TOLERANCE INTERVALS FOR GENE FLOW RATES FROM TRANSGENIC TO NON-TRANSGENIC WHEAT AND CORN USING A LOGISTIC REGRESSION MODEL WITH RANDOM LOCATION EFFECTS

Crop scientists and government regulators are interested in mediating pollen flow from transgenic crops to other crops and weed species. To this end, a multi-year, multilocation series of experiments was conducted in eastern Colorado by the Department of Soil and Crop Sciences at Colorado State University. These experiments were done to estimate the distance required between plots of transgenic corn and wheat and plots of the respective non-transgenic crop to obtain at most a regulated limit of cross-pollination. The experiments involved planting a rectangle of transgenic crop in the middle of a non-transgenic field and measuring the proportion of cross-pollinated crop at various distances along transects radiating in multiple directions. Gene flow to the non-transgenic crop was evaluated in wheat using herbicide tolerance and in corn using kernel color. An initial Generalized Linear Mixed Model with binomial response and logit link was estimated with independent variables: a square root transformation of distance, an additional covariate, and a random location effect. For corn, the additional covariate was transect orientation; for wheat, it was the relative heading time of the recipient variety. An enhanced model that included additional sources of variation was also examined. The analysis for both of these assumed models addresses two problems: 1) an Upper Tolerance Limit on the binomial probability of cross-pollination, which includes 100c% of the locations with 100d% confidence, at set values of the independent variables; and 2) an Upper Tolerance Limit on the distance at which 100c% of the locations will have binomial probability of cross-pollination less than a specified value, with 100d% confidence, at set values of the other independent variables. The problems are addressed using Frequentist and Bayesian methods

Hidden diversity of allogromiid foraminiferans in low-latitude environments

Abstrac

Civil and Mechanical Engineering Students Learning Mechanics in a Multidisciplinary Engineering Foundation Spiral

This paper describes how mechanical and civil engineering students are introduced to and develop an understanding of mechanics concepts through a sequence of integrated courses as part of a new curriculum taken during the freshman and sophomore years. The Multi- Disciplinary Engineering Foundation Spiral is a four-semester sequence of engineering courses, matched closely with the development of students’ mathematical sophistication and analytical capabilities and integrated with course work in the sciences. Students develop a conceptual understanding of engineering basics in this series of courses, which stress practical applications of these principles. Mechanics concepts are introduced in a pair of first year courses, EAS107P, Project-Based Introduction to Engineering and EAS112, Methods of Engineering Analysis. During the second year, students’ understanding of these concepts is further developed in three courses, two offered during the fall semester, EAS211, Introduction to Modeling of Engineering Systems and EAS213, Materials in Engineering Systems and one during the spring semester, EAS222, Fundamentals of Mechanics and Materials. In the third semester of discipline specific classes, ME300 Rigid Body Dynamics and CE312 Structural Analysis for mechanical and civil engineering respectively, students are evaluated compared to their peers who have either transferred in from other universities or taken a previous traditional sequence of mechanics courses. The first course, EAS107P, introduces students to concepts related to structural systems and trusses, such as internal and external forces, reactions, compression and tension. This is done in the context of a team project in which students gain a qualitative understanding of these concepts using computer simulation models. In the second course EAS112, students use computer tools such as spreadsheets to solve problems including the analysis of trusses. Mechanics of materials are explored as students use spreadsheets to analyze tensile test properties. In the second year, resolution of forces is further developed in EAS211 as students use force balances to solve various statics problems. Students study the properties, behavior and application of materials in EAS213, including discussion of such concepts as torsion, compression, tension, fatigue, creep and fracture. This course focuses on the differences between materials and selection of materials for engineering applications. In EAS222, students develop an understanding of the basic principles and applications of engineering mechanics including the behavior of structures under various loads, bending and Mohr’s circle. This paper discusses how the mechanics topics are threaded through this sequence of courses and how mastery of these topics is being assessed at the disciplinary level in the junior year. Assessment of students’ understanding of mechanics topics includes the following instruments: data drawn from quiz/exam grades and/or particular question(s) on exams/quizzes related to specific concepts; and faculty observations gathered using a survey tool. Our current data evaluates the first group of students to reach the junior level in the new curriculum that was implemented during the 2004-05 academic year

Testing General Relativity with Accretion-Flow Imaging of SgrA*

The Event Horizon Telescope is a global, very long baseline interferometer capable of probing potential deviations from the Kerr metric, which is believed to provide the unique description of astrophysical black holes. Here, we report an updated constraint on the quadrupolar deviation of Sagittarius A∗ within the context of a radiatively inefficient accretion flow model in a quasi-Kerr background. We also simulate near-future constraints obtainable by the forthcoming eight-station array and show that in this model already a one-day observation can measure the spin magnitude to within 0.005, the inclination to within 0.09°, the position angle to within 0.04°, and the quadrupolar deviation to within 0.005 at 3σ confidence. Thus, we are entering an era of high-precision strong gravity measurements

Testing General Relativity with the Shadow Size of Sgr

In general relativity, the angular radius of the shadow of a black hole is primarily determined by its mass-to-distance ratio and depends only weakly on its spin and inclination. If general relativity is violated, however, the shadow size may also depend strongly on parametric deviations from the Kerr metric. Based on a reconstructed image of Sagittarius A∗ (Sgr A∗) from a simulated one-day observing run of a seven-station Event Horizon Telescope (EHT) array, we employ a Markov chain Monte Carlo algorithm to demonstrate that such an observation can measure the angular radius of the shadow of Sgr A∗ with an uncertainty of ∼1.5 μas (6%). We show that existing mass and distance measurements can be improved significantly when combined with upcoming EHT measurements of the shadow size and that tight constraints on potential deviations from the Kerr metric can be obtained.Gordon and Betty Moore Foundation (Grant GBMF-3561

Jet-Launching Structure Resolved Near the Supermassive Black Hole in M87

Approximately 10% of active galactic nuclei exhibit relativistic jets, which are powered by the accretion of matter onto supermassive black holes. Although the measured width profiles of such jets on large scales agree with theories of magnetic collimation, the predicted structure on accretion disk scales at the jet launch point has not been detected. We report radio interferometry observations, at a wavelength of 1.3 millimeters, of the elliptical galaxy M87 that spatially resolve the base of the jet in this source. The derived size of 5.5 ± 0.4 Schwarzschild radii is significantly smaller than the innermost edge of a retrograde accretion disk, suggesting that the M87 jet is powered by an accretion disk in a prograde orbit around a spinning black hole

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have influenced organizations such as the United States Department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances