15,180 research outputs found
challenges to multi-level capacity building
Communities facing the effects of climate change are actively trying to boost
their resilience. At the same time, governments are mainstreaming climate
change into their development frameworks. Close examination of current
practice, however, points at a disconnect between government policy and
community initiatives. This study explores how strengthening specific
capabilities at various levels can ensure synchronization of policy and
practice and further community resilience in face of climate change. Choosing
an approach that appreciates the interplay of top-‐down and bottom-‐up
logics towards performance under stress, it illust rates that understanding
resilience in terms of capacity opens the door to practical thinking on
policies as well as practices. Evidence is taken from case studies in Chile
and Vietnam to show how governments can play an enabling role when connecting
their efforts to initiatives taken by communities. At the same time,
top-‐down structures, such as the United Nations Framework Convention on
Climate Change (UNFCCC) and the Sustainable Development Goals (SDGs), can help
to break silos between different (inter)national political agendas and
underscore the need to link top-‐down and bottom-‐up approaches to ensure
resilience. This paper contends that improving communities' adaptive capacity
demands bridging the disconnect between multiple levels of policy and
practice. In doing so, different, and too often conflicting, values,
interests, and political agendas need to be aligned. Moreconcretely, we found
that resilience, as an emergent property of human systems, can be enhanced
when government and local stakeholders work together in a number of specific
areas. For instance, combining multi-‐stakeholder platforms in which diverse
actors – ranging from policy-‐makers to researchers to community
representatives – translate lessons learned at the community level intolocal
and national policy, with initiatives aimed at strengthening capacitiesand
ensuring access to relevant assets at the community level
Correlations between hidden units in multilayer neural networks and replica symmetry breaking
We consider feed-forward neural networks with one hidden layer, tree
architecture and a fixed hidden-to-output Boolean function. Focusing on the
saturation limit of the storage problem the influence of replica symmetry
breaking on the distribution of local fields at the hidden units is
investigated. These field distributions determine the probability for finding a
specific activation pattern of the hidden units as well as the corresponding
correlation coefficients and therefore quantify the division of labor among the
hidden units. We find that although modifying the storage capacity and the
distribution of local fields markedly replica symmetry breaking has only a
minor effect on the correlation coefficients. Detailed numerical results are
provided for the PARITY, COMMITTEE and AND machines with K=3 hidden units and
nonoverlapping receptive fields.Comment: 9 pages, 3 figures, RevTex, accepted for publication in Phys. Rev.
Storage capacity of correlated perceptrons
We consider an ensemble of single-layer perceptrons exposed to random
inputs and investigate the conditions under which the couplings of these
perceptrons can be chosen such that prescribed correlations between the outputs
occur. A general formalism is introduced using a multi-perceptron costfunction
that allows to determine the maximal number of random inputs as a function of
the desired values of the correlations. Replica-symmetric results for and
are compared with properties of two-layer networks of tree-structure and
fixed Boolean function between hidden units and output. The results show which
correlations in the hidden layer of multi-layer neural networks are crucial for
the value of the storage capacity.Comment: 16 pages, Latex2
City@home: Monte Carlo derivative pricing distributed on networked computers
Monte Carlo is a powerful and versatile derivative pricing tool, with the main drawback of requiring a large amount of computing time to generate enough realisations of the stochastic process. However, since realisations are independent from each other, the task is “embarrassingly” parallel and the workload can be easily distributed on a large set of processors without the need for fast networking and thus an expensive dedicated supercomputer. Such an alternative, much cheaper and more accessible way can be realised with the BOINC toolkit, distributing the Monte Carlo runs on networked clients running under Windows, Linux or various Unix variants, and recollecting the results at the end for a statistical evaluation of the price distribution at the final time. Though it is likely that the clients will belong to the intranet of a large company or institution, we gave our program the evocative name City@home in honour of the paradigmatic SETI@home project. As an application, we present the generation of synthetic high frequency financial time series for speculative option valuation in the context of uncoupled continuous-time random walks (fractional diffusion), with a Lévy marginal density function for the tick-by-tick log returns and a Mittag-Leffler marginal density function for the waiting times. Lévy deviates are generated with the Chambers-Mallows-Stuck method, Mittag-Leffler deviates with the Kozubowski-Pakes method
Multilayer neural networks with extensively many hidden units
The information processing abilities of a multilayer neural network with a
number of hidden units scaling as the input dimension are studied using
statistical mechanics methods. The mapping from the input layer to the hidden
units is performed by general symmetric Boolean functions whereas the hidden
layer is connected to the output by either discrete or continuous couplings.
Introducing an overlap in the space of Boolean functions as order parameter the
storage capacity if found to scale with the logarithm of the number of
implementable Boolean functions. The generalization behaviour is smooth for
continuous couplings and shows a discontinuous transition to perfect
generalization for discrete ones.Comment: 4 pages, 2 figure
Long-lived quantum coherence in photosynthetic complexes at physiological temperature
Photosynthetic antenna complexes capture and concentrate solar radiation by
transferring the excitation to the reaction center which stores energy from the
photon in chemical bonds. This process occurs with near-perfect quantum
efficiency. Recent experiments at cryogenic temperatures have revealed that
coherent energy transfer - a wavelike transfer mechanism - occurs in many
photosynthetic pigment-protein complexes (1-4). Using the Fenna-Matthews-Olson
antenna complex (FMO) as a model system, theoretical studies incorporating both
incoherent and coherent transfer as well as thermal dephasing predict that
environmentally assisted quantum transfer efficiency peaks near physiological
temperature; these studies further show that this process is equivalent to a
quantum random walk algorithm (5-8). This theory requires long-lived quantum
coherence at room temperature, which never has been observed in FMO. Here we
present the first evidence that quantum coherence survives in FMO at
physiological temperature for at least 300 fs, long enough to perform a
rudimentary quantum computational operation. This data proves that the
wave-like energy transfer process discovered at 77 K is directly relevant to
biological function. Microscopically, we attribute this long coherence lifetime
to correlated motions within the protein matrix encapsulating the chromophores,
and we find that the degree of protection afforded by the protein appears
constant between 77 K and 277 K. The protein shapes the energy landscape and
mediates an efficient energy transfer despite thermal fluctuations. The
persistence of quantum coherence in a dynamic, disordered system under these
conditions suggests a new biomimetic strategy for designing dedicated quantum
computational devices that can operate at high temperature.Comment: PDF files, 15 pages, 3 figures (included in the PDF file
Mesoscopic Spin-Hall Effect in 2D electron systems with smooth boundaries
Spin-Hall effect in ballistic 2D electron gas with Rashba-type spin-orbit
coupling and smooth edge confinement is studied. We predict that the interplay
of semiclassical electron motion and quantum dynamics of spins leads to several
distinct features in spin density along the edge that originate from
accumulation of turning points from many classical trajectories. Strong peak is
found near a point of the vanishing of electron Fermi velocity in the lower
spin-split subband. It is followed by a strip of negative spin density that
extends until the crossing of the local Fermi energy with the degeneracy point
where the two spin subbands intersect. Beyond this crossing there is a wide
region of a smooth positive spin density. The total amount of spin accumulated
in each of these features exceeds greatly the net spin across the entire edge.
The features become more pronounced for shallower boundary potentials,
controlled by gating in typical experimental setups.Comment: 4 pages, 4 figures, published versio
On the violation of a local form of the Lieb-Oxford bound
In the framework of density-functional theory, several popular density
functionals for exchange and correlation have been constructed to satisfy a
local form of the Lieb-Oxford bound. In its original global expression, the
bound represents a rigorous lower limit for the indirect Coulomb interaction
energy. Here we employ exact-exchange calculations for the G2 test set to show
that the local form of the bound is violated in an extensive range of both the
dimensionless gradient and the average electron density. Hence, the results
demonstrate the severity in the usage of the local form of the bound in
functional development. On the other hand, our results suggest alternative ways
to construct accurate density functionals for the exchange energy.Comment: (Submitted on 27 April 2012
Equilibrium spin currents: Non-Abelian gauge invariance and color diamagnetism in condensed matter
The spin-orbit (SO) interaction in condensed matter can be described in terms
of a non-Abelian potential known in high-energy physics as a color field. I
show that a magnetic component of this color field inevitably generates
diamagnetic color currents which are just the equilibrium spin currents
discussed in a condensed matter context. These dissipationless spin currents
thus represent a universal property of systems with SO interaction. In
semiconductors with linear SO coupling the spin currents are related to the
effective non-Abelian field via Yang-Mills magnetostatics equation.Comment: RevTeX, 4 page
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