1,488 research outputs found
SQG-Differential Evolution for difficult optimization problems under a tight function evaluation budget
In the context of industrial engineering, it is important to integrate
efficient computational optimization methods in the product development
process. Some of the most challenging simulation-based engineering design
optimization problems are characterized by: a large number of design variables,
the absence of analytical gradients, highly non-linear objectives and a limited
function evaluation budget. Although a huge variety of different optimization
algorithms is available, the development and selection of efficient algorithms
for problems with these industrial relevant characteristics, remains a
challenge. In this communication, a hybrid variant of Differential Evolution
(DE) is introduced which combines aspects of Stochastic Quasi-Gradient (SQG)
methods within the framework of DE, in order to improve optimization efficiency
on problems with the previously mentioned characteristics. The performance of
the resulting derivative-free algorithm is compared with other state-of-the-art
DE variants on 25 commonly used benchmark functions, under tight function
evaluation budget constraints of 1000 evaluations. The experimental results
indicate that the new algorithm performs excellent on the 'difficult' (high
dimensional, multi-modal, inseparable) test functions. The operations used in
the proposed mutation scheme, are computationally inexpensive, and can be
easily implemented in existing differential evolution variants or other
population-based optimization algorithms by a few lines of program code as an
non-invasive optional setting. Besides the applicability of the presented
algorithm by itself, the described concepts can serve as a useful and
interesting addition to the algorithmic operators in the frameworks of
heuristics and evolutionary optimization and computing
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Redox-triggered buoyancy and size modulation of a dynamic covalent gel
The development of stimuli-responsive materials capable of transducing external stimuli into mechanical and physical changes has always been an intriguing challenge and an inspiration for scientists. Several stimuli-responsive gels have been developed and applied to biomimetic actuators or artificial muscles. Redox active actuators in which the mechanical motion is driven chemically or electrochemically have attracted much interest and their actuation mechanism is based on the change in electrostatic repulsion and the loss or gain of counterions to balance newly formed charges. Actuation can also be promoted by changing the hydration state of the material leading to the release/adsorption of water molecules from the network, inducing a direct shrinking/swelling of the material respectively. A cationic crystalline dynamic covalent gel was obtained via the formation of imine bonds between 2,6-diformyl pyridine and triamino guanidinium chloride. The gel exhibits a reversible contraction/expansion behavior in response to base (oxidation, âH+, âeâ) and acid (reduction +H+, +eâ) respectively. The oxidation induces a color change and contraction of the gel with a concomitant increase in its strength. As synthesized, the cationic gel is denser than water and sinks when placed in water. Upon oxidation, the radical cationic gel expels water molecules rendering it less dense than water and the gel is propelled to the surface without any loss of its structural integrity. These results demonstrate that a careful choice of amine and aldehyde linkers can give rise to imine-linked materials capable of tolerating and resisting extreme acidic and basic conditions while performing work
10 simple rules to create a serious game, illustrated with examples from structural biology
Serious scientific games are games whose purpose is not only fun. In the
field of science, the serious goals include crucial activities for scientists:
outreach, teaching and research. The number of serious games is increasing
rapidly, in particular citizen science games, games that allow people to
produce and/or analyze scientific data. Interestingly, it is possible to build
a set of rules providing a guideline to create or improve serious games. We
present arguments gathered from our own experience ( Phylo , DocMolecules ,
HiRE-RNA contest and Pangu) as well as examples from the growing literature on
scientific serious games
Measurement of Contractile Stress Generated by Cultured Rat Muscle on Silicon Cantilevers for Toxin Detection and Muscle Performance Enhancement
Background: To date, biological components have been incorporated into MEMS devices to create cell-based sensors and assays, motors and actuators, and pumps. Bio-MEMS technologies present a unique opportunity to study fundamental biological processes at a level unrealized with previous methods. The capability to miniaturize analytical systems enables researchers to perform multiple experiments in parallel and with a high degree of control over experimental variables for high-content screening applications.Methodology/Principal Findings: We have demonstrated a biological microelectromechanical system (BioMEMS) based on silicon cantilevers and an AFM detection system for studying the physiology and kinetics of myotubes derived from embryonic rat skeletal muscle. It was shown that it is possible to interrogate and observe muscle behavior in real time, as well as selectively stimulate the contraction of myotubes with the device. Stress generation of the tissue was estimated using a modification of Stoney's equation. Calculated stress values were in excellent agreement with previously published results for cultured myotubes, but not adult skeletal muscle. Other parameters such as time to peak tension (TPT), the time to half relaxation (KRT) were compared to the literature. It was observed that the myotubes grown on the BioMEMS device, while generating stress magnitudes comparable to those previously published, exhibited slower TPT and KRT values. However, growth in an enhanced media increased these values. From these data it was concluded that the myotubes cultured on the cantilevers were of an embryonic phenotype. The system was also shown to be responsive to the application of a toxin, veratridine.Conclusions/Significance: The device demonstrated here will provide a useful foundation for studying various aspects of muscle physiology and behavior in a controlled high-throughput manner as well as be useful for biosensor and drug discovery applications
Coordinated optimization of visual cortical maps (I) Symmetry-based analysis
In the primary visual cortex of primates and carnivores, functional
architecture can be characterized by maps of various stimulus features such as
orientation preference (OP), ocular dominance (OD), and spatial frequency. It
is a long-standing question in theoretical neuroscience whether the observed
maps should be interpreted as optima of a specific energy functional that
summarizes the design principles of cortical functional architecture. A
rigorous evaluation of this optimization hypothesis is particularly demanded by
recent evidence that the functional architecture of OP columns precisely
follows species invariant quantitative laws. Because it would be desirable to
infer the form of such an optimization principle from the biological data, the
optimization approach to explain cortical functional architecture raises the
following questions: i) What are the genuine ground states of candidate energy
functionals and how can they be calculated with precision and rigor? ii) How do
differences in candidate optimization principles impact on the predicted map
structure and conversely what can be learned about an hypothetical underlying
optimization principle from observations on map structure? iii) Is there a way
to analyze the coordinated organization of cortical maps predicted by
optimization principles in general? To answer these questions we developed a
general dynamical systems approach to the combined optimization of visual
cortical maps of OP and another scalar feature such as OD or spatial frequency
preference.Comment: 90 pages, 16 figure
Identification of moaA3 gene in patient isolates of Mycobacterium tuberculosis in Kerala, which is absent in M. tuberculosis H37Rv and H37Ra
BACKGROUND: Tuberculosis is endemic to developing countries like India. Though the whole genome sequences of the type strain M. tuberculosis H37Rv and the clinical strain M. tuberculosis CDC1551 are available, the clinical isolates from India have not been studied extensively at the genome level. This study was carried out in order to have a better understanding of isolates from Kerala, a state in southern India. RESULTS: A PCR based strategy was followed making use of the deletion region primers to understand the genome level differences between the type strain H37Rv and the clinical isolates of M. tuberculosis from Kerala. PCR analysis of patient isolates using RD1 region primers revealed the amplification of a 386 bp region, in addition to the expected 652 bp amplicon. Southern hybridization of genomic DNA with the 386 bp amplicon confirmed the presence of this new region in a majority of the patient isolates from Kerala. Sequence comparison of this amplicon showed close homology with the moaA3 gene of M. bovis. In M. bovis this gene is present in the RvD5 region, an IS6110 mediated deletion that is absent in M. tuberculosis H37Rv. CONCLUSION: This study demonstrates the presence of moaA3 gene, that is absent in M. tuberculosis H37Rv and H37Ra, in a large number of local isolates. Whether the moaA3 gene provides any specific advantage to the field isolates of the pathogen is unclear. Field strains from Kerala have fewer IS6110 sequences and therefore are likely to have fewer IS6110 dependent rearrangements. But as deletions and insertions account for much of the genomic diversity of M. tuberculosis, the mechanisms of formation of sequence polymorphisms in the local isolates should be further examined. These results suggest that studies should focus on strains from endemic areas to understand the complexities of this pathogen
Coordinated optimization of visual cortical maps (II) Numerical studies
It is an attractive hypothesis that the spatial structure of visual cortical
architecture can be explained by the coordinated optimization of multiple
visual cortical maps representing orientation preference (OP), ocular dominance
(OD), spatial frequency, or direction preference. In part (I) of this study we
defined a class of analytically tractable coordinated optimization models and
solved representative examples in which a spatially complex organization of the
orientation preference map is induced by inter-map interactions. We found that
attractor solutions near symmetry breaking threshold predict a highly ordered
map layout and require a substantial OD bias for OP pinwheel stabilization.
Here we examine in numerical simulations whether such models exhibit
biologically more realistic spatially irregular solutions at a finite distance
from threshold and when transients towards attractor states are considered. We
also examine whether model behavior qualitatively changes when the spatial
periodicities of the two maps are detuned and when considering more than 2
feature dimensions. Our numerical results support the view that neither minimal
energy states nor intermediate transient states of our coordinated optimization
models successfully explain the spatially irregular architecture of the visual
cortex. We discuss several alternative scenarios and additional factors that
may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with
arXiv:1102.335
Singlet-doublet Higgs mixing and its implications on the Higgs mass in the PQ-NMSSM
We examine the implications of singlet-doublet Higgs mixing on the properties
of a Standard Model (SM)-like Higgs boson within the Peccei-Quinn invariant
extension of the NMSSM (PQ-NMSSM). The SM singlet added to the Higgs sector
connects the PQ and visible sectors through a PQ-invariant non-renormalizable
K\"ahler potential term, making the model free from the tadpole and domain-wall
problems. For the case that the lightest Higgs boson is dominated by the
singlet scalar, the Higgs mixing increases the mass of a SM-like Higgs boson
while reducing its signal rate at collider experiments compared to the SM case.
The Higgs mixing is important also in the region of parameter space where the
NMSSM contribution to the Higgs mass is small, but its size is limited by the
experimental constraints on the singlet-like Higgs boson and on the lightest
neutralino constituted mainly by the singlino whose Majorana mass term is
forbidden by the PQ symmetry. Nonetheless the Higgs mixing can increase the
SM-like Higgs boson mass by a few GeV or more even when the Higgs signal rate
is close to the SM prediction, and thus may be crucial for achieving a 125 GeV
Higgs mass, as hinted by the recent ATLAS and CMS data. Such an effect can
reduce the role of stop mixing.Comment: 26 pages, 3 figures; published in JHE
Quantum physics in inertial and gravitational fields
Covariant generalizations of well-known wave equations predict the existence
of inertial-gravitational effects for a variety of quantum systems that range
from Bose-Einstein condensates to particles in accelerators. Additional effects
arise in models that incorporate Born reciprocity principle and the notion of a
maximal acceleration. Some specific examples are discussed in detail.Comment: 25 pages,1 figure,to appear in "Relativity in Rotating Frame
Coverage, Continuity and Visual Cortical Architecture
The primary visual cortex of many mammals contains a continuous
representation of visual space, with a roughly repetitive aperiodic map of
orientation preferences superimposed. It was recently found that orientation
preference maps (OPMs) obey statistical laws which are apparently invariant
among species widely separated in eutherian evolution. Here, we examine whether
one of the most prominent models for the optimization of cortical maps, the
elastic net (EN) model, can reproduce this common design. The EN model
generates representations which optimally trade of stimulus space coverage and
map continuity. While this model has been used in numerous studies, no
analytical results about the precise layout of the predicted OPMs have been
obtained so far. We present a mathematical approach to analytically calculate
the cortical representations predicted by the EN model for the joint mapping of
stimulus position and orientation. We find that in all previously studied
regimes, predicted OPM layouts are perfectly periodic. An unbiased search
through the EN parameter space identifies a novel regime of aperiodic OPMs with
pinwheel densities lower than found in experiments. In an extreme limit,
aperiodic OPMs quantitatively resembling experimental observations emerge.
Stabilization of these layouts results from strong nonlocal interactions rather
than from a coverage-continuity-compromise. Our results demonstrate that
optimization models for stimulus representations dominated by nonlocal
suppressive interactions are in principle capable of correctly predicting the
common OPM design. They question that visual cortical feature representations
can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure
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