259 research outputs found
Revisiting the design intent concept in the context of mechanical CAD education
[EN] Design intent is generally understood simply as a CAD model¿s anticipated behavior when altered.
However, this representation provides a simplified view of the model¿s construction and purpose,
which may hinder its general understanding and future reusability. Our vision is that design intent
communication may be improved by recognizing the multifaceted nature of design intent, and by
instructing users to convey each facet of design intent through the better-fitted CAD resource. This
paper reviews the current understanding of design intent and its relationship to design rationale and
builds on the idea that communication of design intent conveyed via CAD models can be satisfied
at three levels provided that specialized instruction is used to instruct users in selection of the most
suitable level for each intent.Otey, J.; Company, P.; Contero, M.; Camba, J. (2018). Revisiting the design intent concept in the context of mechanical CAD education. Computer-Aided Design and Applications. 15(1):47-60. https://doi.org/10.1080/16864360.2017.1353733S476015
New hadrons as ultra-high energy cosmic rays
Ultra-high energy cosmic ray (UHECR) protons produced by uniformly
distributed astrophysical sources contradict the energy spectrum measured by
both the AGASA and HiRes experiments, assuming the small scale clustering of
UHECR observed by AGASA is caused by point-like sources. In that case, the
small number of sources leads to a sharp exponential cutoff at the energy
E<10^{20} eV in the UHECR spectrum. New hadrons with mass 1.5-3 GeV can solve
this cutoff problem. For the first time we discuss the production of such
hadrons in proton collisions with infrared/optical photons in astrophysical
sources. This production mechanism, in contrast to proton-proton collisions,
requires the acceleration of protons only to energies E<10^{21} eV. The diffuse
gamma-ray and neutrino fluxes in this model obey all existing experimental
limits. We predict large UHE neutrino fluxes well above the sensitivity of the
next generation of high-energy neutrino experiments. As an example we study
hadrons containing a light bottom squark. These models can be tested by
accelerator experiments, UHECR observatories and neutrino telescopes.Comment: 17 pages, revtex style; v2: shortened, as to appear in PR
On the selection of AGN neutrino source candidates for a source stacking analysis with neutrino telescopes
The sensitivity of a search for sources of TeV neutrinos can be improved by
grouping potential sources together into generic classes in a procedure that is
known as source stacking. In this paper, we define catalogs of Active Galactic
Nuclei (AGN) and use them to perform a source stacking analysis. The grouping
of AGN into classes is done in two steps: first, AGN classes are defined, then,
sources to be stacked are selected assuming that a potential neutrino flux is
linearly correlated with the photon luminosity in a certain energy band (radio,
IR, optical, keV, GeV, TeV). Lacking any secure detailed knowledge on neutrino
production in AGN, this correlation is motivated by hadronic AGN models, as
briefly reviewed in this paper.
The source stacking search for neutrinos from generic AGN classes is
illustrated using the data collected by the AMANDA-II high energy neutrino
detector during the year 2000. No significant excess for any of the suggested
groups was found.Comment: 43 pages, 12 figures, accepted by Astroparticle Physic
Thrive: Success Strategies for the Modern-Day Faculty Member
The THRIVE collection is intended to help faculty thrive in their roles as educators, scholars, researchers, and clinicians. Each section contains a variety of thought-provoking topics that are designed to be easily digested, guide personal reflection, and put into action. Please use the THRIVE collection to help: Individuals study topics on their own, whenever and wherever they want Peer-mentoring or other learning communities study topics in small groups Leaders and planners strategically insert faculty development into existing meetings
Faculty identify campus experts for additional learning, grand rounds, etc. If you have questions or want additional information on a topic, simply contact the article author or email [email protected]://digitalcommons.unmc.edu/facdev_books/1000/thumbnail.jp
Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research
Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes
The genetic architecture of the human cerebral cortex
INTRODUCTION
The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure.
RATIONALE
To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations.
RESULTS
We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness).
Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness.
To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity.
We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism.
CONCLUSION
This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function
All-sky search for long-duration gravitational wave transients with initial LIGO
We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society
All-sky search for long-duration gravitational wave transients with initial LIGO
We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society
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