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directly. The diluted filtrate could be augmented
with TPGS-750-M to the original level (2 wt %) and
reused, thereby creating little to no wastewater
stream. The environmental factor (E factor) (21),
ametricof“greenness”that has previously been
applied to micellar catalysis (22), is very low (E
factor = 3).
We used ICP to analyze the palladium content
(<10 ppm) of a product formed via the technology
presented here, and we compared the result with
that quantified following atraditionalSuzuki-
Miyaura coupling in organic solvent (fig. S4). Re-
sidual palladium in the product derived from a
standard coupling in dioxane was far higher than
that observed using our nanoparticle approach.
Prospects for incorporating this water-based
nanomicelle-nanometal technology into a one-
pot sequence of reactions are shown in Fig. 5A.
Heteroaryl iodide 4, containing carbamate and
trimethylsilyl (TMS) protecting groups, was gen-
erated in situ and then subjected to cross-coupling
with alkenyl tetrafluoroborate salt 5,usingthe
Fe–ppm Pd nanoparticle protocol. The coupling
product 6was then exposed to aqueous base to
remove the TMS groups and effect elimination to
7, followed by butoxycarbonyl (Boc) deprotection
to 8. Final aryl amination with bromobenzene to
9provided entry to the bioactive class of 2,4,5-
substituted pyrazol-3-one compounds in a one-
pot sequence with an overall isolated yield of
68% (23).
In addition, testing the potential for this mixed-
metal catalyst system to effect other important
Pd-catalyzed reactions, such as Sonogashira cou-
plings, was carried out (in the absence of added
copper), following the example illustrated in
Fig. 5B. The prognosis for a similar outcome is
good.
REFERENCES AND NOTES
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V. Snieckus, Angew. Chem. Int. Ed. 51, 5062–5085 (2012).
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1147–1164 (2012).
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T. Sweijs, A. Diederen, M. Beerthuizen, S. de Goede, Scarcity
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12. N. A. Isley, F. Gallou, B. H. Lipshutz, J. Am. Chem. Soc. 135,
17707–17710 (2013).
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49, 8860–8863 (2010).
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(2006).
15. S. Darses, J.-P. Genet, Chem. Rev. 108, 288–325 (2008).
16. T. H. Bointon et al., Nano Lett. 14, 1751–1755 (2014).
17. S. L. Buchwald, C. Bolm, Angew. Chem. Int. Ed. 48, 5586–5587
(2009).
18.C.L.Chun,D.R.Baer,D.W.Matson,J.E.Amonette,R.L.Penn,
Environ. Sci. Technol. 44,5079–5085 (2010).
19. Y.-P. Sun, X. Q. Li, J. Cao, W.-X. Zhang, H. P. Wang, Adv. Colloid
Interface Sci. 120,47–56 (2006).
20. I. Thomé, A. Nijs, C. Bolm, Chem. Soc. Rev. 41, 979–987
(2012).
21. R. A. Sheldon, Green Chem. 9, 1273 (2007).
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Chem. Int. Ed. 52, 10952–10958 (2013).
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ACKNOW LEDGM ENTS
We thank Novartis for financial support; J. Feng for technical
assistance; M. Cornish for acquisition of the AFM images;
S. Kraemer for obtaining the cryo-TEM, SEM, and EDX data; and
J. Matthey for providing Pd salts. Parts of this work were carried
out in the Characterization Facility, University of Minnesota, which
receives partial support from NSF through the Materials Research
Science and Engineering Center (MRSEC) program. This work also
made use of the University of California–Santa Barbara (UCSB)
Materials Research Laboratory Central Facilities, supported by
NSF’s MRSEC program under award no. DMR-1121053. ICP-MS
analyses were provided by J. Reilly (Novartis, Cambridge, MA). We
also acknowledge support from NIH in the form of a Shared
Instrument Grant to UCSB(1S10OD012077-01A1). A preliminary
patent covering this chemistry has been filed by the University of
California–Santa Barbara. The exp erimental data r eported in this
paper are availab le in the supplemen tary materials.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/349/6252/1087/suppl/DC1
Materials and Methods
Figs. S1 to S18
Tables S1 to S15
References (24–34)
13 June 2015; accepted 30 July 2015
10.1126/science.aac6936
NATURAL HAZARDS
Slip pulse and resonance of the
Kathmandu basin during the 2015
Gorkha earthquake, Nepal
J. Galetzka,
1
*D. Melgar,
2
J. F. Genrich,
1
J. Geng,
3
S. Owen,
4
E. O. Lindsey,
3
X. Xu,
3
Y. Bock,
3
J.-P. Avouac,
5,1
†L. B. Adhikari,
6
B. N. Upreti,
7
B. Pratt-Sitaula,
8
T. N. Bhattarai,
9
B. P. Sitaula,
9
A. Moore,
4
K. W. Hudnut,
10
W. Szeliga,
11
J. Normandeau,
12
M. Fend,
12
M. Flouzat,
13
L. Bollinger,
13
P. Shrestha,
6
B. Koirala,
6
U. Gautam,
6
M. Bhatterai,
6
R. Gupta,
6
T. Kandel,
6
C. Timsina,
6
S. N. Sapkota,
6
S. Rajaure,
6
N. Maharjan
6
Detailed geodetic imaging of earthquake ruptures enhances our understanding of earthquake
physics and associated ground shaking.The 25 April 2015 moment magnitude 7.8 earthquake in
Gorkha, Nepal was the first large continental megathrust rupture to have occurred beneath a
high-rate (5-hertz) Global Positioning System (GPS) network. We used GPS and interferometric
synthetic aperture radar data to model the earthquake rupture as a slip pulse ~20 kilometers in
width, ~6 seconds in duration, and with a peak sliding velocity of 1.1 meters per second, which
propagated toward the Kathmandu basin at ~3.3 kilometers per second over ~140 kilometers.
The smooth slip onset, indicating a large (~5-meter) slip-weakening distance, caused moderate
ground shaking at high frequencies (>1 hertz; peak ground acceleration, ~16% of Earth’s
gravity) and minimized damage to vernacular dwellings. Whole-basin resonance at a period of
4 to 5 seconds caused the collapse of tall structures, including cultural artifacts.
The shape of the slip-rate time function
(STF) during a seismic rupture provides
critical insight into the constitutive fault
properties. The abruptness of the slip on-
set determines the high-frequency con-
tent of the STF, and hence the intensity of the
near-field ground motion (1), whereas the tail,
which discriminates pulse-like and crack-like rup-
tures (2), has a low-frequency signature. Therefore,
resolving the STF with band-limited strong-motion
recordsisdifficult.Combininghigh-rateGlobal
Positioning System (GPS) waveforms (3,4), which
capture both dynamic and permanent deforma-
tion,overcomesthislimitation.
The 25 April 2015 moment magnitude (M
w
)
7.8 earthquake in Gorkha, Nepal resulted from
the unzipping of the lower edge of the locked
portion of the Main Himalayan Thrust (MHT)
fault, along which the Himalayan wedge is thrust
over India (5). The earthquake nucleated ~80 km
northwest of Kathmandu and ruptured a 140-km-
longsegmentofthefault(Fig.1A),withahypo-
central dept h of ~15 km and a dip angle of 7°
to 12° (5,6). The MHT accommodates most of
the convergence between India and southern
Tibet, with a convergence rate between 17 and
21 mm/year (7). For the 2015 event, which re-
sulted in over 8000 deaths (mostly in Kathmandu
and adjacent districts), modified Mercalli inten-
sities (MMIs) reported by the National Society
for Earthquake Technology–Nepal (NSET) (8)
reached up to IX (violent shaking) and exceeded
VI (strong shaking) over an area 170 km by 40 km.
Kathmandu has been struck by repeated earth-
quakes in the past, with major destruction [MMI >
X (extreme shaking)] in the years 1255, 1344, 1408,
1681, 1833, and 1934 (9–11). These earthquakes
all occurred close to Kathmandu and have been
SCIENCE sciencemag.org 4SEPTEMBER2015•VOL 349 ISSUE 6252 1091
RESEARCH |REPORTS
on September 20, 2015www.sciencemag.orgDownloaded from on September 20, 2015www.sciencemag.orgDownloaded from on September 20, 2015www.sciencemag.orgDownloaded from on September 20, 2015www.sciencemag.orgDownloaded from on September 20, 2015www.sciencemag.orgDownloaded from
assigned magnitudes between M
w
7.5 and 8.4.
During the Gorkha earthquake, damages in the
Kathmandu basin were probably amplified by site
effects, as has happened in past events (12,13).
The basin is filled with 500 to 600 m of fluvio-
lacustrine sediments resting on a metamorphic
basement (14).
The damage to the most vulnerable vernac-
ular dwellings in Kathmandu, which rarely ex-
ceed four stories, was much less than expected
in view of the 2015 earthquake’s magnitude
and its proximity to Kathmandu. In contrast,
some taller structures were more severely af-
fected, such as the 60-m-tall Dharahara tower,
which collapsed even though it had partially sur-
vived an M
w
8.1 to 8.4 earthquake in 1934. The
1934 event caused much more extensive de-
struction to vernacular dwellings in Kathmandu
than the 2015 event did: 20% of the buildings in
Kathmandu were destroyed in 1934 versus less
than 1% in 2015 (15).Theseobservationsreflect
the combined effects of the earthquake source
characteristics and local geological conditions, in
addition to the evolution of building practices.
The 2015 Gorkha earthquake ruptured a sub-
horizontal portion of the MHT that lies directly
beneath a network (16) of continuous GPS (cGPS)
stations, which record data at a high rate of
five samples per second, and one accelerometer
station (17) (Fig. 1A). In addition, surface displace-
ments were measured with interferometric syn-
thetic aperture radar [InSAR (18,19)] (fig. S1).
Although a number of recent earthquakes have
been documented with similar techniques (20,21),
the Gorkha event is the first occurrence of a large
continental thrust earthquake to be recorded by
high-rate cGPS stations very close to and com-
pletely encompassing the rupture area. The
combination of these measurements provides
the opportunity to image the kinematics of the
source process and the strong ground motion
that led to the particular pattern of structural
damage observed during this earthquake.
The records of seismic displacements and ac-
celerations (Fig. 2 and fig. S2) show southward
motion of up to 2 m, with a rise time on the
order of 6 s. The pulse is particularly clear at
cGPS station KKN4, located on bedrock just
north of Kathmandu and only ~13 km above the
fault. The displacement at this station started
about 25 s after the onset of the rupture, corre-
sponding to 15 s after the P-wave arrival (Fig. 2);
it reached its final static value by about 32 s,
based on the origin time of 06:11:26.270 UTC
determined by the U.S. Geological Survey (USGS)
from the arrival of radiated direct Pwaves (6).
The records indicate a pulse-like rupture (22),
with slip on any given portion of the fault oc-
curring over a short fraction of the total ~70-s
earthquake source duration (5). Given the ~78-km
distance of KKN4 from the epicenter, the pulse
must have propagated at ~3 km/s, a value con-
sistent with waveform modeling and back pro-
jection of high-frequency seismic waves recorded
at teleseismic distances (5). Surface velocities
reached values of ~0.7 m/s. In addition to the
pulse recorded at KKN4, the cGPS station NAST
within the Kathmandu basin detected strong
oscillations of about 3- to 4-s periods lasting for
~20 s (Fig. 2 and Fig. 3A). The Gorkha earthquake
1092 4 SEPTEMBER 2015 •VOL 349 ISSUE 6252 sciencemag.org SCIENCE
1
Department of Geology and Planetary Sciences, California
Institute of Technology (Caltech), Pasadena, CA 91125, USA.
2
Berkeley Seismological Laboratory, University of California
(UC)–Berkeley, Berkeley, CA 94720, USA.
3
Cecil H. and Ida M.
Green Institute of Geophysics and Planetary Physics, Scripps
Institution of Oceanography, UC–SanDiego,LaJolla,CA92037,
USA.
4
Jet Propulsion Laboratory (JPL), Caltech, Pasadena, CA
91109, USA.
5
Department of Earth Sciences, University of
Cambridge, Cambridge CB2 3EQ, UK.
6
Department of Mines
and Geology, Lainchour, Kathmandu, Nepal.
7
Nepal Academy of
Science and Technology, Khumaltar, Lalitpur, Nepal.
8
Department of Geological Sciences, Central Washington
University (CWU), Ellensberg, WA 98926, USA.
9
Tri-Chandra
Campus, Tribhuvan University, Ghantaghar, Kathmandu, Nepal.
10
U.S. Geological Survey (USGS), Pasadena, CA 91106, USA.
11
Pacific Northwest Geodetic Array and Department of
Geol ogical Sciences, CWU, Ellensberg, WA 98926, USA.
12
UNAVCO,
Boulder, CO 80301, USA.
13
Département Analyse et Sureveillance
de l’Environnement (DASE), Commissariat à l’Energie Atomique
(CEA), 91297 Bruyères-le-Châtel, Arpajon, France.
*Present address: UNAVCO, Boulder, CO 80301, USA.
†Corresponding author. E-mail: avouac@gps.caltech.edu
84.0° 86.0°
85.0°
27.0°
28.0°
29.0°
1m
INDIA
NEPAL
CHINA
5km
15km
25km
KKN4
NAST
SNDL
CHLM
KATNP
KIRT
DAMA
SYBC
RMTE
BELT
BESI
DMAU
GHER
0
2
4
6
Slip (m)
27.0°
28.0°
29.0°
0 km 100 km
5km
15km
25km
INDIA
NEPAL
CHINA
Kathmandu
−8
−4
0
4
8
Stress drop (MPa)
12/05/15
Mw 7.3
Fig. 1. Cumulative slip distribution of and static stress drop due to the Gorkha earthquake. (A)
Slip inversion results for the M
w
7.8 Gorkha event. The red star is the hypocenter. Dashed contours are
depths to the fault. Orange diamonds are 5-HzcGPS stations, and white diamonds are low-rate (1/30-Hz)
stations. The green triangle is the strong-motion station. Kathmandu is represented by the blue square.
The black arrows indicate the coseismic offsets measured at the sites (the values and uncertainties are
given in table S1). Vectors with less than 10 cm of displacement are not shown. (B)Staticstressdrop
predicted by the model of Fig. 1A. Green circles are aftershocks with local magnitudes greater than four,
recorded and located by the Nepal National Seismic Center. Focal mechanisms (yellow and white circles)
represent the global centroid-moment tensor solutions for aftershocks with magnitudes greater than six.
RESEARCH |REPORTS
must have excited a resonance of the Kathmandu
basin as a whole. The resonance is evident in
the response spectra from these stations and in
data from the accelerometer station, KATNP
(Fig. 3, G to I).
To determine the kinematics of the seismic
rupture, we carried out a formal inversion of
time-dependent slip on the fault (23,24) and
compared the recorded waveforms with for-
ward predictions, assuming a propagating slip
pulse with varied characteristics. We assumed
a planar fault geometry with a strike of 295° and
a dip of 11°, in accordance with the teleseismic
W-phase moment tensor solution calculated by
the USGS (6). We tested shallower dips up to
7° but found that 11° provided a better fit to
the data. The fault was discretized into 10 km by
10 km subfault segments. We jointly inverted the
three-component 5-Hz GPS–derived velocity wave-
forms, the GPS static offsets, and the InSAR line
of sight (LOS) static displacements measured
between 22 February and 3 May (fig. S1). The
GPS displacement time series shows large post-
seismic motion at only one station (CHLM), with
a magnitude of less than 2 cm in both the hor-
izontal and vertical directions over the week af-
ter the earthquake. Therefore, we neglected the
contribution of postseismic deformation to the
LOS displacements. The model fits both data
sets closely (Fig. 1A), with an 86% reduction in
variance for the InSAR and GPS coseismic dis-
placements and a 74% reduction in variance
for the GPS velocity waveforms (figs. S2 and
S4). The model indicates a predominantly uni-
lateral rupture to the southeast, with a peak
slip of ~6.5 m on a large asperity to the north of
Kathmandu. The event duration was 65 s (fig.
S4), with the peak moment release at 23 s when
the slip pulse was less than 10 km north of
Kathmandu (movie S1); the peak slip rate was
1.1 m/s. Most of the slip was concentrated within
a narrow region between the 10- and 20-km fault-
depth contours. We found a large asperity with
3.0 m of slip, located east of the main asperity
and between 20 and 23 km below the surface.
The rupture velocity of the propagating slip pulse,
indicated by the onset of slip in our best-fitting
model, was ~3.2 km/s and had a maximum al-
lowed velocity of 3.3 km/s (fig. S4). This velocity
corresponds to ~95% of the shear wave speed at
the depth where the majority of the slip occurred
(15 km), according to the local velocity model
used to calculate the Green’sfunctions(tableS2),
which indicates a very fast rupture propagation.
The slip tapered at 17 to 20 km depth along the
edge of the locked zone of the MHT.
The inversion that we performed includes a
large number of parameters, which would allow
for a relatively complex rupture history. However,
the resulting model is simple, with essentially a
single propagating slip pulse. The spatiotemporal
evolution of the slip pulse matches well with the
location of the sources of high-frequency seismic
waves (0.5 to 2 Hz) derived from back projection
of the teleseismic waveforms (5)(movieS1).
We calculated the static stress change on the
fault plane due to the earthquake (Fig. 1B). This
SCIENCE sciencemag.org 4SEPTEMBER2015•VOL 349 ISSUE 6252 1093
−2
0
North
KKN4 (m)
−1
0
NAST (m)
−1
1
KATNP (m /s 2)
0.0
0.5
East
0.0
0.5
−1
1
020 40 60
0.0
1.5
Up
020 40 60
Seconds after P-wave arrival
0
1
020 40 60
−1
1
Fig. 2. Records of ground displacements and accelerations during the Gorkha earthquake.
Shown are displacement waveforms at cGPS stations KKN4 and NAST (five samples per second)
and acceleration waveforms at strong-motion station KATNP (Fig. 1).
Fig. 3. Evidence for resonance of the
Kathmandu basin. (Ato C) Three compo-
nents of ground velocity observed at two
high-rate GPS stations (KKN4 and NAST)
and one strong-motion station (KATNP) in
the Kathmandu region. KKN4 is located on
hard rock northwest of Kathmandu, whereas
the other two stations are located on soft
sediment in the basin.The GPS is differen-
tiated to velocity, and the strong-motion
data are integrated after high-pass filtering at 0.02 Hz. (Dto F) Ground-motion amplification observed at the two basin stations. Plotted is the ratio of the
amplitude spectra of the basin stations to the amplitude spectra of the reference bedrock station, KKN4. (Gto I) Five-percent damped velocity response
spectra for all three stations. (J) Close-up map showing the location of the basin and bedrock stations.
RESEARCH |REPORTS
calculation showed loading of the fault around
the main asperity where most of the aftershocks
occurred, including the M
w
7.3 aftershock of 12
May, as expected for aftershocks triggered by
coseismic stress transfer (25). The model pre-
dicted a pattern of uplift in the Kathmandu basin
and subsidence at the front of the high range (fig.
S4), approximately opposite to the pattern ob-
served in the interseismic period, as expected
from simple models of the seismic cycle on the
MHT (26,27).
The record at station KKN4 should be a close
representation of the STF, as it lies only about
13 km above the propagating slip pulse and is
not affected by the site effects observed at the
stations in the Kathmandu basin. We conducted
synthetic tests with the same Earth structure
model used in the inversion (table S1) to assess
the distortion and smoothing introduced by the
elastic half-space response (fig. S5). We found a
vertical velocity amplitude of about 70% of the
peak slip rate on the fault directly beneath the sta-
tion, along with a well-preserved temporal shape.
Furthermore, the tests demonstrated that the
smooth onset of slip is not an artifact of the trans-
fer through the elastic medium, represented by
the elastodynamic Green’sfunctions.Theshapeof
the slip pulse can also be retrieved from the GPS
records at NAST and the strong-motion vertical
records at KATNP, which are less affected by site
effects than the horizontal records (Fig. 1). All
three records indicate a pulse ~6 s in duration.
The shape of the pulse fits the regularized Yoffe
function (28), yielding a smooth rise, with an
acceleration time to the peak slip rate of t
s
=1.7s,
a rise time of t
R
= 3.3 s, and a total effective du-
ration of t
eff
= 6.7 s. The slip-rate pulse derived
from the inversion also fits well, using the same
values of t
s
and t
R
and peak slip-rate of ~0.9 m/s
(Fig. 4). We compared the recorded waveforms
with predictions from a suite of forward models
to test the robustness of our results. We used the
static slip model in these tests, deduced from the
inversion of the GPS static and InSAR measure-
ments (fig. S7). We assumed a propagating slip
pulse and a regularized Yoffe STF with varying
characteristics. We varied the rupture velocity
between 2.8 and 3.6 km/s and the rise time be-
tween 2 and 10 s (fig. S8). By inverting synthetics
calculated from forward modeling, we also tested
the resolution power of the inversion and the
limitedbiasintroducedbytheregularization
applied to the inversion (24) (figs. S10 and S11).
Together, these tests demonstrated that the du-
ration of the slip pulse was probably less than
10 s, the time to the peak slip rate could not have
been shorter than 1 s (we would otherwise have
observed a much larger amplitude at high fre-
quencies), and the average propagation rate of
the slip pulse was not less than ~3.0 km/s over
the first 30 s (until KKN4, NAST, and KATNP
recorded a pulse signal).
Tinti et al. (28) analyzed how the shape of
the STF relates to the characteristics of the
friction law that governs the dynamics of the
rupture. Based on this rationale (their equations
6 and 11), we estimated the slip-weakening dis-
tancetobe~5m(forapeakslipof6.5m).This
distance is large compared with those estimated
from kinematic and dynamic modeling of seis-
mic ruptures (29,30), which tend to be over-
estimated (1) and are typically on the order of
0.5to1m.Thelargevalueweobtainedispos-
sibly related to the earthquake’shavingoccurred
close to the brittle-ductile transition at the lower
edge of the locked portion of the MHT. The mod-
eled smooth onset of the STF and the related large
slip-weakening distance provide an explanation
oftherelativelylowamplitudeofshakingatfre-
quencies above 1 Hz. The observed slip-weakening
behavior does not require the slip-weakening
friction law to be in effect: A fault obeying the
rate-and-state friction law can show an appar-
ent slip-weakening behavior with an effective
critical distance that is several orders of mag-
nitude larger than the critical distance entering
the friction law (31). Aspects of the rupture kine-
matics and ground strong motion observed during
the Gorkha event may also be due to hanging wall
effects, the importance of which could be assessed
through dynamic modeling of the rupture (32,33).
Our study provides insight into the main
factors that determined the damage sustained
during the Gorkha earthquake. Although the
hypocenter was ~80 km away from the city, the
main asperity that radiated most of the energy
was much closer, just north of the basin and at
a relatively shallow depth. Comparison of the
waveforms recorded within the sedimentary
basin at NAST and KATNP (Fig. 3) with the
bedrock records at KKN4 shows prominent
differences, even though the stations are less
than 13 km apart. The waveforms recorded at
the bedrock station KKN4 were simple, mostly
dominated by the single pulse, whereas within
the basin, peak horizontal ground velocities of
0.5 to 0.8 m/s [considered severe to violent (34)]
were sustained for 20 s at KATNP and 40 s at
NAST. The ratio of the amplitude spectra of the
basin waveforms to those recorded at the bed-
rock station (Fig. 3, D to F) indicates an ampli-
fication of long-period energy between 1 and 9 s,
with horizontal-direction amplitudes in the basin
six to seven times as large as those at the bedrock
station. The response spectra (Fig. 3, G to I) show
that, within this amplified period band, the 4-s-
period shaking was the strongest at the basin
stations.
The 4-s peak in the response spectra agrees
with the observation that the source time func-
tion beneath Kathmandu had a duration of ~6
to 7 s. The net effect of this long source duration
with a slow onset time was to produce radiated
energy depleted in the high-frequency component
(fig. S11). This explains why vernacular dwellings
with only a few stories were not severely affected,
despite the anticipated short-period site effects
from microzoning (13). Furthermore, high-frequency
intensity measures such as peak ground accel-
erations (Fig. 2) were modest (~1.6 m/s
2
, MMI =
VI), whereas longer-period intensity measures
such as peak ground velocity (Fig. 3) were very
large (80 cm/s, MMI = IX). Kathmandu was faced
with a combination of source and site effects. The
rupture directivity focused radiated seismic ene rgy
toward the city; the smooth onset and 6- to 7-s
duration of the pulse excited a resonance of the
Kathmandu basin, producing a protracted dura-
tion of violent shaking at a period of around 4 s.
1094 4SEPTEMBER2015•VOL 349 ISSUE 6252 sciencemag.org SCIENCE
84.0°
27.0°
84.0 85.0° 86.0° 87.0°
28.0°
0 km 100 km
Kathmandu
5km
15km
25km
t=27.0s
0.00 0.25 0.50 0.75 1.00
Slip rate (m/s)
0.67a
1.03b
Slip rate (m/s)
0.98c
Ti m e( s)
0.53d
10 20 30 40
Time (s)
0.43e
Slip model
Yof fe
abcde
Fig. 4. Slip-pulse kinematics during the Gorkha earthquake. (A) Snapshot of the slip rate on the
MTH at 27 s after the origin time, during propagation of the seismic rupture from the model in Fig. 1.
The red star is the hypocenter, and dashed contours represent the depth to the fault. The white
circles are the centers of five subfaults used to compare against theoretical regularized Yoffe source
time functions (28). (B) STFs at the five locations from (A). Plotted are the inverted slip rates and the
regularized Yoffe functions measured from the vertical velocity at KKN4, scaled to the maximum
observed slip rate at each point, which is indicated numerically. Time is relative to the hypocentral
origin (28.147°N, 84.708°E; 25 April 2015, 06:11:26.270 UTC).
RESEARCH |REPORTS
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ACKNOWL EDGME NTS
The GPS data are available from the UNAVCO website. The InSAR
data are available at http://topex.ucsd.edu/nepal/. The Nepal
Geodetic Array was funded by Caltech and DASE (to J.-P.A.) and
by the Gordon and Betty Moore Foundation, through grant GBMF
423.01 to the Caltech Tectonics Observatory; support was
maintained by NSF grant EAR-1345136. A. Miner and the Pacific
Northwest Geodetic Array (PANGA) at CWU are thanked for
technical assistance with the construction and operation of the
Tribhuvan University (TU)–CWU network. Additional funding for the
TU-CWU network came from the United Nations Development
Programme and the Nepal Academy for Science and Technology.
The high-rate data were recovered thanks to (i) a rapid
intervention funded by NASA (USA) and the Department of Foreign
International Development (UK) and (ii) engineering services
provided by UNAVCO via the GAGE (Geodesy Advancing
Geosciences and EarthScope) Facility, with support from NSF and
NASA under NSF Cooperative Agreement no. EAR-1261833. We
also thank Trimble Navigation and the Vaidya family for supporting
the rapid response. The accelerometer record at KATNP was
provided by USGS. We thank A. Nathan (U.S. Embassy in
Kathmandu), S. Hough, D. Given, I. Flores, and J. Luetgert for
contributions to the installation of this station. Research at
UC–Berkeley was funded by the Gordon and Betty Moore
Foundation through grant GBMF 3024. A portion of this work
was carried out at JPL under a contract with the NASA.
The GPS data were processed by the Advanced Rapid Imaging and
Analysis Center for Natural Hazards (JPL) and the Scripps Orbit
and Permanent Array Center. The effort at the Scripps Institution
of Oceanography was funded by NASA grants NNX14AQ53G and
NNX14AT33G. Advanced Land Observing Satellite–2 data were
provided by the Japan Aerospace Exploration Agency under
investigations 1148 and 1413. J.-P.A. thanks the Royal Society for
support. We thank D. Dreger for discussion and W. Mooney for
comments. J.-P.A led the study and wrote the article. D.M.
performed the kinematic modeling and wrote the article. Y.B.
supervised the high-rate data processing and wrote the article.
J.Ga. led the field operations. J.Ge. conducted the high-rate data
processing. S.O., A.M., W.S., and J.F.G. conducted the low-rate
data analysis to estimate coseismic offsets. E.O.L. and X.X.
conducted the InSAR data processing. L.B. helped to organize the
field operations. All other authors contributed to building and
servicing the GPS stations and to the post-earthquake data
recovery. All authors edited the article.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/349/6252/1091/suppl/DC1
Materials and Methods
Figs. S1 to S11
Tables S1 and S2
Movie S1
References (35–45)
25 May 2015; accepted 29 July 2015
Published online 6 August 2015
10.1126/science.aac6383
SYNT HETIC B IOLOGY
Complete biosynthesis of opioids
in yeast
Stephanie Galanie,
1
Kate Thodey,
2
Isis J. Trenchard,
2
Maria Filsinger Interrante,
2
Christina D. Smolke
2
*
Opioids are the primary drugs used in Western medicine for pain management and
palliative care. Farming of opium poppies remains the sole source of these essential
medicines, despite diverse market demands and uncertainty in crop yields due to weather,
climate change, and pests. We engineered yeast to produce the selected opioid
compounds thebaine and hydrocodone starting from sugar. All work was conducted in a
laboratory that is permitted and secured for work with controlled substances. We
combined enzyme discovery, enzyme engineering, and pathway and strain optimization
to realize full opiate biosynthesis in yeast. The resulting opioid biosynthesis strains
required the expression of 21 (thebaine) and 23 (hydrocodone) enzyme activities from
plants, mammals, bacteria, and yeast itself. This is a proof of principle, and major hurdles
remain before optimization and scale-up could be achieved. Open discussions of options
for governing this technology are also needed in order to responsibly realize alternative
supplies for these medically relevant compounds.
Opioids are an important class of medicines
that include the analgesic morphine and
the antitussive codeine. The World Health
Organization (WHO) classifies these com-
pounds as essential medicines because of
their utility in treating severe pain, in pain man-
agement, and in palliative care (1). In the de-
veloping world, there are shortages of painkillers;
the WHO has estimated that 5.5 billion people
have “low to nonexistent access to treatment for
moderate or severe pain”(2).
All natural opiates (e.g., morphine and codeine)
and semisynthetic opioids (e.g., oxycodone, hydro-
codone, and hydromorphone) are currently de-
rived from the opium poppy (Papaver somniferum).
Approximately 100,000 ha of opium poppy are
cultivated annually to yield poppy straw contain-
ing more than 800 tons of opiates, primarily mor-
phine and thebaine, to meet licit medical and
scientific demand (3). The majority of poppy-
derived morphine and thebaine is chemically
converted into higher-value compounds, includ-
ing codeine, oxycodone, and hydrocodone. Indus-
trial poppy farming is susceptible to environmental
factors such as pests, disease, and climate, which
can introduce instability and variability into this
geographically concentrated supply chain, result-
ing in pressure to diversify supply (4). Despite
diverse market demands and increasing supply
risks, poppy farming remains the sole source of
opioids, in part because chemical synthesis of
these complex molecules is not commercially
competitive. Approximately 30 chemical syntheses
SCIENCE sciencemag.org 4SEPTEMBER2015•VOL 349 ISSUE 6252 1095
1
Department of Chemistry, Stanford University, Stanford, CA
94305, USA.
2
Department of Bioengineering, Stanford
University, Stanford, CA 94305, USA.
*Corresponding author. E-mail: csmolke@stanford.edu
RESEARCH |REPORTS
DOI: 10.1126/science.aac6383
, 1091 (2015);349 Science et al.J. Galetzka
Gorkha earthquake, Nepal
Slip pulse and resonance of the Kathmandu basin during the 2015
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