Analysis of genetic diversity and population structure in a mini core collection of flax (Linum usitatissimum L.) based on URP and SCoT markers

Ghobadi-Namin Leila,Etminan Alireza,Ghanavati Farangis,Azizinezhad Reza,Abdollahi Parisa 한국작물학회 2024 Journal of crop science and biotechnology Vol.27 No.1

The importance of plant genetic resources has received increasing attention in crop improvement and plant variation in breeding procedures. Here, plant variation and the structures of plant populations were examined among 93 flax accessions using SCoT and URP molecular markers. Polymorphic-fragments by URP and SCoT primers were, on average, 9.3 and 10.9, respectively, and the mean of polymorphism information content for primers revealed a good efficiency of both marker techniques (0.34 and 0.35 for URP and SCoT, respectively). The neighbor-joining (NJ)-based clustering, via combined data, classified all investigated accessions into four main groups that were further confirmed by principal coordinate analysis (PCoA). Moreover, molecular diversity (88%) was mostly observed inside the populations. STRUCTURE-analysis confirmed the cluster analysis and all samples were separated into four subpopulations (∆K = 4). The results implied that the sub-populations consisted of diverse accessions, suggesting that this gene pool has the potential for flax breeding programs. Furthermore, our findings indicated that URP and SCoT markers are reliable techniques in assessing plant variation, especially in elucidating the structures of flax populations. However, gene-targeting markers like SCoT are preferable because of their roots in functional genome-based regions.

Assessment of Questionnaire of Physical Activity at Workplace Based on the Social Cognitive Theory (PAWPQ-SCT): A Psychometric Study in Iranian Gas Refinery Workers

Ghobadi Kamel,Eslami AhmadAli,Pirzadeh Asiyeh,Mazloomi Seyed Mohammad,Hosseini Fatemeh 한국산업안전보건공단 산업안전보건연구원 2023 Safety and health at work Vol.14 No.4

Background: This study aimed to develop and assess the psychometric features of the Physical Activity at Workplace Questionnaire (PAWPQ) based on the Social Cognitive Theory (SCT) to evaluate employees' physical activity (PA) behaviors at the workplace. Methods: This psychometric cross-sectional study was conducted on 455 employees working in one of the gas refineries in Iran. The participants were selected using the proportional stratified sampling method in 2019. The data collection tools were a demographic information questionnaire, the short form of the International Physical Activity Questionnaire (IPAQ), and a questionnaire developed based on the SCT, whose psychometric features were confirmed in terms of validity and reliability. Data were analyzed using SPSS22 and AMOS20 software. Results: The first version of PAWPQ-SCT had 74 items. After evaluating content and face validity, nine items were removed. The results of the content validity index (0.98), content validity ratio (0.86), and impact score (3.62) were acceptable for the whole instrument. In exploratory factor analysis, after removing seven items—58-item final version of the scale—six factors could explain 73.54% of the total variance. The results of structural equation modeling showed the acceptable fit of the model into the data (RMSEA = 0.052, CFI = 0.917, NFI = 0.878, TLI = 0.905, IFI = 0.917, CMIN/DF = 2.818). Cronbach's alpha coefficient and Intraclass Correlation were 0.90 and 0.86, respectively. Conclusion: This study confirmed that the psychometric features of the 58-item final version of PAWPQ-SCT constructs were acceptable in a sample of Iranian employees. This questionnaire can be used as a valid and reliable tool to evaluate Iranian employees' PA behaviors and develop effective educational interventions for workers and managers.

A comparative study of the mechanical properties of multilayer MoS2 and graphene/MoS2 heterostructure: effects of temperature, number of layers and stacking order

Nayereh Ghobadi 한국물리학회 2017 Current Applied Physics Vol.17 No.11

In this paper molecular dynamic simulation is used to examine the mechanical properties of multilayer molybdenum disulfide (MoS2) and graphene/MoS2 heterostructure under uniaxial tensile and normal compressive strain. The effects of temperature, layer number and stacking order of layers on the stressstrain curve and elastic properties are studied. We find that the Young's modulus and vertical elastic constant of the heterostructure are much larger than that of MoS2 which is due to the higher stiffness and Young's modulus of graphene compared to MoS2. Furthermore, the results reveal that graphene/ MoS2 heterostructure is more resistant to the variation of temperature. While the rise in temperature results in the decrease of elastic constants, fracture strain and fracture stress of both structures, the increase in the number of layers only affects the elastic properties of heterostructure and has little influence on the stiffness of multilayer MoS2. Our simulations also illustrate that the highest energy stacking orders, AA3 and AB3, wherein S atoms of top layer are located above the S atoms of bottom layer, have the lowest elastic constants among all structures.

Device characteristics and tight binding based modeling of bilayer graphene field-effect transistor

N. Ghobadi,Y. Abdi 한국물리학회 2013 Current Applied Physics Vol.13 No.6

In this work the device characteristic of bilayer graphene MOSFET is investigated by calculation of transmission coefficient using tight-binding method. The real shape of applied potential on the bilayer graphene was included in the tight binding calculation. As obtained transmission coefficient is used to explore the currentevoltage characteristics of the device in both on and off regimes. Electrical behavior of the device was obtained for different gate and drains voltages and channel length.

Restrained edge domination number in graphs

S. Ghobadi,N. D. Soner 장전수학회 2009 Advanced Studies in Contemporary Mathematics Vol.19 No.1

Let G = (V,E) be a graph. A set D ⊆ E is a restrained edge dominating set if every edge in E − D is adjacent to an edge in D and another edge in E − D. The restrained edge domination number of G, denoted by [수식](G), is the smallest cardinality of a restrained edge dominating set of G. The maximum order of a partition of E into restrained edge dominating sets of G is called the restrained edge domatic number of G and denoted by [수식](G). In this paper we determine restrained edge domination and restrained edge domatic number for certain classes of graphs and obtain some bounds for [수식] (G) and [수식](G). Finally, we construct a special class of restrained edge domatically full graphs.

Mesoscale spatial-temporal prediction of monthly streamflow in poorly gauged basins: A case study

Fatemeh Ghobadi,Doosun Kang 대한토목학회 2021 대한토목학회 학술대회 Vol.2021 No.10

Application of NSGA-II, NSGA-III and R-NSGA-III for Water Pipe Replacement Scheduling Optimization

Fatemeh Ghobadi,Doosun Kang 대한토목학회 2020 대한토목학회 학술대회 Vol.2020 No.10

Inverse dominating set in fuzzy graphs

S. Ghobadi,N. D. Soner,Q. M. Mahyoub 장전수학회 2008 Proceedings of the Jangjeon mathematical society Vol.11 No.1

Let G be a graph with p vertices and let D be a minimum dominating set of G. If V −D contains a dominating set D' of G, then D' is called an inverse dominating set of G with respect to D. The inverse domination number γ(G) of G is the cardinality of a smallest inverse dominating set of G. This concept was introduced and studied by Kulli and Domke in [4] and [2] respectively. In this paper we introduce the concept of inverse dominating set in fuzzy graphs and obtain some bounds for the inverse domination number γ(G). Also we investigate the relationship of γ(G) with the other known parameters. Moreover, we also obtain Nordhaus- Gaddum type results for this parameter.

Factors Predicting Fecal Occult Blood Testing among Residents of Bushehr, Iran, Based on the Health Belief Model

Dashdebi, Kamel Ghobadi,Noroozi, Azita,Tahmasebi, Rahim Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.no.sup3

Colorectal cancer is a major cause of mortality worldwide. Fecal occult blood testing has proven a very effective screening tool for early detection and mortality reduction. The aim of this study was to determine predictors factors related to fecal occult blood testing using the Health Belief Model method among residents of Bushehr, Iran. A cross sectional study was performed on a sample of 600 men and women more than 50 years of age. The sample was selected by a convenience method from patients referred to public and private laboratories throughout the city. Each subject filled out a questionnaire which was designed and developed based on Health Belief Model constructs. Statistical analysis was conducted using ANOVA, T-test, chi-square test, and logistic regression. Fecal occult blood tests were performed on 179 (29.8%) out of 600 subjects, of which 95 patients (58.1%) did a periodic examination test and 84 patients (46.9%) had a doctor's advice for testing. According to the logistic regression model, the perceived barriers (P=0.0, Exp(B)= 0.3), perceived benefits (P<0.01, Exp(B)= 1.9) and self-efficacy (P<0.01, Exp(B)= 1.6) were predictive factors related to occult blood testing among subjects. The results showed that reducing people's perception of barriers to testing, increasing perceived benefits of screening, and reinforcing self efficacy can have major effect in increasing the rate of fecal occult blood screening for colorectal cancer prevention.

Machine Learning-based Classifiers for the Prediction of Low Birth Weight

Mahya Arayeshgari,Somayeh Najafi-Ghobadi,Hosein Tarhsaz,Sharareh Parami,Leili Tapak 대한의료정보학회 2023 Healthcare Informatics Research Vol.29 No.1

Objectives: Low birth weight (LBW) is a global concern associated with fetal and neonatal mortality as well as adverse consequencessuch as intellectual disability, impaired cognitive development, and chronic diseases in adulthood. Numerous factorscontribute to LBW and vary based on the region. The main objectives of this study were to compare four machine learningclassifiers in the prediction of LBW and to determine the most important factors related to this phenomenon in Hamadan,Iran. Methods: We carried out a retrospective cross-sectional study on a dataset collected from Fatemieh Hospital in 2017that included 741 mother-newborn pairs and 13 potential factors. Decision tree, random forest, artificial neural network,support vector machine, and logistic regression (LR) methods were used to predict LBW, with five evaluation criteria utilizedto compare performance. Results: Our findings revealed a 7% prevalence of LBW. The average accuracy of all models was87% or higher. The LR method provided a sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and accuracyof 74%, 89%, 7.04%, 29%, and 88%, respectively. Using LR, gestational age, number of abortions, gravida, consanguinity,maternal age at delivery, and neonatal sex were determined to be the six most important variables associated with LBW. Conclusions: Our findings underscore the importance of facilitating timely diagnosis of causes of abortion, providing geneticcounseling to consanguineous couples, and strengthening care before and during pregnancy (particularly for young mothers)to reduce LBW.