HEDGING CLASS I MILK: THE "ACCELERATION" AND "MOVER" EFFECT

A volatile closing basis prevents class I hedgers from locking in a minimum price. The closing basis is composed of an "acceleration" and "mover" effect. The mover effect always works to the producer's advantage unlike the acceleration effect. This research discusses hedging strategies to minimize the acceleration effect.Marketing,

RISK BALANCING STRATEGIES IN THE FLORIDA DAIRY INDUSTRY: AN APPLICATION OF CONDITIONAL VALUE AT RISK

Legislation has prompted changes in milk price volatility. Milk price volatility impacts the producer's exposure to business risk which is compound by the firms financial risk. Financial risk is a function of the firms capital structure. In the short run it is difficult for the producer to significantly change the firms capital structure and therefore balance increased business risk with reduced financial risk. The producer can however reduce financial and business risk by using futures contracts to lock in a price for milk produced. The producer's risk preferences dictate the producer's hedge ratio. Using the return on equity as a profitability measure and the conditional value at risk as a risk measure the optimal hedge ratio is derived for various probabilities of negative returns on equity.Conditional Value at Risk, cVaR, Risk Management, Futures, Dairy, Agricultural and Food Policy, Livestock Production/Industries, Risk and Uncertainty,

Profiling Mechanisms of Alkane Hydroxylase Activity In Vivo Using the Diagnostic Substrate Norcarane

SummaryMechanistically informative chemical probes are used to characterize the activity of functional alkane hydroxylases in whole cells. Norcarane is a substrate used to reveal the lifetime of radical intermediates formed during alkane oxidation. Results from oxidations of this probe with organisms that contain the two most prevalent medium-chain-length alkane-oxidizing metalloenzymes, alkane ω-monooxygenase (AlkB) and cytochrome P450 (CYP), are reported. The results—radical lifetimes of 1–7 ns for AlkB and less than 100 ps for CYP—indicate that these two classes of enzymes are mechanistically distinguishable and that whole-cell mechanistic assays can identify the active hydroxylase. The oxidation of norcarane by several recently isolated strains (Hydrocarboniphaga effusa AP103, rJ4, and rJ5, whose alkane-oxidizing enzymes have not yet been identified) is also reported. Radical lifetimes of 1–3 ns are observed, consistent with these organisms containing an AlkB-like enzyme and inconsistent with their employing a CYP-like enzyme for growth on hydrocarbons

Observation of a Reflected Shock in an Indirectly Driven Spherical Implosion at the National Ignition Facility

A 200  μm radius hot spot at more than 2 keV temperature, 1  g/cm[superscript 3] density has been achieved on the National Ignition Facility using a near vacuum hohlraum. The implosion exhibits ideal one-dimensional behavior and 99% laser-to-hohlraum coupling. The low opacity of the remaining shell at bang time allows for a measurement of the x-ray emission of the reflected central shock in a deuterium plasma. Comparison with 1D hydrodynamic simulations puts constraints on electron-ion collisions and heat conduction. Results are consistent with classical (Spitzer-Harm) heat flux.United States. Dept. of Energy (Contract DE-AC52-07NA27344)Brookhaven National Laboratory (Laboratory Directed Research and Development Grant 11-ERD-050

Exploration of the Transition from the Hydrodynamiclike to the Strongly Kinetic Regime in Shock-Driven Implosions

Clear evidence of the transition from hydrodynamiclike to strongly kinetic shock-driven implosions is, for the first time, revealed and quantitatively assessed. Implosions with a range of initial equimolar D[superscript 3]He gas densities show that as the density is decreased, hydrodynamic simulations strongly diverge from and increasingly overpredict the observed nuclear yields, from a factor of ∼2 at 3.1  mg/cm[superscript 3] to a factor of 100 at 0.14  mg/cm[superscript 3]. (The corresponding Knudsen number, the ratio of ion mean-free path to minimum shell radius, varied from 0.3 to 9; similarly, the ratio of fusion burn duration to ion diffusion time, another figure of merit of kinetic effects, varied from 0.3 to 14.) This result is shown to be unrelated to the effects of hydrodynamic mix. As a first step to garner insight into this transition, a reduced ion kinetic (RIK) model that includes gradient-diffusion and loss-term approximations to several transport processes was implemented within the framework of a one-dimensional radiation-transport code. After empirical calibration, the RIK simulations reproduce the observed yield trends, largely as a result of ion diffusion and the depletion of the reacting tail ions.United States. Dept. of Energy (Grant DE-NA0001857)United States. Dept. of Energy (Grant DE-FC52-08NA28752)University of Rochester. Fusion Science Center (5-24431)National Laser User’s Facility (DE-NA0002035)University of Rochester. Laboratory for Laser Energetics (415935-G)Lawrence Livermore National Laboratory (B597367

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

RISK BALANCING STRATEGIES IN THE FLORIDA DAIRY INDUSTRY: AN APPLICATION OF CONDITIONAL VALUE AT RISK

Legislation has prompted changes in milk price volatility. Milk price volatility impacts the producer's exposure to business risk which is compound by the firms financial risk. Financial risk is a function of the firms capital structure. In the short run it is difficult for the producer to significantly change the firms capital structure and therefore balance increased business risk with reduced financial risk. The producer can however reduce financial and business risk by using futures contracts to lock in a price for milk produced. The producer's risk preferences dictate the producer's hedge ratio. Using the return on equity as a profitability measure and the conditional value at risk as a risk measure the optimal hedge ratio is derived for various probabilities of negative returns on equity

HEDGING CLASS I MILK: THE "ACCELERATION" AND "MOVER" EFFECT

A volatile closing basis prevents class I hedgers from locking in a minimum price. The closing basis is composed of an "acceleration" and "mover" effect. The mover effect always works to the producer's advantage unlike the acceleration effect. This research discusses hedging strategies to minimize the acceleration effect

Biophysical Mechanistic Modelling Quantifies the Effects of Plant Traits on Fire Severity: Species, Not Surface Fuel Loads, Determine Flame Dimensions in Eucalypt Forests.

The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this