Separation and hedging results with state-contingent production

A state-contingent model of production under uncertainty is developed and compared with more traditional models of production under uncertainty. Producer behaviour with both production and price risk, in the presence and in the absence of futures and forward markets, is analysed in this state-contingent framework. Conditions for the optimal hedge to be positive or negative are derived. We also show that, under plausible conditions, a risk-averse producer facing price uncertainty and the ability to hedge price risk will never willingly adopt a nonstochastic technology. New separation results, which hold in the presence of both price and production risk, are then developed. These separation results generalize Townsend's spanning results by reducing the number of necessary forward markets by one.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Molecular motion in miscible polymer blends .1. Motion in blends of PEO and PVPh studied by solid-state C-13 T-1 rho measurements

Changes in molecular motion in blends of PEO-PVPh have been studied using measurements of C-13 T-1 rho relaxation times. C-13 T-1 rho relaxation has been confirmed as arising from spin-lattice interactions by observation of the variation in T-1 rho with rf field strength and temperature. In the pure homopolymers a minimum in T-1 rho is observed at ca. 50 K above the glass transition temperatures detected by DSC. After blending, the temperature of the minimum in T-1 rho for PEO increased, while that for PVPh decreased, however, the minima, which correspond to the temperatures where the average correlation times for reorientation are close to 3.1 mu s, are separated by 45 K (in a 45% PEO-PVPh blend). These phenomena are explained in terms of the local nature of T-1 rho measurements. The motions of the individual homopolymer chains are only partially coupled in the blend. A short T-1 rho has been observed for protonated aromatic carbons, and assigned to phenyl rings undergoing large-angle oscillatory motion, The effects of blending, and temperature, on the proportion of rings undergoing oscillatory motion are analyzed.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Estimation of the pore size of the large-conductance mechanosensitive ion channel of Escherichia coli

The open channel diameter of Escherichia coli recombinant large-conductance mechanosensitive ion channels (MscL) was estimated using the model of Hille (Hille, B. 1968. Pharmacological modifications of the sodium channels of frog nerve. J. Gen. Physiol. 51:199-219)that relates the pore size to conductance. Based on the MscL conductance of 3.8 nS, and assumed pore lengths, a channel diameter of 34 to 46 Angstrom was calculated. To estimate the pore size experimentally, the effect of large organic ions on the conductance of MscL was examined. Poly-L-lysines (PLLs) with a diameter of 37 Angstrom or larger significantly reduced channel conductance, whereas spermine (similar to 15 Angstrom), PLL19 (similar to 25 Angstrom) and 1,1'-bis-(3-(1'-methyl-(4,4'-bipyridinium)-1-yl)-propyl)-4,4'-bipyridinium (similar to 30 Angstrom) had no effect. The smaller organic ions putrescine, cadaverine, spermine, and succinate all permeated the channel. We conclude that the open pore diameter of the MscL is similar to 40 Angstrom, indicating that the MscL has one of the largest channel pores yet described. This channel diameter is consistent with the proposed homohexameric model of the MscL.

The Potential Impact of Using Donations After Cardiac Death on the Liver Transplantation Program and Waiting List in the State of Sao Paulo, Brazil

Liver transplantation was first performed at the University of Sao Paulo School of Medicine in 1968. Since then, the patient waiting list for liver transplantation has increased at a rate of 150 new cases per month. Liver transplantation itself rose 1.84-fold (from 160 to 295) from 1988 to 2004. However, the number of patients on the liver waiting list jumped 2.71-fold (from 553 to 1500). Consequently, the number of deaths on the liver waiting list moved to a higher level, from 321 to 671, increasing 2.09-fold. We have applied a mathematical model to analyze the potential impact of using a donation after cardiac death (DCD) policy on our liver transplantation program and on the waiting list. Five thousand one hundred people died because of accidents and other violent causes in our state in 2004; of these, only 295 were donors of liver grafts that were transplanted. The model assumed that 5% of these grafts would have been DCD. We found a relative reduction of 27% in the size of the liver transplantation waiting list if DCD had been used by assuming that 248 additional liver transplants would have been performed annually. In conclusion, the use of DCD in our transplantation program would reduce the pressure on our liver transplantation waiting list, reducing it by at least 27%. On the basis of this model, the projected number of averted deaths is about 41,487 in the next 20 years. Liver Transpl 14:1732-1736, 2008. (C) 2008 AASLD.

State-dependent microstructural white matter changes in bipolar I depression

Abnormalities in fronto-limbic-striatal white matter (WM) have been reported in bipolar disorder (BD), but results have been inconsistent across studies. Furthermore, there have been no detailed investigations as to whether acute mood states contribute to microstructural changes in WM tracts. In order to compare fiber density and structural integrity within WM tracts between BD depression and remission, whole-brain fractional anisotropy (FA) and mean diffusivity (MD) were assessed in 37 bipolar I disorder (BD-I) patients (16 depressed and 21 remitted), and 26 healthy individuals with diffusion tensor imaging. Significantly decreased FA and increased MD in bilateral prefronto-limbic-striatal white matter and right inferior fronto-occipital, superior and inferior longitudinal fasciculi were shown in all BD-I patients versus controls, as well as in depressed BD-I patients compared to both controls and remitted BD-I patients. Depressed BD-I patients also exhibited increased FA in the ventromedial prefrontal cortex. Remitted BD-I patients did not differ from controls in FA or MD. These findings suggest that BD-I depression may be associated with acute microstructural WM changes.

Limitations of the Mini-Mental State Examination for screening dementia in a community with low socioeconomic status

The Mini-Mental State Examination (MMSE) is the most widely used instrument for the screening of cognitive impairment worldwide, but its ability to produce valid estimates of dementia in populations of low socioeconomic status and minimal literacy skills has not been adequately established. The authors investigated the psychometric properties of the MMSE in a community-based sample of older Brazilians. Cross-sectional one-phase population-based study of all residents of pre-defined areas of the city of Sao Paulo, aged 65 years or over. The Brazilian version of the MMSE was compared with DSM-IV diagnosis of dementia assessed with a harmonized one-phase procedure developed by the 10/66 Dementia Research Group. Analyses were performed with 1,933 participants of the SPAH study. Receiver operating characteristic analysis showed that the MMSE cut-point of 14/15 was associated with 78.7% sensitivity and 77.8% specificity for the diagnosis of dementia amongst participants with no formal education, and the cut-point 17/18 with 91.9% sensitivity and 89.5% specificity for those with at least 1 year of formal education (areas under the curves 0.87 and 0.94, respectively; P = 0.03). Even with these best fitting cut-points, the MMSE estimate of the prevalence of dementia was four times higher than determined by the DSM-IV criteria. Education, age, sex and income influenced MMSE scores, independently of dementia caseness. The MMSE is an adequate tool for screening dementia in older adults with minimum literacy skills, but misclassification is unacceptably high for older adults who are illiterate, which has serious consequences for research and clinical practice in low and middle income countries, where the proportion of illiteracy among older adults is high.

The risk of chikungunya fever in a dengue-endemic area

Background. Chikungunya, an alphavirus of the Togaviridae family, causes a febrile disease transmitted to humans by the bite of infected Aedes mosquitoes. This infection is reaching endemic levels in many Southeast Asian countries. Symptoms include sudden onset of fever, chills, headache, nausea, vomiting, joint pain with or without swelling, low back pain, and rash. According to the World Health Organization, there are 2 billion people living in Aedes-infested areas. In addition, traveling to these areas is popular, making the potential risk of infections transmitted by the bite of infected Aedes mosquitoes very high. Methods. We proposed a mathematical model to estimate the risk of acquiring chikungunya fever in an Aedes-infested area by taking the prevalence of dengue fever into account. The basic reproduction number for chikungunya fever R-0chik can be written as a function of the basic reproduction number of dengue R-0dengue by calculating the ratio R-0chik/R-0dengue. From R-0chik, we estimated the force of infection and the risk of acquiring the disease both for local residents of a dengue-endemic area and for travelers to this area. Results. We calculated that R-0chik is 64.4% that of R-0dengue. The model was applied to a hypothetical situation, namely, estimating the individual risk of acquiring chikungunya fever in a dengue-endemic area, both for local inhabitants (22% in steady state) and for visiting travelers (from 0.31% to 1.23% depending on the time spent in the area). Conclusions. The method proposed based on the output of a dynamical model is innovative and provided an estimation of the risk of infection, both for local inhabitants and for visiting travelers.

Elevated Amygdala Activity to Sad Facial Expressions: A State Marker of Bipolar but Not Unipolar Depression

Background: Difficulties in emotion processing and poor social function are common to bipolar disorder (BD) and major depressive disorder (MDD) depression, resulting in many BID depressed individuals being misdiagnosed with MDD. The amygdala is a key region implicated in processing emotionally salient stimuli, including emotional facial expressions. It is unclear, however, whether abnormal amygdala activity during positive and negative emotion processing represents a persistent marker of BD regardless of illness phase or a state marker of depression common or specific to BID and MDD depression. Methods: Sixty adults were recruited: 15 depressed with BID type 1 (BDd), 15 depressed with recurrent MDD, 15 with BID in remission (BDr), diagnosed with DSM-IV and Structured Clinical Interview for DSM-IV Research Version criteria; and 15 healthy control subjects (HC). Groups were age- and gender ratio-matched; patient groups were matched for age of illness onset and illness duration; depressed groups were matched for depression severity. The BDd were taking more psychotropic medication than other patient groups. All individuals participated in three separate 3T neuroimaging event-related experiments, where they viewed mild and intense emotional and neutral faces of fear, happiness, or sadness from a standardized series. Results: The BDd-relative to HC, BDr, and MDD-showed elevated left amygdala activity to mild and neutral facial expressions in the sad (p < .009) but not other emotion experiments that was not associated with medication. There were no other significant between-group differences in amygdala activity. Conclusions: Abnormally elevated left amygdala activity to mild sad and neutral faces might be a depression-specific marker in BID but not MDD, suggesting different pathophysiologic processes for BD versus MDD depression.