Response of Bean and Tobacco to Ozone: Effect of Light Intensity,Temperature and Relative Humidity

Pinto bean (Phaseolus vulgaris, L.) and Bel W₃ tobacco (Nicotiana tabacum, L.) were grown and exposed to 40 pphm ozone for 1 hr under a range of light intensities, temperatures, and relative humidities. Foliar injury to the more sensitive plant leaves was determined on the third day after exposure. Each atmospheric factor was independently assessed. Two significant three-way interactions were found: exposure light intensity by growth light intensity by species, and growth temperature by exposure temperature by species. Three significant two-way interactions were found for humidity: growth humidity by exposure humidity, growth humidity by species, and exposure humidity by species. The sensitivity of each species to ozone changed with changes in each environmental condition.     

Overview of Proposed Air Emission Standards and Guidelines for Municipal Waste Combustors

The EPA proposed regulations for municipal waste combustors (MWCs) on December 20, 1989. The regulations include (1) performance standards under Section lll(b) of the Clean Air Act (CAA) for new, modified, or reconstructed MWCs and (2) draft emission guidelines and compliance schedules for the states to use to develop control requirements from existing MWCs under Section 111(d).

This paper will outline the proposed air emission standards and guidelines, as well as the basis for the prescribed emission limits. The schedule for the remainder of the regulations development will also be discussed.     

Detection of presumed genes encoding beta-lactamases by sequence based screening of metagenomes derived from Antarctic microbial mats

• Beta-lactamase genes were found in all samples from distant places in Antarctica. • Class C beta-lactamase coding genes were the most frequently found. • Diversity of sequences exceeds that of the beta-lactamases from clinical environment. Analysis of environmental samples for bacterial antibiotic resistance genes may have different objectives and analysis strategies. In some cases, the purpose was to study diversity and evolution of genes that could be grouped within a mechanism of antibiotic resistance. Different protocols have been designed for detection and confirmation that a functional gene was found. In this study, we present a sequence-based screening of candidate genes encoding beta-lactamases in 14 metagenomes of Antarctic microbial mats. The samples were obtained from different sites, representing diverse biogeographic regions of maritime and continental Antarctica. A protocol was designed based on generation of Hidden Markov Models from the four beta-lactamase classes by Ambler classification, using sequences from the Comprehensive Antibiotic Resistance Database (CARD). The models were used as queries for metagenome analysis and recovered contigs were subsequently annotated using RAST. According to our analysis, 14 metagenomes analyzed contain A, B and C beta-lactamase genes. Class D genes, however, were identified in 11 metagenomes. The most abundant was class C (46.8%), followed by classes B (35.5%), A (14.2%) and D (3.5%). A considerable number of sequences formed clusters which included, in some cases, contigs from different metagenomes. These assemblies are clearly separated from reference clusters, previously identified using CARD beta-lactamase sequences. While bacterial antibiotic resistance is a major challenge of public health worldwide, our results suggest that environmental diversity of beta-lactamase genes is higher than that currently reported, although this should be complemented with gene function analysis.     

Business closure and relocation: a comparative analysis of the Loma Prieta earthquake and Hurricane Andrew

The occurrence of a number of large‐scale disasters or catastrophes in recent years, including the Indian Ocean tsunami (2004), the Kashmir earthquake (2005), Hurricane Katrina (2005) and Hurricane Ike (2008), have raised our awareness regarding the devastating effects of disasters on human populations and the importance of developing mitigation and preparedness strategies to limit the consequences of such events. However, there is still a dearth of social science research focusing on the socio‐economic impact of disasters on businesses in the United States. This paper contributes to this research literature by focusing on the impact of disasters on business closure and relocation through the use of multivariate logistic regression models, specifically focusing on the Loma Prieta earthquake (1989) and Hurricane Andrew (1992). Using a multivariate model, we examine how physical damage to the infrastructure, lifeline disruption and business characteristics, among others, impact business closure and relocation following major disasters.