12 research outputs found
Model Hubungan Antara Volume Lalulintas Dengan Tarif Jalan Tol
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
Distribution of the positive fleas according to species and country.
<p>Distribution of the positive fleas according to species and country.</p
Immunohistochemistry localization of <i>B</i>. <i>quintana</i> inside the digestive tract of infected bed bugs.
<p>Immunohistochemistry localization of <i>B</i>. <i>quintana</i> inside the digestive tract of infected bed bugs.</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><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
Persistence of <i>Bartonella quintana</i> in the feces of bed bug.
<p>Persistence of <i>Bartonella quintana</i> in the feces of bed bug.</p
Persistence of <i>Bartonella quintana</i> in the bodies of bed bugs.
<p>Persistence of <i>Bartonella quintana</i> in the bodies of bed bugs.</p
Phylogenetic tree showing the position of <i>Anaplasma</i> sp. amplified from <i>Argas persicus</i> in this study compared to other species.
<p>Phylogenetic inferences were obtained using MEGA 6. GenBank accession numbers are indicated at the beginning and the geographic origin of the species is indicated at the end. The 23S rRNA gene sequences were aligned using CLUSTALW, and phylogenetic inferences were obtained using the ML phylogenetic analysis with TOPALi 2.5 software (Biomathematics and Statistics Scotland, Edinburgh, UK) within the integrated ML application, using the K81uf + I + Г substitution model.</p
Detection and identification of <i>Borrelia</i> spp., <i>Bartonella</i> spp. and Anaplasmataceae in Algerian argasid ticks.
<p>Detection and identification of <i>Borrelia</i> spp., <i>Bartonella</i> spp. and Anaplasmataceae in Algerian argasid ticks.</p
Geographical distribution of argasid ticks collected and screened for the presence of <i>Borrelia</i>, <i>Bartonella</i> and Anaplasmataceae DNA in Algeria.
<p>Geographical distribution of argasid ticks collected and screened for the presence of <i>Borrelia</i>, <i>Bartonella</i> and Anaplasmataceae DNA in Algeria.</p