Materials and Methods: Simple and complex sounds were used (pure tones and the naturally produced Malay consonant-vowels [CVs]) to evoke the cortical auditory-evoked potential (CAEP) signals. Moreover, this study analyzed the influence of related CAEP components that are distinct to the selected population and determined which of the ERP components among (CAEP) components is most affected by the two distinct stimuli. Moreover, the study used classification algorithms to discover the ability of the brain in distinguishing CAEP evoked by stimuli contrasts.
Results: The results showed some resemblance between our results and ERP waveforms outlined in previous studies conducted on native speakers of English. On the other hand, it was also observed that the P1 and N2 had a significant effect in amplitude due to different stimulus.
Conclusion: The results show high classification accuracy for the brain to distinguish auditory stimuli. Moreover, the results indicated some resemblance to previous studies conducted on native English speakers using similar tones and English CV stimuli. However, the amplitudes and latencies of the P1 were found to have a significant difference due to stimuli complexity.
Methods: Databases such as PubMed, Science Direct, Google Scholar, Magiran, SID, IranDoc, and IranMedex were evaluated systematically using the terms "HHI," "psychometric," "validity," "reliability," and related terms (with the use of OR and AND operators) and no restrictions on the year of publication. A total of 13 eligible studies were found published between 1992 and 2018 in the USA, Portugal, Switzerland, Iran, Germany, Petersburg, Japan, the Netherlands, Lima, Peru, and Norway. The methodology used in the available studies included principal component analysis (n = 6), maximum likelihood estimation (n = 5), and principal axis factoring (n = 1). One study did not point the methodology.
Results: Four studies reported the total extracted variances to be less than 50%, six studies reported variance between 50% and 60%, and three papers reported variance that exceeded 60%. Of the papers that examined the factor structure of the HHI, two studies reported a one-factor solution, seven reported two factors, and four reported a three-factor solution. Although the HHI is the most widely translated and psychometrically tested tool in languages other than English, psychometric variations in factor solutions remain inconsistent.
Conclusion: Findings highlight the need for future research that appraises the validity of the HHI in different countries, and how the measure relates to other scales that evaluate hope.
Methods: Suspected Gram-negative bacteria with their identities from the clinical samples were confirmed using Microgen GN-A-ID Kit. The double-disc synergy test was used to confirm for ESBL-producing E. coli. The susceptibility of the organisms was tested against eleven antimicrobial agents. A singleplex PCR assay was carried out targeting TEM, SHV, CTX-M, and OXA. ERIC-PCR performed, and band patterns obtained were visually evaluated. A dendrogram of the ERIC-PCR fingerprint pattern was done with the aid of DendroUPGMA using the cluster method.
Results: Of the 576 clinical samples collected, 23 isolates were confirmed E. coli, and all (100%) are ESBL producers. The highest antibiotic resistance rate was recorded in cefixime (95.6%), and the least was amikacin (17.4%). The predominant ESBL gene is blaTEM genes (95.6%). Gel analysis of ERIC-PCR revealed 1-6 bands. The profiles of the ERIC-PCR differentiated the 23 E. coli isolates into four ERIC cluster types.
Conclusion: More than 80% of the isolates are sensitive to amikacin, with greater than 95% harboring blaTEM genes. Overall, ERIC obtained from the clinical specimens indicated some evidence in the genetic relatedness of the ESBL genes among E. coli isolates.