Vector meson form factors and their quark-mass dependence

The electromagnetic form factors of vector mesons are calculated in an explicitly Poincar\'e covariant formulation, based on the Dyson--Schwinger equations of QCD, that respects electromagnetic current conservation, and unambiguously incorporates effects from vector meson poles in the quark-photon vertex. This method incorporates a 2-parameter effective interaction, where the parameters are constrained by the experimental values of chiral condensate and $f_{\pi}$. This approach has successfully described a large amount of light-quark meson experimental data, e.g. ground state pseudoscalar masses and their electromagnetic form factors; ground state vector meson masses and strong and electroweak decays. Here we apply it to predict the electromagnetic properties of vector mesons. The results for the static properties of the $\rho$-meson are: charge radius $= 0.54 {\rm fm}^2$, magnetic moment $\mu = 2.01$, and quadrupole moment ${\cal Q} = -0.41$. We investigate the quark mass dependence of these static properties and find that our results at the charm quark mass are in agreement with recent lattice simulations. The charge radius decreases with increasing quark mass, but the magnetic moment is almost independent of the quark mass.Comment: 13 pages, 7 figure

Chiral Extrapolation of Lattice Data for Heavy Meson Hyperfine Splittings

We investigate the chiral extrapolation of the lattice data for the light-heavy meson hyperfine splittings D^*-D and B^*-B to the physical region for the light quark mass. The chiral loop corrections providing non-analytic behavior in m_\pi are consistent with chiral perturbation theory for heavy mesons. Since chiral loop corrections tend to decrease the already too low splittings obtained from linear extrapolation, we investigate two models to guide the form of the analytic background behavior: the constituent quark potential model, and the covariant model of QCD based on the ladder-rainbow truncation of the Dyson-Schwinger equations. The extrapolated hyperfine splittings remain clearly below the experimental values even allowing for the model dependence in the description of the analytic background.Comment: 14 pages, 4 figures, typos corrected, presentation clarifie

Draft Model for Network Information System: Working Paper Series--03-15

This paper presents a model to aid researchers with the task of identifying the elements of a network-based information system in their studies. If the elements are not properly identified, the results of a study may be misinterpreted or lost. The elements of network-based information can be divided into three major categories: Use: people using or benefiting from use of the information system, procedures used by the people, and functional area data; Applications: people developing or maintaining software, development and maintenance procedures, application configuration data, and the applications; Infrastructure: systems personnel, systems procedures, protocols, system data, system software, and hardware. Proper identification of network-based information system elements can make delimiting the study easier and make the results more convincing

Dyson-Schwinger Equations - aspects of the pion

The contemporary use of Dyson-Schwinger equations in hadronic physics is exemplified via applications to the calculation of pseudoscalar meson masses, and inclusive deep inelastic scattering with a determination of the pion's valence-quark distribution function.Comment: 4 pages. Contribution to the Proceedings of ``DPF 2000,'' the Meeting of the Division of Particles and Fields of the American Physical Society, August 9-12, 2000, Department of Physics, the Ohio State University, Columbus, Ohi

Signal words and signal icons in application control and information technology exception messages - Hazard matching and habituation effects: Working paper series--06-05

People often encounter warnings in various life situations. These warnings typically include a variety and combination of signal phrases (e.g., "Deadly") and signal icons (e.g., a skull and cross-bones). Users of information technology (IT) frequently encounter such signal words and icons in "exception messages" that appear on computer screens when the user performs an incorrect action or if a condition could arise that may result in a negative occurrence. For example, in the context of accounting application controls which deal with exposures within specific computer application programs. This paper reports the results of two experiments. The first examines the "arousal strength" associated with various signal words and signal icons that are commonly used in IT exception messages. An elicitation exercise was completed by 316 participants, in which each participant viewed exception messages containing combinations of signal words and signal icons and provided their perception as to the severity of a computer problem communicated by the exception message. The results can be used to achieve "hazard matching," whereby the severity of hazard that is implied by the signal word and icon within the exception message can be matched to the level of the potential hazard faced by the user. The second experiment investigated the factor of habituation and if the negative results of habituation can be overcome through the design of exception messages. A strong habituation effect was found to exist and the effect was also found to be mitigated by altering the signal word and icon combination of an exception message

On The Basis Properties And Convergence Of Expansions In Terms Of Eigenfunctions For A Spectral Problem With A Spectral Parameter In The Boundary Condition

In this paper, we consider the spectral problem − y 00 + q (x) y = λy, 0 < x < 1, y (0) = 0, y0 (0) − dλy (1) = 0, where λ is a spectral parameter, q (x) ∈ L1 (0, 1) is a complex-valued function and d is an arbitrary nonzero complex number. We study the spectral properties ( asymptotic formulae for eigenvalues and eigenfunctions, minimality and basicity of the system of eigenfunctions, the uniform convergence of expansions in terms of eigenfunctions ) of the considered boundary value problem

ADAGSS: Automatic Dataset Generation for Semantic Segmentation

A common issue in medical deep learning research is the creation of dataset for training the neural networks. Medical data collection is also tied-up by privacy laws and even if a lot of medical data are available, often their elaboration can be time demanding. This problem can be avoided using neural networks architectures that can achieve a good predicting precision with few images (e.g. U-Net). In the case of semantic segmentation, the dataset generation is even more cumbersome since it requires the creation of segmentation masks manually. Some automatic ground-truth creation techniques may be employed like filtering, thresholding and Self Organized Maps1 (SOM). These automatic methods can be very powerful and useful, but they always have a bottle-neck phase: data validation. Due to algorithm reliability (that sometimes can fail), data needs to be validated manually before they can be included in a dataset for training. In this work, we propose a method to automatize this phase by moving manual intervention to an easier task: instead of creating masks and then validate them manually, we train a convolutional neural network to classify segmentation quality. Therefore, the validation is performed automatically. An initial manual phase is still required, but the classification task requires a smaller number of elements in the dataset that will feed a network employed for classification. After this phase, similar dataset creations will require less effort. This procedure is based on the fact that to obtain a high classification precision, fewer data are required than the data that are needed to obtain high precision in semantic segmentation. High classification score, can automatize validation procedure in dataset creation, being able to discard failure case in dataset creation. Being able to produce bigger dataset in less time can led to higher precision in semantic segmentation

Valence-quark distributions in the pion

We calculate the pion's valence-quark momentum-fraction probability distribution using a Dyson-Schwinger equation model. Valence-quarks with an active mass of 0.30 GeV carry 71% of the pion's momentum at a resolving scale q_0=0.54 GeV = 1/(0.37 fm). The shape of the calculated distribution is characteristic of a strongly bound system and, evolved from q_0 to q=2 GeV, it yields first, second and third moments in agreement with lattice and phenomenological estimates, and valence-quarks carrying 49% of the pion's momentum. However, pointwise there is a discrepancy between our calculated distribution and that hitherto inferred from parametrisations of extant pion-nucleon Drell-Yan data.Comment: 8 pages, 3 figures, REVTEX, aps.sty, epsfig.sty, minor corrections, version to appear in PR

Toward iconic-based information technology and application control exception messages: Working paper series--07-09

Users of information technology (IT) commonly encounter exception messages during their interactions with application programs. Exception messages are an important element in accounting application controls which address exposures within specific computer application programs such as payroll, sales processing, and cash disbursements. Exception messages are similar in purpose to the warning messages that appear on consumer products and equipment (e.g., cigarettes, power tools, etc.), in various work environments (e.g., around machinery), and on chemicals. This manuscript reviews the normative elements and information that are included in product, chemical, and environment warnings and proposes that these elements and information should also be included in IT and application control exception messages. It is argued that including these elements will increase the effectiveness, informativeness, and consistency of exception messages. Additionally, we report the results of an experiment carried out to determine if IT and application control exception messages designed to conform to the normative elements, by specifically including descriptive icons, improves user interactions. The results of the experiment confirm that user's behavioral compliance increases when interacting with a system that incorporates iconic-based exception messages