Technological Change in Economic Models of Environmental Policy: A Survey

This paper provides an overview of the treatment of technological change in economic models of environmental policy. Numerous economic modeling studies have confirmed the sensitivity of mid- and long-run climate change mitigation cost and benefit projections to assumptions about technology costs. In general, technical progress is considered to be a noneconomic, exogenous variable in global climate change modeling. However, there is overwhelming evidence that technological change is not an exogenous variable but to an important degree endogenous, induced by needs and pressures. Hence, some environmenteconomy models treat technological change as endogenous, responding to socio-economic variables. Three main elements in models of technological innovation are: (i) corporate investment in research and development, (ii) spillovers from R&D, and (iii) technology learning, especially learning-by-doing. The incorporation of induced technological change in different types of environmental-economic models tends to reduce the costs of environmental policy, accelerates abatement and may lead to positive spillover and negative leakage

Heritable patterns of tooth decay in the permanent dentition: Principal components and factor analyses

Background: Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Therefore, global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. We used two methods to extract patterns of decay from surface-level caries data in order to generate novel phenotypes with which to explore the genetic regulation of caries.Methods: The 128 tooth surfaces of the permanent dentition were scored as carious or not by intra-oral examination for 1,068 participants aged 18 to 75 years from 664 biological families. Principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without a priori surface classifications, were applied to our data.Results: The three strongest caries patterns identified by PCA recaptured variation represented by DMFS index (correlation, r = 0.97), pit and fissure surface caries (r = 0.95), and smooth surface caries (r = 0.89). However, together, these three patterns explained only 37% of the variability in the data, indicating that a priori caries measures are insufficient for fully quantifying caries variation. In comparison, the first pattern identified by FA was strongly correlated with pit and fissure surface caries (r = 0.81), but other identified patterns, including a second pattern representing caries of the maxillary incisors, were not representative of any previously defined caries indices. Some patterns identified by PCA and FA were heritable (h 2 = 30-65%, p = 0.043-0.006), whereas other patterns were not, indicating both genetic and non-genetic etiologies of individual decay patterns.Conclusions: This study demonstrates the use of decay patterns as novel phenotypes to assist in understanding the multifactorial nature of dental caries. © 2012 Shaffer et al; licensee BioMed Central Ltd

Epidemic Leptospirosis Associated with Pulmonary Hemorrhage—Nicaragua, 1995

In October 1995, epidemic “hemorrhagic fever,” without jaundice or renal manifestations, was reported in rural Nicaragua following heavy flooding; 2259 residents were evaluated for nonmalarial febrile illnesses (cumulative incidence, 6.1%) and 15 (0.7%) died with pulmonary hemorrhage. A case-control study found that case-patients were more likely than controls to have ever walked in creeks (matched odds ratio [MOR], 15.0; 95% confidence interval [CI], 1.7–132.3), have household rodents (MOR, 10.4; 95% CI, 1.1–97.1), or own dogs with titers ≥ 400 to Leptospira species (MOR, 23.4; 95% CI, 3.6–`). Twenty-six of 51 case-patients had serologic or postmortem evidence of acute leptospirosis. Leptospira species were isolated from case-patients and potential animal reservoirs. This leptospirosis epidemic likely resulted from exposure to flood waters contaminated by urine from infected animals, particularly dogs. Leptospirosis should be included in the differential diagnosis for nonmalarial febrile illness, particularly during periods of flooding or when pulmonary hemorrhage occurs

Macroeconomic impact of stranded fossil-fuel assets

Several major economies rely heavily on fossil-fuel production and exports, yet current low-carbon technology diffusion, energy efficiency and climate policy may be substantially reducing global demand for fossil fuels.1-4 This trend is inconsistent with observed investment in new fossil-fuel ventures1,2, which could become stranded as a result. Here we use an integrated global economy environment simulation model to study the macroeconomic impact of stranded fossil-fuel assets (SFFA). Our analysis suggests that part of the SFFA would occur as a result of an already ongoing technological trajectory, irrespective of whether new climate policies are adopted or not; the loss would be amplified if new climate policies to reach the 2°C target are adopted and/or if low-cost producers (some OPEC countries) maintain their level of production (‘sell-out’) despite declining demand; the magnitude of the loss from SFFA may amount to a discounted global wealth loss of $1-4tn; and there are clear distributional impacts, with winners (e.g. net importers such as China or the EU) and losers (e.g. Russia, the US or Canada, which could see their fossil-fuel industries nearly shut down), although the two effects would largely offset each other at the level of aggregate global GDP.The authors acknowledge C-EERNG and Cambridge Econometrics for support, and funding from EPSRC (JFM, fellowship no. EP/ K007254/1); the Newton Fund (JFM, PS, JV, EPSRC grant no EP/N002504/1 and ESRC grant no ES/N013174/1), NERC (NRE, PH, HP, grant no NE/P015093/1), CONICYT (PS), the Philomathia Foundation (JV), the Cambridge Humanities Research Grants Scheme (JV), and Horizon 2020 (HP, JFM; Sim4Nexus project)

Two-Component Direct Fluorescent-Antibody Assay for Rapid Identification of Bacillus anthracis

A two-component direct fluorescent-antibody (DFA) assay, using fluorescein-labeled monoclonal antibodies specific to the Bacillus anthracis cell wall (CW-DFA) and capsule (CAP-DFA) antigens, was evaluated and validated for rapid identification of B. anthracis. We analyzed 230 B. anthracis isolates; 228 and 229 were positive by CW-DFA and CAP-DFA assays, respectively. We also tested 56 non–B. anthracis strains; 10 B. cereus and 2 B. thuringiensis were positive by the CW-DFA assay, and 1 B. megaterium strain was positive by CAP-DFA. Analysis of the combined DFA results identified 227 of 230 B. anthracis isolates; all 56 strains of the other Bacillus spp. were negative. Both DFA assays tested positive on 14 of 26 clinical specimens from the 2001 anthrax outbreak investigation. The two-component DFA assay is a sensitive, specific, and rapid confirmatory test for B. anthracis in cultures and may be useful directly on clinical specimens

The SDSS-III Baryon Oscillation Spectroscopic Survey: Quasar Target Selection for Data Release Nine

The SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS), a five-year spectroscopic survey of 10,000 deg^2, achieved first light in late 2009. One of the key goals of BOSS is to measure the signature of baryon acoustic oscillations in the distribution of Ly-alpha absorption from the spectra of a sample of ~150,000 z>2.2 quasars. Along with measuring the angular diameter distance at z\approx2.5, BOSS will provide the first direct measurement of the expansion rate of the Universe at z > 2. One of the biggest challenges in achieving this goal is an efficient target selection algorithm for quasars over 2.2 < z < 3.5, where their colors overlap those of stars. During the first year of the BOSS survey, quasar target selection methods were developed and tested to meet the requirement of delivering at least 15 quasars deg^-2 in this redshift range, out of 40 targets deg^-2. To achieve these surface densities, the magnitude limit of the quasar targets was set at g <= 22.0 or r<=21.85. While detection of the BAO signature in the Ly-alpha absorption in quasar spectra does not require a uniform target selection, many other astrophysical studies do. We therefore defined a uniformly-selected subsample of 20 targets deg^-2, for which the selection efficiency is just over 50%. This "CORE" subsample will be fixed for Years Two through Five of the survey. In this paper we describe the evolution and implementation of the BOSS quasar target selection algorithms during the first two years of BOSS operations. We analyze the spectra obtained during the first year. 11,263 new z>2.2 quasars were spectroscopically confirmed by BOSS. Our current algorithms select an average of 15 z > 2.2 quasars deg^-2 from 40 targets deg^-2 using single-epoch SDSS imaging. Multi-epoch optical data and data at other wavelengths can further improve the efficiency and completeness of BOSS quasar target selection. [Abridged]Comment: 33 pages, 26 figures, 12 tables and a whole bunch of quasars. Submitted to Ap