Energy-based numerical models for assessment of soil liquefaction

AbstractThis study presents promising variants of genetic programming (GP), namely linear genetic programming (LGP) and multi expression programming (MEP) to evaluate the liquefaction resistance of sandy soils. Generalized LGP and MEP-based relationships were developed between the strain energy density required to trigger liquefaction (capacity energy) and the factors affecting the liquefaction characteristics of sands. The correlations were established based on well established and widely dispersed experimental results obtained from the literature. To verify the applicability of the derived models, they were employed to estimate the capacity energy values of parts of the test results that were not included in the analysis. The external validation of the models was verified using statistical criteria recommended by researchers. Sensitivity and parametric analyses were performed for further verification of the correlations. The results indicate that the proposed correlations are effectively capable of capturing the liquefaction resistance of a number of sandy soils. The developed correlations provide a significantly better prediction performance than the models found in the literature. Furthermore, the best LGP and MEP models perform superior than the optimal traditional GP model. The verification phases confirm the efficiency of the derived correlations for their general application to the assessment of the strain energy at the onset of liquefaction

Investigating Dynamic Properties of Residues of Warfarin-Azapropazone Binding Site in Human Serum Albumin

Introduction: Human Serum Albumin is one of the most important proteins in blood that can bind a wide range of components and different drugs such as Warfarin. Therefore, studying human serum albumin is very significant in pharmacology. In this research, dynamic behavior of residues of Warfain binding site of human serum albumin was investigated. Method: First, three-dimensional format of human serum albumin (PDB ID: 4G04) was downloaded from RCSB. Then, using GROMACS package, molecular dynamics simulation has been done on chain A of crystallography structure during 30ns. Results: RMSD analysis on residues of binding site showed that Arginines 186 and 218 have wide fluctuations in their RMSD plot. Also, Lysines 185 and 190 have nearly wide fluctuations of RMSD; however, these fluctuations were less than Arginine's. Other residues such as Glycine 189 have few fluctuations. Fluctuations in RMSD have direct relationship with accessible surface area of the residues. Conclusion: The results show that Warfarin binding site in human serum albumin can have various conformational situations because of the dynamics of its residues. This can be important in drug design. Overall, according to the results of this study, residues are divided into 3 categories. Among them, Tryptophan 214, that is one of the most important residues according to different studies, was placed in the category of residues with the least mobility

Lévy-Flight Krill Herd Algorithm

To improve the performance of the krill herd (KH) algorithm, in this paper, a Lévy-flight krill herd (LKH) algorithm is proposed for solving optimization tasks within limited computing time. The improvement includes the addition of a new local Lévy-flight (LLF) operator during the process when updating krill in order to improve its efficiency and reliability coping with global numerical optimization problems. The LLF operator encourages the exploitation and makes the krill individuals search the space carefully at the end of the search. The elitism scheme is also applied to keep the best krill during the process when updating the krill. Fourteen standard benchmark functions are used to verify the effects of these improvements and it is illustrated that, in most cases, the performance of this novel metaheuristic LKH method is superior to, or at least highly competitive with, the standard KH and other population-based optimization methods. Especially, this new method can accelerate the global convergence speed to the true global optimum while preserving the main feature of the basic KH

Multi-drug resistant Staphylococcus aureus isolated from emergency ward of an Iranian hospital

Purpose: To study the prevalence of resistant strains of S. aureus isolated from surfaces, beds and various equipment of an Iranian hospital emergency ward.Methods: Two hundred swab samples were collected from the surfaces, beds, trolleys, surgical equipment and diagnostic medical devices in emergency ward. Samples were cultured and those that were S. aureus-positive were confirmed using polymerase chain reaction (PCR). Antimicrobial resistance pattern was analyzed using disk diffusion method.Results: Nine of 200 samples (4.5 %) collected were positive for S. aureus. Surfaces (8.8 %), beds (5 %) and trolleys (5 %) were the most commonly contaminated. S. aureus isolates exhibited varying levels of resistance against antibiotics with the following being the highest: tetracycline (88.8 %), penicillin (88.8 %) and ampicillin (77.7 %). The prevalence of resistance against methicillin, oxacillin and azithromycin were 44.4, 33.3 and 33.3 %, respectively. There was no pattern of resistance against imipenem.Conclusion: Efficient disinfection of surfaces, beds, trolleys and surgical instruments should be performed periodically to reduce colonization of resistant strains of S. aureus in various areas of emergency health care centers.Keywords: Staphylococcus aureus, Nocosomial infection, Antibiotic resistance, Hospital equipment, Emergency war

Metaheuristics in water, geotechnical and transport engineering

Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are often large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems. This book examines the latest developments of metaheuristics and their applications in water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks. This book can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheursitics, optimization in civil engineering and computational intelligence. (from publisher's website