Colour-Kinematics Duality for One-Loop Rational Amplitudes

Colour-kinematics duality is the conjecture of a group theory-like structure for the kinematic dependence of scattering amplitudes in gauge theory and gravity. This structure has been verified at tree level in various ways, but similar progress has been lacking at loop level, where the power of the duality would be most significant. Here we explore colour-kinematics duality at one loop using the self-dual sector as a starting point. The duality is shown to exist in pure Yang-Mills theory for two infinite classes of amplitudes: amplitudes with any number of particles either all of the same helicity or with one particle helicity opposite the rest. We provide a simple Lagrangian-based argument in favour of the double copy relation between gauge theory and gravity amplitudes in these classes, and provide some explicit examples. We further discuss aspects of the duality which persist after integration, leading to relations among partial amplitudes. Finally, we describe form factors in the self-dual theory at tree level which also satisfy the duality.Comment: 36 pages, 5 figures; v2: published versio

New relations for scattering amplitudes in Yang-Mills theory at loop level

The calculation of scattering amplitudes in Yang-Mills theory at loop level is important for the analysis of background processes at particle colliders as well as our understanding of perturbation theory at the quantum level. We present tools to derive relations for especially one loop amplitudes, as well as several explicit examples for gauge theory coupled to a wide variety of matter. These tools originate in certain scaling behavior of permutation and cyclic sums of Yang-Mills tree amplitudes and loop integrands. In the latter case evidence exists for relations at all loop orders.Comment: 12 pages, 4 figures. v3: typos corrected, figures and clarifications adde

Rain volume estimation over areas using satellite and radar data

The analysis of 18 convective clusters demonstrates that the extension of the Area-Time-Integral (ATI) technique to the use of satellite data is possible. The differences of the internal structures of the radar reflectivity features, and of the satellite features, give rise to differences in estimating rain volumes by delineating area; however, by focusing upon the area integrated over the lifetime of the storm, it is suggested that some of the errors produced by the differences in the cloud geometries as viewed by radar or satellite are minimized. The results are good and future developments should consider data from different climatic regions and should allow for implementation of the technique in a general circulation model

Design and Fabrication of a Prototype Coupler Component to Facilitate the Concurrent Collection of Mixing Chamber and Breath-By-Breath Metabolic Measurements

Metabolic measurements are often a critical element of sports and exercise science research efforts, and numerous different systems are available for taking these measurements both in laboratory settings and outside of the laboratory environment. Laboratory-based mixing chamber systems, such as the Parvomedics TrueOne 2400, and portable breath-by-breath systems, such as the Cosmed Kb42, are extremely effective and widely used systems for taking metabolic measurements that have their own distinct strengths and weaknesses. Researchers in the Department of Kinesiology at Seattle University are interested in collecting data on research subjects using the both the TrueOne and Kb42 systems concurrently in the interest of better understanding the relationship between these two systems and in order to take advantage of both systems’ inherent strengths. The collection of data using these two systems concurrently has not been reported in the literature to date, and thus components and equipment for coupling these two metabolic measurement systems in an effective way does not exist. Researchers in the Mechanical Engineering Department at Seattle University approach this component issues as a mechanical design problem. Over the course of numerous design iterations involving computer 2 aided design tools and 3D printing, an effective coupling component was developed and prototyped. Preliminary qualitative results observed suggest that the coupler is functioning as desired, and that the coupler designed by mechanical engineering researchers has the potential to collect novel sports and exercise data and that the coupled system allowing for simultaneous mixing chamber and breath-by-breath data collection merits further study

Common Loons Respond Adaptively to a Black Fly that Reduces Nesting Success

Nesting birds must often cope with harassment from biting insects, but it is difficult to ascertain what effect such pests might have on breeding success and population dynamics. We tested the hypothesis that a black fly (Simulium annulus) that feeds on the blood of nesting Common Loons (Gavia immer) causes nest abandonment in this charismatic diving bird. In addition, we measured effects of fly-induced abandonment on a loon population, and examined potential predictors of fly abundance and nest abandonment. We also tested a second hypothesis, which holds that loon pairs that abandon a nest owing to flies should often remain at the site for their subsequent nesting attempt, since fly outbreaks last only 1–2 weeks. All predictions of the fly-induced abandonment hypothesis were supported, including strong correlations between fly counts and rate of abandonment, reduced incubation during severe fly years, and increased abandonment during cool springs, which promote longevity of the flies. The correlation between nest abandonment and population breeding success suggests that S. annulus reduced the chick fledging rate by as much as 23% in a year of severe infestation. Fly numbers on loons and their nests were highest when temperatures were high and winds were light. Surprisingly, however, exposure to the prevailing wind increased, not decreased, nest abandonment, perhaps because of wave action. Lake size was inversely and female age directly correlated with abandonment rate, possibly due to food limitation in small lakes and senescence of females, respectively. Finally, pairs that abandoned a first nest renested at the same site with much greater frequency than did pairs that lost eggs to a predator, indicating that loons are capable of responding adaptively to a cause of nest failure that is time- but not space-dependent

Dimethylaminomethylene-α-D-xylo-hept-5-ulofuranurononitrile as building block in the synthesis of 'reversed' C-nucleoside analogues

3-O-Benzyl-6-deoxy-1,2-O-isopropylidene-6-(dimethylaminomethylene) -α-D-xylo-hept-5-ulofuranurononitrile (1) was reacted with amidinium salts, S-methylisothiouronium sulfate, and guanidinium chloride, respectively, in the presence of bases to furnish the 4-(3-O-benzyl-1,2-O-isopropylidene- α-D-xylo-tetrofuranos-4-yl)pyrimidine-5-carbonitriles 2 and the 4-(1,2-O-isopropylidene-α-D-glycero-tetr-3-enofuranos-4-yl) pyrimidine-5-carbonitriles 3, respectively. Treatment of 1 with ethyl 5-aminopyrazole-4-carboxylates yielded the ethyl 7-(3-O-benzyl-1,2-O- isopropylidene-α-D-xylo-tetrofuranos-4-yl)-6-cyanopyrazolo[1,5-a] pyrimidine-3-carboxylates 4 and the ethyl 7-amino-6-(3-O-benzyl-1,2-O- isopropylidene-α-D-xylo-pentofuranuronoyl)pyrazolo[1,5-a] pyrimidine-3-carboxylates 5, respectively. Reaction of 1 with 2-benzimidazolylacetonitrile in the presence of sodium methanolate afforded 1-amino-2-(3-O-benzyl-1,2-O-isopropylidene-α-D-xylo-pentofuranuronoyl) benzo[4,5]imidazo[1,2-a]pyridine-4-carbonitrile (6) and 1-amino-2-(3-deoxy-1,2- O-isopropylidene-α-D-glycero-pent-S-enofuranuronoyl)benzo[4,5]imidazo[1, 2-a]pyridine-4-carbonitrile (7). © 2006 Verlag der Zeitschrift für Naturforschung

Learning ‘‘graph-mer’’ Motifs that Predict Gene Expression Trajectories in Development

A key problem in understanding transcriptional regulatory networks is deciphering what cis regulatory logic is encoded in gene promoter sequences and how this sequence information maps to expression. A typical computational approach to this problem involves clustering genes by their expression profiles and then searching for overrepresented motifs in the promoter sequences of genes in a cluster. However, genes with similar expression profiles may be controlled by distinct regulatory programs. Moreover, if many gene expression profiles in a data set are highly correlated, as in the case of whole organism developmental time series, it may be difficult to resolve fine-grained clusters in the first place. We present a predictive framework for modeling the natural flow of information, from promoter sequence to expression, to learn cis regulatory motifs and characterize gene expression patterns in developmental time courses. We introduce a cluster-free algorithm based on a graph-regularized version of partial least squares (PLS) regression to learn sequence patterns—represented by graphs of k-mers, or “graph-mers”—that predict gene expression trajectories. Applying the approach to wildtype germline development in Caenorhabditis elegans, we found that the first and second latent PLS factors mapped to expression profiles for oocyte and sperm genes, respectively. We extracted both known and novel motifs from the graph-mers associated to these germline-specific patterns, including novel CG-rich motifs specific to oocyte genes. We found evidence supporting the functional relevance of these putative regulatory elements through analysis of positional bias, motif conservation and in situ gene expression. This study demonstrates that our regression model can learn biologically meaningful latent structure and identify potentially functional motifs from subtle developmental time course expression data

Temporal updating scheme for probabilistic neural network with application to satellite cloud classification

Includes bibliographical references.In cloud classification from satellite imagery, temporal change in the images is one of the main factors that causes degradation in the classifier performance. In this paper, a novel temporal updating approach is developed for probabilistic neural network (PNN) classifiers that can be used to track temporal changes in a sequence of images. This is done by utilizing the temporal contextual information and adjusting the PNN to adapt to such changes. Whenever a new set of images arrives, an initial classification is first performed using the PNN updated up to the last frame while at the same time, a prediction using Markov chain models is also made based on the classification results of the previous frame. The results of both the old PNN and the predictor are then compared. Depending on the outcome, either a supervised or an unsupervised updating scheme is used to update the PNN classifier. Maximum likelihood (ML) criterion is adopted in both the training and updating schemes. The proposed scheme is examined on both a simulated data set and the Geostationary Operational Environmental Satellite (GOES) 8 satellite cloud imagery data. These results indicate the improvements in the classification accuracy when the proposed scheme is used.This work was supported by the Department of Defense under the Contract DAAH04 94 G0420

Matching for Several Sparse Nominal Variables in a Case-Control Study of Readmission Following Surgery.

Matching for several nominal covariates with many levels has usually been thought to be difficult because these covariates combine to form an enormous number of interaction categories with few if any people in most such categories. Moreover, because nominal variables are not ordered, there is often no notion of a close substitute when an exact match is unavailable. In a case-control study of the risk factors for read-mission within 30 days of surgery in the Medicare population, we wished to match for 47 hospitals, 15 surgical procedures grouped or nested within 5 procedure groups, two genders, or 47 × 15 × 2 = 1410 categories. In addition, we wished to match as closely as possible for the continuous variable age (65-80 years). There were 1380 readmitted patients or cases. A fractional factorial experiment may balance main effects and low-order interactions without achieving balance for high-order interactions. In an analogous fashion, we balance certain main effects and low-order interactions among the covariates; moreover, we use as many exactly matched pairs as possible. This is done by creating a match that is exact for several variables, with a close match for age, and both a near-exact match and a finely balanced match for another nominal variable, in this case a 47 × 5 = 235 category variable representing the interaction of the 47 hospitals and the five surgical procedure groups. The method is easily implemented in R