26 research outputs found

    Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors

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    This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analysis supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Comparison groups on bills: Automated, personalized energy information

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    A program called ``Innovative Billing?? has been developed to provide individualized energy information for a mass audience?the entire residential customer base of an electric or gas utility. Customers receive a graph on the bill that compares that customer?s consumption with other similar customers for the same month. The program aims to stimulate customers to make ef?ciency improvements. To group as many as several million customers into small ``comparison groups??, an automated method must be developed drawing solely from the data available to the utility. This paper develops and applies methods to compare the quality of resulting comparison groups. A data base of 114,000 customers from a utility billing system was used to evaluate Innovative Billing comparison groups, comparing four alternative criteria: house characteristics (?oor area, housing type, and heating fuel); street; meter read route; billing cycle. Also, customers were interviewed to see what forms of comparison graphs made most sense and led to fewest errors of interpretation. We ?nd that good quality comparison groups result from using street name, meter book, or multiple house characteristics. Other criteria we tested, such as entire cycle, entire meter book, or single house characteristics such as ?oor area, resulted in poor quality comparison groups. This analysis provides a basis for choosing comparison groups based on extensive user testing and statistical analysis. The result is a practical set of guidelines that can be used to implement realistic, inexpensive innovative billing for the entire customer base of an electric or gas utility
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