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Global Pattern Formation and Ethnic/Cultural Violence

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We identify a process of global pattern formation that causes regions to differentiate by culture. Violence arises at boundaries between regions that are not sufficiently well defined. We model cultural differentiation as a separation of groups whose members prefer similar neighbors, with a characteristic group size at which violence occurs. Application of this model to the area of the former Yugoslavia and to India accurately predicts the locations of reported conflict. This model also points to imposed mixing or boundary clarification as mechanisms for promoting peace.
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(Fig. 3C). The degeneracy of the effective ac-
tivation barriers is lifted at high tunneling cur-
rents, and based on the Arrhenius-like switching
behavior, the mean lifetimes t0;1can be ex-
pressed as (21,22)
t0;1¼u1
aexp Eb
kBT1I
Ic

ð1Þ
where u
a
is the attempt frequency, E
b
is the
effective activation barrier of the island at zero
current, k
B
is the Boltzmann constant, Idenotes
the tunneling current, and I
c
is the threshold
current to switch the magnetization at T=0K.
E
b
was determined by a variation of Tfrom 50.6
to 48.5 K and derivation of the respective mean
lifetimest0;1at low tunneling currents (I=1nA).
For the particular island of Fig. 3, we find E
b
=
133 ± 4 meV, leading to a threshold current of
I
c
=89±4mA. Because such high currents are
not realizable within the tunneling regime, we do
not expect to switch islands of the given di-
mensions at T0 K. Assuming an effective
tunneling area given by the lateral STM resolu-
tion, the corresponding threshold current density
is (113 ± 5) × 10
8
A/cm
2
. This value is, by two to
three orders of magnitude, higher than the current
density used in similar experiments based on
TMR devices (23), which may be attributed to
the fact that, in contrast to planar junctions, the
current density is not distributed homogenously
on the whole nanoisland but acts very locally.
The splitting of the effective activation barrier DE
due to spin-torque effects can be quantified by
DE¼kBTln 1þat
1at
ð2Þ
where a
t
is the lifetime asymmetry. For I= 800
nA, the current-induced spin torque leads to an
effective activation barrier splitting of DE=1.
0.1 meV, which is only 1% of E
b
.
Using a SP-STM tip as the source or drain for
spin-polarized electrons, we were able to perform
spatially resolved measurements where the tip is
moved to different sites of one particular nano-
island, allowing information of site-specific prop-
erties to be gained that cannot be obtained in
spatially averaging experiments performed with
nanopillars. Figure 4A shows the topography of a
nanoisland consisting of about 100 atoms. While
scanning this island with I= 600 nA, we
measured the magnetic dI/dUsignal on each of
the pixels for a duration of 12 s to calculate the
site-specific histogram asymmetry a
H
on the
basis of the corresponding datapoint histograms.
The result is shown in a color-coded representa-
tion in Fig. 4B. In spite of the rather large sta-
tistical error, a gradient along the [001] direction
can clearly be recognized. The effect can even be
analyzed quantitatively by averaging a
H
column-
and row-wise: that is, along the ½110and the
[001] directions, respectively. Whereas aHis
constant within the error at about 42% when
moving the tip along the ½110direction, it clearly
reduces by about 16% from the left to the right
side of the island. The lateral tip position ob-
viously may influence the switching behavior of
the nanoisland at high tunneling currents, as il-
lustrated in Fig. 4, C to E. If the tip is positioned
above the island center, the influence of the
Oersted field along the ½110direction, which is
the easy axis of the nanoisland, cancels (Fig. 4C).
In this case, pure spin-currentinduced switching
occurs. Likewise, no influence by the Oersted
field is expected if the tip is moved from the
center to either island edge along the ½110di-
rection (Fig. 4D) as the effective field acting on
the island is oriented perpendicular to the easy
axis. Only if the tip is moved from the center
along the [001] direction one magnetic state is
favored over the other by the Oersted field (Fig.
4E). In this case, Oersted field effects influence
the magnetic switching behavior, dependent on
the tip position. A detailed analysis of the data
yields that the effective activation barrier
splitting of DE=2.4 ± 0.2 meV at the center
of the island is increased or decreased by up to
0.7 ± 0.2 meV when moving along the [001]
direction to either island edge. This finding
indicates that the magnetization switching is
dominated by the spin torque induced by
the spin-polarized current, whereas the in-
fluence of the Oersted field remains small. A
simple estimation of the energy splitting
caused by the Oersted field, as obtained by
integrating the expected field distribution of
an infinitely expanded current line over the
island area, yields a Zeeman energy of up to
DEOersted ¼
i
m
Bð
riÞ0.2 meV [j
mj=
2.79m
B
(24)] , where
mis the magnetic moment,
Bis the Oersted field,
riis the position of atom i,
and m
B
is the Bohr magneton. This estimated
value is somewhat lower than the experimental
result. We attribute the difference to the over-
simplified geometry of our model.
Our SP-STM studies provide insight into the
details of current-induced magnetization switch-
ing that has been inaccessible in experiments
with lithographically fabricated tunnel junctions.
The ultimate lateral resolution of SP-STM com-
bined with CIMS promises innovative perspec-
tives for future data storage technologies.
References and Notes
1. J. C. Slonczewski, J. Magn. Magn. Mater. 159, L1 (1996).
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D. C. Ralph, Phys. Rev. Lett. 84, 3149 (2000).
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R. A. Buhrman, Phys. Rev. Lett. 89, 226802 (2002).
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Spectroscopy: Methods and Applications (Cambridge
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Hyperfine Interact. 57, 1845 (1990).
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Phys. Rev. Lett. 88, 057201 (2002).
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Phys. Rev. Lett. 92, 067201 (2004).
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R. Wiesendanger, Microsc. Res. Tech. 66, 117 (2005).
18. Supporting materials are available on Science Online.
19. M. P. Seah, W. A. Dench, Surf. Interface Anal. 1,2
(1979).
20. H. Goldenberg, Br. J. Appl. Phys. 3, 296 (1952).
21. J. Z. Sun, IBM J. Res. Dev. 50, 81 (2006).
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(2004).
23. G. D. Fuchs et al., Appl. Phys. Lett. 85, 1205 (2004).
24. J. Hauschild, H. J. Elmers, U. Gradmann, Phys. Rev. B 57,
R677 (1998).
25. Financial support from the Deutsche Forschungsgemeinschaft
(SFB668-B4) and the European Union project Advanced
Scanning Probes for Innovative Science and Technology
(ASPRINT) is acknowledged.
Supporting Online Material
www.sciencemag.org/cgi/content/full/317/5844/1537/DC1
SOM Text
Fig. S1
17 May 2007; accepted 26 July 2007
10.1126/science.1145336
Global Pattern Formation and
Ethnic/Cultural Violence
May Lim,
1,2
Richard Metzler,
1,3
Yaneer Bar-Yam
1
*
We identify a process of global pattern formation that causes regions to differentiate by culture.
Violence arises at boundaries between regions that are not sufficiently well defined. We model
cultural differentiation as a separation of groups whose members prefer similar neighbors, with a
characteristic group size at which violence occurs. Application of this model to the area of the
former Yugoslavia and to India accurately predicts the locations of reported conflict. This model
also points to imposed mixing or boundary clarification as mechanisms for promoting peace.
Over the past 100 years, more than 100
million people have died in violent con-
flicts (1). Of these deaths, a great number
are attributable to ongoing local conflict between
culturally or ethnically distinct groups. A scien-
tific understanding of the underlying causes of
ethnic violence could lead to policy changes that
may help stop or prevent it. The existing literature
(213) [see also bibliography of ethnic and cul-
tural conflict in the supporting online materials
(14)] generally considers (i) the process by which
ethno-religious identity is established and if inter-
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ventions could diminish its importance relative to
more inclusive identities, and (ii) control mech-
anisms of the state and of organizations of ethnic
groups and if interventions could strengthen the
state while subsuming or accommodating ethnic
groups within state authority. More specific so-
cial and economic factors identified in the litera-
ture as contributing to violence include oppression
of minorities, economic grievances, historical prec-
edents, competition for resources, favoritism, avail-
ability of resources for violence, security fears,
mobilization by elites, weak social ties, national
ethnic diversity, territorial claims, religious or po-
litical polarization, incendiary media, and inter-
national influences. Although most of these studies
consider national conditions, a few consider lo-
cal violence to identify the role of local socio-
economic or geographic factors (79). Here, we
focus on an aspect of spatial population structure
that has been neglected so far; we analyze the
global pattern of violence and propose that many
instances are consistent with the natural dynam-
ics of type separation (1518), a form of pattern
formation (19) also seen in physical or chemical
phase separation. Violence arises due to the struc-
ture of boundaries between groups rather than as
a result of inherent conflicts between the groups
themselves. In this approach, diverse social and
economic causal factors trigger violence when
the spatial population structure creates a propen-
sity to conflict, so that spatial heterogeneity itself
is predictive of local violence. The local ethnic
patch size serves as an order parameter,a mea-
sure of the degree of order of collective behavior,
to which other aspects of behavior are coupled.
The importance of collective behavior implies that
ethnic violence can be studied in the universal
context of collective dynamics, where models
can identify how individual and collective be-
havior are related.
A simple model of type separation is shown
in Fig. 1, A to E. The dynamics of this model
assume that individuals preferentially move to
areas where more individuals of the same type
reside (14). The resulting dynamics lead to pro-
gressively larger patches (islandsor peninsu-
las) of each type. The average size of patches at
a particular time can be obtained by a number of
different methods. We used overlapping spatial
waves that represent the spatial variation of the
population density. Each wave makes a contribu-
tion proportional to its correlation with the pop-
ulation density (the structure factor or Fourier
transform). The wavelength of the wave that has
the maximum amplitude gives the average size of
the patches. Other methods of obtaining the size
of patches give similar results. The size of the
patches grows as a characteristic power of time
(Fig. 1F, inset). This behaviorhas been proven (20)
to be a universal behaviorthat does not depend
on many of the details of the model and therefore
may be relied on to describe a large variety of
systems of interacting elements; in particular, simi-
lar models have been used to describe the relation
of chemical interaction energies and chemical
precipitation or phase separation (21,22). The
universal properties of the patterns upon rescal-
ing of length and time also imply that a number
of individual agents of the model can be
aggregated into a single agent if time is rescaled
correspondingly without changing the behavior
at the larger scales (Fig. 1F). Thus, it is possible
to consider a model agent to represent a local
population, and it is not necessary to model the
behavior of each individualan impractical
undertaking.
To model violence, we assume that highly
mixed regions do not engage in violence, and
neither do well-segregated groups, an intuitive
hypothesis with empirical support (7). The analy-
1
New England Complex Systems Institute, 24 Mt. Auburn
Street, Cambridge, MA 02138, USA.
2
Brandeis University,
Waltham, MA 02454, USA.
3
Massachusetts Institute of
Technology, Cambridge, MA 02139, USA.
*To whom correspondence should be addressed. E-mail:
yaneer@necsi.edu
ED
012 34
5
10
15
S(k,t) k2max(t)
t=1
t=16
t=512
t=256
t=2048
t=4096
t=8192
t=16384
t=32768
t=256
t1/3
0
5
10
15
20
25
patch size
N/2kmax
Fit to At1/3+B—
F
ABC
010 20 30
k/kmax(t)
Fig. 1. Simulation of type separation with two types of agents [(A)to(E)show
the system at 8, 64, 512, 4096, and 32768 attempted moves per particle,
respectively]. The shape of domains (as characterized by the rescaled structure
factor amplitude squared) remains constant after an initial transient (F), and
the average size of clusters grows as a power law [inset of (F)] (14). Patches of a
certain size that are surrounded by the other type are highlighted by red
shading overlay in (A) to (E). We identify such regions with a high likelihood of
conflict.
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sis is applicable to communal violence and not to
criminal activity or interstate warfare. In highly
mixed regions, groups of the same type are not
large enough to develop strong collective identi-
ties, or to identify public spaces as associated with
one or another cultural group. They are neither
imposed upon nor impose upon other groups,
and are not perceived as a threat to the cultural
values or social/political self-determination of
other groups. Partial separation with poorly de-
fined boundaries fosters conflict. Violence arises
when groups are of a size that they are able to
impose cultural norms on public spaces, but where
there are still intermittent violations of these rules
due to the overlap of cultural domains. When
groups are larger than the critical size, they typi-
cally form self-sufficient entities that enjoy local
sovereignty. Hence, we expect violence to arise
when groups of a certain characteristic size are
formed, and not when groups are much smaller
or larger than this size. The model of violence
depends on the distribution of the population and
not on the specific mechanism by which the
population achieves this structure, which may
include internally or externally directed migra-
tions. By focusing on the geographic distribution
of the population, the model seeks a predictor of
conflict that can be easily determined by census.
This may work well because geography is an im-
portant aspect of the dimensions of social space,
the dynamic coarsening process is universal, and
other aspects of social behavior (e.g., isolation-
ism, conformity, as well as violence) are corre-
latedtoit.
The predictor that we identify based on spatial
census data need not describe the immediate social
or institutional triggers of violence, only the
conditions under which violence becomes likely.
Previous research aiming to characterize ethnic
conflict by census data has focused on measures of
ethnic or religious fragmentation(2327). Such
measures characterize the diversity of a country
without reference to its spatial structure, i.e., the
overall proportions of ethnically distinct groups in a
country. They are therefore distinct from the spatial
characterization of our study. The literature is
divided about whether or which correlations exist
with measures of national ethnic composition. We
0
0
Based on opstina data from 1991 census
Albanian
Bulgarian
Croat
Hungarian
Macedonian
Muslim
Serb
Slovak
Montenegrin
Slovene
100 kilometers
100 miles
No majority present
Hungarian, 1.9
Montenegrin, 2.5
Yugoslav, 5.4*
Macedonia, 5.9
Albanian, 7.7
Slovene, 7.8
Muslim, 8.9
Other, 3.9
Croat, 19.7
Self-identified as Yugoslavs.
Dispersed around country.
*
AB
C
Muslims
Croats
Serbs
Albanians
Conflict
Muslims
Croats
Serbs
Albanians
0 1
D
Serb, 36.3
Fig. 2. (A) Census data from 1991 shown here in map form were
converted into a spatial representation and used in an agent-based
simulation shown in (B). Our prediction of populations likely to be in
conflict with neighboring groups [red overlay, (C) and (D)] agrees well
with the location of cities reported as sites of major fights and massacres
[yellow dots, (D)].
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find, however, that the spatial distribution of ethnic
groups is a strong predictor of locations of violence.
Mathematically, the expected violence was de-
termined by detecting patches consisting of islands
or peninsulas of one type surrounded by popula-
tions of other types. We detected these features by
correlation of the population for each population
type with a template that has a positive center and a
negative surround. To illustrate the effect of this
correlation, for a particular template size, the
maximum correlation over population types is
superimposed as a red overlay in Fig. 1, A to E.
Over time in this simulation, the patch size starts
smaller, then passes through and becomes larger
than the template size chosen. The specific tem-
plate that we used is based on a wavelet filter
(14,2830). Wavelets are designed to obtain a
local measure of the degree to which a certain scale
of variation (wavelength) is present. Outcomes are
highly robust, and other templates give similar
results. Given the universality of the dynamic
behavior, the diameter of the positive region of the
wavelet, i.e., the size of the local population patches
that are likely to experience violence, is the only
essential parameter of the model. The parameter is
to be determined by agreement of the model with
reports of violence, though as we will see, the
agreement is robust to variation of the parameter.
The quality of the agreement provides a measure of
the validity of the model.
To test the predictive ability of the model, we
performed simulations based on census data for the
former Yugoslavia and India. We assigned areas of
pixelated geographic maps pixel by pixel to ethnic
groups at random, but in proportion to their relative
population census in the region. Although this does
not reflect the physical geography or local mixing of
groups in buildings and villages, over an area of
multiple pixels it captures the regional composition
of the census. The pixelated map serves as the
beginning state for the agent model. For Yugoslavia,
census data from the early 1990s before the outbreak
of conflict (31,32), as shown in Fig. 2A, were
captured into an agent simulation (Fig. 2B),
which was used to obtain the regions of expected
violence shown in Fig. 2C.
We then obtained from books (2), newspapers,
and Internet sources (see supporting online text) the
locations of reported violence for the area of the
former Yugoslavia. Multiple independent sources
were used to provide validation for each location of
violence (14). We consider these reports as indi-
cators of areas of actual violence, keeping in mind
possible bias and incompleteness and that areas of
widespread violence are identified only by local
urban centers. In comparing such reports with mod-
el predictions, we note that the model identifies
locations of groups of a particular size, but the loca-
tion of the actual violence should occur somewhere
in the area between adjacent groups. Despite these
caveats, overlaying the locations of reported and
predicted violence in Fig. 2D demonstrates a
significant ability of our simple model to identify
regions of reported violence. We performed statis-
tical analyses comparing the predicted to the re-
ported violence, evaluating the ability of the model
to determine both where violence occurs and where
violence does not occur. For comparison, we ran-
domized the locations of reported violence. We
defined conflict proximityas the distance between
a given position and the nearest location of violence
(predicted, reported, or randomized). We calculated
Pearson's correlation and other statistical measures
between the proximities of predicted and reported
violence, and compared them with the same mea-
sures in relation to randomized reports. We found
that the model has a correlation of 0.9 with reports
(0.89 to two significant digits), a level of agreement
not reached in any of 100,000 randomized trials.
Moreover, the predicted results are highly robust to
parameter variation, with essentially equivalent
agreement obtained for filter diameters ranging from
18 to 60 km, a range that is in agreement with
intuition about the size of conflict areas. Below or
above this range, poorer agreement occurs. Details
are provided in the supporting online text.
We studied conflict in India as a second case
study of the ethnic violence model. We constructed
a spatial representation of India on a district level
from maps at www.censusindia.net and obtained
the distribution of ethno-cultural groups from the
2001 Census data at www.indiastat.com. The re-
sult can be seen in the form of three-color maps in
Fig. 3, A and B, representing the relative densities
of Hindus, Muslims, Christians, Sikhs, Buddhists,
and Others (primarily Jains). The agent model is
shown in Fig. 3C and the prediction of ethnic vi-
olence is indicated in Fig. 3D. Predictions cor-
respond very well to the primary locations of
extremistviolence of government reports as
given by indiastat.com (Fig. 3E) and confirmed
by independent sources (14), particularly in
Kashmir, Punjab, and the states of Northeast India.
Some additional areas of lesser violence were also
predicted by the model, particularly Jharkhand
an eastern state created in 2000 that has recently
experienced some violence (14,33). Consistent
with predicted results, the violence in this region is
not as prevalent as in other violence-prone areas of
India. Statistical correlation measures of conflict
proximity yield a correlation of 0.998 when the
threshold is set above the value of predicted
violence in Jharkhand. If the threshold is set low-
er, so that violence in Jharkhand is included in
predicted but not in reported cases, the correlation
falls to 0.92. Including reported violence in
Jharkhand when comparing at the lower threshold
increases the correlation to 0.98. Additional details
are provided in the supporting online text. The
range of filter diameter values for which good
agreement was obtained overlaps that of the former
Yugoslavia. However, it is shifted to larger values,
up to ~100 km. This may reflect not only the larger
granularity of data, but perhaps also the effect of
violence itself on separation. Unlike Yugoslavia, in
India the census was performed during ongoing
violence. Because violence accelerates the process
of separation, groups in conflict are likely to have
separated substantially and reflect the high end
of group sizes susceptible to violence.
Governmental and nongovernmental organi-
zations are devoting increasing attention to the
prevention of major conflict (34).Under some
circumstances, social and institutional factors that
affect violence might serve to suppress the trig-
gering of violence without changing the spatial
structure of the population. However, influencing
the spatial structure might address the conditions
that promote violence described here. Such ap-
ABC
DE
Fig. 3. (Aand B) Spatial representation of Indian census data from 2001 of six indicated groups was
converted into an agent-based simulation shown in (C). Our prediction of conflict-prone areas [red areas
in (D)] agrees with states where major ethnic violence has been reported [red areas in (E)] between 1999
and 2002, with the red shading intensity corresponding to the rank order of states by number of incidents.
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proaches have been and are being considered. For
example, in Singapore, where 84% of the popu-
lation lives in public housing (35), regulations that
explicitly recognize the role of spatial segregation in
sectarianism specify the percentage of ethnic groups
to occupy housing blocks (36). This legally
compels ethnic mixing at a scale finer than that
which our study finds likely to lead to violence.
Given the natural tendency toward social separa-
tion, maintaining such mixing requires a level of
authoritarianism that might not be entertained in
other locations. Still, despite social tensions (37),
the current absence of violence provides some
support to our analysis. The alternative approach
aiding in the separation process by establishing
clear boundaries between cultural groups to
prevent violencehas also gained recent atten-
tion (38,39). Although further studies are
needed, there exist assessments (39)oftheimpact
of historical partitions in Ireland, Cyprus, the
Indian subcontinent, and the Middle East that
may be consistent with the understanding of type
separation and a critical scale of mixing or
separation presented here.
The insight provided by this study may help
inform policy debates by guiding our understanding
of the consequences of policy alternatives. The
purpose of this paper does not include promoting
specific policy options. Although our work re-
inforces suggestions to consider separation, we are
not diminishing the relevance of concerns about the
desirability of separation or its process. Even where
separation may be indicated as a way of preventing
violence, caution is warranted to ensure that the
goal of preventing violence does not become a
justification for violence. Moreover, even a peaceful
process of separation is likely to be objectionable.
There may be ways to positively motivate
separation using incentives, as well as to mitigate
negative aspects of separation that often include
displacement of populations and mobility barriers.
Our results for the range of filter diameters that
provide good statistical agreement between
reported and predicted violence in the former
Yugoslavia and India suggest that regions of width
less than 10 km or greater than 100 km may
provide sufficient mixing or isolation to reduce the
chance of violence. These bounds may be affected
by a variety of secondary factors including social
and economic conditions; the simulation resolu-
tion may limit the accuracy of the lower limit; and
boundaries such as rivers, other physical barriers,
or political divisions will surely play a role. Still,
this may provide initial guidance for strategic
planning. Identifying the nature of boundaries to
be established and the means for ensuring their
stability, however, must reflect local issues.
Our approach does not consider the relative
merits of cultures, individual acts, or immediate
causes of violence, but rather the conditions that may
promote violence. It is worth considering whether, in
places where cultural differentiation is taking place,
conflict might be prevented or minimized by political
acts that create appropriate boundaries suited to the
current geocultural regions rather than the existing
historically based state boundaries. Such bounda-
ries need not inhibit trade and commerce and need
not mark the boundaries of states, but should allow
each cultural group to adopt independent behav-
iors in separate domains. Peaceful coexistence
need not require complete integration.
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Muslims in India (Yale Univ. Press, New Haven, CT, 2003).
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Supporting Online Material
www.sciencemag.org/cgi/content/full/317/5844/1540/DC1
Methods
Figs. S1.1 to S4.3
SOM Text
Table S1
References
Bibliography
30 November 2006; accepted 13 August 2007
10.1126/science.1142734
Crystal Structure of an Ancient
Protein: Evolution by
Conformational Epistasis
Eric A. Ortlund,
1
*Jamie T. Bridgham,
2
*Matthew R. Redinbo,
1
Joseph W. Thornton
2
The structural mechanisms by which proteins have evolved new functions are known only indirectly.
We report x-ray crystal structures of a resurrected ancestral proteinthe ~450 million-year-old
precursor of vertebrate glucocorticoid (GR) and mineralocorticoid (MR) receptors. Using structural,
phylogenetic, and functional analysis, we identify the specific set of historical mutations that
recapitulate the evolution of GRs hormone specificity from an MR-like ancestor. These
substitutions repositioned crucial residues to create new receptor-ligand and intraprotein contacts.
Strong epistatic interactions occur because one substitution changes the conformational position
of another site. Permissivemutationssubstitutions of no immediate consequence, which
stabilize specific elements of the protein and allow it to tolerate subsequent function-switching
changesplayed a major role in determining GRs evolutionary trajectory.
Acentral goal in molecular evolution is to
understand the mechanisms and dynam-
ics by which changes in gene sequence
generate shifts in function and therefore pheno-
type (1,2). A complete understanding of this
process requires analysis of how changes in protein
structure mediate the effects of mutations on
function. Comparative analyses of extant proteins
have provided indirect insights into the diversifi-
cation of protein structure (36), and protein
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(5844), 1540-1544. [doi: 10.1126/science.1142734]317Science
2007)
May Lim, Richard Metzler and Yaneer Bar-Yam (September 14,
Global Pattern Formation and Ethnic/Cultural Violence
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Chaim D. Kaufmann is Associate Professor of International Relations at Lehigh University. The author's thanks are owed to Robert Art, Pauline Baker, John Mearsheimer, Robert Pape, Edward Rhodes, Jack Snyder, Monica Toft, Stephen Van Evera, Barbara Walter, and the members of the University of Chicago Program on International Security and Policy for comments. Research for this article was supported by the United States Institute of Peace. 1. John J. Mearsheimer, "Shrink Bosnia to Save It," New York Times, March 31, 1993; Mearsheimer and Stephen W. Van Evera, "When Peace Means War," New Republic, December 18, 1995, pp. 16-21; Robert M. Hayden, "Schindler's Fate: Genocide, Ethnic Cleansing, and Population Transfers," Slavic Review, Vol. 55, No. 4 (Winter 1996), pp. 740-742; Ivo H. Daalder, "Bosnia after SFOR: Options for Continued U.S. Engagement," Survival, Vol. 39, No. 4 (Winter 1997-98), pp. 5-18; Robert A. Pape, "Partition: An Exit Strategy for Bosnia," Survival, Vol. 39, No. 4 (Winter 1997-98), pp. 25-28; and Michael O'Hanlon, "Turning the Cease-fire into Peace," Brookings Review, Vol. 16, No. 1 (Winter 1998), pp. 41-44. In addition, some analysts who oppose the partition of Bosnia admit that reintegration of the separated populations would be very difficult. See Charles G. Boyd, "Making Bosnia Work," Foreign Affairs, Vol. 77, No. 1 (January/February 1998), pp. 42-55; Susan L. Woodward, "Avoiding Another Cyprus or Israel," Brookings Review, Vol. 16, No. 1 (Winter 1998), pp. 45-48; and Jane M.O. Sharp, "Dayton Report Card," International Security, Vol. 22, No. 3 (Winter 1997/98), p. 133. Flora Lewis, "Reassembling Yugoslavia," Foreign Policy, No. 98 (Spring 1995), pp. 132-144, argues that Bosnia could be reintegrated. 2. Barry R. Posen, "The Security Dilemma and Ethnic Conflict," in Michael E. Brown, ed., Ethnic Conflict and International Security (Princeton, N.J.: Princeton University Press, 1993), pp. 103-124; Chaim Kaufmann, "Possible and Impossible Solutions to Ethnic Civil Wars," International Security, Vol. 20, No. 4 (Spring 1996), pp. 136-175; and Daniel L. Byman, "Divided They Stand: Lessons about Partition from Iraq and Lebanon," Security Studies, Vol. 7, No. 1 (Autumn 1997), pp. 1-29. See also Myron S. Weiner, "Bad Neighbors, Bad Neighborhoods: An Inquiry into the Causes of Refugee Flows," International Security, Vol. 21, No. 1 (Summer 1996), pp. 37-38; and Clive J. Christie, "Partition, Separatism, and National Identity," Political Quarterly, Vol. 63, No. 1 (January-March 1992), pp. 68-78. On why separation can resolve ethnic conflicts but not ideological civil wars, see Chaim Kaufmann, "Intervention in Ethnic and Ideological Civil Wars," Security Studies, Vol. 6, No. 1 (Autumn 1996), pp. 62-103. 3. Radha Kumar, "The Troubled History of Partition," Foreign Affairs, Vol. 76, No. 1 (January/February 1997), pp. 22-34. 4. Posen, "Security Dilemma and Ethnic Conflict," pp. 108-111. 5. The processes of war, especially reports of real or imagined enemy atrocities, also harden ethnic identities and solidify hostility and mistrust, creating additional hard-to-counter threat perceptions even in excess of real threats; this effect persists for a considerable time even after the end of large-scale fighting. Kaufmann, "Possible and Impossible Solutions," pp. 141-145, 150-151. 6. For additional types of proposed solutions to ethnic conflicts, see Donald L. Horowitz, "Making Moderation Pay," in Joseph V. Montville, ed., Conflict and Peacemaking in Multiethnic Societies (New York: Lexington Books, 1991), pp. 451-476; Arend J. Lijphart, "The Power-Sharing Approach," in ibid., pp. 491-510; Gidon Gottlieb, Nation against State (New York: Council on Foreign Relations, 1993); and I. William Zartman, "Putting Things Back Together," in Zartman, ed., Collapsed States: The Disintegration and Restoration of Legitimate Authority (Boulder, Colo.: Lynne Rienner, 1995), pp. 267-273. For an analysis that focuses on perceptual rather than structural aspects of intergroup security dilemmas, and recommends solutions based on institution and confidence building, see David A. Lake and Donald Rothchild, "Containing Fear: The Origins and Management of Ethnic Conflict," International Security, Vol. 21, No. 1 (Fall 1996), pp. 41-75. 7. Although, in principle, final political arrangements could be based on either regional autonomy or separate sovereignty, in practice, demographic separation is likely to be...
Article
This article outlines a consistent and rational model for solving ethnic conflicts. We argue that ethnic separation should be regarded as an alternative to national unity, and not simply dismissed as impossible. A decision on separation or unity should be made democratically by the group whose separation has been proposed. If separation is approved, migration over the border between the newly formed states should be part of such a solution. The article has three main parts: (1) a model for solving separationist demands; (2) an analysis of the evolutionary background to ethnic conflicts; and (3) a discussion of principal objections to the proposed model. The present international impotence in situations of ethnic conflict is to a high degree caused by seeing most solutions as impossible - either realistically or morally. This article stresses the virtue of having one model instead of the "flexibility" that currently prevails under the disguise of generally acclaimed, but contradictory ideals.