16 research outputs found

    Relationship between EFL Learners’ Perceived Social Self-Efficacy and their Foreign Language Classroom Anxiety

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    The present study was conducted to investigate the relationship between the perceived social self-efficacy of the students of English and their foreign language classroom anxiety. The required data were gathered through the application of the original versions of two standard questionnaires: Smith and Betz’s (2000) 25-item Scale of Perceived Social Self-Efficacy (SPSSE) and Horwitz, Horwitz and Cope’s (1986) 33-item Foreign Language Classroom Anxiety Scale (FLCAS). A total of 151 participants (including 127 students of English Language and Literature in B.A. level and 24 students of Teaching English as a Foreign Language at M.A. level) took part in the study. Correlational analysis was employed to determine the relationship between perceived social self-efficacy and foreign language classroom anxiety. Pearson Product-Moment correlation analysis results (r = -.164, p < .05) showed that the participants’ perceived social self-efficacy had a reverse relationship with their foreign language classroom anxiety. Further calculations were done for the type and rate of the influence of demographic variables (namely age, gender, academic seniority, and educational level) on students’ PSSE and FLCA. According to the One-Way ANOVA results, no meaningful relationship was observed between age, gender, academic seniority, and educational level of the participants, and their perceived social self-efficacy or foreign language classroom anxiety. Based on the findings of this study, the rate of perceived social self-efficacy (i.e. trust in self in social situations) seems to play a key role in the intensity of foreign language learners’ anxiety and a vital parameter in their full-functioning and efficient learning

    Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules

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    Link prediction is an important task in addressing the incompleteness problem of knowledge graphs (KG). Previous link prediction models suffer from issues related to either performance or explanatory capability. Furthermore, models that are capable of generating explanations, often struggle with erroneous paths or reasoning leading to the correct answer. To address these challenges, we introduce a novel Neural-Symbolic model named FaSt-FLiP (stands for Fast and Slow Thinking with Filtered rules for Link Prediction task), inspired by two distinct aspects of human cognition: "commonsense reasoning" and "thinking, fast and slow." Our objective is to combine a logical and neural model for enhanced link prediction. To tackle the challenge of dealing with incorrect paths or rules generated by the logical model, we propose a semi-supervised method to convert rules into sentences. These sentences are then subjected to assessment and removal of incorrect rules using an NLI (Natural Language Inference) model. Our approach to combining logical and neural models involves first obtaining answers from both the logical and neural models. These answers are subsequently unified using an Inference Engine module, which has been realized through both algorithmic implementation and a novel neural model architecture. To validate the efficacy of our model, we conducted a series of experiments. The results demonstrate the superior performance of our model in both link prediction metrics and the generation of more reliable explanations

    Ethical Performance of Neonatal Nurses in Neonatal Intensive Care Units

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    Introduction: Lack of adherence to the nursing code of ethics in neonatal wards is usually an issue in hospitals. The present study explored neonatal nurses’ adherence to the nursing code of ethics in the neonatal ward, using the Neonatal Nurses' Ethical Performance Self-Report Questionnaire and the Neonatal Nurses' Ethical Performance Observation Checklist.Methods: In this descriptive study, 132 Nurses from 5 neonatal wards from two pediatric hospitals in Tehran were recruited by census sampling.Results: The results showed that the mean score of the self-report questionnaire (86.12+10.34) and observational checklist (80.98+10.34) was within the desired performance range. The domain of improving the quality of care had the highest score (94.25+3.40) in the self-report questionnaire, and the domain of justice had the highest score (95.00+0) in the observational checklist. The domain of respect for autonomy had the lowest mean score in the self-report questionnaire (64.31+22.22) and the observational checklist (67.50+6.19). There was no significant relationship between the ethical performance score reported by nurses and nurses' demographic variables (P&gt;0.05), and the specific condition of the neonates affected the ethical performance of nurses in neonates' demographic variables (P-value =0.002).Conclusions: The finding showed that, overall, the performance of neonatal nurses regarding ethical codes is desirable

    Eamining and Comparing Data Mining-Based Techniques for Hepatitis Diagnosis

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    ABSTRACT: Increasing advances in information technology has led to significant growth in sciences. One of the fields in which significant changes has occurred is the medical field. Using data-mining techniques in this branch of science has helped physicians in all subjects, in particular diagnosis of sicknesses. Hepatitis diagnosis is highly difficult due to limited clinical diagnosis of the disease in its early stages. To this end, this paper tries to introduce and recommend the best way to diagnose hepatitis as well as to compare common clustering methods such as decision trees, neural networks, and SVM. Evaluation criteria of classification methods are the accuracy of each of methods and Clementine software along with data base in the University of California has been used to test each method. Obtained results show that neural network algorithm enjoys higher accuracy in comparison with other algorithms. Using neural network algorithm can accurately predict 89.74% hepatitis

    A case report of congenital myasthenic syndrome caused by a mutation in the CHRNE gene in the Iranian population

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    Congenital myasthenic syndrome (CMS) refers to a heterogeneous group of inherited disorders, characterized by defective transmission at the neuromuscular junction (NMJ). Patients with CMS showed similar muscle weakness, while other clinical manifestations are mostly dependent on genetic factors. This disease, caused by different DNA mutations, is genetically inherited. It is also associated with mutations of genes at NMJ, involving the acetylcholine receptor (AChR) subunits. Here, we present the case of a five-year-old Iranian boy with CMS, undergoing targeted sequencing of a panel of genes, associated with arthrogryposis and CMS. The patient had six affected relatives in his genetic pedigree chart. The investigations indicated a homozygous single base pair deletion at exon 12 of the CHRNE gene (chr17:4802186delC). This region was conserved across mammalian evolution and was not submitted to the 1000 Genomes Project database. Overall, the CHRNE variant may be classified as a significant variant in the etiology of CMS. It can be suggested that the Iranian CMS population carry regional pathogenic mutations, which can be detected via targeted and whole genome sequencing

    Association of rs4784227-CASC16 (LOC643714 locus) and rs4782447-ACSF3 polymorphisms and their association with breast cancer risk among Iranian population

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    TOX3 and FOXA1 proteins are believed to be involved in the susceptibility of breast cancer. rs4782447 and rs4784227, as single nucleotide polymorphisms (SNPs), located at the 16q may affect the FOXA1 DNA binding sequence change and therefore may enhance the FOXA1-binding affinity to the promoter of TOX3 gene. This study aimed to investigate the association of these SNPs/haplotypes with breast cancer susceptibility in Iranian population. We conducted a case-control study of 1072 blood samples (505 breast cancer patients and 567 controls). Genotyping of rs4784227 and rs4782447 SNPs was carried out by ARMS PCR. Moreover, statistical analysis was done by SPSS 20.0 (IBM Inc., Chicago, IL, USA) and SNP analyser 2.0. There was a strongly significant statistical association between alleles and genotypes of rs4784227 with breast cancer susceptibility in a group of Iranian women (p<0.05). Moreover, a significant association was demonstrated between TA haplotype and breast cancer risk (OR=0.78; 95% CI (0.62-0.96); P-value=0.025). In this respect, although we did not observe a statistically significant association between rs4782447 with breast cancer susceptibility, the combination of the alleles of rs4784227 and rs4782447 SNPs may also affect the risk. This is in line with other studies where they suggest these SNPs as risk-associated polymorphisms by which lead to disruption of as a distal enhancer, FOXA1, binding and following that change in TOX3 expression that can eventually affect the risk of breast cancer

    MicroRNAs as Biomarkers for Early Diagnosis, Prognosis, and Therapeutic Targeting of Ovarian Cancer

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    Ovarian cancer is the major cause of gynecologic cancer-related mortality. Regardless of outstanding advances, which have been made for improving the prognosis, diagnosis, and treatment of ovarian cancer, the majority of the patients will die of the disease. Late-stage diagnosis and the occurrence of recurrent cancer after treatment are the most important causes of the high mortality rate observed in ovarian cancer patients. Unraveling the molecular mechanisms involved in the pathogenesis of ovarian cancer may help find new biomarkers and therapeutic targets for ovarian cancer. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression, mostly at the posttranscriptional stage, through binding to mRNA targets and inducing translational repression or degradation of target via the RNA-induced silencing complex. Over the last two decades, the role of miRNAs in the pathogenesis of various human cancers, including ovarian cancer, has been documented in multiple studies. Consequently, these small RNAs could be considered as reliable markers for prognosis and early diagnosis. Furthermore, given the function of miRNAs in various cellular pathways, including cell survival and differentiation, targeting miRNAs could be an interesting approach for the treatment of human cancers. Here, we review our current understanding of the most updated role of the important dysregulation of miRNAs and their roles in the progression and metastasis of ovarian cancer. Furthermore, we meticulously discuss the significance of miRNAs as prognostic and diagnostic markers. Lastly, we mention the opportunities and the efforts made for targeting ovarian cancer through inhibition and/or stimulation of the miRNAs

    A characterization property of the simple group {\rm PSL}\sb 4(5) by the set of its element orders

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    summary:Let ω(G)\omega (G) denote the set of element orders of a finite group GG. If HH is a finite non-abelian simple group and ω(H)=ω(G)\omega (H)=\omega (G) implies GG contains a unique non-abelian composition factor isomorphic to HH, then GG is called quasirecognizable by the set of its element orders. In this paper we will prove that the group PSL4(5)PSL_{4}(5) is quasirecognizable

    Study of antibacterial effect of the extracts of the sea cucumber (Holothuria leucospilota) of Persian Gulf on the Escherichia coli

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    Background and Aim: Sea cucumber has different properties through having different biological compounds. In this study, the antibacterial activity of the extracts of the sea cucumber Holothuria leucospilota was investigated on Escherichia coli. Materials and Methods: Sea cucumber fishery samples after washing were crushed and powdered. The methanol, chloroform and hexane extracts of body wall, gonads and intestine were prepared. The antibacterial effect of the extracts was studied on the Escherichia coli at several concentrations. Also minimum inhibitory concentration and minimum bactericidal concentration of the extracts were studied against bacteria. Results: The results showed that methanol extracts had no effect, chloroform extracts showed antibacterial activity at concentrations of 5 and 10 mg per ml. Hexane extract of wall at concentrations of 5 and 10 and the intestine hexane extract at a concentration of 2.5, 5 and 10 mg per ml have antibacterial activity against bacteria. None of the concentrations of the gonadal hexane extract showed any antibacterial activity. Only the hexane extract of intestine killed the bacteria at a concentration of 10 mg /ml. Conclusions: According to the findings of this research, extracts of sea cucumber Holothuria leucospilota can be used in preparation of natural antimicrobial drugs as a valuable source of compounds with potential of antibacterial
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