domoic acid, an triprotic amino acid:
Domoic acid in acidic solution.
Glutamic acid in acidic solution.
Domoic acid is a molecular Trojan Horse. Nerve cells mistakenly
recognize domoic acid as glutamic acid- a fatal error. Domoic acid's
structure is obviously similar to glutamic acid. But its five-sided ring
makes it less flexible than glutamate, which causes it to bind very
tightly to glutamate receptors. As a result, the excitatory effect of
domoate is 30 to 100 times more powerful than that of glutamate
[Perl].
Individualization
Forensic laboratories
Items of physical evidence
identification
evaluation
individualization
Characteristics of evidence
• Class characteristics
features that place the
item into a specific
category
• Individual
characteristics
features that distinguish
one item from another
of the same type
Types of physical evidence
• BODY FLUIDS
 Conventional serology:
 presence of blood in stains
 species identification and
ABO grouping
 is not adequately
informative to positive
identify a person
 DNA analysis can associate
victim and/or suspect with each
other or with the crime scene
• BLOODSTAIN PATTERNS
 additional information
SEM: erythrocytes & lymphocytes
Types of physical evidence
• BODY TISSUES
 organ samples collected at
autopsy, including blood,
urine and stomach contents
• DRUGS & CONTROLLED
SUBSTANCES
 plant materials, powders,
tablets, capsules
 toxicological analysis
 volatile compounds (ethanol,
methanol, isopropanol)
 heavy metals (arsenic)
 nonvolatile organic compounds
(drugs of abuse, pharmaceuticals)
 miscellaneous (strychnine,
cyanide)
 trace drug presence, identity,
and quantity
 Black tar heroine wrapped in cellophane
Types of physical evidence
• DOCUMENTS
examination
 typed, handwritten and printed
materials for evidence of forgery
 indented writings, obliterated or
altered writings, used carbon
paper, burned or charred paper
paper and ink analysis
handwriting comparison to
determine authenticity
Obliterated writing examination
Types of physical evidence
• HAIRS
hairs analysis can
determine
morphological features
DNA analysis
toxicological
examination
 FIBERS





human/animal
race
body area
cosmetic treatments
method of removal (crushed,
cut, burned, forcibly removed,
fallen out naturally)
 can associate a hair to a
person
 positive identification
 presence of drugs and poisons
 type
 color, composition construction
Types of physical evidence
Two matching hairs identified with the
comparison microscope
Flax fibers viewed with
polarized light
Types of physical evidence
• FINGERPRINTS
 the strongest possible
evidence of a person’s
identity
Fingerprint Matching
• FIRE DEBRIS &
EXPLOSIVES RESIDUE
EXAMINATIONS
 identification of accelerants
and explosive residues
Unburned accelerator liquid on a soot covered carpet
Types of physical evidence
• FIREARMS & AMMUNITION
 individual microscopic marks
 identification, source,
operability of firearms.
 detection and characterization
of gunpowder residues
Photomicrograph: test
bullet - questioned bullet
 muzzle-to-garments distance
estimation
• GLASS FRAGMENTS
 Cause of breakage
 Direction of breakage force
 Physical fitting
 Glass fragment comparisons
Glass fracture produced
by a high-speed projectile
Types of physical evidence
• PAINT & PAINT PRODUCTS
 analysis and comparison of
paint transferred from the
surface of an object to another
during the commission of a
crime:
 Suspect vehicle impacting a
victim vehicle; a pedestrian or a
stationary object
 Tool impacting stationary object
 Paint databases can help
identify the year, make and/or
color of a motor vehicle from a
chip of paint left at the scene.
Paint Layers on Wood Surface
Types of physical evidence
• TOOLMARK IDENTIFICATION
 microscopic side-by-side
comparison
 attempts to link a particular tool
with a particular mark to the
exclusion of any other tool
• ROPE & CORDAGE
 composition, construction, color
and diameter
Spacing between teeth in gripping -major
role in toolmark examinations
manufacturer
Types of physical evidence
• SOILS & MINERALS
 comparison between two or
more soils to determine if
they share a common origin
 color, texture, composition
comparison
Layers of soil exposed at a grave site. Each
layer must be sampled
• WOOD
 place the suspect at the
crime scene
 side or end matching,
fracture matching and
species identification.
Cross-section - Xylem
Types of physical evidence
• OILS/GREASE &
COSMETIC PRODUCTS
• SHOEPRINTS & TIRE
TREAD IMPRESSIONS
 have value for forensic
comparisons.
 can provide positive
identification of the suspect’s
shoes or tires from the
suspect’s vehicle.
 possess unique composition
for comparison
Shoeprint
collected
using a
gelatin lifter.
Processing physical evidence
• discovering, recognizing and examining it;
• collecting, recording and identifying it;
• packaging, conveying and storing it;
• exhibiting it in court;
• disposing of it when the case is closed.
Lecture: Forensic Evidence and
Probability
Characteristics of evidence
• Class characteristics
features that place the
item into a specific
category
• Individual
characteristics
features that distinguish
one item from another
of the same type
The arithmetic mean is the "standard"
average, often simply called the "mean"
The standard deviation (SD) quantifies variability.
If the data follow a bell-shaped Gaussian
distribution, then 68% of the values lie within one
SD of the mean (on either side) and 95% of the
values lie within two SD of the mean. The SD is
expressed in the same units as your data.
1% of women at age forty who participate in routine screening have breast
cancer. 80% of women with breast cancer will get positive mammographies. 9.6%
of women without breast cancer will also get positive mammographies. A woman
in this age group had a positive mammography in a routine screening. What is the
probability that she actually has breast cancer?
1% of women at age forty who participate in routine screening have breast
cancer. 80% of women with breast cancer will get positive mammographies. 9.6%
of women without breast cancer will also get positive mammographies. A woman
in this age group had a positive mammography in a routine screening. What is the
probability that she actually has breast cancer?
STATISTICAL SOLUTION
To put it another way, before the mammography screening, the 10,000 women can
be divided into two groups:
•Group 1: 100 women with breast cancer.
•Group 2: 9,900 women without breast cancer.
After the mammography, one gets:
* 80 women with breast cancer, and a positive mammography.
i.e. 80% of 100
* 950 women without breast cancer, and a positive mammography.
i.e. 9.6% of 9900
The probability that a patient with a positive mammogram has breast cancer is:
# (breast cancer + positive mammorgraphy) / #(positive mammorgraphy )
= 80/(80+950) = 7.8%
1% of women at age forty who participate in routine screening have breast
cancer. 80% of women with breast cancer will get positive mammographies. 9.6%
of women without breast cancer will also get positive mammographies. A woman
in this age group had a positive mammography in a routine screening. What is the
probability that she actually has breast cancer?
BAYESIAN SOLUTION
The original proportion of patients with breast cancer is known as the prior
probability:
P(C) = 1% and P(~C) = 99%
The chance of a patient having a positive mammography given that she has cancer,
and the chance that of a patient having a positive mammography given that she does
not have cancer, are known as the two conditional probabilities. Collectively
information is often termed the liklehood ratio:
P(M | C) = 80% i.e probability of +ve mammogram given that she has cancer
P(M | ~C) = 9.6% i.e probability of +ve mammogram given that she does not
have cancer
The final answer - the estimated probability that a patient has breast cancer given
that we know she has a positive result on her mammography - is known as the
revised probability or the posterior probability.
1% of women at age forty who participate in routine screening have breast
cancer. 80% of women with breast cancer will get positive mammographies. 9.6%
of women without breast cancer will also get positive mammographies. A woman
in this age group had a positive mammography in a routine screening. What is the
probability that she actually has breast cancer?
prior probability x conditional probability = posterior probability
P(C) . P(M | C) = P(C | M)
P(~C) P(M | ~C) P(~C | M)
0.01 . 0.8 = 0.008 = 80
0.99 0.096 0.095
950
the estimated odds that a patient has breast cancer given that we know she has a
positive result on her mammography are 80 to 950
the estimated probability that a patient has breast cancer given that we know she
has a positive result on her mammography is 80 / (80+950) = 7.8%
prior probability P(C) .
P(~C)
The probability that the suspect is or is not guilty prior to presenting this
evidence
conditional probability P(M | C)
P(M | ~C)
Also called the Likelihood Ratio (LR) and represents the probability that this
evidence would be present if the suspect is or is not guilty
posterior probability P(C | M)
P(~C | M)
The probability that the suspect is or is not guilty given the evidence
presented
Bayesian Probability
•
Problem#1
A suspect is seen fleeing the crime. The suspect is positively identified as being at least six feet tall and was
wearing a nurse’s uniform. Exactly 5% of the male population is at least 6 feet tall, while 0.5% of the
female population is at least 6 feet tall, and 98% of all nurses are female. What are the odds that the suspect
is a male.
•
Problem#2
1 million people in America have HIV/AIDS. HIV tests correctly identify a HIV infected person with a
positive result 97.7% of the time. HIV tests correctly identify a non-HIV infected person with a negative
result 92.6% of the time. If an American gets a positive HIV test result what are the odds that they are
infected with HIV? (Assume an american population of 260 million)
•
Problem#3
Suppose that a barrel contains many small plastic eggs. Some eggs are painted red and some are painted
blue. 40% of the eggs in the bin contain pearls, and 60% contain nothing. 30% of eggs containing pearls
are painted blue, and 10% of eggs containing nothing are painted blue. What is the probability that a blue
egg contains a pearl?
•
Problem#4
There are 100 people in a room, 20 women and 80 men. 80% of women are blonde, while 30% of the men
are blonde. The suspect has blonde hair and is definitely one of the people in the room. What are the odds
that the suspect is a female.
•
Problem#5
The investigator on the case informs you that the odds that the suspect committed the crime are 2 to 1.
Your DNA fingerprint analysis of the suspect’s blood gives a 1 in a million probability that it is a random
match to the blood found at the crime scene. You also know that your lab has a 1 in a 1000 chance of a false
positive. What are the odds that the blood found at the crime scene came from your suspect?
Defender’s Fallacy :
P(S | M) = P(M | ~S) x sample population
Prosecutor’s Fallacy :
P(S | M) = 1 - P(M | ~S)
A crime has been committed, and a blood sample has been found at the
crime scene. The blood is typed as A- , a blood type found in 5% of the
population A suspect is identified, who also happens to have the Ablood type. In addition a DNA profile of the suspect gives the odds of a
random match of his blood to the blood found at the crime scene of
105 to 1.
What are the odds that this suspect was present at the crime scene?
What is the probability that this suspect was present at the crime
scene?
If the odds of a false positive for the DNA profile are one in a
thousand, what are the odds that this suspect was present at the crime
scene? What is the probability that this suspect was present at the
crime scene?
Bayesian Probability
•
Problem#1
A suspect is seen fleeing the crime. The suspect is positively identified as being at least six feet tall and was
wearing a nurse’s uniform. Exactly 5% of the male population is at least 6 feet tall, while 0.5% of the
female population is at least 6 feet tall, and 98% of all nurses are female. What are the odds that the suspect
is a male.
•
Problem#2
1 million people in America have HIV/AIDS. HIV tests correctly identify a HIV infected person with a
positive result 97.7% of the time. HIV tests correctly identify a non-HIV infected person with a negative
result 92.6% of the time. If an American gets a positive HIV test result what are the odds that they are
infected with HIV? (Assume an american population of 260 million)
•
Problem#3
Suppose that a barrel contains many small plastic eggs. Some eggs are painted red and some are painted
blue. 40% of the eggs in the bin contain pearls, and 60% contain nothing. 30% of eggs containing pearls
are painted blue, and 10% of eggs containing nothing are painted blue. What is the probability that a blue
egg contains a pearl?
•
Problem#4
There are 100 people in a room, 20 women and 80 men. 80% of women are blonde, while 30% of the men
are blonde. The suspect has blonde hair and is definitely one of the people in the room. What are the odds
that the suspect is a female.
•
Problem#5
The investigator on the case informs you that the odds that the suspect committed the crime are 2 to 1.
Your DNA fingerprint analysis of the suspect’s blood gives a 1 in a million probability that it is a random
match to the blood found at the crime scene. You also know that your lab has a 1 in a 1000 chance of a false
positive. What are the odds that the blood found at the crime scene came from your suspect?