9 research outputs found

    Model Hubungan Antara Volume Lalulintas Dengan Tarif Jalan Tol

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    Indonesia has experienced increasing economic growth every year. This recent trend needs to be supported by adequate transportation infrastructures, especially roads. Since there is limited budget for infrastructure development, the government has invited private investors for toll road construction. Toll tariff and traffic volume are two main factors that affect toll road income and investment. A method based on financial approach needs to be developed to enhance the benefit cost analysis of toll road construction and furthermore to determine the toll tariff. Factors that affect toll tariff were analyzed based on vehicle number and vehicle growth rate. The elasticity theory was applied in this case study to identify the effects of toll tariff on traffic volume. A model of critical traffic volume was created based on the analysis of several factors such as construction cost, operation and maintenance cost, payback period, and internal rate of return. The results from Jia method and the Present Worth Factor (PWF) method show that the relationship between traffic volume and toll tariff is very sensitive, indicated by the elasticity value equal to 1. The difference between the two method is about 27% and is caused by the double counting on taxes on Jia method

    Primer and probe alignments with partial Phum_PHUM540560 gene sequences from body and head lice [35].

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    <p>A portion of the Phum_PHUM540560 gene sequences from body and head lice were aligned with the primers and probes designed for the multiplex RT-PCR assay. Part of the first exon spanings nucleotides 1 to 64 was analyzed. The forward and reverse primer sequences are boxed in black. The FAM- and VIC-labeled probe sequences are boxed in purple and green, respectively. The nucleotides in blue represent single-nucleotide polymorphisms that are specific to head lice. The nucleotides in black represent single-nucleotide polymorphisms that are specific to body lice. BL: body louse; HL: head louse; NW_002987859.1: <i>Pediculus humanus corporis</i> strain USDA 1103172108290 Phum_PHUM540560 (gene sequence available in GenBank).</p

    Amplification curves from multiplex real-time PCR assays.

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    <p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058088#pone-0058088-g001" target="_blank">Figure 1A</a>. Real-time PCR amplification curves for body lice using a partial Phum_PHUM540560 gene in the FAM channel (495–520). <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058088#pone-0058088-g001" target="_blank">Figure 1B</a>. Amplification curves for head licee louse using a partial Phum_PHUM540560 gene in the VIC channel (522–544).</p

    The Clade A lice examined in this study and the results of the real-time PCR assay.

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    <p>The Clade A lice examined in this study and the results of the real-time PCR assay.</p

    Molecular, culture, and immunohistologic methods for detection and isolation of <i>B</i>. <i>quintana</i> in blood meals, bed bugs, and their feces.

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    <p><b>Group 1:</b> 30 infected bed bugs adults; <b>Group 2:</b> 30 infected bed bugs instars L1; <b>Group Control 1:</b> 30 uninfected bed bugs adults; <b>Control 2:</b> 30 uninfected bed bugs instars L1</p><p><b>No:</b> number of bed bugs; <b>(+)</b> positive <b>; (-)</b> negative </p><p><b>ND:</b> Not Done (because we haven’t enough feces to be cultured)<b>; (≈)</b>: approximately</p><p><b>qPCR:</b> Quantitative real-time polymerase chain reaction</p><p><sup>(‡)</sup> Infected or uninfected blood</p><p>(*) observed in gut</p><p><sup>(¥)</sup> Confirmation by qPCR</p><p>Molecular, culture, and immunohistologic methods for detection and isolation of <i>B</i>. <i>quintana</i> in blood meals, bed bugs, and their feces.</p
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