Incidence and distribution of seed-borne fungi associated with wheat in Markazi Province, Iran

53 seed samples collected from harvested seed loads of irrigated wheat fields in Markazi province in the central of Iran was used for this study. Isolation and identification of seed-borne fungi were conducted according to standard tests described by the International Seed Testing Association (ISTA). A total of 15 fungal species including Tilletia laevis, Tilletia tritici, Ustilago tritici, Fusarium graminearum, Fusarium culmorum, Microdochium nivale, Bipolaris sorokiniana, Alternaria alternata, Curvularia sp., Aspergillus niger, Aspergillus candidus, Aspergillus flavus, Penicillium sp., Mucor sp. and Rhizopus sp. were identified in three wheat cultivars of Backcross Roshan, Alvand and C-78-14. The average of infection level in tested samples to both T. laevis and T. tritici was estimated as much as 7.1% in the province and the minimum and maximum infection levels were found in Lilian (Khomein) and Jirya regions (Arak), respectively. The average of infection rate by U. tritici in seed samples was 1.3% while it was as much as 17.4% for both F. culmorum and B. sorokiniana in the province. The frequency of A. niger and Penicillium sp. was predominant with an infection range of 37.8 and 29.1%, respectively. For the first time, the incidence and infection level of seed-borne fungi in wheat seeds have been determined in the central part of Iran.Key words: Infection rate, seed-borne fungi, seed quality, wheat

The study of the rate of convergence in the stock exchange market of the persian gulf countries

Stock exchange is one of the main pillars and principles of the country’s economy and paying attention to this organization not only flourishes and promotes it, but also causes the growth and development of the national economy. For this reason, the factors that affect this organization should be analyzed to develop it through the obtained results. Sudden shocks of the market, global financial crises and the  increase of vitality of stock returns at an international level during the past years have created some concerns to managers and investors. The study of the presenceand absence of the effectiveness of global financial markets from each other can  significantly help the prediction of global crises and timely performance to these crises. This study used the stock price index of the Persian Gulf countries available on formal informational databases for 5 years (2005-2010) as daily in order to study the long-term convergence between the price index of the stock exchange in the Persian Gulf countries. In this study, the relationship between the indices was examined by correlation analysis method and the stationary of series related to  each country by the Augmented Dicky Fuller test and the long term convergence by Johansson cointegration method. The study results show the most of these countries have a high correlation and the relationship between these countries is significant. The results of Johansson cointegration test in the both tested methods of max-Eigenvalue proved 3 long term convergence equations and Static Traceproved 6 long term convergence equations at 0/05 significance level.Keywords: correlation, long term convergence, cointegration, price inde

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype

Increased Glucose Availability Sensitizes Pancreatic Cancer to Chemotherapy

Pancreatic Ductal Adenocarcinoma (PDAC) is highly resistant to chemotherapy. Effective alternative therapies have yet to emerge, as chemotherapy remains the best available systemic treatment. However, the discovery of safe and available adjuncts to enhance chemotherapeutic efficacy can still improve survival outcomes. We show that a hyperglycemic state substantially enhances the efficacy of conventional single- and multi-agent chemotherapy regimens against PDAC. Molecular analyses of tumors exposed to high glucose levels reveal that the expression of GCLC (glutamate-cysteine ligase catalytic subunit), a key component of glutathione biosynthesis, is diminished, which in turn augments oxidative anti-tumor damage by chemotherapy. Inhibition of GCLC phenocopies the suppressive effect of forced hyperglycemia in mouse models of PDAC, while rescuing this pathway mitigates anti-tumor effects observed with chemotherapy and high glucose

The application of particle swarm optimization in slope stability analysis of homogeneous soil slopes

This paper applies particle swarm optimization (PSO) to find the most possible failure surface in stability analysis of homogeneous soil slopes. The stability of slopes is an important issue on geotechnical engineering. This problem includes two general concepts, factor of safety (FOS) and the critical slip surface (CSS). The resultant ratio of dividing strengthens forces by driving forces is called FOS. The critical slip surface is defined as a failure surface with the minimum value of FOS among all candidates. Regarding to the vast number of trial slip surfaces and the non-linear nature of equation of FOS, a global optimization algorithm is needed to locate CSS. As an optimization technique, the original version of PSO with little improvements in initial parameters is used. With this aim in view, we developed a computer code to find CSS by particle swarm optimization. Moreover, a sensitivity analysis is conducted to find the optimum values of initial parameters of PSO. Finally the effectiveness and efficiency of PSO code is verified and compared with the benchmark examples from the literature. The results demonstrated the ability of PSO to find CSS with better outcomes than former methods

Simulation of longitudinal surface settlement due to tunnelling using artificial neural network

A series of artificial neural networks modelling was conducted to investigate the ground deformation induced by tunnelling along the line 2 of Karaj urban railway, Iran. The tunnels were excavated using New Austrian Tunnelling Method. During excavation, surface settlement was monitored using optical survey points installed on the centre, left and right sides of the tunnel axis. The measured data have been used to establish an artificial neural network model to predict longitudinal surface settlement. This paper focuses on the prediction of ground deformation due to tunnelling using artificial neural networks, particularly longitudinal settlements in relation to the ground condition and tunnelling method. The obtained results demonstrate that artificial neural networks are applicable techniques for predicting longitudinal surface settlement due to tunnelling

The effects of method of generating circular slip surfaces on determining the critical slip surface by particle swarm optimization

The main objectives of slope stability analysis are evaluating factor of safety for a given slip surface and determining the critical slip surface for a given slope. Factor of safety is usually calculated by limit equilibrium method. The main steps to determine the critical slip surface are generating trial slip surfaces as probable solutions and searching among them to determine the one with the lowest factor of safety. Although the process of searching the critical slip surface received much attention between researchers, the significance of method of generating slip surfaces is seldom addressed in the literature. The authors believe that this ignorance can affect the accuracy of the results of slope stability analysis even in the simplest problems with circular slip surfaces. Consequently, this paper focused on the method of generating circular trial slip surfaces as the simplest mechanism of sliding and considered its effect on determining the critical slip surface. A new method of generating circular slip surface was presented, which is more efficient and less restricted than the conventional method. A computer program was also developed to determine the critical slip surface of slopes by using particle swarm optimization. The performances of the proposed method and developed computer program were verified during comparative studies and sensitivity analysis. Based on the results, the effect of method of generating circular slip surfaces on determining the critical slip surface was confirmed successfully. In all considered problems, the proposed method of generating circular slip surfaces led to the lower values of factor of safety compare with the conventional method

Applications of Particle Swarm Optimization in Geotechnical Engineering: A Comprehensive Review

Particle swarm optimization (PSO) is an evolutionary computation approach to solve nonlinear global optimization problems. The PSO idea was made based on simulation of a simplified social system, the graceful but unpredictable choreography of birds flock. This system is initialized with a population of random solutions that are updated during iterations. Over the last few years, PSO has been extensively applied in various geotechnical engineering aspects such as slope stability analysis, pile and foundation engineering, rock and soil mechanics, and tunneling and underground space design. A review on the literature shows that PSO has utilized more widely in geotechnical engineering compared with other civil engineering disciplines. This is due to comprehensive uncertainty and complexity of problems in geotechnical engineering which can be solved by using the PSO abilities in solving the complex and multi-dimensional problems. This paper provides a comprehensive review on the applicability, advantages and limitation of PSO in different disciplines of geotechnical engineering to provide an insight to an alternative and superior optimization method compared with the conventional optimization techniques for geotechnical engineers

Effects of tunnel face distance on surface settlement

Underground activities such as tunnel excavation may cause soil movements around the excavation area and subsequently the ground surface. Several tunnel construction methods have been developed during the last decades and the most significant effort is to reduce the ground surface settlement. New Austrian Tunnelling Method (NATM) is one of the well-known methods which is widely used in the construction of tunnels and metro stations. This paper discusses the effects of excavation sequence and heading distance on the surface settlement induced by tunnelling in Side Gallery (SG) method, as an alternative to NATM, in Karaj Metro Tunnel (KMT) project, Iran. The Abaqus software was used to simulate the Finite Element modelling of both methods. The results showed that the removal of top head in NATM for KMT project caused 80% of the total surface settlement, but it was only 60% in SG method due to the existence of middle liner