5,151 research outputs found
Impacts of government risk management policies on hedging in futures and options:LPM2 hedge model vs. EU hedge model
The main objective of this study is to compare the impacts of government payments and crop insurance policies on the use of futures and options measured from a downside risk hedge model with the impacts analyzed by the expected utility (EU) hedge model. Understanding the effects of government-provided risk management tools on the private market risk management tools, such as futures and options, provides value to both crop farmers and policy makers. Comparison of the impacts from the two hedge models shows that crop farmer will hedge less in futures under the LPM2 model than under the EU hedge model. This finding indicates that model misspecification is another reason for the phenomenon that farmers actually hedge less in futures than predicted by the EU model. From the perspective of exploring new research techniques, this study applied two relatively new simulation concepts, copula simulation and conditional kernel density approach, to make the simulation assumptions less restrictive and more consistent with observations. The copula simulation applied in this study allows yield and price to have more flexible joint distribution functions than multivariate normal; the conditional kernel density approach used in farm yield simulation enables the variance of farm yield varies with county yield rather than being constant.Down-side Risk, LPM2 Hedge Model, Government Payments, Crop Insurance Policies, Copula Simulation, Conditional Kernel Density, Agricultural Finance,
Lunar surface engineering properties experiment definition Quarterly report, 1 Oct. - 31 Dec. 1968
Mechanical properties of simulated lunar soil
Hedging Downside Risk to Farm Income with Futures and Options: Effects of Government Payment Programs and Federal Crop Insurance Plans
The high proportion of government payments in total crop farm income and the purchase of subsidized crop insurance have changed the income distribution of U.S. crop farmers. As a result, the risk management behaviors of U.S. crop farmers are affected by these programs in terms of the use of private market risk management tools, such as futures and options. The objective of this research is to investigate the effects of the government payments and federal crop insurance policies on the usage of futures and options by crop farmers from a downside risk management perspective. Results in this study suggest that both yield insurance and revenue insurance creates more hedging demands for futures. But revenue insurance decreases the buying of put options at the same time. Loan deficiency government payments substitutes largely for the hedging role of put options while Counter Cyclical payments substitutes futures hedge. This research contributes the literature by proposing to use a downside risk hedge model, the second-order lower partial moment (LPM2) hedge model, to investigate the interaction of government and private risk management tools used by crop farmers. This study also initiatively applies the conditional kernel density method and the copula approach in the data simulation process. The conditional kernel density method generates county yield and farm yield with the same conditional pattern as revealed in the historical yields. The copula simulation allows the crop yield and prices have more flexible joint distributions other than bivariate normal.Agricultural and Food Policy, Agricultural Finance,
Characterising the tumour morphological response to therapeutic intervention:an ex vivo model
In cancer, morphological assessment of histological tissue samples is a fundamental part of both diagnosis and prognosis. Image analysis offers opportunities to support that assessment through quantitative metrics of morphology. Generally, morphometric analysis is carried out on two dimensional tissue section data and so only represents a small fraction of any tumour. We present a novel application of three-dimensional (3D) morphometrics for 3D imaging data obtained from tumours grown in a culture model. Minkowski functionals, a set of measures that characterise geometry and topology in n-dimensional space, are used to quantify tumour topology in the absence of and in response to therapeutic intervention. These measures are used to stratify the morphological response of tumours to therapeutic intervention. Breast tumours are characterised by estrogen receptor (ER) status, human epidermal growth factor receptor (HER)2 status and tumour grade. Previously, we have shown that ER status is associated with tumour volume in response to tamoxifen treatment ex vivo. Here, HER2 status is found to predict the changes in morphology other than volume as a result of tamoxifen treatment ex vivo. Finally, we show the extent to which Minkowski functionals might be used to predict tumour grade.Minkowski functionals are generalisable to any 3D data set, including in vivo and cellular systems. This quantitative topological analysis can provide a valuable link among biomarkers, drug intervention and tumour morphology that is complementary to existing, non-morphological measures of tumour response to intervention and could ultimately inform patient treatment
Advancing Aircraft Operations in a Net-Centric Environment with the Incorporation of Increasingly Autonomous Systems and Human Teaming
NextGen has begun the modernization of the nations air transportation system, with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness. With these improvements, NextGen is poised to handle significant increases in air traffic operations, more than twice the number recorded in 2016, by 2025.1 NextGen is evolving toward collaborative decision-making across many agents, including automation, by use of a Net-Centric architecture, which in itself creates a very complex environment in which the navigation and operation of aircraft are to take place. An intricate environment such as this, coupled with the expected upsurge of air traffic operations generates concern respecting the ability of the human-agent to both fly and manage aircraft within. Therefore, it is both necessary and practical to begin the process of increasingly autonomous systems within the cockpit that will act independently to assist the human-agent achieve the overall goal of NextGen. However, the straightforward technological development and implementation of intelligent machines into the cockpit is only part of what is necessary to maintain, at minimum, or improve human-agent functionality, as desired, while operating in NextGen. The full integration of Increasingly Autonomous Systems (IAS) within the cockpit can only be accomplished when the IAS works in concert with the human, formulating trust between the two, thereby establishing a team atmosphere. Imperative to cockpit implementation is ensuring the proper performance of the IAS by the development team and the human-agent with which it will be paired when given a specific piloting, navigation, or observational task. Described in this paper are the steps taken, at NASA Langley Research Center, during the second and third phases of the development of an IAS, the Traffic Data Manager (TDM), its verification and validation by human-agents, and the foundational development of Human Autonomy Teaming (HAT) between the two
Analysis of Iterative Methods for the Linear Boltzmann Transport Equation
In this article we consider the iterative solution of the linear system of
equations arising from the discretisation of the poly-energetic linear
Boltzmann transport equation using a discontinuous Galerkin finite element
approximation in space, angle, and energy. In particular, we develop
preconditioned Richardson iterations which may be understood as generalisations
of source iteration in the mono-energetic setting, and derive computable a
posteriori bounds for the solver error incurred due to inexact linear algebra,
measured in a relevant problem-specific norm. We prove that the convergence of
the resulting schemes and a posteriori solver error estimates are independent
of the discretisation parameters. We also discuss how the poly-energetic
Richardson iteration may be employed as a preconditioner for the generalised
minimal residual (GMRES) method. Furthermore, we show that standard
implementations of GMRES based on minimising the Euclidean norm of the residual
vector can be utilized to yield computable a posteriori solver error estimates
at each iteration, through judicious selections of left- and
right-preconditioners for the original linear system. The effectiveness of
poly-energetic source iteration and preconditioned GMRES, as well as their
respective a posteriori solver error estimates, is demonstrated through
numerical examples arising in the modelling of photon transport.Comment: 27 pages, 8 figure
Impact of Advanced Synoptics and Simplified Checklists During Aircraft Systems Failures
AbstractNatural human capacities are becoming increasingly mismatched to the enormous data volumes, processing capabilities, and decision speeds demanded in todays aviation environment. Increasingly Autonomous Systems (IAS) are uniquely suited to solve this problem. NASA is conducting research and development of IAS - hardware and software systems, utilizing machine learning algorithms, seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. IAS offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. A human-in-the-loop test was conducted in NASA Langleys Integration Flight Deck B-737-800 simulator to evaluate advanced synoptic pages with simplified interactive electronic checklists as an IAS for routine air carrier flight operations and in response to aircraft system failures. Twelve U.S. airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to failures. These data are fundamental to and critical for the design and development of future increasingly autonomous systems that can better support the human in the cockpit. Synoptic pages and electronic checklists significantly improved pilot responses to non-normal scenarios, but implementation of these aids and other intelligent assistants have barriers to implementation (e.g., certification cost) that must overcome
Quantum noise of non-ideal Sagnac speed meter interferometer with asymmetries
The speed meter concept has been identified as a technique that can
potentially provide laser-interferometric measurements at a sensitivity level
which surpasses the Standard Quantum Limit (SQL) over a broad frequency range.
As with other sub-SQL measurement techniques, losses play a central role in
speed meter interferometers and they ultimately determine the quantum noise
limited sensitivity that can be achieved. So far in the literature, the quantum
noise limited sensitivity has only been derived for lossless or lossy cases
using certain approximations (for instance that the arm cavity round trip loss
is small compared to the arm cavity mirror transmission). In this article we
present a generalised, analytical treatment of losses in speed meters that
allows accurate calculation of the quantum noise limited sensitivity of Sagnac
speed meters with arm cavities. In addition, our analysis allows us to take
into account potential imperfections in the interferometer such as an
asymmetric beam splitter or differences of the reflectivities of the two arm
cavity input mirrors. Finally,we use the examples of the proof-of-concept
Sagnac speed meter currently under construction in Glasgow and a potential
implementation of a Sagnac speed meter in the Einstein Telescope (ET) to
illustrate how our findings affect Sagnac speed meters with meter- and
kilometre-long baselines.Comment: 22 pages, 8 figures, 1 table, (minor corrections and changes made to
text and figures in version 2
Sliding Mode Implementation of an Attitude Command Flight Control System for a Helicopter in Hover
This paper presents an investigation into the design of a flight control system, using a decoupled non-linear sliding mode control structure, designed using a linearised, 9th order representation of the dynamics of a PUMA helicopter in hover. The controllers are then tested upon a higher order, non-linear helicopter model, called RASCAL. This design approach is used for attitude command flight control implementation and the control performance is assessed in the terms of handling qualities through the Aeronautical Design Standards for Rotorcraft (ADS-33). In this context a linearised approximation of the helicopter system is used to design an SMC control scheme. These controllers have been found to yield a system that satisfies the Level 1 handling qualities set out by ADS-33.
Ferromagnetic resonance force microscopy on a thin permalloy film
Ferromagnetic Resonance Force Microscopy (FMRFM) offers a means of performing
local ferromagnetic resonance. We have studied the evolution of the FMRFM force
spectra in a continuous 50 nm thick permalloy film as a function of probe-film
distance and performed numerical simulations of the intensity of the FMRFM
probe-film interaction force, accounting for the presence of the localized
strongly nonuniform magnetic field of the FMRFM probe magnet. Excellent
agreement between the experimental data and the simulation results provides
insight into the mechanism of FMR mode excitation in an FMRFM experiment.Comment: 9 pages, 2 figure
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