Cognitive Information Processing

Contains reports on six research projects.National Institutes of Health (Grant 5 PO1 GM14940-03)National Institutes of Health (Grant 5 PO1 GM15006-03)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U.S. Air Force) under Contract DA 28-043-AMC-02536(E)National Institutes of Health (Grant 5 TO1 GM01555-03

Properties of continuous Fourier extension of the discrete cosine transform and its multidimensional generalization

A versatile method is described for the practical computation of the discrete Fourier transforms (DFT) of a continuous function $g(t)$ given by its values $g_{j}$ at the points of a uniform grid $F_{N}$ generated by conjugacy classes of elements of finite adjoint order $N$ in the fundamental region $F$ of compact semisimple Lie groups. The present implementation of the method is for the groups SU(2), when $F$ is reduced to a one-dimensional segment, and for $SU(2)\times ... \times SU(2)$ in multidimensional cases. This simplest case turns out to result in a transform known as discrete cosine transform (DCT), which is often considered to be simply a specific type of the standard DFT. Here we show that the DCT is very different from the standard DFT when the properties of the continuous extensions of these two discrete transforms from the discrete grid points $t_j; j=0,1, ... N$ to all points $t \in F$ are considered. (A) Unlike the continuous extension of the DFT, the continuous extension of (the inverse) DCT, called CEDCT, closely approximates $g(t)$ between the grid points $t_j$. (B) For increasing $N$, the derivative of CEDCT converges to the derivative of $g(t)$. And (C), for CEDCT the principle of locality is valid. Finally, we use the continuous extension of 2-dimensional DCT to illustrate its potential for interpolation, as well as for the data compression of 2D images.Comment: submitted to JMP on April 3, 2003; still waiting for the referee's Repor

Measurement of the Top-Quark Mass with Dilepton Events Selected Using Neuroevolution at CDF

We report a measurement of the top-quark mass Mt in the dilepton decay channel tt̄→bl′+νl′b̄l-ν̄l. Events are selected with a neural network which has been directly optimized for statistical precision in top-quark mass using neuroevolution, a technique modeled on biological evolution. The top-quark mass is extracted from per-event probability densities that are formed by the convolution of leading order matrix elements and detector resolution functions. The joint probability is the product of the probability densities from 344 candidate events in 2.0fb-1 of pp̄ collisions collected with the CDF II detector, yielding a measurement of Mt=171.2±2.7(stat)±2.9(syst)GeV/c2

Cognitive Information Processing

Contains research objectives, summary of research and reports on four research projects.National Institutes of Health (Grant 5 PO1 GM14940-02)National Institutes of Health (Grant 5 P01 GM15006-03)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 28-043-AMC-02536(E)National Institutes of Health (Grant 5 T01 GM01555-03

Y-Chromosomal Diversity in Lebanon Is Structured by Recent Historical Events

Lebanon is an eastern Mediterranean country inhabited by approximately four million people with a wide variety of ethnicities and religions, including Muslim, Christian, and Druze. In the present study, 926 Lebanese men were typed with Y-chromosomal SNP and STR markers, and unusually, male genetic variation within Lebanon was found to be more strongly structured by religious affiliation than by geography. We therefore tested the hypothesis that migrations within historical times could have contributed to this situation. Y-haplogroup J∗(xJ2) was more frequent in the putative Muslim source region (the Arabian Peninsula) than in Lebanon, and it was also more frequent in Lebanese Muslims than in Lebanese non-Muslims. Conversely, haplogroup R1b was more frequent in the putative Christian source region (western Europe) than in Lebanon and was also more frequent in Lebanese Christians than in Lebanese non-Christians. The most common R1b STR-haplotype in Lebanese Christians was otherwise highly specific for western Europe and was unlikely to have reached its current frequency in Lebanese Christians without admixture. We therefore suggest that the Islamic expansion from the Arabian Peninsula beginning in the seventh century CE introduced lineages typical of this area into those who subsequently became Lebanese Muslims, whereas the Crusader activity in the 11th–13th centuries CE introduced western European lineages into Lebanese Christians

GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Prediction

We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its main strength is its efficient handling of the input data, enabling learning from large datasets. GENN is built on a two-layered neural network and has the option to use separate inputs–output pairs or window-based data using data structures to efficiently represent input–output pairs. The program was tested on predicting the accessible surface area of globular proteins, scoring proteins according to similarity to native, predicting protein disorder, and has performed remarkably well. In this paper we describe the program and its use. Specifically, we give as an example the construction of a similarity to native protein scoring function that was constructed using GENN. The source code and Linux executables for GENN are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org. Bugs and problems with the GENN program should be reported to EF

Evidence for t\bar{t}\gamma Production and Measurement of \sigma_t\bar{t}\gamma / \sigma_t\bar{t}

Using data corresponding to 6.0/fb of ppbar collisions at sqrt(s) = 1.96 TeV collected by the CDF II detector, we present a cross section measurement of top-quark pair production with an additional radiated photon. The events are selected by looking for a lepton, a photon, significant transverse momentum imbalance, large total transverse energy, and three or more jets, with at least one identified as containing a b quark. The ttbar+photon sample requires the photon to have 10 GeV or more of transverse energy, and to be in the central region. Using an event selection optimized for the ttbar+photon candidate sample we measure the production cross section of, and the ratio of cross sections of the two samples. Control samples in the dilepton+photon and lepton+photon+\met, channels are constructed to aid in decay product identification and background measurements. We observe 30 ttbar+photon candidate events compared to the standard model expectation of 26.9 +/- 3.4 events. We measure the ttbar+photon cross section to be 0.18+0.08 pb, and the ratio of the cross section of ttbar+photon to ttbar to be 0.024 +/- 0.009. Assuming no ttbar+photon production, we observe a probability of 0.0015 of the background events alone producing 30 events or more, corresponding to 3.0 standard deviations.Comment: 9 pages, 3 figure

Precision Top-Quark Mass Measurements at CDF

We present a precision measurement of the top-quark mass using the full sample of Tevatron $\sqrt{s}=1.96$ TeV proton-antiproton collisions collected by the CDF II detector, corresponding to an integrated luminosity of 8.7 $fb^{-1}$. Using a sample of $t\bar{t}$ candidate events decaying into the lepton+jets channel, we obtain distributions of the top-quark masses and the invariant mass of two jets from the $W$ boson decays from data. We then compare these distributions to templates derived from signal and background samples to extract the top-quark mass and the energy scale of the calorimeter jets with {\it in situ} calibration. The likelihood fit of the templates from signal and background events to the data yields the single most-precise measurement of the top-quark mass, \mtop = 172.85 \pm$0.71 (stat)$\pm$0.85 (syst) GeV/c^{2}.$Comment: submitted to Phys. Rev. Let