►
From YouTube: DevoWorm #39: Breast Cancer Physics, Composing Braitenberg Vehicles, Simulating Tensegrity
Description
Discussion of breast cancer physics, simulating tensegrity and its consequences for biological organization (left-right asymmetry and robustness). Composing Braitenberg Vehicles in development and evolution. Going from a parts list to a phenotype that works. Paper on the interactions between organismal physics (bending forces) and molecular mechanisms. Attendees: Richard Gordon, Susan Crawford-Young, Bradly Alicea, and Morgan Hough
A
D
B
B
A
A
A
So,
however,
they're
not
going
near
the
damn
thing
and
I
had
someone
friend
she's
now
deceased,
she
had
breast
cancer
and
she
went
in
one
time
to
have
an
exam,
and
she
said
the
technician.
There
was
something
wrong
with
the
technician
that
day
he
didn't
care
whether
whether
the
whole
thing
is
flattened
permanently
like
it
was
a
bad
experience,
and
this
is
a
person
who
went
regularly
to
get
this
done
because
she
had
breast
cancer.
B
A
A
A
B
B
C
B
I
had
that
once,
but
not
not
for
breast,
it
was
for
some
sort
of
opioid
to
Painkiller
Painkiller,
where
you
could
control
the
painkiller.
Oh
okay,
and
this
this.
This
came
some
well
I
guess
in
the
last
10
20
years
it
came
in,
but
they
did
allows
the
patience
to
to
give
the
minimum
dose.
That
kills
the
pain
rather
than
somebody
deciding
in
advance
with
pain
doses,
so
they
control
the
injection
of
the
painkiller.
B
B
A
B
B
I
think
we'll
continue
with
it
and
but
take
your
take
your
warning
because
we
do
have
to
look
at
some
literature
on
y
compression
has
to
be
three
to
five
centimeters.
Is
that
due
to
the
x-rays
or
is
it
due
to
you
Well?
It
can't
be
doing
mechanical
positioning
because
if
they
find
something,
the
woman
has
to
come
back
yeah
for
treatment
just
now.
If
the
treatment
is
not
done
separately,.
B
B
A
B
B
A
Me
I'm
still
fighting
with
console
and
mice,
so
I
figured
out
that
I've
got
to
make
a
nice
little
hexagon
to
surround
it
instead
of
cylinder,
because
the
cylinder
has
four
nodes
to
describe
it.
So
I'm
going
to
make
this
hexagonal
thing
with
lots
of
nodes
around
the
side
and
then
I
can
hook
up
my
tissue
to
whatever
so
I'm,
making
I
think
I'll
make
it
out
of
I.
Don't
know
some
interesting
metal
or
glass
or
something,
although
I
could
make
it
a
beef
ring.
Apparently.
D
A
The
the
matrices
for
the
tensegrity
that
I'm
making
has
negative
eigenvalues
or
something
or
empty
matrices,
because
I
have
two
two
things
attached
to
one
node,
two
or
three
elastics
attached
to
one
node
or
one
one
rod
and
two
elastics.
So
it
doesn't
like
it
so
I'm
suspending
it
like
it
was
a
3D
spider
web
okay,
because
that's
actually
what
our
epithelial
tissues
look
like.
B
B
How
many
told
you
one
strange
observation,
I
made
I
once
used
the
high
voltage
electron
microscope
in
Albany
New
York
Axolotl,
epithelial?
Okay,
it
was
probably
a
nerved
and
the
pictures
you
know
you're
dealing
with
thick
tissues.
So
you
don't
get
sharp
tissue.
You
don't
get
sharpened,
but
it
looked
like
microtubules
went
right
across
from
one
cell
to
the
next.
A
Well,
I
I
have
to
get
I,
have
to
get
a
working
model.
First,
okay,
think
about
other
things,
but
it's
just
yeah.
It's
it's
being
a
pain,
I'm
learning
console
like
I.
Try
to
do
this
and
I
was
told
by
my
advisors
that
couldn't
I
just
get
something
or
other
and
thought
together
and
get
it
to
work
and
well.
No
I
actually
have
to
learn
console
and
rather
some
sort
of
death,
yeah
advisors,
don't.
B
A
A
B
A
As
my
main
method
of
modeling,
because
it
looks
like
I,
could
just
put
it
in
Matlab
and
just
use-
continue
mechanics
and
stop
messing
around
with
things
that
that
give
me
negative
eigenvectors
and
then
they
don't
give
me
the
matrices,
so
I
can
see
where
I
can
get.
It
goes
so
I'm
doing.
Guess.
Yes,
my
gosh
and
you
don't
do
that.
But
that's
not
I!
You
don't
do
that.
B
A
A
B
D
A
I
had
I
have
a
book
on
how
to
make
tensegrity
objects
in
actually
in
Matlab,
and
you
have
to
put
a
half
Twist
on
them.
They're
like
they
can't
just
have
them
like
line
up
like
this
yeah
the
Twist
on
them
like
this,
and
then
then
they
can
be
stable.
Oh
interesting,
but
Stills
aren't
like
that.
They're
not
like
this.
Unless
they're,
maybe
a
single-celled
organism
well,.
A
B
A
A
B
A
B
A
B
B
A
B
D
B
B
They
all
rotate
the
same
way.
So
what
this
means,
if
the
left
and
right
sides
of
an
animal
are
not
bilaterally
symmetric,
because
you
can't
you
can't
get
the
microtubules
on
the
left
side
are
not
a
mirror
image
of
the
ones
on
the
right
side,
they're
all
the
same
okay.
So
if
the,
if
they
do
something
mechanically
different
because
they're
on
the
left
and
right
sides,
they
might
end
up
causing
a
change
in
gene
expression.
A
Okay,
then
yeah
about
the
zebrafish
by
Merkel
that
you
had
that
you
had
saying
that
that
was
the
split
between
left
right
asymmetry
yeah
a
couple
of
months
back.
Maybe
it
was
last
winter,
some
of
that,
but
it
was
I,
think
it
was
maybe
poorly
written
because
I
read
it
several
times
and
wasn't
understanding
how
that
worked.
B
A
A
A
That's
the
the
the
paper
you
sent
me
about
well,
a
cytoskeleton
was
using
the
same
biochemistry
and
act
and
treadmilling
forms,
as
this
course
was
describing.
So
it
was
a
very
I
said.
It
was
very
helpful
because
I
was
using
this
new
knowledge
of
Art
and
bed
Milling
to
understand
what
the
paper
was
saying
and
it
was.
It
was
nice
somewhere.
D
A
lot
of
this
get
yeah,
it
gets
lost,
sometimes
just
it
there's
just
so
much
that
but
yeah
I
have
to
look
back
and
see
I.
Think
I
have
like
all
the
papers
arranged
in
different
weeks,
and
things
like
that.
So
I'll
take
a
look
too
okay,
so
yeah
what
what
am
I
move
on
to
the
thing
I
was
gonna
I
just
promised
that
I
dick
asked
me
about
the
breitenberg
vehicles,
which
we
talked
about
several
years
ago
in
this
group.
D
I
mean
in
my
other
group
we're
doing
some
work
with
it
in
terms
of
simulating
the
vehicles
in
their
nervous
system
and
all
that,
and
but
this
is
a
separate
stream
of
work.
This
is
something
we
talked
about
several
years
ago
in
terms
of
the
morphology
of
the
vehicles
and
how
you
can
have
these
different
parts
and
how
you
can
analyze
the
shape
and-
and
you
know
so
dick
asked
me-
you
know
he's
working
on
the
origins
of
life
and
I.
D
Think
this
was
you
know
the
question
was:
can
you
do
an
inventory
of
Parts
on
different
vehicles
so
to
to
understand?
Why
that's
relevant?
You
have
to
go
back
to
the
original
source,
which
was
Valentino
breitenberg's
book
on
vehicles,
and
he
publishes
this
in
1984.
and
the
vehicles
that
he's
so
hit.
D
The
point
of
the
book
was
to
take
he's
trying
to
he's
asking
the
question:
how
does
the
Mind
emerge
or
how
does
the
Mind
evolve,
and
how
can
you
get
go
from
like
say
like
the
bacteria
to
a
simple
nervous
system
that
exhibits
behaviors,
so
he
uses
this
thought
experiment
where
he
built
these
vehicles
and
the
vehicles
are.
You
know
mechanical
analogs,
of
very
simple
organisms,
so
they
could
be
like
bacteria.
They
could
be
like
little.
D
They
could
be
kind
of
like
C
elegans,
maybe
with
just
one
or
two
circuits,
and
so
he
built
he
designed
these
vehicles
in
the
book.
He
has
about
eight
of
them,
I
think
with
a
couple
of
variants,
so
there
may
be
about
12
total,
and
that
was
fourteen
fourteen
okay
and
and
so
they
all
have
their
own
shape.
So
like
there's
a
vehicle
one
which
is
a
square,
let
me
share
my
screen.
You
can
show
this
better
until.
A
D
Just
driving
from
memory
on
this
I,
don't
like
so
vehicle
one.
You
did
a
typology
of
vehicles
in
the
book,
so
he
starts
with
the
simplest
one,
which
is
one
and
that's
like
a
square
with
two
wheels:
two
light
sensors
at
the
front
and
then
connections
between
the
sensors
and
effectors
I
think
there's
a
full
connection
there.
So
it's
bilateral,
so
these
are
are
basically
bioetarians
but
they're
Vehicles.
You
know
they're
like
little
carts
that
move
around
in
their
environment
and
these
are
the
effectors
of
the
wheels.
D
This
is
what
moves
the
organism
the
sensors
are
in
the
front
which
detect
sensory
information
and
then
it
Maps
it
back
to
the
effectors
and
the
sensory
information
could
be
like
light
sources
or
chemical
sources
and
that
sort
of
thing
there
are
other
vehicles,
I
can't
remember,
but
they're
they're,
some
that
you
know
get
really
creative
with
their
morphology.
So
something
like
this,
where
you
have
like
multiple
effectors,
maybe
like
four
wheels,
you
know
and
they
may
turn
independently.
D
System
would
be
more
complex
inside
you
know
he
doesn't
really
specify
like
I
guess
you
know
they.
It
gives
drawings
and
that's
about
the
end
of
the
specification.
But
it's
basically
this
this
type
of
thing,
where
you
go
from
simple
to
more
complexity.
Just
you
know
draws
these
vehicles
out
and
and
roboticists
have
used
this
to
test.
You
know
they've
built
robots
where
they
build
these
little
vehicles
and
and
physically
and
they've
wired
them
up
and
done
experiments.
A
D
D
I
should
be
able
to
find
it.
Okay,
so
yeah
that
that's
the
idea,
but
what
I
guess
dick
wanted
to
know
is,
can
we
take
it?
Can
we
do
an
inventory
of
vehicles?
In
other
words,
can
we
take
the
parts
of
the
vehicle
and
do
an
inventory,
so
the
parts
would
be
like
the
sensors.
The
effect
is
the
connections
parts
of
the
body.
So
in
this
Square
instance,
it's
not
so
critical,
but
in
something
like
this,
you
have
like
a
compound
phenotype
or
you
have
the
front
just
now.
D
Yeah
I
mean
I,
guess
the
way
he
envisioned
it
was
that
you
have
you
go
from
simple
to
complex,
so
you
start
with
a
motif
like
the
square
and
then
you
move
up
to
like
the
square
would
be
like
here.
You
know
and
then
you
add
on
this
part
later
he
doesn't
get
into
like
a
lot
of
the
sort
of
the
phylogenetics
of
it,
which
I
will
talk
about
in
a
minute.
But
that's
that's
the
way
he
envisions
it.
So
it's.
D
D
D
So
I
put
together
a
couple
years
ago.
This
was
in
2016
I.
Think,
and
this
was
just
describing
I
did
a
talk
in
the
group
and
then
I
did
this
paper
to
put
it
together.
So
the
idea
is
that
you
have
rainbow
Vehicles,
which
are
these
vehicles
compound
polygons,
which
are
like
taking
these
polygons,
these
shapes
of
the
vehicles
and
then
composing
them
and
then
evolutionary
developmental
structural
complexity.
D
So
the
idea
is
that
you
have,
and-
and
this
paper
kind
of
goes
over,
like
some
comparisons
of
something
called
celebic,
Networks
and
other
things,
but
this
is
basically
you
know
you
have
the
Brandenburg
vehicle,
which
is
the
composite
polygon.
You
can
use
komodorov
complexity
to
evaluate
it
with
respect
to
its
its
physical
complexity,
how
many
sides
it
has
and
that
and
then
the
complexity
metric,
which
is
coherence
metric.
D
So
you
can
use
a
mathematical
measure
of
complexity
as
well,
so
I'm
going
to
skip
over
this
first
part,
but
I'm
going
to
go
to
a
second
part.
Let's
just
think
is
the
more
interesting
thing
here.
This
is
the
figure
that
I
wanted.
This
is
figure
three
and
so
red
side
is
the
key
part,
but
the
left
side
is
so.
This
is
a
phylogeny
of
a
type
1
vehicle,
and
so
this
isn't
so
much
the
evolution
of
the
body
plan,
but
the
evolution
of
the
connectivity
within
the
body.
D
Then
B
is
like
this
contralateral
connectivity,
which
is
where
you
go
from
the
right
hand,
sensor
to
the
left
hand
the
vectors
and
then
the
third
variant
is
where
you
have
both
types
of
connectivity,
and
so
you
see
that
you
can
put
a
make
a
phylogeny
out
of
that,
but
you
could
easily
do
this
for
like
the
morphology
as
well.
So
if
you
had
a
compound
phenotype,
you
could
have
like
where
it
has
you're
adding
on
like
parts
of
this
rectangle.
D
You
know
the
first
part
of
the
rectangle
on
the
bottom
might
be
the
sort
of
the
basal
condition.
The
second
part,
the
front
part
of
the
rectangle
might
be
the
derived
condition,
which
is
what
they
say
in
phylogenetics.
The
the
basal
would
be
like
the
adaptations
that
occur
down
at
the
base
of
the
tree
and
then
the
derived
conditions
are
the
ones
that
are
on
the
branches.
So
the
derived
runs
always
come
after
the
basal
ones,
so
you're
basically
composing
a
phenotype
based
on
these
changes.
D
D
So
those
things
are
at
the
sort
of
the
base
of
there
of
the
tree.
Then
you
have
the
hemispheric
segregation
of
connectivity
on
the
left.
So
this
is
where
we
say
that
that's
derived,
you
know,
and
there
are
ways
you
can
do
this
cross
connectivity
is
then
derived
between
B
and
C
and
then
cross
and
interest
hemisphere.
Connectivity
evolves
from
the
cross
connectivity
in
C,
and
so
you
can
have
this
kind
of
phylogeny.
Where
you
know
each
trait
has
like
a
An
Origin,
a
common
ancestry,
and
then
it
moves.
D
So
this
is
a
a
syllabic
network.
This
is
just
a
way
to
characterize
these
different
parts
of
the
vehicle
in
terms
of
syllables.
So
this
would
be
like
right,
wheel,
RW
LC
would
be
left.
The
left
connection
CC
would
be
cross
connection.
Fc
would
be
forward
connection
or
something
like
that
and
then
fsfs
as
another
descriptor,
and
then
it's
just
mapping
this
out
into
a
network
all
the
parts
of
this
and
then
giving
like
a
complexity
measure.
D
Another
slave
of
network-
and
then
this
is
actually
some
work
on
the
geometry
and
evaluating
it
in
terms
of
its
the
connectivity
of
the
different
shapes
that
get
composed
together.
So
the
idea
is,
you
should
be
able
to
draw
lines
through
the
edges
and
not
do
any
self-crossings
and
then
evaluate
it
that
way,
topological
analysis
and
then
there's
this
final
part
here,
which
I
thought
was
interesting.
D
D
So
these
would
be
like
the
regions
here
of
the
sort
of
this
vehicle
shape
and
then
you're
sort
of
looking
at
this
from
Two
on
Two
Dimensions
you're,
looking
at
it
as
a
you,
can't
really
see
the
labels
here
on
this,
but
there
are
divisions
in
this
direction
and
divisions
in
the
sort
of
the
horizontal
Direction
in
the
vertical
Direction,
and
this
comes
from
the
the
square
vehicle
the
vehicle
one
and
that
square
vehicle,
then,
is
you
know
decomposed
into
these
sets
of
divisions?
Or
you
know,
as
this
vehicle
expands
in
size?
D
You
know
what
do
we
need
do
we
need
a
number
of
Divisions
in
One,
Direction
or
another,
and
then
those
divisions
can
be
analyzed
as
a
differentiation
tree
where
these
different
parts
are
differentiating
over
time.
So
you
have
the
smaller
vehicle
where
it
may
be,
adding
on
to
it
as
a
composition,
but
you're
just
maybe
replicating
some
part
of
this,
some
smaller
part
of
the
vehicle.
It's
like
you
get
a
say
like
a
a
polygon
that
replicates
three
times
that
you
know
that
shows
up.
D
You
can
map
that
out
in
a
differentiation
tree
and
then
show
maybe
the
smaller
and
larger
components,
or
you
know
if
a
component
shrinks
or
expands
in
some
way
as
it
as
it
composes
a
more
complex
phenotype.
You
can
demonstrate
that
and
then
that
would
all
be
kind
of
like
in
this
origin
of
Life
thing
where
you
know
you
start
from
a
very
small,
primitive
and
you
expand
out.
D
B
D
B
D
D
D
D
B
B
B
D
D
Yeah
and
then,
of
course,
we've
created
a
in
terms
of
connectivity,
we've
created
a
well.
This
was
something
we
just
published
on
it's
a
platform
called
broaden
brain
which
actually
just
takes
the
internal
topology
of
the
of
the
brain
of
the
vehicles
and
generates
a
bunch
of
variants
from
a
genetic
algorithm,
and
so,
in
that
case,
you're,
actually
creating
different
possibilities
for
like
connectivity.
Some
of
them
don't
work,
but
some
of
them
do
work
and
get
promoted
to
the
Next
Generation.
So
yeah.
B
B
A
Put
the
book
by
again
here:
it's
you
can
get
it
for
I
think
you
can
get
it
for
free,
just
online,
okay
and
computational
modeling
of
tensegrity
structures
and
that's
where,
where
they
show
you
that
you
need
to
put
this
half
Twist
on
on
them,
even
a
triangular
one
has
to
have
a
twist
and
other
configurations.
So
it
was
a
somewhat
difficult,
read:
I
I
read
half
of
it,
and
that
was
fine
and
the
last
half
of
the
book
is
a
bit
it's
difficult.
Yeah.
A
So
just
put
it
that
way,
and
then
there's
an
MIT
course
online
about
origami
and
I
want
to
take
it.
But
it
said
I
needed
to
know
my
differential
equations,
so
I've
started
off
learning
relearning
my
differential
equations,
oh
boy,
good
the
course
for
a
long
time.
I
need
to
know
it
anyway.
Somebody's
going
to
think
I
know
that
and
they're
going
to
throw
something
at
me
and
I.
Don't
want
to
look
like
a
deer
in
headlights
because
that's
a
crash
foreign.
B
A
D
So
I
wanted
to
go
over
a
paper
dick
mentioned
in
the
meeting
that
we
had.
There
might
be
interactions
between
physical
forces
and
molecular
forces
in
some
cases
of
morphogenesis,
particularly
this
tensegrity
structure.
So
in
tensegrity
it's
Dynamic
tension,
it's
mediated
by
different
parts
of
the
phenotype
being
joined
together
in
different
ways.
Molecular
Pathways
May
either
affect
that
or
be
triggered
by
that
and
affect
it
subsequent
to
its
configuration.
So
this
is
all
fascinating,
but
I
wanted
to
go
over
a
paper
that
was
recently
share.
A
screen
recently
came
out.
D
So
let's
read
the
abstract,
so
apt
hydrolysis
coupled
actin
polymerization,
which
is
the
creation
of
actin
molecules
or
the
polymerization
of
actin
molecules
using
ATP
hydrolysis.
It's
actually
coupled
as
a
process
as
a
fundamental
mechanism
of
cellular
Force
generation.
So
this
is
where
cells
move
around
their
motile
and
to
be
motile.
D
They
don't
use
muscles
per
se.
They
use
actin
molecules
and,
of
course,
actin
molecules
are
components
of
muscle,
the
muscles
that
we
have
in
our
body.
So
they
behave
in
a
similar
way.
They
are
contr,
they're
contractile,
and
so,
when
you
expand
and
contract
them,
they
generate
forces
and
they
generate
movement.
So
in
turn.
So
this
is
the
first
part
of
this,
the
first
sentence,
so
cellular
Force
generation.
Just
so
we
know
what
we're
talking
about
in
turn,
force
and
actin
filament
or
F
actin.
D
So
what
we
have
is
we
have
Force,
which
is
the
physical
property.
We
can
measure
force
and
actin
filament,
nucleotide
state
or
f-acting
nucleotide
State
regulate
these
actin
Dynamics
and
so
they're
mechanisms
that
involve
Atkin,
binding
proteins
and
this
whole
process
of
polymerizing
actin,
so
that
the
cell
can
move.
D
So
there's
a
modulation
that
goes
on
through
bending
the
action
and
bending
forces,
and
this
affects
first
nucleotide,
state,
crayon,
electron,
electron,
microscopy
structures
of
ADP
effect
and
ADP
Pi
effect
and
with
sufficient
resolution
of
visualized
bound
solvent,
reveal
inter-subunit
interfaces
bridge
by
water
molecules
that
could
mediate.
Filament
lattice
flexibility,
despite
extensive,
ordered
solvent
differences
in
the
nucleotide
cleft.
These
structures
feature
nearly
identical,
lattices,
an
essentially
indistinguishable
protein
backbone
conformations,
which
is
the
shape
of
the
protein
backbone
that
are
unlikely
to
be
discriminable
by
actin,
binding
proteins.
D
So
that's
that's
the
abstract.
Let's
see
if
we
can
find
some
images
here
are
some
nice
images
of
the
nucleotide
cleft
water,
Networks,
they're,
remodeled,
upon
phosphate
released
by
a
fact
and
in
a
we
have
pry
OEM
Maps
of
this
ADM
effactin,
that's
on
the
left
and
the
admpi.
So
we
talk
about
those
two
things
in
the
abstract.
This
is
their
structure
using
cranial
electron
microscopy
in
B.
Atomic.
Models
of
the
densities
are
shown,
there's
the
barbed
end,
which
is
be.
B
D
And
so
this
is
just
information
about
the
structure
and
then
C
is
superposition
of
individual
adpf,
actin,
blue
and
ADP
Pi
effect
and
protomers
blue
and
orange
respectively.
So
they
just
place
them
atop
one
another
and
they
show
how
this
is.
This
is
the
nuclear
clef.
This
is
the
d-loop
very,
very
Advanced
structural
biology
here.
D
Then
we
get
into
this
water
molecule
aspect,
so
the
water
molecules
mediate,
key
longitudinal
and
literal
context
and
effective.
So
this
at
the
top.
You
have
your
water
molecules,
Violet
contained
within
the
filament
core,
so
you
can
see
the
Violet
Dots
here
that
are
within
this
filament
core
and
then
B
talks
about
solvent
mediated
contacts
at
lateral,
longitudinal
interfaces,
the
lateral
or
at
the
top,
the
longitudinal
or
at
the
bottom.
These
are
the
interfaces
of
ADP
act
and
during
shades
of
blue
and
adppif
actin,
which
are
shades
of
orange.
D
D
This
figure
shows
a
cryoelectron
microscopy
reconstructions
of
mechanically
deformed
effect
and
reveal
Bend
twist
coupling,
and
so
this
is
where
we
get
into
the
the
forces
in
the
movement.
You
have
this
Bend
twist
coupling
here
and
indeed
special
UCB,
stick
volumes
of
straight
and
bent
Maps,
and
you
can
see
this
for
how
this
it
unfolds.
D
In
this
case,
actinucleotide
State
modulate
subunit
sharing
during
filament
bending,
so
this
shows
kind
of
the
action
of
how
subunits
are
shared
during
this
bending
Force.
So
here
we
have
the
bending
this.
This
figure
actually
shows
it,
and
you
see
that
the
cartoon
shows
the
bending
and
how
this
shears
off
and
changes
the
structure.
This
is
in
the
ADP.
This
is
an
adppi
where
the.
D
A
little
bit
different
action
presence
of
the
pi
in
the
nucleotide
cleft
stiffens,
the
subunit
and
Alters
its
deformation
landscape,
so
this
Pi
being
in
this
cleft.
So
each
of
these
have
a
cleft
and
an
EDP
playing
EDP,
there's
no,
nothing
in
the
cleft,
the
bending
sort
of
this
thing
collapses
and
it
changes.
The
conformational
structure
here
is
dating
for
a
steric
incursion
of
neighbors
deforms,
the
subunit.
So
the
subunit
gets
deformed
this
in
adppi,
where
you
have
these
pis
occupying
the
cleft,
they
stiffen
the
subunit
and
Alters
the
deformation
landscape.
D
And
so
that's
a
that's
all
they
they
have
in
in
terms
of
figures,
so
I
hope
this
paper
rolling
over
this
paper
was
useful
in
thinking
about
some
of
the
things
we've
talked
about
in
the
meeting.
I
hope
you
learned
something
all
right.
Well,
that's
all
I
had
for
today.
Yeah
did
you
have
anything
else
you
wanted
to.
B
B
A
C
B
B
B
Metabolism
would
be
the
interactions
between
whatever
molecules
end
up
in
these
vesicles
and
you'd
have
to
simulate
each
one
and
have
a
Criterion
for
whether
or
not
it's
a
viable
metabolism.
But
in
our
case,
if
we
do
a
toy
model,
the
Criterion
for
something
being
working,
it
doesn't
have
to
be
alive.
But
if
it
meets
the
criteria,
then
you
can
get
an
idea
of
whether
or
not
this
approach
Works,
which
I
think
it
will
work.
B
B
D
C
You
know
phone
that
element
environment
right,
so
you
know
but
kind
of
the
burdens
on
you
to
to
create
of
the
appropriate
geometric
objects,
and
things
like
that-
and
you
know
just
just
to
even
get
started.
You
know
these
are
these
are
kind
of
more
limited
approaches,
but
but
again
they
were
just
very
much
designed
to
create
these.
C
You
know
simple
structures
that
that
might
might
be
useful
or
certainly-
but
this
is
this
is
unfortunately
kind
of
kind
of
an
old
NASA
project
like
I
forget
the
guy's
name,
it's
it's
kind
of
an
unusual
name.
I
can't
remember
the
the
lead
Pi's
anyway.
It
should
be
there
and
I
believe
he's
still
trying
to
work
on
something
similar,
although
he's
no
longer
at
NASA,
but
yeah.
C
You
know
in
this
approach
that
that
they
thought
would
be
super
useful
in
kind
of
Mars
missions
and
things
where
you
know
something
could
go
wrong,
but
yeah.
It
was
really
interesting
right
because
you
know
you,
you
don't
think
about
that
with
a
car
right
like
a
car
breaks
down,
and
then
you
just
go,
get
a
spare
part
kind
of
thing.
Yeah
right,
you
take
the
shot
not
out
here.
C
But
but
very
very
interested
following
the
conversation
and
and
again
like
hopefully,
hopefully
this
week,
I'll
I'll
with
the
the
Big
Nerd
Tech
X
hackathon
done
I
can
focus
on
some
some
other
things
and
I
I
think
there
are
some
other
good
software
projects
that
that
try
to
get
it
these
kind
of
more.
You
know
cellular
models.
C
Yeah
yeah
well,
and-
and
you
know
again,
this
was
like
a
big
part
of
his
work
right
was
was
was
making
you
know,
you
know
as
they'd
call
it
a
soft
body
robot
but
yeah,
but
but
in
a
sense
I
mean
it's
a
strange.
You
know
it's
a
strange
mechanical
design,
though
right
because
yeah
he
wanted
to
let
it
you
know,
for
you
to
kind
of
be
able
to
lose
tension
and
then
reconfigure
into
another.
C
B
C
It
self-repair
what
but
but
I
like
that
in
the
sense
of
like
like
to
me
that
you
know
again
and
thinking
about
I'm
trying
to
think
of
the
the
particular
evolutionary
biologist,
but
when
you
think
about
Evolution,
not
as
survival
of
the
fittest,
but
as
the
most
adaptable
right
that
these
kinds
of
you
know
these
kinds
of
resilient
designs.
And
these
you
know
possible.