New analyticity constraints on the high energy behavior of hadron-hadron cross sections

We here comment on a series of recent papers by Igi and Ishida[K. Igi and M. Ishida, Phys. Lett B 622, 286 (2005)] and Block and Halzen[M. M. Block and F. Halzen, Phys. Rev D 72, 036006 (2005)] that fit high energy $pp$ and $\bar pp$ cross section and $\rho$-value data, where $\rho$ is the ratio of the real to the imaginary portion of the forward scattering amplitude. These authors used Finite Energy Sum Rules and analyticity consistency conditions, respectively, to constrain the asymptotic behavior of hadron cross sections by anchoring their high energy asymptotic amplitudes--even under crossing--to low energy experimental data. Using analyticity, we here show that i) the two apparently very different approaches are in fact equivalent, ii) that these analyticity constraints can be extended to give new constraints, and iii) that these constraints can be extended to crossing odd amplitudes. We also apply these extensions to photoproduction. A new interpretation of duality is given.Comment: 9 pages, 1 postscript figure; redone for clarity, removal of typos, changing reference; figure replace

Proton Polarization Shifts in Electronic and Muonic Hydrogen

The contribution of virtual excitations to the energy levels of electronic and muonic hydrogen is investigated combining a model-independent approach for the main part with quark model predictions for the remaining corrections. Precise values for the polarization shifts are obtained in the long-wavelength dipole approximation by numerically integrating over measured total photoabsorption cross sections. These unretarded results are considerably reduced by including retardation effects in an approximate way since the average momentum transfer (together with the mean excitation energy) turns out to be larger than usually assumed. Transverse and seagull contributions are estimated in a simple harmonic oscillator quark model and found to be non-negligible. Possible uncertainties and improvements of the final results are discussed.Comment: 8 pages, LATEX, no figures, discussion improved and references updated, final version accepted for publication in Phys. Lett.

Human assessments of document similarity

Two studies are reported that examined the reliability of human assessments of document similarity and the association between human ratings and the results of n-gram automatic text analysis (ATA). Human interassessor reliability (IAR) was moderate to poor. However, correlations between average human ratings and n-gram solutions were strong. The average correlation between ATA and individual human solutions was greater than IAR. N-gram length influenced the strength of association, but optimum string length depended on the nature of the text (technical vs. nontechnical). We conclude that the methodology applied in previous studies may have led to overoptimistic views on human reliability, but that an optimal n-gram solution can provide a good approximation of the average human assessment of document similarity, a result that has important implications for future development of document visualization systems

The moderating role of maternal supervision in the social ecology of children's unintentional injuries

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on January 31, 2008)Vita.Thesis (Ph. D.) University of Missouri-Columbia 2007.Unintentional injuries are the leading cause of death for young children in the United States. Gaining a better understanding of the ways in which maternal behaviors relate to children's injuries may help researchers develop effective strategies for preventing childhood injuries. The present study examined whether maternal supervision moderated the relation of child and social-ecological variables (i.e., maternal, intrafamilial, and extrafamilial factors) to children's injuries. The study also examined whether the moderating effects of supervision were due to between-mother differences in typical supervision levels or due to individual mothers' fluctuations in supervision across time periods. Mothers of 170 toddlers were interviewed biweekly about their children's injuries and their supervision over a 6-month period. Supervision interacted with child gender so that higher supervision predicted lower injury severities for boys but not girls. Supervision also interacted with maternal locus of control and marital satisfaction; however, lower supervision appeared to be protective for children. Findings were due to changes in mothers' time-period-specific supervision levels rather than differences between mothers' typical supervision levels.Includes bibliographical reference

Anomalous Payload-Based Network Intrusion Detection

We present a payload-based anomaly detector, we call PAYL, for intrusion detection. PAYL models the normal application payload of network traffic in a fully automatic, unsupervised and very efficient fashion. We first compute during a training phase a profile byte frequency distribution and their standard deviation of the application payload flowing to a single host and port. We then use Mahalanobis distance during the detection phase to calculate the similarity of new data against the pre-computed profile. The detector compares this measure against a threshold and generates an alert when the distance of the new input exceeds this threshold. We demonstrate the surprising effectiveness of the method on the 1999 DARPA IDS dataset and a live dataset we collected on the Columbia CS department network. In once case nearly 100% accuracy is achieved with 0.1% false positive rate for port 80 traffic

Intrinsic Image Popularity Assessment

The goal of research in automatic image popularity assessment (IPA) is to develop computational models that can accurately predict the potential of a social image to go viral on the Internet. Here, we aim to single out the contribution of visual content to image popularity, i.e., intrinsic image popularity. Specifically, we first describe a probabilistic method to generate massive popularity-discriminable image pairs, based on which the first large-scale image database for intrinsic IPA (I$^2$PA) is established. We then develop computational models for I$^2$PA based on deep neural networks, optimizing for ranking consistency with millions of popularity-discriminable image pairs. Experiments on Instagram and other social platforms demonstrate that the optimized model performs favorably against existing methods, exhibits reasonable generalizability on different databases, and even surpasses human-level performance on Instagram. In addition, we conduct a psychophysical experiment to analyze various aspects of human behavior in I$^2$PA.Comment: Accepted by ACM Multimedia 201

Evolving rules for document classification

We describe a novel method for using Genetic Programming to create compact classification rules based on combinations of N-Grams (character strings). Genetic programs acquire fitness by producing rules that are effective classifiers in terms of precision and recall when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from a classification task using the Reuters 21578 dataset. We also suggest that because the induced rules are meaningful to a human analyst they may have a number of other uses beyond classification and provide a basis for text mining applications

A Behavior-Based Approach To Securing Email Systems

The Malicious Email Tracking (MET) system, reported in a prior publication, is a behavior-based security system for email services. The Email Mining Toolkit (EMT) presented in this paper is an offline email archive data mining analysis system that is designed to assist computing models of malicious email behavior for deployment in an online MET system. EMT includes a variety of behavior models for email attachments, user accounts and groups of accounts. Each model computed is used to detect anomalous and errant email behaviors. We report on the set of features implemented in the current version of EMT, and describe tests of the system and our plans for extensions to the set of models

The Elusive p-air Cross Section

For the \pbar p and $pp$ systems, we have used all of the extensive data of the Particle Data Group[K. Hagiwara {\em et al.} (Particle Data Group), Phys. Rev. D 66, 010001 (2002).]. We then subject these data to a screening process, the ``Sieve'' algorithm[M. M. Block, physics/0506010.], in order to eliminate ``outliers'' that can skew a $\chi^2$ fit. With the ``Sieve'' algorithm, a robust fit using a Lorentzian distribution is first made to all of the data to sieve out abnormally high \delchi, the individual i$^{\rm th}$ point's contribution to the total $\chi^2$. The $\chi^2$ fits are then made to the sieved data. We demonstrate that we cleanly discriminate between asymptotic $\ln s$ and $\ln^2s$ behavior of total hadronic cross sections when we require that these amplitudes {\em also} describe, on average, low energy data dominated by resonances. We simultaneously fit real analytic amplitudes to the ``sieved'' high energy measurements of $\bar p p$ and $pp$ total cross sections and $\rho$-values for $\sqrt s\ge 6$ GeV, while requiring that their asymptotic fits smoothly join the the $\sigma_{\bar p p}$ and $\sigma_{pp}$ total cross sections at $\sqrt s=$4.0 GeV--again {\em both} in magnitude and slope. Our results strongly favor a high energy $\ln^2s$ fit, basically excluding a $\ln s$ fit. Finally, we make a screened Glauber fit for the p-air cross section, using as input our precisely-determined $pp$ cross sections at cosmic ray energies.Comment: 15 pages, 6 figures, 2 table,Paper delivered at c2cr2005 Conference, Prague, September 7-13, 2005. Fig. 2 was missing from V1. V3 fixes all figure

Consistent Calculation of the Nucleon Electromagnetic Polarizabilities in Chiral Perturbation Theory Beyond Next-to-Leading Order

We calculate the nucleons' electromagnetic polarizabilities in heavy baryon chiral perturbation theory including all terms to order ${\cal O} (q^4)$. The chiral prediction of the electric polarizabilities for the neutron and the proton are in good agreement with the data. In the case of the magnetic polarizabilities the big positive contribution from the $\Delta(1232)$ resonance is largely cancelled by a non--analytic loop contribution of the $\ln M_\pi$ type. This novel effect helps to understand the rather small empirical value of the nucleons' magnetic polarizability.Comment: 10 pp, TeX, BUTP-93/22 and CRN-93-3