Electromagnetic Corrections to Charged Pion Scattering at Low Energies

The electromagnetic corrections to the low energy scattering amplitude involving charged pions only are investigated at leading and next-to-leading orders in the two-flavour chiral expansion. As an application, the corresponding variation in the strong $2S-2P$ level shift is evaluated. The relative variation is of the order of 5%.Comment: LateX2e, 10 pages, 2 figure

Information Requirements for MCM and ISR Missions : PUMA Phase II

This document contains display requirements for Littoral Combat Ship (LCS) control station displays to be used by unmanned vehicle units in support of heterogeneous unmanned vehicle missions (such as Special Operations Force (SOF) insertion). The method used for generating the requirements was that of a Hybrid Cognitive Task Analysis (CTA)1 which entails describing a scenario overview of a representative mission, generating event flow diagrams, and depicting decision ladders for the key decisions identified in the event flow diagrams. These steps are then used together to generate an informational requirements summary which includes the situational awareness requirements that are derived from the event flow and display requirements of the decision ladders. This method was developed in Phase I of the PUMA (Plan Understanding for Mixed-initiative control of Autonomous systems) project2. In PUMA I, the mission scenario primarily consisted of Intelligence, Surveillance and Reconnaissance (ISR) tasks. For PUMA II, the scenario has been expanded to include Mine Counter Measures (MCM), Harbor Bottom Image-Mapping (HBI), and Anti- Terrorism / Force Protection (AT/FP) mission types. There is a specific emphasis on the MCM and ISR missions to highlight the informational requirement differences between the two task types. This document incorporates the expanded vehicle and mission type heterogeneities that are present in PUMA II in order to develop a cohesive set of informational requirements necessary for such a complex mission.Prepared for Charles River Analytic

Isospin-Breaking quark condensates in Chiral Perturbation Theory

We analyze the isospin-breaking corrections to quark condensates within one-loop SU(2) and SU(3) Chiral Perturbation Theory including $m_u\neq m_d$ as well as electromagnetic (EM) contributions. The explicit expressions are given and several phenomenological aspects are studied. We analyze the sensitivity of recent condensate determinations to the EM low-energy constants (LEC). If the explicit chiral symmetry breaking induced by EM terms generates a ferromagnetic-like response of the vacuum, as in the case of quark masses, the increasing of the order parameter implies constraints for the EM LEC, which we check with different estimates in the literature. In addition, we extend the sum rule relating quark condensate ratios in SU(3) to include EM corrections, which are of the same order as the $m_u\neq m_d$ ones, and we use that sum rule to estimate the vacuum asymmetry within ChPT. We also discuss the matching conditions between the SU(2) and SU(3) LEC involved in the condensates, when both isospin-breaking sources are taken into account.Comment: 16 pages, 1 figure, final version accepted for publication in Journal of Physics

Randomised study of the effects of fluoride and time on in situ remineralisation of acid-softened enamel

Objectives This single-centre, randomised, crossover study used a short-term in situ dental erosion remineralisation model to explore the remineralisation of acid-softened enamel in the 4-h period immediately following brushing with an anti-erosion, dentin hypersensitivity test dentifrice containing 1150 ppm fluoride (as sodium fluoride [NaF]) or a placebo dentifrice with no fluoride. Materials and methods Fifty participants wearing a palatal appliance holding surface-softened bovine enamel specimens brushed their natural teeth with their assigned dentifrice. Specimens were removed at 5-, 10-, 15-, 30-, 60-, 120- and 240-min post brushing. Enamel remineralisation effect was evaluated at each timepoint by percent surface microhardness recovery (%SMHR) and enamel fluoride uptake (EFU). After a second in vitro erosive challenge, the percent relative erosion resistance (%RER) was calculated. Results Statistically significant differences in %SMHR were observed for the test dentifrice compared with the placebo dentifrice from the 60-min timepoint onwards (all p < 0.02; mean difference of 8.66 [95% CI 3.46, 13.87] at 60 min). At each specimen removal time, %RER and EFU were statistically significantly higher for the test dentifrice compared with the placebo dentifrice (p < 0.0001 for all). No treatment-related or serious adverse events were reported. Conclusions The NaF-containing anti-erosion, dentin hypersensitivity dentifrice improved remineralisation of acid-softened enamel starting at 60 min of intra-oral exposure. It also improved enamel erosion resistance and fluoride uptake as early as 5 min after exposure to fluoridated dentifrice slurry

One Work Analysis, Two Domains: A Display Information Requirements Case Study

Work domain analyses can be time consuming, requiring extensive interviews, documentation review, and observations, among other techniques. Given the time and resources required, we examine how to generalize a work domain analysis technique, namely the hybrid Cognitive Task Analysis (hCTA) method across two domains in order to generate a common set of display information requirements. The two domains of interest are field workers troubleshooting low voltage distribution networks and telecommunication problems. Results show that there is a high degree of similarity between the two domains due to their service call nature, particularly in tasking and decision-making. While the primary differences were due to communication protocols and equipment requirements, the basic overall mission goals, functions, phases of operation, decision processes, and situation requirements were very similar. A final design for both domains is proposed based on the joint requirements

CaDIS: Cataract dataset for surgical RGB-image segmentation

Video feedback provides a wealth of information about surgical procedures and is the main sensory cue for surgeons. Scene understanding is crucial to computer assisted interventions (CAI) and to post-operative analysis of the surgical procedure. A fundamental building block of such capabilities is the identification and localization of surgical instruments and anatomical structures through semantic segmentation. Deep learning has advanced semantic segmentation techniques in the recent years but is inherently reliant on the availability of labelled datasets for model training. This paper introduces a dataset for semantic segmentation of cataract surgery videos complementing the publicly available CATARACTS challenge dataset. In addition, we benchmark the performance of several state-of-the-art deep learning models for semantic segmentation on the presented dataset. The dataset is publicly available at https://cataracts-semantic-segmentation2020.grand-challenge.org/

Can surgical simulation be used to train detection and classification of neural networks?

Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems

Development and Evaluation of a Trapping System for Anoplophora glabripennis (Coleoptera: Cerambycidae) in the United States

Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae), commonly known as the Asian longhorned beetle, is an invasive wood-boring pest that infests a number of hardwood species and causes considerable economic losses in North America, several countries in Europe, and in its native range in Asia. The success of eradication efforts may depend on early detection of introduced populations; however, detection has been limited to identification of tree damage (oviposition pits and exit holes), and the serendipitous collection of adults, often by members of the public. Here we describe the development, deployment, and evaluation of semiochemical-baited traps in the greater Worcester area in Massachusetts. Over 4 yr of trap evaluation (2009-2012), 1013 intercept panel traps were deployed, 876 of which were baited with three different families of lures. The families included lures exhibiting different rates of release of the male-produced A. glabripennis pheromone, lures with various combinations of plant volatiles, and lures with both the pheromone and plant volatiles combined. Overall, 45 individual beetles were captured in 40 different traps. Beetles were found only in traps with lures. In several cases, trap catches led to the more rapid discovery and management of previously unknown areas of infestation in the Worcester county regulated area. Analysis of the spatial distribution of traps and the known infested trees within the regulated area provides an estimate of the relationship between trap catch and beetle pressure exerted on the traps. Studies continue to optimize lure composition and trap placemen