604 research outputs found
The Use of Mobile Devices as Group Wisdom Support Systems to Support Dynamic Crowdsourcing Efforts
Early group decision support systems (GDSS) literature discussed how group size and member proximity impacted the design of the room and technology necessary to facilitate group decision-making. A Legislative Session is the early term for a large group that holds face to face meetings. With advances in mobile technology, we can turn any large group meeting into an opportunity to capture the wisdom of the crowd. This paper will describe how both crowdsourcing initiatives and group wisdom support systems (GWSS) initiatives can be supported by mobile devices. An example of a keynote address at an academic conference and the use of JoinSpeaker technology will be presented as a way to hold a dynamic crowdsourcing effort
The Case for a Mixed-Initiative Collaborative Neuroevolution Approach
It is clear that the current attempts at using algorithms to create
artificial neural networks have had mixed success at best when it comes to
creating large networks and/or complex behavior. This should not be unexpected,
as creating an artificial brain is essentially a design problem. Human design
ingenuity still surpasses computational design for most tasks in most domains,
including architecture, game design, and authoring literary fiction. This leads
us to ask which the best way is to combine human and machine design capacities
when it comes to designing artificial brains. Both of them have their strengths
and weaknesses; for example, humans are much too slow to manually specify
thousands of neurons, let alone the billions of neurons that go into a human
brain, but on the other hand they can rely on a vast repository of common-sense
understanding and design heuristics that can help them perform a much better
guided search in design space than an algorithm. Therefore, in this paper we
argue for a mixed-initiative approach for collaborative online brain building
and present first results towards this goal.Comment: Presented at WebAL-1: Workshop on Artificial Life and the Web 2014
(arXiv:1406.2507
Quantification of epidermal growth factor receptor T790M mutant transcripts in lung cancer cells by real-time reverse transcriptase-quantitative polymerase chain reaction.
peer reviewedA simple and sensitive real-time reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was developed to quantify threonine-to-methionine substitution at amino acid position 790 (T790M) mutant transcripts in a wild-type (wt) epidermal growth factor receptor background. The assay is based on three unmodified oligonucleotides, and both SYBR Green and a Taqman probe can be used. To increase the discrimination between mutant and wt signals, ARMS (amplification refractory mutation system) and LNA (locked nucleic acid) primers were tested, but a benefit was observed only with plasmids and not with cellular complementary DNA. The RT-qPCR assay using transcript-specific primers can detect as few as 1% T790M transcripts in a wt background and, therefore, will be useful in RNA interference studies specifically targeting mutant RNA
A Simultaneous Stacking and Deblending Algorithm for Astronomical Images
Stacking analysis is a means of detecting faint sources using a priori
position information to estimate an aggregate signal from individually
undetected objects. Confusion severely limits the effectiveness of stacking in
deep surveys with limited angular resolution, particularly at far infrared to
submillimeter wavelengths, and causes a bias in stacking results. Deblending
corrects measured fluxes for confusion from adjacent sources; however, we find
that standard deblending methods only reduce the bias by roughly a factor of
two while tripling the variance. We present an improved algorithm for
simultaneous stacking and deblending that greatly reduces bias in the flux
estimate with nearly minimum variance. When confusion from neighboring sources
is the dominant error, our method improves upon RMS error by at least a factor
of three and as much as an order of magnitude compared to other algorithms.
This improvement will be useful for Herschel and other telescopes working in a
source confused, low signal to noise regime.Comment: accepted to The Astronomical Journal. 18 pages, 6 figure
Low and intermediate-mass close binary evolution and the initial - final mass relation
Using Eggleton's stellar evolution code, we carry out 150 runs of Pop I
binary evolution calculations, with the initial primary mass between 1 and 8
solar masses the initial mass ratio between 1.1 and 4, and the onset of Roche
lobe overflow (RLOF) at an early, middle, or late Hertzsprung-gap stage. We
assume that RLOF is conservative in the calculations, and find that the remnant
mass of the primary may change by more than 40 per cent over the range of
initial mass ratio or orbital period, for a given primary mass. This is
contrary to the often-held belief that the remnant mass depends only on the
progenitor mass if mass transfer begins in the Hertzsprung gap. We fit a
formula, with an error less than 3.6 per cent, for the remnant (white dwarf)
mass as a function of the initial mass of the primary, the initial mass ratio,
and the radius of the primary at the onset of RLOF. We also find that a
carbon-oxygen white dwarf with mass as low as 0.33 solar masses may be formed
if the primary's initial mass is around 2.5 solar masses.Comment: 7 pages for main text, 11 pages for appendix (table A1), 12 figure
On the origin of non-monotonic doping dependence of the in-plane resistivity anisotropy in Ba(Fe)As, = Co, Ni and Cu
The in-plane resistivity anisotropy has been measured for detwinned single
crystals of Ba(FeNi)As and Ba(FeCu)As.
The data reveal a non-monotonic doping dependence, similar to previous
observations for Ba(FeCo)As. Magnetotransport measurements
of the parent compound reveal a non-linear Hall coefficient and a strong linear
term in the transverse magnetoresistance. Both effects are rapidly suppressed
with chemical substitution over a similar compositional range as the onset of
the large in-plane resistivity anisotropy. It is suggested that the relatively
small in-plane anisotropy of the parent compound in the spin density wave state
is due to the presence of an isotropic, high mobility pocket of reconstructed
Fermi surface. Progressive suppression of the contribution to the conductivity
arising from this isotropic pocket with chemical substitution eventually
reveals the underlying in-plane anisotropy associated with the remaining FS
pockets.Comment: 12 pages, 9 figure
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Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management
We develop a new large-scale hydrological and water resources model, the Community Water Model (CWatM), which can simulate hydrology both globally and regionally at different resolutions from 30 arcmin to 30 arcsec at daily time steps. CWatM is open source in the Python programming environment and has a modular structure. It uses global, freely available data in the netCDF4 file format for reading, storage, and production of data in a compact way. CWatM includes general surface and groundwater hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demands, water use, and return flows. Reservoirs and lakes are included in the model scheme. CWatM is used in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which compares global model outputs. The flexible model structure allows for dynamic interaction with hydro-economic and water quality models for the assessment and evaluation of water management options. Furthermore, the novelty of CWatM is its combination of state-of-the-art hydrological modeling, modular programming, an online user manual and automatic source code documentation, global and regional assessments at different spatial resolutions, and a potential community to add to, change, and expand the open-source project. CWatM also strives to build a community learning environment which is able to freely use an open-source hydrological model and flexible coupling possibilities to other sectoral models, such as energy and agriculture
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