An Unpublished Act of David II, 1359

This is a transcription, translation and commentary on an overlooked act of David II of Scotland from a 1359 treaty of alliance with France

Planetary Candidates Observed by Kepler VI: Planet Sample from Q1-Q16 (47 Months)

\We present the sixth catalog of Kepler candidate planets based on nearly 4 years of high precision photometry. This catalog builds on the legacy of previous catalogs released by the Kepler project and includes 1493 new Kepler Objects of Interest (KOIs) of which 554 are planet candidates, and 131 of these candidates have best fit radii <1.5 R_earth. This brings the total number of KOIs and planet candidates to 7305 and 4173 respectively. We suspect that many of these new candidates at the low signal-to-noise limit may be false alarms created by instrumental noise, and discuss our efforts to identify such objects. We re-evaluate all previously published KOIs with orbital periods of >50 days to provide a consistently vetted sample that can be used to improve planet occurrence rate calculations. We discuss the performance of our planet detection algorithms, and the consistency of our vetting products. The full catalog is publicly available at the NASA Exoplanet Archive.Comment: 18 pages, to be published in the Astrophysical Journal Supplement Serie

Sequencing of the Sea Lamprey (Petromyzon marinus) Genome Provides Insights into Vertebrate Evolution

Lampreys are representatives of an ancient vertebrate lineage that diverged from our own ∼500 million years ago. By virtue of this deeply shared ancestry, the sea lamprey (P. marinus) genome is uniquely poised to provide insight into the ancestry of vertebrate genomes and the underlying principles of vertebrate biology. Here, we present the first lamprey whole-genome sequence and assembly. We note challenges faced owing to its high content of repetitive elements and GC bases, as well as the absence of broad-scale sequence information from closely related species. Analyses of the assembly indicate that two whole-genome duplications likely occurred before the divergence of ancestral lamprey and gnathostome lineages. Moreover, the results help define key evolutionary events within vertebrate lineages, including the origin of myelin-associated proteins and the development of appendages. The lamprey genome provides an important resource for reconstructing vertebrate origins and the evolutionary events that have shaped the genomes of extant organisms

Feasibility of preoperative chemotherapy for locally advanced, operable colon cancer: The pilot phase of a randomised controlled trial

Summary: Background Preoperative (neoadjuvant) chemotherapy and radiotherapy are more eff ective than similar postoperative treatment for oesophageal, gastric, and rectal cancers, perhaps because of more eff ective micrometastasis eradication and reduced risk of incomplete excision and tumour cell shedding during surgery. The FOxTROT trial aims to investigate the feasibility, safety, and effi cacy of preoperative chemotherapy for colon cancer. Methods In the pilot stage of this randomised controlled trial, 150 patients with radiologically staged locally advanced (T3 with ≥5 mm invasion beyond the muscularis propria or T4) tumours from 35 UK centres were randomly assigned (2:1) to preoperative (three cycles of OxMdG [oxaliplatin 85 mg/m², l-folinic acid 175 mg, fl uorouracil 400 mg/m² bolus, then 2400 mg/m² by 46 h infusion] repeated at 2-weekly intervals followed by surgery and a further nine cycles of OxMdG) or standard postoperative chemotherapy (12 cycles of OxMdG). Patients with KRAS wild-type tumours were randomly assigned (1:1) to receive panitumumab (6 mg/kg; every 2 weeks with the fi rst 6 weeks of chemotherapy) or not. Treatment allocation was through a central randomisation service using a minimised randomisation procedure including age, radiological T and N stage, site of tumour, and presence of defunctioning colostomy as stratifi cation variables. Primary outcome measures of the pilot phase were feasibility, safety, and tolerance of preoperative therapy, and accuracy of radiological staging. Analysis was by intention to treat. This trial is registered, number ISRCTN 87163246. Findings 96% (95 of 99) of patients started and 89% (85 of 95) completed preoperative chemotherapy with grade 3–4 gastrointestinal toxicity in 7% (seven of 94) of patients. All 99 tumours in the preoperative group were resected, with no signifi cant diff erences in postoperative morbidity between the preoperative and control groups: 14% (14 of 99) versus 12% (six of 51) had complications prolonging hospital stay (p=0·81). 98% (50 of 51) of postoperative chemotherapy patients had T3 or more advanced tumours confi rmed at post-resection pathology compared with 91% (90 of 99) of patients following preoperative chemotherapy (p=0·10). Preoperative therapy resulted in signifi cant downstaging of TNM5 compared with the postoperative group (p=0·04), including two pathological complete responses, apical node involvement (1% [one of 98] vs 20% [ten of 50], p<0·0001), resection margin involvement (4% [ four of 99] vs 20% [ten of 50], p=0·002), and blinded centrally scored tumour regression grading: 31% (29 of 94) vs 2% (one of 46) moderate or greater regression (p=0·0001). Interpretation Preoperative chemotherapy for radiologically staged, locally advanced operable primary colon cancer is feasible with acceptable toxicity and perioperative morbidity. Proceeding to the phase 3 trial, to establish whether the encouraging pathological responses seen with preoperative therapy translates into improved long-term oncological outcome, is appropriate

Multi-scale path planning for reduced environmental impact of aviation

A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year

Convective Weather Avoidance Modeling in Low-Altitude Airspace

Thunderstorms are a leading cause of delay in the National Airspace System (NAS), and significant research has been conducted to predict the areas pilots will avoid during a storm. An example of such research is the Convective Weather Avoidance Model (CWAM), which provides the likelihood of pilot deviation due to convective weather in a given area. This paper extends the scope of CWAM to include low-altitude flights, which typically occur below the tops of convective weather and have slightly different operational constraints. In general, the set of low-altitude flights includes short-hop routes and low-altitude escape routes used to reduce the impact of convective weather in the terminal area. This paper will discuss the classification procedure, present the performance of low-altitude CWAM on observed and forecasted weather, analyze areas of poor performance, and suggest potential improvements to the model. I. Introduction ONVECTIVE weather is a significant impediment to effective and efficient Air Traffic Management (ATM) decisions, and sometimes results in unnecessary delays to the National Airspace System (NAS). In the NAS, 70% of delays are caused by weather, and of those delays, 60% are specifically accounted for by convective weather [1]. Currently, rerouting decisions made by air traffic managers are aided by weather products such as the Corridor Integrated Weather System (CIWS) and the National Convective Weather Forecast (NCWF) [2, 3]. In a Next Generation ATM system, decision support tools such as the Route Availability Planning Tool (RAPT) will mitigate weather-induced delays by supplementing the situational awareness of an air traffic manager with a forecast of the availability of specific flight routes [4]. RAPT is based on the Convective Weather Avoidance Model (CWAM), which is a probabilistic model of pilot decision making in the presence of convective weather [5]. CWAM is a tool originally developed for the en route flight regime to predict pilot deviation decisions by correlating in-flight deviations of aircraft to the weather features they encounter. The model is based on a database comprised of the deviation decision of each flight and weather statistics along each route, which are obtained from CIWS. Pattern classification experiments on the en route CWAM database show that the most descriptive predictors for deviation are related to echo top height, where the most descriptive is the difference in altitude between the aircraft and the echo top height [5]. In the terminal area, deviations are predicted with a different set of features. Several studies of the Dallas and Memphis areas using weather information from the Integrated Terminal Weather System (ITWS) show that deviation decisions are closely related to the radar intensity of the storm and the proximity of the aircraft to the airport [6, 7]. This paper presents the development of a low-altitude version of CWAM which is based on a database composed of weather encounters that occur during level flight between FL100 and FL240. This model is applicable to jet traffic that uses low altitude air routes to „escape‟ from terminal areas when weather or volume congestion impacts lead to constraints on high-altitude airspace, or to low-altitude flight by regional jets on „short hop‟ routes. Such traffic is common in major metroplex airspaces. In this analysis, flight trajectories are obtained from the Enhanced Traffic Management System (ETMS) database, and weather data are acquired from CIWS for 23 convective weather days across two geographical regions (Chicago and New York). A Gaussian classifier is used to determine a set of deviation predictors and the results are tested on observed and forecasted data. The predictor performance is compared to the existing terminal departure CWAM used in RAPT, and the differences are discussed

Air Traffic Decision Analysis During Convective Weather Events in Arrival Airspace

Decision making during convective weather events in the terminal area is shared among pilots and air traffic management, where uninformed decisions can result in wide-spread cascading delays with high-level impacts. Future traffic management systems capable of predicting terminal impacts will mitigate these unnecessary delays; however in order to realize this vision, it is important to understand the decision mechanisms behind convective weather avoidance. This paper utilizes an arrival adaptation of the Convective Weather Avoidance Model (CWAM) to investigate the catalysts for arrival traffic management decision making. The analysis is broken down by category of terminal airspace structure in addition to the type of decision. The results show that pilot behavior in convective weather is heavily dependent on the terminal airspace structure. In addition, pilot and air traffic management decisions in convective weather can be discriminated with large-scale weather features. I. Introductio

Evaluation of the Convective Weather Avoidance Model for Arrival Traffic

The effective management of traffic flows during convective weather events in congested air space requires decision support tools that can translate weather information into anticipated air traffic operational impact. In recent years, MIT Lincoln Laboratory has been maturing the Convective Weather Avoidance Model (CWAM) to correlate pilot behavior in the enroute airspace with observable weather parameters from convective weather forecast systems. This paper evaluates the adaptation of the CWAM to terminal airspace with a focus on arrival decision making. The model is trained on data from five days of terminal convective weather impacts. The performance of the model is evaluated on an independent dataset consisting of six days of convective weather over a variety of terminal areas. Model performance in different terminal areas is discussed and the sensitivity of prediction accuracy to weather forecast horizon is presented. I. Introduction future air traffic system capable of predicting convective weather impacts and proactively issuing TMIs will more effectively use the available airspace, and in turn mitigate the effect of convective weather on the system. The Convective Weather Avoidance Model (CWAM) is a probabilistic model of pilot decision making in the presence of convective weather. CWAM is based on the correlation of spatially filtered weather observations with trajectories of aircraft that penetrated or avoided areas of convective weather in the en route flight regime [1]. The output of the en route CWAM is a three-dimensional {cloud tops, flight altitude, precipitation intensity} Weather Avoidance Field (WAF) that provides the likelihood that a pilot will deviate at a specific position and time given the current and forecasted weather. Outside of the en route phase (e.g. during departure and arrival), aircraft are commonly below the tops of most convection and are subject to different decision mechanisms, both of which are not modeled in the original CWAM. Therefore, in order to model impacts over an entire flight trajectory, CWAM should be adapted to include low-altitude flight phases such as arrival and departure [2]. This paper presents an evaluation of the adaptation of CWAM for arrival operations. Arrival CWAM is trained on approximately 11,000 flights and 1,900 terminal weather encounters over five convective weather days [3]. The training database includes multiple types of weather avoidance decisions that occur during arrival operations to four major metroplex areas (ORD, DFW, CLT, DEN). The decisions types distinguish between strategic and tactical time horizons and encompass both pilot and air traffic management decisions. Additionally, unlike pilots in en route airspace who may have an option to fly at higher altitudes over storms, pilots in arrival airspace are constrained to follow descending trajectories that are typically below the cloud tops. For this reason, the output of the arrival CWAM is a two-dimensional WAF {precipitation intensity, cloud tops}. The performance of arrival CWAM is evaluated by an independent dataset, where the sensitivity of the model to terminal airspace structure and weather forecast horizon are investigated. The independent dataset contains weather decisions from six convective weather days in a variety of terminal areas (ORD, DFW, DEN, CLT, BOS, JFK/LGA/EWR, DCA/IAD). The most descriptive features of pilot avoidance of convective weather are precipitation intensity and storm height, where a 4 km spatial filter on the 90 th percentile value of each feature corresponds to the best tradeoff between probability of detection and false alarm rate.The performance of the mode

Engaging first year students in collaborative learning through practical applications : walking the walk or just talking the talk?

Collaborative partnerships enable humans to harness synergies that exponentially multiply the value of individual contributions. In the context of learning environments. collaborative partnerships can transform ordinary learning experiences into dynamic relationships. culminating in powerful. synergistic accomplishments (Saltiel. 1998), This paper examines the effectiveness of a course offered at Central Queensland University in encouraging learning networks and engaging students in collaborative learning. EDEDl1354 Networks and Partnerships is a first year course in the Bachelor of Learning Management. The aim of the course is to provide students with the fundamental concepts for understanding and implementing partnership and network practices and to participate in a range of authentic experiences including a community project that enables students to plan. implement and reflect on communication processes and collaborative team skills. The project task requires that students work col/aboratively in groups to actively explore existing partnerships in a learning site or community organisation. This involves communicating and liaising with relevant stakeholders to identify ways of enhancing and promoting effective partnerships (Central Queensland University, 2005a). This paper reports on feedback gathered from a sample of students. via an online survey, on whether as a result of the collaborative learning task. the learning experience transformed into a dynamic, powerful outcome and how this feedback might be used to improve future learning outcomes