►
From YouTube: DevoWorm, Meeting #11: GSoC Update, Soft Matter and Aneural Behavior, Synteny as Building Blocks
Description
Google Summer of Code projects and application process. Soft Matter and Physics of intentional and collective behavior. Synteny (Chromosomal Organization) as Developmental Building Blocks. Attendees: Susan Crawford-Young, Karan Lohaan, Harikrishna Pillai, Ishan Shanware, ABD, Jiahang Li, Ujjwal Singh, Abhipsha Das, Anh Nguyen, and Bradly Alicea
B
I
went
to
that
aps
physics,
symposium,
and
there
was
one
on
networks
that
I'm
going
to
send
you.
She
did
work
with
zebra
fish
and
she
pulled
on
the
tissue
of
the
developing
dome,
the
first
one
of
the
first
stages
in
the
zebrafish
with
a
pipette,
and
she
found
that
the
tissue
that
was
on
the
sides
was
more
firm
than
the
top
and
then
they
did.
They
looked
at
it
through
a
microscope
and
looked
at
the
tissues
and
then
made
a
network
out
of
where
the
how
the
tissues
were
joined.
B
B
A
A
C
C
A
A
Well,
that's
good
yeah!
Thank
you
for
attending.
Welcome,
yeah,
we'll
talk
about
that
in
a
little
bit
and
then
we'll
probably
talk
about
some
other
things.
Our
meetings
are
usually
pretty
broad,
but
if
you're,
in
our
slack
in
the
open
worm
slack
and
the
diva
worm,
channel
you'll
get
news
about
the
project
as
we
go
through
the
application
process.
I'll
be
posting
more.
There.
D
D
E
Like
last
few
months
are
very
busy,
so
I
was
a
little
bit
distinct,
but
I
guess
now
I
can
start
regularly
attending
meetings
once
again.
Okay,
so
I
was
working
on
my
bachelor
thesis
project
and
there
is
a
side
party
that
we
are
doing
with
our
professor
to
change
some
to
create
some
sort
of
new
navigation
which
is
still
under
patent.
So
I
cannot
talk
much
about
it.
So
that's
it
well,.
G
G
So
if
you
want,
I
can
introduce
myself
again,
yeah
go
ahead.
My
name
is
muhammad
abdullah
and
I'm
currently
a
third
year.
So
when
I
joined
the
open,
I
was
second
year
so
now
I
have
a
third
year
from
vnit
and
I'm
currently
learning
object,
detection
and
segment
segmentation
along
with
just
started.
The
gnn
part.
A
So
all
right,
so
why
don't
we
start
with
gsoc?
I?
I
know
a
lot
of
people
are
here
for
that
and
again
I
like
to
go
through
this
weekly
so
that
people
have
an
idea
of
what
we're
doing
so.
So
this
is
the
website
here.
This
is
the
timeline
for
2022.
So,
let's
see
the
contributor
proposals
are
open
on
april
4th,
so
we're
somewhere
in
here,
and
the
next
deadline
of
course,
is
when
the
proposal
portal
opens.
A
A
So
that's
in
about
a
month,
so
you
have
four
weeks
or
so
to
write
your
proposals
up
and
I
talked
about
the
proposals.
Last
week
I
talked
about
the
outline
and
proposal.
What
a
proposal
should
look
like
it
should
have
the
introduction
motivating
what
you're
doing
then
it
should
have
the
maybe
some
some
sort
of
proof
of
concept
or
some
sort
of
details
about
the
method.
If
you
can
work
with
some
of
the
data,
you
know
that
we
have
it's
it's
better,
because
you
can
show
how
your
method
is
going
to
work.
A
You
know
sometimes
with
some
of
these
methods
you
have
to
tune
them.
You
know
play
around
with
them
in
advance
to
get
a
sense
of
what
they
can
do.
So
you
don't
want
to
propose
something.
That's
wildly
off
base.
You
know
you
want
to
be
able
to
have
a
good
proposal,
because
when
you
start
the
program,
then
you
want
to
jump
right
into
it
and
you
want
to
be
able
to
hit
your
goals
and
so
that
last
part
of
the
proposal
is
a
timeline
that
has
you
know
everything
week
by
week.
A
So
I
want
to
make
sure
that
people
have
that
in
their
heads
kind
of
the
deadline
and
then
how
to
outline
everything-
and
you
know
so-
and
you
can
send
me
a
proposal
draft
if
you're
you
know
when
you're
at
a
good
stage,
don't
send
me
something,
you
know,
that's
very
loose
set
of
ideas.
Just
send
me
something.
A
A
It's
a
run
by
incf,
that's
our
sponsoring
organization,
and
so,
if
you
go
to
neurostars.org,
if
you
haven't
gone
there,
you
can
log
in,
and
you
can
ask
questions
in
this
forum.
This
is
kind
of
you
know
it's.
It's
runs
parallel
to
our
slack.
Our
slack
is
private
to
our
open
worm
group,
but
incs
incf
is
broader
and
it's
a
lot
of
times.
People
will
come
here
to
find
out
just
to
find
out
about
the
project
to
see
what
projects
are
being
offered
by
incf.
A
A
A
A
Those
are
two
that
we've
been
working
on
over
the
last
several
years
and
bringing
those
resources
together.
So
if
you're
working
on
the
gnns,
you
know
that
would
that
would
be
added
to
this
library.
So
you
know
you
would
be
contributing
to
that
area
of
research,
and
so
then
we
have
this
other
project.
I
don't
know
how
many
other,
how
many
people
are
interested
in
this
one.
I
know
at
least
one
or
two
of
you
are,
and
this
is
the
digital
microsphere,
so
this
is
based
on
susan
crawford,
young
who's.
A
A
You
know
working
on
getting
people
so
that
they
can
do
this
project,
and
there
are
a
couple
readings
here
and
you
know
the
skill
there
is
just
kind
of
like
you
know:
can
you
build
a
three-dimensional
or
a
four-dimensional
model?
Actually,
but
can
you
project
that
onto
a
sphere
and
do
you
have
a
method
for
doing
that?
A
B
B
And
then
you
can
adjust
the
angle
here
so
that
you
can
zoom
in
on
the
spot
in
the
middle,
which
is,
I
don't
know
whatever
you're
taking
a
3d
image
of,
and
it
could
be
anything
from
a
snail
to
a
well.
In
my
case,
I
want
to
take
pictures
of
axolotl
embryos
which
are
basically
around
objects
in
the
center
of
this
and
they're
they're
digital
microscopes,
so
you're
getting
images
from
criminal
sides
taken
sequentially
at
the
the
rate.
Well,
the
way
I've
got
it
set
up
for
the
moment.
A
Thank
you
for
showing
that
yeah,
so
yeah,
that's
the
the
apparatus
for
that
one
and,
like
you
know
it's
either
project
is
good
and
you
know
I
know
a
lot
of
you
are
interested
in
gnns
for
the
gnns.
Again
we
have
the
diva
worm
or
the
devozu
data
source
so
that
data
source
is
I'll.
Put
that
in
the
slack
and
it's
just
like
a
lot
of
microscopy
images
from
different
sources.
A
You
know,
and-
and
I
know
from
years
past
that
you
know
you
have
to
try-
maybe
a
couple
different
data
sets
to
get
what
you
want.
So
some
data
sets
are
really
good
for
just
kind
of
taking
them
and
segmenting
them
with
a
really
simple
algorithm
and
then
going
from
there.
So
you
can
like
actually
one
of
the
things
you
need
to
do
to
be
able
to
segment
things
and
in
some
of
the
other
projects.
This
was
like
a
big
part
of
it,
but
I
don't
know
about
the
gnns.
A
A
If
you
use
something
like
a
fluorescent
microscopy
image
which
we
have
and
we've
used
in
the
past,
which
have
worked
typically
a
lot
better
than
some
of
the
other
types
of
imaging,
even
that
can
be
a
problem
and
you
have
to
come
up
with
ways
around
that.
So
I
mean
those
are
just
some
of
the
difficulties
of
working
with
microscopy
data,
but
I
think
it's
it's
something
that
we've
overcome
in
the
past.
We
have
techniques
for
doing
that.
A
So
that's
not
a
problem.
Really
I
mean
we
can
figure
it
out.
Really.
You
know
you
the
data.
You
want
to
just
pick
something
that
you
know
you
can
do
a
proof
of
concept
on
even
for
the
project
really,
because
you
know
you
could
throw
a
lot
of
data
at
it,
but
you
just
want
to
show
how
it
works.
Like
you
know,
I
want
to
be
able
to
run
the
software.
I
want
to
be
able
to
take
some
data,
put
it
in
and
get
something
out.
A
So
that's
that's
what
you
want
to
do
and
we
have
like.
I
said
we.
We
have
a
lot
of
tricks
and
tips
for
people
if
they're
stuck
on
on
segmentation
steps,
because
that
can
be
something
that
can
hold
you
back
but
like
when
you
do
the
schedule
for
your
project.
You
know
you'll
want
to
start
with.
You
know.
Ideally,
you'll
want
to
have
worked
with
the
data.
A
A
That's
basically
the
goal
here
you
want
to
have
a
complete
software
package
that
you
know
you
can
host
it
on
like
a
gist
or
you
can
have
it
as
something
on
your
github,
but
they
have
to
be
able
to
download
the
software
and
run
it
successfully
in
order
for
you
to
pass
so
you
know
you
can't
just
say
this
is
what
I'm
gonna
do
in
the
future
and
I'm
not
done
yet.
You
really
have
to
get
it
done
in
that
amount
of
time.
So.
A
Have
to
be
you
can't
like
try
to
solve
the
world's
problems
in
this
project.
You're
just
going
to
have
to
come
up
with.
You
know
the
shortest
route
to
getting
to
a
piece
of
software
and
then
releasing
it.
And
so
that's
that's
the
challenge,
because
you
know-
and
I
don't
know
how
I
can't
remember
how
many
weeks
you
have
total,
because
there's
a
community
period
in
there,
but
it's
like
13
weeks
or
something
it's
not
very.
It's
not
very
long
to
do
that.
C
C
A
A
A
Right
yeah
again,
if
you
have
questions
you
can
drop
them
to
me.
In
slack
and
like
you
know,
you
have
some
comments
in
the
chat.
Okay,
it's!
Okay!
Yeah!
If
you
have
an
audio
issue,
you
can
type
in
the
chat.
If
you
have
an
audio
issue
too,
so
feel
free
to
like
ask
questions
in
the
chat
and
then
says
feel
free
to
contact
me
over
slack
to
get
help
advice
on
proposals.
A
So
if
you
want
to
ask
him
he's
in
the
slack
as
usual
sing,
so
you
can,
you
know,
search
for
his
name
and
adam.
If
you
have
a
question
or
at
me
so
yeah
okay,
well,
if
there
are
more
questions-
and
you
can
leave
them
in
the
chat
here-
if
you
want
I'll,
come
back
to
them
in
a
bit,
why
now
we
go
on
to
some
other
things
and
so
a
couple
things
I
found
they're
interesting
this
week.
A
I
know
susan
had
mentioned
that
she
went
to
aps
and-
and
she
did
the
biophysics
a
couple
biophysics
sessions
there.
This
is
something
I
found
from
aps,
but
it
is
like
a
prize
that
they're
running,
so
they
have
this
gallery
of
soft
matter.
So
this
is
where
they
take
pictures
of
soft
matter
structures,
or
I
don't
know
exactly
what
it
is,
but
basically
there
are
different
projects
that
involve
soft
matter.
So
soft
matter
is
where
you
have.
A
You
know
something
like
tissues
or
soft
robots
that
are,
you
know,
different
materials
that
are
soft,
so
you
know
we
usually
think
of
like
mechanical
systems
as
being
hard
in
biological
systems
as
being
soft.
In
this
case,
it
could
be
a
mechanical
system,
it's
soft
or
it
could
be
a
living
system
that
or
a
mechanical
system
that
acts
like
a
living
system.
A
They're
just
you
know,
they're
different
ways
that
people
define
this,
but
this
is
a
nice
set
of
projects
that
they
have
selected
as
the
winners
for
their
their
thing
here,
their
competition.
So
this
is
the
first
one
inflatable
muscles
for
soft
robots
and
so
one
day,
while
fabricating
long
thin
rods
of
a
silicone
elastomer
graduate
student
trevor
jones
said
that
he
and
his
colleagues
at
princeton
had
a
happy
accident.
A
A
A
A
A
A
A
A
A
Okay,
I
think
that's
a
good.
I
gives
you
a
good
idea
of
what
it
is,
so
that
was
something
that
the
it
was
a
mechanical
system
that
was
made
of
a
soft
material
and
they
used
compressed
air.
To
sort
of
you
know,
manipulate
the
the
cavity
and
then
get
this
sort
of
actuation.
That
kind
of
looks
like
it's
moving
around
looks
like
some
fingers
grasping
something
or
like
a
worm,
or
something
like
that.
So
it's
it's
it's
very
interesting
what
you
can
do
with
soft
materials.
It's
not
a
biological
system.
A
This
is
a.
I
wouldn't
call
it
a
mechanical
system,
but
it's
a
synthetic
system
that
can
be
done.
You
know
you
can
do
things.
You
can
program
it
to
perform
all
these
different
movements,
so
you're
just
using
air
to
inject
it
with
different
amounts
of
air
and
at
different
pressures,
and
you
can
program
it
in
different
ways
to
do
these
types
of
things.
A
A
A
A
And
you
just
see
how
this
pattern
formation
proceeds,
so
this
is
from
a
simple
chemical
reaction
and
there
there's
a
lot
of
complexity
there
that
gets
revealed,
then
there's
ceramics,
liquid
crystals
and
bubbles,
and
then
so.
These
were
also
some
things
that
one
prizes
these
posters
showed
the
effects
of
bubbles
on
shape
of
an
elastic
ribbon.
The
release
of
material
frustration
and
a
structure
made
two
types
of
clay
that
shrink
by
different
amounts
when
fired
and
the
structural
fly
there.
I've.
B
D
A
A
B
A
B
A
A
This
is
the
animal
trichoplax
adherens
and
it
moves
in
response
to
its
environment
with
agility
and
seeming
purpose.
It
has
no
neurons
or
muscles
to
coordinate
its
movements.
Newark
shows
that
biomechanical
interactions
among
the
animal
cilia
are
sufficient
to
explain
how
it
moves,
and
so
this
is
a
nice.
You
know
it's
collective
behavior
in
this
organism.
A
It's
basically
these
biomechanical
interactions
amongst
the
cilia
and
it's
moving
the
moving
the
organism
and
it
doesn't
necessarily
have
a
brain.
It's
just
moving
like
this,
and
so
the
biophysicist
manu
prakash
vividly
remembers
the
moment
late
one
night
in
a
colleague's
laboratory
a
dozen
years
ago,
when
he
peered
into
a
microscope
and
met
his
new
obsession.
A
But
what
intrigued
prakash
most
was
the
well
orchestrated
grace,
agility
and
efficiency
with
which
thousands
to
millions
of
cells
and
trichoplax
moved,
and
so
this
is
an
example
of
like
something
that
you
would
have
like
a
microscopy
image
that
people
take.
I
mean
you
know
people
take
these
things
in
time
series,
so
you
can
get
a
sense
of
like
you
know,
movement
of
of
the
different
cells
and
cilia
and
other
types
of
structures
in
the
organism.
So
you
can
see
some
of
the
challenges
here,
maybe
of
segmenting
something
like
this.
A
B
H
A
So
he
put
out
a
trio
of
pre-prints
over
a
hundred.
You
know
over
100
pages
of
work,
and
this
is
on
the
archive
and
he
and
matthew
stormball
who's.
His
collaborator
showed
that
the
behavior
of
trichoplax
could
be
described
entirely
in
the
language
of
physics
and
dynamical
systems.
So
this
is
a
type
of.
E
A
That
we
would
use,
if
you
you
know,
take
the
data
from
this
this
organism
and
you
break
it
down
into
you,
know
cilia
or
cells
or
movements.
You
can
then
use
a
model
to
analyze
the
data.
So
you
know
if
you
use,
if
you
know
in
one
of
these
projects,
you're
creating
the
software
to
like
break.
You
know,
take
these
images
and
decompose
them
into
numbers.
A
Basically,
and
then
we
can
use
those
numbers
to
plug
them
into
other
types
of
models
like
dynamical
systems
models
or
you
know
fit
other
physics
models
and
we
can
anal.
We
can
analyze
the
movement,
we
can,
you
know,
simulate
the
movement
and
all
these
other
great
things.
So
you
know,
when
you
do
this
kind
of
a
project,
it
can
lead
to
other
things
down
the
road
and
so
mechanical
interactions.
A
That
begin
at
the
level
of
a
single
psyllium
and
then
multiplied
over
millions
of
cells
and
extended
to
higher
levels
of
structure,
fully
explain
the
coordinate
locomotion
of
the
entire
animal,
the
organisms.
The
organism
doesn't
choose
what
to
do.
Instead,
the
horde
of
individual
cilia
simply
move
and
the
animal
as
a
whole
performs,
as
though
it's
being
directed
by
a
nervous
system.
So
this
is
an
example.
Here
of
this
is.
A
So
that's
I
don't
want
to
go
through
that
too
much,
but
that's
the
idea
it
kind
of
goes
through.
Why
they're
doing
this
there's?
No,
this
doesn't
have
a
nervous
system,
so
they
want
to
see
how
this
organism
can
generate
these
complex
behaviors
without
a
nervous
system,
and
so
here's
a
here's,
a
quote
brains
are
overrated.
A
In
fact,
single
cells
alone
are
capable
of
remarkable
behaviors
and
they
can
self-assemble
into
collective
systems
such
as
slime
olds
or
xenobots.
Xenobots.
Are
these
interesting
kind
of
organic
robots
that
people
have
made
slime
molds,
of
course,
are
these
collective
flexion
of
cells
that
ooze
around
in
different
wet
environments
that
can
achieve
even
more
all
without
the
help
of
neurons
or
muscle.
A
A
So
this
is
a
picture
of
manu
prakash,
giving
he's
a
biophysicist
at
stanford
and
he's
showing
the
fold
scope,
which
is
a
nice
one
dollar
microscope
that
he's
created-
and
you
know
he's
kind
of
talking
about
this,
this
organism.
So
here's
an
a
side
view
of
trichoplax,
where
it's
crawling
along
a
surface
with
its
cilia
touching
this
surface
and
the
cells
up
here
taking
a
ride.
So
it's
walking,
it
looks
like
it's
walking,
but
it's
doing
it
without
a
brain.
A
It's
basically
coordinating
all
these
collective
movements
in
in
the
way
in
a
way
that
allows
it
to
walk
almost
like
something
with
a
brain
might
walk,
but
it
doesn't
have
a
brain,
and
so
that's
the
idea
here
in
this
paper.
So
we
usually
think
when
we
have
something
going
on
like
that
like
when
we
have
an
internal
clock-like
signal.
It's
saying:
okay,
go
now!
Stop
that
that's
controlled
by
a
brain.
That's
not
what's
happening
here,
so
we
aren't
getting
paced.
There's,
not
some
central
thing.
That's
saying!
Go,
go!
A
Go
it's
the
collective
mechanical
interactions
that
are
setting
up
something
that
goes
goes
goes.
So
we
have
we're
working
on
a
paper,
dick
gordon
and
I
and
jesse
parent
who's.
Also
someone
who
works
in
the
group
and
we've
done
a
thing
on
diatoms,
where
we've
kind
of
proposed
some.
I
guess
similar
ideas,
it's
a
little
bit
different,
but
I
think
next
week
I
might
show
people
this
paper,
so
you
know
we're
kind
of
finishing
it
up
now.
A
A
A
So
this
is
our
group
meetings
repository
on
github,
here's
our
diva
worm
group.
If
you
want
to
follow
or
dvoram
group
on
github
that
you
know
you
can
find
out
more
about
some
of
the
things
we
do,
but
our
group
meetings
repository
actually
has
a
lot
of
the
stuff.
It
has
a
lot
of
issues
on
our
issue
board
that
we've
talked
about
in
the
past.
A
A
A
A
In
reference
to
susan's
microscope
on
says,
this
claim
in
the
paper
largely
depends
on
how
behavior
is
defined.
Now
it
seems
like
the
trichoplax
is
interacting
with
its
environment.
Much
as
a
plant,
a
multicellular
organism
interacts
with
the
world.
We
classify
the
plant's
interactions
with
the
world
as
behavior.
I'm
not
sure
so
I
was
on
was
that
the
question
you
were
gonna
ask.
A
Okay,
yeah,
so
yeah,
that's
a
that's
a
good
question,
so
it
I
guess
behavior
is
an
interesting
thing.
I
guess
if
it's
maybe,
if
it's
moving
people
call
it
behavior,
sometimes
it
depends
on
what
it
looks
like.
So
if
something
looks
like
it's
like
it's
moving
or
it's
like
animated
in
some
way,
people
will
claim
that's
behavior
in
plants.
A
I
do
know
they're
people
who
study
plant
behavior,
it's
not
a
very
common
field,
but
people
do,
and
you
know
the
the
definition
I
guess
of
behavior
is
if
it's
moving,
if
it's
doing
interacting
with
other
things,
and
so
you
know
it's
a
very
clear
thing:
when
we
have
an
organism
of
the
brain,
we
know
that
like
if
the
brain's
generating
it,
maybe
it's
behavior
or
something
like
that.
But
if
it
doesn't
have
a
brain
or
if
it's
a
plant,
then
it's
you
know
the
the
actually.
We
know
if
it's
a.
A
A
And
I
guess
it's
behavior,
I
I
yeah,
I
don't
know
so
a
lot
of
the
stuff
that
people
do.
Is
they
actually
look
at
things
and
they
say:
does
it
look
like
something
I'm
familiar
with
so
if
it
could
be
behavior?
If
it's
doing
nothing,
you
know
if
there's
a
lot
of
a
lot
of
biochemical
interactions
or
signaling
interactions,
for
example,
but
we
don't
generally
classify
that
as
behavior
so
yeah.
I
think
that's.
That's
a
great
question.
Thank
you
for
asking.
A
I
know
it
wasn't
a
very
clear
answer,
but
I
don't
yeah.
I
don't.
I
don't
think
there's
a
good
good
answer
for
that
and
it's
not
because
it's
not
a
good
question.
It's
yeah
so
usually
says
adding
to
on
how
would
how
how
this
mechanical
behavior
is
any
different
from
the
distributed
consciousness
shown
in
bees?
A
I
mean
there's
a
huge
literature
on
on
collective
behavior
and
then
swarm
intelligence
and
things
like
that,
and
so
the
mechanical
behavior
part.
Though
people
have
tried.
You
know
people
have
looked
at
swarms
for
centuries
and
said
well
that
looks
intelligent.
That's
interesting,
but
they've
never
really
been
able
to
characterize
the
interactions,
and
so
a
lot
of
these
physical
studies
are
ways
to
sort
of
characterize.
What's
going
on
like
say
that
there
are
rules
to
this
or
that
there's
certain
physical
conditions
that
result
from
this.
A
A
A
So
this
is
an
this
is
a
non-newtonian
effect.
The
propulsion.
This
propulsion
mechanism
is
demonstrated
using
a
robotic
swimmer,
so
they
are
able
to
build
a
robotic
swimmer,
comprised
of
a
head
sphere
and
a
tail
sphere
where
the
swimming
speed
is
showing
a
reasonable
agreement
with
the
with
some
theory
and
some
simulations,
and
so
then
they
also
have
this
image.
They
do
some
imaging.
A
They
show
the
propulsion
of
the
swimmers
driven
by
a
viscoelastic
jet
at
the
tail,
which
is
the
tail
end
of
the
animal
and
there
this
develops
because
of
some
of
the
asymmetries
in
the
body
of
the
swimmer
and
so
they're
able
to
look
at
the
geometry
of
the
organism
and
they're
able
to
look
at
how
it's
moving
in
the
water
and
show
that
that
organism
is
actually
generating
the
conditions
for
its
further
propulsion.
So
that's
kind
of
really
interesting
kind
of
interactions
between
the
physics
and
the
organism.
A
This
next
paper
then
talks
about
excitable
mechanics
embodied
in
a
walking
psyllium.
So
this
is
where
they
look
at
well.
The
abstract
reads:
rapid
transduction
of
sensory
stimulation
to
action,
which
is
what
we
see
in
the
nervous
system.
It's
taking
things
from
the
environment,
stimuli
and
converting
it
into
something
in
the
nervous
system
that
then
converts
it
back
to
some
sort
of
movement,
some
sort
of
action.
So
it's
what
the
nervous
system
does
it
takes
in
sensory
input.
A
To
this
end,
most
animals
use
the
sub-second,
excitable
and
multi-stable
dynamics
of
a
neuromuscular
system,
so
the
neuromuscular
system
like
ours,
where
we
have
inputs
and
and
outputs
in
terms
of
movement
here
studying
an
animal
without
neurons
and
muscles.
We
report
analogous
excitable
and
multi-stable
dynamics
embodying
the
physics
of
a
walking
psilium,
so
they
define
a
walking
psyllium
as
a
phenomenon
where
the
locomotive
force
is
generated
through
contact
with
the
substrate,
which
is
periodically
reset
by
steps
and
the
direction
of
motion.
A
A
So
this
can
you
know
that
they
show
evidence
of
a
localized
multi-stability
of
of
the
different
cilia,
so
there's
this
they
can
exist
in
different
states
and
there's
local
synchronization,
and
so
there's
this
out
of
equilibrium,
mechanics
and
this
directly
controls
the
locomotive
forcing
of
walking
cilia.
So
this
is
where
you
get
these.
A
We
can
show
minimal
mechanism
what
they
call
trigger
waves
by
which
these
walking
cells
may
work
together
to
achieve
collaboration
such
as
coordination
of
hunting
strikes
across
10
to
the
fifth
cells,
which
is,
is
it
10,
000
or
so,
without
central
control?
So
this
is
really
a
nice
paper.
It
shows
like
these.
Actually,
it
shows
an
example
of
the
fitsu
nagumo
oscillator,
which
is
an
oscillating
system.
A
So
then,
there's
also
this
paper.
Mobile
deficits
born
from
an
energy
cascade,
shape
the
locomotive
behavior
of
a
headless
animal.
So
again,
there's
this
headless
aspect
where
it
doesn't
have
a
brain,
but
it
does
have
this
sort
of
behavior
that
looks
like
it
is
generated
by
a
brain,
and
so
again
this
paper
talks
about
some
of
the
physics
of
it.
A
I
don't
think
there's
anything
special
about
this
paper,
but
it
kind
of
talks
about
some
of
the
modeling
that
they
do
these
this
geometric
model,
and
then
this
one
is
similar.
Ciliary
flocking
and
emergent
instabilities
enable
collective
agility.
So
this
is
again
where
they
don't
have
muscles.
They
don't
have
neurons,
they
don't
have
brains,
but
they
have
this
sort
of
coordinated
behavior.
This
is
what
they
call
ciliary
flocking,
so
this
is
where
they
have
these
collective
collective
ciliary
behaviors
that
can
move
the
organism
in
different
directions.
A
We
say
you
know:
behavior
is
generated
by
our
brain,
but
you
know,
maybe
bacteria
have
behavior
and
it
doesn't
have
a
brain
or
plants
could
have
behaviors,
they
move,
they
move
all
the
time,
but
they
don't
have
brains,
and
so
actually
it's
the
physics
of
these
systems.
That
can
explain
a
lot
of
this
and
in
our
paper
on
on
diatoms,
we
talk
about
maybe
some
models
from
neuroscience
that
might
explain
this,
but
models
from
neuroscience
that
don't
really
have
any
neuronal
content.
A
A
So
I
might
do
one
more
paper
before
we
end
and
if
you
have
to
go
now
is
the
top
of
the
hour.
We
usually
go
for
like
an
hour
and
then
maybe
we
have
something
right
after
the
hour.
So
we
don't
have
any
more
questions.
I'll
continue
with
one
more
paper
and
then
maybe
if
you
have
any
questions
to
end
the
meeting,
maybe
you
know
something
about
gsoc
or
something
else.
Then
I'll
be
happy
to
answer.
A
I'll
talk
about
this
one
we've
had
this
one
sitting
around
for
a
while
and
we
haven't
talked
about
it.
This
is
something
called,
and
this
is
something
that
we've
been
interested
in
in
the
group
for
a
while,
but
it
hasn't.
We
haven't,
really
found
the
right
way
to
approach
this
problem
or
to
write
it
up.
A
Those
things
can
be
expressed
together
and
then
you
know
they.
They
tend
not
to
be
moved
around
during
recombination
or
anything
like
that.
So
this
order,
this
gene
order
can
be
quite
important,
sometimes
for
maintaining,
like
developmental
programs,
where
you
know,
tissues
form
in
a
certain
order
and
genes
are
expressed
in
a
certain
order.
So
this
is
can
be
quite
important.
A
We
talked
about
hox
gene
clusters
before
hox.
Gene
clusters
are
similar
to
this,
where
they
have
an
order
of
different
hops
genes,
and
that
order
is
very
important
for
maintaining,
like
you
know,
segmentation
in
an
organism,
so
that's
good,
but
sometimes
that
can
be
ripped
apart,
and
so
there
is
of
course
recombination
where
different
parts
of
the
genome
flip
they
flip
their
position.
A
No,
it's
I
don't.
I
don't
know
why,
like
you
get
the
sort
of
synteny
translocation,
sometimes
it's
just
that,
like
things
recombine
randomly
in
the
genome
and
they
get
flipped
a
lot
of
times,
the
things
are
conserved
if
they're
close
to
one
another.
So
if
you
have
two
genes
that
are
next
to
one
another,
the
probability
of
them
getting
recombined
is
low,
there's
no
real
causal
mechanism
other
than
like
random
recombination.
A
A
Anyways
the
so
this
changes
the
order,
and
so
now
this
has
consequences
for
how
the
phenotype
is
expressed,
because
maybe
now
you're
say
these
are
hox
genes.
Your
hox
genes
are
in
different
positions
and
your
segmentation
can
be
mucked
with
so
you
know
there
are
different
mutants
of
drosophila,
where
you
have
different
sort
of
pox,
gene
mutations
or
hox
gene
rearrangements
and
those
are
not.
You
know,
those
are
sometimes
they're,
not
functional
mutants,
sometimes
they're,
very
special
mutants
special
phenotypes.
A
A
So
the
idea,
though,
is
it's
very
important
for
development,
and
I
just
wanted
to
go
over
that
concept
to
go
over
some
of
these
papers,
so
this
is
what
they
call
chromosomal
chaos,
and
if
I
can
find
this
okay
here
it
is
so
this
is
something
they
call
chromosomal
tectonics,
and
so
this
is
early
animal
evolution.
This
works.
A
A
Let's
try
it
again
all
right:
there
we
go
so
this
is
from
quantum
magazine.
This
is
secrets
of
early
animal
evolution
revealed
by
chromosome
tectonics,
so
large
blocks
of
genes
can
serve
through
hundreds
of
millions
of
years
of
evolution
into
how
the
first
animal
chromosomes
came
to
be
so
blocks
of
linked
genes
can
maintain
their
integrity
and
be
tracked
revolution,
meaning
that
you
can
see
these
genes
in
the
same
order
in
a
lot
of
different
organisms
that
have
a
common
ancestor,
then
discovery
of
its
foundation
is
when
being
what
is
being
called
genome
tectonics.
A
So
this
is
an
idea
that,
like
you
know
it's
kind
of
like
plate,
tectonics,
where
you
have
these
continental
plates
that
are
drifting
along
the
surface
of
the
earth
and
that
they,
you
know
they
don't
really
they're,
always
there
they're
kind
of
there
over
geologic
time.
You
know
they
build
up
from
like
creighton's,
but
you
know
they're
they're
there
for
longer
periods
of
time.
So
they're
you
know,
continents
just
don't
break
up
at
random.
They're
they're,
really
you
know
kind
of
conserved,
and
so
this
is
the
idea
they're
talking
about
here.
A
But
the
thing
is:
is
that
these?
I
guess,
if
you
want
to
call
different
gene
orders
tectonic
plates,
sometimes
they
can
break
apart
and
that's
why
they
call
this
genome
tectonics,
so
chromosomes,
the
bundles
of
dna
that
star
in
the
mitotic
ballet
of
cell
division.
That's
a
little
poetic
play,
a
reading
leading
role
in
complex
life,
but
the
question
of
how
chromosomes
came
to
exist
and
evolve
has
long
been
discouragingly
hard
to
answer.
A
This
is
due
partly
to
the
lack
of
chromosome
level,
genomic
information
and
partially
to
the
suspicion
that
long
periods
of
evolutionary
change
have
washed
away
clues
about
than
ancient
history.
And
then,
in
this
paper,
in
scientific
advances,
this
team
they've
been
able
to
track
changes
in
chromosomes
that
occur
as
much
as
800
million
years
ago.
A
So
this
is,
you
know
your
different
parts
of
the
tree.
Like
you
know,
you
have
plants
and
animals
for
multicellular
organisms
as
well
as
your
yeah,
so
you
have
basically
plants
and
animals
using
these
mark
blots
as
markers
the
scientists
deduced
how
the
chromosomes,
fused
and
recombined
as
those
early
groups
of
animals
became
distinct.
A
The
researchers
call
this
approach
genome
tectonics.
In
the
same
way,
the
geologists
use
their
understanding
of
plate
tectonics
to
make
sense
of
the
movement
of
continents
there.
These
biologists
are
reconstructing
how
various
genome
duplications,
fusions
and
translocations
create
the
chromosomes
we
see
today.
A
So
we
can
use
that
information
to
make
statistical
predictions
and
rigorously
test
hypotheses
about
groups
of
organisms
are
related.
So
this
is
a
tool
to
understand
evolution
a
bit
better,
but
also
development,
because
these
blocks
of
genes
that
we
have
here
contribute
to
developmental
or
you
know
order.
So
you
know
the
different
segments
of
of
the
organism
but
also
kind
of
you
know.
A
These
processes
are
governed
by
genes
that
are
linked
together.
So
a
and
b
may
be
linked
functionally
they
might
you
know
a
b
might
be
dependent
on
a
for
something
to
produce
a
like
an
enzyme
or
some
sort
of
product
in
the
cell.
If
b
and
a
are
broken
apart,
then
that
can
no
longer
happen
so
that
function
is
is
gone
and
that
becomes
something
that
can
be
deleterious
of
the
organism.
It
can
kill
the
organism
in
development.
A
So
this
is
an
important
thing.
This
physical
linkage,
but
physical
linkage
over
a
little
bit
longer
scales.
Usually,
if
two
genes
are
next
to
one
another
they're
linked
in
the
sense
that
they
don't
get
pulled
apart,
often
because
recombination
is
something
that
happens
probabilistically
but
also
like,
as
you
get
away
from
like
like,
if
you
get
away
from
a
d,
is
more
likely
to
be
recombined
away
from
a
than
b,
so
those
blocks
are
are
somewhat
stable
and
over
different
distances.
A
We
don't
really
understand
the
the
you
know
if
whole
big
blocks
can
be
conserved
or
kept
together
by
any
mechanism,
but
we
know
that,
like
recombination
is
something
that
happens
a
lot
in
genomes,
so
that
that's
a
that's
a
thing
that
can
happen
so
they're
able
to
you
know
this
is
an
important
part
of
like
genomes
and
of
evolution
and
of
development,
so
so
using
similar
innovative
methods.
This
group
resolved
a
long-standing
mystery
about
the
timing
of
genome
duplications
that
accompanied
the
emergence
of
jawed
vertebrates.
So
these
are
verti.
A
We
have
jaws
and
there's
a
dephase
stones
is
the
group
of
organisms
that
have
jaws.
So
this
includes
you
know
your
your
your
mammals,
some
you
know
some
well
birds,
and
you
know
I
don't.
I
think
it
goes
into
fishes
a
little
bit,
but
that's
but
anyways
there's
this
group
of
organisms
called
naphtha
stems,
and
these
are
the
jawed
vertebrates,
but
the
importance
of
the
approach
isn't
purely
retrospective
in
the
process
of
making
these
discoveries.
A
That
information
can
guide
future
genomic
studies
and
help
biologists
predict
when
they'll
find
in
the
genomes
of
the
species
not
yet
sequenced,
so
they're
actually
looking
for
rules
in
this
data.
So
again
you
know
we
don't
know
the
rules
that
govern
like
syntony.
We
don't
know
the
rules
that
govern
some
of
the.
You
know
how
these
things
are
kept
together
or
broken
apart.
A
We
only
know
that
they're
generally
like
probabilistic
things
that
it
happened,
but
we
don't
really
know
much
more
about
it,
we're
starting
to
get
a
broader
picture
of
chromosome
evolution
across
the
tree
of
life,
and
now
we
can
actually
understand
this
a
little
bit
better,
because
we
understand
these
kind
of
processes
and
then
we
can
attach
rules
to
them.
Perhaps
if
we
have
the
data,
if
we
can
build
computational
models
of
them,
so
what
do
ancient
genomes
share?
A
They
have
actually
looked
at
the
genome
of
the
hydra,
which
they
described
as
a
model
of
a
veritable
cnidarian
venerable
cnidarian.
By
comparing
it
to
the
available
animal
genomes,
they
discovered
highly
conserved
groups
of
linked
genes,
so
hydra
is
an
marine
invertebrate.
That's
they're
using
is
sort
of
like
the
the
baseline
for
this
or
the
common
ancestor
and
they're.
A
A
You
know
you
can
see
that
that's
a
source
of
diversity,
the
blocks
themselves
are
stable
over
long
stretches
of
time,
and
so
this
is
something
that
you
know.
We
think
talk
about
like
mutations
in
genes.
We
talk
about
proteins.
We
talk
about
that.
We
never
really
talk
too
much
about
the
larger
scale,
things
in
the
genome,
like
these
synteny
blocks
or
chromosomes
themselves,
but
there's
a
lot
to
understand
about
that
and
that's
a
lot
of
the
diversity
between
species
as
well.
A
A
So
this
is
where
you
have
this
sequence:
divergence
and
they're
using
syntony
based
analysis
to
look
at
it
so
they're,
looking
at
orphan
genes,
which
are
species-specific
sequences
that
lack
detectable
relations
in
other
species
and
then
they're
saying
that
they
can
use
a
sentiment-based
analysis
to
show
that
that
that
sequence,
divergence
isn't
the
source
of
orphan
genes
or
that
they
didn't
evolve
out
of
like
multiple
mutations
they
evolve.
That
is
something
else,
and
so
this
is
an
example
of
how
they
use
syntony.
A
A
So
we'll
have
a
period
of
time
at
the
beginning,
where
you
can
show
your
project
and
you
can
show
your
progress
and
then
we'll
have
questions
about
that
as
well,
and
then
you
know
you'll
be
able
to
contribute
in
other
ways
as
well.
So
if
you're
working
on
the
project,
I
would
recommend
that
that
be
your
first
priority,
but
anyways
just
wanted
to
wish
everyone
a
good
week.
If
you
don't
have
any
other
questions.
A
A
I
hope
that
we
get
one,
you
know
we
we
applied
as
an
organization
and
we
didn't
get
in,
but
that's
that
was
just
to
maybe
facilitate
more
positions
but
anyways.
It's
it's.
It
usually
is
somewhat
competitive,
so
you
know
but,
but
I
think
the
best
strategy
is
just
to
like
you
know,
you
know,
have
have
me,
review
your
proposal
or
have
visual
review
it
and
that'll
that'll
help.