The malachite green microtube (MGMT) susceptibility assay was performed directly on sputum specimens (n ‫؍‬ 80) and indirectly on Mycobacterium tuberculosis clinical isolates (n ‫؍‬ 60). The technique is based on the malachite green dye, which changes color in response to M. tuberculosis growth. The MGMT assay is simple and rapid and does not require expensive instruments.Recent advances in technology have introduced many rapid and reliable methods to differentiate between susceptible and resistant Mycobacterium tuberculosis strains (7,10,12,16). However, due to their high cost and equipment requirement, these new methods are not feasible in the clinical laboratories of developing countries in the diagnosis of tuberculosis (TB). Instead, these countries use the proportional method, which is very time-consuming (2, 11). Consequently, physicians base their diagnosis of TB on microscopy results. Therefore, supplementary rapid and reliable methods are highly needed for clinical laboratories with limited resources. In 1995, Yajko et al. (15) used an oxidation-reduction indicator, Alamar blue, which changes color in response to the growing bacteria. In 2004, we demonstrated the viability of M. tuberculosis in sputum specimens of TB patients using malachite green indicator dye, a compound routinely used in Löwenstein-Jensen (LJ) medium (3, 4). Malachite green is a triphenylmethane dye and has a dark green color, which becomes colorless during M. tuberculosis metabolism (6).In the present study, the malachite green indicator dye was used to assess the susceptibility of M. tuberculosis clinical isolates against first-and second-line anti-TB drugs. The test was also performed directly on sputum specimens of patients with pulmonary TB. In total, 80 sputum specimens from TB patients and 30 sputum specimens from patients without mycobacterial infection (e.g., with lung cancer or asthma) were collected. Furthermore, the malachite green microtube (MGMT) assay was tested indirectly on 60 M. tuberculosis clinical isolates and the M. tuberculosis H 37 R V ATCC 27294 reference strain (American Type Cell Culture Collection, Rockville, MD). The accuracy and feasibility of the MGMT assay were compared to those of the standard LJ culture method for drug susceptibility testing.Sputum specimens were digested and decontaminated by the Petroff method with a 2% final concentration of NaOH.

The aim of this study is to investigate in details the effects of a number of combustion parameters to optimize the reactivity controlled compression ignition operation running on natural gas and diesel fuel. In the present work, a singlecylinder heavy-duty diesel engine with a specially modified bathtub piston bowl profile for reactivity controlled compression ignition operation is studied and simulated through commercial software. A broad load range from 5.6 to 13.5 bar indicated mean effective pressure at a constant engine speed of 1300 r/min, fixed amount of diesel fuel mass, and with no exhaust gas recirculation is considered. The results from the developed model confirm that the model can accurately simulate the reactivity controlled compression ignition combustion. Also, by focusing on the time of formation of certain important radicals in combustion, the start of combustion and the time of natural gas dissociation are accurately predicted. Furthermore, the influence of some parameters such as different diesel fuel injection strategies, intake temperature, and intake pressure on the reactivity controlled compression ignition combustion is evaluated and the limitation of the engine operation at low temperature combustion is investigated.

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The drainage system is used to guide the flow of water in the earth dams. Construction of drainage in the dam body to collect and direct the drainage formed in the dam body to keep the slope dry and prevent the increase of pore water pressure in the body. One of the main goals of the designers is to find the minimum factor of safety and, consequently, reduce the cost of construction. In this study, the Marvak dam is modeled with the actual characteristics of the materials in the Geostudio software, and with the change in the dimensions of the drain, the material and the slope of the dam body, the minimum Factor of safety of the dam is obtained. In order to predict the minimum Factor of safety, a two-layer neural network has been used. With the training of the neural network based on the data obtained from heterogeneous dams, a minimum Factor of safety has been extracted for optimization of drainage. Finally, it was determined that the internal friction angle of the body material and the slope of the dam have the greatest effect on the dam factor of safety.