►
Description
Attendees: Bradly Alicea, Mayukh Deb, Ujjwal Singh, Susan Crawford-Young, Jesse Parent, and Richard Gordon.
A
B
A
A
B
Thank
you,
yeah.
Basically,
there's
two
methods
of
doing
what's
going
through
the
mechanics
and
that's
where
you're
trying
to
calculate
the
flow
of
the
fluid
and
one
way
is
to
divide
space
into
little
boxes
and
calculate
how
much
fuel
comes
into
each
box
and
how
much
goes
out
and
that's
called
eulerian.
B
B
B
B
So
that's
that
these
are
the
ideas.
Then
I
sent
three
papers
two
recent
ones
on
nematodes.
I
think
there
are
new
drugs
and
a
paper
I
did
a
while
ago
on
the
motion:
what
happens
in
a
an
embryo,
the
very
first
cell
stage
at
low
gravity,
which
was
with
some
fellows
from
the
netherlands,
who
are
experts
in
lagrangian.
B
A
B
B
Somebody
then
maybe
we
can
proceed
with
it,
but
it's
obviously
a
large
combination
of
a
database
plus
a
plus
simulation
of
fluid
motion.
Basically
in
lagrangian
mechanics
now,
lagrangian
mechanics
is
used
in
water
research,
for
instance
in
the
wave
where
you
want
to
follow
the
drops
in
the
wave
and
see
how
they
how
they
move
and
they
can
separate
from
the
mass.
B
C
B
B
It's
been
quite
a
while,
since
I
worked
with
them
and
they
probably
improved
their
software
quite
a
bit.
I
don't
know
if
the
current
versions
are
available
or
not,
but
you
know
first.
First,
the
question
is
interest
right,
okay,
but
this
this
question
of
calculating
the
embryo
has
been
a
challenge
in
the
literature
for
a
long
long
time
and-
and
now
I
think,
we'll
reach
a
point
where
we
can
seriously
think
about
it.
B
C
A
On
that
orientation,
I'm
not
sure
I
think
it
would
just
have
to
be
a
matter
of
like
tracking
the
like.
If
you
had
the
a
good
resolution
image
and
you
could
track
it
in
the
way
that
well,
you
know
they
have
tracking
software.
That
is
sort
of
allows
you
to
sort
of
calculate
space
and
and
but
then
we
also
have
our
featured
detection.
So
you
know
we
might
be
able
to
detect
features
that
sort
of
align
with
that.
A
B
A
A
A
Pick
gunshier
and
streets,
strengths
and
weiss.
This
is
this.
Is
the
group
from
germany
I
take
it,
and
so
this
is
mechanical
cues
in
the
early
embryogenesis
of
c
elegans,
and
so
this
is
where
biochemical
signaling
pathways
and
developmental
processes
have
been
extensively
studied.
Yet
the
role
of
mechanical
cues
during
embryogenesis
is
much
less
explored.
A
So
there's
of
course
we
didn't.
We
don't
talk
a
lot
about
the
different
phases
of
development
in
in
this
group
too
much,
but
this
is
like
early
embryo
genesis.
This
is,
I
don't
know
how
many
I
can't
remember
how
many
cells
you
get.
You
have
to
get
two
to
get
the
gastrulation
and
c
elegans,
but
the
idea
is
that
you
know
they
divide
from
a
single
cell.
They
divide
into
two
cells.
A
One
is
the
posterior
and
one
is
the
anterior
end,
and
then
those
two
cells
form
two.
They
call
sublineages,
so
the
a
b
sublineage
and
then
the
p
sub
lineage
and
the
p
gives
rise
to
a
lot
of
the
specialized
lineage
is
like
ms
and
and
c
and
e,
and
those
are
usually
like
different
tissues.
P.
If
you
follow
that
there
is
the
germ
line,
which
is
where
the
eggs
come
from.
A
So
this
is
the
setup
here
so
they're
doing
this
custom-made
spim
image
acquisition,
there's
image
processing,
and
then
this
is
so.
This
is
let's
see
this
is
the
different
sections
of
c
elegans
that
they
have
and
actually
it
looks
like
they
have
a
graph.
It
looks
like
something
mayak
made
a
couple
weeks
ago,
where
you
have
this
three-dimensional
space.
A
You
know
you
have
have
these
cells
and
you,
you
know,
put
a
reference
frame
around
these
points
and
then
you
track
the
cells
and
you
find
that
they
yeah
they
have
this
trajectory
yeah.
My
oak
made
a
figure
like
this
a
couple
weeks
ago
and
I
think
it's
in
one
of
his
notebooks,
where
he
was
tracking
sort
of
the
position
of
cells
or
the
cell
lineage
in
the
embryo.
A
You
know,
given
that
you
normalize
the
the
embryo
across
embryos
and
you
know
across
divisions,
you
end
up
with
this
kind
of
space
and
then
you
can
track
the
motion
of
these
cells
and
these
motions,
of
course,
are
I
mean
some
of
them.
You
know
they're,
maybe
driven
by
mechanics
but
they're.
It's
basic
cell
motility.
A
The
cells
have
to
move
when
they
divide
when
they
divide
into
two
cells.
The
cells
reposition
themselves,
so
they
track
nuclei.
So
again,
this
is.
This
is
very
similar
to
what
we're
doing
in
in
the
machine
learning
context
where
you're
trying
to
find
like
a
centroid
or
something,
and
then
you
have
this,
you
can
track
those
centroids
assign
them
a
position
in
the
reference.
You
know,
assign
a
reference
frame
positions
and
then
that's
what
we
have
so
then
they've
done
this.
A
A
Maybe
another
level
we
need
to
add
to
it
where
you
have
like
a
physics
model.
Where
now
you
have
the
information
about,
you
know
the
positions
or
the
tracking
of
the
cells.
Now
you
need
to
have
like
sort
of
a
more
general
framework
how
cells
are
behaving
in
some
way,
and
so
this
arguing
that
a
good
physics
model
we'll
do
this,
so
we
probably
self-arrangements
that
arises
early
in
c
elegans
embryos
without
the
guidance
of
an
egg
experimentally,
a
t-like
arrangement
of
aba,
abp,
ems
and
p2
have
been
observed
when
removing
the
eggshell.
A
So
this
is
actually
an
experiment
that
we
did
it.
I
I
don't
know
if
I
was
talking
about
with
this
group,
maybe
several
years
ago,
but
there's
a
set
of
experiments
that
you
can
do
that
when
you
take
the
cells
out
of
their
egg
and
you
dissociate
the
a
b
and
the
p1
cells,
and
you
put
them
on
in
a
culture.
A
A
Can
they?
You
use
the
same
sort
of
hues
that
they're
using
in
the
egg
and
the
answer
at
least
based
on
that
that
set
of
experiments
is
no,
and
so
that's
how
the
physics
layer
is
important
here.
I
guess
so,
then
that's
that
paper
and
then
we
have.
The
teon
paper
explain
how
the
nematodes
early
embryogenesis
can
be
re,
precise
and
robust.
A
Here
we
set
out
to
provide
a
mechanistic
explanation
of
how
combining
mechanical
forces
with
the
order
and
orientation
of
cell
division
ensures
a
robust
arrangement
of
cells.
So
these
are
simplified
mechanical
model.
They
simulate
the
arrangement
of
these
cells.
They
they
introduce
different
disturbances,
so
they're
through
ordering.
A
A
They
review
the
mechanical
forces,
and
so
you
see
the
egg
here
in
the
cells
and
they
have
these
mechanical
forces
that
act
between
cells
and
then
between
the
egg,
shell
and
the
cell,
and
then
they
show
the
classic
lineage
tree,
which
is
just
how
things
are
ordered
in
time.
Well,
they're
ordered
in
time,
but
they're
also
ordered
along
this
anterior
posterior
axis.
A
A
So
you
have
this
force
that's
generated,
and
then
this
distance
and
the
I
guess
the
idea
is
that
there's
this
relationship
between
forces
between
the
cells
and
the
distance
between
cells,
and
so
they
model
that
as
well.
So,
let's
see
there,
they
model
this.
They
focus
on
the
mechanical
robustness
of
cell
arrangement
against
perturbation
up
to
the
24
cell
stage
and
c
elegans.
A
A
You
know
basically
what's
happening
when
you
get
these
sublimations
work
so
by
the
24
cell
stage.
You
get
all
your
major
sublineages
formed
they're
what
they,
when
you
get
to
the
eight
cell
stage
of
c
elegans.
They
have
what
they
call
the
eight
sub
lineages,
which
will
be
the
sub
lineages
that
exist
for
the
rest
of
c
elegans
life.
A
There
are
four
a
b
sublineages
and
then
there
are
four
sublineages
in
the
p
sub
lineage.
So
there's
I
can't
remember
the
names
right
now,
but
but
they're
they're,
four
and
four
so
they're
four
they're
coming
from
the
posterior
two
cell
and
four
that
come
from
the
anterior
two
cells,
so
there's
that
sort
of
symmetry
and
so
then
from
there.
A
You
know
that,
like
all
these
sublimages
are
sort
of
in,
as
maybe
some
position
in
this
in
the
egg,
and
you
can
look
at
basically
how
that
that
establishing
process
works
so
it
maybe.
It
makes
sense
to
look
only
to
the
24
cell
stage,
because
that's
where
a
lot
of
your
you
know,
sublineages
are
sort
of
positioned
to
start
to
proliferate
in
in
sort
of
the
areas
of
this
embryo
that
they're
going
to
later
form
tissues
and
other
things.
So,
let's
see
so.
This
is
the
figure
here.
A
So
they
have
these
different
conditions
that
they
do
and
then
b.
Is
this
one
cell
cell
contact
map
of
eight
cell
stages
after
changing
the
sequence
of
events,
two
and
three,
so
they
change
the
event
order
and
they
see
what
the
contact
looks
like
so
they're.
You
know
they're
like
you're,
taking
that
lineage
tree
they're,
changing
the
division,
events
or
the
order
of
them
and
then
they're
looking
at
these
cells.
A
So
I
guess
that
they're
doing
is
they're
taking
like
they're
taking.
If
you
didn't
divide
a
cell
and
you
divided
some
other
cell
and
you
wanted
to
look
at
how
they
would
sit
together,
you
know
they're,
basically
asking
do
these
mechanical
constraints,
explain
the
order
of
the
timing
of
division
and
their
relative
locations,
or
is
it
maybe
you
know,
does
it
really
matter,
because
you
know
the
cells
are
basically
all
in
the
same
place?
Where
that
you
know
it's
all
equivalent
and
there's
just
this
general
set
of
forces.
A
A
About
playing
around
with
the
order
and
thinking
about
like,
why
is
c
elegans
development?
Why
does
it
unfold
in
a
certain
way?
We
just
kind
of
sometimes
default
to
this
explanation
about
genes
and
this
and
that,
but
you
know
it
could
be
mechanical
constraints
or
it
could
be
something
else
entirely,
but
I
think
doing
these
kind
of
experiments
are
quite
useful
for
that,
and
you
can
do
this
a
bit
computationally
if
you
have
like
a
good
model
of
the
cells-
and
this
is
so.
A
Data
on
that,
I
don't
know
how
accurate
they
are.
Those
were
derived
from
the
epic
data
set
a
long
time
ago,
so
we
might
pull
those
back
up
and
look
at
them
again.
I
don't
know
exactly
how
accurate
they
are,
but
they
might
be
useful
to
look
at.
We
might
be
able
to
re-extract
them
out
of
the
image
data.
A
That's
what
I'm
saying
and
that
might
be
a
bit
more
accurate,
but
this
is
so
they've
done
this
experiment
and
again
this
is
just
like
tracking
this,
the
mother
cell
and
the
daughter
cells,
they're,
they're,
centroids
and
then
looking
at
the
angle
of
so
one
daughter
cell
goes
in
one
direction.
One
daughter
cell
goes
in
another
direction
and
there's
this
angle
between
them
and
so
the
angle,
then,
what
does
that
represent?
Is
that,
like
you
know,
is
that
random?
A
A
A
A
This
is
another
physical
biology
paper.
The
one
cell
amphibian
embryo
is
modeled
as
a
rigid
spherical
shell
containing
equal
volumes
of
two
immiscible
fluids,
with
different
densities
and
viscosities
and
a
surface
tension
between
them.
The
fluids
represent
denser
yolk
in
the
bottom
hemisphere
and
a
clear
cytoplasm
and
the
germinal
vesicle
in
the
top
hemisphere,
and
so
the
unstable
equilibrium
configuration
of
the
inverted
system
depends
on
the
value
of
the
contact
angle.
A
Yeah
and
so
the
two
dominant
types
of
modes
of
perturbation
give
rise
to
a
axis
symmetric
and
asymmetric
sloshing
of
the
cytoplasm
of
the
inverted
embryos
respectively.
This
is
where
it
quantifies
our
hypothesis
that
the
axi
axis
symmetric
mode
corresponds
to
the
failure
of
development
and
the
asymmetric
sloshing
mode
corresponds
to
developmental
development,
proceeding
normally,
but
with
reverse
pigmentation
for
inverted
embryos,
so
here
they're,
showing
like
some
of
these
properties
of
the
cell
and
they're.
Looking
at
like
these
instabilities,
so
rally
instability
is,
I
can't
quite
remember
what
that
is.
Oh.
A
A
A
The
dotted
line
shows
the
flat
surface
when
the
contact
angle
is
at
90
degrees.
So
you
get
this
slight
curvature
and
then
so
this
is,
this
is
actually
inspired
by
amphibian
eggs.
So
our
axolotl
eggs
that
we've
talked
about
in
the
meeting
are
amphibian
eggs,
and
this
is
a
bit
different
from
c
elegans.
If
you've,
we
just
talked
about
c
elegans
in
the
last
two
papers.
A
So
now
this
embryo,
this
type
of
embryo
that
we're
talking
about
here,
is
different
from
c
elegans,
and
then
it
doesn't
have
that
same
programmed
fate
aspect
to
it.
There's
a
lot
of
signaling
that
goes
on,
and
you
know
you
have
different
things
it.
The
the
the
egg
is
much
different
in
terms
of
how
it
develops.
A
So
we
divide
the
problem
into
two
separate
steps.
First,
we
calculate
the
unstable
equilibrium
configuration
of
the
system
where
the
heavier
liquid
is
on
top
and
try
to
find
the
equation,
describing
the
non-planar
interfacial
surface
between
the
two
liquids
and
then
the
second
thing
is
that
they
introduce
some
small
deviation
from
the
equilibrium
configuration
and
study
the
growth
rate
of
each
normal
mode
of
perturbation.
A
A
So
that's
what
they're
doing
with
this,
and
so
they
use.
Let's
see
these
this
sort
of
mathematical
model,
so
you're,
using
in
a
set
of
navier-stokes
equations
for
free
surface
flows,
and
so
that's
simulation.
You
can
run
in
a
computer
program,
of
course,
and
then
you
can
get
you
know
you
can
solve
some
of
this.
A
A
So
each
plot
shows
these
coefficients
versus
time.
So
this
is
time-
and
this
is
the
coefficient
value
indicating
that
to
a
fairly
good
approximation,
only
the
initial
mode
is
oscillating
and
the
rest
of
the
modes
stay
calm,
showing
that
the
modes
are
in
fact
normal
modes
of
the
system.
So
this
is
for
the
different
modes,
and
then
this
is
a
velocity
field
analysis.
A
A
So
I
think
I'm
going
to
wrap
that
up.
I
think
that's
a
nice
set
of
papers
and
again,
if
you're
interested
in
this
go
to
that
folder
look
at
the
papers
and
you
know,
share
some
of
your
ideas
of
this.
Let's
see
what
we
have
in
the
chat
here,
some
things,
so
we
have
I'm
interested
in
fluid
modeling
for
my
thesis,
susan
says
and
then
maya
says.
A
So
if
you're
interested
feldman
dr
veldman
recommended
open
foam
to
me
and
that's
susan
and
then
dick
says,
can
we
say
anything
about
variability
at
the
local
level,
such
a
spatial
angle
of
a
division
versus
longer
range
effects?
That's
a
good
question.
We
if
we
have
the
angles-
and
we
know
in
like
in
c
elegans-
we
know
what
the
cells
are
that
are
dividing
in
the
angle.
A
A
So
a
couple
words
before
we
start
with
like
updates
number
one,
is
that
the
this
is
the
final
week
of
g
suck,
so
everyone,
our
ojuan
mayokar,
probably
excited
to
be
done
with
gsoc,
and
if
we,
I
think
I
can't
remember
exactly
the
time
that
they're
due,
I
think
they're
due
next
this
weekend
or
next
monday
or
something
the
31st.
Is
it
I
would
double
check
the
schedule
just
to
make
sure,
because
they
have
like
a
certain
time
of
day
it
has
to
be
in.
A
And
so,
and
the
time
of
course,
is
utc
so
make
sure
that
you
convert
the
time.
So
you
have
it
in
on
time,
then
I
guess
would
you
need
to
turn
in?
Like
I
said
last
time
is
some
sort
of
readme
or
you
know
you
could
use
a
gist.
I
don't
know
what
you
want
to
use
to
submit
okay,
but
you
know
just
basically
have
a
description
of
the
project,
and
this
is
you
know,
irrespective
of
if
you
have
like
a
bunch
of
notebooks,
you
basically
want
to
clear
like
sort
of
readme.
A
That
says
this
is
what
I
did.
This
is
what
I've
learned
and
then
these
are
the
links
that
are
important
to
see
the
project
and,
again,
you
know
they're
going
to
go
into
the
project
they're
going
to
go
into
this
readme
and
they're
going
to
click
on
the
links
and
they
have
to
run
or
produce
some
sort
of
output.
A
In
order
for
you
to
pass
so
I
mean
like
it's
not
too
scary
just
to
say
that,
like
you
know,
you
just
want
to
make
sure
that
they're
all
sort
of
in
working
order,
no
bugs
or
anything-
and
I
just
say
that
just
to
because
you
know,
if
something
ever
happens,
people
get
upset
or
something.
But
so
then
I
think
both
of
you
have
done
pretty
good
work.
I've
asked
oswald
to
assemble
all
the
links
to
the
work
that
he's
done.
So
he's
got
a
bunch
of
links
in
different
places.
A
A
I
think
I
don't
think
dick
has
seen
the
diva
learn
organization,
but
this
is
divalern
and
has
a
number
of
things.
So
we
have
data
science,
demos,
which
are
actually
something
that
mayuk
and
krishna
katyal
have
contributed
to
already
so
the
network's
stuff
is
from
or
from
mayuk,
and
he
pushed
a
bunch
of
things
related
to
these
embryo
networks.
A
So
he's
produced
some
graphs
here
that
are,
you,
know,
kind
of
show
some
principles,
there's
some
data
in
here
and
some
other
animations,
and
then
we
have
krishna
actually
pushed
a
tutorial
on
you.
Next
command
line,
basics
or
linux
command
line
basics.
And
so
that's
that's
nice.
It's
a
notebook,
and
I
see
that
in
slack
slack
suggested.
You
know
making
a
notebook
free
version,
which
I
I
agree
with,
because
I
think
notebooks
on
github
are
not
always
they
don't
always
render
properly
so,
but
we
have.
This
is
c
elegans,
divo
learn.
A
This
is
the
the
library
that
my
has
been
working
on
well.
Actually,
no,
this
is
this
is
my
ex
is
diva
learn
here.
This
is
the
one
that
mayak's
been
working
on
the
libraries
with
all
of
the
notebooks
and
then
c
elegans
evil
learn
is
actually
usually
project
and
that's
with
a
lot
of
the
things
pushed
to
this,
and
so
we
have
so
that's
all
in
place
pretty
much
and
then
the
contribution
guidelines
which.
A
And
this
just
describes
like
how
do
you
contribute
to
this
and
then
the
final
one
is
the
media,
which
is
just
where
we
put
a
lot
of
files
that
are
don't
really
have
any
other
home
and
so
we're
going
to
publicize
this
start.
I
think,
starting
this
week,
we're
going
to
sort
of
announce
it
to
the
world,
and
so
I've
been
preparing
a
blog
post.
A
A
Maybe
tomorrow
and
then
we
can
start
to
announce
it
and
then
we'll
turn
the
gsoc
projects
in
by
the
31st,
and
then
you
know,
and
then
we
can.
You
know
if
we
want
to
build
on
on
top
of
this,
and
I
think
it's
nice
to
have
as
a
reference
as
a
resource,
but
I
think
you
can
also
build
on
top
of
it
like
we
just
talked
about
with
the
physics
modeling.
A
You
know
it
allows
you
to
this.
This
platform
will
allow
you
to
take
data
or
take
images
or
image.
You
know
movie
images,
images
of
movies
of
images,
put
them
into
this
program
and
it
will
yield
some
sort
of
quantitative
analysis
of
those
images,
so
it
could
be
like
cell
centroids.
It
could
be
other
types
of
information
about
angles
or
about
networks
between
dependencies
between
the
cells
in
terms
of
distance,
so
we
have
all
of
that
in
place,
and
that
can
be
done
and
now.
A
The
next
step,
of
course,
is
to
use,
like
you
know,
maybe
build
a
theoretical
model
or
some
sort
of
other
model
that
you
know
whatever
you
want
to
do.
It's
going
to
be
a
lot
easier
now,
and
people
in
the
community
can
use
it
as
well.
So
people
want
to
you
know
if
someone
is
interested
in
the
topic
and
they
don't
know
where
to
start
with
respect
to
you
know:
quantity
quantifying
their
images,
we
can,
we
have
a
platform
for
them
and
so
well.
A
D
D
E
A
Yeah,
I
mean
that's,
that's
pretty
much.
I
mean
he'll
be
back
he'll
finish
up,
but
I
think
that's
the
overview
of
what
he's
gonna
have.
What's
I
guess
it's
live
now,
so
I
can
send
that.
Well,
I
think
I'll
put
the
links
in
the
blog
post
and
I
can
send
the
links
out
as
well
to
people
if
they
didn't
get
stuff.
A
The
data
sets
are
organized
that
ones
that
we
had
that
were
sort
of
collected
from
different
sources.
So
we
have
a
broad
variety
of
input.
Data
and
those
are
organized
so
people
they
come
into
the
thing
and
they
want
to
do
some
analysis.
They
want
to
find
a
data
set
that
they
can.
You
know,
quantify
really
quickly,
they
can
download
a
video
and
then
they
can
put
it.
You
know
up
into
this
platform
and
then
it'll
give
them
some
quantitative
output
and
then
they
can
work
with
that
output
and
it
will
give
you.
A
You
know
a
pretty
quick
analysis
of
this.
I
think
a
lot
of
the
analyses
in
the
past
have
been
sort
of
you
know,
like
you
saw
in
that
paper,
where
they
had
a
method
section
where
it
was
very.
You
know
I
mean
it
basically
described
what
they
were
doing,
but
then
could
you
do
it
yourself?
Well,
you
know
that's
why
I
think
one
of
the
reasons
why
we
went
into
this
whole
project
is
that
you
know
we
wanted
to
make
this
a
lot
easier
to
do
for
a
wide.
C
A
F
F
F
So
these
two
things
I
am
working
on
and
apart
from
that,
I
have
like
started
working
on
table
editor
that
I
have
proposed,
so
it
is
almost
complete,
like
I
have
just
used
some
java
script
weeks
that
it
is
not
copy
yet,
so
these
sort
of
things
will
also
be
completed
by
this
week.
So
I
think
that
my
badness
day.
A
A
Yes,
okay!
So
that's
those
are
the
urls.
So
that's
where
everything's
gonna
be
hosted.
We
have
so
it's
gonna
be
nice
and
then
I
think
the
only
thing
left
is.
I
think
that
the
when
this
is
done,
we're
going
to
have
to
think
about
maybe
how
to
more
of
a
community
point
but
like
how
to
guide
people
through,
because
I
know
we're
trying
to
make
it
accessible.
F
A
Yeah,
I
think
that's
good
yeah
and
I
think,
like
you,
know
that
sort
of
thing
and
then
you
know
we'll
have,
I
think
you
know.
After
we
start
getting
contributors,
we
might
end
up
sort
of
getting
like
these
little
guideposts
where
they
can
go
through.
You
know
they
can
walk
through
the
platform
and
you
know
say
they
want
to
do
some
sort
of
analysis.
A
I
think
another
step
might
be
to
have
you
know,
like
maybe
videos
where
people
walk
through.
I
mean
this
is
after
gsoc,
of
course,
but
I'm
just
thinking
about
how
we
can
make
it
easy
to
use
and
again
it's
all
going
to
come
down
to
who's,
using
it
and
kind
of
like
getting
a
sense
of
who's,
contributing
or
who's
just
using
it
or
what
how
how
it's
being
used
so
and
again,
like
I
said
I
think,
that's
good.
I
think
there's
always
room
for
like
contributing
in
terms
of
like
data
science
content.
A
So,
like
people
have
ideas
about
how
they
might
apply,
you
know
some
sort
of
technique,
or
maybe
a
tutorial
on
that.
That's
always
useful,
or
you
know
we
can
go
in
the
direction
of
modeling,
which
we
don't
have
a
repo
up
there
for
yet,
but
you
know
to
have
like
think
about
it.
This
in
terms
of
models.
We
can
take
the
images,
get
data,
quantitative
data
out
and
then
maybe
not
a
machine
learning
model
like
a
physics
based
model
or
something
where
we
can
actually
look
at
different
sets
of
questions.