Objective Rapid on‐site evaluation (ROSE) is a technique beneficial in determining the adequacy of the samples, thereby increasing the diagnostic yield, useful in triage of specimens for ancillary studies and can also help determine a preliminary diagnosis in emergency cases. The different rapid stains for on‐site evaluation described in the literature are diff quik, toluidine blue (TB), brilliant cresyl blue (BCB), ultra‐fast Pap stains, and rapid hematoxylin and eosin (H&E). This study was undertaken as there is sparse literature regarding the best and the most cost‐effective rapid stain. Method Fine needle aspiration samples from 200 patients with palpable swellings in easily accessible regions were taken. Smears stained by rapid and routine stains were assessed based on four parameters, with provisional diagnosis on the rapid stained smears. A comparative analysis of the advantages and disadvantages of the rapid stains was carried out with appropriate statistical tests with the routinely stained smears as gold standard. Results There was adequate material in 100% of ROSE smears. rapid pap stained smears showed well preserved cytoplasmic details, nuclear details, and background details. The time taken was least with TB and BCB being 5 s each. The most cost‐effective was found to be TB. Conclusions We conclude that TB is the most cost‐effective, quick, least labor‐intensive, and reliable rapid stain for ROSE especially in resource‐poor settings.

Background: As the number of COVID-19 cases grows worldwide, one solution to the global pandemic is vaccination. Unfortunately, the hesitancy of receiving vaccines is still high, particularly among younger age groups (eg, students). Because the hesitancy of receiving vaccines is an important issue, instruments have been developed to assess vaccine hesitancy. Moreover, the use of these instruments among specific groups such as students is of critical importance. Aim: The present study examined the psychometric properties of the nine-item MoVac-COVID19S (also known as the DrVac-COVID19S) including its measurement invariance among university students in three different countries (ie, Taiwan, Indonesia, and Malaysia). Methods: A multi-country, web-based cross-sectional survey study was conducted among 1809 university students, recruited from the three countries from May to September 2021. The nine-item scale was translated into Traditional Chinese, Bahasa Indonesian, and Malay. Results:The results of the confirmatory factor analysis indicated that the one-factor structure of the MoVac-COVID19S was fully supported among Indonesian and Malay participants (comparative fit index [CFI] = 0.991 and 0.998; Tucker-Lewis index [TLI] = 0.997 and 0.987; root mean sqaure error of approximation [RMSEA] = 0.040 and 0.071; and standardized root mean square residual [SRMR] = 0.014 and 0.039). Moreover, the four-factor structure was supported among Indonesian, Malay, and Taiwanese participants (CFI = 0.998, 0.998, and 0.985; TLI = 0.997, 0.996, and 0.973; RMSEA = 0.044, 0.038, and 0.091; and SRMR = 0.013, 0.018, and 0.049). Conclusion:The MoVac-COVID19S has good construct validity among university students from three different countries (ie, Taiwan, Indonesia, and Malaysia). The four-factor structure of the MoVac-COVID19S was supported. Therefore, health-care providers may want to assess the four underlying constructs to better understand why a university student accepts or declines COVID-19 vaccine uptake in the three countries. Using the findings, government policymakers and health-care authorities can design appropriate programs to help decrease vaccine hesitancy.

The study aims to examine the influence of human resource management (HRM) practices and proactive personality on job performance. HRM practices comprised of compensation and benefits, training and development, and performance appraisal and achievement. Employees who participated in the study are employees of commercial banks located in Klang Valley. The results reported that compensation and benefits and proactive personality have a significant and positive influence on job performance. Discussions delineated on the predicting role of compensation and benefits and proactive personality in boosting job performance among employees in the study. Theoretical implications in terms of Social Exchange Theory and Self-Determination Theory are highlighted while practical implications are also brought to fore. Finally, limitations, directions for future research, and conclusion are also presented.

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Wearable speech enhancement can improve the recognition accuracy of the speech signals in stationary noise environments at 0dB to 60dB signal to noise ratio. Beamforming, adaptive noise reduction, and voice activity detection algorithms are used in wearable speech enhancement systems to enhance speech signals. In recent works, a word rate recognition accuracy of 63% for a 0db signal-to-noise ratio is not satisfactory for a robust speech recognition system. This paper discusses the experimental study using fixed beamforming, adaptive noise reduction, and voice activity detection algorithms with the inclusion of −10dB to 20dB signal to noise ratio for different types of noises to test the wearable speech enhancement system's performance in noisy environments. It also compares deep learning-based noise reduction methods as a benchmark for speech enhancement and word recognition for different noise levels. We have obtained an average word rate recognition accuracy of 5.74% at −10dB and 93.79% at 20dB for non-stationary noisy environments. The outcome of the experiments shows that the selected methods perform significantly better in the environment with high noise dB for both stationary and non-stationary noise. We found that there is no significant statistical difference between the stationary and non-stationary noise word recognition and SNRs level. However, the deep learning-based method performs significantly better than the fixed beamforming, adaptive noise reduction, and voice activity detection algorithms in all noisy levels.