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The present study examined the role of IQ and the Theory of Mind understanding in children with an autism spectrum disorder and down syndrome. Sixty-six Swedish children with ASD (n = 26), DS (n = 18), and typically developed group (n = 22) ranged between 6 and 12 years old were compared on ToM tasks consisted of standard ToM and IQ tasks. SPSS 25 program was used to analyze data. The results indicated that individuals with ASD reach a better understanding of first-order ToM tasks than children with DS. This picture was the same in the TD group to show better ability than children with ASD and DS on first-order tasks, except one task which was not found significant differences. To employ second-order TD performed better than clinical groups, while, there was no significant difference between ASD and DS. The scores for the third-order task in children with ASD were significantly better than children with DS.

The COVID-19 pandemic has imposed significant challenges on education worldwide, particularly in areas with limited online teaching experience. The research design is based on constructivism learning theory and the technology acceptance model. A questionnaire was also distributed to a university of finance and economics in China. Structural equation model was used to test the influence mechanism of social media interaction on college students' willingness to use e-learning platform continuously. The positive moderating effect of online teaching context on this mechanism is further analyzed. Therefore, the use of social media in the online teaching process in higher education institutions should be encouraged, and a good online teaching context should be fostered.

The present study examined the role of IQ and the Theory of Mind understanding in children with an autism spectrum disorder and down syndrome. Sixty-six Swedish children with ASD (n = 26), DS (n = 18), and typically developed group (n = 22) ranged between 6 and 12 years old were compared on ToM tasks consisted of standard ToM and IQ tasks. SPSS 25 program was used to analyze data. The results indicated that individuals with ASD reach a better understanding of first-order ToM tasks than children with DS. This picture was the same in the TD group to show better ability than children with ASD and DS on first-order tasks, except one task which was not found significant differences. To employ second-order TD performed better than clinical groups, while, there was no significant difference between ASD and DS. The scores for the third-order task in children with ASD were significantly better than children with DS., Author(s): Nazila Shojaeian [sup.1] , Zeyun Li [sup.2] , Rahul Pratap Singh Kaurav [sup.3] , Ashraf Atta M. S. Salem [sup.4] Author Affiliations: (1) grid.7080.f, 0000 0001 2296 0625, Department [...]

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer death globally. More accurate and reliable diagnostic methods/biomarkers are urgently needed. Joint application of metabolomics and transcriptomics technologies possesses the high efficiency of identifying key metabolic pathways and functional genes in lung cancer patients. In this study, we performed an untargeted metabolomics analysis of 142 NSCLC patients and 159 healthy controls; 35 identified metabolites were significantly different between NSCLC patients and healthy controls, of which 6 metabolites (hypoxanthine, inosine, L-tryptophan, indoleacrylic acid, acyl-carnitine C10:1, and lysoPC(18:2)) were chosen as combinational potential biomarkers for NSCLC. The area under the curve (AUC) value, sensitivity (SE), and specificity (SP) of these six biomarkers were 0.99, 0.98, and 0.99, respectively. Potential diagnostic implications of the metabolic characteristics in NSCLC was studied. The metabolomics results were further verified by transcriptomics analysis of 1027 NSCLC patients and 108 adjacent peritumoral tissues from TCGA database. This analysis identified 2202 genes with significantly different expressions in cancer cells compared to normal controls, which in turn defined pathways implicated in the metabolism of the compounds revealed by metabolomics analysis. We built a fully connected network of metabolites and genes, which shows a good correspondence between the transcriptome analysis and the metabolites selected for diagnosis. In conclusion, this work provides evidence that the metabolic biomarkers identified may be used for NSCLC diagnosis and screening. Comprehensive analysis of metabolomics and transcriptomics data offered a validated and comprehensive understanding of metabolism in NSCLC.

The manufacturing organizations are threatening the earth and its wildlife because of their growing concern about environmental pollution and industrial waste. Hence, in the present study, the three potential solutions, Green Intellectual Capital, Environmental Management Accounting and Energy Efficiency, are evaluated for excelling the organizational operations towards business sustainability and attaining the Competitive Advantage. With the assistance of 'Partial Least Square-Structural Equation Modelling' on the dataset of 364 respondents from the manufacturing organizations in China, the outcome reported the positive and significant impact of all of the studied potential solutions in excelling and enhancing business sustainability and competitive advantage. Based on the findings, it is proposed that manufacturing organizations need to apportion due attention to developing the green intellectual capital, improve the level of consumption of energy and need to disclose their environmental management through proper Environmental Management Accounting. [ABSTRACT FROM AUTHOR]