A matrix population model to aid agency response to grass carp (Ctenopharyngodon idella) in the Great Lakes Basin - Lake Erie

Managers and researchers have identified a reproducing population of grass carp (Ctenopharyngodon idella) in the western basin of Lake Erie, generating concern over the potential threat to ecosystem function in the Great Lakes Basin. Capture histories indicate that grass carp may be present at low levels in other areas of Lake Erie, necessitating a large scale, multi-jurisdictional response. As a result, a group of experts and decision makers began a structured decision making exercise to collaboratively address the threat and identify potential response actions. To aid this process, we developed a spatially-explicit periodic matrix population model to project grass carp abundance, and probabilistically evaluate specific management actions. We evaluated four potential management response actions ranging from no action, diffuse removal efforts, and concentrated removal efforts with and without a barrier on the Sandusky River to reduce spawning success. Based on our current knowledge, concentrated removal including a barrier on the Sandusky River provides the most likely path to achieving and maintaining a management target of no more than 10 fish/ha. Our understanding of grass carp ecology in Lake Erie is growing. This model and parameter development methods were designed to flexibly accommodate new information as our understanding of grass carp ecology evolves, or management objectives change. Ultimately, this modeling framework and use of Bayesian methods could facilitate management response efforts for other invasive species occurring over large scales and multiple jurisdictions.     

Economics of small-scale on-farm use of canola and soybean for biodiesel and straight vegetable oil biofuels

While the cost competitiveness of vegetable oil-based biofuels (VOBB) has impeded extensive commercialization on a large-scale, the economic viability of small-scale on-farm production of VOBB is unclear. This study assessed the cost competitiveness of small-scale on-farm production of canola- [Brassica napus (L.)] and soybean-based [Glycine max (L.)] biodiesel and straight vegetable oil (SVO) biofuels in the upper Midwest at 2007 price levels. The effects of feedstock type, feedstock valuation (cost of production or market price), biofuel type, and capitalization level on the cost L⁻¹ of biofuel were examined. Valuing feedstock at the cost of production, the cost of canola-based biodiesel ranged from 0.94 to 1.13 $ L⁻¹ and SVO from 0.64 to 0.83 $ L⁻¹ depending on capitalization level. Comparatively, the cost of soybean-based biodiesel and SVO ranged from 0.40 to 0.60 $ L⁻¹ and from 0.14 to 0.33 $ L⁻¹, respectively, depending on capitalization level. Valuing feedstock at the cost of production, soybean biofuels were cost competitive whereas canola biofuels were not. Valuing feedstock at its market price, canola biofuels were more cost competitive than soybean-based biofuels, though neither were cost competitive with petroleum diesel. Feedstock type proved important in terms of the meal co-product credit, which decreased the cost of biodiesel by 1.39 $ L⁻¹ for soybean and 0.44 $ L⁻¹ for canola. SVO was less costly to produce than biodiesel due to reduced input costs. At a small scale, capital expenditures have a substantial impact on the cost of biofuel, ranging from 0.03 to 0.25 $ L⁻¹.     

Microfiltration of thin stillage: Process simulation and economic analyses

In plant scale operations, multistage membrane systems have been adopted for cost minimization. We considered design optimization and operation of a continuous microfiltration (MF) system for the corn dry grind process. The objectives were to develop a model to simulate a multistage MF system, optimize area requirements and stages required for a multistage system and perform economic analysis of a multistage MF system for a 40 million gal/yr ethanol plant. Total area requirement decreased with number of stages but there was tradeoff between higher capital costs involved at higher number of stages. To achieve thin stillage total solids concentration from 7 to 35%, a 5 stage membrane system was found to be optimum with area requirement of 655 m² for minimum cost. Increase in the input stream flow rate from 1.54 × 10⁶ to 2.89 × 10⁶ L/day significantly increased the total capital cost of the system by 47%. Compared to a single stage system, an optimal system had a 50% reduction in operating costs. Optimal system also showed potential to process more than twice the amount of thin stillage compared to a 4 effect evaporator system for given conditions.     

Heat transfer from multiple row arrays of low aspect ratio pin fins

Pin fin arrays are used in many applications to enhance heat transfer. In modern gas turbines, for example, airfoils are designed with sophisticated internal and external cooling techniques. One method for cooling is routing air from the compressor through intricate cooling channels embedded in turbine airfoils. Heat transfer from the blade to the coolant air can be increased by installing arrays of cylindrical pedestals often referred to as pin fins. Pin fin arrays increase heat transfer by increasing the flow turbulence and surface area of the airfoil exposed to the coolant.For the current study, experiments were conducted to determine the effects of pin spacing on heat transfer and pressure loss through pin fin arrays for a range of Reynolds numbers between 5000 and 30,000. Results showed that spanwise pin spacing had a larger effect than streamwise spacing on array pressure loss while streamwise spacing had a larger effect than spanwise spacing on array heat transfer.     

Design Flood Estimation Using GIS Supported GIUHApproach

Quantitative understanding and prediction of theprocesses of runoff generation and its transmission to theoutlet represent one of the most basic and challenging areasof hydrology. Traditional techniques for design floodestimation use historical rainfall-runoff data for unithydrograph derivation. Such techniques have been widelyapplied for the estimation of design flood hydrograph at thesites of gauged catchment. For ungauged catchments, unithydrograph may be derived using either regional unithydrograph approach or alternatively GeomorhologicalInstantaneous Unit Hydrograph (GIUH) approach. The unithydrograph thus derived may be used for the simulation offlood events for the ungauged catchments. In this study Gambhiri dam catchment located inRajasthan, India is selected for applying this approach. Gambhiri river is a small tributary of the Berach/Banasriver of the Chambal basin in Rajasthan, India. Theobjective of the present study is to apply GeographicalInformation System (GIS) supported GIUH approach for theestimation of design flood. A mathematical model has beendeveloped at the National Institute of Hydrology, whichenables the evaluation of the Clark Model parameters usinggeomorphological characteristics of the basin. This modelhas been applied for the present study.From this study it is observed that the peakcharacteristics of the design flood are more sensitive tothe various storm pattern as well as method of criticalsequencing followed for the computation of design stormpatterns. Earlier estimates for the peak and time to peakhydrograph was 9143.74 cumec and 18 hrs. respectively.However, the estimates for the peak characteristics ofdesign flood hydrograph obtained from the GIUH basedapproach are 11870.6 cumec and 19 hrs. respectivelyconsidering the same design storm pattern.     

Stakeholder Perspectives about Marine Oil Spill Response Objectives: A Comparative Q Study of Four Regions

Marine oil spills can cause major social, economic, and ecological disruptions. Spill response managers must weigh different options and objectives when deciding what to do. We investigated the ways in which preferences for spill response objectives vary among those who are responsible for oil spill contingency planning and response in Buzzards Bay, Delaware Bay, San Francisco Bay, and Washington State regions. We begin this paper with a discussion of the research method used in the study: the Q method. In Buzzards Bay, Delaware Bay, and San Francisco Bay three perspectives were identified in each case. In Washington State, two perspectives were identified. An analysis of the 11 case‐specific perspectives reveals that they can be described by four ‘composite’ perspectives that describe how different stakeholders prioritize spill response objectives. These four perspectives are compared on several themes, including the emphasis they placed on mitigating economic impacts, protecting health and safety, mitigating ecological impacts, implementing a coordinated and timely response, addressing the needs and concerns of the affected public/communities, gaining public support for the response, mitigating cultural impacts, and mitigating social nuisance impacts. The implications for spill response planning and spill response evaluation are discussed.     

The benefits of flexible team interaction during crises.

Organizations increasingly rely on teams to respond to crises. While research on team effectiveness during nonroutine events is growing, naturalistic studies examining team behaviors during crises are relatively scarce. Furthermore, the relevant literature offers competing theoretical rationales concerning effective team response to crises. In this article, the authors investigate whether high- versus average-performing teams can be distinguished on the basis of the number and complexity of their interaction patterns. Using behavioral observation methodology, the authors coded the discrete verbal and nonverbal behaviors of 14 nuclear power plant control room crews as they responded to a simulated crisis. Pattern detection software revealed systematic differences among crews in their patterns of interaction. Mean comparisons and discriminant function analysis indicated that higher performing crews exhibited fewer, shorter, and less complex interaction patterns. These results illustrate the limitations of standardized response patterns and highlight the importance of team adaptability. Implications for future research and for team training are included. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Natural disaster risk analysis for critical infrastructure systems: An approach based on statistical learning theory

Probabilistic risk analysis has historically been developed for situations in which measured data about the overall reliability of a system are limited and expert knowledge is the best source of information available. There continue to be a number of important problem areas characterized by a lack of hard data. However, in other important problem areas the emergence of information technology has transformed the situation from one characterized by little data to one characterized by data overabundance. Natural disaster risk assessments for events impacting large-scale, critical infrastructure systems such as electric power distribution systems, transportation systems, water supply systems, and natural gas supply systems are important examples of problems characterized by data overabundance. There are often substantial amounts of information collected and archived about the behavior of these systems over time. Yet it can be difficult to effectively utilize these large data sets for risk assessment. Using this information for estimating the probability or consequences of system failure requires a different approach and analysis paradigm than risk analysis for data-poor systems does. Statistical learning theory, a diverse set of methods designed to draw inferences from large, complex data sets, can provide a basis for risk analysis for data-rich systems. This paper provides an overview of statistical learning theory methods and discusses their potential for greater use in risk analysis.     

Higher derivative network sensitivities using adjoint network

Higher derivative sensitivity coefficients for a lumped linear time-invariant networks are derived by an extension of the method used by Richards to calculate second derivative sensitivity coefficients. A computer algorithm to generate these coefficients efficiently is provided together with array space and the number of operations required at each stage. Extensions of the above approach for networks containing distributed and nonlinear elements are also discussed. Finally, time domain sensitivity results are derived and the corresponding changes in the computer algorithm indicated.     

Recombinant modified vaccinia virus Ankara-simian immunodeficiency virus gag pol elicits cytotoxic T lymphocytes in rhesus monkeys detected by a major histocompatibility complex class I/peptide tetramer

The utility of modified vaccinia virus Ankara (MVA) as a vector for eliciting AIDS virus-specific cytotoxic T lymphocytes (CTL) was explored in the simian immunodeficiency virus (SIV)/rhesus monkey model. After two intramuscular immunizations with recombinant MVA-SIVSM gag pol, the monkeys developed a Gag epitope-specific CTL response readily detected in peripheral blood lymphocytes by using a functional killing assay. Moreover, those immunizations also elicited a population of CD8+ T lymphocytes in the peripheral blood that bound a specific major histocompatibility complex class I/peptide tetramer. These Gag epitope-specific CD8+ T lymphocytes also were demonstrated by using both functional and tetramer-binding assays in lymph nodes of the immunized monkeys. These observations suggest that MVA may prove a useful vector for an HIV-1 vaccine. They also suggest that tetramer staining may be a useful technology for monitoring CTL generation in vaccine trials in nonhuman primates and in humans.