Suicidal Ideation in Patients With Gender Identity Disorder in Western Iran From March 2019 to March 2020

Background: In recent years, the number of patients with gender identity disorder (GID) has rapidly increased. These people are at risk of adverse life events that influence their health and wellbeing. Research studies have also shown a significant rate of suicide in these individuals. This study aims to determine the prevalence of suicidal ideation in patients with GID referred to Legal Medicine Office in Ilam Province.Methods: In study sample comprised 21 patients without psychiatric comorbidity visited the Legal Medicine Office in Ilam Province for confirmation of transsexuals from March 2019 to March 2020. GID disorder was diagnosed through a GIDYQ (A-A) questionnaire and clinical interview. The Beck scale for suicide ideation was used to clarify and measure the intensity of attitudes, behaviors, and planning for a suicide attempt.Results: In 21 patients with GID, the average score for suicide ideation was 11.6. The average age of patients was 19 years, and all of them were single. In this sample, 19.1% had low risks, 71.5% high risks, 9.5% had very high-risk suicide ideation. Linear regression analysis showed that higher education and higher age were risk factors for suicide ideation in patients with GID.Conclusion: The high rate of suicidal ideation in patients with gender identity disorder makes it essential to pay attention to their mental health. It should be noted that suicidal thoughts can be a basis for suicide attempts

Ethical and Unethical Methods of Plagiarism Prevention in Academic Writing

This paper discusses plagiarism origins, and the ethical solutions to prevent it. It also reviews some unethical approaches, which may be used to decrease the plagiarism rate in academic writings. We propose eight ethical techniques to avoid unconscious and accidental plagiarism in manuscripts without using online systems such as Turnitin and/or iThenticate for cross checking and plagiarism detection. The efficiency of the proposed techniques is evaluated on five different texts using students individually. After application of the techniques on the texts, they were checked by Turnitin to produce the plagiarism and similarity report. At the end, the “effective factor” of each method has been compared with each other; and the best result went to a hybrid combination of all techniques to avoid plagiarism. The hybrid of ethical methods decreased the plagiarism rate reported by Turnitin from nearly 100 to the average of 8.4 on 5 manuscripts

Association between abcc8 ala1369ser polymorphism (Rs757110 t/g) and type 2 diabetes risk in an Iranian population: A case-control study

Objective: Glucose metabolism increases ATP/ADP ratio within the β-cells and causes ATP-sensitive K+ (KATP) channel closure and consequently insulin secretion. The enhanced activity of the channel may be a mechanism contributing to the reduced first-phase of insulin secretion observed in T2DM. There is no study to date in the Kurdish ethnic group regarding the relationship between SNP Ala1369Ser (rs757110 T/G) of SUR1 gene and T2DM, and additionally, the results of this association in other populations are inconsistent. Therefore, our aim in this study was to explore the possible association between SNP Ala1369Ser and type 2 diabetes in an Iranian Kurdish ethnic group. Methods: In this study, we checked out the frequency of alleles and genotypes of SNP Ala1369Ser in T2DM individuals (207 patients; men/women: 106/101) and non-T2DM subjects (201 controls; men/women: 97/104), and their effects on anthropometric, clinical, and biochemical parameters. Genomic DNA was extracted from the leukocytes of blood specimens using a standard method. We amplified the ABCC8 rs757110 polymorphic site (T/G) using a polymerase chain reaction (PCR) method and a designed primer pair. To perform the PCR-RFLP method, the amplicons were subjected to restriction enzymes and the resulting fragments separated by gel electrophoresis. Results: The frequency of the G-allele of Ala1369Ser polymorphism was significantly (0.01) higher in the case group than the control group (19% vs. 9%, respectively). In the dominant model (TT vs. TG+GG), there was a significant relationship between this SNP and an increased risk of T2DM (P = 0.00). T2DM patients with TG+GG genotypes had significantly higher fasting plasma insulin and HOMA-IR than those who had the TT genotype (P = 0.02 and 0.01, respectively). Conclusion: Our study is the first study to investigate the association between Ala1369Ser ABCC8 genetic variation and T2DM in the Kurdish population of western Iran. The obtained results clearly show that Ala1369Ser polymorphism of ABCC8 is associated with an increased risk of T2DM in this population

Feasibility of ANFIS-PSO and ANFIS-GA Models in Predicting Thermophysical Properties of Al2O3-MWCNT/Oil Hybrid Nanofluid

The main purpose of the present paper is to improve the performance of the adaptive neuro-fuzzy inference system (ANFIS) in predicting the thermophysical properties of Al2O3-MWCNT/thermal oil hybrid nanofluid through mixing using metaheuristic optimization techniques. A literature survey showed that the use of an artificial neural network (ANN) is the most widely used method, although there are other methods that showed better performance. Moreover, it was found in the literature that artificial intelligence methods have been widely used for predicting the thermal conductivity of nanofluids. Thus, in the present study, genetic algorithms (GAs) and particle swarm optimization (PSO) have been utilized to search and determine the antecedent and consequent parameters of the ANFIS model. Solid concentration and temperature were considered as input variables, and thermal conductivity, dynamic viscosity, heat transfer performance, and pumping power in both the internal laminar and turbulent flow regimes were the outputs. In order to evaluate and compare the performance of the models, two statistical indices of root mean square error (RMSE) and determination coefficient (R) were utilized. Based on the results, both of the models are able to predict the thermophysical properties appropriately. However, the ANFIS-PSO model had a better performance than the ANFIS-GA model. Finally, the studied thermophysical properties were developed by the trained ANFIS-PSO model