One-Loop Self-Dual and N=4 Super Yang-Mills

We conjecture a simple relationship between the one-loop maximally helicity violating gluon amplitudes of ordinary QCD (all helicities identical) and those of N=4 supersymmetric Yang-Mills (all but two helicities identical). Because the amplitudes in self-dual Yang Mills have been shown to be the same as the maximally helicity violating ones in QCD, this conjecture implies that they are also related to the maximally helicity violating ones of N=4 supersymmetric Yang-Mills. We have an explicit proof of the relation up to the six-point amplitude; for amplitudes with more external legs, it remains a conjecture. A similar conjecture relates amplitudes in self-dual gravity to maximally helicity violating N=8 supergravity amplitudes.Comment: 14 pages, TeX, three figures, two new references adde

EFFICIENT ANALYTIC COMPUTATION OF HIGHER-ORDER QCD AMPLITUDES

We review techniques simplifying the analytic calculation of one-loop QCD amplitudes with many external legs, for use in next-to-leading-order corrections to multi-jet processes. Particularly useful are the constraints imposed by perturbative unitarity, collinear singularities and a supersymmetry-inspired organization of helicity amplitudes. Certain sequences of one-loop helicity amplitudes with an arbitrary number of external gluons have been obtained using these constraints.Comment: Talk given at Beyond the Standard Model IV, December 13-18 1994, Lake Tahoe, CA. Latex, 4 pages, no figures

Checks and cheques : implementing a population health and recall system to improve coverage of patients with diabetes in a rural general practice

Identification of all diabetic patients in the population is essential if diabetic care is to be effective in achieving the targets of the St Vincent Declaration.1 The challenge therefore is to establish population based monitoring and control systems by means of state of the art technology in order to achieve quality assurance in the provision of care for patients with diabetes. 2,3 Disease management receives extensive international support as the most appropriate approach to organising and delivering healthcare for chronic conditions like diabetes.4 This approach is achieved through a combination of guidelines for practice, patient education, consultations and follow up using a planned team approach and a strong focus on continuous quality improvement using information technology. 5,6 The current software (Medical Director) could not easily meet these requirements which led us to adopt a trial of Ferret. In designing this project we used change management7 and the plan, do, study, act cycle8 illustrated in Diagram 1.<br /

Gossip on Weighted Networks

We investigate how suitable a weighted network is for gossip spreading. The proposed model is based on the gossip spreading model introduced by Lind et.al. on unweighted networks. Weight represents "friendship." Potential spreader prefers not to spread if the victim of gossip is a "close friend". Gossip spreading is related to the triangles and cascades of triangles. It gives more insight about the structure of a network. We analyze gossip spreading on real weighted networks of human interactions. 6 co-occurrence and 7 social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks and computer generated networks based on ER, BA, WS models are also investigated. They are found to be quite different than the human interaction networks.Comment: 8 pages, 4 figures, 1 tabl

Observation of enhanced transmission for s-polarized light through a subwavelength slit

Enhanced optical transmission (EOT) through subwavelength apertures is usually obtained for p-polarized light. The present study experimentally investigates EOT for s-polarized light. A subwavelength slit surrounded on each side by periodic grooves has been fabricated in a gold film and covered by a thin dielectric layer. The excitation of s-polarized dielectric waveguide modes inside the dielectric film strongly increases the s-polarized transmission. Transmission measurements are compared with a coupled mode model and show good qualitative agreement. Adding a waveguide can improve light transmission through subwavelength apertures, as both s and p-polarization can be efficiently transmitted.Comment: 11 pages, 3 figures, submitted to Applied Physics Letter

Evolution of Ego-networks in Social Media with Link Recommendations

Ego-networks are fundamental structures in social graphs, yet the process of their evolution is still widely unexplored. In an online context, a key question is how link recommender systems may skew the growth of these networks, possibly restraining diversity. To shed light on this matter, we analyze the complete temporal evolution of 170M ego-networks extracted from Flickr and Tumblr, comparing links that are created spontaneously with those that have been algorithmically recommended. We find that the evolution of ego-networks is bursty, community-driven, and characterized by subsequent phases of explosive diameter increase, slight shrinking, and stabilization. Recommendations favor popular and well-connected nodes, limiting the diameter expansion. With a matching experiment aimed at detecting causal relationships from observational data, we find that the bias introduced by the recommendations fosters global diversity in the process of neighbor selection. Last, with two link prediction experiments, we show how insights from our analysis can be used to improve the effectiveness of social recommender systems.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM 2017), Cambridge, UK. 10 pages, 16 figures, 1 tabl

Efficient Blind-Spot Neural Network Architecture for Image Denoising

Image denoising is an essential tool in computational photography. Standard denoising techniques, which use deep neural networks at their core, require pairs of clean and noisy images for its training. If we do not possess the clean samples, we can use blind-spot neural network architectures, which estimate the pixel value based on the neighbouring pixels only. These networks thus allow training on noisy images directly, as they by-design avoid trivial solutions. Nowadays, the blind-spot is mostly achieved using shifted convolutions or serialization. We propose a novel fully convolutional network architecture that uses dilations to achieve the blind-spot property. Our network improves the performance over the prior work and achieves state-of-the-art results on established datasets