An analysis of US greenhouse gas cap-and-trade proposals using a forward-looking economic model

We develop a forward-looking version of the recursive dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model, and apply it to examine the economic implications of proposals in the US Congress to limit greenhouse gas (GHG) emissions. We find that shocks in the consumption path are smoothed out in the forward-looking model and that the lifetime welfare cost of GHG policy is lower than in the recursive model, since the forward-looking model can fully optimize over time. The forward-looking model allows us to explore issues for which it is uniquely well suited, including revenue-recycling and early action crediting. We find capital tax recycling to be more welfare-cost reducing than labor tax recycling because of its long-term effect on economic growth. Also, there are substantial incentives for early action credits; however, when spread over the full horizon of the policy they do not have a substantial effect on lifetime welfare costs.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Stimulating dormancy release and emergence of annual ryegrass (Lolium rigidum) seeds using short-term hydrated storage in darkness

Experiments were performed to determine whether the dormancy release effect of hydrated storage in darkness (dark-stratification) is common amongst annual ryegrass populations and has the potential to occur under field conditions. Dormant seeds from all populations tested (22) became sensitive to light during dark-stratification, enabling them to germinate when subsequently exposed to light. Under controlled temperature (25/15degreesC), light (12-h photoperiod), and hydration (solidified agar-water) conditions, more seeds germinated by 28 days if the first 14 days were in darkness followed by exposure to light for 12 h per day than if they were exposed to light throughout or darkness throughout. Constraint over the conditions imposed during dark-stratification and germination was gradually reduced to investigate whether the dormancy release effect was diminished. Dark-stratification was effective in promoting germination when performed under natural diurnal temperatures, and burial in moist soil provided suitable conditions for dark-stratification to occur. The surface of moist soil, with natural diurnal temperatures and sunlight, was suitable for germination of dark-stratified seeds. Dark-stratification is a quick and effective means to enhance the sensitivity of dormant annual ryegrass seeds to light, enabling the majority of the population to germinate. However, large quantities of light are required to promote germination of dark-stratified seeds, so buried seeds must be moved to the soil surface to allow exposure to adequate light for germination.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Thermal Characteristics of Polybia scutellaris Nests (Hymenoptera: Vespidae) Using Computational Fluid Dynamics: A Possible Adaptation to Tropical Climates

Polybia scutellaris constructs huge nests characterized by numerous spinal projections on the surface. We investigated the thermal characteristics of P scutellaris nests in order to determine whether their nest temperature is homeothermically maintained and whether the spines play a role in the thermoregulation of the nests. In order to examine these hypotheses, we measured the nest temperature in a active nest and in an abandoned nest. The temperature in the active nest was almost stable at 27 degrees C, whereas that of the abandoned nest varied with changes in the ambient temperature, suggesting that nest temperature was maintained by the thermogenesis of colony individuals. In order to predict the thermal properties of the spines, a numerical simulation was employed. To construct a 3D-model of a P scutellaris nest, the nest architecture was simplified into an outer envelope and the surface spines, for both of which the initial temperature was set at 27 degrees C. The physical properties of the simulated nest were regarded to be those of wood since the nest of this species is constructed from plant materials. When the model was exposed to cool air (12 degrees C), the temperature was lower in the models with more spines. On the other hand, when the nest was heated (42 degrees C), the temperature increase was smaller in models with more spines. It is suggested that the spines act as a heat radiator, not as an insulator, against the changes in ambient temperature.

Production of beta-fructofuranosidases by Aspergillus niveus using agroindustrial residues as carbon sources: Characterization of an intracellular enzyme accumulated in the presence of glucose

The production of beta-fructofuranosidases by Aspergillus niveus, cultivated under submerged fermentation using agroindustrial residues, was investigated. The highest productivity of beta-fructofuranosidases was obtained in Khanna medium supplemented with sugar cane bagasse as carbon source. Glucose enhanced the production of the intracellular enzyme, whereas that of the extracellular one was decreased. The intracellular beta-fructofuranosidase was a trimeric protein of approximately 141 kDa (gel filtration) with 53.5% carbohydrate content, composed of 57 kDa monomers (SDS-PAGE). The optimum temperature and optimum pH were 60 degrees C and 4.5, respectively. The purified enzyme showed good thermal stability and exhibited a half-life of 53 min at 60 degrees C. beta-Fructofuranosidase activity was slightly activated by Cu(2+), Mn(2+), Mg(2+), and Na(+) at 1 mM concentration. The enzyme hydrolyzed sucrose, raffinose, and inulin, with K(d) values of 5.78 mM, 5.74 mM, and 1.74 mM, respectively. (C) 2008 Elsevier Ltd. All rights reserved.

Production of xylanase by Aspergilli using alternative carbon sources: application of the crude extract on cellulose pulp biobleaching

The ability of xylanolytic enzymes produced by Aspergillus fumigatus RP04 and Aspergillus niveus RP05 to promote the biobleaching of cellulose pulp was investigated. Both fungi grew for 4-5 days in liquid medium at 40A degrees C, under static conditions. Xylanase production was tested using different carbon sources, including some types of xylans. A. fumigatus produced high levels of xylanase on agricultural residues (corncob or wheat bran), whereas A. niveus produced more xylanase on birchwood xylan. The optimum temperature of the xylanases from A. fumigatus and A. niveus was around 60-70A degrees C. The enzymes were stable for 30 min at 60A degrees C, maintaining 95-98% of the initial activity. After 1 h at this temperature, the xylanase from A. niveus still retained 85% of initial activity, while the xylanase from A. fumigatus was only 40% active. The pH optimum of the xylanases was acidic (4.5-5.5). The pH stability for the xylanase from A. fumigatus was higher at pH 6.0-8.0, while the enzyme from A. niveus was more stable at pH 4.5-6.5. Crude enzymatic extracts were used to clarify cellulose pulp and the best result was obtained with the A. niveus preparation, showing kappa efficiency around 39.6% as compared to only 11.7% for that of A. fumigatus.

Visualization of drip channels in meat using NMR microimaging

The progressive changes in the water distribution within rabbit muscles were studied by nuclear magnetic resonance microscopy during the first 24 h postmortem. T-2 images revealed development of interspersed lines with higher signal intensities in the muscle, reflecting formation of channels containing mobile water. The appearance of the interspersed lines progressed throughout the measuring period and became increasingly evident. After about 3 h postmortem the signal intensity also increased in areas near the surface of the samples, which reflects migration of the mobile water to the sample surface. Proton density images showed the presence of a chemical shift artifact in the interspersed lines, implying that the intrinsic development of water channels progressed in close proximity to the connective tissue. (C) 2004 Elsevier Ltd. All rights reserved.

Characterization of pore wall heterogeneity in nanoporous carbons using adsorption: the slit pore model revisited

In this paper, we propose a new nonlocal density functional theory characterization procedure, the finite wall thickness model, for nanoporous carbons, whereby heterogeneity of pore size and pore walls in the carbon is probed simultaneously. We determine the pore size distributions and pore wall thickness distributions of several commercial activated carbons and coal chars, with good correspondence with X-ray diffraction. It is shown that the conventional infinite wall thickness approach overestimates the pore size slightly. Pore-pore correlation has been shown to have a negligible effect on prediction of pore size and pore wall thickness distributions for small molecules such as argon used in characterization. By utilizing the structural parameters (pore size and pore wall thickness distribution) in the generalized adsorption isotherm (GAI) we are able to predict adsorption uptake of supercritical gases in BPL and Norit RI Extra carbons, in excellent agreement with experimental adsorption uptake data up to 60 MPa. The method offers a useful technique for probing features of the solid skeleton, hitherto studied by crystallographic methods.

Solid-phase microextraction using poly(pyrrole) film and liquid chromatography with UV detection for analysis of antidepressants in plasma samples

Poly(pyrrole) (PPY) coating was prepared on a stainless-steel (SS) wire for solid-phase microextraction (SPME) by electrochemical deposition (cyclic voltammetric). The PPY was evaluated by analyzing new-generation antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine, and sertraline) in plasma sample by SPME and liquid chromatography with UV detection (LC-UV). The effect of electrolyte Solution (lithium perchlorate or tetrabutylammonium perchlorate) and the number of cycles (50, 100 or 200) applied during the polymerization process on the SPME performance was evaluated. Important factors in the optimization of SPME efficiency such as extraction time, temperature, pH, influence of plasma proteins on sorption mechanisms, and desorption conditions are discussed. The SPME-PPY/LC method showed to be linear in concentrations ranging from the limit of quantification (LOQ) to 1200 ng mL(-1). The LOQ values range from 16 to 25 ng mL-1. The inter-day precision of the SPME-PPY/LC method presented coefficient of variation (CV) lower than 15%. Based on analytical validation results, the SPME-PPY/LC methodology showed to be adequate for antidepressant analysis, from therapeutic to toxic levels. In order to evaluate the proposed method for clinical use, the SPME-PPY/LC method was applied to the analysis of plasma samples from elderly depressed patients. (c) 2009 Elsevier B.V. All rights reserved,

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.