The iHLRF algorithm is a popular iterative algorithm for determining the failure probability in structural reliability problems. It belongs to the family of first-order reliability methods (FORM) and is known for its fast convergence and remarkable simplicity. However, in cases where the limit state function oscillates significantly near the design point, which often occurs in high nonlinear limit state functions, the iHLRF algorithm may suffer from convergence issues. To address these convergence issues, this paper proposes three Two-step direction determination techniques for first-order analysis. These techniques are based on Two-step root-finding methods with a higher convergence rate than existing methods. The proposed techniques aim to improve the accuracy and robustness of the iHLRF algorithm, especially in cases where the limit state function shows highly nonlinear behavior. A numerical example with high nonlinear limit state functions in standard normal space is presented to demonstrate the proposed techniques' efficiency and capability. The performance of each proposed technique is compared with other existing methods, highlighting the advantages and limitations of each approach. Overall, this paper aims to contribute to developing more accurate and reliable methods for determining the reliability index in structural reliability problems, with the potential to be applied in various engineering fields.

In data envelopment analysis (DEA), multiplier and envelopment CCR models evaluate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of decision-making units are evaluated under the same conditions, and a number of Two-stage neTwork DEA models are proposed within the framework of multi-objective linear programming (MOLP) for finding common weights. Furthermore, using the infinity norm, common weight sets are determined in Two-stage neTwork models with MOLP structures.

Background: Cockroaches mechanically spread pathogenic agents, however, little is known about their gut microbiota. Identification of midgut microbial community helps targeting novel biological control strategies such as paratransgenesis. Here the bacterial microbiota of Periplaneta americana midgut, were identified and evaluated for finding proper paratransgenesis candidate.Methods: Midgut of specimens were dissected and cultivated in different media. The bacterial isolates were then identified using the phenotypic and 16S-rRNA sequencing methods.Results: The analytical profile index (API) kit showed presence of 11 bacterial species including: Escherichia coli, Shigella flexineri, Citrobacter freundii, E. vulneris, Enterobacter cloacae, Yersinia pseudotuberculosis, Y. intermedia, Leclericia adecarboxylata, Klebsiella oxytoca, K. planticola, and Rahnella aquatilis in the cockroach midguts. The first three species are potentially symbiotic whereas others are transient. The conventional plating method revealed presence of only four isolates of Salmonella, E. coli, and Proteus which in three cases mismatched with API and 16S-rRNA genotyping. The API correctly identified the four isolates as Shigella flexneri, Citrobacter freundii, and E. coli (n=2).16S-rRNA sequence analysis confirmed the API results; however the C. freundii sequence was identical with C. murliniae indicating lack of genetic variation in the gene between these Two closely related species.Conclusion: A low number of potentially symbiotic bacteria were found in the American cockroach midguts. Among them Enterobacter cloacae is a potential candidate for paratransgenesis approach whereas other bacteria are pathogens and are not useful for the approach. Data analysis showed that identification levels increase from the conventional to API and to genotyping respectively.

Two-step anodizing approach is a simple way to produce an adhesive and continuous layer while improving the stability of titanium oxide in aggressive aqueous media. A comparative study of the electrochemical behavior of TiO2 anodic films formed by single-step (SSA) and Two-step (TSA) anodizing processes has been investigated. The anodic films have been characterized by SEM, EDX, GDOES, XRD, and FTIR analysis. Potentiodynamic polarization and EIS were used to investigate corrosion behavior in corrosive environments. A completely different surface morphology of anodic films has been obtained. Surface oxide film thicknesses of specimens were estimated at 51.86 and 60.67 µm for the SSA and TSA processes, respectively. In both cases, X-ray diffraction revealed an amorphous nature. EIS results showed that corrosion performance is closely related to anodic film morphology including thick layers, compactness, uniformity, and stability, as proved by the TSA process. Analysis of dynamic potential polarization confirmed that the TSA approach enhanced corrosion resistance by increasing (Ecorr) and lowering (Icorr). The corrosion potential (Ecorr) increased from -0.309 V/ECS to -0.271 V/ECS for the SSA and TSA and the Icorr value decreased from 1.410 μA.cm-2 to 1.032 μA.cm-2 for SSA and TSA approaches respectively.

Improvements in the Two-step synthesis of 1, 1, 1, 3, 3, 3-hexafluoro-2-(fluoromehoxy)propane (Sevoflurane) that result in the product cost reduction, safety level enhancement and positive environmental impacts are described. This process consists of chloromethylation reaction of 1, 1, 1, 3, 3, 3-hexafluoro-2-propanol (HFIP) followed by a halogen-exchange fluorination. This is the first synthesis of Sevoflurane in Iran which was successfully scaled up. During this work, several improvements have been achieved by optimization of the reaction time, the amount of consumed starting materials and solvents and work up procedure while keeping the yield and purity intact. The reaction time of the first step (24 h) was diminished to 4 h. 19F NMR spectroscopy was used to investigate the rate of the reaction in the first step and to evaluate the influence of different parameters mentioned on the achieved improvements.