Experimental performance of three design factors for ventral nozzles for SSTOVL aircraft

An experimental study of three variations of a ventral nozzle system for supersonic short-takeoff and vertical-landing (SSTOVL) aircraft was performed at the NASA LeRC Powered Lift Facility. These test results include the effects of an annular duct flow into the ventral duct, a blocked tailpipe, and a short ventral duct length. An analytical study was also performed on the short ventral duct configuration using the PARC3D computational dynamics code. Data presented include pressure losses, thrust and flow performance, internal flow visualization, and pressure distributions at the exit plane of the ventral nozzle

Investigation of ground effects on large and small scale models of a three fan V/STOL aircraft configuration

Induced lift of a subsonic, three fan, lift/cruise, V/STOL aircraft configuration was investigated using scale modes of a multimission aircraft whose design incorporates a nose mounted lift fan and two lift/cruise units located over the wing. Configuration effects were assessed for lift improvement devices, lift/cruise nozzle rails, nozzle perimeter plates, and alternate nose fan exit hubs. Tests were conducted at four model heights (H/D = 0.95, 1.53, 3.06 and 6.45, where D is the average nozzle exit diameter equal to 0.997 m.) Results are presented and discussed

Advancing agricultural research using machine learning algorithms

Rising global population and climate change realities dictate that agricultural productivity must be accelerated. Results from current traditional research approaches are difficult to extrapolate to all possible fields because they are dependent on specific soil types, weather conditions, and background management combinations that are not applicable nor translatable to all farms. A method that accurately evaluates the effectiveness of infinite cropping system interactions (involving multiple management practices) to increase maize and soybean yield across the US does not exist. Here, we utilize extensive databases and artificial intelligence algorithms and show that complex interactions, which cannot be evaluated in replicated trials, are associated with large crop yield variability and thus, potential for substantial yield increases. Our approach can accelerate agricultural research, identify sustainable practices, and help overcome future food demands

Meta-analysis of the linear relationship between soybean yield loss and rust severity from uniform fungicide trials.

To quantify yield loss in soybean as affected by rust severity, meta-analysis was used to examine data from uniform fungicide trials (UFTs) conducted across 25 locations and 5 years (2003?2008) in the main soybean production regions of Brazil. Trials (n = 81) were selected based on predefined criteria and examined for the linear relationships between soybean yield loss (%) and rust severity (%) at the R6 growth stage. Slopes of the yield loss × severity relationship were estimated by linear regression. The influence of potential moderator variables on slopes was examined by a random effects model. Forty-one trials were excluded due to the presence of influential observations in the negative linear relationship between yield and severity. There was considerable variation among slope estimates for the increase in yield loss with respect to the change in soybean rust severity (0.31?1.81 p.p./p.p.). A significant and positive relationship between soybean rust severity and yield loss was found. For every increase of 1 p.p. in soybean rust severity, the average increase in yield loss was 0.71 p.p. (95% CI = 0.60?0.82 p.p.). The moderator variable timing of disease onset and severity class accounted for 17 and 16% of the overall and between-trial variability of slopes, respectively. This study provides an approach for quantitative risk assessments of rust-related soybean yield loss, an important step for an economic evaluation of alternative rust management strategies.Edição do Proceedings of the National Soybean Rust Symposium, New Orleans, 2009

Perceptions of Midwestern Crop Advisors and Growers on Foliar Fungicide Adoption and Use in Maize

Foliar fungicide use in hybrid maize in the United States was rare before 2000. The decade from 2000 to 2010 saw foliar fungicides increasingly applied to maize in the absence of appreciable disease pressure, a practice seemingly at odds with integrated pest management philosophy. Yet, it is commonly believed that growers do not employ management strategies unless there are perceived benefits. Maize (corn) growers (CGs) and certified crop advisors (CCAs) across four Midwestern states (Iowa, Illinois, Ohio, and Wisconsin) were surveyed to better understand their practices, values and perceptions concerning the use of foliar fungicides during 2005 to 2009. The survey results demonstrated the rapid rise in maize foliar fungicide applications from 2000 through 2008, with 84% of CGs who sprayed having used a foliar fungicide in maize production for the very first time during 2005 to 2009. During 2005 to 2009, 73% of CCAs had recommended using a foliar fungicide, but only 35% of CGs sprayed. Perceived yield gains, conditional on having sprayed, were above the break-even point on average. However, negative yield responses were also observed by almost half of CCAs and a quarter of CGs. Hybrid disease resistance was a more important factor to economically successful maize production than foliar fungicides. Diseases as a yield-limiting factor were more important to CGs than CCAs. As a group, CGs were not as embracing of foliar fungicide as were CCAs, and remained more conservative about the perceived benefits to yield

Modeling the Relationship Between Estimated Fungicide Use and Disease-Associated Yield Losses of Soybean in the United States I: Foliar Fungicides vs Foliar Diseases

Fungicide use in the United States to manage soybean diseases has increased in recent years. The ability of fungicides to reduce disease-associated yield losses varies greatly depending on multiple factors. Nonetheless, historical data are useful to understand the broad sense and long-term trends related to fungicide use practices. In the current study, the relationship between estimated soybean yield losses due to selected foliar diseases and foliar fungicide use was investigated using annual data from 28 soybean growing states over the period of 2005 to 2015. For national and regional (southern and northern United States) scale data, mixed effects modeling was performed considering fungicide use as a fixed and state and year as random factors to generate generalized R2 values for marginal (R2GLMM(m); contains only fixed effects) and conditional (R2GLMM(c); contains fixed and random effects) models. Similar analyses were performed considering soybean production data to see how fungicide use affected production. Analyses at both national and regional scales showed that R2GLMM(m) values were significantly smaller compared to R2GLMM(c) values. The large difference between R2 values for conditional and marginal models indicated that the variation of yield loss as well as production were predominantly explained by the state and year rather than the fungicide use, revealing the general lack of fit between fungicide use and yield loss/production at national and regional scales. Therefore, regression models were fitted across states and years to examine their importance in combination with fungicide use on yield loss or yield. In the majority of cases, the relationship was nonsignificant. However, the relationship between soybean yield and fungicide use was significant and positive for majority of the years in the study. Results suggest that foliar fungicides conferred yield benefits in most of the years in the study. Furthermore, the year-dependent usefulness of foliar fungicides in mitigating soybean yield losses suggested the possible influence of temporally fluctuating abiotic factors on the effectiveness of foliar fungicides and/or target disease occurrence and associated loss magnitudes

Upper bounds for number of removed edges in the Erased Configuration Model

Models for generating simple graphs are important in the study of real-world complex networks. A well established example of such a model is the erased configuration model, where each node receives a number of half-edges that are connected to half-edges of other nodes at random, and then self-loops are removed and multiple edges are concatenated to make the graph simple. Although asymptotic results for many properties of this model, such as the limiting degree distribution, are known, the exact speed of convergence in terms of the graph sizes remains an open question. We provide a first answer by analyzing the size dependence of the average number of removed edges in the erased configuration model. By combining known upper bounds with a Tauberian Theorem we obtain upper bounds for the number of removed edges, in terms of the size of the graph. Remarkably, when the degree distribution follows a power-law, we observe three scaling regimes, depending on the power law exponent. Our results provide a strong theoretical basis for evaluating finite-size effects in networks

From Cell Death to Metabolism:Holin-Antiholin Homologues with New Functions

Programmed cell death in bacteria is generally triggered by membrane proteins with functions analogous to those of bacteriophage holins: they disrupt the membrane potential, whereas antiholins antagonize this process. The holin-like class of proteins is present in all three domains of life, but their functions can be different, depending on the species. Using a series of biochemical and genetic approaches, in a recent article in mBio, Charbonnier et al. (mBio 8:e00976-17, 2017, https://doi.org/10.1128/mBio.00976-17) demonstrate that the antiholin homologue in Bacillus subtilis transports pyruvate and is regulated in an unconventional way by its substrate molecule. Here, we discuss the connection between cell death and metabolism in various bacteria carrying genes encoding these holin-antiholin analogues and place the recent study by Charbonnier et al. in an evolutionary context

Initial operation of the recoil mass spectrometer EMMA at the ISAC-II facility of TRIUMF

The Electromagnetic Mass Analyser (EMMA) is a new vacuum-mode recoil mass spectrometer currently undergoing the final stages of commissioning at the ISAC-II facility of TRIUMF. EMMA employs a symmetric configuration of electrostatic and magnetic deflectors to separate the products of nuclear reactions from the beam, focus them in both energy and angle, and disperse them in a focal plane according to their mass/charge (m∕q) ratios. The spectrometer was designed to accommodate the γ-ray detector array TIGRESS around the target position in order to provide spectroscopic information from electromagnetic transitions. EMMA is intended to be used in the measurement of fusion evaporation, radiative capture, and transfer reactions for the study of nuclear structure and astrophysics. Its complement of focal plane detectors facilitates the identification of recoiling nuclei and subsequent recoil decay spectroscopy. Here we describe the facility and report on commissioning efforts