NetKAT: Semantic Foundations for Networks

Recent years have seen growing interest in high-level languages for programming networks. But the design of these languages has been largely ad hoc, driven more by the needs of applications and the capabilities of network hardware than by foundational principles. The lack of a semantic foundation has left language designers with little guidance in determining how to incorporate new features, and programmers without a means to reason precisely about their code. This paper presents NetKAT, a new network programming language that is based on a solid mathematical foundation and comes equipped with a sound and complete equational theory. We describe the design of NetKAT, including primitives for filtering, modifying, and transmitting packets; operators for combining programs in parallel and in sequence; and a Kleene star operator for iteration. We show that NetKAT is an instance of a canonical and well studied mathematical structure called a Kleene algebra with tests (KAT) and prove that its equational theory is sound and complete with respect to its denotational semantics. Finally, we present practical applications of the equational theory including syntactic techniques for checking reachability properties, proving the correctness of compilation and optimization algorithms, and establishing a non-interference property that ensures isolation between programs.Supported in part by the NSF under grant CNS-1111698, the ONR under award N00014-12-1-0757, a Sloan Research Fellowship, and a Google Research Award

Stream Assessment on the Impact of Agricultural Activity in the Dry River, VA

Stream Bioassessments using macroinvertebrate population dynamics is a technique that determines water quality in natural aquatic environments based on the taxa found at the site. The aim of this study is to determine if agricultural activity in Rockingham County, VA has an impact on water quality in Dry River. Stream quality was evaluated by sampling and identifying macroinvertebrate taxa at various sites above and below disturbances. Each individual was ranked from 1-10 based on pollution tolerance or intolerance using the Biological Monitoring Working Party Index. The results in this study indicate that agricultural activity does impact water quality in Dry River, VA

Passport Experience: Impact Analytics Fall 2014 to Fall 2018

Utah State University (USU) dedicates substantial resources to support student transition to higher education. The Passport Experience cuts across all university domains to support early student participation in curricular, co-curricular, and extra-curricular activities. Students are invited to attend a variety of events, when milestones are reached, students are rewarded. Persistence is a primary objective of the Passport Experience. The Passport Experience helps students develop an increased awareness of campus events, broad their engagement in the university experience, and become more involved in the University community. This report explores the association between the Passport Experience and students’ persistence toward graduation. METHODS: Passport participation was captured through card swipes. Students who had enough records of Passport participation to receive a reward were compared to similar students who had no record of participation. Students were matched for comparison using prediction- based propensity score matching. Students were matched with non-users based on their persistence predication and their propensity to participate. FINDINGS: Students were 97% similar following matching. Participating and comparison students were compared using difference-in-difference testing. Students who participated were significantly more likely to persist at USU than similar students who did not (DID = 0.054, p \u3c .001). The unstandardized effect size can be estimated through student impact. It is estimated that the Passport Experience assisted in retaining 6 (CI: 1 – 9) students each year who were otherwise not expected to persist. When data collection procedures were improved in 2017, the impact of the Passport Experience increased to an estimated retention of 37 (CI: 1 to 72) students. Further tracking of this program is warrented given improved data collection and new practices

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

High C/O Chemistry and Weak Thermal Inversion in the Extremely Irradiated Atmosphere of Exoplanet WASP-12b

The carbon-to-oxygen ratio (C/O) in a planet provides critical information about its primordial origins and subsequent evolution. A primordial C/O greater than 0.8 causes a carbide-dominated interior as opposed to the silicate-dominated composition as found on Earth; the solar C/O is 0.54. Theory, shows that high C/O leads to a diversity of carbon-rich planets that can have very different interiors and atmospheres from those in the solar system. Here we report the detection of C/O greater than or equal to 1 in a planetary atmosphere. The transiting hot Jupiter WASP-12b has a dayside atmosphere depleted in water vapour and enhanced in methane by over two orders of magnitude compared to a solar-abundance chemical equilibrium model at the expected temperatures. The observed concentrations of the prominent molecules CO, CH4, and H2O are consistent with theoretical expectations for an atmosphere with the observed C/O = 1. The C/O ratios are not known for giant planets in the solar system, although they are expected to equal the solar value. If high C/O ratios are common, then extrasolar planets are likely very different in interior composition, and formed very differently, from expectations based on solar composition, potentially explaining the large diversity in observed radii. We also find that the extremely irradiated atmosphere (greater than 2500 K) of WASP-12b lacks a prominent thermal inversion, or a stratosphere, and has very efficient day-night energy circulation. The absence of a strong thermal inversion is in stark contrast to theoretical predictions for the most highly irradiated hot-Jupiter atmospheres

Teachers\u27 Preferences on the Qualities and Roles of a Mentor Teacher

Research Note: From the preface: The purpose of this investigation was to address the gap in professional development literature related to mentoring, specifically as it applies to nontraditional cases, beyond new teacher induction. In particular, we examined teachers\u27 preferences on mentoring characteristics and practices to determine whether nontraditional mentoring (owing to grade level changes, subject area changes, and newly adopted school district curricula) would be consistent with or contradict models of mentoring based primarily on the induction of new teachers. This report is part of a larger investigation that explored a curricular change initiative in a large urban school district and is a companion to another article published in JTPE about the same program (see McCaughtry, Kulinna, Cothran, Martin, & Faust, 2005). This report takes a more phenomenological approach to the investigation of mentoring as we report only teachers\u27 mentoring preferences. We wanted to share, in their own words, how teachers described effective mentoring and then compare that perspective to theorized models

Study Protocol for a Cluster-Randomized Trial of a Bundle of Implementation Support Strategies to Improve the Fidelity of Implementation of Schoolwide Positive Behavioral Interventions and Supports in Rural Schools

Background: Improving the implementation of evidence-based interventions is important for population-level impacts. Positive Behavioral Interventions and Supports (PBIS) is effective for improving school climate and students’ behavioral outcomes, but rural schools often lag behind urban and suburban schools in implementing such initiatives. Methods/Design: This paper describes a Type 3 hybrid implementation-effectiveness trial of Rural School Support Strategies (RS3), a bundle of implementation support strategies selected to improve implementation outcomes in rural schools. In this two-arm parallel group trial, 40 rural public schools are randomized to receive: 1) a series of trainings about PBIS; or 2) an enhanced condition with training plus RS3. The trial was planned for two years, but due to the pandemic has been extended another year. RS3 draws from the Interactive Systems Framework, with a university-based team (support system) that works with a team at each school (school-based delivery system), increasing engagement through strategies such as: providing technical assistance, facilitating school team functioning, and educating implementers. The primary organizational-level outcome is fidelity of implementation, with additional implementation outcomes of feasibility, acceptability, appropriateness, and cost. Staff-level outcomes include perceived climate and self-reported adoption of PBIS core components. Student-level outcomes include disciplinary referrals, academic achievement, and perceived climate. Mediators being evaluated include organizational readiness, school team functioning, and psychological safety. Discussion: The study tests implementation strategies, with strengths including a theory-based design, mixed methods data collection, and consideration of mediational mechanisms. Results will yield knowledge about how to improve implementation of universal prevention initiatives in rural schools

Drivers and mechanisms of tree mortality in moist tropical forests

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change

The Student Movement Volume 108 Issue 6: Tayloring the Future: Andrews Inaugurates New President

HUMANS Filipino Pride and the Bayanihan Spirit, Savannah Tyler Intangible Impressions of Spiritual Life at Andrews, Savannah Tyler Meet the Majors: Part 2, Reagan McCain From Underdog to gRad-dog: A graduate student\u27s perspective on the transition from undergraduate to graduate school, Anna Rybachek ARTS & ENTERTAINMENT A New Chapter in Seasons, Nailea Soto A Report on the Eras Tour Movie, Nate Miller Gilmore Girls: The Downfall of College Rory, Audrey Lim How to Enter Music Circles on Campus, Reagan McCain NEWS Armenia - Azerbaijan Conflict, Katie Davis The Inauguration, Kiheon Chung Noche Latina: A Night to Celebrate Hispanic Heritage, Melissa Moore Understanding Tomorrow Today: The Fall 2023 Kingman Lecture, Jonathan Clough IDEAS My Struggle with Secular Music, Kiheon Chung No News Is Good News - But Here\u27s Some Good News!, Reagan Westerman Pakistan\u27s First Miss Universe Winner, Katie Davis PULSE American Melodies in Harmony with the AUSO, Aiko J. Ayala Rios Celebrating Filipino American History Month, Brooklyn Anderson Why We Can\u27t Seem to Get Enough Sleep, Alyssa Caruthers LAST WORD Do it For The Plot, Lily Burkehttps://digitalcommons.andrews.edu/sm-108/1005/thumbnail.jp

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms.

BACKGROUND: Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates. METHODS: We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model. RESULTS: In the ECG-AI GWAS, we identified 3 signals (P<5×10-8) at established AF susceptibility loci marked by the sarcomeric gene TTN and sodium channel genes SCN5A and SCN10A. We also identified 2 novel loci near the genes VGLL2 and EXT1. In contrast, the clinical variable model prediction GWAS indicated a different genetic profile. In genetic correlation analysis, the prediction from the ECG-AI model was estimated to have a higher correlation with AF than that from the clinical variable model. CONCLUSIONS: Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways