1,588 research outputs found
Horizon Scanning Report: An Investigation into the Development of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) - Enabled Healthcare Technologies
Algorithm for normal random numbers
We propose a simple algorithm for generating normally distributed pseudo
random numbers. The algorithm simulates N molecules that exchange energy among
themselves following a simple stochastic rule. We prove that the system is
ergodic, and that a Maxwell like distribution that may be used as a source of
normally distributed random deviates follows when N tends to infinity. The
algorithm passes various performance tests, including Monte Carlo simulation of
a finite 2D Ising model using Wolff's algorithm. It only requires four simple
lines of computer code, and is approximately ten times faster than the
Box-Muller algorithm.Comment: 5 pages, 3 encapsulated Postscript Figures. Submitted to
Phys.Rev.Letters. For related work, see http://pipe.unizar.es/~jf
Explanations of Black-Box Model Predictions by Contextual Importance and Utility
The significant advances in autonomous systems together with an immensely
wider application domain have increased the need for trustable intelligent
systems. Explainable artificial intelligence is gaining considerable attention
among researchers and developers to address this requirement. Although there is
an increasing number of works on interpretable and transparent machine learning
algorithms, they are mostly intended for the technical users. Explanations for
the end-user have been neglected in many usable and practical applications. In
this work, we present the Contextual Importance (CI) and Contextual Utility
(CU) concepts to extract explanations that are easily understandable by experts
as well as novice users. This method explains the prediction results without
transforming the model into an interpretable one. We present an example of
providing explanations for linear and non-linear models to demonstrate the
generalizability of the method. CI and CU are numerical values that can be
represented to the user in visuals and natural language form to justify actions
and explain reasoning for individual instances, situations, and contexts. We
show the utility of explanations in car selection example and Iris flower
classification by presenting complete (i.e. the causes of an individual
prediction) and contrastive explanation (i.e. contrasting instance against the
instance of interest). The experimental results show the feasibility and
validity of the provided explanation methods
Phase diffusion as a model for coherent suppression of tunneling in the presence of noise
We study the stabilization of coherent suppression of tunneling in a driven
double-well system subject to random periodic function ``kicks''. We
model dissipation due to this stochastic process as a phase diffusion process
for an effective two-level system and derive a corresponding set of Bloch
equations with phase damping terms that agree with the periodically kicked
system at discrete times. We demonstrate that the ability of noise to localize
the system on either side of the double-well potenital arises from overdamping
of the phase of oscillation and not from any cooperative effect between the
noise and the driving field. The model is investigated with a square wave
drive, which has qualitatively similar features to the widely studied
cosinusoidal drive, but has the additional advantage of allowing one to derive
exact analytic expressions.Comment: 17 pages, 4 figures, submitted to Phys. Rev.
In situ normothermic regional perfusion for controlled donation after circulatory death - The United Kingdom experience
Curve crossing in linear potential grids: the quasidegeneracy approximation
The quasidegeneracy approximation [V. A. Yurovsky, A. Ben-Reuven, P. S.
Julienne, and Y. B. Band, J. Phys. B {\bf 32}, 1845 (1999)] is used here to
evaluate transition amplitudes for the problem of curve crossing in linear
potential grids involving two sets of parallel potentials. The approximation
describes phenomena, such as counterintuitive transitions and saturation
(incomplete population transfer), not predictable by the assumption of
independent crossings. Also, a new kind of oscillations due to quantum
interference (different from the well-known St\"uckelberg oscillations) is
disclosed, and its nature discussed. The approximation can find applications in
many fields of physics, where multistate curve crossing problems occur.Comment: LaTeX, 8 pages, 8 PostScript figures, uses REVTeX and psfig,
submitted to Physical Review
Dark-in-Bright Solitons in Bose-Einstein Condensates with Attractive Interactions
We demonstrate a possibility to generate localized states in effectively
one-dimensional Bose-Einstein condensates with a negative scattering length in
the form of a dark soliton in the presence of an optical lattice (OL) and/or a
parabolic magnetic trap. We connect such structures with twisted localized
modes (TLMs) that were previously found in the discrete nonlinear
Schr{\"o}dinger equation. Families of these structures are found as functions
of the OL strength, tightness of the magnetic trap, and chemical potential, and
their stability regions are identified. Stable bound states of two TLMs are
also found. In the case when the TLMs are unstable, their evolution is
investigated by means of direct simulations, demonstrating that they transform
into large-amplitude fundamental solitons. An analytical approach is also
developed, showing that two or several fundamental solitons, with the phase
shift between adjacent ones, may form stable bound states, with
parameters quite close to those of the TLMs revealed by simulations. TLM
structures are found numerically and explained analytically also in the case
when the OL is absent, the condensate being confined only by the magnetic trap.Comment: 13 pages, 7 figures, New Journal of Physics (in press
Contribution of extracellular negatively charged residues to ATP action and zinc modulation of rat P2X 2 receptors
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65506/1/j.1471-4159.2008.05228.x.pd
Social preferences, accountability, and wage bargaining
We assess the extent of preferences for employment in a collective wage bargaining situation with heterogeneous workers. We vary the size of the union and introduce a treatment mechanism transforming the voting game into an individual allocation task. Our results show that highly productive workers do not take employment of low productive workers into account when making wage proposals, regardless of whether insiders determine the wage or all workers. The level of pro-social preferences is small in the voting game, while it increases as the game is transformed into an individual allocation task. We interpret this as an accountability effect
Interpol: An R package for preprocessing of protein sequences
<p>Abstract</p> <p>Background</p> <p>Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequences, that often differ in length due to insertions and deletions. It is also notable that performance in classification and regression is often improved by numerical encoding of amino acids, compared to the commonly used sparse encoding.</p> <p>Results</p> <p>The software "Interpol" encodes amino acid sequences as numerical descriptor vectors using a database of currently 532 descriptors (mainly from AAindex), and normalizes sequences to uniform length with one of five linear or non-linear interpolation algorithms. Interpol is distributed with open source as platform independent R-package. It is typically used for preprocessing of amino acid sequences for classification or regression.</p> <p>Conclusions</p> <p>The functionality of Interpol widens the spectrum of machine learning methods that can be applied to biological sequences, and it will in many cases improve their performance in classification and regression.</p
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