Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

New calibration technique for multiple-component stress wave force balances

Force measurement in hypervelocity expansion tubes is not possible using conventional techniques. The stress wave force balance technique can be applied in expansion tubes to measure forces despite the short test times involved. This paper presents a new calibration technique for multiple-component stress wave force balances where an impulse response created using a load distribution is required and no orthogonal surfaces on the model exist.. This new technique relies on the tensorial superposition of single-component impulse responses analogous to the vectorial superposition of the calibration loads. The example presented here is that of a scale model of the Mars Pathfinder, but the technique is applicable to any geometry and may be useful for cases where orthogonal loads cannot be applied.

A mathematical model of HIV transmission in NSW prisons

A mathematical model was developed to estimate HIV incidence in NSW prisons. Data included: duration of imprisonment; number of inmates using each needle; lower and higher number of shared injections per IDU per week; proportion of IDUs using bleach; efficacy of bleach; HIV prevalence and probability of infection. HIV prevalence in IDUs in prison was estimated to have risen from 0.8 to 5.7% (12.2%) over 180 weeks when using lower (and higher) values for frequency of shared injections. The estimated minimum (and maximum) number of IDU inmates infected with HIV in NSW prisons was 38 (and 152) in 1993 according to the model. These figures require confirmation by seroincidence studies. (C) 1998 Published by Elsevier Science Ireland Ltd. All rights reserved.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Dendritic cells in rheumatoid arthritis - A model autoimmune inflammatory site

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease in which unknown arthrogenic autoantigen is presented to CD4+ T cells. The strong association of the disease with an epitope within the HLA-DR chain shared between various alleles of HLA-DR4 and DR1 emphasizes the importance of antigen presentation. This immune response predominantly occurs in the synovial tissue and fluid of the joints and autoreactive T cells are readily demonstrable in both the synovial compartment and blood. Circulating dendritic cells (DC) are phenotypically and functionally identical with normal peripheral blood (PB) DC. In the synovial tissue, fully differentiated perivascular DC are found in close association with T cells and with B cell follicles, sometimes containing follicular DC. These perivascular DC migrate across the activated endothelium from blood and receive differentiative signals within the joint from monocyte-derived cytokines and CD40-ligand+ T cells. In the SF, DC manifest an intermediate phenotype, similar to that of monocyte-derived DC in vitro. Like a delayed-type hypersensitivity response, the rheumatoid synovium represents an effector site. DC at many effector sites have a characteristic pattern of infiltration and differentiation. It is important to note that the effector response is not self-limiting in RA autoimmune inflammation. In this article, we argue that the presentation of self-antigen by DC and by autoantibody-producing B cells is critical for the perpetuation of the autoimmune response. Permanently arresting this ongoing immune response with either pharmaceutical agents or immunotherapy is a major challenge for immunology.

A model of specification-based testing of interactive systems

In this paper we present a model of specification-based testing of interactive systems. This model provides the basis for a framework to guide such testing. Interactive systems are traditionally decomposed into a functionality component and a user interface component; this distinction is termed dialogue separation and is the underlying basis for conceptual and architectural models of such systems. Correctness involves both proper behaviour of the user interface and proper computation by the underlying functionality. Specification-based testing is one method used to increase confidence in correctness, but it has had limited application to interactive system development to date.

A new formation model for M32: a threshed early-type spiral galaxy?

The origin of M32, the closest compact elliptical galaxy (cE), is a long-standing puzzle of galaxy fort-nation in the Local Group. Our N-body/smoothed particle hydrodynamics simulations suggest a new scenario in which the strong tidal field of M31 can transform a spiral galaxy into a compact elliptical galaxy. As a low-luminosity spiral galaxy plunges into the central region of M31, most of the outer stellar and gaseous components of its disk are dramatically stripped as a result of M31's tidal field. The central bulge component, on the other hand, is just weakly influenced by the tidal field, owing to its compact configuration, and retains its morphology. M31's strong tidal field also induces rapid gas transfer to the central region, triggers a nuclear starburst, and consequently forms the central high-density and more metal-rich stellar populations with relatively young ages. Thus, in this scenario, M32 was previously the bulge of a spiral galaxy tidally interacting with M31 several gigayears ago. Furthermore, we suggest that cE's like M32 are rare, the result of both the rather narrow parameter space for tidal interactions that morphologically transform spiral galaxies into cE's and the very short timescale (less than a few times 10(9) yr) for cE's to be swallowed by their giant host galaxies (via dynamical friction) after their formation.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Shared structural determinants for the calcium-independent liposome membrane permeabilization and sarcolemma depolarization in Bothropstoxin-I, a LYS49-PLA(2) from the venom of Bothrops jararacussu

The structural determinants of myotoxicity of bothropstoxin-I (BthTX-I), a Lys49 phospholipase A(2) from Bothrops jararacussu venom, were studied by measuring the resting membrane potential in the mouse phrenic nerve-diaphragm preparation. This method proved to be around 100-fold more sensitive than the creatine kinase release assay, and was used to evaluate a total of 31 site-directed BthTX-I alanine scanning mutants. Mutants that reduced the resting membrane potential were located in a surface patch defined by residues in the C-terminal loop (residues 115-129), positions 37-39 in the membrane interfacial recognition surface (Y46 and K54), and residue K93. These results expand the known structural determinants of the biological activity as evaluated by previous creatine kinase release experiments. Furthermore, a strong correlation is observed between the structural determinants of sarcolemma depolarization and calcium-independent disruption of liposome membranes, suggesting that a common mechanism of action underlies the permeabilization of the biological and model membranes. (C) 2009 Elsevier Ltd. All rights reserved.

HUMAN CHOLESTERYL ESTER TRANSFER PROTEIN EXPRESSION ENHANCES THE MOUSE SURVIVAL RATE IN AN EXPERIMENTAL SYSTEMIC INFLAMMATION MODEL: A NOVEL ROLE FOR CETP

Mice expressing human cholesteryl ester transfer protein (huCETP) are more resistant to Escherichia coli bacterial wall LIPS because death rates 5 days after intraperitoneal inoculation of LIPS were higher in wild-type than in huCETP(+/-) mice, whereas all huCETP(+/+) mice remained alive. After LIPS inoculation, plasma concentrations of TNF-alpha and IL-6 increased less in huCETP(+/+) than in wild-type mice. LPS in vitro elicited lower TNF-alpha production by CETP expressing than by wild-type macrophages. In addition, TNF-alpha production by RAW 264.7 murine macrophages increased on incubation with LPS but decreased in a dose-dependent manner when human CETP was added to the medium. Human CETP in vitro enhanced the LIPS binding to plasma high-density lipoprotein/low-density lipoprotein. The liver uptake of intravenous infused C-14-LPS from Salmonella typhimurium was greater in huCETP(+/+) than in wild-type mice. Present data indicate for the first time that CETP is an endogenous component involved in the first line of defense against an exacerbated production of proinflammatory mediators.

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.